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b059b880de3f859a5969b06be9518974df6aa833 | f6d08b29b76713165fcdb50f78bd9c74b6b38c22 | /Collect/S30/DataAccess.py | b4ea6f8e898d457761a400b8cb3c13d44347eeb3 | [
"Apache-2.0"
] | permissive | joan-gathu/watertools | b4b22071897e21d2fb306344f9ace42511e9f3ef | 55e383942ed3ddb3ba1d26596badc69922199300 | refs/heads/master | 2022-04-11T17:49:06.324478 | 2020-03-13T11:11:16 | 2020-03-13T11:11:16 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,459 | py | # -*- coding: utf-8 -*-
"""
WaterSat
author: Tim Martijn Hessels
Created on Sun Feb 10 18:26:30 2019
"""
import datetime
import pandas as pd
import numpy as np
import os
import urllib
import gdal
#S2_tile = "10SGE"
#output_folder = "F:\Project_Jain\Case_California\Input_Data\S30"
#Startdate = "2018-03-01"
#Enddate = "2018-10-31"
def DownloadData(Dir, Startdate, Enddate, S2_tile):
# Import watertools modules
import watertools.General.data_conversions as DC
# Define the dates
Dates = pd.date_range(Startdate, Enddate, freq = "D")
# Create output folder
output_folder_end = os.path.join(Dir, S2_tile)
if not os.path.exists(output_folder_end):
os.makedirs(output_folder_end)
# Loop over the days
for Date in Dates:
# Get the datum
doy = int(Date.dayofyear)
year = Date.year
try:
# Create the right url
url = "https://hls.gsfc.nasa.gov/data/v1.4/S30/%s/%s/%s/%s/%s/HLS.S30.T%s.%s%03d.v1.4.hdf" % (year, S2_tile[0:2], S2_tile[2:3], S2_tile[3:4], S2_tile[4:5],S2_tile, year, doy)
filename_out = os.path.join(output_folder_end, "HLS.S30.T%s.%s%03d.v1.4.hdf" % (S2_tile, year, doy))
# Download the data
urllib.request.urlretrieve(url, filename=filename_out)
# Create a folder for the end results
folder_tile = os.path.join(output_folder_end, "HLS_S30_T%s_%s%03d_v1_4" % (S2_tile, year, doy))
if not os.path.exists(folder_tile):
os.makedirs(folder_tile)
# Write the hdf file in tiff files and store it in the folder
dataset = gdal.Open(filename_out)
sdsdict = dataset.GetMetadata('SUBDATASETS')
for Band in range(1,15):
dest = gdal.Open(sdsdict["SUBDATASET_%d_NAME" %Band])
Array = dest.GetRasterBand(1).ReadAsArray()
if Band < 9.:
Array = Array * 0.0001
Array[Array == -0.1] = -9999.
Band_name = "B%02d" %(Band)
if Band == 9.:
Band_name = "B8A"
Array = Array * 0.0001
Array[Array == -0.1] = -9999.
if (Band >= 10. and Band < 14.):
Band_name = "B%02d" %(Band - 1)
Array = Array * 0.0001
Array[Array == -0.1] = -9999.
if Band == 14.:
Array[Array == 255] = -9999.
Band_name = "QC"
meta = dataset.GetMetadata()
ulx = int(meta["ULX"])
uly = int(meta["ULY"])
size = int(meta["SPATIAL_RESOLUTION"])
projection = int(meta["HORIZONTAL_CS_CODE"].split(":")[-1])
time_string = meta["SENSING_TIME"].split(";")[0]
Time = datetime.datetime.strptime(time_string[:-5],"%Y-%m-%dT%H:%M:%S")
hour = int(Time.hour)
minute = int(Time.minute)
geo = tuple([ulx, size, 0, uly, 0, -size])
DC.Save_as_tiff(os.path.join(folder_tile, "HLS_S30_T%s_%s%03d_H%02dM%02d_%s.tif" % (S2_tile, year, doy, hour, minute, Band_name)), Array, geo, projection)
except:
pass
return() | [
"[email protected]"
] | |
6ce225b27e57b222c5803bee8ef647f9c9f5b6e1 | aaa762ce46fa0347cdff67464f56678ea932066d | /AppServer/lib/django-1.3/tests/regressiontests/test_client_regress/views.py | c40f34fe563a797d6d3a7c364eeb614697b044db | [
"Apache-2.0",
"BSD-3-Clause",
"LGPL-2.1-or-later",
"MIT",
"GPL-2.0-or-later",
"MPL-1.1"
] | permissive | obino/appscale | 3c8a9d8b45a6c889f7f44ef307a627c9a79794f8 | be17e5f658d7b42b5aa7eeb7a5ddd4962f3ea82f | refs/heads/master | 2022-10-01T05:23:00.836840 | 2019-10-15T18:19:38 | 2019-10-15T18:19:38 | 16,622,826 | 1 | 0 | Apache-2.0 | 2022-09-23T22:56:17 | 2014-02-07T18:04:12 | Python | UTF-8 | Python | false | false | 4,115 | py | from django.conf import settings
from django.contrib.auth.decorators import login_required
from django.http import HttpResponse, HttpResponseRedirect
from django.core.exceptions import SuspiciousOperation
from django.shortcuts import render_to_response
from django.utils import simplejson
from django.utils.encoding import smart_str
from django.core.serializers.json import DjangoJSONEncoder
from django.test.client import CONTENT_TYPE_RE
from django.template import RequestContext
def no_template_view(request):
"A simple view that expects a GET request, and returns a rendered template"
return HttpResponse("No template used. Sample content: twice once twice. Content ends.")
def staff_only_view(request):
"A view that can only be visited by staff. Non staff members get an exception"
if request.user.is_staff:
return HttpResponse('')
else:
raise SuspiciousOperation()
def get_view(request):
"A simple login protected view"
return HttpResponse("Hello world")
get_view = login_required(get_view)
def request_data(request, template='base.html', data='sausage'):
"A simple view that returns the request data in the context"
return render_to_response(template, {
'get-foo':request.GET.get('foo',None),
'get-bar':request.GET.get('bar',None),
'post-foo':request.POST.get('foo',None),
'post-bar':request.POST.get('bar',None),
'request-foo':request.REQUEST.get('foo',None),
'request-bar':request.REQUEST.get('bar',None),
'data': data,
})
def view_with_argument(request, name):
"""A view that takes a string argument
The purpose of this view is to check that if a space is provided in
the argument, the test framework unescapes the %20 before passing
the value to the view.
"""
if name == 'Arthur Dent':
return HttpResponse('Hi, Arthur')
else:
return HttpResponse('Howdy, %s' % name)
def login_protected_redirect_view(request):
"A view that redirects all requests to the GET view"
return HttpResponseRedirect('/test_client_regress/get_view/')
login_protected_redirect_view = login_required(login_protected_redirect_view)
def set_session_view(request):
"A view that sets a session variable"
request.session['session_var'] = 'YES'
return HttpResponse('set_session')
def check_session_view(request):
"A view that reads a session variable"
return HttpResponse(request.session.get('session_var', 'NO'))
def request_methods_view(request):
"A view that responds with the request method"
return HttpResponse('request method: %s' % request.method)
def return_unicode(request):
return render_to_response('unicode.html')
def return_json_file(request):
"A view that parses and returns a JSON string as a file."
match = CONTENT_TYPE_RE.match(request.META['CONTENT_TYPE'])
if match:
charset = match.group(1)
else:
charset = settings.DEFAULT_CHARSET
# This just checks that the uploaded data is JSON
obj_dict = simplejson.loads(request.raw_post_data.decode(charset))
obj_json = simplejson.dumps(obj_dict, encoding=charset,
cls=DjangoJSONEncoder,
ensure_ascii=False)
response = HttpResponse(smart_str(obj_json, encoding=charset), status=200,
mimetype='application/json; charset=' + charset)
response['Content-Disposition'] = 'attachment; filename=testfile.json'
return response
def check_headers(request):
"A view that responds with value of the X-ARG-CHECK header"
return HttpResponse('HTTP_X_ARG_CHECK: %s' % request.META.get('HTTP_X_ARG_CHECK', 'Undefined'))
def raw_post_data(request):
"A view that is requested with GET and accesses request.raw_post_data. Refs #14753."
return HttpResponse(request.raw_post_data)
def request_context_view(request):
# Special attribute that won't be present on a plain HttpRequest
request.special_path = request.path
return render_to_response('request_context.html', context_instance=RequestContext(request, {}))
| [
"[email protected]"
] | |
37b87d12218bc68211a3ef73adb34d6e5eb43721 | e3365bc8fa7da2753c248c2b8a5c5e16aef84d9f | /indices/nnhog.py | 7c1879ae52723fe68f6909d57aba4d78d84117a7 | [] | no_license | psdh/WhatsintheVector | e8aabacc054a88b4cb25303548980af9a10c12a8 | a24168d068d9c69dc7a0fd13f606c080ae82e2a6 | refs/heads/master | 2021-01-25T10:34:22.651619 | 2015-09-23T11:54:06 | 2015-09-23T11:54:06 | 42,749,205 | 2 | 3 | null | 2015-09-23T11:54:07 | 2015-09-18T22:06:38 | Python | UTF-8 | Python | false | false | 1,016 | py | ii = [('CookGHP3.py', 1), ('LyelCPG2.py', 6), ('RogePAV2.py', 5), ('CoolWHM2.py', 4), ('RogePAV.py', 6), ('SadlMLP.py', 2), ('WilbRLW.py', 1), ('ProuWCM.py', 4), ('MartHSI2.py', 1), ('LeakWTI2.py', 1), ('LeakWTI3.py', 4), ('PeckJNG.py', 11), ('AubePRP.py', 1), ('FitzRNS3.py', 2), ('SeniNSP.py', 1), ('AinsWRR3.py', 2), ('KiddJAE.py', 1), ('BailJD1.py', 1), ('RoscTTI2.py', 1), ('CoolWHM.py', 3), ('CrokTPS.py', 3), ('BuckWGM.py', 6), ('LyelCPG.py', 1), ('GilmCRS.py', 3), ('CrocDNL.py', 15), ('MedwTAI.py', 7), ('GodwWLN.py', 6), ('KirbWPW2.py', 3), ('LeakWTI4.py', 5), ('LeakWTI.py', 3), ('MedwTAI2.py', 1), ('BuckWGM2.py', 1), ('WheeJPT.py', 1), ('HowiWRL2.py', 2), ('HogaGMM.py', 1), ('MartHRW.py', 1), ('MackCNH.py', 2), ('WestJIT.py', 1), ('FitzRNS4.py', 5), ('CoolWHM3.py', 5), ('LewiMJW.py', 4), ('BellCHM.py', 1), ('JacoWHI.py', 2), ('MartHRW2.py', 2), ('FitzRNS2.py', 11), ('MartHSI.py', 2), ('EvarJSP.py', 6), ('LyelCPG3.py', 1), ('KeigTSS.py', 1), ('WaylFEP.py', 1), ('BentJDO.py', 3), ('ClarGE4.py', 1)] | [
"[email protected]"
] | |
81245d58715ad29d167143f1b4294119e1df2941 | 5a5bcfe21defcaf6b050b0c92e8ec03cee7eb50f | /gencrud/gen/page/forms/__init__.py | 7d15d4a929cddb986ec8904a4487e97f10a941fc | [] | no_license | marychev/gencrud | dc146c570a81ed0665f6bec309f106d966be349a | d6dc478b9a079aba5589591fa2e79665179e28a2 | refs/heads/master | 2023-01-06T18:50:13.417451 | 2020-10-23T18:05:38 | 2020-10-23T18:05:38 | 262,617,213 | 2 | 0 | null | 2020-05-10T18:35:19 | 2020-05-09T16:55:28 | Python | UTF-8 | Python | false | false | 38 | py | from .page_comment import CommentForm
| [
"[email protected]"
] | |
5f0505f36af2d39f955a7c0c374ddee7f52a9465 | 024ad288e3e8c4407c147d3e5a3cef9c97ddecce | /keras/keras98_randomsearch.py | 3188609d3745a71add73ce93d8b27576dc61a945 | [] | no_license | keumdohoon/STUDY | a17f62549e5dc59640875970b79b41ba8f62932c | 83a1369d8e93767ebc445a443d8f55921cd984ce | refs/heads/master | 2022-12-15T17:25:00.809774 | 2020-09-07T02:00:30 | 2020-09-07T02:00:30 | 264,050,749 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,264 | py | #원래는 randomizedSearchCV로 변환, 파일 keras97불러오기.
#score 을 추가해준다.
from keras.datasets import mnist
from keras.utils import np_utils
from keras.models import Sequential, Model
from keras.layers import Input, Dropout, Conv2D, Flatten, Dense
from keras.layers import MaxPooling2D
import numpy as np
#. 1. 데이터
(x_train, y_train), (x_test, y_test) = mnist.load_data()
#데이터를 불러옴과 동시에 x, y와 트레인과 테스트를 분리해준다.
print(x_train.shape)#(60000, 28, 28)
print(x_test.shape)#(10000, 28, 28)
# x_train = x_train.reshape(x_train[0], 28,28,1)/255
# x_test = x_test.reshape(x_test[0], 28,28,1)/255
#0부터 255개의 데이터가 들어가있는데 이것은 결국 민맥스와 같은 결과를 가져다 준다.
x_train = x_train.reshape(x_train.shape[0], 28 * 28)/255
x_test = x_test.reshape(x_test.shape[0], 28 * 28)/255
#위에거는 dense모델을 위해서 만들어 준 것이다.
y_train = np_utils.to_categorical(y_train)
y_test = np_utils.to_categorical(y_test)
#캐라스에서 하는거는 라벨의 시작이 0부터이니 원핫 인코딩을 할때에는 y의 차원을 반드시확인하고 들어가야한다.
#
print(y_train.shape)
#########################################################################################################
# model = GridSearchCV(modelthat we will use, Parameters that we will use, cv=kfold= u can just input a number)
###################################################################################################
#위에 모델을 만들어주기 위해서 모델, 파라미터, cv를 각각 만들어준다.
#2. 모델
#gridsearch 에 있는 parameter으의 순서를 보면
def build_model(drop=0.5, optimizer= 'adam'):
inputs = Input(shape=(28*28, ), name = 'input')
x = Dense(512, activation = 'relu', name= 'hidden1')(inputs)
x= Dropout(drop)(x)
x = Dense(256, activation = 'relu', name= 'hidden2')(x)
x= Dropout(drop)(x)
x = Dense(128, activation = 'relu', name= 'hidden3')(x)
x= Dropout(drop)(x)
output = Dense(10, activation = 'softmax', name= 'outputs')(x)
model = Model(inputs =inputs, outputs = output)
model.compile (optimizer, metrics =["acc"], loss = 'categorical_crossentropy')
return model
#이렇게 직접 함수형을 만들어 줄 수도 있는 것이다.
#그리드 서치를 사용하려면 맨처음에 들어가는 것이 모델이기 때문에 우리가 이미 모델을 만들어주고 그걸 사용하기 위해서 직접 모델을 만들어준다.
#컴파일까지만 만들어주고 핏은 아직 안만들어준다 왜냐하면 핏은 나중에 랜덤서치나 그리드 서치에서 할것이기 때문이다.
#모델을 만들었고 이제 두번째 파라미터를 만들어준다.
def create_hyperparameters():
batches =[10, 20, 30, 40, 50]
optimizers = ['rmsprop', 'adam', 'adadelta']
dropout = np.linspace(0.1,0.5, 5)
return{"batch_size" : batches, "optimizer" : optimizers,
"drop" :linspace}
#위에 딕셔너리형태이다. 파라미터에 들어가는 매개변수 형테는 딕셔너리 형태이다. 그래서 무조건 딕셔너리 형태로 맞춰줘야한다. 케라스가 아니라 싸이킷런에 맞는 모델로 래핑을 만들어주기 위해서 이런식으로 해준다.
#k fold에서는 숫자만 들어가면 되는것이니 그것도 이미 준비 된것이다.
#여기다가 에포도 넣을수 있고 노드의 갯수도 변수명을 넣어주고 하이퍼 파라미터에 넣을수 있고 activation도 넣어 줄 수 있다. 여기서 원하는건 다 넣을수 있음.
#케라스를 그냥 사용하면 안되고 케라스에 보면 사이킷런에 사용할수 있는 wrapper이라는 것이 존재하고 사이킷런에 케라스를 쌓아 올리겠다는는 뜻이다.
from keras.wrappers.scikit_learn import KerasClassifier
#케라스건 사이킷런이건 분류와 회기를 항상 잃지 말고
#케라스에서 wrapping을 해주는 이유는 사이킷런에서 해주기 위해서
model= KerasClassifier(build_fn= build_model, verbose= 1)
#우리가 만들어둔 모델을 wrapping 해 주는 것이다. kerasClassifier 모델을 이렇게 만들어주는 것이다.
hyperparameters = create_hyperparameters()
#help buiild a hyper parameters , 위데짜놓은 create_hyperparameters()를 hyperparamer 에 대입시켜준다.
#여기서 부터가 모델 핏 부분이 되는 것이다.
from sklearn.model_selection import GridSearchCV, RandomizedSearchCV
search = RandomizedSearchCV(model, hyperparameters, cv = 3 , n_jobs =-1)
search.fit(x_train, y_train)
print(search.best_params_)
#이 폴더에서 항상 주의해야할것들은 소스와 하이퍼 파라미터
# acc: 0.9311
# {'optimizer': 'rmsprop', 'drop': 0.1, 'batch_size': 50}
#score
#score 을 추가하여 작성
acc = search.score(x_test, y_test, verbose=0)
print(search.best_params_)
print("acc :", acc)
# acc: 0.9143
# {'optimizer': 'adadelta', 'drop': 0.30000000000000004, 'batch_size': 20}
# Traceback (most recent call last):
# File "d:\Study\Bitcamp\keras\keras98_randomsearch.py", line 105, in <module>
# print("최적의 매개변수 :", model.best_params_) | [
"[email protected]"
] | |
ea0437398c5d2f0e423bd627eaa886ffd929f096 | 64bf39b96a014b5d3f69b3311430185c64a7ff0e | /intro-ansible/venv2/lib/python3.8/site-packages/ansible/modules/database/postgresql/postgresql_ext.py | 97bd549f21b13edb26860e7beac097a8cf22f526 | [
"MIT"
] | permissive | SimonFangCisco/dne-dna-code | 7072eba7da0389e37507b7a2aa5f7d0c0735a220 | 2ea7d4f00212f502bc684ac257371ada73da1ca9 | refs/heads/master | 2023-03-10T23:10:31.392558 | 2021-02-25T15:04:36 | 2021-02-25T15:04:36 | 342,274,373 | 0 | 0 | MIT | 2021-02-25T14:39:22 | 2021-02-25T14:39:22 | null | UTF-8 | Python | false | false | 5,700 | py | #!/usr/bin/python
# -*- coding: utf-8 -*-
# Copyright: Ansible Project
# GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
from __future__ import absolute_import, division, print_function
__metaclass__ = type
ANSIBLE_METADATA = {'metadata_version': '1.1',
'status': ['preview'],
'supported_by': 'community'}
DOCUMENTATION = '''
---
module: postgresql_ext
short_description: Add or remove PostgreSQL extensions from a database.
description:
- Add or remove PostgreSQL extensions from a database.
version_added: "1.9"
options:
name:
description:
- name of the extension to add or remove
required: true
default: null
db:
description:
- name of the database to add or remove the extension to/from
required: true
default: null
login_user:
description:
- The username used to authenticate with
required: false
default: null
login_password:
description:
- The password used to authenticate with
required: false
default: null
login_host:
description:
- Host running the database
required: false
default: localhost
port:
description:
- Database port to connect to.
required: false
default: 5432
state:
description:
- The database extension state
required: false
default: present
choices: [ "present", "absent" ]
notes:
- The default authentication assumes that you are either logging in as or sudo'ing to the C(postgres) account on the host.
- This module uses I(psycopg2), a Python PostgreSQL database adapter. You must ensure that psycopg2 is installed on
the host before using this module. If the remote host is the PostgreSQL server (which is the default case), then PostgreSQL must also be installed
on the remote host. For Ubuntu-based systems, install the C(postgresql), C(libpq-dev), and C(python-psycopg2) packages on the remote host before using
this module.
requirements: [ psycopg2 ]
author: "Daniel Schep (@dschep)"
'''
EXAMPLES = '''
# Adds postgis to the database "acme"
- postgresql_ext:
name: postgis
db: acme
'''
import traceback
try:
import psycopg2
import psycopg2.extras
except ImportError:
postgresqldb_found = False
else:
postgresqldb_found = True
from ansible.module_utils.basic import AnsibleModule
from ansible.module_utils._text import to_native
class NotSupportedError(Exception):
pass
# ===========================================
# PostgreSQL module specific support methods.
#
def ext_exists(cursor, ext):
query = "SELECT * FROM pg_extension WHERE extname=%(ext)s"
cursor.execute(query, {'ext': ext})
return cursor.rowcount == 1
def ext_delete(cursor, ext):
if ext_exists(cursor, ext):
query = "DROP EXTENSION \"%s\"" % ext
cursor.execute(query)
return True
else:
return False
def ext_create(cursor, ext):
if not ext_exists(cursor, ext):
query = 'CREATE EXTENSION "%s"' % ext
cursor.execute(query)
return True
else:
return False
# ===========================================
# Module execution.
#
def main():
module = AnsibleModule(
argument_spec=dict(
login_user=dict(default="postgres"),
login_password=dict(default="", no_log=True),
login_host=dict(default=""),
port=dict(default="5432"),
db=dict(required=True),
ext=dict(required=True, aliases=['name']),
state=dict(default="present", choices=["absent", "present"]),
),
supports_check_mode=True
)
if not postgresqldb_found:
module.fail_json(msg="the python psycopg2 module is required")
db = module.params["db"]
ext = module.params["ext"]
state = module.params["state"]
changed = False
# To use defaults values, keyword arguments must be absent, so
# check which values are empty and don't include in the **kw
# dictionary
params_map = {
"login_host": "host",
"login_user": "user",
"login_password": "password",
"port": "port"
}
kw = dict((params_map[k], v) for (k, v) in module.params.items()
if k in params_map and v != '')
try:
db_connection = psycopg2.connect(database=db, **kw)
# Enable autocommit so we can create databases
if psycopg2.__version__ >= '2.4.2':
db_connection.autocommit = True
else:
db_connection.set_isolation_level(psycopg2
.extensions
.ISOLATION_LEVEL_AUTOCOMMIT)
cursor = db_connection.cursor(
cursor_factory=psycopg2.extras.DictCursor)
except Exception as e:
module.fail_json(msg="unable to connect to database: %s" % to_native(e), exception=traceback.format_exc())
try:
if module.check_mode:
if state == "present":
changed = not ext_exists(cursor, ext)
elif state == "absent":
changed = ext_exists(cursor, ext)
else:
if state == "absent":
changed = ext_delete(cursor, ext)
elif state == "present":
changed = ext_create(cursor, ext)
except NotSupportedError as e:
module.fail_json(msg=to_native(e), exception=traceback.format_exc())
except Exception as e:
module.fail_json(msg="Database query failed: %s" % to_native(e), exception=traceback.format_exc())
module.exit_json(changed=changed, db=db, ext=ext)
if __name__ == '__main__':
main()
| [
"[email protected]"
] | |
1657f962a8133600e36bf5a5651983e5160d9d34 | 9f2f386a692a6ddeb7670812d1395a0b0009dad9 | /python/paddle/fluid/tests/unittests/dygraph_group_sharded_stage3_offload.py | 5f9ec5c6e708e37b208ed07a321428f056f83a77 | [
"Apache-2.0"
] | permissive | sandyhouse/Paddle | 2f866bf1993a036564986e5140e69e77674b8ff5 | 86e0b07fe7ee6442ccda0aa234bd690a3be2cffa | refs/heads/develop | 2023-08-16T22:59:28.165742 | 2022-06-03T05:23:39 | 2022-06-03T05:23:39 | 181,423,712 | 0 | 7 | Apache-2.0 | 2022-08-15T08:46:04 | 2019-04-15T06:15:22 | C++ | UTF-8 | Python | false | false | 6,441 | py | # -*- coding: UTF-8 -*-
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import numpy as np
import argparse
import ast
import time
import paddle
import paddle.fluid as fluid
from paddle.fluid.dygraph.nn import Linear
from paddle.distributed import fleet
from paddle.fluid.dygraph import nn
from paddle.fluid.framework import _test_eager_guard
from paddle.distributed.fleet.meta_parallel.sharding.group_sharded_stage3 import GroupShardedStage3
from paddle.distributed.fleet.meta_parallel.sharding.group_sharded_utils import GroupShardedScaler
epoch = 10
paddle.seed(2022)
np.random.seed(2022)
base_lr = 0.1
momentum_rate = 0.9
l2_decay = 1e-4
class MLP(fluid.Layer):
def __init__(self, linear_size=1000, param_attr=None, bias_attr=None):
super(MLP, self).__init__()
self._linear1 = Linear(linear_size, linear_size)
self._linear2 = Linear(linear_size, linear_size)
self._linear3 = Linear(linear_size, 10)
def forward(self, inputs):
y = self._linear1(inputs)
y = self._linear2(y)
y = self._linear3(y)
return y
def reader_decorator(linear_size=1000):
def __reader__():
for _ in range(100):
img = np.random.rand(linear_size).astype('float32')
label = np.ones(1).astype('int64')
yield img, label
return __reader__
def optimizer_setting(model, use_pure_fp16, opt_group=False):
clip = paddle.nn.ClipGradByGlobalNorm(clip_norm=1.0)
optimizer = paddle.optimizer.AdamW(
parameters=[{
"params": model.parameters()
}] if opt_group else model.parameters(),
learning_rate=0.001,
weight_decay=0.00001,
grad_clip=clip,
multi_precision=use_pure_fp16)
return optimizer
def train_mlp(model,
use_pure_fp16=False,
accumulate_grad=False,
offload=False,
batch_size=100,
convert2cpu=False):
group = paddle.distributed.new_group([0, 1])
optimizer = optimizer_setting(model=model, use_pure_fp16=use_pure_fp16)
if use_pure_fp16:
model = paddle.amp.decorate(
models=model, level='O2', save_dtype='float32')
scaler = paddle.amp.GradScaler(init_loss_scaling=32768)
scaler = GroupShardedScaler(scaler)
model = GroupShardedStage3(
model,
optimizer=optimizer,
group=group,
offload=offload,
segment_size=2**15)
train_reader = paddle.batch(
reader_decorator(), batch_size=batch_size, drop_last=True)
train_loader = paddle.io.DataLoader.from_generator(
capacity=32,
use_double_buffer=True,
iterable=True,
return_list=True,
use_multiprocess=True)
train_loader.set_sample_list_generator(train_reader)
for eop in range(epoch):
model.train()
for batch_id, data in enumerate(train_loader()):
img, label = data
label.stop_gradient = True
img.stop_gradient = True
with paddle.amp.auto_cast(True, level='O2'):
out = model(img)
loss = paddle.nn.functional.cross_entropy(
input=out, label=label)
avg_loss = paddle.mean(x=loss.cast(dtype=paddle.float32))
if accumulate_grad:
avg_loss = avg_loss / 5
if not use_pure_fp16:
avg_loss.backward()
else:
scaler.scale(avg_loss).backward()
if not accumulate_grad:
if not use_pure_fp16:
optimizer.step()
else:
scaler.step(optimizer)
scaler.update()
optimizer.clear_grad()
if accumulate_grad:
if not use_pure_fp16:
optimizer.step()
else:
scaler.step(optimizer)
scaler.update()
optimizer.clear_grad()
if not convert2cpu:
model.get_all_parameters()
else:
model.get_all_parameters(convert2cpu)
return model.parameters()
def test_stage3_offload():
paddle.distributed.init_parallel_env()
mlp, mlp1, mlp2, mlp3, mlp4, mlp5, mlp6 = MLP(), MLP(), MLP(), MLP(), MLP(
), MLP(), MLP()
state_dict = mlp.state_dict()
mlp1.set_state_dict(state_dict)
mlp2.set_state_dict(state_dict)
mlp3.set_state_dict(state_dict)
mlp4.set_state_dict(state_dict)
mlp5.set_state_dict(state_dict)
mlp6.set_state_dict(state_dict)
# fp32 offload
stage3_params = train_mlp(mlp1, use_pure_fp16=False)
stage3_params_offload = train_mlp(mlp2, use_pure_fp16=False, offload=True)
for i in range(len(stage3_params)):
np.testing.assert_allclose(
stage3_params[i].numpy(),
stage3_params_offload[i].numpy(),
rtol=1e-6,
atol=1e-8)
# fp16 offload
stage3_params = train_mlp(mlp3, use_pure_fp16=True)
stage3_params_offload = train_mlp(mlp4, use_pure_fp16=True, offload=True)
for i in range(len(stage3_params)):
np.testing.assert_allclose(
stage3_params[i].numpy(),
stage3_params_offload[i].numpy(),
rtol=1e-2,
atol=1e-2)
# fp32 accumulate grad offload
stage3_params = train_mlp(
mlp5, use_pure_fp16=False, batch_size=20, accumulate_grad=True)
stage3_params_offload = train_mlp(
mlp6,
use_pure_fp16=False,
accumulate_grad=True,
offload=True,
batch_size=20,
convert2cpu=True)
for i in range(len(stage3_params)):
np.testing.assert_allclose(
stage3_params[i].numpy(),
stage3_params_offload[i].numpy(),
rtol=1e-6,
atol=1e-8)
return
if __name__ == '__main__':
with _test_eager_guard():
test_stage3_offload()
| [
"[email protected]"
] | |
22c8c50b7859ffd0b128c08f3f64b0fcca6754d2 | 55ab64b67d8abc02907eb43a54ff6c326ded6b72 | /scripts/addon_library/local/uvpackmaster3/scripted_pipeline/panels/grouping_panels.py | 6e772957a8c34014a5e61cf1284f7cdbd0d6afda | [
"MIT"
] | permissive | Tilapiatsu/blender-custom_config | 2f03b0bb234c3b098d2830732296d199c91147d0 | 00e14fc190ebff66cf50ff911f25cf5ad3529f8f | refs/heads/master | 2023-08-16T14:26:39.990840 | 2023-08-16T01:32:41 | 2023-08-16T01:32:41 | 161,249,779 | 6 | 2 | MIT | 2023-04-12T05:33:59 | 2018-12-10T23:25:14 | Python | UTF-8 | Python | false | false | 9,945 | py | # ##### BEGIN GPL LICENSE BLOCK #####
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software Foundation,
# Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
#
# ##### END GPL LICENSE BLOCK #####
from ...utils import get_prefs, in_debug_mode
from ...panel import UVPM3_PT_Registerable, GroupingSchemeAccess
from ...labels import Labels
from ...enums import GroupLayoutMode, TexelDensityGroupPolicy
from ...operator_islands import UVPM3_OT_SetManualGroupIParam, UVPM3_OT_SelectManualGroupIParam, UVPM3_OT_ShowManualGroupIParam, UVPM3_OT_ApplyGroupingToScheme
from ...presets_grouping_scheme import UVPM3_PT_PresetsGroupingScheme
from ...grouping_scheme import\
(UVPM3_OT_NewGroupingScheme,
UVPM3_OT_RemoveGroupingScheme,
UVPM3_OT_NewGroupInfo,
UVPM3_OT_RemoveGroupInfo,
UVPM3_OT_NewTargetBox,
UVPM3_OT_RemoveTargetBox,
UVPM3_OT_MoveGroupInfo,
UVPM3_OT_MoveTargetBox)
from ...grouping_scheme_ui import UVPM3_MT_BrowseGroupingSchemes, UVPM3_UL_GroupInfo, UVPM3_UL_TargetBoxes
from ...box_ui import GroupingSchemeBoxesEditUI
class UVPM3_PT_GroupingBase(UVPM3_PT_Registerable, GroupingSchemeAccess):
@classmethod
def poll(cls, context):
prefs = get_prefs()
scene_props = context.scene.uvpm3_props
return prefs.get_mode(scene_props.active_main_mode_id, context).grouping_enabled()
def should_draw_grouping_options(self):
return hasattr(self.active_mode, 'draw_grouping_options')
def draw_grouping_options(self, g_options, layout, g_scheme=None):
self.active_mode.draw_grouping_options(g_scheme, g_options, layout)
def draw_impl(self, context):
self.init_access(context, ui_drawing=True)
self.draw_impl2(context)
class UVPM3_PT_Grouping(UVPM3_PT_GroupingBase):
bl_idname = 'UVPM3_PT_Grouping'
bl_label = 'Island Grouping'
# bl_options = {'DEFAULT_CLOSED'}
PANEL_PRIORITY = 800
APPLY_GROUPING_TO_SCHEME_HELP_URL_SUFFIX = '30-packing-modes/30-groups-to-tiles/#apply-automatic-grouping-to-a-grouping-scheme'
def draw_grouping_schemes_presets(self, context, layout):
layout.emboss = 'NONE'
layout.popover(panel=UVPM3_PT_PresetsGroupingScheme.__name__, icon='PRESET', text="")
def draw_grouping_schemes(self, context, layout):
main_col = layout.column(align=True)
main_col.label(text='Select a grouping scheme:')
row = main_col.row(align=True)
row.menu(UVPM3_MT_BrowseGroupingSchemes.bl_idname, text="", icon='GROUP_UVS')
if self.active_g_scheme is not None:
row.prop(self.active_g_scheme, "name", text="")
row.operator(UVPM3_OT_NewGroupingScheme.bl_idname, icon='ADD', text='' if self.active_g_scheme is not None else UVPM3_OT_NewGroupingScheme.bl_label)
if self.active_g_scheme is not None:
row.operator(UVPM3_OT_RemoveGroupingScheme.bl_idname, icon='REMOVE', text='')
box = row.box()
box.scale_y = 0.5
self.draw_grouping_schemes_presets(context, box)
if self.active_g_scheme is None:
return None
if self.should_draw_grouping_options():
main_col.separator()
main_col.separator()
main_col.label(text='Scheme options:')
self.draw_grouping_options(self.active_g_scheme.options, main_col, self.active_g_scheme)
def draw_impl2(self, context):
layout = self.layout
col = layout.column(align=True)
box = col.box()
col2 = box.column(align=True)
col2.label(text=Labels.GROUP_METHOD_NAME + ':')
row = col2.row(align=True)
row.prop(self.scene_props, "group_method", text='')
if self.scene_props.auto_grouping_enabled():
if self.should_draw_grouping_options():
options_box = col.box()
options_col = options_box.column(align=True)
options_col.label(text='Grouping options:')
# options_box = options_col.box()
self.draw_grouping_options(self.scene_props.auto_group_options, options_col)
box = col.box()
self.operator_with_help(UVPM3_OT_ApplyGroupingToScheme.bl_idname, box, self.APPLY_GROUPING_TO_SCHEME_HELP_URL_SUFFIX)
else:
# col.separator()
box = col.box()
self.draw_grouping_schemes(context, box)
class UVPM3_PT_SchemeGroups(UVPM3_PT_GroupingBase):
bl_idname = 'UVPM3_PT_SchemeGroups'
bl_label = 'Scheme Groups'
bl_parent_id = UVPM3_PT_Grouping.bl_idname
# bl_options = {'DEFAULT_CLOSED'}
PANEL_PRIORITY = 810
@classmethod
def poll(cls, context):
scene_props = context.scene.uvpm3_props
return super().poll(context) and\
scene_props.active_grouping_scheme(context) is not None
def draw_impl2(self, context):
layout = self.layout
main_col = layout.column(align=True)
groups_layout = main_col # .box()
show_more = self.active_g_scheme is not None and len(self.active_g_scheme.groups) > 1
row = groups_layout.row()
row.template_list(UVPM3_UL_GroupInfo.bl_idname, "", self.active_g_scheme, "groups",
self.active_g_scheme,
"active_group_idx", rows=4 if show_more else 2)
col = row.column(align=True)
col.operator(UVPM3_OT_NewGroupInfo.bl_idname, icon='ADD', text="")
col.operator(UVPM3_OT_RemoveGroupInfo.bl_idname, icon='REMOVE', text="")
if show_more:
col.separator()
col.operator(UVPM3_OT_MoveGroupInfo.bl_idname, icon='TRIA_UP', text="").direction = 'UP'
col.operator(UVPM3_OT_MoveGroupInfo.bl_idname, icon='TRIA_DOWN', text="").direction = 'DOWN'
if self.active_group is None:
return
col = groups_layout.column(align=True)
col.separator()
if hasattr(self.active_mode, 'draw_group_options'):
col.label(text='Group options:')
col2 = col.column(align=True)
props_count = self.active_mode.draw_group_options(self.active_g_scheme, self.active_group, col2)
if props_count == 0:
box = col2.box()
box.label(text='No group options available the for currently selected modes')
col.separator()
col.separator()
row = col.row(align=True)
row.operator(UVPM3_OT_SetManualGroupIParam.bl_idname)
col.separator()
col.label(text="Select islands assigned to the group:")
row = col.row(align=True)
op = row.operator(UVPM3_OT_SelectManualGroupIParam.bl_idname, text="Select")
op.select = True
op = row.operator(UVPM3_OT_SelectManualGroupIParam.bl_idname, text="Deselect")
op.select = False
row = col.row(align=True)
row.operator(UVPM3_OT_ShowManualGroupIParam.bl_idname)
class UVPM3_PT_GroupTargetBoxes(UVPM3_PT_GroupingBase):
bl_idname = 'UVPM3_PT_GroupTargetBoxes'
bl_label = 'Group Target Boxes'
bl_parent_id = UVPM3_PT_Grouping.bl_idname
# bl_options = {'DEFAULT_CLOSED'}
PANEL_PRIORITY = 820
@classmethod
def poll(cls, context):
if not super().poll(context):
return False
prefs = get_prefs()
scene_props = context.scene.uvpm3_props
active_mode = prefs.get_active_main_mode(scene_props, context)
if not active_mode.group_target_box_editing():
return False
active_g_scheme = scene_props.active_grouping_scheme(context)
if active_g_scheme is None:
return False
return active_g_scheme.group_target_box_editing()
def draw_impl2(self, context):
layout = self.layout
complementary_group_is_active = self.active_g_scheme.complementary_group_is_active()
target_boxes_col = layout.column(align=True)
target_boxes_col.enabled = not complementary_group_is_active
if complementary_group_is_active:
target_boxes_text='Group Target Boxes: (target boxes of the complementary group cannot be edited)'
target_boxes_icon='ERROR'
row = target_boxes_col.row()
row.label(text=target_boxes_text, icon=target_boxes_icon)
show_more = self.active_group is not None and len(self.active_group.target_boxes) > 1
row = target_boxes_col.row()
row.template_list(UVPM3_UL_TargetBoxes.bl_idname, "", self.active_group, "target_boxes",
self.active_group,
"active_target_box_idx", rows=4 if show_more else 2)
col = row.column(align=True)
col.operator(UVPM3_OT_NewTargetBox.bl_idname, icon='ADD', text="")
col.operator(UVPM3_OT_RemoveTargetBox.bl_idname, icon='REMOVE', text="")
if show_more:
col.separator()
col.operator(UVPM3_OT_MoveTargetBox.bl_idname, icon='TRIA_UP', text="").direction = 'UP'
col.operator(UVPM3_OT_MoveTargetBox.bl_idname, icon='TRIA_DOWN', text="").direction = 'DOWN'
# col = groups_layout.column(align=True)
target_boxes_col.separator()
box_edit_UI = GroupingSchemeBoxesEditUI(context, self.scene_props)
box_edit_UI.draw(target_boxes_col)
| [
"[email protected]"
] | |
edf52ab76db2cfd99a0af88763f296ce469be40c | d3efc82dfa61fb82e47c82d52c838b38b076084c | /Autocase_Result/SjShRightSide/YW_GGQQ_QLFSJHA_191.py | 7b402aecbf55309b2714b38ef26372383e256c92 | [] | no_license | nantongzyg/xtp_test | 58ce9f328f62a3ea5904e6ed907a169ef2df9258 | ca9ab5cee03d7a2f457a95fb0f4762013caa5f9f | refs/heads/master | 2022-11-30T08:57:45.345460 | 2020-07-30T01:43:30 | 2020-07-30T01:43:30 | 280,388,441 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,954 | py | #!/usr/bin/python
# -*- encoding: utf-8 -*-
import sys
import json
sys.path.append("/home/yhl2/workspace/xtp_test/xtp/api")
from xtp_test_case import *
sys.path.append("/home/yhl2/workspace/xtp_test/option/service")
from OptMainService import *
from OptQueryStkPriceQty import *
sys.path.append("/home/yhl2/workspace/xtp_test/service")
from log import *
from CaseParmInsertMysql import *
sys.path.append("/home/yhl2/workspace/xtp_test/option/mysql")
from Opt_SqlData_Transfer import *
sys.path.append("/home/yhl2/workspace/xtp_test/mysql")
from QueryOrderErrorMsg import queryOrderErrorMsg
sys.path.append("/home/yhl2/workspace/xtp_test/utils")
from env_restart import *
reload(sys)
sys.setdefaultencoding('utf-8')
class YW_GGQQ_QLFSJHA_191(xtp_test_case):
def setUp(self):
sql_transfer = Opt_SqlData_Transfer()
sql_transfer.transfer_fund_asset('YW_GGQQ_QLFSJHA_191')
clear_data_and_restart_sh()
Api.trade.Logout()
Api.trade.Login()
def test_YW_GGQQ_QLFSJHA_191(self):
title = '卖平（权利方平仓）：FOK市价全成或撤销-验资（可用资金不足）（下单金额<费用&&可用资金<（费用-下单金额））'
# 定义当前测试用例的期待值
# 期望状态：初始、未成交、部成、全成、部撤已报、部撤、已报待撤、已撤、废单、撤废、内部撤单
# xtp_ID和cancel_xtpID默认为0，不需要变动
case_goal = {
'期望状态': '废单',
'errorID': 11010120,
'errorMSG': queryOrderErrorMsg(11010120),
'是否生成报单': '是',
'是否是撤废': '否',
'xtp_ID': 0,
'cancel_xtpID': 0,
}
logger.warning(title)
# 定义委托参数信息------------------------------------------
# 参数：证券代码、市场、证券类型、证券状态、交易状态、买卖方向（Ｂ买Ｓ卖）、期望状态、Api
stkparm = QueryStkPriceQty('10001034', '1', '*', '1', '0', '*', case_goal['期望状态'], Api)
# 如果下单参数获取失败，则用例失败
if stkparm['返回结果'] is False:
rs = {
'用例测试结果': stkparm['返回结果'],
'测试错误原因': '获取下单参数失败,' + stkparm['错误原因'],
}
logger.error('查询结果为False,错误原因: {0}'.format(
json.dumps(rs['测试错误原因'], encoding='UTF-8', ensure_ascii=False)))
self.assertEqual(rs['用例测试结果'], True)
else:
wt_reqs = {
'business_type':Api.const.XTP_BUSINESS_TYPE['XTP_BUSINESS_TYPE_OPTION'],
'order_client_id':1,
'market': Api.const.XTP_MARKET_TYPE['XTP_MKT_SH_A'],
'ticker': stkparm['证券代码'],
'side': Api.const.XTP_SIDE_TYPE['XTP_SIDE_SELL'],
'position_effect':Api.const.XTP_POSITION_EFFECT_TYPE['XTP_POSITION_EFFECT_CLOSE'],
'price_type': Api.const.XTP_PRICE_TYPE['XTP_PRICE_BEST_OR_CANCEL'],
'price': stkparm['涨停价'],
'quantity': 1
}
ParmIni(Api, case_goal['期望状态'], wt_reqs['price_type'])
CaseParmInsertMysql(case_goal, wt_reqs)
rs = serviceTest(Api, case_goal, wt_reqs)
if rs['用例测试结果']:
logger.warning('执行结果为{0}'.format(str(rs['用例测试结果'])))
else:
logger.warning('执行结果为{0},{1},{2}'.format(
str(rs['用例测试结果']), str(rs['用例错误源']),
json.dumps(rs['用例错误原因'], encoding='UTF-8', ensure_ascii=False)))
self.assertEqual(rs['用例测试结果'], True) # 4
if __name__ == '__main__':
unittest.main()
| [
"[email protected]"
] | |
0da92cbd0e4ade8ad9bc3e92c2eeb5dba366e385 | 99d17ddba93db1105e8941b1b592d9d9e22864fb | /superset/dashboards/permalink/exceptions.py | c234d614f1a27fea248bc5ed03cb5599a37c9fc3 | [
"Apache-2.0",
"OFL-1.1"
] | permissive | apache-superset/incubator-superset | f376dc15d6e2187d0b65a0dc5476d6c6c3378f21 | 0945d4a2f46667aebb9b93d0d7685215627ad237 | refs/heads/master | 2023-03-15T04:12:40.478792 | 2022-07-25T14:44:43 | 2022-07-25T14:44:43 | 146,225,581 | 21 | 20 | Apache-2.0 | 2023-03-13T16:00:14 | 2018-08-26T23:56:08 | TypeScript | UTF-8 | Python | false | false | 1,253 | py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
from flask_babel import lazy_gettext as _
from superset.commands.exceptions import CommandException, CreateFailedError
class DashboardPermalinkInvalidStateError(CommandException):
message = _("Invalid state.")
class DashboardPermalinkCreateFailedError(CreateFailedError):
message = _("An error occurred while creating the value.")
class DashboardPermalinkGetFailedError(CommandException):
message = _("An error occurred while accessing the value.")
| [
"[email protected]"
] | |
ed3eebeafc63f9ab053b14216164390517280d87 | 30b5179e32c3f31b56b100238ee9d14449d02071 | /tests/components/picnic/test_config_flow.py | b731fce74f9bbc1033373b6eca43f0a513a03586 | [
"Apache-2.0"
] | permissive | Verbalinsurection/Home-Assistant-core | e149c13ecae32c34b7cabd0216abcfddd6244bdc | 5f69ae436003c75b1eeac2ec488049197e87e9ff | refs/heads/dev | 2023-09-01T18:34:53.715026 | 2023-02-14T21:17:22 | 2023-02-14T21:17:22 | 247,318,244 | 0 | 0 | Apache-2.0 | 2023-02-22T06:14:24 | 2020-03-14T17:04:17 | Python | UTF-8 | Python | false | false | 9,501 | py | """Test the Picnic config flow."""
from unittest.mock import patch
import pytest
from python_picnic_api.session import PicnicAuthError
import requests
from homeassistant import config_entries, data_entry_flow
from homeassistant.components.picnic.const import CONF_COUNTRY_CODE, DOMAIN
from homeassistant.const import CONF_ACCESS_TOKEN
from homeassistant.core import HomeAssistant
from tests.common import MockConfigEntry
@pytest.fixture
def picnic_api():
"""Create PicnicAPI mock with set response data."""
auth_token = "af3wh738j3fa28l9fa23lhiufahu7l"
auth_data = {
"user_id": "f29-2a6-o32n",
"address": {
"street": "Teststreet",
"house_number": 123,
"house_number_ext": "b",
},
}
with patch(
"homeassistant.components.picnic.config_flow.PicnicAPI",
) as picnic_mock:
picnic_mock().session.auth_token = auth_token
picnic_mock().get_user.return_value = auth_data
yield picnic_mock
async def test_form(hass, picnic_api):
"""Test we get the form and a config entry is created."""
result = await hass.config_entries.flow.async_init(
DOMAIN, context={"source": config_entries.SOURCE_USER}
)
assert result["type"] == data_entry_flow.FlowResultType.FORM
assert result["step_id"] == "user"
assert result["errors"] is None
with patch(
"homeassistant.components.picnic.async_setup_entry",
return_value=True,
) as mock_setup_entry:
result2 = await hass.config_entries.flow.async_configure(
result["flow_id"],
{
"username": "test-username",
"password": "test-password",
"country_code": "NL",
},
)
await hass.async_block_till_done()
assert result2["type"] == "create_entry"
assert result2["title"] == "Teststreet 123b"
assert result2["data"] == {
CONF_ACCESS_TOKEN: picnic_api().session.auth_token,
CONF_COUNTRY_CODE: "NL",
}
assert len(mock_setup_entry.mock_calls) == 1
async def test_form_invalid_auth(hass: HomeAssistant) -> None:
"""Test we handle invalid authentication."""
result = await hass.config_entries.flow.async_init(
DOMAIN, context={"source": config_entries.SOURCE_USER}
)
with patch(
"homeassistant.components.picnic.config_flow.PicnicHub.authenticate",
side_effect=PicnicAuthError,
):
result2 = await hass.config_entries.flow.async_configure(
result["flow_id"],
{
"username": "test-username",
"password": "test-password",
"country_code": "NL",
},
)
assert result2["type"] == data_entry_flow.FlowResultType.FORM
assert result2["errors"] == {"base": "invalid_auth"}
async def test_form_cannot_connect(hass: HomeAssistant) -> None:
"""Test we handle connection errors."""
result = await hass.config_entries.flow.async_init(
DOMAIN, context={"source": config_entries.SOURCE_USER}
)
with patch(
"homeassistant.components.picnic.config_flow.PicnicHub.authenticate",
side_effect=requests.exceptions.ConnectionError,
):
result2 = await hass.config_entries.flow.async_configure(
result["flow_id"],
{
"username": "test-username",
"password": "test-password",
"country_code": "NL",
},
)
assert result2["type"] == data_entry_flow.FlowResultType.FORM
assert result2["errors"] == {"base": "cannot_connect"}
async def test_form_exception(hass: HomeAssistant) -> None:
"""Test we handle random exceptions."""
result = await hass.config_entries.flow.async_init(
DOMAIN, context={"source": config_entries.SOURCE_USER}
)
with patch(
"homeassistant.components.picnic.config_flow.PicnicHub.authenticate",
side_effect=Exception,
):
result2 = await hass.config_entries.flow.async_configure(
result["flow_id"],
{
"username": "test-username",
"password": "test-password",
"country_code": "NL",
},
)
assert result2["type"] == data_entry_flow.FlowResultType.FORM
assert result2["errors"] == {"base": "unknown"}
async def test_form_already_configured(hass, picnic_api):
"""Test that an entry with unique id can only be added once."""
# Create a mocked config entry and make sure to use the same user_id as set for the picnic_api mock response.
MockConfigEntry(
domain=DOMAIN,
unique_id=picnic_api().get_user()["user_id"],
data={CONF_ACCESS_TOKEN: "a3p98fsen.a39p3fap", CONF_COUNTRY_CODE: "NL"},
).add_to_hass(hass)
result_init = await hass.config_entries.flow.async_init(
DOMAIN, context={"source": config_entries.SOURCE_USER}
)
result_configure = await hass.config_entries.flow.async_configure(
result_init["flow_id"],
{
"username": "test-username",
"password": "test-password",
"country_code": "NL",
},
)
await hass.async_block_till_done()
assert result_configure["type"] == data_entry_flow.FlowResultType.ABORT
assert result_configure["reason"] == "already_configured"
async def test_step_reauth(hass, picnic_api):
"""Test the re-auth flow."""
# Create a mocked config entry
conf = {CONF_ACCESS_TOKEN: "a3p98fsen.a39p3fap", CONF_COUNTRY_CODE: "NL"}
MockConfigEntry(
domain=DOMAIN,
unique_id=picnic_api().get_user()["user_id"],
data=conf,
).add_to_hass(hass)
# Init a re-auth flow
result_init = await hass.config_entries.flow.async_init(
DOMAIN, context={"source": config_entries.SOURCE_REAUTH}, data=conf
)
assert result_init["type"] == data_entry_flow.FlowResultType.FORM
assert result_init["step_id"] == "user"
with patch(
"homeassistant.components.picnic.async_setup_entry",
return_value=True,
):
result_configure = await hass.config_entries.flow.async_configure(
result_init["flow_id"],
{
"username": "test-username",
"password": "test-password",
"country_code": "NL",
},
)
await hass.async_block_till_done()
# Check that the returned flow has type abort because of successful re-authentication
assert result_configure["type"] == data_entry_flow.FlowResultType.ABORT
assert result_configure["reason"] == "reauth_successful"
assert len(hass.config_entries.async_entries()) == 1
async def test_step_reauth_failed(hass: HomeAssistant) -> None:
"""Test the re-auth flow when authentication fails."""
# Create a mocked config entry
user_id = "f29-2a6-o32n"
conf = {CONF_ACCESS_TOKEN: "a3p98fsen.a39p3fap", CONF_COUNTRY_CODE: "NL"}
MockConfigEntry(
domain=DOMAIN,
unique_id=user_id,
data=conf,
).add_to_hass(hass)
# Init a re-auth flow
result_init = await hass.config_entries.flow.async_init(
DOMAIN, context={"source": config_entries.SOURCE_REAUTH}, data=conf
)
assert result_init["type"] == data_entry_flow.FlowResultType.FORM
assert result_init["step_id"] == "user"
with patch(
"homeassistant.components.picnic.config_flow.PicnicHub.authenticate",
side_effect=PicnicAuthError,
):
result_configure = await hass.config_entries.flow.async_configure(
result_init["flow_id"],
{
"username": "test-username",
"password": "test-password",
"country_code": "NL",
},
)
await hass.async_block_till_done()
# Check that the returned flow has type form with error set
assert result_configure["type"] == "form"
assert result_configure["errors"] == {"base": "invalid_auth"}
assert len(hass.config_entries.async_entries()) == 1
async def test_step_reauth_different_account(hass, picnic_api):
"""Test the re-auth flow when authentication is done with a different account."""
# Create a mocked config entry, unique_id should be different that the user id in the api response
conf = {CONF_ACCESS_TOKEN: "a3p98fsen.a39p3fap", CONF_COUNTRY_CODE: "NL"}
MockConfigEntry(
domain=DOMAIN,
unique_id="3fpawh-ues-af3ho",
data=conf,
).add_to_hass(hass)
# Init a re-auth flow
result_init = await hass.config_entries.flow.async_init(
DOMAIN, context={"source": config_entries.SOURCE_REAUTH}, data=conf
)
assert result_init["type"] == data_entry_flow.FlowResultType.FORM
assert result_init["step_id"] == "user"
with patch(
"homeassistant.components.picnic.async_setup_entry",
return_value=True,
):
result_configure = await hass.config_entries.flow.async_configure(
result_init["flow_id"],
{
"username": "test-username",
"password": "test-password",
"country_code": "NL",
},
)
await hass.async_block_till_done()
# Check that the returned flow has type form with error set
assert result_configure["type"] == "form"
assert result_configure["errors"] == {"base": "different_account"}
assert len(hass.config_entries.async_entries()) == 1
| [
"[email protected]"
] | |
985a61e35a1166affcae13bcd6cc900782271bde | 9825db945e7bfe68319b086e9fb7091a63645d5c | /transcribe/mommy_recipes.py | 69965c1794946191d35991093b0493aa8e916c17 | [] | no_license | lupyanlab/telephone | e1ee095d5698dc228deec5ba5878a46b76d43f2d | 136f27fb2b41263f53fba6bd44711cf57598a1a4 | refs/heads/master | 2020-04-12T07:33:05.849287 | 2017-04-04T01:16:14 | 2017-04-04T01:16:14 | 41,316,823 | 1 | 1 | null | 2015-11-17T04:44:40 | 2015-08-24T17:20:23 | Python | UTF-8 | Python | false | false | 1,059 | py | from unipath import Path
from django.conf import settings
from django.core.files import File
from model_mommy.recipe import Recipe, foreign_key, related
import grunt.models as grunt_models
import ratings.models as ratings_models
import transcribe.models as transcribe_models
django_file_path = Path(settings.APP_DIR, 'grunt/tests/media/test-audio.wav')
assert django_file_path.exists()
django_file = File(open(django_file_path, 'rb'))
chain = Recipe(grunt_models.Chain,
name = 'mommy_chain')
seed = Recipe(grunt_models.Message,
chain = foreign_key(chain),
audio = django_file)
recording = Recipe(grunt_models.Message,
chain = foreign_key(chain),
parent = foreign_key(seed),
audio = django_file)
transcription_survey = Recipe(transcribe_models.TranscriptionSurvey)
message_to_transcribe = Recipe(transcribe_models.MessageToTranscribe,
survey = foreign_key(transcription_survey),
given = foreign_key(recording),
)
transcription = Recipe(transcribe_models.Transcription,
message = foreign_key(message_to_transcribe))
| [
"[email protected]"
] | |
48983f1ea96897668bf4f661b7f0605254dc330d | 02d1d89ed3c2a71a4f5a36f3a19f0683a0ae37e5 | /navigation/sonar/maxsonar_class.py~ | fbc039ae23b20329bb3f04d51f235e36260bfd38 | [] | no_license | lforet/robomow | 49dbb0a1c873f75e11228e24878b1e977073118b | eca69d000dc77681a30734b073b2383c97ccc02e | refs/heads/master | 2016-09-06T10:12:14.528565 | 2015-05-19T16:20:24 | 2015-05-19T16:20:24 | 820,388 | 11 | 6 | null | null | null | null | UTF-8 | Python | false | false | 2,504 | #!/usr/bin/env python
import serial
import threading
import time
# need to find best way to search seria ports for find device
class MaxSonar(object):
def __init__(self):
self._isConnected = False
self._ser = self._open_serial_port()
self._should_stop = threading.Event()
self._start_reading()
self._data = 0
#self._port = port
def _open_serial_port(self):
while self._isConnected == False:
print "class MaxSonar: searching serial ports for ultrasonic sensor package..."
for i in range(11):
port = "/dev/ttyUSB"
port = port[0:11] + str(i)
print "class MaxSonar: searching on port:", port
time.sleep(.2)
try:
ser = serial.Serial(port, 9600, timeout=1)
data = ser.readline()
#print "data=", int(data[3:(len(data)-1)])
if data[0:2] == "s1":
#ser.write("a\n") # write a string
print "class MaxSonar: found ultrasonic sensor package on serial port: ", port
self._isConnected = True
#self._port = ser
time.sleep(.3)
break
except:
pass
for i in range(11):
port = "/dev/ttyACM"
port = port[0:11] + str(i)
print "class MaxSonar: searching on port:", port
time.sleep(.2)
try:
ser = serial.Serial(port, 9600, timeout=1)
data = ser.readline()
#print "data=", int(data[3:(len(data)-1)])
if data[0:2] == "s1":
#ser.write("a\n") # write a string
print "class MaxSonar: found ultrasonic sensor package on serial port: ", port
self._isConnected = True
#self._port = ser
time.sleep(.3)
break
except:
pass
if self._isConnected == False:
print "class MaxSonar: ultrasonic sensor package not found!"
time.sleep(1)
#print "returning", ser
return ser
def _start_reading(self):
def read():
#print self._should_stop.isSet()
#print self._ser.isOpen()
while not self._should_stop.isSet():
try:
data = self._ser.readline()
#print "recieved: ", data
#self._data = int(data[5:(len(data)-1)])
self._data = data[0:(len(data)-1)]
except:
try:
print "class MaxSonar:no connection...attempting to reconnect"
self._data = 0
self._isConnected = False
self._ser = self._open_serial_port()
time.sleep(.5)
except:
pass
thr = threading.Thread(target=read)
thr.start()
return thr
def stop(self):
self._should_stop.set()
self._read_thread.wait()
def distances_cm(self):
return self._data
| [
"[email protected]"
] | ||
bb5bf27549da60b54e5a034ea948dda8c9c4d2d6 | eba05d8b5f45c109b68c5d19f7658fe62f9083ec | /client/verta/tests/test_entities.py | 839a00dcf025688f0b5b507482ed6082c33d058e | [
"Apache-2.0"
] | permissive | fagan2888/modeldb | 4b47d5ded2024ae1f61fda6d2980f8228e3937a5 | 7182cb9432eeb10b84abc89f925106abf5c43d21 | refs/heads/master | 2023-01-15T01:01:42.090856 | 2020-11-21T01:49:54 | 2020-11-21T01:49:54 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 23,592 | py | import six
import itertools
import os
import shutil
import requests
import pytest
from verta._registry import RegisteredModels
from verta._tracking.deployable_entity import _CACHE_DIR
from . import utils
import verta
import verta._internal_utils._utils
import json
from verta.external.six.moves.urllib.parse import urlparse # pylint: disable=import-error, no-name-in-module
KWARGS = {
'desc': [None, "A test."],
'tags': [None, ['test']],
'attrs': [None, {'is_test': True}],
}
KWARGS_COMBOS = [dict(zip(KWARGS.keys(), values))
for values
in itertools.product(*KWARGS.values())
if values.count(None) != len(values)]
# for `tags` typecheck tests
TAG = "my-tag"
class TestClient:
@pytest.mark.oss
def test_no_auth(self, host):
EMAIL_KEY, DEV_KEY_KEY = "VERTA_EMAIL", "VERTA_DEV_KEY"
EMAIL, DEV_KEY = os.environ.pop(EMAIL_KEY, None), os.environ.pop(DEV_KEY_KEY, None)
try:
client = verta.Client(host)
# still has source set
assert 'Grpc-Metadata-source' in client._conn.auth
assert client.set_project()
client.proj.delete()
finally:
if EMAIL is not None:
os.environ[EMAIL_KEY] = EMAIL
if DEV_KEY is not None:
os.environ[DEV_KEY_KEY] = DEV_KEY
@pytest.mark.skipif('VERTA_EMAIL' not in os.environ or 'VERTA_DEV_KEY' not in os.environ, reason="insufficient Verta credentials")
def test_verta_https(self):
hosts = [
"app.verta.ai",
]
for host in hosts:
# https by default
conn = verta.Client(host)._conn
assert conn.scheme == "https"
assert conn.scheme == conn.auth['Grpc-Metadata-scheme']
# http if provided
conn = verta.Client("http://{}".format(host))._conn
assert conn.scheme == "http"
assert conn.scheme == conn.auth['Grpc-Metadata-scheme']
# https if provided
conn = verta.Client("https://{}".format(host))._conn
assert conn.scheme == "https"
assert conn.scheme == conn.auth['Grpc-Metadata-scheme']
def test_else_http(self):
# test hosts must not redirect http to https
hosts = [
"www.google.com",
]
for host in hosts:
# http by default
try:
verta.Client(host, max_retries=0)
except requests.HTTPError as e:
assert e.request.url.split(':', 1)[0] == "http"
else:
raise RuntimeError("faulty test; expected error")
# http if provided
try:
verta.Client("http://{}".format(host), max_retries=0)
except requests.HTTPError as e:
assert e.request.url.split(':', 1)[0] == "http"
else:
raise RuntimeError("faulty test; expected error")
# https if provided
try:
verta.Client("https://{}".format(host), max_retries=0)
except requests.HTTPError as e:
assert e.request.url.split(':', 1)[0] == "https"
else:
raise RuntimeError("faulty test; expected error")
@pytest.mark.skipif(not all(env_var in os.environ for env_var in ('VERTA_HOST', 'VERTA_EMAIL', 'VERTA_DEV_KEY')), reason="insufficient Verta credentials")
def test_config_file(self):
self.config_file_with_type_util(connect = False)
@pytest.mark.skipif(not all(env_var in os.environ for env_var in ('VERTA_HOST', 'VERTA_EMAIL', 'VERTA_DEV_KEY')), reason="insufficient Verta credentials")
def test_config_file_connect(self):
self.config_file_with_type_util(connect = True)
def config_file_with_type_util(self, connect):
PROJECT_NAME = verta._internal_utils._utils.generate_default_name()
DATASET_NAME = verta._internal_utils._utils.generate_default_name()
EXPERIMENT_NAME = verta._internal_utils._utils.generate_default_name()
CONFIG_FILENAME = "verta_config.json"
HOST_KEY, EMAIL_KEY, DEV_KEY_KEY = "VERTA_HOST", "VERTA_EMAIL", "VERTA_DEV_KEY"
HOST, EMAIL, DEV_KEY = os.environ[HOST_KEY], os.environ[EMAIL_KEY], os.environ[DEV_KEY_KEY]
try:
del os.environ[HOST_KEY], os.environ[EMAIL_KEY], os.environ[DEV_KEY_KEY]
try:
with open(CONFIG_FILENAME, 'w') as f:
json.dump(
{
'host': HOST,
'email': EMAIL, 'dev_key': DEV_KEY,
'project': PROJECT_NAME,
'experiment': EXPERIMENT_NAME,
'dataset': DATASET_NAME,
},
f,
)
client = verta.Client(_connect=connect)
conn = client._conn
back_end_url = urlparse(HOST)
socket = back_end_url.netloc + back_end_url.path.rstrip('/')
assert conn.socket == socket
assert conn.auth['Grpc-Metadata-email'] == EMAIL
assert conn.auth['Grpc-Metadata-developer_key'] == DEV_KEY
if connect:
try:
assert client.set_experiment_run()
assert client.proj.name == PROJECT_NAME
assert client.expt.name == EXPERIMENT_NAME
finally:
if client.proj is not None:
client.proj.delete()
dataset = client.set_dataset()
try:
assert dataset.name == DATASET_NAME
finally:
utils.delete_datasets([dataset.id], conn)
else:
assert client._set_from_config_if_none(None, "project") == PROJECT_NAME
assert client._set_from_config_if_none(None, "experiment") == EXPERIMENT_NAME
assert client._set_from_config_if_none(None, "dataset") == DATASET_NAME
finally:
if os.path.exists(CONFIG_FILENAME):
os.remove(CONFIG_FILENAME)
finally:
os.environ[HOST_KEY], os.environ[EMAIL_KEY], os.environ[DEV_KEY_KEY] = HOST, EMAIL, DEV_KEY
@pytest.mark.not_oss
def test_wrong_credentials(self):
EMAIL_KEY, DEV_KEY_KEY = "VERTA_EMAIL", "VERTA_DEV_KEY"
old_email, old_dev_key = os.environ[EMAIL_KEY], os.environ[DEV_KEY_KEY]
try:
os.environ[EMAIL_KEY] = "[email protected]"
os.environ[DEV_KEY_KEY] = "def"
with pytest.raises(requests.exceptions.HTTPError) as excinfo:
verta.Client()
excinfo_value = str(excinfo.value).strip()
assert "401 Client Error" in excinfo_value
assert "authentication failed; please check `VERTA_EMAIL` and `VERTA_DEV_KEY`" in excinfo_value
finally:
os.environ[EMAIL_KEY], os.environ[DEV_KEY_KEY] = old_email, old_dev_key
class TestEntities:
def test_cache(self, client, strs):
client.set_project()
client.set_experiment()
entities = (
client.set_experiment_run(),
)
for entity in entities:
filename = strs[0]
filepath = os.path.join(_CACHE_DIR, filename)
contents = six.ensure_binary(strs[1])
assert not os.path.isfile(filepath)
assert not entity._get_cached_file(filename)
try:
assert entity._cache_file(filename, contents) == filepath
assert os.path.isfile(filepath)
assert entity._get_cached_file(filename)
with open(filepath, 'rb') as f:
assert f.read() == contents
finally:
shutil.rmtree(_CACHE_DIR, ignore_errors=True)
class TestProject:
def test_create(self, client):
assert client.set_project()
assert client.proj is not None
name = verta._internal_utils._utils.generate_default_name()
assert client.create_project(name)
assert client.proj is not None
with pytest.raises(requests.HTTPError) as excinfo:
assert client.create_project(name)
excinfo_value = str(excinfo.value).strip()
assert "409" in excinfo_value
assert "already exists" in excinfo_value
with pytest.warns(UserWarning, match='.*already exists.*'):
client.get_or_create_project(name=name, tags=["tag1", "tag2"])
def test_get(self, client):
name = verta._internal_utils._utils.generate_default_name()
with pytest.raises(ValueError):
client.get_project(name)
proj = client.set_project(name)
assert proj.id == client.get_project(proj.name).id
assert proj.id == client.get_project(id=proj.id).id
def test_get_by_name(self, client):
proj = client.set_project()
client.set_project() # in case get erroneously fetches latest
assert proj.id == client.set_project(proj.name).id
def test_get_by_id(self, client):
proj = client.set_project()
client.set_project() # in case get erroneously fetches latest
assert proj.id == client.set_project(id=proj.id).id
def test_get_nonexistent_id(self, client):
with pytest.raises(ValueError):
client.set_project(id="nonexistent_id")
@pytest.mark.parametrize("tags", [TAG, [TAG]])
def test_tags_is_list_of_str(self, client, tags):
proj = client.set_project(tags=tags)
endpoint = "{}://{}/api/v1/modeldb/project/getProjectTags".format(
client._conn.scheme,
client._conn.socket,
)
response = verta._internal_utils._utils.make_request("GET", endpoint, client._conn, params={'id': proj.id})
verta._internal_utils._utils.raise_for_http_error(response)
assert response.json().get('tags', []) == [TAG]
class TestExperiment:
def test_create(self, client):
client.set_project()
assert client.set_experiment()
assert client.expt is not None
name = verta._internal_utils._utils.generate_default_name()
assert client.create_experiment(name)
assert client.expt is not None
with pytest.raises(requests.HTTPError) as excinfo:
assert client.create_experiment(name)
excinfo_value = str(excinfo.value).strip()
assert "409" in excinfo_value
assert "already exists" in excinfo_value
with pytest.warns(UserWarning, match='.*already exists.*'):
client.set_experiment(name=name, attrs={"a": 123})
def test_get(self, client):
proj = client.set_project()
name = verta._internal_utils._utils.generate_default_name()
with pytest.raises(ValueError):
client.get_experiment(name)
expt = client.set_experiment(name)
assert expt.id == client.get_experiment(expt.name).id
assert expt.id == client.get_experiment(id=expt.id).id
# test parents are restored
client.set_project()
client.get_experiment(id=expt.id)
assert client.proj.id == proj.id
assert client.expt.id == expt.id
def test_get_by_name(self, client):
client.set_project()
expt = client.set_experiment()
client.set_experiment() # in case get erroneously fetches latest
assert expt.id == client.set_experiment(expt.name).id
def test_get_by_id(self, client):
proj = client.set_project()
expt = client.set_experiment()
client.set_experiment() # in case get erroneously fetches latest
assert expt.id == client.set_experiment(id=expt.id).id
assert proj.id == client.proj.id
def test_get_nonexistent_id_error(self, client):
with pytest.raises(ValueError):
client.set_experiment(id="nonexistent_id")
@pytest.mark.parametrize("tags", [TAG, [TAG]])
def test_tags_is_list_of_str(self, client, tags):
client.set_project()
expt = client.set_experiment(tags=tags)
endpoint = "{}://{}/api/v1/modeldb/experiment/getExperimentTags".format(
client._conn.scheme,
client._conn.socket,
)
response = verta._internal_utils._utils.make_request("GET", endpoint, client._conn, params={'id': expt.id})
verta._internal_utils._utils.raise_for_http_error(response)
assert response.json().get('tags', []) == [TAG]
class TestExperimentRun:
def test_create(self, client):
client.set_project()
client.set_experiment()
assert client.set_experiment_run()
name = verta._internal_utils._utils.generate_default_name()
assert client.create_experiment_run(name)
with pytest.raises(requests.HTTPError) as excinfo:
assert client.create_experiment_run(name)
excinfo_value = str(excinfo.value).strip()
assert "409" in excinfo_value
assert "already exists" in excinfo_value
with pytest.warns(UserWarning, match='.*already exists.*'):
client.set_experiment_run(name=name, attrs={"a": 123})
def test_get(self, client):
proj = client.set_project()
expt = client.set_experiment()
name = verta._internal_utils._utils.generate_default_name()
with pytest.raises(ValueError):
client.get_experiment_run(name)
run = client.set_experiment_run(name)
assert run.id == client.get_experiment_run(run.name).id
assert run.id == client.get_experiment_run(id=run.id).id
# test parents are restored by first setting new, unrelated ones
client.set_project()
client.set_experiment()
client.get_experiment_run(id=run.id)
assert client.proj.id == proj.id
assert client.expt.id == expt.id
def test_get_by_name(self, client):
client.set_project()
client.set_experiment()
run = client.set_experiment_run()
client.set_experiment_run() # in case get erroneously fetches latest
assert run.id == client.set_experiment_run(run.name).id
def test_get_by_id(self, client):
proj = client.set_project()
expt = client.set_experiment()
expt_run = client.set_experiment_run()
client.set_experiment_run() # in case get erroneously fetches latest
assert expt_run.id == client.set_experiment_run(id=expt_run.id).id
assert proj.id == client.proj.id
assert expt.id == client.expt.id
def test_get_nonexistent_id_error(self, client):
with pytest.raises(ValueError):
client.set_experiment_run(id="nonexistent_id")
def test_no_experiment_error(self, client):
with pytest.raises(AttributeError):
client.set_experimennt_run()
@pytest.mark.parametrize("tags", [TAG, [TAG]])
def test_tags_is_list_of_str(self, client, tags):
client.set_project()
client.set_experiment()
run = client.set_experiment_run(tags=tags)
endpoint = "{}://{}/api/v1/modeldb/experiment-run/getExperimentRunTags".format(
client._conn.scheme,
client._conn.socket,
)
response = verta._internal_utils._utils.make_request("GET", endpoint, client._conn, params={'id': run.id})
verta._internal_utils._utils.raise_for_http_error(response)
assert response.json().get('tags', []) == [TAG]
def test_clone(self, experiment_run):
expt_run = experiment_run
expt_run._conf.use_git = False
expt_run.log_hyperparameters({"hpp1" : 1, "hpp2" : 2, "hpp3" : "hpp3"})
expt_run.log_metrics({"metric1" : 0.5, "metric2" : 0.6})
expt_run.log_tags(["tag1", "tag2"])
expt_run.log_attributes({"attr1" : 10, "attr2" : {"abc": 1}})
expt_run.log_artifact("my-artifact", "README.md")
expt_run.log_code()
# set various things in the run
new_run_no_art = expt_run.clone()
old_run_msg = expt_run._get_proto_by_id(expt_run._conn, expt_run.id)
new_run_no_art_msg = new_run_no_art._get_proto_by_id(new_run_no_art._conn, new_run_no_art.id)
# ensure basic data is the same
assert expt_run.id != new_run_no_art_msg.id
assert old_run_msg.description == new_run_no_art_msg.description
assert old_run_msg.tags == new_run_no_art_msg.tags
assert old_run_msg.metrics == new_run_no_art_msg.metrics
assert old_run_msg.hyperparameters == new_run_no_art_msg.hyperparameters
assert old_run_msg.observations == new_run_no_art_msg.observations
assert old_run_msg.artifacts == new_run_no_art_msg.artifacts
def test_clone_into_expt(self, client):
expt1 = client.set_experiment()
expt2 = client.set_experiment()
assert expt1.id != expt2.id # of course, but just to be sure
old_run = client.set_experiment_run()
assert old_run._msg.experiment_id == expt2.id # of course, but just to be sure
old_run.log_hyperparameters({"hpp1" : 1, "hpp2" : 2, "hpp3" : "hpp3"})
old_run.log_metrics({"metric1" : 0.5, "metric2" : 0.6})
old_run.log_tags(["tag1", "tag2"])
old_run.log_attributes({"attr1" : 10, "attr2" : {"abc": 1}})
old_run.log_artifact("my-artifact", "README.md")
new_run = old_run.clone(experiment_id=expt1.id)
old_run_msg = old_run._get_proto_by_id(old_run._conn, old_run.id)
new_run_msg = new_run._get_proto_by_id(new_run._conn, new_run.id)
assert old_run_msg.id != new_run_msg.id
assert new_run_msg.experiment_id == expt1.id
assert old_run_msg.description == new_run_msg.description
assert old_run_msg.tags == new_run_msg.tags
assert old_run_msg.metrics == new_run_msg.metrics
assert old_run_msg.hyperparameters == new_run_msg.hyperparameters
assert old_run_msg.observations == new_run_msg.observations
assert old_run_msg.artifacts == new_run_msg.artifacts
def test_log_attribute_overwrite(self, client):
initial_attrs = {"str-attr": "attr", "int-attr": 4, "float-attr": 0.5}
new_attrs = {"str-attr": "new-attr", "int-attr": 5, "float-attr": 0.3, "bool-attr": False}
single_new_attr = new_attrs.popitem()
experiment_run = client.set_experiment_run(attrs=initial_attrs)
with pytest.raises(ValueError) as excinfo:
experiment_run.log_attribute("str-attr", "some-attr")
assert "already exists" in str(excinfo.value)
experiment_run.log_attribute(*single_new_attr, overwrite=True)
experiment_run.log_attributes(new_attrs, True)
expected_attrs = initial_attrs.copy()
expected_attrs.update([single_new_attr])
expected_attrs.update(new_attrs)
assert experiment_run.get_attributes() == expected_attrs
class TestExperimentRuns:
def test_getitem(self, client):
client.set_project()
expt_runs = client.set_experiment().expt_runs
local_run_ids = set(client.set_experiment_run().id for _ in range(3))
assert expt_runs[1].id in local_run_ids
def test_negative_indexing(self, client):
client.set_project()
expt_runs = client.set_experiment().expt_runs
local_run_ids = set(client.set_experiment_run().id for _ in range(3))
assert expt_runs[-1].id in local_run_ids
def test_index_out_of_range_error(self, client):
client.set_project()
expt_runs = client.set_experiment().expt_runs
[client.set_experiment_run() for _ in range(3)]
with pytest.raises(IndexError):
expt_runs[6]
with pytest.raises(IndexError):
expt_runs[-6]
def test_iter(self, client):
client.set_project()
expt_runs = client.set_experiment().expt_runs
expt_runs._ITER_PAGE_LIMIT = 3
local_run_ids = set(client.set_experiment_run().id for _ in range(6))
# iterate through all 6 runs
assert local_run_ids == set(run.id for run in expt_runs)
# don't fail ungracefully while runs are added
for i, _ in enumerate(expt_runs):
if i == 4:
[client.set_experiment_run() for _ in range(3)]
def test_len(self, client):
client.set_project()
expt_runs = client.set_experiment().expt_runs
assert len([client.set_experiment_run().id for _ in range(3)]) == len(expt_runs)
def test_as_dataframe(self, client, strs):
np = pytest.importorskip("numpy")
pytest.importorskip("pandas")
# initialize entities
client.set_project()
expt = client.set_experiment()
for _ in range(3):
client.set_experiment_run()
# log metadata
hpp1, hpp2, metric1, metric2 = strs[:4]
for run in expt.expt_runs:
run.log_hyperparameters({
hpp1: np.random.random(),
hpp2: np.random.random(),
})
run.log_metrics({
metric1: np.random.random(),
metric2: np.random.random(),
})
# verify that DataFrame matches
df = expt.expt_runs.as_dataframe()
assert set(df.index) == set(run.id for run in expt.expt_runs)
for run in expt.expt_runs:
row = df.loc[run.id]
assert row['hpp.'+hpp1] == run.get_hyperparameter(hpp1)
assert row['hpp.'+hpp2] == run.get_hyperparameter(hpp2)
assert row['metric.'+metric1] == run.get_metric(metric1)
assert row['metric.'+metric2] == run.get_metric(metric2)
def test_find(self, client):
client.set_project()
expt = client.set_experiment()
tag = "some-tag"
diff_tag = "diff-tag"
run_with_diff_tag = client.set_experiment_run("run-with-diff-tag")
run_with_diff_tag.log_tag(diff_tag)
runs_with_tag = []
for _ in range(5):
runs_with_tag.append(client.set_experiment_run())
runs_with_tag[-1].log_tag(tag)
found_runs = expt.expt_runs.find("tags ~= {}".format(tag))
assert len(found_runs) == len(runs_with_tag)
runs_with_tag[-1].log_hyperparameter("some-hyper", 1)
# compound conditions:
assert len(expt.expt_runs.find(["tags ~= {}".format(tag), "hyperparameters.some-hyper == 1"])) == 1 # old syntax
assert len(expt.expt_runs.find("tags ~= {}".format(tag), "hyperparameters.some-hyper == 1")) == 1 # new syntax
# if any predicate is not string, should fail:
with pytest.raises(TypeError, match="predicates must all be strings"):
expt.expt_runs.find("tag ~= {}".format(tag), 1234)
@pytest.mark.skip("functionality removed")
def test_add(self, client):
client.set_project()
expt1 = client.set_experiment()
local_expt1_run_ids = set(client.set_experiment_run().id for _ in range(3))
expt2 = client.set_experiment()
local_expt2_run_ids = set(client.set_experiment_run().id for _ in range(3))
# simple concatenation
assert local_expt1_run_ids | local_expt2_run_ids == set(run.id for run in expt1.expt_runs + expt2.expt_runs)
# ignore duplicates
assert local_expt1_run_ids == set(run.id for run in expt1.expt_runs + expt1.expt_runs)
| [
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e10f712169e012afe52d661cee1079d73d473cf5 | a4deea660ea0616f3b5ee0b8bded03373c5bbfa2 | /executale_binaries/register-variants/vpblendvb_xmm_xmm_xmm_xmm.gen.vex.py | 24114f1b5661dc25199fcafb0f1753e89bd770d4 | [] | no_license | Vsevolod-Livinskij/x86-64-instruction-summary | 4a43472e26f0e4ec130be9a82f7e3f3c1361ccfd | c276edab1b19e3929efb3ebe7514489f66087764 | refs/heads/master | 2022-02-02T18:11:07.818345 | 2019-01-25T17:19:21 | 2019-01-25T17:19:21 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 169 | py | import angr
proj = angr.Project('vpblendvb_xmm_xmm_xmm_xmm.exe')
print proj.arch
print proj.entry
print proj.filename
irsb = proj.factory.block(proj.entry).vex
irsb.pp() | [
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] | |
73f759e34e0bb373fed5832be2d79bf6a4727643 | c9ddbdb5678ba6e1c5c7e64adf2802ca16df778c | /cases/pa3/benchmarks/prime-193.py | a9022462728d26ffa25a7f481c9f9b2ca1f06f24 | [] | no_license | Virtlink/ccbench-chocopy | c3f7f6af6349aff6503196f727ef89f210a1eac8 | c7efae43bf32696ee2b2ee781bdfe4f7730dec3f | refs/heads/main | 2023-04-07T15:07:12.464038 | 2022-02-03T15:42:39 | 2022-02-03T15:42:39 | 451,969,776 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 571 | py | # Get the n-th prime starting from 2
def get_prime(n:int) -> int:
candidate:int = 2
found:int = 0
while True:
if is_prime(candidate):
found = found + 1
if found == n:
return candidate
candidate = candidate + 1
return 0 # Never happens
def is_prime(x:int) -> bool:
div:int = 2
while div < x:
if x % div == 0:
return False
div = div + 1
return True
# Input parameter
n:int = 15
# Run [1, n]
i:int = 1
# Crunch
while i <= n:
print($Exp(i))
i = i + 1
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bceb5d5fd70239529410c669bae6ea96ca0148fd | dbaec1262c8966d66512cadd343249786a8c266d | /tests/test_scraper.py | 1d196eeb7ad9cd52a2a34f6599ba263fbe8d42da | [] | no_license | andreqi/django-manolo | 96e50021a843cff1c223692853993c5dbb685acd | 01552875a47c4da90c89db6f0b9c05a269fa07ca | refs/heads/master | 2020-04-01T18:00:59.213208 | 2014-11-20T21:28:04 | 2014-11-20T21:28:04 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,654 | py | # -*- coding: utf-8 -*-
"""
test_django-manolo
------------
Tests for `django-manolo` models module.
"""
import datetime
from datetime import timedelta as td
import unittest
import dataset
import sqlalchemy
from django.conf import settings
from manolo.models import Manolo
from manolo.management.commands.scraper import Command
class TestManolo(unittest.TestCase):
def setUp(self):
db = dataset.connect('sqlite:///' + settings.DATABASES['default']['NAME'])
table = db['manolo_manolo']
table.create_column('office', sqlalchemy.String(length=250))
table.create_column('sha512', sqlalchemy.String(length=200))
table.create_column('visitor', sqlalchemy.String(length=250))
table.create_column('meeting_place', sqlalchemy.String(length=250))
table.create_column('host', sqlalchemy.String(length=250))
table.create_column('entity', sqlalchemy.String(length=250))
table.create_column('objective', sqlalchemy.String(length=250))
table.create_column('id_document', sqlalchemy.String(length=250))
table.create_column('date', sqlalchemy.Date())
table.create_column('time_start', sqlalchemy.String(length=100))
table.create_column('time_end', sqlalchemy.String(length=100))
Manolo.objects.get_or_create(date=None)
Manolo.objects.get_or_create(date=datetime.date(2011, 7, 28))
Manolo.objects.get_or_create(date=datetime.date.today())
def test_get_last_date_in_db(self):
d1 = Command()
d1.__init__()
result = d1.get_last_date_in_db() + td(3)
self.assertEqual(result, datetime.date.today())
| [
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15eb534642b2dbaf5eb98339e0cd15a18f7b59d6 | 4c228cca5bfdf3bd34dab2bedd7350ff501230b3 | /tools/ex_network.py | daaafecdccaa5dfaf16ca6adbc450de5273af72f | [] | no_license | gauenk/xi_uai18 | 3575b4b6db3393f4bc6a640a6b3c607a2d6bca6f | c24040f43e3d8779b7c2fff88f8ab787cf22c385 | refs/heads/master | 2022-02-24T04:29:14.037754 | 2020-04-04T16:57:17 | 2020-04-04T16:57:17 | 234,967,333 | 0 | 0 | null | 2021-03-29T23:13:54 | 2020-01-19T21:05:51 | Python | UTF-8 | Python | false | false | 2,877 | py | import plotly.graph_objects as go
import networkx as nx
def plot_network(G):
#
# plot the edges
#
edge_x = []
edge_y = []
for edge in G.edges():
x0, y0 = G.nodes[edge[0]]['pos']
x1, y1 = G.nodes[edge[1]]['pos']
edge_x.append(x0)
edge_x.append(x1)
edge_x.append(None)
edge_y.append(y0)
edge_y.append(y1)
edge_y.append(None)
edge_trace = go.Scatter(
x=edge_x, y=edge_y,
line=dict(width=0.5, color='#888'),
hoverinfo='none',
mode='lines')
#
# plot the nodes; allow for hover
#
node_x = []
node_y = []
for node in G.nodes():
x, y = G.nodes[node]['pos']
node_x.append(x)
node_y.append(y)
node_trace = go.Scatter(
x=node_x, y=node_y,
mode='markers',
hoverinfo='text',
marker=dict(
showscale=True,
# colorscale options
#'Greys' | 'YlGnBu' | 'Greens' | 'YlOrRd' | 'Bluered' | 'RdBu' |
#'Reds' | 'Blues' | 'Picnic' | 'Rainbow' | 'Portland' | 'Jet' |
#'Hot' | 'Blackbody' | 'Earth' | 'Electric' | 'Viridis' |
colorscale='YlGnBu',
reversescale=True,
color=[],
size=10,
colorbar=dict(
thickness=15,
title='Node Connections',
xanchor='left',
titleside='right'
),
line_width=2))
#
# set the text when hovering to show number of connections
#
node_adjacencies = []
node_text = []
for node, adjacencies in enumerate(G.adjacency()):
node_adjacencies.append(len(adjacencies[1]))
node_text.append('# of connections: '+str(len(adjacencies[1])))
node_trace.marker.color = node_adjacencies
node_trace.text = node_text
#
# plot the entire figure
#
fig = go.Figure(data=[edge_trace, node_trace],
layout=go.Layout(
title='<br>Network graph made with Python',
titlefont_size=16,
showlegend=False,
hovermode='closest',
margin=dict(b=20,l=5,r=5,t=40),
annotations=[ dict(
text="Python code: <a href='https://plot.ly/ipython-notebooks/network-graphs/'> https://plot.ly/ipython-notebooks/network-graphs/</a>",
showarrow=False,
xref="paper", yref="paper",
x=0.005, y=-0.002 ) ],
xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
yaxis=dict(showgrid=False, zeroline=False, showticklabels=False))
)
fig.show()
if __name__ == "__main__":
G = nx.random_geometric_graph(200, 0.125)
plot_network(G)
| [
"[email protected]"
] | |
52a051a1f273e344066b4ddedd4c4d3304bced08 | b21525fdcbb9724d51fd4b317c24f218d05144d2 | /FastBridgeApp/data/Latin/cicero_de_provinciis_consularibus.py | ade71b6415b0619a3190b8717db404d9d95ebc33 | [] | no_license | HCDigitalScholarship/FastBridge | 6202da636bcc2b6a6c7efe7b2a6d067510e7fa57 | 9037b0d5dee5da7d93ea53538595883559b07cda | refs/heads/master | 2023-09-02T02:58:47.683943 | 2023-06-06T19:20:09 | 2023-06-06T19:20:09 | 218,993,365 | 1 | 5 | null | 2023-06-06T19:20:10 | 2019-11-01T13:45:05 | Python | UTF-8 | Python | false | false | 261,464 | py | import text
nan=""
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133, 'ac', '', '', '2_3', 26), ('PAENE', 134, 'paene', '', '', '2_4', 4), ('FVNVS', 135, 'funera', '', '', '2_4', 5), ('CVM/3', 136, 'cum', '', '', '2_4', 29), ('PROPTER/2', 137, 'propter', '', '', '2_4', 10), ('ALIVS', 138, 'alias', '', '', '2_4', 15), ('CAVSA', 139, 'causas', '', '', '2_4', 9), ('TVM', 140, 'tum', '', '', '2_4', 12), ('MAGIS/2', 141, 'maxime', '', '', '2_4', 8), ('PROPTER/2', 142, 'propter', '', '', '2_4', 10), ('ILLE', 143, 'illud', '', '', '2_5', 96), ('INSIGNIS', 144, 'insigne', '', '', '2_5', 5), ('SCELVS', 145, 'scelus', '', '', '2_5', 10), ('IS', 146, 'eorum', '', '', '2_5', 77), ('ET/2', 147, 'et', '', '', '2_5', 110), ('IMPORTVNVS', 148, 'importunam', '', '', '2_5', 1), ('IN', 149, 'in', '', '', '2_5', 99), ('EGO', 150, 'me', '', '', '2_5', 88), ('CRVDELITAS', 151, 'crudelitatem', '', '', '2_5', 3), ('NON', 152, 'non', '', '', '2_6', 106), ('SOLVM/2', 153, 'solum', '', '', '2_6', 14), ('SENTENTIA', 154, 'sententia', '', '', '2_6', 17), ('SVVS', 155, 'sua', '', '', '2_6', 22), ('SED', 156, 'sed', '', '', '2_6', 42), ('ETIAM', 157, 'etiam', '', '', '2_6', 28), ('VERBVM', 158, 'uerborum', '', '', '2_6', 3), ('GRAVITAS', 159, 'grauitate', '', '', '2_6', 3), ('SVM/1', 160, 'esse', '', '', '2_6', 200), ('NOTO', 161, 'notandos', '', '', '2_7', 3), ('PVTO', 162, 'putauit', '', '', '2_7', 15), ('QVISNAM', 163, 'quonam', '', '', '2_7', 1), ('EGO', 164, 'me', '', '', '2_7', 88), ('ANIMVS', 165, 'animo', '', '', '2_7', 12), ('IN', 166, 'in', '', '', '2_7', 99), ('IS', 167, 'eos', '', '', '2_7', 77), ('SVM/1', 168, 'esse', '', '', '2_7', 200), ('OPORTET', 169, 'oportet', '', '', '2_7', 6), ('QVI/1', 170, 'cuius', '', '', '2_8', 172), ('ILLE', 171, 'illi', '', '', '2_8', 96), ('SALVS', 172, 'salutem', '', '', '2_8', 6), ('PRO/1', 173, 'pro', '', '', '2_8', 7), ('PIGNVS', 174, 'pignore', '', '', '2_8', 1), ('TRADO', 175, 'tradiderunt', '', '', '2_8', 4), ('AD/2', 176, 'ad', '', '', '2_8', 35), ('EXPLEO', 177, 'explendas', '', '', '2_8', 2), ('SVVS', 178, 'suas', '', '', '2_8', 22), ('CVPIDITAS', 179, 'cupiditates', '', '', '2_9', 4), ('SED', 180, 'sed', '', '', '2_9', 42), ('EGO', 181, 'ego', '', '', '2_9', 88), ('IN', 182, 'in', '', '', '2_9', 99), ('HIC/1', 183, 'hac', '', '', '2_9', 69), ('SENTENTIA', 184, 'sententia', '', '', '2_9', 17), ('DICO/2', 185, 'dicenda', '', '', '2_9', 23), ('NON', 186, 'non', '', '', '2_9', 106), ('PAREO', 187, 'parebo', '', '', '2_9', 2), ('DOLOR', 188, 'dolori', '', '', '2_10', 8), ('MEVS', 189, 'meo', '', '', '2_10', 36), ('NON', 190, 'non', '', '', '2_10', 106), ('IRACVNDIA', 191, 'iracundiae', '', '', '2_10', 1), ('SERVIO', 192, 'seruiam', '', '', '2_10', 1), ('QVI/1', 193, 'quo', '', '', '2_10', 172), ('ANIMVS', 194, 'animo', '', '', '2_10', 12), ('VNVSQVISQVE', 195, 'unus quisque', '', '', '2_11', 1), ('VOS', 196, 'uestrum', '', '', '2_11', 31), ('DEBEO', 197, 'debet', '', '', '2_11', 14), ('SVM/1', 198, 'esse', '', '', '2_11', 200), ('IN', 199, 'in', '', '', '2_11', 99), ('ILLE', 200, 'illos', '', '', '2_11', 96), ('HIC/1', 201, 'hoc', '', '', '2_11', 69), ('SVM/1', 202, 'ero', '', '', '2_11', 200), ('PRAECIPVVS', 203, 'praecipuum', '', '', '2_11', 1), ('ILLE', 204, 'illum', '', '', '2_11', 96), ('ET/2', 205, 'et', '', '', '2_12', 110), ('PROPRIVS', 206, 'proprium', '', '', '2_12', 1), ('SENSVS', 207, 'sensum', '', '', '2_12', 1), ('DOLOR', 208, 'doloris', '', '', '2_12', 8), ('MEVS', 209, 'mei', '', '', '2_12', 36), ('QVI/1', 210, 'quem', '', '', '2_12', 172), ('TAMEN', 211, 'tamen', '', '', '2_12', 16), ('VOS', 212, 'uos', '', '', '2_12', 31), ('COMMVNIS', 213, 'communem', '', '', '2_12', 6), ('SEMPER', 214, 'semper', '', '', '2_13', 7), ('VOS', 215, 'uobis', '', '', '2_13', 31), ('EGO', 216, 'me', '', '', '2_13', 88), ('CVM/2', 217, 'cum', '', '', '2_13', 33), ('SVM/1', 218, 'esse', '', '', '2_13', 200), ('DVCO', 219, 'duxistis', '', '', '2_13', 4), ('AB', 220, 'a', '', '', '2_13', 41), ('SENTENTIA', 221, 'sententia', '', '', '2_13', 17), ('DICO/2', 222, 'dicenda', '', '', '2_13', 23), ('AMOVEO', 223, 'amouebo', '', '', '2_14', 1), ('AD/2', 224, 'ad', '', '', '2_14', 35), ('VLCISCOR', 225, 'ulciscendi', '', '', '2_14', 1), ('TEMPVS/1', 226, 'tempora', '', '', '2_14', 13), ('RESERVO', 227, 'reseruabo', '', '', '2_14', 2), ('QVATVOR', 228, 'quattuor', '', '', '3_1', 1), ('SVM/1', 229, 'sunt', '', '', '3_1', 200), ('PROVINCIA', 230, 'prouinciae', '', '', '3_1', 31), ('PATER', 231, 'patres', '', '', '3_1', 17), ('CONSCRIBO', 232, 'conscripti', '', '', '3_1', 15), ('DE', 233, 'de', '', '', '3_1', 34), ('QVI/1', 234, 'quibus', '', '', '3_1', 172), ('ADHVC', 235, 'adhuc', '', '', '3_2', 2), ('INTELLIGO', 236, 'intellego', '', '', '3_2', 4), ('SENTENTIA', 237, 'sententias', '', '', '3_2', 17), ('SVM/1', 238, 'esse <dictas>', '', '', '3_2', 200), ('DICO/2', 239, '<esse> dictas', '', '', '3_2', 23), ('GALLIA/N', 240, 'Galliae', '', '', '3_2', 12), ('DVO', 241, 'duae', '', '', '3_2', 6), ('QVI/1', 242, 'quas', '', '', '3_2', 172), ('HIC/1', 243, 'hoc', '', '', '3_3', 69), ('TEMPVS/1', 244, 'tempore', '', '', '3_3', 13), ('VNVS', 245, 'uno', '', '', '3_3', 13), ('IMPERIVM', 246, 'imperio', '', '', '3_3', 18), ('VIDEO', 247, 'uidemus', '', '', '3_3', 24), ('SVM/1', 248, 'esse <coniunctas>', '', '', '3_3', 200), ('CONIVNGO', 249, '<esse> coniunctas', '', '', '3_3', 6), ('ET/2', 250, 'et', '', '', '3_3', 110), ('SYRIA/N', 251, 'Syria', '', '', '3_4', 10), ('ET/2', 252, 'et', '', '', '3_4', 110), ('MACEDONIA/N', 253, 'Macedonia', '', '', '3_4', 8), ('QVI/1', 254, 'quas', '', '', '3_4', 172), ('VOS', 255, 'uobis', '', '', '3_4', 31), ('INVITVS', 256, 'inuitis', '', '', '3_4', 3), ('ET/2', 257, 'et', '', '', '3_4', 110), ('OPPRIMO', 258, 'oppressis', '', '', '3_4', 1), ('PESTIFER', 259, 'pestiferi', '', '', '3_4', 1), ('ILLE', 260, 'illi', '', '', '3_5', 96), ('CONSVL', 261, 'consules', '', '', '3_5', 15), ('PRO/1', 262, 'pro', '', '', '3_5', 7), ('PERVERTO', 263, 'peruersae', '', '', '3_5', 1), ('RESPVBLICA', 264, 'rei publicae', '', '', '3_5', 44), ('PRAEMIVM', 265, 'praemiis', '', '', '3_5', 3), ('OCCVPO/2', 266, 'occupauerunt', '', '', '3_6', 1), ('DECERNO', 267, 'decernendae', '', '', '3_6', 23), ('NOS', 268, 'nobis', '', '', '3_6', 10), ('SVM/1', 269, 'sunt', '', '', '3_6', 200), ('LEX', 270, 'lege', '', '', '3_6', 21), ('SEMPRONIVS/A', 271, 'Sempronia', '', '', '3_6', 1), ('DVO', 272, 'duae', '', '', '3_6', 6), ('QVIS/1', 273, 'quid', '', '', '3_6', 31), ('SVM/1', 274, 'est', '', '', '3_7', 200), ('QVOD/1', 275, 'quod', '', '', '3_7', 20), ('POSSVM/1', 276, 'possimus', '', '', '3_7', 40), ('DE', 277, 'de', '', '', '3_7', 34), ('SYRIA/N', 278, 'Syria', '', '', '3_7', 10), ('MACEDONIA/N', 279, 'Macedonia', '', '', '3_7', 8), ('QVE', 280, 'que', '', '', '3_7', 36), ('DVBITO', 281, 'dubitare', '', '', '3_7', 3), ('MITTO', 282, 'mitto', '', '', '3_7', 6), ('QVOD/1', 283, 'quod', '', '', '3_8', 20), ('IS', 284, 'eas', '', '', '3_8', 77), ('ITA', 285, 'ita', '', '', '3_8', 14), ('PARIO/2', 286, 'partas', '', '', '3_8', 3), ('HABEO', 287, 'habent', '', '', '3_8', 19), ('IS', 288, 'ii', '', '', '3_8', 77), ('QVI/1', 289, 'qui', '', '', '3_8', 172), ('NVNC', 290, 'nunc', '', '', '3_8', 12), ('OBTINEO', 291, 'obtinent', '', '', '3_8', 1), ('VT/4', 292, 'ut', '', '', '3_8', 46), ('NON', 293, 'non', '', '', '3_8', 106), ('ATTINGO', 294, 'attigerint', '', '', '3_9', 1), ('ANTEQVAM', 295, '<ante> quam', '', '', '3_9', 6), ('HIC/1', 296, 'hunc', '', '', '3_9', 69), ('ORDO', 297, 'ordinem', '', '', '3_9', 16), ('CONDEMNO', 298, 'condemnarint', '', '', '3_9', 2), ('ANTEQVAM', 299, '<ante> quam', '', '', '3_9', 6), ('AVCTORITAS', 300, 'auctoritatem', '', '', '3_10', 7), ('VESTER', 301, 'uestram', '', '', '3_10', 11), ('EX', 302, 'e', '', '', '3_10', 16), ('CIVITAS', 303, 'ciuitate', '', '', '3_10', 9), ('EXTERMINO', 304, 'exterminarint', '', '', '3_10', 1), ('ANTEQVAM', 305, '<ante> quam', '', '', '3_10', 6), ('FIDES/2', 306, 'fidem', '', '', '3_10', 3), ('PVBLICVS/2', 307, 'publicam', '', '', '3_10', 2), ('ANTEQVAM', 308, '<ante> quam', '', '', '3_11', 6), ('PERPETVVS', 309, 'perpetuam', '', '', '3_11', 3), ('POPVLVS/1', 310, 'populi', '', '', '3_11', 15), ('ROMANVS/A', 311, 'Romani', '', '', '3_11', 13), ('SALVS', 312, 'salutem', '', '', '3_11', 6), ('ANTEQVAM', 313, '<ante> quam', '', '', '3_11', 6), ('EGO', 314, 'me', '', '', '3_11', 88), ('AC/1', 315, 'ac', '', '', '3_11', 26), ('MEI', 316, 'meos', '', '', '3_11', 1), ('OMNIS', 317, 'omnis', '', '', '3_12', 36), ('FOEDE', 318, 'foedissime', '', '', '3_12', 1), ('CRVDELITER', 319, 'crudelissime', '', '', '3_12', 1), ('QVE', 320, 'que', '', '', '3_12', 36), ('VEXO', 321, 'uexarint', '', '', '3_12', 4), ('OMNIS', 322, 'omnia', '', '', '4_1', 36), ('DOMESTICVS/2', 323, 'domestica', '', '', '4_2', 1), ('ATQVE/1', 324, 'atque', '', '', '4_2', 36), ('VRBANVS', 325, 'urbana', '', '', '4_2', 2), ('MITTO', 326, 'mitto', '', '', '4_2', 6), ('QVI/1', 327, 'quae', '', '', '4_2', 172), ('TANTVS', 328, 'tanta', '', '', '4_2', 3), ('SVM/1', 329, 'sunt', '', '', '4_2', 200), ('VT/4', 330, 'ut', '', '', '4_2', 46), ('NVMQVAM', 331, 'numquam', '', '', '4_2', 6), ('HANNIBAL/N', 332, 'Hannibal', '', '', '4_3', 1), ('HIC/1', 333, 'huic', '', '', '4_3', 69), ('VRBS', 334, 'urbi', '', '', '4_3', 9), ('TANTVM/2', 335, 'tantum', '', '', '4_3', 4), ('MALVM/1', 336, 'mali', '', '', '4_3', 1), ('OPTO', 337, 'optarit', '', '', '4_3', 1), ('QVANTVM/3', 338, 'quantum', '', '', '4_3', 3), ('ILLE', 339, 'illi', '', '', '4_3', 96), ('EFFICIO', 340, 'effecerint', '', '', '4_4', 1), ('AD/2', 341, 'ad', '', '', '4_4', 35), ('IPSE', 342, 'ipsas', '', '', '4_4', 33), ('VENIO', 343, 'uenio', '', '', '4_4', 2), ('PROVINCIA', 344, 'prouincias', '', '', '4_4', 31), ('QVI/1', 345, 'quarum', '', '', '4_4', 172), ('MACEDONIA/N', 346, 'Macedonia', '', '', '4_4', 8), ('QVI/1', 347, 'quae', '', '', '4_4', 172), ('SVM/1', 348, 'erat <munita>', '', '', '4_5', 200), ('ANTEA', 349, 'antea', '', '', '4_5', 11), ('MVNIO/2', 350, '<erat> munita', '', '', '4_5', 4), ('MVLTVS', 351, 'plurimorum', '', '', '4_5', 10), ('IMPERATOR', 352, 'imperatorum', '', '', '4_5', 14), ('NON', 353, 'non', '', '', '4_5', 106), ('TVRRIS', 354, 'turribus', '', '', '4_5', 1), ('SED', 355, 'sed', '', '', '4_5', 42), ('TROPAEVM', 356, 'tropaeis', '', '', '4_6', 1), ('QVI/1', 357, 'quae', '', '', '4_6', 172), ('MVLTVS', 358, 'multis', '', '', '4_6', 10), ('VICTORIA', 359, 'uictoriis', '', '', '4_6', 5), ('SVM/1', 360, 'erat <pacata>', '', '', '4_6', 200), ('IAMDIV', 361, 'iam diu', '', '', '4_6', 2), ('TRIVMPHVS', 362, 'triumphis', '', '', '4_6', 3), ('QVE', 363, 'que', '', '', '4_6', 36), ('PACO', 364, '<erat> pacata', '', '', '4_7', 2), ('SIC', 365, 'sic', '', '', '4_7', 7), ('AB', 366, 'a', '', '', '4_7', 41), ('BARBARVS/2', 367, 'barbaris', '', '', '4_7', 3), ('QVI/1', 368, 'quibus', '', '', '4_7', 172), ('SVM/1', 369, 'est <erepta>', '', '', '4_7', 200), ('PROPTER/2', 370, 'propter', '', '', '4_7', 10), ('AVARITIA', 371, 'auaritiam', '', '', '4_7', 2), ('PAX', 372, 'pax', '', '', '4_7', 7), ('ERIPIO', 373, '<est> erepta', '', '', '4_8', 2), ('VEXO', 374, 'uexatur', '', '', '4_8', 4), ('VT/4', 375, 'ut', '', '', '4_8', 46), ('THESSALONICENSIS/A', 376, 'Thessalonicenses', '', '', '4_8', 1), ('PONO', 377, 'positi', '', '', '4_8', 1), ('IN', 378, 'in', '', '', '4_8', 99), ('GREMIVM', 379, 'gremio', '', '', '4_8', 1), ('IMPERIVM', 380, 'imperi', '', '', '4_9', 18), ('NOSTER', 381, 'nostri', '', '', '4_9', 17), ('RELINQVO', 382, 'relinquere', '', '', '4_9', 4), ('OPPIDVM', 383, 'oppidum', '', '', '4_9', 3), ('ET/2', 384, 'et', '', '', '4_9', 110), ('ARX', 385, 'arcem', '', '', '4_9', 1), ('MVNIO/2', 386, 'munire', '', '', '4_9', 4), ('COGO', 387, 'cogantur', '', '', '4_9', 2), ('VT/4', 388, 'ut', '', '', '4_10', 46), ('VIA', 389, 'uia', '', '', '4_10', 2), ('ILLE', 390, 'illa', '', '', '4_10', 96), ('NOSTER', 391, 'nostra', '', '', '4_10', 17), ('QVI/1', 392, 'quae', '', '', '4_10', 172), ('PER', 393, 'per', '', '', '4_10', 10), ('MACEDONIA/N', 394, 'Macedoniam', '', '', '4_10', 8), ('SVM/1', 395, 'est', '', '', '4_10', 200), ('VSQVE', 396, 'usque', '', '', '4_10', 3), ('AD/2', 397, 'ad', '', '', '4_10', 35), ('HELLESPONTVS/N', 398, 'Hellespontum', '', '', '4_11', 1), ('MILITARIS', 399, 'militaris', '', '', '4_11', 2), ('NON', 400, 'non', '', '', '4_11', 106), ('SOLVM/2', 401, 'solum', '', '', '4_11', 14), ('EXCVRSIO', 402, 'excursionibus', '', '', '4_11', 1), ('BARBARVS/2', 403, 'barbarorum', '', '', '4_12', 3), ('SVM/1', 404, 'sit', '', '', '4_12', 200), ('INFESTVS', 405, 'infesta', '', '', '4_12', 1), ('SED', 406, 'sed', '', '', '4_12', 42), ('ETIAM', 407, 'etiam', '', '', '4_12', 28), ('CASTRA/2', 408, 'castris', '', '', '4_12', 1), ('THRACIVS/A', 409, 'Thraeciis', '', '', '4_12', 1), ('DISTINGVO', 410, 'distincta (sit)', '', '', '4_12', 1), ('AC/1', 411, 'ac', '', '', '4_12', 26), ('NOTO', 412, 'notata (sit)', '', '', '4_13', 3), ('ITA', 413, 'ita', '', '', '4_13', 14), ('GENS', 414, 'gentes', '', '', '4_13', 8), ('IS', 415, 'eae', '', '', '4_13', 77), ('QVI/1', 416, 'quae', '', '', '4_13', 172), ('VT/4', 417, 'ut', '', '', '4_13', 46), ('PAX', 418, 'pace', '', '', '4_13', 7), ('VTOR', 419, 'uterentur', '', '', '4_13', 3), ('VIS', 420, 'uim', '', '', '4_13', 4), ('ARGENTVM', 421, 'argenti', '', '', '4_13', 1), ('DO', 422, 'dederant', '', '', '4_14', 5), ('PRAECLARVS', 423, 'praeclaro', '', '', '4_14', 1), ('NOSTER', 424, 'nostro', '', '', '4_14', 17), ('IMPERATOR', 425, 'imperatori', '', '', '4_14', 14), ('VT/4', 426, 'ut', '', '', '4_14', 46), ('EXHAVRIO', 427, 'exhaustas', '', '', '4_14', 2), ('DOMVS', 428, 'domos', '', '', '4_14', 1), ('REPLEO', 429, 'replere', '', '', '4_15', 1), ('POSSVM/1', 430, 'possent', '', '', '4_15', 40), ('PRO/1', 431, 'pro', '', '', '4_15', 7), ('EMO', 432, 'empta', '', '', '4_15', 6), ('PAX', 433, 'pace', '', '', '4_15', 7), ('BELLVM', 434, 'bellum', '', '', '4_15', 23), ('NOS', 435, 'nobis', '', '', '4_15', 10), ('PROPE/2', 436, 'prope', '', '', '4_15', 6), ('IVSTVS', 437, 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('ORDO', 1148, 'ordinis', '', '', '11_7', 16), ('EQVESTER', 1149, 'equestris', '', '', '11_7', 2), ('BONI', 1150, 'bonorum', '', '', '11_7', 3), ('QVE', 1151, 'que', '', '', '11_7', 36), ('OMNIS', 1152, 'omnium', '', '', '11_7', 36), ('NON', 1153, 'non', '', '', '11_7', 106), ('SOLVM/2', 1154, 'solum', '', '', '11_7', 14), ('BONVM', 1155, 'bona', '', '', '11_7', 2), ('SED', 1156, 'sed', '', '', '11_7', 42), ('ETIAM', 1157, 'etiam', '', '', '11_8', 28), ('HONESTAS', 1158, 'honestatem', '', '', '11_8', 1), ('MISER', 1159, 'miseri', '', '', '11_8', 4), ('DEPERDO', 1160, 'deperdiderunt', '', '', '11_8', 1), ('QVI/1', 1161, 'quos', '', '', '11_8', 172), ('NON', 1162, 'non', '', '', '11_8', 106), ('PARSIMONIA', 1163, 'parsimonia', '', '', '11_8', 2), ('NON', 1164, 'non', '', '', '11_9', 106), ('CONTINENTIA', 1165, 'continentia', '', '', '11_9', 1), ('NON', 1166, 'non', '', '', '11_9', 106), ('VIRTVS', 1167, 'uirtus', '', '', '11_9', 5), ('NON', 1168, 'non', '', '', '11_9', 106), ('LABOR/1', 1169, 'labor', '', '', '11_9', 4), ('NON', 1170, 'non', '', '', '11_9', 106), ('SPLENDOR', 1171, 'splendor', '', '', '11_9', 1), ('TVEOR', 1172, 'tueri', '', '', '11_9', 2), ('POSSVM/1', 1173, 'potuit', '', '', '11_10', 40), ('CONTRA/2', 1174, 'contra', '', '', '11_10', 9), ('ILLE', 1175, 'illius', '', '', '11_10', 96), ('HELLVO', 1176, 'helluonis', '', '', '11_10', 1), ('ET/2', 1177, 'et', '', '', '11_10', 110), ('PRAEDO', 1178, 'praedonis', '', '', '11_10', 1), ('AVDACIA', 1179, 'audaciam', '', '', '11_10', 4), ('QVIS/1', 1180, 'quid', '', '', '12_1', 31), ('QVI/1', 1181, 'qui', '', '', '12_2', 172), ('SVI/1', 1182, 'se', '', '', '12_2', 26), ('ETIAMNVNC', 1183, 'etiam nunc', '', '', '12_2', 1), ('SVBSIDIVM', 1184, 'subsidiis', '', '', '12_2', 2), ('PATRIMONIVM', 1185, 'patrimoni', '', '', '12_2', 1), ('AVT', 1186, 'aut', '', '', '12_2', 35), ('AMICVS/2', 1187, 'amicorum', '', '', '12_2', 8), ('LIBERALITAS', 1188, 'liberalitate', '', '', '12_3', 2), ('SVSTENTO', 1189, 'sustentant', '', '', '12_3', 2), ('HIC/1', 1190, 'hos', '', '', '12_3', 69), ('PEREO/1', 1191, 'perire', '', '', '12_3', 1), ('PATIOR', 1192, 'patiemur', '', '', '12_3', 2), ('AN', 1193, 'an', '', '', '12_3', 11), ('SI/2', 1194, 'si', '', '', '12_3', 62), ('QVIS/2', 1195, 'qui', '', '', '12_3', 6), ('FRVOR', 1196, 'frui', '', '', '12_3', 4), ('PVBLICVM', 1197, 'publico', '', '', '12_3', 1), ('NON', 1198, 'non', '', '', '12_4', 106), ('POSSVM/1', 1199, 'potuit', '', '', '12_4', 40), ('PER', 1200, 'per', '', '', '12_4', 10), ('HOSTIS', 1201, 'hostem', '', '', '12_4', 8), ('HIC/1', 1202, 'hic', '', '', '12_4', 69), ('TEGO', 1203, 'tegitur', '', '', '12_4', 2), ('IPSE', 1204, 'ipsa', '', '', '12_4', 33), ('LEX', 1205, 'lege', '', '', '12_4', 21), ('CENSORIVS/2', 1206, 'censoria', '', '', '12_4', 2), ('QVI/1', 1207, 'quem', '', '', '12_4', 172), ('IS', 1208, 'is', '', '', '12_5', 77), ('FRVOR', 1209, 'frui', '', '', '12_5', 4), ('NON', 1210, 'non', '', '', '12_5', 106), ('SINO', 1211, 'sinit', '', '', '12_5', 2), ('QVI/1', 1212, 'qui', '', '', '12_5', 172), ('SVM/1', 1213, 'est', '', '', '12_5', 200), ('ETIAMSI', 1214, 'etiam si', '', '', '12_5', 4), ('NON', 1215, 'non', '', '', '12_5', 106), ('APPELLO/1', 1216, 'appellatur', '', '', '12_5', 2), ('HOSTIS', 1217, 'hostis', '', '', '12_5', 8), ('HIC/1', 1218, 'huic', '', '', '12_5', 69), ('FERO', 1219, 'ferri', '', '', '12_6', 8), ('AVXILIVM', 1220, 'auxilium', '', '', '12_6', 2), ('NON', 1221, 'non', '', '', '12_6', 106), ('OPORTET', 1222, 'oportet', '', '', '12_6', 6), ('RETINEO', 1223, 'retinete', '', '', '12_6', 6), ('IGITVR', 1224, 'igitur', '', '', '12_6', 5), ('IN', 1225, 'in', '', '', '12_6', 99), ('PROVINCIA', 1226, 'prouincia', '', '', '12_6', 31), ('DIV', 1227, 'diutius', '', '', '12_7', 3), ('IS', 1228, 'eum', '', '', '12_7', 77), ('QVI/1', 1229, 'qui', '', '', '12_7', 172), ('DE', 1230, 'de', '', '', '12_7', 34), ('SOCIVS/1', 1231, 'sociis', '', '', '12_7', 6), ('CVM/2', 1232, 'cum', '', '', '12_7', 33), ('HOSTIS', 1233, 'hostibus', '', '', '12_7', 8), ('DE', 1234, 'de', '', '', '12_7', 34), ('CIVIS', 1235, 'ciuibus', '', '', '12_7', 7), ('CVM/2', 1236, 'cum', '', '', '12_7', 33), ('SOCIVS/1', 1237, 'sociis', '', '', '12_8', 6), ('FACIO', 1238, 'faciat', '', '', '12_8', 16), ('PACTIO', 1239, 'pactiones', '', '', '12_8', 3), ('QVI/1', 1240, 'qui', '', '', '12_8', 172), ('HIC/1', 1241, 'hoc', '', '', '12_8', 69), ('ETIAM', 1242, 'etiam', '', '', '12_8', 28), ('SVI/1', 1243, 'se', '', '', '12_8', 26), ('MVLTVS', 1244, 'pluris', '', '', '12_8', 10), ('SVM/1', 1245, 'esse', '', '', '12_8', 200), ('QVAM/1', 1246, 'quam', '', '', '12_8', 19), ('COLLEGA', 1247, 'conlegam', '', '', '12_9', 2), ('PVTO', 1248, 'putet', '', '', '12_9', 15), ('QVOD/1', 1249, 'quod', '', '', '12_9', 20), ('ILLE', 1250, 'ille', '', '', '12_9', 96), ('VOS', 1251, 'uos', '', '', '12_9', 31), ('TRISTITIA', 1252, 'tristitia', '', '', '12_9', 1), ('VVLTVS', 1253, 'uultu', '', '', '12_9', 1), ('QVE', 1254, 'que', '', '', '12_9', 36), ('DECIPIO', 1255, 'deceperit', '', '', '12_9', 1), ('IPSE', 1256, 'ipse', '', '', '12_10', 33), ('NVMQVAM', 1257, 'numquam', '', '', '12_10', 6), ('SVI/1', 1258, 'se', '', '', '12_10', 26), ('PARVM/2', 1259, 'minus', '', '', '12_10', 7), ('QVAM/1', 1260, 'quam', '', '', '12_10', 19), ('SVM/1', 1261, 'erat', '', '', '12_10', 200), ('NEQVAM/2', 1262, 'nequam', '', '', '12_10', 2), ('SVM/1', 1263, 'esse', '', '', '12_10', 200), ('SIMVLO', 1264, 'simularit', '', '', '12_10', 1), ('PISO/N', 1265, 'Piso', '', '', '12_11', 7), ('AVTEM', 1266, 'autem', '', '', '12_11', 2), ('ALIVS', 1267, 'alio', '', '', '12_11', 15), ('QVIDAM', 1268, 'quodam', '', '', '12_11', 8), ('MODVS', 1269, 'modo', '', '', '12_11', 5), ('GLORIOR', 1270, 'gloriatur', '', '', '12_11', 2), ('SVI/1', 1271, 'se', '', '', '12_11', 26), ('BREVIS', 1272, 'breui', '', '', '12_11', 2), ('TEMPVS/1', 1273, 'tempore', '', '', '12_11', 13), ('PERFICIO', 1274, 'perfecisse', '', '', '12_12', 4), ('NE/4', 1275, 'ne', '', '', '12_12', 14), ('GAIVS/N', 1276, 'C.', '', '', '12_12', 19), ('GABINIVS/N', 1277, 'Gabinius', '', '', '12_12', 9), ('VNVS', 1278, 'unus', '', '', '12_12', 13), ('OMNIS', 1279, 'omnium', '', '', '12_12', 36), ('NEQVAM/2', 1280, 'nequissimus', '', '', '12_12', 2), ('EXISTIMO', 1281, 'existimaretur', '', '', '12_13', 3), ('HIC/1', 1282, 'hos', '', '', '13_1', 69), ('VOS', 1283, 'uos', '', '', '13_1', 31), ('DE', 1284, 'de', '', '', '13_1', 34), ('PROVINCIA', 1285, 'prouinciis', '', '', '13_1', 31), ('SI/2', 1286, 'si', '', '', '13_1', 62), ('NON', 1287, 'non', '', '', '13_1', 106), ('ALIQVANDO', 1288, 'aliquando', '', '', '13_1', 2), ('DEDVCO', 1289, 'deducendi', '', '', '13_1', 1), ('SVM/1', 1290, 'essent', '', '', '13_1', 200), ('DERIPIO', 1291, 'deripiendos', '', '', '13_2', 1), ('NON', 1292, 'non', '', '', '13_2', 106), ('PVTO', 1293, 'putaretis', '', '', '13_2', 15), ('ET/2', 1294, 'et', '', '', '13_2', 110), ('HIC/1', 1295, 'has', '', '', '13_2', 69), ('DVPLEX', 1296, 'duplicis', '', '', '13_2', 1), ('PESTIS', 1297, 'pestis', '', '', '13_2', 1), ('SOCIVS/1', 1298, 'sociorum', '', '', '13_2', 6), ('MILES', 1299, 'militum', '', '', '13_3', 3), ('CLADES', 1300, 'cladis', '', '', '13_3', 1), ('PVBLICANVS/1', 1301, 'publicanorum', '', '', '13_3', 6), ('RVINA', 1302, 'ruinas', '', '', '13_3', 2), ('PROVINCIA', 1303, 'prouinciarum', '', '', '13_3', 31), ('VASTITAS', 1304, 'uastitates', '', '', '13_3', 2), ('IMPERIVM', 1305, 'imperi', '', '', '13_4', 18), ('MACVLA', 1306, 'maculas', '', '', '13_4', 1), ('TENEO', 1307, 'teneretis', '', '', '13_4', 9), ('AT/2', 1308, 'at', '', '', '13_4', 5), ('IDEM', 1309, 'idem', '', '', '13_4', 27), ('VOS', 1310, 'uos', '', '', '13_4', 31), ('ANNVS', 1311, 'anno', '', '', '13_4', 2), ('SVPERVS', 1312, 'superiore', '', '', '13_4', 13), ('HIC/1', 1313, 'hos', '', '', '13_4', 69), ('IDEM', 1314, 'eosdem', '', '', '13_5', 27), ('REVOCO', 1315, 'reuocabatis', '', '', '13_5', 3), ('CVM/3', 1316, 'cum', '', '', '13_5', 29), ('IN', 1317, 'in', '', '', '13_5', 99), ('PROVINCIA', 1318, 'prouincias', '', '', '13_5', 31), ('PERVENIO', 1319, 'peruenissent', '', '', '13_5', 3), ('QVI/1', 1320, 'quo', '', '', '13_5', 172), ('TEMPVS/1', 1321, 'tempore', '', '', '13_6', 13), ('SI/2', 1322, 'si', '', '', '13_6', 62), ('LIBER/2', 1323, 'liberum', '', '', '13_6', 4), ('VESTER', 1324, 'uestrum', '', '', '13_6', 11), ('IVDICIVM', 1325, 'iudicium', '', '', '13_6', 4), ('SVM/1', 1326, 'fuisset', '', '', '13_6', 200), ('NEC/2', 1327, 'nec', '', '', '13_6', 7), ('TOTIENS', 1328, 'totiens', '', '', '13_6', 1), ('DIFFERO', 1329, 'dilata (esset)', '', '', '13_7', 2), ('RES', 1330, 'res', '', '', '13_7', 18), ('NEC/2', 1331, 'nec', '', '', '13_7', 7), ('AD/2', 1332, 'ad', '', '', '13_7', 35), ('EXTREMVS', 1333, 'extremum', '', '', '13_7', 3), ('EX', 1334, 'e', '', '', '13_7', 16), ('MANVS/1', 1335, 'manibus', '', '', '13_7', 3), ('ERIPIO', 1336, 'erepta (esset)', '', '', '13_7', 2), ('RESTITVO', 1337, 'restituissetis', '', '', '13_7', 2), ('IS', 1338, 'id', '', '', '13_8', 77), ('QVI/1', 1339, 'quod', '', '', '13_8', 172), ('CVPIO', 1340, 'cupiebatis', '', '', '13_8', 2), ('VESTER', 1341, 'uestram', '', '', '13_8', 11), ('AVCTORITAS', 1342, 'auctoritatem', '', '', '13_8', 7), ('IS', 1343, 'iis', '', '', '13_8', 77), ('PER', 1344, 'per', '', '', '13_8', 10), ('QVI/1', 1345, 'quos', '', '', '13_8', 172), ('SVM/1', 1346, 'erat <amissa>', '', '', '13_8', 200), ('AMITTO', 1347, '<erat> amissa', '', '', '13_9', 3), ('REVOCO', 1348, 'reuocatis', '', '', '13_9', 3), ('ET/2', 1349, 'et', '', '', '13_9', 110), ('IS', 1350, 'iis', '', '', '13_9', 77), ('IPSE', 1351, 'ipsis', '', '', '13_9', 33), ('PRAEMIVM', 1352, 'praemiis', '', '', '13_9', 3), ('EXTORQVEO', 1353, 'extortis', '', '', '13_9', 2), ('QVI/1', 1354, 'quae', '', '', '13_9', 172), ('SVM/1', 1355, 'erant <consecuti>', '', '', '13_9', 200), ('PRO/1', 1356, 'pro', '', '', '13_9', 7), ('SCELVS', 1357, 'scelere', '', '', '13_10', 10), ('ATQVE/1', 1358, 'atque', '', '', '13_10', 36), ('EVERSIO', 1359, 'euersione', '', '', '13_10', 1), ('PATRIA', 1360, 'patriae', '', '', '13_10', 7), ('CONSEQVOR', 1361, '<erant> consecuti', '', '', '13_10', 3), ('QVI/1', 1362, 'qua', '', '', '14_1', 172), ('EX', 1363, 'e', '', '', '14_1', 16), ('POENA', 1364, 'poena', '', '', '14_1', 3), ('SI/2', 1365, 'si', '', '', '14_1', 62), ('TVM', 1366, 'tum', '', '', '14_2', 12), ('ALIVS', 1367, 'aliorum', '', '', '14_2', 15), ('OPS', 1368, 'opibus', '', '', '14_2', 2), ('NON', 1369, 'non', '', '', '14_2', 106), ('SVVS', 1370, 'suis', '', '', '14_2', 22), ('INVITVS', 1371, 'inuitissimis', '', '', '14_2', 3), ('VOS', 1372, 'uobis', '', '', '14_2', 31), ('EVOLO/2', 1373, 'euolarunt', '', '', '14_2', 1), ('AT/2', 1374, 'at', '', '', '14_3', 5), ('ALIVS', 1375, 'aliam', '', '', '14_3', 15), ('MVLTO/2', 1376, 'multo', '', '', '14_3', 1), ('MAGNVS', 1377, 'maiorem', '', '', '14_3', 17), ('GRAVIS', 1378, 'grauiorem', '', '', '14_3', 6), ('QVE', 1379, 'que', '', '', '14_3', 36), ('SVBEO/1', 1380, 'subierunt', '', '', '14_3', 3), ('QVIS/1', 1381, 'quae', '', '', '14_3', 31), ('ENIM/2', 1382, 'enim', '', '', '14_4', 10), ('HOMO', 1383, 'homini', '', '', '14_4', 30), ('IN', 1384, 'in', '', '', '14_4', 99), ('QVI/1', 1385, 'quo', '', '', '14_4', 172), ('ALIQVIS', 1386, 'aliqui', '', '', '14_4', 11), ('SI/2', 1387, 'si', '', '', '14_4', 62), ('NON', 1388, 'non', '', '', '14_4', 106), ('FAMA', 1389, 'famae', '', '', '14_4', 3), ('PVDOR', 1390, 'pudor', '', '', '14_4', 2), ('AT/2', 1391, 'at', '', '', '14_4', 5), ('SVPPLICIVM', 1392, 'supplici', '', '', '14_4', 1), ('TIMOR', 1393, 'timor', '', '', '14_5', 1), ('SVM/1', 1394, 'est', '', '', '14_5', 200), ('GRAVIS', 1395, 'grauior', '', '', '14_5', 6), ('POENA', 1396, 'poena', '', '', '14_5', 3), ('ACCIDO/1', 1397, 'accidere', '', '', '14_5', 2), ('POSSVM/1', 1398, 'potuit', '', '', '14_5', 40), ('QVAM/1', 1399, 'quam', '', '', '14_5', 19), ('NON', 1400, 'non', '', '', '14_5', 106), ('CREDO', 1401, 'credi', '', '', '14_5', 6), ('LITTERA', 1402, 'litteris', '', '', '14_6', 8), ('IS', 1403, 'iis', '', '', '14_6', 77), ('QVI/1', 1404, 'quae', '', '', '14_6', 172), ('RESPVBLICA', 1405, 'rem publicam', '', '', '14_6', 44), ('BENE', 1406, 'bene', '', '', '14_6', 6), ('GERO', 1407, 'gestam (esse)', '', '', '14_6', 10), ('IN', 1408, 'in', '', '', '14_6', 99), ('BELLVM', 1409, 'bello', '', '', '14_6', 23), ('NVNTIO', 1410, 'nuntiarent', '', '', '14_6', 1), ('HIC/1', 1411, 'hoc', '', '', '14_7', 69), ('STATVO', 1412, 'statuit', '', '', '14_7', 3), ('SENATVS', 1413, 'senatus', '', '', '14_7', 13), ('CVM/3', 1414, 'cum', '', '', '14_7', 29), ('FREQVENS', 1415, 'frequens', '', '', '14_7', 1), ('SVPPLICATIO', 1416, 'supplicationem', '', '', '14_7', 9), ('GABINIVS/N', 1417, 'Gabinio', '', '', '14_7', 9), ('DENEGO', 1418, 'denegauit', '', '', '14_8', 3), ('PRIMVM', 1419, 'primum', '', '', '14_8', 5), ('HOMO', 1420, 'homini', '', '', '14_8', 30), ('SCELVS', 1421, 'sceleribus', '', '', '14_8', 10), ('FLAGITIVM', 1422, 'flagitiis', '', '', '14_8', 1), ('CONTAMINO', 1423, 'contaminatissimo', '', '', '14_9', 1), ('NIHIL', 1424, 'nihil', '', '', '14_9', 16), ('SVM/1', 1425, 'esse', '', '', '14_9', 200), ('CREDO', 1426, 'credendum', '', '', '14_9', 6), ('DEINDE', 1427, 'deinde', '', '', '14_9', 3), ('AB', 1428, 'a', '', '', '14_9', 41), ('PRODITOR', 1429, 'proditore', '', '', '14_9', 1), ('ATQVE/1', 1430, 'atque', '', '', '14_9', 36), ('IS', 1431, 'eo', '', '', '14_9', 77), ('QVI/1', 1432, 'quem', '', '', '14_10', 172), ('PRAESENS', 1433, 'praesentem', '', '', '14_10', 2), ('HOSTIS', 1434, 'hostem', '', '', '14_10', 8), ('RESPVBLICA', 1435, 'rei publicae', '', '', '14_10', 44), ('COGNOSCO', 1436, 'cognosset', '', '', '14_10', 1), ('BENE', 1437, 'bene', '', '', '14_10', 6), ('RESPVBLICA', 1438, 'rem publicam', '', '', '14_11', 44), ('GERO', 1439, 'geri', '', '', '14_11', 10), ('NON', 1440, 'non', '', '', '14_11', 106), ('POSSVM/1', 1441, 'potuisse', '', '', '14_11', 40), ('POSTERIVS', 1442, 'postremo', '', '', '14_11', 2), ('NE/4', 1443, 'ne', '', '', '14_11', 14), ('DEVS', 1444, 'deos', '', '', '14_11', 4), ('QVIDEM', 1445, 'quidem', '', '', '14_11', 9), ('IMMORTALIS', 1446, 'immortalis', '', '', '14_12', 3), ('VOLO/3', 1447, 'uelle', '', '', '14_12', 17), ('APERIO', 1448, 'aperiri', '', '', '14_12', 1), ('SVVS', 1449, 'sua', '', '', '14_12', 22), ('TEMPLVM', 1450, 'templa', '', '', '14_12', 2), ('ET/2', 1451, 'et', '', '', '14_12', 110), ('SVI/1', 1452, 'sibi', '', '', '14_12', 26), ('SVPPLICO', 1453, 'supplicari', '', '', '14_12', 1), ('HOMO', 1454, 'hominis', '', '', '14_12', 30), ('IMPVRVS', 1455, 'impurissimi', '', '', '14_13', 1), ('ET/2', 1456, 'et', '', '', '14_13', 110), ('SCELERATVS', 1457, 'sceleratissimi', '', '', '14_13', 3), ('NOMEN', 1458, 'nomine', '', '', '14_13', 3), ('ITAQVE', 1459, 'itaque', '', '', '14_13', 8), ('ILLE', 1460, 'ille', '', '', '14_13', 96), ('ALTER', 1461, 'alter', '', '', '14_13', 10), ('AVT', 1462, 'aut', '', '', '14_13', 35), ('IPSE', 1463, 'ipse', '', '', '14_14', 33), ('SVM/1', 1464, 'est', '', '', '14_14', 200), ('HOMO', 1465, 'homo', '', '', '14_14', 30), ('DOCTVS', 1466, 'doctus', '', '', '14_14', 1), ('ET/2', 1467, 'et', '', '', '14_14', 110), ('AB', 1468, 'a', '', '', '14_14', 41), ('SVVS', 1469, 'suis', '', '', '14_14', 22), ('GRAECVS/A', 1470, 'Graecis', '', '', '14_14', 2), ('SVBTILIS', 1471, 'subtilius', '', '', '14_14', 1), ('ERVDIO', 1472, 'eruditus', '', '', '14_14', 1), ('QVI/1', 1473, 'quibus', '', '', '14_15', 172), ('CVM/2', 1474, 'cum', '', '', '14_15', 33), ('IAM', 1475, 'iam', '', '', '14_15', 14), ('IN', 1476, 'in', '', '', '14_15', 99), ('EXOSTRA', 1477, 'exostra', '', '', '14_15', 1), ('HELVOR', 1478, 'helluatur', '', '', '14_15', 1), ('ANTEA', 1479, 'antea', '', '', '14_15', 11), ('POST/2', 1480, 'post', '', '', '14_15', 4), ('SIPARIVM', 1481, 'siparium', '', '', '14_15', 1), ('SOLEO', 1482, 'solebat', '', '', '14_16', 1), ('AVT', 1483, 'aut', '', '', '14_16', 35), ('AMICVS/2', 1484, 'amicos', '', '', '14_16', 8), ('HABEO', 1485, 'habet', '', '', '14_16', 19), ('PRVDENS', 1486, 'prudentiores', '', '', '14_16', 1), ('QVAM/1', 1487, 'quam', '', '', '14_16', 19), ('GABINIVS/N', 1488, 'Gabinius', '', '', '14_16', 9), ('QVI/1', 1489, 'cuius', '', '', '14_16', 172), ('NVLLVS', 1490, 'nullae', '', '', '14_17', 9), ('LITTERA', 1491, 'litterae', '', '', '14_17', 8), ('PROFERO', 1492, 'proferuntur', '', '', '14_17', 1), ('HIC/1', 1493, 'hosce', '', '', '15_1', 69), ('IGITVR', 1494, 'igitur', '', '', '15_1', 5), ('IMPERATOR', 1495, 'imperatores', '', '', '15_1', 14), ('HABEO', 1496, 'habebimus', '', '', '15_1', 19), ('QVI/1', 1497, 'quorum', '', '', '15_1', 172), ('ALTER', 1498, 'alter', '', '', '15_1', 10), ('NON', 1499, 'non', '', '', '15_1', 106), ('AVDEO', 1500, 'audet', '', '', '15_2', 4), ('NOS', 1501, 'nos', '', '', '15_2', 10), ('CERTVS', 1502, 'certiores', '', '', '15_2', 3), ('FACIO', 1503, 'facere', '', '', '15_2', 16), ('QVARE/1', 1504, 'qua re', '', '', '15_2', 4), ('IMPERATOR', 1505, 'imperator', '', '', '15_2', 14), ('APPELLO/1', 1506, 'appelletur', '', '', '15_2', 2), ('ALTER', 1507, 'alterum', '', '', '15_2', 10), ('SI/2', 1508, 'si', '', '', '15_3', 62), ('TABELLARIVS/1', 1509, 'tabellarii', '', '', '15_3', 1), ('NON', 1510, 'non', '', '', '15_3', 106), ('CESSO', 1511, 'cessarint', '', '', '15_3', 1), ('NECESSE', 1512, 'necesse', '', '', '15_3', 3), ('SVM/1', 1513, 'est', '', '', '15_3', 200), ('PAVCI', 1514, 'paucis', '', '', '15_3', 1), ('DIES', 1515, 'diebus', '', '', '15_3', 11), ('PAENITEO', 1516, 'paeniteat', '', '', '15_3', 1), ('AVDEO', 1517, 'audere', '', '', '15_4', 4), ('QVI/1', 1518, 'cuius', '', '', '15_4', 172), ('AMICVS/2', 1519, 'amici', '', '', '15_4', 8), ('SI/2', 1520, 'si', '', '', '15_4', 62), ('QVIS/2', 1521, 'qui', '', '', '15_4', 6), ('SVM/1', 1522, 'sunt', '', '', '15_4', 200), ('AVT', 1523, 'aut', '', '', '15_4', 35), ('SI/2', 1524, 'si', '', '', '15_4', 62), ('BELVA', 1525, 'beluae', '', '', '15_4', 1), ('TAM', 1526, 'tam', '', '', '15_4', 5), ('IMMANIS', 1527, 'immani', '', '', '15_4', 3), ('TAM', 1528, 'tam', '', '', '15_5', 5), ('QVE', 1529, 'que', '', '', '15_5', 36), ('TETER', 1530, 'taetrae', '', '', '15_5', 2), ('POSSVM/1', 1531, 'possunt', '', '', '15_5', 40), ('VLLVS', 1532, 'ulli', '', '', '15_5', 7), ('SVM/1', 1533, 'esse', '', '', '15_5', 200), ('AMICVS/2', 1534, 'amici', '', '', '15_5', 8), ('HIC/1', 1535, 'hac', '', '', '15_5', 69), ('CONSOLATIO', 1536, 'consolatione', '', '', '15_5', 1), ('VTOR', 1537, 'utuntur', '', '', '15_6', 3), ('ETIAM', 1538, 'etiam', '', '', '15_6', 28), ('TITVS/N', 1539, 'T.', '', '', '15_6', 1), ('ALBVCIVS/N', 1540, 'Albucio', '', '', '15_6', 3), ('SVPPLICATIO', 1541, 'supplicationem', '', '', '15_6', 9), ('HIC/1', 1542, 'hunc', '', '', '15_6', 69), ('ORDO', 1543, 'ordinem', '', '', '15_6', 16), ('DENEGO', 1544, 'denegasse', '', '', '15_7', 3), ('QVI/1', 1545, 'quod', '', '', '15_7', 172), ('SVM/1', 1546, 'est', '', '', '15_7', 200), ('PRIMVM', 1547, 'primum', '', '', '15_7', 5), ('DISSIMILIS', 1548, 'dissimile', '', '', '15_7', 1), ('RES', 1549, 'res', '', '', '15_7', 18), ('IN', 1550, 'in', '', '', '15_7', 99), ('SARDINIA/N', 1551, 'Sardinia', '', '', '15_7', 2), ('CVM/2', 1552, 'cum', '', '', '15_7', 33), ('MASTRVCATVS', 1553, 'mastrucatis', '', '', '15_8', 1), ('LATRVNCVLVS', 1554, 'latrunculis', '', '', '15_8', 1), ('AB', 1555, 'a', '', '', '15_8', 41), ('PROPRAETOR', 1556, 'propraetore', '', '', '15_8', 1), ('VNVS', 1557, 'una', '', '', '15_8', 13), ('COHORS', 1558, 'cohorte', '', '', '15_8', 3), ('AVXILIARIS', 1559, 'auxiliaria', '', '', '15_8', 1), ('GERO', 1560, 'gesta (est)', '', '', '15_9', 10), ('ET/2', 1561, 'et', '', '', '15_9', 110), ('BELLVM', 1562, 'bellum', '', '', '15_9', 23), ('CVM/2', 1563, 'cum', '', '', '15_9', 33), ('MAGNVS', 1564, 'maximis', '', '', '15_9', 17), ('SYRIA/N', 1565, 'Syriae', '', '', '15_9', 10), ('GENS', 1566, 'gentibus', '', '', '15_9', 8), ('ET/2', 1567, 'et', '', '', '15_9', 110), ('TYRANNVS', 1568, 'tyrannis', '', '', '15_9', 2), ('CONSVLARIS/2', 1569, 'consulari', '', '', '15_10', 4), ('EXERCITVS/1', 1570, 'exercitu', '', '', '15_10', 8), ('IMPERIVM', 1571, 'imperio', '', '', '15_10', 18), ('QVE', 1572, 'que', '', '', '15_10', 36), ('CONFICIO', 1573, 'confectum (est)', '', '', '15_10', 7), ('DEINDE', 1574, 'deinde', '', '', '15_10', 3), ('ALBVCIVS/N', 1575, 'Albucius', '', '', '15_10', 3), ('QVI/1', 1576, 'quod', '', '', '15_11', 172), ('AB', 1577, 'a', '', '', '15_11', 41), ('SENATVS', 1578, 'senatu', '', '', '15_11', 13), ('PETO', 1579, 'petebat', '', '', '15_11', 3), ('IPSE', 1580, 'ipse', '', '', '15_11', 33), ('SVI/1', 1581, 'sibi', '', '', '15_11', 26), ('IN', 1582, 'in', '', '', '15_11', 99), ('SARDINIA/N', 1583, 'Sardinia', '', '', '15_11', 2), ('ANTE/2', 1584, 'ante', '', '', '15_11', 7), ('DECERNO', 1585, 'decreuerat', '', '', '15_11', 23), ('CONSTO', 1586, 'constabat', '', '', '15_12', 2), ('ENIM/2', 1587, 'enim', '', '', '15_12', 10), ('GRAECVS/A', 1588, 'Graecum', '', '', '15_12', 2), ('HOMO', 1589, 'hominem', '', '', '15_12', 30), ('AC/1', 1590, 'ac', '', '', '15_12', 26), ('LEVIS/1', 1591, 'leuem', '', '', '15_12', 2), ('IN', 1592, 'in', '', '', '15_12', 99), ('IPSE', 1593, 'ipsa', '', '', '15_12', 33), ('PROVINCIA', 1594, 'prouincia', '', '', '15_12', 31), ('QVASI/1', 1595, 'quasi', '', '', '15_13', 1), ('TRIVMPHO', 1596, 'triumphasse', '', '', '15_13', 3), ('ITAQVE', 1597, 'itaque', '', '', '15_13', 8), ('HIC/1', 1598, 'hanc', '', '', '15_13', 69), ('IS', 1599, 'eius', '', '', '15_13', 77), ('TEMERITAS', 1600, 'temeritatem', '', '', '15_13', 2), ('SENATVS', 1601, 'senatus', '', '', '15_13', 13), ('SVPPLICATIO', 1602, 'supplicatione', '', '', '15_14', 9), ('DENEGO', 1603, 'denegata', '', '', '15_14', 3), ('NOTO', 1604, 'notauit', '', '', '15_14', 3), ('SED', 1605, 'sed', '', '', '16_1', 42), ('FRVOR', 1606, 'fruatur', '', '', '16_1', 4), ('SANE', 1607, 'sane', '', '', '16_1', 1), ('HIC/1', 1608, 'hoc', '', '', '16_1', 69), ('SOLACIVM', 1609, 'solacio', '', '', '16_1', 1), ('ATQVE/1', 1610, 'atque', '', '', '16_2', 36), ('HIC/1', 1611, 'hanc', '', '', '16_2', 69), ('INSIGNIS', 1612, 'insignem', '', '', '16_2', 5), ('IGNOMINIA', 1613, 'ignominiam', '', '', '16_2', 3), ('QVONIAM', 1614, 'quoniam', '', '', '16_2', 1), ('VNVS', 1615, 'uni', '', '', '16_2', 13), ('PRAETER/2', 1616, 'praeter', '', '', '16_2', 1), ('SVI/1', 1617, 'se', '', '', '16_2', 26), ('INVRO', 1618, 'inusta <est>', '', '', '16_3', 1), ('SVM/1', 1619, '<inusta> est', '', '', '16_3', 200), ('PVTO', 1620, 'putet', '', '', '16_3', 15), ('SVM/1', 1621, 'esse', '', '', '16_3', 200), ('LEVIS/1', 1622, 'leuiorem', '', '', '16_3', 2), ('DVMMODO', 1623, 'dum modo', '', '', '16_3', 1), ('QVI/1', 1624, 'cuius', '', '', '16_3', 172), ('EXEMPLVM', 1625, 'exemplo', '', '', '16_3', 6), ('SVI/1', 1626, 'se', '', '', '16_4', 26), ('CONSOLOR', 1627, 'consolatur', '', '', '16_4', 1), ('IS', 1628, 'eius', '', '', '16_4', 77), ('EXITVS', 1629, 'exitum', '', '', '16_4', 1), ('EXSPECTO', 1630, 'exspectet', '', '', '16_4', 4), ('PRAESERTIM', 1631, 'praesertim', '', '', '16_4', 6), ('CVM/3', 1632, 'cum', '', '', '16_4', 29), ('IN', 1633, 'in', '', '', '16_4', 99), ('ALBVCIVS/N', 1634, 'Albucio', '', '', '16_5', 3), ('NEC/2', 1635, 'nec', '', '', '16_5', 7), ('PISO/N', 1636, 'Pisonis', '', '', '16_5', 7), ('LIBIDO', 1637, 'libidines', '', '', '16_5', 4), ('NEC/2', 1638, 'nec', '', '', '16_5', 7), ('AVDACIA', 1639, 'audacia', '', '', '16_5', 4), ('GABINIVS/N', 1640, 'Gabini', '', '', '16_5', 9), ('SVM/1', 1641, 'fuerit', '', '', '16_5', 200), ('AC/1', 1642, 'ac', '', '', '16_5', 26), ('TAMEN', 1643, 'tamen', '', '', '16_6', 16), ('HIC/1', 1644, 'hac', '', '', '16_6', 69), ('VNVS', 1645, 'una', '', '', '16_6', 13), ('PLAGA/1', 1646, 'plaga', '', '', '16_6', 2), ('CONCIDO/1', 1647, 'conciderit', '', '', '16_6', 1), ('IGNOMINIA', 1648, 'ignominia', '', '', '16_6', 3), ('SENATVS', 1649, 'senatus', '', '', '16_6', 13), ('ATQVI', 1650, 'atqui', '', '', '17_1', 1), ('DVO', 1651, 'duas', '', '', '17_1', 6), ('GALLIA/N', 1652, 'Gallias', '', '', '17_1', 12), ('QVI/1', 1653, 'qui', '', '', '17_1', 172), ('DECERNO', 1654, 'decernit', '', '', '17_1', 23), ('CONSVL', 1655, 'consulibus', '', '', '17_1', 15), ('DVO', 1656, 'duobus', '', '', '17_1', 6), ('HIC/1', 1657, 'hos', '', '', '17_1', 69), ('RETINEO', 1658, 'retinet', '', '', '17_2', 6), ('AMBO/2', 1659, 'ambo', '', '', '17_2', 1), ('QVI/1', 1660, 'qui', '', '', '17_2', 172), ('AVTEM', 1661, 'autem', '', '', '17_2', 2), ('ALTER', 1662, 'alteram', '', '', '17_2', 10), ('GALLIA/N', 1663, 'Galliam', '', '', '17_2', 12), ('ET/2', 1664, 'et', '', '', '17_2', 110), ('AVT', 1665, 'aut', '', '', '17_2', 35), ('SYRIA/N', 1666, 'Syriam', '', '', '17_2', 10), ('AVT', 1667, 'aut', '', '', '17_2', 35), ('MACEDONIA/N', 1668, 'Macedoniam', '', '', '17_3', 8), ('TAMEN', 1669, 'tamen', '', '', '17_3', 16), ('ALTER', 1670, 'alterum', '', '', '17_3', 10), ('RETINEO', 1671, 'retinet', '', '', '17_3', 6), ('ET/2', 1672, 'et', '', '', '17_3', 110), ('IN', 1673, 'in', '', '', '17_3', 99), ('VTERQVE', 1674, 'utriusque', '', '', '17_3', 1), ('PAR/2', 1675, 'pari', '', '', '17_3', 1), ('SCELVS', 1676, 'scelere', '', '', '17_4', 10), ('DISPAR', 1677, 'disparem', '', '', '17_4', 1), ('CONDICIO', 1678, 'condicionem', '', '', '17_4', 3), ('FACIO', 1679, 'facit', '', '', '17_4', 16), ('FACIO', 1680, 'faciam', '', '', '17_4', 16), ('INQVIO', 1681, 'inquit', '', '', '17_4', 3), ('ILLE', 1682, 'illas', '', '', '17_4', 96), ('PRAETORIVS/2', 1683, 'praetorias', '', '', '17_5', 2), ('VT/4', 1684, 'ut', '', '', '17_5', 46), ('PISO/N', 1685, 'Pisoni', '', '', '17_5', 7), ('ET/2', 1686, 'et', '', '', '17_5', 110), ('GABINIVS/N', 1687, 'Gabinio', '', '', '17_5', 9), ('SVCCEDO/1', 1688, 'succedatur', '', '', '17_5', 4), ('STATIM', 1689, 'statim', '', '', '17_5', 2), ('SI/2', 1690, 'si', '', '', '17_5', 62), ('HIC/1', 1691, 'hic', '', '', '17_5', 69), ('SINO', 1692, 'sinat', '', '', '17_6', 2), ('TVM', 1693, 'tum', '', '', '17_6', 12), ('ENIM/2', 1694, 'enim', '', '', '17_6', 10), ('TRIBVNVS', 1695, 'tribunus', '', '', '17_6', 5), ('INTERCEDO/1', 1696, 'intercedere', '', '', '17_6', 4), ('POSSVM/1', 1697, 'poterit', '', '', '17_6', 40), ('NVNC', 1698, 'nunc', '', '', '17_6', 12), ('NON', 1699, 'non', '', '', '17_6', 106), ('POSSVM/1', 1700, 'potest', '', '', '17_7', 40), ('ITAQVE', 1701, 'itaque', '', '', '17_7', 8), ('EGO', 1702, 'ego', '', '', '17_7', 88), ('IDEM', 1703, 'idem', '', '', '17_7', 27), ('QVI/1', 1704, 'qui', '', '', '17_7', 172), ('NVNC', 1705, 'nunc', '', '', '17_7', 12), ('CONSVL', 1706, 'consulibus', '', '', '17_7', 15), ('IS', 1707, 'iis', '', '', '17_7', 77), ('QVI/1', 1708, 'qui', '', '', '17_7', 172), ('DESIGNO', 1709, 'designati <erunt>', '', '', '17_8', 3), ('SVM/1', 1710, '<designati> erunt', '', '', '17_8', 200), ('SYRIA/N', 1711, 'Syriam', '', '', '17_8', 10), ('MACEDONIA/N', 1712, 'Macedoniam', '', '', '17_8', 8), ('QVE', 1713, 'que', '', '', '17_8', 36), ('DECERNO', 1714, 'decerno', '', '', '17_8', 23), ('DECERNO', 1715, 'decernam', '', '', '17_9', 23), ('IDEM', 1716, 'easdem', '', '', '17_9', 27), ('PRAETORIVS/2', 1717, 'praetorias', '', '', '17_9', 2), ('VT/4', 1718, 'ut', '', '', '17_9', 46), ('ET/2', 1719, 'et', '', '', '17_9', 110), ('PRAETOR', 1720, 'praetores', '', '', '17_9', 1), ('ANNVVS', 1721, 'annuas', '', '', '17_9', 1), ('PROVINCIA', 1722, 'prouincias', '', '', '17_9', 31), ('HABEO', 1723, 'habeant', '', '', '17_10', 19), ('ET/2', 1724, 'et', '', '', '17_10', 110), ('IS', 1725, 'eos', '', '', '17_10', 77), ('QVAMPRIMVM', 1726, 'quam primum', '', '', '17_10', 1), ('VIDEO', 1727, 'uideamus', '', '', '17_10', 24), ('QVI/1', 1728, 'quos', '', '', '17_10', 172), ('ANIMVS', 1729, 'animo', '', '', '17_10', 12), ('AEQVVS', 1730, 'aequo', '', '', '17_11', 1), ('VIDEO', 1731, 'uidere', '', '', '17_11', 24), ('NON', 1732, 'non', '', '', '17_11', 106), ('POSSVM/1', 1733, 'possumus', '', '', '17_11', 40), ('SED', 1734, 'sed', '', '', '17_11', 42), ('EGO', 1735, 'mihi', '', '', '17_11', 88), ('CREDO', 1736, 'credite', '', '', '17_11', 6), ('NVMQVAM', 1737, 'numquam', '', '', '17_12', 6), ('SVCCEDO/1', 1738, 'succedetur', '', '', '17_12', 4), ('ILLE', 1739, 'illis', '', '', '17_12', 96), ('NISI', 1740, 'nisi', '', '', '17_12', 7), ('CVM/3', 1741, 'cum', '', '', '17_12', 29), ('IS', 1742, 'ea', '', '', '17_12', 77), ('LEX', 1743, 'lege', '', '', '17_12', 21), ('REFERO', 1744, 'referetur', '', '', '17_12', 4), ('QVI/1', 1745, 'qua', '', '', '17_12', 172), ('INTERCEDO/1', 1746, 'intercedi', '', '', '17_13', 4), ('DE', 1747, 'de', '', '', '17_13', 34), ('PROVINCIA', 1748, 'prouinciis', '', '', '17_13', 31), ('NON', 1749, 'non', '', '', '17_13', 106), ('LICET/1', 1750, 'licebit', '', '', '17_13', 8), ('ITAQVE', 1751, 'itaque', '', '', '17_13', 8), ('HIC/1', 1752, 'hoc', '', '', '17_13', 69), ('TEMPVS/1', 1753, 'tempore', '', '', '17_13', 13), ('AMITTO', 1754, 'amisso', '', '', '17_14', 3), ('ANNVS', 1755, 'annus', '', '', '17_14', 2), ('SVM/1', 1756, 'est', '', '', '17_14', 200), ('INTEGER', 1757, 'integer', '', '', '17_14', 1), ('VOS', 1758, 'uobis', '', '', '17_14', 31), ('EXSPECTO', 1759, 'exspectandus', '', '', '17_14', 4), ('QVI/1', 1760, 'quo', '', '', '17_14', 172), ('INTERICIO', 1761, 'interiecto', '', '', '17_14', 1), ('CIVIS', 1762, 'ciuium', '', '', '17_15', 7), ('CALAMITAS', 1763, 'calamitas', '', '', '17_15', 1), ('SOCIVS/1', 1764, 'sociorum', '', '', '17_15', 6), ('AERVMNA', 1765, 'aerumna', '', '', '17_15', 1), ('SCELERATVS', 1766, 'sceleratissimorum', '', '', '17_15', 3), ('HOMO', 1767, 'hominum', '', '', '17_16', 30), ('IMPVNITAS', 1768, 'impunitas', '', '', '17_16', 1), ('PROPAGO/2', 1769, 'propagatur', '', '', '17_16', 1), ('QVOD/1', 1770, 'quod', '', '', '18_1', 20), ('SI/2', 1771, 'si', '', '', '18_1', 62), ('SVM/1', 1772, 'essent', '', '', '18_1', 200), ('ILLE', 1773, 'illi', '', '', '18_1', 96), ('BONVS', 1774, 'optimi', '', '', '18_1', 7), ('VIR', 1775, 'uiri', '', '', '18_1', 14), ('TAMEN', 1776, 'tamen', '', '', '18_1', 16), ('EGO', 1777, 'ego', '', '', '18_1', 88), ('MEVS', 1778, 'mea', '', '', '18_1', 36), ('SENTENTIA', 1779, 'sententia', '', '', '18_1', 17), ('GAIVS/N', 1780, 'C.', '', '', '18_2', 19), ('CAESAR/N', 1781, 'Caesari', '', '', '18_2', 25), ('SVCCEDO/1', 1782, 'succedendum', '', '', '18_2', 4), ('NONDVM', 1783, 'nondum', '', '', '18_2', 5), ('PVTO', 1784, 'putarem', '', '', '18_2', 15), ('QVI/1', 1785, 'qua', '', '', '18_2', 172), ('DE', 1786, 'de', '', '', '18_2', 34), ('RES', 1787, 're', '', '', '18_2', 18), ('DICO/2', 1788, 'dicam', '', '', '18_3', 23), ('PATER', 1789, 'patres', '', '', '18_3', 17), ('CONSCRIBO', 1790, 'conscripti', '', '', '18_3', 15), ('QVI/1', 1791, 'quae', '', '', '18_3', 172), ('SENTIO', 1792, 'sentio', '', '', '18_3', 10), ('ATQVE/1', 1793, 'atque', '', '', '18_3', 36), ('ILLE', 1794, 'illam', '', '', '18_3', 96), ('INTERPELLATIO', 1795, 'interpellationem', '', '', '18_4', 1), ('MEVS', 1796, 'mei', '', '', '18_4', 36), ('FAMILIARIS/2', 1797, 'familiarissimi', '', '', '18_4', 1), ('QVI/1', 1798, 'qua', '', '', '18_4', 172), ('PAVLO', 1799, 'paulo', '', '', '18_4', 4), ('ANTE/2', 1800, 'ante', '', '', '18_4', 7), ('INTERRVMPO', 1801, 'interrupta <est>', '', '', '18_4', 1), ('SVM/1', 1802, '<interrupta> est', '', '', '18_4', 200), ('ORATIO', 1803, 'oratio', '', '', '18_5', 1), ('MEVS', 1804, 'mea', '', '', '18_5', 36), ('NON', 1805, 'non', '', '', '18_5', 106), ('PERTIMESCO', 1806, 'pertimescam', '', '', '18_5', 3), ('NEGO', 1807, 'negat', '', '', '18_5', 4), ('EGO', 1808, 'me', '', '', '18_5', 88), ('VIR', 1809, 'uir', '', '', '18_5', 14), ('BONVS', 1810, 'optimus', '', '', '18_5', 7), ('INIMICVS/2', 1811, 'inimiciorem', '', '', '18_6', 7), ('GABINIVS/N', 1812, 'Gabinio', '', '', '18_6', 9), ('DEBEO', 1813, 'debere', '', '', '18_6', 14), ('SVM/1', 1814, 'esse', '', '', '18_6', 200), ('QVAM/1', 1815, 'quam', '', '', '18_6', 19), ('CAESAR/N', 1816, 'Caesari', '', '', '18_6', 25), ('OMNIS', 1817, 'omnem', '', '', '18_6', 36), ('ILLE', 1818, 'illam', '', '', '18_6', 96), ('TEMPESTAS', 1819, 'tempestatem', '', '', '18_7', 2), ('QVI/1', 1820, 'cui', '', '', '18_7', 172), ('CEDO/1', 1821, 'cesserim', '', '', '18_7', 1), ('CAESAR/N', 1822, 'Caesare', '', '', '18_7', 25), ('IMPVLSOR', 1823, 'impulsore', '', '', '18_7', 1), ('ATQVE/1', 1824, 'atque', '', '', '18_7', 36), ('ADIVTOR/1', 1825, 'adiutore', '', '', '18_7', 1), ('SVM/1', 1826, 'esse <excitatam>', '', '', '18_8', 200), ('EXCITO/1', 1827, '<esse> excitatam', '', '', '18_8', 2), ('QVI/1', 1828, 'cui', '', '', '18_8', 172), ('SI/2', 1829, 'si', '', '', '18_8', 62), ('PRIMVM', 1830, 'primum', '', '', '18_8', 5), ('SIC', 1831, 'sic', '', '', '18_8', 7), ('RESPONDEO', 1832, 'respondeam', '', '', '18_8', 2), ('EGO', 1833, 'me', '', '', '18_8', 88), ('COMMVNIS', 1834, 'communis', '', '', '18_9', 6), ('VTILITAS', 1835, 'utilitatis', '', '', '18_9', 6), ('HABEO', 1836, 'habere', '', '', '18_9', 19), ('RATIO', 1837, 'rationem', '', '', '18_9', 11), ('NON', 1838, 'non', '', '', '18_9', 106), ('DOLOR', 1839, 'doloris', '', '', '18_9', 8), ('MEVS', 1840, 'mei', '', '', '18_9', 36), ('POSSVM/1', 1841, 'possim', '', '', '18_9', 40), ('NE/2', 1842, 'ne', '', '', '18_9', 2), ('PROBO', 1843, 'probare', '', '', '18_10', 5), ('CVM/3', 1844, 'cum', '', '', '18_10', 29), ('IS', 1845, 'id', '', '', '18_10', 77), ('EGO', 1846, 'me', '', '', '18_10', 88), ('FACIO', 1847, 'facere', '', '', '18_10', 16), ('DICO/2', 1848, 'dicam', '', '', '18_10', 23), ('QVI/1', 1849, 'quod', '', '', '18_10', 172), ('EXEMPLVM', 1850, 'exemplo', '', '', '18_10', 6), ('FORTIS', 1851, 'fortissimorum', '', '', '18_11', 7), ('ET/2', 1852, 'et', '', '', '18_11', 110), ('CLARVS', 1853, 'clarissimorum', '', '', '18_11', 6), ('CIVIS', 1854, 'ciuium', '', '', '18_11', 7), ('FACIO', 1855, 'facere', '', '', '18_11', 16), ('POSSVM/1', 1856, 'possim', '', '', '18_11', 40), ('AN', 1857, 'an', '', '', '18_11', 11), ('TIBERIVS/N', 1858, 'Ti.', '', '', '18_11', 1), ('GRACCHVS/N', 1859, 'Gracchus', '', '', '18_12', 1), ('PATER', 1860, 'patrem', '', '', '18_12', 17), ('DICO/2', 1861, 'dico', '', '', '18_12', 23), ('QVI/1', 1862, 'cuius', '', '', '18_12', 172), ('VTINAM', 1863, 'utinam', '', '', '18_12', 2), ('FILIVS', 1864, 'filii', '', '', '18_12', 2), ('NE/4', 1865, 'ne', '', '', '18_12', 14), ('DEGENERO', 1866, 'degenerassent', '', '', '18_12', 1), ('AB', 1867, 'a', '', '', '18_13', 41), ('GRAVITAS', 1868, 'grauitate', '', '', '18_13', 3), ('PATRIVS', 1869, 'patria', '', '', '18_13', 1), ('TANTVS', 1870, 'tantam', '', '', '18_13', 3), ('LAVS', 1871, 'laudem', '', '', '18_13', 4), ('SVM/1', 1872, 'est <adeptus>', '', '', '18_13', 200), ('ADIPISCOR', 1873, '<est> adeptus', '', '', '18_13', 3), ('QVOD/1', 1874, 'quod', '', '', '18_13', 20), ('TRIBVNVS', 1875, 'tribunus', '', '', '18_13', 5), ('PLEBS', 1876, 'plebis', '', '', '18_14', 5), ('SOLVS', 1877, 'solus', '', '', '18_14', 2), ('EX', 1878, 'ex', '', '', '18_14', 16), ('TOTVS', 1879, 'toto', '', '', '18_14', 8), ('ILLE', 1880, 'illo', '', '', '18_14', 96), ('COLLEGIVM', 1881, 'conlegio', '', '', '18_14', 1), ('LVCIVS/N', 1882, 'L.', '', '', '18_14', 5), ('SCIPIO/N', 1883, 'Scipioni', '', '', '18_14', 2), ('AVXILIVM', 1884, 'auxilio', '', '', '18_14', 2), ('SVM/1', 1885, 'fuit', '', '', '18_14', 200), ('INIMICVS/2', 1886, 'inimicissimus', '', '', '18_15', 7), ('ET/2', 1887, 'et', '', '', '18_15', 110), ('IPSE', 1888, 'ipsius', '', '', '18_15', 33), ('ET/2', 1889, 'et', '', '', '18_15', 110), ('FRATER', 1890, 'fratris', '', '', '18_15', 2), ('IS', 1891, 'eius', '', '', '18_15', 77), ('AFRICANVS/N', 1892, 'Africani', '', '', '18_15', 1), ('IVRO', 1893, 'iurauit', '', '', '18_15', 1), ('QVE', 1894, 'que', '', '', '18_15', 36), ('IN', 1895, 'in', '', '', '18_15', 99), ('CONTIO', 1896, 'contione', '', '', '18_16', 2), ('SVI/1', 1897, 'se', '', '', '18_16', 26), ('IN', 1898, 'in', '', '', '18_16', 99), ('GRATIA', 1899, 'gratiam', '', '', '18_16', 9), ('NON', 1900, 'non', '', '', '18_16', 106), ('REDEO/1', 1901, 'redisse', '', '', '18_16', 6), ('SED', 1902, 'sed', '', '', '18_16', 42), ('ALIENVS/2', 1903, 'alienum', '', '', '18_16', 5), ('SVI/1', 1904, 'sibi', '', '', '18_16', 26), ('VIDEO', 1905, 'uideri', '', '', '18_16', 24), ('DIGNITAS', 1906, 'dignitate', '', '', '18_17', 13), ('IMPERIVM', 1907, 'imperi', '', '', '18_17', 18), ('QVO/2', 1908, 'quo', '', '', '18_17', 5), ('DVX', 1909, 'duces', '', '', '18_17', 1), ('SVM/1', 1910, 'essent <ducti>', '', '', '18_17', 200), ('HOSTIS', 1911, 'hostium', '', '', '18_17', 8), ('SCIPIO/N', 1912, 'Scipione', '', '', '18_17', 2), ('TRIVMPHO', 1913, 'triumphante', '', '', '18_18', 3), ('DVCO', 1914, '<essent> ducti', '', '', '18_18', 4), ('EODEM', 1915, 'eodem', '', '', '18_18', 1), ('IPSE', 1916, 'ipsum', '', '', '18_18', 33), ('DVCO', 1917, 'duci', '', '', '18_18', 4), ('QVI/1', 1918, 'qui', '', '', '18_18', 172), ('TRIVMPHO', 1919, 'triumphasset', '', '', '18_18', 3), ('QVIS/1', 1920, 'quis', '', '', '19_1', 31), ('PLENVS', 1921, 'plenior', '', '', '19_2', 1), ('INIMICVS/1', 1922, 'inimicorum', '', '', '19_2', 12), ('SVM/1', 1923, 'fuit', '', '', '19_2', 200), ('GAIVS/N', 1924, 'C.', '', '', '19_2', 19), ('MARIVS/N', 1925, 'Mario', '', '', '19_2', 3), ('LVCIVS/N', 1926, 'L.', '', '', '19_2', 5), ('CRASSVS/N', 1927, 'Crassus', '', '', '19_2', 1), ('MARCVS/N', 1928, 'M.', '', '', '19_2', 4), ('SCAVRVS/N', 1929, 'Scaurus', '', '', '19_2', 1), ('ALIENVS/2', 1930, 'alieni', '', '', '19_3', 5), ('INIMICVS/1', 1931, 'inimici', '', '', '19_3', 12), ('OMNIS', 1932, 'omnes', '', '', '19_3', 36), ('METELLVS/N', 1933, 'Metelli', '', '', '19_3', 2), ('AT/2', 1934, 'at', '', '', '19_3', 5), ('IS', 1935, 'ii', '', '', '19_3', 77), ('NON', 1936, 'non', '', '', '19_3', 106), ('MODO/1', 1937, 'modo', '', '', '19_3', 4), ('ILLE', 1938, 'illum', '', '', '19_3', 96), ('INIMICVS/1', 1939, 'inimicum', '', '', '19_4', 12), ('EX', 1940, 'ex', '', '', '19_4', 16), ('GALLIA/N', 1941, 'Gallia', '', '', '19_4', 12), ('SENTENTIA', 1942, 'sententiis', '', '', '19_4', 17), ('SVVS', 1943, 'suis', '', '', '19_4', 22), ('NON', 1944, 'non', '', '', '19_4', 106), ('DETRAHO', 1945, 'detrahebant', '', '', '19_4', 2), ('SED', 1946, 'sed', '', '', '19_4', 42), ('IS', 1947, 'ei', '', '', '19_4', 77), ('PROPTER/2', 1948, 'propter', '', '', '19_4', 10), ('RATIO', 1949, 'rationem', '', '', '19_5', 11), ('GALLICVS/A', 1950, 'Gallici', '', '', '19_5', 5), ('BELLVM', 1951, 'belli', '', '', '19_5', 23), ('PROVINCIA', 1952, 'prouinciam', '', '', '19_5', 31), ('EXTRA/2', 1953, 'extra', '', '', '19_5', 1), ('ORDO', 1954, 'ordinem', '', '', '19_5', 16), ('DECERNO', 1955, 'decernebant', '', '', '19_5', 23), ('BELLVM', 1956, 'bellum', '', '', '19_6', 23), ('IN', 1957, 'in', '', '', '19_6', 99), ('GALLIA/N', 1958, 'Gallia', '', '', '19_6', 12), ('MAGNVS', 1959, 'maximum', '', '', '19_6', 17), ('GERO', 1960, 'gestum <est>', '', '', '19_6', 10), ('SVM/1', 1961, '<gestum> est', '', '', '19_6', 200), ('DOMO', 1962, 'domitae <sunt>', '', '', '19_6', 6), ('SVM/1', 1963, '<domitae> sunt', '', '', '19_6', 200), ('AB', 1964, 'a', '', '', '19_6', 41), ('CAESAR/N', 1965, 'Caesare', '', '', '19_7', 25), ('MAGNVS', 1966, 'maximae', '', '', '19_7', 17), ('NATIO/1', 1967, 'nationes', '', '', '19_7', 9), ('SED', 1968, 'sed', '', '', '19_7', 42), ('NONDVM', 1969, 'nondum', '', '', '19_7', 5), ('LEX', 1970, 'legibus', '', '', '19_7', 21), ('NONDVM', 1971, 'nondum', '', '', '19_7', 5), ('IVS/1', 1972, 'iure', '', '', '19_8', 9), ('CERTVS', 1973, 'certo', '', '', '19_8', 3), ('NONDVM', 1974, 'nondum', '', '', '19_8', 5), ('SATIS/2', 1975, 'satis', '', '', '19_8', 2), ('FIRMVS', 1976, 'firma', '', '', '19_8', 2), ('PAX', 1977, 'pace', '', '', '19_8', 7), ('DEVINCIO', 1978, 'deuinctae <sunt>', '', '', '19_8', 1), ('BELLVM', 1979, 'bellum', '', '', '19_8', 23), ('AFFICIO', 1980, 'adfectum (esse)', '', '', '19_9', 3), ('VIDEO', 1981, 'uidemus', '', '', '19_9', 24), ('ET/2', 1982, 'et', '', '', '19_9', 110), ('VERE', 1983, 'uere', '', '', '19_9', 1), ('VT/4', 1984, 'ut', '', '', '19_9', 46), ('DICO/2', 1985, 'dicam', '', '', '19_9', 23), ('PAENE', 1986, 'paene', '', '', '19_9', 4), ('CONFICIO', 1987, 'confectum (esse)', '', '', '19_9', 7), ('SED', 1988, 'sed', '', '', '19_9', 42), ('ITA', 1989, 'ita', '', '', '19_9', 14), ('VT/4', 1990, 'ut', '', '', '19_10', 46), ('SI/2', 1991, 'si', '', '', '19_10', 62), ('IDEM', 1992, 'idem', '', '', '19_10', 27), ('EXTREMVS', 1993, 'extrema', '', '', '19_10', 3), ('PERSEQVOR', 1994, 'persequitur', '', '', '19_10', 1), ('QVI/1', 1995, 'qui', '', '', '19_10', 172), ('INCHOO', 1996, 'inchoauit', '', '', '19_10', 1), ('IAM', 1997, 'iam', '', '', '19_10', 14), ('OMNIS', 1998, 'omnia', '', '', '19_10', 36), ('PERFICIO', 1999, 'perfecta (esse)', '', '', '19_11', 4), ('VIDEO', 2000, 'uideamus', '', '', '19_11', 24), ('SI/2', 2001, 'si', '', '', '19_11', 62), ('SVCCEDO/1', 2002, 'succeditur', '', '', '19_11', 4), ('PERICVLVM', 2003, 'periculum', '', '', '19_11', 6), ('SVM/1', 2004, 'sit', '', '', '19_11', 200), ('NE/4', 2005, 'ne', '', '', '19_11', 14), ('INSTAVRO', 2006, 'instauratas (esse)', '', '', '19_11', 1), ('MAGNVS', 2007, 'maximi', '', '', '19_12', 17), ('BELLVM', 2008, 'belli', '', '', '19_12', 23), ('RELIQVIAE', 2009, 'reliquias', '', '', '19_12', 1), ('AC/1', 2010, 'ac', '', '', '19_12', 26), ('RENOVO', 2011, 'renouatas (esse)', '', '', '19_12', 2), ('AVDIO', 2012, 'audiamus', '', '', '19_12', 4), ('ERGO/2', 2013, 'ergo', '', '', '19_12', 4), ('EGO', 2014, 'ego', '', '', '19_12', 88), ('SENATOR', 2015, 'senator', '', '', '19_13', 5), ('INIMICVS/1', 2016, 'inimicus', '', '', '19_13', 12), ('SI/2', 2017, 'si', '', '', '19_13', 62), ('ITA', 2018, 'ita', '', '', '19_13', 14), ('VOLO/3', 2019, 'uultis', '', '', '19_13', 17), ('HOMO', 2020, 'homini', '', '', '19_13', 30), ('AMICVS/2', 2021, 'amicus', '', '', '19_13', 8), ('SVM/1', 2022, 'esse', '', '', '19_13', 200), ('SICVT/1', 2023, 'sicut', '', '', '19_13', 1), ('SEMPER', 2024, 'semper', '', '', '19_14', 7), ('SVM/1', 2025, 'fui', '', '', '19_14', 200), ('RESPVBLICA', 2026, 'rei publicae', '', '', '19_14', 44), ('DEBEO', 2027, 'debeo', '', '', '19_14', 14), ('QVIS/1', 2028, 'quid', '', '', '20_1', 31), ('SI/2', 2029, 'si', '', '', '20_1', 62), ('IPSE', 2030, 'ipsas', '', '', '20_1', 33), ('INIMICITIA', 2031, 'inimicitias', '', '', '20_1', 8), ('DEPONO', 2032, 'depono', '', '', '20_2', 2), ('RESPVBLICA', 2033, 'rei publicae', '', '', '20_2', 44), ('CAVSA', 2034, 'causa', '', '', '20_2', 9), ('QVIS/1', 2035, 'quis', '', '', '20_2', 31), ('EGO', 2036, 'me', '', '', '20_2', 88), ('TANDEM', 2037, 'tandem', '', '', '20_2', 1), ('IVRE', 2038, 'iure', '', '', '20_2', 2), ('REPREHENDO', 2039, 'reprehendet', '', '', '20_2', 5), ('PRAESERTIM', 2040, 'praesertim', '', '', '20_3', 6), ('CVM/3', 2041, 'cum', '', '', '20_3', 29), ('EGO', 2042, 'ego', '', '', '20_3', 88), ('OMNIS', 2043, 'omnium', '', '', '20_3', 36), ('MEVS', 2044, 'meorum', '', '', '20_3', 36), ('CONSILIVM', 2045, 'consiliorum', '', '', '20_3', 7), ('ATQVE/1', 2046, 'atque', '', '', '20_3', 36), ('FACTVM', 2047, 'factorum', '', '', '20_4', 2), ('EXEMPLVM', 2048, 'exempla', '', '', '20_4', 6), ('SEMPER', 2049, 'semper', '', '', '20_4', 7), ('EX', 2050, 'ex', '', '', '20_4', 16), ('SVPERVS', 2051, 'summorum', '', '', '20_4', 13), ('HOMO', 2052, 'hominum', '', '', '20_4', 30), ('FACTVM', 2053, 'factis', '', '', '20_4', 2), ('EGO', 2054, 'mihi', '', '', '20_5', 88), ('CENSEO', 2055, 'censuerim', '', '', '20_5', 1), ('PETO', 2056, 'petenda', '', '', '20_5', 3), ('AN', 2057, 'an', '', '', '20_5', 11), ('VERO/3', 2058, 'uero', '', '', '20_5', 10), ('MARCVS/N', 2059, 'M.', '', '', '20_5', 4), ('ILLE', 2060, 'ille', '', '', '20_5', 96), ('LEPIDVS/N', 2061, 'Lepidus', '', '', '20_5', 1), ('QVI/1', 2062, 'qui', '', '', '20_5', 172), ('BIS', 2063, 'bis', '', '', '20_5', 1), ('CONSVL', 2064, 'consul', '', '', '20_6', 15), ('ET/2', 2065, 'et', '', '', '20_6', 110), ('PONTIFEX', 2066, 'pontifex', '', '', '20_6', 1), ('MAGNVS', 2067, 'maximus', '', '', '20_6', 17), ('SVM/1', 2068, 'fuit', '', '', '20_6', 200), ('NON', 2069, 'non', '', '', '20_6', 106), ('SOLVM/2', 2070, 'solum', '', '', '20_6', 14), ('MEMORIA', 2071, 'memoriae', '', '', '20_6', 4), ('TESTIMONIVM', 2072, 'testimonio', '', '', '20_7', 1), ('SED', 2073, 'sed', '', '', '20_7', 42), ('ETIAM', 2074, 'etiam', '', '', '20_7', 28), ('ANNALIS/1', 2075, 'annalium', '', '', '20_7', 1), ('LITTERA', 2076, 'litteris', '', '', '20_7', 8), ('ET/2', 2077, 'et', '', '', '20_7', 110), ('SVPERVS', 2078, 'summi', '', '', '20_7', 13), ('POETA', 2079, 'poetae', '', '', '20_7', 1), ('VOX', 2080, 'uoce', '', '', '20_7', 2), ('LAVDO', 2081, 'laudatus <est>', '', '', '20_8', 2), ('SVM/1', 2082, '<laudatus> est', '', '', '20_8', 200), ('QVOD/1', 2083, 'quod', '', '', '20_8', 20), ('CVM/2', 2084, 'cum', '', '', '20_8', 33), ('MARCVS/N', 2085, 'M.', '', '', '20_8', 4), ('FVLVIVS/N', 2086, 'Fuluio', '', '', '20_8', 1), ('COLLEGA', 2087, 'conlega', '', '', '20_8', 2), ('QVI/1', 2088, 'quo', '', '', '20_8', 172), ('DIES', 2089, 'die', '', '', '20_8', 11), ('CENSOR', 2090, 'censor', '', '', '20_8', 1), ('SVM/1', 2091, 'est <factus>', '', '', '20_9', 200), ('FACIO', 2092, '<est> factus', '', '', '20_9', 16), ('HOMO', 2093, 'homine', '', '', '20_9', 30), ('INIMICVS/2', 2094, 'inimicissimo', '', '', '20_9', 7), ('IN', 2095, 'in', '', '', '20_9', 99), ('CAMPVS/1', 2096, 'campo', '', '', '20_9', 1), ('STATIM', 2097, 'statim', '', '', '20_9', 2), ('REDEO/1', 2098, 'rediit', '', '', '20_9', 6), ('IN', 2099, 'in', '', '', '20_9', 99), ('GRATIA', 2100, 'gratiam', '', '', '20_10', 9), ('VT/4', 2101, 'ut', '', '', '20_10', 46), ('COMMVNIS', 2102, 'commune', '', '', '20_10', 6), ('OFFICIVM', 2103, 'officium', '', '', '20_10', 3), ('CENSVRA', 2104, 'censurae', '', '', '20_10', 1), ('COMMVNIS', 2105, 'communi', '', '', '20_10', 6), ('ANIMVS', 2106, 'animo', '', '', '20_10', 12), ('AC/1', 2107, 'ac', '', '', '20_10', 26), ('VOLVNTAS', 2108, 'uoluntate', '', '', '20_11', 5), ('DEFENDO', 2109, 'defenderent', '', '', '20_11', 5), ('ATQVE/1', 2110, 'atque', '', '', '21_1', 36), ('VT/4', 2111, 'ut', '', '', '21_1', 46), ('VETVS', 2112, 'uetera', '', '', '21_1', 1), ('QVI/1', 2113, 'quae', '', '', '21_1', 172), ('SVM/1', 2114, 'sunt', '', '', '21_1', 200), ('INNVMERABILIS', 2115, 'innumerabilia', '', '', '21_2', 1), ('MITTO', 2116, 'mittam', '', '', '21_2', 6), ('TVVS', 2117, 'tuus', '', '', '21_2', 2), ('PATER', 2118, 'pater', '', '', '21_2', 17), ('PHILIPPVS/N', 2119, 'Philippe', '', '', '21_2', 1), ('NONNE', 2120, 'nonne', '', '', '21_2', 3), ('VNVS', 2121, 'uno', '', '', '21_2', 13), ('TEMPVS/1', 2122, 'tempore', '', '', '21_2', 13), ('CVM/2', 2123, 'cum', '', '', '21_3', 33), ('SVVS', 2124, 'suis', '', '', '21_3', 22), ('INIMICVS/2', 2125, 'inimicissimis', '', '', '21_3', 7), ('IN', 2126, 'in', '', '', '21_3', 99), ('GRATIA', 2127, 'gratiam', '', '', '21_3', 9), ('REDEO/1', 2128, 'rediit', '', '', '21_3', 6), ('QVI/1', 2129, 'quibus', '', '', '21_3', 172), ('IS', 2130, 'eum', '', '', '21_3', 77), ('OMNIS', 2131, 'omnibus', '', '', '21_4', 36), ('IDEM', 2132, 'eadem', '', '', '21_4', 27), ('RESPVBLICA', 2133, 'res publica', '', '', '21_4', 44), ('RECONCILIO', 2134, 'reconciliauit', '', '', '21_4', 2), ('QVI/1', 2135, 'quae', '', '', '21_4', 172), ('ALIENO', 2136, 'alienarat', '', '', '21_4', 1), ('MVLTVS', 2137, 'multa', '', '', '22_1', 10), ('PRAETEREO/1', 2138, 'praetereo', '', '', '22_2', 2), ('QVOD/1', 2139, 'quod', '', '', '22_2', 20), ('INTVEOR', 2140, 'intueor', '', '', '22_2', 1), ('CORAM/1', 2141, 'coram', '', '', '22_2', 1), ('HIC/1', 2142, 'haec', '', '', '22_2', 69), ('LVMEN', 2143, 'lumina', '', '', '22_2', 1), ('ATQVE/1', 2144, 'atque', '', '', '22_2', 36), ('ORNAMENTVM', 2145, 'ornamenta', '', '', '22_2', 7), ('RESPVBLICA', 2146, 'rei publicae', '', '', '22_3', 44), ('PVBLIVS/N', 2147, 'P.', '', '', '22_3', 4), ('SERVILIVS/N', 2148, 'Seruilium', '', '', '22_3', 4), ('ET/2', 2149, 'et', 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2170, 'uiris', '', '', '22_5', 14), ('FORTIS', 2171, 'fortissimis', '', '', '22_6', 7), ('NON', 2172, 'non', '', '', '22_6', 106), ('SOLVM/2', 2173, 'solum', '', '', '22_6', 14), ('EXSTINGVO', 2174, 'exstinxit', '', '', '22_6', 2), ('RESPVBLICA', 2175, 'rei publicae', '', '', '22_6', 44), ('VTILITAS', 2176, 'utilitas', '', '', '22_6', 6), ('DIGNITAS', 2177, 'dignitas', '', '', '22_6', 13), ('QVE', 2178, 'que', '', '', '22_6', 36), ('IPSE', 2179, 'ipsorum', '', '', '22_7', 33), ('SED', 2180, 'sed', '', '', '22_7', 42), ('ETIAM', 2181, 'etiam', '', '', '22_7', 28), ('AD/2', 2182, 'ad', '', '', '22_7', 35), ('AMICITIA', 2183, 'amicitiam', '', '', '22_7', 4), ('CONSVETVDO', 2184, 'consuetudinem', '', '', '22_7', 2), ('QVE', 2185, 'que', '', '', '22_7', 36), ('TRADVCO', 2186, 'traduxit', '', '', '22_7', 2), ('QVIS/1', 2187, 'quid', '', '', '22_8', 31), ('QVINTVS/N', 2188, 'Q.', '', '', '22_8', 1), ('METELLVS/N', 2189, 'Metellus', '', '', '22_8', 2), ('NEPOS/N', 2190, 'Nepos', '', '', '22_8', 1), ('NONNE', 2191, 'nonne', '', '', '22_8', 3), ('CONSVL', 2192, 'consul', '', '', '22_8', 15), ('IN', 2193, 'in', '', '', '22_8', 99), ('TEMPLVM', 2194, 'templo', '', '', '22_8', 2), ('IVPPITER/N', 2195, 'Iouis', '', '', '22_8', 1), ('BONVS', 2196, 'optimi', '', '', '22_9', 7), ('MAGNVS', 2197, 'maximi', '', '', '22_9', 17), ('PERMOVEO', 2198, 'permotus', '', '', '22_9', 1), ('CVM/3', 2199, 'cum', '', '', '22_9', 29), ('AVCTORITAS', 2200, 'auctoritate', '', '', '22_9', 7), ('VESTER', 2201, 'uestra', '', '', '22_9', 11), ('TVM', 2202, 'tum', '', '', '22_9', 12), ('ILLE', 2203, 'illius', '', '', '22_9', 96), ('PVBLIVS/N', 2204, 'P.', '', '', '22_10', 4), ('SERVILIVS/N', 2205, 'Seruili', '', '', '22_10', 4), ('INCREDIBILIS', 2206, 'incredibili', '', '', '22_10', 2), ('GRAVITAS', 2207, 'grauitate', '', '', '22_10', 3), ('DICO/2', 2208, 'dicendi', '', '', '22_10', 23), ('ABSVM/1', 2209, 'absens', '', '', '22_10', 1), ('EGO', 2210, 'me', '', '', '22_10', 88), ('CVM/2', 2211, 'cum', '', '', '22_10', 33), ('SVPERVS', 2212, 'summo', '', '', '22_10', 13), ('SVVS', 2213, 'suo', '', '', '22_11', 22), ('BENEFICIVM', 2214, 'beneficio', '', '', '22_11', 7), ('REDEO/1', 2215, 'rediit', '', '', '22_11', 6), ('IN', 2216, 'in', '', '', '22_11', 99), ('GRATIA', 2217, 'gratiam', '', '', '22_11', 9), ('AN', 2218, 'an', '', '', '22_11', 11), ('EGO', 2219, 'ego', '', '', '22_11', 88), ('POSSVM/1', 2220, 'possum', '', '', '22_11', 40), ('HIC/1', 2221, 'huic', '', '', '22_11', 69), ('SVM/1', 2222, 'esse', '', '', '22_11', 200), ('INIMICVS/1', 2223, 'inimicus', '', '', '22_12', 12), ('QVI/1', 2224, 'cuius', '', '', '22_12', 172), ('LITTERA', 2225, 'litteris', '', '', '22_12', 8), ('FAMA', 2226, 'fama', '', '', '22_12', 3), ('NVNTIVS/1', 2227, 'nuntiis', '', '', '22_12', 1), ('CELEBRO', 2228, 'celebrantur', '', '', '22_12', 1), ('AVRIS', 2229, 'aures', '', '', '22_12', 1), ('COTIDIE', 2230, 'cotidie', '', '', '22_12', 2), ('MEVS', 2231, 'meae', '', '', '22_13', 36), ('NOVVS', 2232, 'nouis', '', '', '22_13', 4), ('NOMEN', 2233, 'nominibus', '', '', '22_13', 3), ('GENS', 2234, 'gentium', '', '', '22_13', 8), ('NATIO/1', 2235, 'nationum', '', '', '22_13', 9), ('LOCVS', 2236, 'locorum', '', '', '22_13', 5), ('ARDEO', 2237, 'ardeo', '', '', '23_1', 1), ('EGO', 2238, 'mihi', '', '', '23_2', 88), ('CREDO', 2239, 'credite', '', '', '23_2', 6), ('PATER', 2240, 'patres', '', '', '23_2', 17), ('CONSCRIBO', 2241, 'conscripti', '', '', '23_2', 15), ('IS', 2242, 'id', '', '', '23_2', 77), ('QVI/1', 2243, 'quod', '', '', '23_2', 172), ('VOS', 2244, 'uosmet', '', '', '23_2', 31), ('DE', 2245, 'de', '', '', '23_2', 34), ('EGO', 2246, 'me', '', '', '23_2', 88), ('EXISTIMO', 2247, 'existimatis', '', '', '23_3', 3), ('ET/2', 2248, 'et', '', '', '23_3', 110), ('FACIO', 2249, 'facitis', '', '', '23_3', 16), ('IPSE', 2250, 'ipsi', '', '', '23_3', 33), ('INCREDIBILIS', 2251, 'incredibili', '', '', '23_3', 2), ('QVIDAM', 2252, 'quodam', '', '', '23_3', 8), ('AMOR', 2253, 'amore', '', '', '23_3', 2), ('PATRIA', 2254, 'patriae', '', '', '23_3', 7), ('QVI/1', 2255, 'qui', '', '', '23_3', 172), ('EGO', 2256, 'me', '', '', '23_4', 88), ('AMOR', 2257, 'amor', '', '', '23_4', 2), ('ET/2', 2258, 'et', '', '', '23_4', 110), ('SVBVENIO', 2259, 'subuenire', '', '', '23_4', 3), ('OLIM', 2260, 'olim', '', '', '23_4', 1), ('IMPENDEO', 2261, 'impendentibus', '', '', '23_4', 2), ('PERICVLVM', 2262, 'periculis', '', '', '23_4', 6), ('MAGNVS', 2263, 'maximis', '', '', '23_4', 17), ('CVM/2', 2264, 'cum', '', '', '23_5', 33), ('DIMICATIO', 2265, 'dimicatione', '', '', '23_5', 1), ('CAPVT', 2266, 'capitis', '', '', '23_5', 3), ('ET/2', 2267, 'et', '', '', '23_5', 110), ('RVRSVS', 2268, 'rursum', '', '', '23_5', 1), ('CVM/3', 2269, 'cum', '', '', '23_5', 29), ('OMNIS', 2270, 'omnia', '', '', '23_5', 36), ('TELVM', 2271, 'tela', '', '', '23_5', 1), ('VNDIQVE', 2272, 'undique', '', '', '23_5', 1), ('SVM/1', 2273, 'esse <intenta>', '', '', '23_6', 200), ('INTENDO', 2274, '<esse> intenta', '', 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('CAESAR/N', 2296, 'Caesare', '', '', '23_8', 25), ('REDVCO', 2297, 'reducit', '', '', '23_8', 3), ('RECONCILIO', 2298, 'reconciliat', '', '', '23_8', 2), ('RESTITVO', 2299, 'restituit', '', '', '23_9', 2), ('IN', 2300, 'in', '', '', '23_9', 99), ('GRATIA', 2301, 'gratiam', '', '', '23_9', 9), ('QVI/1', 2302, 'quod', '', '', '24_1', 172), ('VOLO/3', 2303, 'uolent', '', '', '24_1', 17), ('DENIQVE', 2304, 'denique', '', '', '24_1', 5), ('HOMO', 2305, 'homines', '', '', '24_1', 30), ('EXISTIMO', 2306, 'existiment', '', '', '24_1', 3), ('NEMO', 2307, 'nemini', '', '', '24_1', 9), ('EGO', 2308, 'ego', '', '', '24_1', 88), ('POSSVM/1', 2309, 'possum', '', '', '24_2', 40), ('SVM/1', 2310, 'esse', '', '', '24_2', 200), ('BENE', 2311, 'bene', '', '', '24_2', 6), ('MEREO', 2312, 'merenti', '', '', '24_2', 1), ('DE', 2313, 'de', '', '', '24_2', 34), ('RESPVBLICA', 2314, 're publica', '', '', '24_2', 44), ('NON', 2315, 'non', '', '', '24_2', 106), ('AMICVS/2', 2316, 'amicus', '', '', '24_2', 8), ('ETENIM', 2317, 'etenim', '', '', '24_2', 1), ('SI/2', 2318, 'si', '', '', '24_3', 62), ('IS', 2319, 'iis', '', '', '24_3', 77), ('QVI/1', 2320, 'qui', '', '', '24_3', 172), ('HIC/1', 2321, 'haec', '', '', '24_3', 69), ('OMNIS', 2322, 'omnia', '', '', '24_3', 36), ('FLAMMA', 2323, 'flamma', '', '', '24_3', 1), ('AC/1', 2324, 'ac', '', '', '24_3', 26), ('FERRVM', 2325, 'ferro', '', '', '24_3', 1), ('DELEO', 2326, 'delere', '', '', '24_3', 1), ('VOLO/3', 2327, 'uoluerunt', '', '', '24_3', 17), ('NON', 2328, 'non', '', '', '24_3', 106), ('INIMICITIA', 2329, 'inimicitias', '', '', '24_4', 8), ('SOLVM/2', 2330, 'solum', '', '', '24_4', 14), ('SED', 2331, 'sed', '', '', '24_4', 42), ('ETIAM', 2332, 'etiam', '', '', '24_4', 28), ('BELLVM', 2333, 'bellum', '', '', '24_4', 23), ('INDICO/2', 2334, 'indixi', '', '', '24_4', 2), ('ATQVE/1', 2335, 'atque', '', '', '24_4', 36), ('INFERO', 2336, 'intuli', '', '', '24_4', 2), ('CVM/3', 2337, 'cum', '', '', '24_4', 29), ('PARTIM', 2338, 'partim', '', '', '24_5', 4), ('EGO', 2339, 'mihi', '', '', '24_5', 88), ('ILLE', 2340, 'illorum', '', '', '24_5', 96), ('FAMILIARIS/1', 2341, 'familiares', '', '', '24_5', 1), ('PARTIM', 2342, 'partim', '', '', '24_5', 4), ('ETIAM', 2343, 'etiam', '', '', '24_5', 28), ('EGO', 2344, 'me', '', '', '24_5', 88), ('DEFENDO', 2345, 'defendente', '', '', '24_5', 5), ('CAPVT', 2346, 'capitis', '', '', '24_6', 3), ('IVDICIVM', 2347, 'iudiciis', '', '', '24_6', 4), ('SVM/1', 2348, 'essent <liberati>', '', '', '24_6', 200), ('LIBERO', 2349, '<essent> liberati', '', '', '24_6', 4), ('CVR/1', 2350, 'cur', '', '', '24_6', 3), ('IDEM', 2351, 'eadem', '', '', '24_6', 27), ('RESPVBLICA', 2352, 'res publica', '', '', '24_6', 44), ('QVI/1', 2353, 'quae', '', '', '24_6', 172), ('EGO', 2354, 'me', '', '', '24_7', 88), ('IN', 2355, 'in', '', '', '24_7', 99), ('AMICVS/2', 2356, 'amicos', '', '', '24_7', 8), ('INFLAMMO', 2357, 'inflammare', '', '', '24_7', 1), ('POSSVM/1', 2358, 'potuit', '', '', '24_7', 40), ('INIMICVS/1', 2359, 'inimicis', '', '', '24_7', 12), ('PLACO', 2360, 'placare', '', '', '24_7', 1), ('NON', 2361, 'non', '', '', '24_7', 106), ('POSSVM/1', 2362, 'possit', '', '', '24_7', 40), ('QVIS/1', 2363, 'quod', '', '', '24_8', 31), ('EGO', 2364, 'mihi', '', '', '24_8', 88), ('ODIVM', 2365, 'odium', '', '', '24_8', 2), ('CVM/2', 2366, 'cum', '', '', '24_8', 33), ('PVBLIVS/N', 2367, 'P.', '', '', '24_8', 4), ('CLODIVS/N', 2368, 'Clodio', '', '', '24_8', 2), ('SVM/1', 2369, 'fuit', '', '', '24_8', 200), ('NISI', 2370, 'nisi', '', '', '24_8', 7), ('QVOD/1', 2371, 'quod', '', '', '24_8', 20), ('PERNICIOSVS', 2372, 'perniciosum', '', '', '24_8', 2), ('PATRIA', 2373, 'patriae', '', '', '24_9', 7), ('CIVIS', 2374, 'ciuem', '', '', '24_9', 7), ('SVM/1', 2375, 'fore', '', '', '24_9', 200), ('PVTO', 2376, 'putabam', '', '', '24_9', 15), ('QVI/1', 2377, 'qui', '', '', '24_9', 172), ('TVRPIS', 2378, 'turpissima', '', '', '24_9', 1), ('LIBIDO', 2379, 'libidine', '', '', '24_9', 4), ('INCENDO', 2380, 'incensus', '', '', '24_9', 2), ('DVO', 2381, 'duas', '', '', '24_10', 6), ('RES', 2382, 'res', '', '', '24_10', 18), ('SANCTVS', 2383, 'sanctissimas', '', '', '24_10', 4), ('RELIGIO', 2384, 'religionem', '', '', '24_10', 2), ('ET/2', 2385, 'et', '', '', '24_10', 110), ('PVDICITIA', 2386, 'pudicitiam', '', '', '24_10', 1), ('VNVS', 2387, 'uno', '', '', '24_10', 13), ('SCELVS', 2388, 'scelere', '', '', '24_10', 10), ('VIOLO', 2389, 'uiolasset', '', '', '24_11', 3), ('NVM', 2390, 'num', '', '', '24_11', 1), ('SVM/1', 2391, 'est', '', '', '24_11', 200), ('IGITVR', 2392, 'igitur', '', '', '24_11', 5), ('DVBIVS', 2393, 'dubium', '', '', '24_11', 1), ('EX', 2394, 'ex', '', '', '24_11', 16), ('IS', 2395, 'iis', '', '', '24_11', 77), ('RES', 2396, 'rebus', '', '', '24_11', 18), ('QVI/1', 2397, 'quas', '', '', '24_11', 172), ('IS', 2398, 'is', '', '', '24_11', 77), ('AGO', 2399, 'egit', '', '', '24_11', 9), ('AGO', 2400, 'agit', '', '', '24_12', 9), ('QVE', 2401, 'que', '', 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2691, 'ergo', '', '', '27_11', 4), ('IN', 2692, 'in', '', '', '27_11', 99), ('ILLE', 2693, 'illa', '', '', '27_11', 96), ('SVPPLICATIO', 2694, 'supplicatione', '', '', '27_11', 9), ('QVI/1', 2695, 'quam', '', '', '27_11', 172), ('EGO', 2696, 'ego', '', '', '27_11', 88), ('DECERNO', 2697, 'decreui', '', '', '27_11', 23), ('RES', 2698, 'res', '', '', '27_11', 18), ('IPSE', 2699, 'ipsa', '', '', '27_11', 33), ('TRIBVO', 2700, 'tributa <est>', '', '', '27_12', 6), ('SVM/1', 2701, '<tributa> est', '', '', '27_12', 200), ('DEVS', 2702, 'dis', '', '', '27_12', 4), ('IMMORTALIS', 2703, 'immortalibus', '', '', '27_12', 3), ('ET/2', 2704, 'et', '', '', '27_12', 110), ('MAIORES', 2705, 'maiorum', '', '', '27_12', 2), ('INSTITVTVM', 2706, 'institutis', '', '', '27_12', 1), ('ET/2', 2707, 'et', '', '', '27_12', 110), ('VTILITAS', 2708, 'utilitati', '', '', '27_12', 6), ('RESPVBLICA', 2709, 'rei publicae', '', '', '27_13', 44), ('SED', 2710, 'sed', '', '', '27_13', 42), ('DIGNITAS', 2711, 'dignitas', '', '', '27_13', 13), ('VERBVM', 2712, 'uerborum', '', '', '27_13', 3), ('HONOR', 2713, 'honos', '', '', '27_13', 10), ('ET/2', 2714, 'et', '', '', '27_13', 110), ('NOVITAS', 2715, 'nouitas', '', '', '27_13', 1), ('ET/2', 2716, 'et', '', '', '27_13', 110), ('NVMERVS', 2717, 'numerus', '', '', '27_14', 4), ('DIES', 2718, 'dierum', '', '', '27_14', 11), ('CAESAR/N', 2719, 'Caesaris', '', '', '27_14', 25), ('IPSE', 2720, 'ipsius', '', '', '27_14', 33), ('LAVS', 2721, 'laudi', '', '', '27_14', 4), ('GLORIA', 2722, 'gloriae', '', '', '27_14', 4), ('QVE', 2723, 'que', '', '', '27_14', 36), ('CONCEDO/1', 2724, 'concessus <est>', '', '', '27_14', 4), ('SVM/1', 2725, '<concessus> est', '', '', '27_14', 200), ('REFERO', 2726, 'relatum <est>', '', '', '28_1', 4), ('SVM/1', 2727, '<relatum> est', '', '', '28_1', 200), ('AD/2', 2728, 'ad', '', '', '28_1', 35), ('NOS', 2729, 'nos', '', '', '28_1', 10), ('NVPER', 2730, 'nuper', '', '', '28_1', 1), ('DE', 2731, 'de', '', '', '28_1', 34), ('STIPENDIVM', 2732, 'stipendio', '', '', '28_1', 1), ('EXERCITVS/1', 2733, 'exercitus', '', '', '28_1', 8), ('NON', 2734, 'non', '', '', '28_1', 106), ('DECERNO', 2735, 'decreui', '', '', '28_2', 23), ('SOLVM/2', 2736, 'solum', '', '', '28_2', 14), ('SED', 2737, 'sed', '', '', '28_2', 42), ('ETIAM', 2738, 'etiam', '', '', '28_2', 28), ('VT/4', 2739, 'ut', '', '', '28_2', 46), ('VOS', 2740, 'uos', '', '', '28_2', 31), ('DECERNO', 2741, 'decerneretis', '', '', '28_2', 23), ('LABORO', 2742, 'laboraui', '', '', '28_2', 1), ('MVLTVS', 2743, 'multa', '', '', '28_2', 10), ('DISSENTIO', 2744, 'dissentientibus', '', '', '28_3', 4), ('RESPONDEO', 2745, 'respondi', '', '', '28_3', 2), ('SCRIBO', 2746, 'scribendo', '', '', '28_3', 1), ('ASSVM/1', 2747, 'adfui', '', '', '28_3', 1), ('TVM', 2748, 'tum', '', '', '28_3', 12), ('QVOQVE', 2749, 'quoque', '', '', '28_3', 4), ('HOMO', 2750, 'homini', '', '', '28_4', 30), ('MVLTVS', 2751, 'plus', '', '', '28_4', 10), ('TRIBVO', 2752, 'tribui', '', '', '28_4', 6), ('QVAM/1', 2753, 'quam', '', '', '28_4', 19), ('NESCIOQVIS', 2754, 'nescio cui', '', '', '28_4', 1), ('NECESSITAS', 2755, 'necessitati', '', '', '28_4', 2), ('ILLE', 2756, 'illum', '', '', '28_4', 96), ('ENIM/2', 2757, 'enim', '', '', '28_4', 10), ('ARBITROR', 2758, 'arbitrabar', '', '', '28_5', 4), ('ETIAM', 2759, 'etiam', '', '', '28_5', 28), ('SINE', 2760, 'sine', '', '', '28_5', 7), ('HIC/1', 2761, 'hoc', '', '', '28_5', 69), ('SVBSIDIVM', 2762, 'subsidio', '', '', '28_5', 2), ('PECVNIA', 2763, 'pecuniae', '', '', '28_5', 5), ('RETINEO', 2764, 'retinere', '', '', '28_5', 6), ('EXERCITVS/1', 2765, 'exercitum', '', '', '28_5', 8), ('PRAEDA', 2766, 'praeda', '', '', '28_6', 1), ('ANTE/2', 2767, 'ante', '', '', '28_6', 7), ('PARIO/2', 2768, 'parta', '', '', '28_6', 3), ('ET/2', 2769, 'et', '', '', '28_6', 110), ('BELLVM', 2770, 'bellum', '', '', '28_6', 23), ('CONFICIO', 2771, 'conficere', '', '', '28_6', 7), ('POSSVM/1', 2772, 'posse', '', '', '28_6', 40), ('SED', 2773, 'sed', '', '', '28_6', 42), ('DECVS', 2774, 'decus', '', '', '28_6', 1), ('ILLE', 2775, 'illud', '', '', '28_6', 96), ('ET/2', 2776, 'et', '', '', '28_7', 110), ('ORNAMENTVM', 2777, 'ornamentum', '', '', '28_7', 7), ('TRIVMPHVS', 2778, 'triumphi', '', '', '28_7', 3), ('MINVO', 2779, 'minuendum', '', '', '28_7', 2), ('NOSTER', 2780, 'nostra', '', '', '28_7', 17), ('PARSIMONIA', 2781, 'parsimonia', '', '', '28_7', 2), ('NON', 2782, 'non', '', '', '28_7', 106), ('PVTO', 2783, 'putaui', '', '', '28_8', 15), ('AGO', 2784, 'actum <est>', '', '', '28_8', 9), ('SVM/1', 2785, '<actum> est', '', '', '28_8', 200), ('DE', 2786, 'de', '', '', '28_8', 34), ('DECEM', 2787, 'decem', '', '', '28_8', 3), ('LEGATVS', 2788, 'legatis', '', '', '28_8', 4), ('QVI/1', 2789, 'quos', '', '', '28_8', 172), ('ALIVS', 2790, 'alii', '', '', '28_8', 15), ('OMNINO', 2791, 'omnino', '', '', '28_8', 4), ('NON', 2792, 'non', '', '', '28_8', 106), ('DO', 2793, 'dabant', '', '', '28_9', 5), ('ALIVS', 2794, 'alii', '', '', '28_9', 15), ('EXEMPLVM', 2795, 'exempla', '', '', '28_9', 6), ('QVAERO', 2796, 'quaerebant', '', '', '28_9', 1), ('ALIVS', 2797, 'alii', '', '', '28_9', 15), ('TEMPVS/1', 2798, 'tempus', '', '', '28_9', 13), ('DIFFERO', 2799, 'differebant', '', '', '28_9', 2), ('ALIVS', 2800, 'alii', '', '', '28_9', 15), ('SINE', 2801, 'sine', '', '', '28_10', 7), ('VLLVS', 2802, 'ullis', '', '', '28_10', 7), ('VERBVM', 2803, 'uerborum', '', '', '28_10', 3), ('ORNAMENTVM', 2804, 'ornamentis', '', '', '28_10', 7), ('DO', 2805, 'dabant', '', '', '28_10', 5), ('IN', 2806, 'in', '', '', '28_10', 99), ('IS', 2807, 'ea', '', '', '28_10', 77), ('QVOQVE', 2808, 'quoque', '', '', '28_10', 4), ('RES', 2809, 're', '', '', '28_10', 18), ('SIC', 2810, 'sic', '', '', '28_10', 7), ('SVM/1', 2811, 'sum <locutus>', '', '', '28_11', 200), ('LOQVOR', 2812, '<sum> locutus', '', '', '28_11', 2), ('VT/4', 2813, 'ut', '', '', '28_11', 46), ('OMNIS', 2814, 'omnes', '', '', '28_11', 36), ('INTELLIGO', 2815, 'intellegerent', '', '', '28_11', 4), ('EGO', 2816, 'me', '', '', '28_11', 88), ('IS', 2817, 'id', '', '', '28_11', 77), ('QVI/1', 2818, 'quod', '', '', '28_11', 172), ('RESPVBLICA', 2819, 'rei publicae', '', '', '28_11', 44), ('CAVSA', 2820, 'causa', '', '', '28_12', 9), ('SENTIO', 2821, 'sentirem', '', '', '28_12', 10), ('FACIO', 2822, 'facere', '', '', '28_12', 16), ('VBER/2', 2823, 'uberius', '', '', '28_12', 1), ('PROPTER/2', 2824, 'propter', '', '', '28_12', 10), ('IPSE', 2825, 'ipsius', '', '', '28_12', 33), ('CAESAR/N', 2826, 'Caesaris', '', '', '28_12', 25), ('DIGNITAS', 2827, 'dignitatem', '', '', '28_13', 13), ('AT/2', 2828, 'at', '', '', '29_1', 5), ('EGO', 2829, 'ego', '', '', '29_1', 88), ('IDEM', 2830, 'idem', '', '', '29_1', 27), ('NVNC', 2831, 'nunc', '', '', '29_1', 12), ('IN', 2832, 'in', '', '', '29_1', 99), ('PROVINCIA', 2833, 'prouinciis', '', '', '29_1', 31), ('DECERNO', 2834, 'decernendis', '', '', '29_1', 23), ('QVI/1', 2835, 'qui', '', '', '29_1', 172), ('ILLE', 2836, 'illas', '', '', '29_1', 96), ('OMNIS', 2837, 'omnis', '', '', '29_2', 36), ('RES', 2838, 'res', '', '', '29_2', 18), ('AGO', 2839, 'egi', '', '', '29_2', 9), ('SILENTIVM', 2840, 'silentio', '', '', '29_2', 1), ('INTERPELLO', 2841, 'interpellor', '', '', '29_2', 2), ('CVM/3', 2842, 'cum', '', '', '29_2', 29), ('IN', 2843, 'in', '', '', '29_2', 99), ('SVPERVS', 2844, 'superioribus', '', '', '29_2', 13), ('CAVSA', 2845, 'causis', '', '', '29_2', 9), ('HOMO', 2846, 'hominis', '', '', '29_3', 30), ('ORNAMENTVM', 2847, 'ornamenta', '', '', '29_3', 7), ('ADIVMENTVM', 2848, 'adiumento', '', '', '29_3', 1), ('SVM/1', 2849, 'fuerint', '', '', '29_3', 200), ('IN', 2850, 'in', '', '', '29_3', 99), ('HIC/1', 2851, 'hac', '', '', '29_3', 69), ('EGO', 2852, 'me', '', '', '29_3', 88), ('NIHIL', 2853, 'nihil', '', '', '29_3', 16), ('ALIVS', 2854, 'aliud', '', '', '29_3', 15), ('NISI', 2855, 'nisi', '', '', '29_4', 7), ('RATIO', 2856, 'ratio', '', '', '29_4', 11), ('BELLVM', 2857, 'belli', '', '', '29_4', 23), ('NISI', 2858, 'nisi', '', '', '29_4', 7), ('SVPERVS', 2859, 'summa', '', '', '29_4', 13), ('VTILITAS', 2860, 'utilitas', '', '', '29_4', 6), ('RESPVBLICA', 2861, 'rei publicae', '', '', '29_4', 44), ('MOVEO', 2862, 'moueat', '', '', '29_4', 1), ('NAM', 2863, 'nam', '', '', '29_4', 9), ('IPSE', 2864, 'ipse', '', '', '29_5', 33), ('CAESAR/N', 2865, 'Caesar', '', '', '29_5', 25), ('QVIS/1', 2866, 'quid', '', '', '29_5', 31), ('SVM/1', 2867, 'est', '', '', '29_5', 200), ('CVR/1', 2868, 'cur', '', '', '29_5', 3), ('IN', 2869, 'in', '', '', '29_5', 99), ('PROVINCIA', 2870, 'prouincia', '', '', '29_5', 31), ('COMMOROR/1', 2871, 'commorari', '', '', '29_5', 1), ('VOLO/3', 2872, 'uelit', '', '', '29_5', 17), ('NISI', 2873, 'nisi', '', '', '29_5', 7), ('VT/4', 2874, 'ut', '', '', '29_6', 46), ('IS', 2875, 'ea', '', '', '29_6', 77), ('QVI/1', 2876, 'quae', '', '', '29_6', 172), ('PER', 2877, 'per', '', '', '29_6', 10), ('IS', 2878, 'eum', '', '', '29_6', 77), ('AFFICIO', 2879, 'adfecta <sunt>', '', '', '29_6', 3), ('SVM/1', 2880, '<adfecta> sunt', '', '', '29_6', 200), ('PERFICIO', 2881, 'perfecta', '', '', '29_6', 4), ('RESPVBLICA', 2882, 'rei publicae', '', '', '29_6', 44), ('TRADO', 2883, 'tradat', '', '', '29_6', 4), ('AMOENITAS', 2884, 'amoenitas', '', '', '29_7', 1), ('IS', 2885, 'eum', '', '', '29_7', 77), ('CREDO', 2886, 'credo', '', '', '29_7', 6), ('LOCVS', 2887, 'locorum', '', '', '29_7', 5), ('VRBS', 2888, 'urbium', '', '', '29_7', 9), ('PVLCHRITVDO', 2889, 'pulchritudo', '', '', '29_7', 1), ('HOMO', 2890, 'hominum', '', '', '29_8', 30), ('NATIO/1', 2891, 'nationum', '', '', '29_8', 9), ('QVE', 2892, 'que', '', '', '29_8', 36), ('ILLE', 2893, 'illarum', '', '', '29_8', 96), ('HVMANITAS', 2894, 'humanitas', '', '', '29_8', 1), ('ET/2', 2895, 'et', '', '', '29_8', 110), ('LEPOR', 2896, 'lepos', '', '', '29_8', 1), ('VICTORIA', 2897, 'uictoriae', '', '', '29_8', 5), ('CVPIDITAS', 2898, 'cupiditas', '', '', '29_9', 4), ('FINIS', 2899, 'finium', '', '', '29_9', 1), ('IMPERIVM', 2900, 'imperi', '', '', '29_9', 18), ('PROPAGATIO', 2901, 'propagatio', '', '', '29_9', 1), ('RETINEO', 2902, 'retinet', '', '', '29_9', 6), ('QVIS/1', 2903, 'quid', '', '', '29_9', 31), ('ILLE', 2904, 'illis', '', '', '29_9', 96), ('TERRA', 2905, 'terris', '', '', '29_10', 2), ('ASPER', 2906, 'asperius', '', '', '29_10', 1), ('QVIS/1', 2907, 'quid', '', '', '29_10', 31), ('INCVLTVS/2', 2908, 'incultius', '', '', '29_10', 1), ('OPPIDVM', 2909, 'oppidis', '', '', '29_10', 3), ('QVIS/1', 2910, 'quid', '', '', '29_10', 31), ('NATIO/1', 2911, 'nationibus', '', '', '29_10', 9), ('IMMANIS', 2912, 'immanius', '', '', '29_11', 3), ('QVIS/1', 2913, 'quid', '', '', '29_11', 31), ('PORRO', 2914, 'porro', '', '', '29_11', 1), ('TOT', 2915, 'tot', '', '', '29_11', 2), ('VICTORIA', 2916, 'uictoriis', '', '', '29_11', 5), ('PRAESTABILIS', 2917, 'praestabilius', '', '', '29_11', 2), ('QVIS/1', 2918, 'quid', '', '', '29_11', 31), ('OCEANVS/1', 2919, 'Oceano', '', '', '29_11', 3), ('LONGVS', 2920, 'longius', '', '', '29_12', 3), ('INVENIO', 2921, 'inueniri', '', '', '29_12', 1), ('POSSVM/1', 2922, 'potest', '', '', '29_12', 40), ('AN', 2923, 'an', '', '', '29_12', 11), ('REDITVS', 2924, 'reditus', '', '', '29_12', 2), ('IN', 2925, 'in', '', '', '29_12', 99), ('PATRIA', 2926, 'patriam', '', '', '29_12', 7), ('HABEO', 2927, 'habet', '', '', '29_12', 19), ('ALIQVIS', 2928, 'aliquam', '', '', '29_13', 11), ('OFFENSIO', 2929, 'offensionem', '', '', '29_13', 1), ('VTRVM', 2930, 'utrum', '', '', '29_13', 2), ('APVD', 2931, 'apud', '', '', '29_13', 2), ('POPVLVS/1', 2932, 'populum', '', '', '29_13', 15), ('AB', 2933, 'a', '', '', '29_13', 41), ('QVI/1', 2934, 'quo', '', '', '29_13', 172), ('MITTO', 2935, 'missus (est)', '', '', '29_13', 6), ('AN', 2936, 'an', '', '', '29_13', 11), ('APVD', 2937, 'apud', '', '', '29_14', 2), ('SENATVS', 2938, 'senatum', '', '', '29_14', 13), ('AB', 2939, 'a', '', '', '29_14', 41), ('QVI/1', 2940, 'quo', '', '', '29_14', 172), ('ORNO', 2941, 'ornatus <est>', '', '', '29_14', 6), ('SVM/1', 2942, '<ornatus> est', '', '', '29_14', 200), ('AN', 2943, 'an', '', '', '29_14', 11), ('DIES', 2944, 'dies', '', '', '29_14', 11), ('AVGEO', 2945, 'auget', '', '', '29_14', 1), ('IS', 2946, 'eius', '', '', '29_14', 77), ('DESIDERIVM', 2947, 'desiderium', '', '', '29_15', 1), ('AN', 2948, 'an', '', '', '29_15', 11), ('MAGIS/2', 2949, 'magis', '', '', '29_15', 8), ('OBLIVIO', 2950, 'obliuionem', '', '', '29_15', 1), ('AC/1', 2951, 'ac', '', '', '29_15', 26), ('LAVREA', 2952, 'laurea', '', '', '29_15', 2), ('ILLE', 2953, 'illa', '', '', '29_15', 96), ('MAGNVS', 2954, 'magnis', '', '', '29_15', 17), ('PERICVLVM', 2955, 'periculis', '', '', '29_16', 6), ('PARIO/2', 2956, 'parta', '', '', '29_16', 3), ('AMITTO', 2957, 'amittit', '', '', '29_16', 3), ('LONGVS', 2958, 'longo', '', '', '29_16', 3), ('INTERVALLVM', 2959, 'interuallo', '', '', '29_16', 1), ('VIRIDITAS', 2960, 'uiriditatem', '', '', '29_16', 1), ('QVARE/1', 2961, 'qua re', '', '', '29_16', 4), ('SI/2', 2962, 'si', '', '', '29_16', 62), ('QVIS/2', 2963, 'qui', '', '', '29_17', 6), ('HOMO', 2964, 'hominem', '', '', '29_17', 30), ('NON', 2965, 'non', '', '', '29_17', 106), ('DILIGO/3', 2966, 'diligunt', '', '', '29_17', 2), ('NIHIL', 2967, 'nihil', '', '', '29_17', 16), ('SVM/1', 2968, 'est', '', '', '29_17', 200), ('QVOD/1', 2969, 'quod', '', '', '29_17', 20), ('IS', 2970, 'eum', '', '', '29_17', 77), ('DE', 2971, 'de', '', '', '29_17', 34), ('PROVINCIA', 2972, 'prouincia', '', '', '29_18', 31), ('DEVOCO', 2973, 'deuocent', '', '', '29_18', 2), ('AD/2', 2974, 'ad', '', '', '29_18', 35), ('GLORIA', 2975, 'gloriam', '', '', '29_18', 4), ('DEVOCO', 2976, 'deuocant', '', '', '29_18', 2), ('AD/2', 2977, 'ad', '', '', '29_18', 35), ('TRIVMPHVS', 2978, 'triumphum', '', '', '29_18', 3), ('AD/2', 2979, 'ad', '', '', '29_18', 35), ('GRATVLATIO', 2980, 'gratulationem', '', '', '29_19', 2), ('AD/2', 2981, 'ad', '', '', '29_19', 35), ('SVPERVS', 2982, 'summum', '', '', '29_19', 13), ('HONOR', 2983, 'honorem', '', '', '29_19', 10), ('SENATVS', 2984, 'senatus', '', '', '29_19', 13), ('EQVESTER', 2985, 'equestris', '', '', '29_19', 2), ('ORDO', 2986, 'ordinis', '', '', '29_20', 16), ('GRATIA', 2987, 'gratiam', '', '', '29_20', 9), ('POPVLVS/1', 2988, 'populi', '', '', '29_20', 15), ('CARITAS', 2989, 'caritatem', '', '', '29_20', 1), ('SED', 2990, 'sed', '', '', '30_1', 42), ('SI/2', 2991, 'si', '', '', '30_1', 62), ('ILLE', 2992, 'ille', '', '', '30_1', 96), ('HIC/1', 2993, 'hac', '', '', '30_1', 69), ('TAM', 2994, 'tam', '', '', '30_1', 5), ('EXIMIVS', 2995, 'eximia', '', '', '30_1', 5), ('FORTVNA', 2996, 'fortuna', '', '', '30_2', 4), ('PROPTER/2', 2997, 'propter', '', '', '30_2', 10), ('VTILITAS', 2998, 'utilitatem', '', '', '30_2', 6), ('RESPVBLICA', 2999, 'rei publicae', '', '', '30_2', 44), ('FRVOR', 3000, 'frui', '', '', '30_2', 4), ('NON', 3001, 'non', '', '', '30_2', 106), ('PROPERO', 3002, 'properat', '', '', '30_2', 3), ('VT/4', 3003, 'ut', '', '', '30_3', 46), ('OMNIS', 3004, 'omnia', '', '', '30_3', 36), ('ILLE', 3005, 'illa', '', '', '30_3', 96), ('CONFICIO', 3006, 'conficiat', '', '', '30_3', 7), ('QVIS/1', 3007, 'quid', '', '', '30_3', 31), ('EGO', 3008, 'ego', '', '', '30_3', 88), ('SENATOR', 3009, 'senator', '', '', '30_3', 5), ('FACIO', 3010, 'facere', '', '', '30_3', 16), ('DEBEO', 3011, 'debeo', '', '', '30_3', 14), ('QVI/1', 3012, 'quem', '', '', '30_4', 172), ('ETIAMSI', 3013, 'etiam si', '', '', '30_4', 4), ('ILLE', 3014, 'ille', '', '', '30_4', 96), ('ALIVS', 3015, 'aliud', '', '', '30_4', 15), ('VOLO/3', 3016, 'uellet', '', '', '30_4', 17), ('RESPVBLICA', 3017, 'rei publicae', '', '', '30_4', 44), ('CONSVLO', 3018, 'consulere', '', '', '30_4', 3), ('OPORTET', 3019, 'oporteret', '', '', '30_5', 6), ('EGO', 3020, 'ego', '', '', '30_6', 88), ('VERO/3', 3021, 'uero', '', '', '30_6', 10), ('SIC', 3022, 'sic', '', '', '30_6', 7), ('INTELLIGO', 3023, 'intellego', '', '', '30_6', 4), ('PATER', 3024, 'patres', '', '', '30_6', 17), ('CONSCRIBO', 3025, 'conscripti', '', '', '30_6', 15), ('NOS', 3026, 'nos', '', '', '30_6', 10), ('HIC/1', 3027, 'hoc', '', '', '30_6', 69), ('TEMPVS/1', 3028, 'tempore', '', '', '30_6', 13), ('IN', 3029, 'in', '', '', '30_7', 99), ('PROVINCIA', 3030, 'prouinciis', '', '', '30_7', 31), ('DECERNO', 3031, 'decernendis', '', '', '30_7', 23), ('PERPETVVS', 3032, 'perpetuae', '', '', '30_7', 3), ('PAX', 3033, 'pacis', '', '', '30_7', 7), ('HABEO', 3034, 'habere', '', '', '30_7', 19), ('OPORTET', 3035, 'oportere', '', '', '30_7', 6), ('RATIO', 3036, 'rationem', '', '', '30_8', 11), ('NAM', 3037, 'nam', '', '', '30_8', 9), ('QVIS/1', 3038, 'quis', '', '', '30_8', 31), ('HIC/1', 3039, 'hoc', '', '', '30_8', 69), ('NON', 3040, 'non', '', '', '30_8', 106), ('SENTIO', 3041, 'sentit', '', '', '30_8', 10), ('OMNIS', 3042, 'omnia', '', '', '30_8', 36), ('ALIVS', 3043, 'alia', '', '', '30_8', 15), ('SVM/1', 3044, 'esse', '', '', '30_8', 200), ('NOS', 3045, 'nobis', '', '', '30_8', 10), ('VACVVS', 3046, 'uacua', '', '', '30_9', 1), ('AB', 3047, 'ab', '', '', '30_9', 41), ('OMNIS', 3048, 'omni', '', '', '30_9', 36), ('PERICVLVM', 3049, 'periculo', '', '', '30_9', 6), ('ATQVE/1', 3050, 'atque', '', '', '30_9', 36), ('ETIAM', 3051, 'etiam', '', '', '30_9', 28), ('SVSPICIO/1', 3052, 'suspicione', '', '', '30_9', 1), ('BELLVM', 3053, 'belli', '', '', '30_9', 23), ('IAMDIV', 3054, 'iam diu', '', '', '31_1', 2), ('MARE', 3055, 'mare', '', '', '31_1', 1), ('VIDEO', 3056, 'uidemus', '', '', '31_1', 24), ('ILLE', 3057, 'illud', '', '', '31_1', 96), ('IMMENSVS', 3058, 'immensum', '', '', '31_1', 1), ('QVI/1', 3059, 'cuius', '', '', '31_1', 172), ('FERVOR', 3060, 'feruore', '', '', '31_1', 1), ('NON', 3061, 'non', '', '', '31_1', 106), ('SOLVM/2', 3062, 'solum', '', '', '31_1', 14), ('MARITIMVS', 3063, 'maritimi', '', '', '31_2', 2), ('CVRSVS', 3064, 'cursus', '', '', '31_2', 2), ('SED', 3065, 'sed', '', '', '31_2', 42), ('VRBS', 3066, 'urbes', '', '', '31_2', 9), ('ETIAM', 3067, 'etiam', '', '', '31_2', 28), ('ET/2', 3068, 'et', '', '', '31_2', 110), ('VIA', 3069, 'uiae', '', '', '31_2', 2), ('MILITARIS', 3070, 'militares', '', '', '31_2', 2), ('IAM', 3071, 'iam', '', '', '31_2', 14), ('TENEO', 3072, 'tenebantur', '', '', '31_3', 9), ('VIRTVS', 3073, 'uirtute', '', '', '31_3', 5), ('GNAEVS/N', 3074, 'Cn.', '', '', '31_3', 4), ('POMPEIVS/N', 3075, 'Pompei', '', '', '31_3', 5), ('SIC', 3076, 'sic', '', '', '31_3', 7), ('AB', 3077, 'a', '', '', '31_3', 41), ('POPVLVS/1', 3078, 'populo', '', '', '31_3', 15), ('ROMANVS/A', 3079, 'Romano', '', '', '31_3', 13), ('AB', 3080, 'ab', '', '', '31_3', 41), ('OCEANVS/1', 3081, 'Oceano', '', '', '31_3', 3), ('VSQVE', 3082, 'usque', '', '', '31_4', 3), ('AD/2', 3083, 'ad', '', '', '31_4', 35), ('VLTIMVS', 3084, 'ultimum', '', '', '31_4', 4), ('PONTVS/N', 3085, 'Pontum', '', '', '31_4', 2), ('TAMQVAM/1', 3086, 'tamquam', '', '', '31_4', 2), ('VNVS', 3087, 'unum', '', '', '31_4', 13), ('ALIQVIS', 3088, 'aliquem', '', '', 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26), ('SEDES', 3442, 'sedem', '', '', '34_4', 2), ('PRAEBEO', 3443, 'praebuisset', '', '', '34_5', 1), ('QVI/1', 3444, 'quae', '', '', '34_5', 172), ('IAM', 3445, 'iam', '', '', '34_5', 14), ('LICET/1', 3446, 'licet', '', '', '34_5', 8), ('CONSIDO', 3447, 'considant', '', '', '34_5', 1), ('NIHIL', 3448, 'nihil', '', '', '34_5', 16), ('SVM/1', 3449, 'est', '', '', '34_5', 200), ('ENIM/2', 3450, 'enim', '', '', '34_5', 10), ('VLTRA/2', 3451, 'ultra', '', '', '34_5', 1), ('ILLE', 3452, 'illam', '', '', '34_6', 96), ('ALTITVDO', 3453, 'altitudinem', '', '', '34_6', 1), ('MONS', 3454, 'montium', '', '', '34_6', 1), ('VSQVE', 3455, 'usque', '', '', '34_6', 3), ('AD/2', 3456, 'ad', '', '', '34_6', 35), ('OCEANVS/1', 3457, 'Oceanum', '', '', '34_6', 3), ('QVI/1', 3458, 'quod', '', '', '34_6', 172), ('SVM/1', 3459, 'sit', '', '', '34_6', 200), ('ITALIA/N', 3460, 'Italiae', '', '', '34_7', 4), ('PERTIMESCO', 3461, 'pertimescendum', '', '', '34_7', 3), ('SED', 3462, 'sed', '', '', '34_7', 42), ('TAMEN', 3463, 'tamen', '', '', '34_7', 16), ('VNVS', 3464, 'una', '', '', '34_7', 13), ('ATQVE/1', 3465, 'atque', '', '', '34_7', 36), ('ALTER', 3466, 'altera', '', '', '34_7', 10), ('AESTAS', 3467, 'aestas', '', '', '34_7', 1), ('VEL/1', 3468, 'uel', '', '', '34_8', 8), ('METVS', 3469, 'metu', '', '', '34_8', 3), ('VEL/1', 3470, 'uel', '', '', '34_8', 8), ('SPES', 3471, 'spe', '', '', '34_8', 1), ('VEL/1', 3472, 'uel', '', '', '34_8', 8), ('POENA', 3473, 'poena', '', '', '34_8', 3), ('VEL/1', 3474, 'uel', '', '', '34_8', 8), ('PRAEMIVM', 3475, 'praemiis', '', '', '34_8', 3), ('VEL/1', 3476, 'uel', '', '', '34_8', 8), ('ARMA', 3477, 'armis', '', '', '34_8', 2), ('VEL/1', 3478, 'uel', '', '', '34_8', 8), ('LEX', 3479, 'legibus', '', '', '34_8', 21), ('POSSVM/1', 3480, 'potest', '', '', '34_9', 40), ('TOTVS', 3481, 'totam', '', '', '34_9', 8), ('GALLIA/N', 3482, 'Galliam', '', '', '34_9', 12), ('SEMPITERNVS', 3483, 'sempiternis', '', '', '34_9', 1), ('VINCVLVM', 3484, 'uinculis', '', 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'bellum', '', '', '34_11', 23), ('REVIRESCO', 3505, 'reuirescent', '', '', '34_12', 1), ('QVARE/1', 3506, 'qua re', '', '', '35_1', 4), ('SVM/1', 3507, 'sit', '', '', '35_1', 200), ('IN', 3508, 'in', '', '', '35_1', 99), ('IS', 3509, 'eius', '', '', '35_1', 77), ('TVTELA', 3510, 'tutela', '', '', '35_1', 1), ('GALLIA/N', 3511, 'Gallia', '', '', '35_1', 12), ('QVI/1', 3512, 'cuius', '', '', '35_1', 172), ('FIDES/2', 3513, 'fidei', '', '', '35_1', 3), ('VIRTVS', 3514, 'uirtuti', '', '', '35_2', 5), ('FELICITAS', 3515, 'felicitati', '', '', '35_2', 1), ('COMMENDO', 3516, 'commendata <est>', '', '', '35_2', 2), ('SVM/1', 3517, '<commendata> est', '', '', '35_2', 200), ('QVI/1', 3518, 'qui', '', '', '35_2', 172), ('SI/2', 3519, 'si', '', '', '35_2', 62), ('FORTVNA', 3520, 'Fortunae', '', '', '35_2', 4), ('MVNVS', 3521, 'muneribus', '', '', '35_2', 2), ('AMPLVS', 3522, 'amplissimis', '', '', '35_3', 5), ('ORNO', 3523, 'ornatus', '', '', '35_3', 6), ('SAEPE', 3524, 'saepius', '', '', '35_3', 4), ('IS', 3525, 'eius', '', '', '35_3', 77), ('DEA', 3526, 'deae', '', '', '35_3', 1), ('PERICVLVM', 3527, 'periculum', '', '', '35_3', 6), ('FACIO', 3528, 'facere', '', '', '35_3', 16), ('NOLO', 3529, 'nollet', '', '', '35_3', 2), ('SI/2', 3530, 'si', '', '', '35_4', 62), ('IN', 3531, 'in', '', '', '35_4', 99), ('PATRIA', 3532, 'patriam', '', '', '35_4', 7), ('SI/2', 3533, 'si', '', '', '35_4', 62), ('AD/2', 3534, 'ad', '', '', '35_4', 35), ('DEVS', 3535, 'deos', '', '', '35_4', 4), ('PENATES/N', 3536, 'penatis', '', '', '35_4', 1), ('SI/2', 3537, 'si', '', '', '35_4', 62), ('AD/2', 3538, 'ad', '', '', '35_4', 35), ('IS', 3539, 'eam', '', '', '35_4', 77), ('DIGNITAS', 3540, 'dignitatem', '', '', '35_4', 13), ('QVI/1', 3541, 'quam', '', '', '35_4', 172), ('IN', 3542, 'in', '', '', '35_5', 99), ('CIVITAS', 3543, 'ciuitate', '', '', '35_5', 9), ('SVI/1', 3544, 'sibi', '', '', '35_5', 26), ('PROPONO', 3545, 'propositam', '', '', '35_5', 1), ('VIDEO', 3546, 'uidet', '', '', '35_5', 24), ('SI/2', 3547, 'si', '', '', '35_5', 62), ('AD/2', 3548, 'ad', '', '', '35_5', 35), ('IVCVNDVS', 3549, 'iucundissimos', '', '', '35_5', 1), ('LIBERI', 3550, 'liberos', '', '', '35_5', 1), ('SI/2', 3551, 'si', '', '', '35_6', 62), ('AD/2', 3552, 'ad', '', '', '35_6', 35), ('CLARVS', 3553, 'clarissimum', '', '', '35_6', 6), ('GENER', 3554, 'generum', '', '', '35_6', 4), ('REDEO/1', 3555, 'redire', '', '', '35_6', 6), ('PROPERO', 3556, 'properaret', '', '', '35_6', 3), ('SI/2', 3557, 'si', '', '', '35_6', 62), ('IN', 3558, 'in', '', '', '35_6', 99), ('CAPITOLIVM/N', 3559, 'Capitolium', '', '', '35_7', 2), ('INVEHO', 3560, 'inuehi', '', '', '35_7', 1), ('VICTOR', 3561, 'uictor', '', '', '35_7', 1), ('CVM/2', 3562, 'cum', '', '', '35_7', 33), ('ILLE', 3563, 'illa', '', '', '35_7', 96), ('INSIGNIS', 3564, 'insigni', '', '', '35_7', 5), ('LAVREA', 3565, 'laurea', '', '', '35_7', 2), ('GESTIO/2', 3566, 'gestiret', '', '', '35_7', 1), ('SI/2', 3567, 'si', '', '', '35_7', 62), ('DENIQVE', 3568, 'denique', '', '', '35_7', 5), ('TIMEO', 3569, 'timeret', '', '', '35_8', 2), ('CASVS', 3570, 'casum', '', '', '35_8', 2), ('ALIQVIS', 3571, 'aliquem', '', '', '35_8', 11), ('QVI/1', 3572, 'qui', '', '', '35_8', 172), ('ILLE', 3573, 'illi', '', '', '35_8', 96), ('TANTVM/2', 3574, 'tantum', '', '', '35_8', 4), ('ADDO', 3575, 'addere', '', '', '35_8', 1), ('IAM', 3576, 'iam', '', '', '35_8', 14), ('NON', 3577, 'non', '', '', '35_8', 106), ('POSSVM/1', 3578, 'potest', '', '', '35_8', 40), ('QVANTVM/3', 3579, 'quantum', '', '', '35_9', 3), ('AVFERO', 3580, 'auferre', '', '', '35_9', 2), ('NOS', 3581, 'nos', '', '', '35_9', 10), ('TAMEN', 3582, 'tamen', '', '', '35_9', 16), ('OPORTET', 3583, 'oporteret', '', '', '35_9', 6), ('AB', 3584, 'ab', '', '', '35_9', 41), ('IDEM', 3585, 'eodem', '', '', '35_9', 27), ('ILLE', 3586, 'illa', '', '', '35_9', 96), ('OMNIS', 3587, 'omnia', '', '', '35_9', 36), ('AB', 3588, 'a', '', '', '35_10', 41), ('QVI/1', 3589, 'quo', '', '', '35_10', 172), ('PROFLIGO', 3590, 'profligata <sunt>', '', '', '35_10', 1), ('SVM/1', 3591, '<profligata> sunt', '', '', '35_10', 200), ('CONFICIO', 3592, 'confici', '', '', '35_10', 7), ('VOLO/3', 3593, 'uelle', '', '', '35_10', 17), ('CVM/3', 3594, 'cum', '', '', '35_10', 29), ('VERO/3', 3595, 'uero', '', '', '35_10', 10), ('ILLE', 3596, 'ille', '', '', '35_10', 96), ('SVVS', 3597, 'suae', '', '', '35_10', 22), ('GLORIA', 3598, 'gloriae', '', '', '35_10', 4), ('IAMPRIDEM', 3599, 'iam pridem', '', '', '35_11', 1), ('RESPVBLICA', 3600, 'rei publicae', '', '', '35_11', 44), ('NONDVM', 3601, 'nondum', '', '', '35_11', 5), ('SATISFACIO', 3602, 'satis fecerit', '', '', '35_11', 1), ('ET/2', 3603, 'et', '', '', '35_11', 110), ('MALO', 3604, 'malit', '', '', '35_11', 3), ('TAMEN', 3605, 'tamen', '', '', '35_11', 16), ('TARDVS', 3606, 'tardius', '', '', '35_12', 1), ('AD/2', 3607, 'ad', '', '', '35_12', 35), ('SVVS', 3608, 'suorum', '', '', '35_12', 22), ('LABOR/1', 3609, 'laborum', '', '', '35_12', 4), ('FRVCTVS', 3610, 'fructus', '', '', '35_12', 1), ('PERVENIO', 3611, 'peruenire', '', '', '35_12', 3), ('QVAM/1', 3612, 'quam', '', '', '35_12', 19), ('NON', 3613, 'non', '', '', '35_12', 106), ('EXPLEO', 3614, 'explere', '', '', '35_13', 2), ('SVSCIPIO', 3615, 'susceptum', '', '', '35_13', 1), ('RESPVBLICA', 3616, 'rei publicae', '', '', '35_13', 44), ('MVNVS', 3617, 'munus', '', '', '35_13', 2), ('NEC/2', 3618, 'nec', '', '', '35_13', 7), ('IMPERATOR', 3619, 'imperatorem', '', '', '35_13', 14), ('INCENDO', 3620, 'incensum', '', '', '35_14', 2), ('AD/2', 3621, 'ad', '', '', '35_14', 35), ('RESPVBLICA', 3622, 'rem publicam', '', '', '35_14', 44), ('BENE', 3623, 'bene', '', '', '35_14', 6), ('GERO', 3624, 'gerendam', '', '', '35_14', 10), ('REVOCO', 3625, 'reuocare', '', '', '35_14', 3), ('NEC/2', 3626, 'nec', '', '', '35_14', 7), ('TOTVS', 3627, 'totam', '', '', '35_14', 8), ('GALLICVS/A', 3628, 'Gallici', '', '', '35_15', 5), ('BELLVM', 3629, 'belli', '', '', '35_15', 23), ('RATIO', 3630, 'rationem', '', '', '35_15', 11), ('PROPE/2', 3631, 'prope', '', '', '35_15', 6), ('IAM', 3632, 'iam', '', '', '35_15', 14), ('EXPLICO', 3633, 'explicatam', '', '', '35_15', 2), ('PERTVRBO/2', 3634, 'perturbare', '', '', '35_15', 2), ('ATQVE/1', 3635, 'atque', '', '', '35_15', 36), ('IMPEDIO', 3636, 'impedire', '', '', '35_16', 1), ('DEBEO', 3637, 'debemus', '', '', '35_16', 14), ('NAM', 3638, 'nam', '', '', '36_1', 9), ('ILLE', 3639, 'illae', '', '', '36_1', 96), ('SENTENTIA', 3640, 'sententiae', '', '', '36_1', 17), ('VIR', 3641, 'uirorum', '', '', '36_1', 14), ('CLARVS', 3642, 'clarissimorum', '', '', '36_1', 6), ('PARVM/2', 3643, 'minime', '', '', '36_1', 7), ('PROBO', 3644, 'probandae', '', '', '36_2', 5), ('SVM/1', 3645, 'sunt', '', '', '36_2', 200), ('QVI/1', 3646, 'quorum', '', '', '36_2', 172), ('ALTER', 3647, 'alter', '', '', '36_2', 10), ('VLTIMVS', 3648, 'ulteriorem', '', '', '36_2', 4), ('GALLIA/N', 3649, 'Galliam', '', '', '36_2', 12), ('DECERNO', 3650, 'decernit', 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('SVM/1', 3672, 'esse', '', '', '36_5', 200), ('LEX', 3673, 'legem', '', '', '36_5', 21), ('NEGO', 3674, 'neget', '', '', '36_5', 4), ('ET/2', 3675, 'et', '', '', '36_5', 110), ('QVI/1', 3676, 'quae', '', '', '36_5', 172), ('PARS', 3677, 'pars', '', '', '36_5', 2), ('PROVINCIA', 3678, 'prouinciae', '', '', '36_5', 31), ('SVM/1', 3679, 'sit', '', '', '36_5', 200), ('QVI/1', 3680, 'cui', '', '', '36_6', 172), ('NON', 3681, 'non', '', '', '36_6', 106), ('POSSVM/1', 3682, 'possit', '', '', '36_6', 40), ('INTERCEDO/1', 3683, 'intercedi', '', '', '36_6', 4), ('HIC/1', 3684, 'hanc', '', '', '36_6', 69), ('SVI/1', 3685, 'se', '', '', '36_6', 26), ('AVELLO', 3686, 'auellere', '', '', '36_6', 1), ('QVI/1', 3687, 'quae', '', '', '36_6', 172), ('DEFENSOR', 3688, 'defensorem', '', '', '36_6', 1), ('HABEO', 3689, 'habeat', '', '', '36_7', 19), ('NON', 3690, 'non', '', '', '36_7', 106), ('TANGO', 3691, 'tangere', '', '', '36_7', 2), ('SIMVL/1', 3692, 'simul', '', '', '36_7', 2), ('ET/1', 3693, 'et', 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3715, 'Gallici', '', '', '36_9', 5), ('RATIO', 3716, 'rationem', '', '', '36_9', 11), ('HABEO', 3717, 'habet', '', '', '36_9', 19), ('FVNGOR', 3718, 'fungitur', '', '', '36_10', 1), ('OFFICIVM', 3719, 'officio', '', '', '36_10', 3), ('BONVS', 3720, 'boni', '', '', '36_10', 7), ('SENATOR', 3721, 'senatoris', '', '', '36_10', 5), ('LEX', 3722, 'legem', '', '', '36_10', 21), ('QVI/1', 3723, 'quam', '', '', '36_10', 172), ('NON', 3724, 'non', '', '', '36_10', 106), ('PVTO', 3725, 'putat', '', '', '36_10', 15), ('IS', 3726, 'eam', '', '', '36_10', 77), ('QVOQVE', 3727, 'quoque', '', '', '36_11', 4), ('SERVO', 3728, 'seruat', '', '', '36_11', 5), ('PRAEFINIO', 3729, 'praefinit', '', '', '36_11', 1), ('ENIM/2', 3730, 'enim', '', '', '36_11', 10), ('SVCCESSOR', 3731, 'successori', '', '', '36_11', 1), ('DIES', 3732, 'diem', '', '', '36_11', 11), ('QVAMQVAM/2', 3733, 'quamquam', '', '', '36_11', 2), ('EGO', 3734, 'mihi', '', '', '36_12', 88), ('NIHIL', 3735, 'nihil', '', '', '36_12', 16), ('VIDEO', 3736, 'uidetur', '', '', '36_12', 24), ('ALIENVS/2', 3737, 'alienius', '', '', '36_12', 5), ('AB', 3738, 'a', '', '', '36_12', 41), ('DIGNITAS', 3739, 'dignitate', '', '', '36_12', 13), ('DISCIPLINA', 3740, 'disciplina', '', '', '36_12', 1), ('QVE', 3741, 'que', '', '', '36_12', 36), ('MAIORES', 3742, 'maiorum', '', '', '36_12', 2), ('QVAM/1', 3743, 'quam', '', '', '36_13', 19), ('VT/4', 3744, 'ut', '', '', '36_13', 46), ('QVI/1', 3745, 'qui', '', '', '36_13', 172), ('CONSVL', 3746, 'consul', '', '', '36_13', 15), ('KALENDAE', 3747, 'Kalendis', '', '', '36_13', 2), ('IANVARIVS/A', 3748, 'Ianuariis', '', '', '36_13', 2), ('HABEO', 3749, 'habere', '', '', '36_13', 19), ('PROVINCIA', 3750, 'prouinciam', '', '', '36_13', 31), ('DEBEO', 3751, 'debet', '', '', '36_14', 14), ('IS', 3752, 'is', '', '', '36_14', 77), ('VT/4', 3753, 'ut', '', '', '36_14', 46), ('IS', 3754, 'eam', '', '', '36_14', 77), ('DESPONDEO', 3755, 'desponsam', '', '', '36_14', 1), ('NON', 3756, 'non', '', '', '36_14', 106), ('DECERNO', 3757, 'decretam', '', '', '36_14', 23), ('HABEO', 3758, 'habere', '', '', '36_14', 19), ('VIDEO', 3759, 'uideatur', '', '', '36_14', 24), ('SVM/1', 3760, 'fuerit', '', '', '37_1', 200), ('TOTVS', 3761, 'toto', '', '', '37_1', 8), ('IN', 3762, 'in', '', '', '37_1', 99), ('CONSVLATVS', 3763, 'consulatu', '', '', '37_1', 1), ('SINE', 3764, 'sine', '', '', '37_1', 7), ('PROVINCIA', 3765, 'prouincia', '', '', '37_1', 31), ('QVI/1', 3766, 'cui', '', '', '37_1', 172), ('SVM/1', 3767, 'fuerit <decreta>', '', '', '37_1', 200), ('ANTEQVAM', 3768, 'ante quam', '', '', '37_1', 6), ('DESIGNO', 3769, 'designatus <est>', '', '', '37_2', 3), ('SVM/1', 3770, '<designatus> est', '', '', '37_2', 200), ('DECERNO', 3771, '<fuerit> decreta', '', '', '37_2', 23), ('PROVINCIA', 3772, 'prouincia', '', '', '37_2', 31), ('SORTIOR', 3773, 'sortietur', '', '', '37_2', 3), ('AN', 3774, 'an', '', '', '37_2', 11), ('NON', 3775, 'non', '', '', '37_2', 106), ('NAM', 3776, 'nam', '', '', '37_2', 9), ('ET/2', 3777, 'et', '', '', '37_3', 110), ('NON', 3778, 'non', '', '', '37_3', 106), ('SORTIOR', 3779, 'sortiri', '', '', '37_3', 3), ('ABSVRDVS', 3780, 'absurdum', '', '', '37_3', 1), ('SVM/1', 3781, 'est', '', '', '37_3', 200), ('ET/2', 3782, 'et', '', '', '37_3', 110), ('QVI/1', 3783, 'quod', '', '', '37_3', 172), ('SORTIOR', 3784, 'sortitus <sis>', '', '', '37_3', 3), ('SVM/1', 3785, '<sortitus> sis', '', '', '37_3', 200), ('NON', 3786, 'non', '', '', '37_3', 106), ('HABEO', 3787, 'habere', '', '', '37_3', 19), ('PROFICISCOR', 3788, 'proficiscetur', '', '', '37_4', 1), ('PALVDATVS', 3789, 'paludatus', '', '', '37_4', 1), ('QVO/2', 3790, 'quo', '', '', '37_4', 5), ('QVO/2', 3791, 'quo', '', '', '37_4', 5), ('PERVENIO', 3792, 'peruenire', '', '', '37_4', 3), ('ANTE/2', 3793, 'ante', '', '', '37_4', 7), ('CERTVS', 3794, 'certam', '', '', '37_4', 3), ('DIES', 3795, 'diem', '', '', '37_5', 11), ('NON', 3796, 'non', '', '', '37_5', 106), ('LICET/1', 3797, 'licebit', '', '', '37_5', 8), ('IANVARIVS/A', 3798, 'Ianuario', '', '', '37_5', 2), ('FEBRVARIVS/N', 3799, 'Februario', '', '', '37_5', 1), ('PROVINCIA', 3800, 'prouinciam', '', '', '37_5', 31), ('NON', 3801, 'non', '', '', '37_5', 106), ('HABEO', 3802, 'habebit', '', '', '37_6', 19), ('KALENDAE', 3803, 'Kalendis', '', '', '37_6', 2), ('IS', 3804, 'ei', '', '', '37_6', 77), ('DENIQVE', 3805, 'denique', '', '', '37_6', 5), ('MARTIVS/A', 3806, 'Martiis', '', '', '37_6', 1), ('NASCOR', 3807, 'nascetur', '', '', '37_6', 1), ('REPENTE', 3808, 'repente', '', '', '37_6', 2), ('PROVINCIA', 3809, 'prouincia', '', '', '37_7', 31), ('AC/1', 3810, 'ac', '', '', '38_1', 26), ('TAMEN', 3811, 'tamen', '', '', '38_1', 16), ('HIC/1', 3812, 'his', '', '', '38_1', 69), ('SENTENTIA', 3813, 'sententiis', '', '', '38_1', 17), ('PISO/N', 3814, 'Piso', '', '', '38_1', 7), ('IN', 3815, 'in', '', '', '38_1', 99), ('PROVINCIA', 3816, 'prouincia', '', '', '38_1', 31), ('PERMANEO', 3817, 'permanebit', '', '', '38_2', 1), ('QVI/1', 3818, 'quae', '', '', '38_2', 172), ('CVM/3', 3819, 'cum', '', '', '38_2', 29), ('GRAVIS', 3820, 'grauia', '', '', '38_2', 6), ('SVM/1', 3821, 'sunt', '', '', '38_2', 200), ('TVM', 3822, 'tum', '', '', '38_2', 12), ('NIHIL', 3823, 'nihil', '', '', '38_2', 16), ('GRAVIS', 3824, 'grauius', '', '', '38_2', 6), ('ILLE', 3825, 'illo', '', '', '38_2', 96), ('QVOD/1', 3826, 'quod', '', '', '38_2', 20), ('MVLTO/1', 3827, 'multari', '', '', '38_3', 1), ('IMPERATOR', 3828, 'imperatorem', '', '', '38_3', 14), ('DEMINVTIO', 3829, 'deminutione', '', '', '38_3', 1), ('PROVINCIA', 3830, 'prouinciae', '', '', '38_3', 31), ('CONTVMELIOSVS', 3831, 'contumeliosum', '', '', '38_3', 1), ('SVM/1', 3832, 'est', '', '', '38_4', 200), ('NEQVE', 3833, 'neque', '', '', '38_4', 3), ('SOLVM/2', 3834, 'solum', '', '', '38_4', 14), ('SVPERVS', 3835, 'summo', '', '', '38_4', 13), ('IN', 3836, 'in', '', '', '38_4', 99), ('VIR', 3837, 'uiro', '', '', '38_4', 14), ('SED', 3838, 'sed', '', '', '38_4', 42), ('ETIAM', 3839, 'etiam', '', '', '38_4', 28), ('MEDIOCRIS', 3840, 'mediocri', '', '', '38_4', 2), ('IN', 3841, 'in', '', '', '38_4', 99), ('HOMO', 3842, 'homine', '', '', '38_5', 30), ('NE/4', 3843, 'ne', '', '', '38_5', 14), ('ACCIDO/1', 3844, 'accidat', '', '', '38_5', 2), ('PROVIDEO', 3845, 'prouidendum', '', '', '38_5', 4), ('EGO', 3846, 'ego', '', '', '38_6', 88), ('VOS', 3847, 'uos', '', '', '38_6', 31), ('INTELLIGO', 3848, 'intellego', '', '', '38_6', 4), ('PATER', 3849, 'patres', '', '', '38_6', 17), ('CONSCRIBO', 3850, 'conscripti', '', '', '38_6', 15), ('MVLTVS', 3851, 'multos', '', '', '38_6', 10), ('DECERNO', 3852, 'decreuisse', '', '', '38_6', 23), ('EXIMIVS', 3853, 'eximios', '', '', '38_7', 5), ('HONOR', 3854, 'honores', '', '', '38_7', 10), ('GAIVS/N', 3855, 'C.', '', '', '38_7', 19), ('CAESAR/N', 3856, 'Caesari', '', '', '38_7', 25), ('ET/2', 3857, 'et', '', '', '38_7', 110), ('PROPE/2', 3858, 'prope', '', '', '38_7', 6), ('SINGVLARIS', 3859, 'singularis', '', '', '38_7', 2), ('SI/2', 3860, 'si', '', '', '38_7', 62), ('QVOD/1', 3861, 'quod', '', '', '38_7', 20), ('ITA', 3862, 'ita', '', '', '38_8', 14), ('MEREOR', 3863, 'meritus <erat>', '', '', '38_8', 1), ('SVM/1', 3864, '<meritus> erat', '', '', '38_8', 200), ('GRATVS', 3865, 'grati', '', '', '38_8', 4), ('SIN', 3866, 'sin', '', '', '38_8', 1), ('ETIAM', 3867, 'etiam', '', '', '38_8', 28), ('VT/4', 3868, 'ut', '', '', '38_8', 46), ('QVAM/1', 3869, 'quam', '', '', '38_8', 19), ('CONIVNGO', 3870, 'coniunctissimus', '', '', '38_8', 6), ('HIC/1', 3871, 'huic', '', '', '38_9', 69), ('ORDO', 3872, 'ordini', '', '', '38_9', 16), ('SVM/1', 3873, 'esset', '', '', '38_9', 200), ('SAPIENS/2', 3874, 'sapientes', '', '', '38_9', 2), ('AC/1', 3875, 'ac', '', '', '38_9', 26), ('DIVINVS/2', 3876, 'diuini', '', '', '38_9', 3), ('SVM/1', 3877, 'fuistis', '', '', '38_9', 200), ('NEMO', 3878, 'neminem', '', '', '38_9', 9), ('VMQVAM', 3879, 'umquam', '', '', '38_10', 4), ('SVM/1', 3880, 'est <complexus>', '', '', '38_10', 200), ('HIC/1', 3881, 'hic', '', '', '38_10', 69), ('ORDO', 3882, 'ordo', '', '', '38_10', 16), ('COMPLECTOR', 3883, '<est> complexus', '', '', '38_10', 1), ('HONOR', 3884, 'honoribus', '', '', '38_10', 10), ('ET/2', 3885, 'et', '', '', '38_10', 110), ('BENEFICIVM', 3886, 'beneficiis', '', '', '38_10', 7), ('SVVS', 3887, 'suis', '', '', '38_11', 22), ('QVI/1', 3888, 'qui', '', '', '38_11', 172), ('VLLVS', 3889, 'ullam', '', '', '38_11', 7), ('DIGNITAS', 3890, 'dignitatem', '', '', '38_11', 13), ('PRAESTABILIS', 3891, 'praestabiliorem', '', '', '38_11', 2), ('IS', 3892, 'ea', '', '', '38_11', 77), ('QVI/1', 3893, 'quam', '', '', '38_11', 172), ('PER', 3894, 'per', '', '', '38_11', 10), ('VOS', 3895, 'uos', '', '', '38_11', 31), ('SVM/1', 3896, 'esset <adeptus>', '', '', '38_12', 200), ('ADIPISCOR', 3897, '<esset> adeptus', '', '', '38_12', 3), ('PVTO', 3898, 'putarit', '', '', '38_12', 15), ('NEMO', 3899, 'nemo', '', '', '38_12', 9), ('VMQVAM', 3900, 'umquam', '', '', '38_12', 4), ('HIC/2', 3901, 'hic', '', '', '38_12', 1), ('POSSVM/1', 3902, 'potuit', '', '', '38_12', 40), ('SVM/1', 3903, 'esse', '', '', '38_12', 200), ('PRINCEPS/2', 3904, 'princeps', '', '', '38_13', 4), ('QVI/1', 3905, 'qui', '', '', '38_13', 172), ('MALO', 3906, 'maluerit', '', '', '38_13', 3), ('SVM/1', 3907, 'esse', '', '', '38_13', 200), ('POPVLARIS/2', 3908, 'popularis', '', '', '38_13', 5), ('SED', 3909, 'sed', '', '', '38_13', 42), ('HOMO', 3910, 'homines', '', '', '38_13', 30), ('AVT', 3911, 'aut', '', '', '38_13', 35), ('PROPTER/2', 3912, 'propter', '', '', '38_13', 10), ('INDIGNITAS', 3913, 'indignitatem', '', '', '38_14', 1), ('SVVS', 3914, 'suam', '', '', '38_14', 22), ('DIFFIDO', 3915, 'diffisi', '', '', '38_14', 1), ('IPSE', 3916, 'ipsi', '', '', '38_14', 33), ('SVI/1', 3917, 'sibi', '', '', '38_14', 26), ('AVT', 3918, 'aut', '', '', '38_14', 35), ('PROPTER/2', 3919, 'propter', '', '', '38_14', 10), ('RELIQVVS', 3920, 'reliquorum', '', '', '38_14', 4), ('OBTRECTATIO', 3921, 'obtrectationem', '', '', '38_15', 1), ('AB', 3922, 'ab', '', '', '38_15', 41), ('HIC/1', 3923, 'huius', '', '', '38_15', 69), ('ORDO', 3924, 'ordinis', '', '', '38_15', 16), ('CONIVNCTIO', 3925, 'coniunctione', '', '', '38_15', 2), ('DEPELLO', 3926, 'depulsi', '', '', '38_15', 2), ('SAEPE', 3927, 'saepe', '', '', '38_15', 4), ('EX', 3928, 'ex', '', '', '38_16', 16), ('HIC/1', 3929, 'hoc', '', '', '38_16', 69), ('PORTVS', 3930, 'portu', '', '', '38_16', 2), ('SVI/1', 3931, 'se', '', '', '38_16', 26), ('IN', 3932, 'in', '', '', '38_16', 99), ('ILLE', 3933, 'illos', '', '', '38_16', 96), ('FLVCTVS', 3934, 'fluctus', '', '', '38_16', 1), ('PROPE/2', 3935, 'prope', '', '', '38_16', 6), ('NECESSARIO', 3936, 'necessario', '', '', '38_16', 1), ('CONFERO', 3937, 'contulerunt', '', '', '38_16', 1), ('QVI/1', 3938, 'qui', '', '', '38_17', 172), ('SI/2', 3939, 'si', '', '', '38_17', 62), ('EX', 3940, 'ex', '', '', '38_17', 16), ('ILLE', 3941, 'illa', '', '', '38_17', 96), ('IACTATIO', 3942, 'iactatione', '', '', '38_17', 1), ('CVRSVS', 3943, 'cursu', '', '', '38_17', 2), ('QVE', 3944, 'que', '', '', '38_17', 36), ('POPVLARIS/2', 3945, 'populari', '', '', '38_17', 5), ('BENE', 3946, 'bene', '', '', '38_17', 6), ('GERO', 3947, 'gesta', '', '', '38_17', 10), ('RESPVBLICA', 3948, 're publica', '', '', '38_18', 44), ('REFERO', 3949, 'referunt', '', '', '38_18', 4), ('ASPECTVS', 3950, 'aspectum', '', '', '38_18', 1), ('IN', 3951, 'in', '', '', '38_18', 99), ('CVRIA', 3952, 'curiam', '', '', '38_18', 1), ('ATQVE/1', 3953, 'atque', '', '', '38_18', 36), ('HIC/1', 3954, 'huic', '', '', '38_18', 69), ('AMPLVS', 3955, 'amplissimae', '', '', '38_18', 5), ('DIGNITAS', 3956, 'dignitati', '', '', '38_19', 13), ('SVM/1', 3957, 'esse <commendati>', '', '', '38_19', 200), ('COMMENDO', 3958, '<esse> commendati', '', '', '38_19', 2), ('VOLO/3', 3959, 'uolunt', '', '', '38_19', 17), ('NON', 3960, 'non', '', '', '38_19', 106), ('MODO/1', 3961, 'modo', '', '', '38_19', 4), ('NON', 3962, 'non', '', '', '38_19', 106), ('REPELLO', 3963, 'repellendi', '', '', '38_19', 3), ('SVM/1', 3964, 'sunt', '', '', '38_20', 200), ('VERVM/4', 3965, 'uerum', '', '', '38_20', 3), ('ETIAM', 3966, 'etiam', '', '', '38_20', 28), ('EXPETO', 3967, 'expetendi', '', '', '38_20', 1), ('MONEO', 3968, 'monemur', '', '', '39_1', 2), ('AB', 3969, 'a', '', '', '39_1', 41), ('FORTIS', 3970, 'fortissimo', '', '', '39_1', 7), ('VIR', 3971, 'uiro', '', '', '39_1', 14), ('ATQVE/1', 3972, 'atque', '', '', '39_2', 36), ('BONVS', 3973, 'optimo', '', '', '39_2', 7), ('POST/2', 3974, 'post', '', '', '39_2', 4), ('HOMO', 3975, 'hominum', '', '', '39_2', 30), ('MEMORIA', 3976, 'memoriam', '', '', '39_2', 4), ('CONSVL', 3977, 'consule', '', '', '39_2', 15), ('VT/4', 3978, 'ut', '', '', '39_2', 46), ('PROVIDEO', 3979, 'prouideamus', '', '', '39_3', 4), ('NE/4', 3980, 'ne', '', '', '39_3', 14), ('CITERIOR', 3981, 'citerior', '', '', '39_3', 2), ('GALLIA/N', 3982, 'Gallia', '', '', '39_3', 12), ('NOS', 3983, 'nobis', '', '', '39_3', 10), ('INVITVS', 3984, 'inuitis', '', '', '39_3', 3), ('ALIQVIS', 3985, 'alicui', '', '', '39_3', 11), ('DECERNO', 3986, 'decernatur', '', '', '39_3', 23), ('POST/2', 3987, 'post', '', '', '39_3', 4), ('IS', 3988, 'eos', '', '', '39_3', 77), ('CONSVL', 3989, 'consules', '', '', '39_4', 15), ('QVI/1', 3990, 'qui', '', '', '39_4', 172), ('NVNC', 3991, 'nunc', '', '', '39_4', 12), ('SVM/1', 3992, 'erunt <designati>', '', '', '39_4', 200), ('DESIGNO', 3993, '<erunt> designati', '', '', '39_4', 3), ('PERPETVO/2', 3994, 'perpetuo', '', '', '39_4', 1), ('QVE', 3995, 'que', '', '', '39_4', 36), ('POSTHAC', 3996, 'posthac', '', '', '39_4', 1), ('AB', 3997, 'ab', '', '', '39_4', 41), ('IS', 3998, 'iis', '', '', '39_4', 77), ('QVI/1', 3999, 'qui', '', '', '39_5', 172), ('HIC/1', 4000, 'hunc', '', '', '39_5', 69), ('ORDO', 4001, 'ordinem', '', '', '39_5', 16), ('OPPVGNO', 4002, 'oppugnent', '', '', '39_5', 4), ('POPVLARIS/2', 4003, 'populari', '', '', '39_5', 5), ('AC/1', 4004, 'ac', '', '', '39_5', 26), ('TVRBVLENTVS', 4005, 'turbulenta', '', '', '39_5', 1), ('RATIO', 4006, 'ratione', '', '', '39_5', 11), ('TENEO', 4007, 'teneatur', '', '', '39_6', 9), ('QVI/1', 4008, 'quam', '', '', '39_6', 172), ('EGO', 4009, 'ego', '', '', '39_6', 88), ('PLAGA/1', 4010, 'plagam', '', '', '39_6', 2), ('ETSI/2', 4011, 'etsi', '', '', '39_6', 2), ('NON', 4012, 'non', '', '', '39_6', 106), ('CONTEMNO', 4013, 'contemno', '', '', '39_6', 1), ('PATER', 4014, 'patres', '', '', '39_6', 17), ('CONSCRIBO', 4015, 'conscripti', '', '', '39_7', 15), ('PRAESERTIM', 4016, 'praesertim', '', '', '39_7', 6), ('MONEO', 4017, 'monitus', '', '', '39_7', 2), ('AB', 4018, 'a', '', '', '39_7', 41), ('SAPIENS/2', 4019, 'sapientissimo', '', '', '39_7', 2), ('CONSVL', 4020, 'consule', '', '', '39_7', 15), ('ET/2', 4021, 'et', '', '', '39_7', 110), ('DILIGENS', 4022, 'diligentissimo', '', '', '39_8', 2), ('CVSTOS', 4023, 'custode', '', '', '39_8', 1), ('PAX', 4024, 'pacis', '', '', '39_8', 7), ('ATQVE/1', 4025, 'atque', '', '', '39_8', 36), ('OTIVM', 4026, 'oti', '', '', '39_8', 3), ('TAMEN', 4027, 'tamen', '', '', '39_8', 16), ('VEHEMENTER', 4028, 'uehementius', '', '', '39_8', 1), ('ARBITROR', 4029, 'arbitror', '', '', '39_9', 4), ('PERTIMESCO', 4030, 'pertimescendum', '', '', '39_9', 3), ('SI/2', 4031, 'si', '', '', '39_9', 62), ('HOMO', 4032, 'hominum', '', '', '39_9', 30), ('CLARVS', 4033, 'clarissimorum', '', '', '39_9', 6), ('AC/1', 4034, 'ac', '', '', '39_9', 26), ('POTENS', 4035, 'potentissimorum', '', '', '39_10', 2), ('AVT', 4036, 'aut', '', '', '39_10', 35), ('HONOR', 4037, 'honorem', '', '', '39_10', 10), ('MINVO', 4038, 'minuero', '', '', '39_10', 2), ('AVT', 4039, 'aut', '', '', '39_10', 35), ('STVDIVM', 4040, 'studium', '', '', '39_10', 1), ('ERGA', 4041, 'erga', '', '', '39_10', 2), ('HIC/1', 4042, 'hunc', '', '', '39_11', 69), ('ORDO', 4043, 'ordinem', '', '', '39_11', 16), ('REPVDIO', 4044, 'repudiaro', '', '', '39_11', 2), ('NAM', 4045, 'nam', '', '', '39_11', 9), ('VT/4', 4046, 'ut', '', '', '39_11', 46), ('GAIVS/N', 4047, 'C.', '', '', '39_11', 19), ('IVLIVS/N', 4048, 'Iulius', '', '', '39_11', 1), ('OMNIS', 4049, 'omnibus', '', '', '39_11', 36), ('AB', 4050, 'a', '', '', '39_11', 41), ('SENATVS', 4051, 'senatu', '', '', '39_12', 13), ('EXIMIVS', 4052, 'eximiis', '', '', '39_12', 5), ('AVT', 4053, 'aut', '', '', '39_12', 35), ('NOVVS', 4054, 'nouis', '', '', '39_12', 4), ('RES', 4055, 'rebus', '', '', '39_12', 18), ('ORNO', 4056, 'ornatus', '', '', '39_12', 6), ('PER', 4057, 'per', '', '', '39_12', 10), ('MANVS/1', 4058, 'manus', '', '', '39_12', 3), ('HIC/1', 4059, 'hanc', '', '', '39_12', 69), ('PROVINCIA', 4060, 'prouinciam', '', '', '39_13', 31), ('TRADO', 4061, 'tradat', '', '', '39_13', 4), ('IS', 4062, 'ei', '', '', '39_13', 77), ('QVI/1', 4063, 'cui', '', '', '39_13', 172), ('PARVM/2', 4064, 'minime', '', '', '39_13', 7), ('VOS', 4065, 'uos', '', '', '39_13', 31), ('VOLO/3', 4066, 'uelitis', '', '', '39_13', 17), ('PER', 4067, 'per', '', '', '39_13', 10), ('QVI/1', 4068, 'quem', '', '', '39_13', 172), ('ORDO', 4069, 'ordinem', '', '', '39_13', 16), ('IPSE', 4070, 'ipse', '', '', '39_14', 33), ('AMPLVS', 4071, 'amplissimam', '', '', '39_14', 5), ('SVM/1', 4072, 'sit <consecutus>', '', '', '39_14', 200), ('GLORIA', 4073, 'gloriam', '', '', '39_14', 4), ('CONSEQVOR', 4074, '<sit> consecutus', '', '', '39_14', 3), ('IS', 4075, 'ei', '', '', '39_14', 77), ('NE/4', 4076, 'ne', '', '', '39_14', 14), ('LIBERTAS', 4077, 'libertatem', '', '', '39_14', 1), ('QVIDEM', 4078, 'quidem', '', '', '39_15', 9), ('RELINQVO', 4079, 'relinquat', '', '', '39_15', 4), ('ADDVCO', 4080, 'adduci', '', '', '39_15', 1), ('AD/2', 4081, 'ad', '', '', '39_15', 35), ('SVSPICOR', 4082, 'suspicandum', '', '', '39_15', 2), ('NVLLVS', 4083, 'nullo', '', '', '39_15', 9), ('MODVS', 4084, 'modo', '', '', '39_15', 5), ('POSSVM/1', 4085, 'possum', '', '', '39_16', 40), ('POSTERIVS', 4086, 'postremo', '', '', '39_16', 2), ('QVIS/1', 4087, 'quo', '', '', '39_16', 31), ('QVISQVE/2', 4088, 'quisque', '', '', '39_16', 1), ('ANIMVS', 4089, 'animo', '', '', '39_16', 12), ('SVM/1', 4090, 'futurus', '', '', '39_16', 200), ('SVM/1', 4091, 'sit', '', '', '39_16', 200), ('NESCIO', 4092, 'nescio', '', '', '39_16', 1), ('QVIS/1', 4093, 'quid', '', '', '39_17', 31), ('SPERO', 4094, 'sperem', '', '', '39_17', 1), ('VIDEO', 4095, 'uideo', '', '', '39_17', 24), ('PRAESTO/1', 4096, 'praestare', '', '', '39_17', 2), ('HIC/1', 4097, 'hoc', '', '', '39_17', 69), ('SENATOR', 4098, 'senator', '', '', '39_17', 5), ('DEBEO', 4099, 'debeo', '', '', '39_17', 14), ('QVANTVM/3', 4100, 'quantum', '', '', '39_17', 3), ('POSSVM/1', 4101, 'possum', '', '', '39_18', 40), ('NE/4', 4102, 'ne', '', '', '39_18', 14), ('QVIS/2', 4103, 'quis', '', '', '39_18', 6), ('VIR', 4104, 'uir', '', '', '39_18', 14), ('CLARVS', 4105, 'clarus', '', '', '39_18', 6), ('AVT', 4106, 'aut', '', '', '39_18', 35), ('POTENS', 4107, 'potens', '', '', '39_18', 2), ('HIC/1', 4108, 'huic', '', '', 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4150, 'ac', '', '', '40_6', 26), ('PRIMVS', 4151, 'primum', '', '', '40_6', 2), ('ILLE', 4152, 'illud', '', '', '40_6', 96), ('TEMPVS/1', 4153, 'tempus', '', '', '40_6', 13), ('FAMILIARITAS', 4154, 'familiaritatis', '', '', '40_6', 1), ('ET/2', 4155, 'et', '', '', '40_6', 110), ('CONSVETVDO', 4156, 'consuetudinis', '', '', '40_6', 2), ('QVI/1', 4157, 'quae', '', '', '40_6', 172), ('EGO', 4158, 'mihi', '', '', '40_7', 88), ('CVM/2', 4159, 'cum', '', '', '40_7', 33), ('ILLE', 4160, 'illo', '', '', '40_7', 96), ('QVI/1', 4161, 'quae', '', '', '40_7', 172), ('FRATER', 4162, 'fratri', '', '', '40_7', 2), ('MEVS', 4163, 'meo', '', '', '40_7', 36), ('QVI/1', 4164, 'quae', '', '', '40_7', 172), ('GAIVS/N', 4165, 'C.', '', '', '40_7', 19), ('VARRO/N', 4166, 'Varroni', '', '', '40_7', 1), ('CONSOBRINVS', 4167, 'consobrino', '', '', '40_7', 1), ('NOSTER', 4168, 'nostro', '', '', '40_8', 17), ('AB', 4169, 'ab', '', '', '40_8', 41), ('OMNIS', 4170, 'omnium', '', '', '40_8', 36), ('NOS', 4171, 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('AMICITIA', 4191, 'amicitia', '', '', '40_11', 4), ('MANEO', 4192, 'maneremus', '', '', '40_11', 3), ('CONSVL', 4193, 'consul', '', '', '41_1', 15), ('ILLE', 4194, 'ille', '', '', '41_1', 96), ('AGO', 4195, 'egit', '', '', '41_1', 9), ('IS', 4196, 'eas', '', '', '41_1', 77), ('RES', 4197, 'res', '', '', '41_1', 18), ('QVI/1', 4198, 'quarum', '', '', '41_1', 172), ('EGO', 4199, 'me', '', '', '41_1', 88), ('PARTICEPS/2', 4200, 'participem', '', '', '41_2', 2), ('SVM/1', 4201, 'esse', '', '', '41_2', 200), ('VOLO/3', 4202, 'uoluit', '', '', '41_2', 17), ('QVI/1', 4203, 'quibus', '', '', '41_2', 172), ('EGO', 4204, 'ego', '', '', '41_2', 88), ('SI/2', 4205, 'si', '', '', '41_2', 62), ('PARVM/2', 4206, 'minus', '', '', '41_2', 7), ('ASSENTIOR', 4207, 'adsentiebar', '', '', '41_2', 4), ('TAMEN', 4208, 'tamen', '', '', '41_3', 16), ('ILLE', 4209, 'illius', '', '', '41_3', 96), ('EGO', 4210, 'mihi', '', '', '41_3', 88), ('IVDICIVM', 4211, 'iudicium', '', '', '41_3', 4), ('GRATVS', 4212, 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4233, 'quanto', '', '', '41_6', 1), ('CVM/2', 4234, 'cum', '', '', '41_6', 33), ('HONOR', 4235, 'honore', '', '', '41_6', 10), ('VOLO/3', 4236, 'uellem', '', '', '41_6', 17), ('DEFERO', 4237, 'detulit', '', '', '41_6', 1), ('QVI/1', 4238, 'quae', '', '', '41_6', 172), ('EGO', 4239, 'ego', '', '', '41_7', 88), ('OMNIS', 4240, 'omnia', '', '', '41_7', 36), ('NON', 4241, 'non', '', '', '41_7', 106), ('INGRATVS', 4242, 'ingrato', '', '', '41_7', 2), ('ANIMVS', 4243, 'animo', '', '', '41_7', 12), ('SED', 4244, 'sed', '', '', '41_7', 42), ('OBSTINATIO', 4245, 'obstinatione', '', '', '41_7', 1), ('QVIDAM', 4246, 'quadam', '', '', '41_7', 8), ('SENTENTIA', 4247, 'sententiae', '', '', '41_8', 17), ('REPVDIO', 4248, 'repudiaui', '', '', '41_8', 2), ('QVAM/1', 4249, 'quam', '', '', '41_8', 19), ('SAPIENTER', 4250, 'sapienter', '', '', '41_8', 2), ('NON', 4251, 'non', '', '', '41_8', 106), ('DISPVTO', 4252, 'disputo', '', '', '41_8', 4), ('MVLTI', 4253, 'multis', '', '', '41_8', 2), ('ENIM/2', 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5), ('PRAESIDIVM', 4275, 'praesidio', '', '', '41_11', 2), ('PROPVLSO', 4276, 'propulsare', '', '', '41_11', 1), ('POSSVM/1', 4277, 'possem', '', '', '41_11', 40), ('QVIVIS', 4278, 'quamuis', '', '', '41_12', 1), ('EXCIPIO', 4279, 'excipere', '', '', '41_12', 2), ('FORTVNA', 4280, 'fortunam', '', '', '41_12', 4), ('SVBEO/1', 4281, 'subire', '', '', '41_12', 3), ('VIS', 4282, 'uim', '', '', '41_12', 4), ('ATQVE/1', 4283, 'atque', '', '', '41_12', 36), ('INIVRIA', 4284, 'iniuriam', '', '', '41_12', 6), ('MALO', 4285, 'malui', '', '', '41_12', 3), ('QVAM/1', 4286, 'quam', '', '', '41_13', 19), ('AVT', 4287, 'aut', '', '', '41_13', 35), ('AB', 4288, 'a', '', '', '41_13', 41), ('VESTER', 4289, 'uestris', '', '', '41_13', 11), ('SANCTVS', 4290, 'sanctissimis', '', '', '41_13', 4), ('MENS', 4291, 'mentibus', '', '', '41_13', 3), ('DISSIDEO', 4292, 'dissidere', '', '', '41_13', 1), ('AVT', 4293, 'aut', '', '', '41_13', 35), ('DE', 4294, 'de', '', '', '41_13', 34), ('MEVS', 4295, 'meo', '', '', 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('IDEM', 4338, 'eodem', '', '', '41_18', 27), ('LOCVS', 4339, 'loco', '', '', '41_18', 5), ('QVI/1', 4340, 'quo', '', '', '41_18', 172), ('PRINCEPS/2', 4341, 'principem', '', '', '41_18', 4), ('CIVIS', 4342, 'ciuium', '', '', '41_19', 7), ('SVVS', 4343, 'suum', '', '', '41_19', 22), ('GENER', 4344, 'generum', '', '', '41_19', 4), ('SENTIO', 4345, 'sentiebam', '', '', '41_19', 10), ('TRADVCO', 4346, 'traduxit', '', '', '42_1', 2), ('AD/2', 4347, 'ad', '', '', '42_1', 35), ('PLEBS', 4348, 'plebem', '', '', '42_1', 5), ('INIMICVS/1', 4349, 'inimicum', '', '', '42_2', 12), ('MEVS', 4350, 'meum', '', '', '42_2', 36), ('SIVE/1', 4351, 'siue', '', '', '42_2', 2), ('IRATVS', 4352, 'iratus', '', '', '42_2', 1), ('EGO', 4353, 'mihi', '', '', '42_2', 88), ('QVOD/1', 4354, 'quod', '', '', '42_2', 20), ('EGO', 4355, 'me', '', '', '42_2', 88), ('SVI/1', 4356, 'se', '', '', '42_2', 26), ('CVM/2', 4357, 'cum', '', '', '42_2', 33), ('NE/4', 4358, 'ne', '', '', '42_2', 14), ('IN', 4359, 'in', '', '', 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4885, 'notionem', '', '', '46_5', 1), ('ET/2', 4886, 'et', '', '', '46_5', 110), ('ILLE', 4887, 'illud', '', '', '46_5', 96), ('MOS', 4888, 'morum', '', '', '46_5', 1), ('SEVERVS', 4889, 'seuerissimum', '', '', '46_5', 1), ('MAGISTERIVM', 4890, 'magisterium', '', '', '46_5', 1), ('NON', 4891, 'non', '', '', '46_6', 106), ('SVM/1', 4892, 'esse <sublatum>', '', '', '46_6', 200), ('NEFARIVS', 4893, 'nefariis', '', '', '46_6', 1), ('LEX', 4894, 'legibus', '', '', '46_6', 21), ('DE', 4895, 'de', '', '', '46_6', 34), ('CIVITAS', 4896, 'ciuitate', '', '', '46_6', 9), ('TOLLO', 4897, '<esse> sublatum', '', '', '46_6', 3), ('SI/2', 4898, 'si', '', '', '46_6', 62), ('PATRICIVS', 4899, 'patricius', '', '', '46_6', 1), ('TRIBVNVS', 4900, 'tribunus', '', '', '46_7', 5), ('PLEBS', 4901, 'plebis', '', '', '46_7', 5), ('SVM/1', 4902, 'fuerit', '', '', '46_7', 200), ('CONTRA/2', 4903, 'contra', '', '', '46_7', 9), ('LEX', 4904, 'leges', '', '', '46_7', 21), ('SACRATVS', 4905, 'sacratas', '', '', 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('REQVIRO', 4948, 'requirebant', '', '', '46_12', 1), ('LEX', 4949, 'leges', '', '', '46_12', 21), ('COMPROBO', 4950, 'comprobabant', '', '', '46_12', 1), ('IN', 4951, 'in', '', '', '46_12', 99), ('CLODIVS/N', 4952, 'Clodio', '', '', '46_12', 2), ('AVSPICIVM', 4953, 'auspiciorum', '', '', '46_13', 5), ('RATIO', 4954, 'ratio', '', '', '46_13', 11), ('SVM/1', 4955, 'sit', '', '', '46_13', 200), ('IDEM', 4956, 'eadem', '', '', '46_13', 27), ('LEX', 4957, 'leges', '', '', '46_13', 21), ('OMNIS', 4958, 'omnes', '', '', '46_13', 36), ('SVM/1', 4959, 'sint', '', '', '46_13', 200), ('EVERTO', 4960, 'euersae', '', '', '46_13', 4), ('AC/1', 4961, 'ac', '', '', '46_13', 26), ('PERDO', 4962, 'perditae', '', '', '46_14', 1), ('CIVITAS', 4963, 'ciuitatis', '', '', '46_14', 9), ('EXTER', 4964, 'extremum', '', '', '47_1', 1), ('ILLE', 4965, 'illud', '', '', '47_1', 96), ('SVM/1', 4966, 'est', '', '', '47_1', 200), ('EGO', 4967, 'ego', '', '', '47_1', 88), ('SI/2', 4968, 'si', '', '', '47_1', 62), ('SVM/1', 4969, 'essent', '', '', '47_1', 200), ('EGO', 4970, 'mihi', '', '', '47_1', 88), ('CVM/2', 4971, 'cum', '', '', '47_2', 33), ('GAIVS/N', 4972, 'C.', '', '', '47_2', 19), ('CAESAR/N', 4973, 'Caesare', '', '', '47_2', 25), ('TAMEN', 4974, 'tamen', '', '', '47_2', 16), ('HIC/1', 4975, 'hoc', '', '', '47_2', 69), ('TEMPVS/1', 4976, 'tempore', '', '', '47_2', 13), ('RESPVBLICA', 4977, 'rei publicae', '', '', '47_2', 44), ('CONSVLO', 4978, 'consulere', '', '', '47_2', 3), ('INIMICITIA', 4979, 'inimicitias', '', '', '47_3', 8), ('IN', 4980, 'in', '', '', '47_3', 99), ('ALIVS', 4981, 'aliud', '', '', '47_3', 15), ('TEMPVS/1', 4982, 'tempus', '', '', '47_3', 13), ('RESERVO', 4983, 'reseruare', '', '', '47_3', 2), ('DEBEO', 4984, 'deberem', '', '', '47_3', 14), ('POSSVM/1', 4985, 'possem', '', '', '47_3', 40), ('ETIAM', 4986, 'etiam', '', '', '47_3', 28), ('SVPERVS', 4987, 'summorum', '', '', '47_4', 13), ('VIR', 4988, 'uirorum', '', '', '47_4', 14), ('EXEMPLVM', 4989, 'exemplo', '', 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'dignitas', '', '', '47_7', 13), ('AGO', 5010, 'agitur', '', '', '47_7', 9), ('CAESAR/N', 5011, 'Caesaris', '', '', '47_7', 25), ('HOMO', 5012, 'homini', '', '', '47_7', 30), ('TRIBVO', 5013, 'tribuam', '', '', '47_7', 6), ('SI/2', 5014, 'si', '', '', '47_7', 62), ('HONOR', 5015, 'honos', '', '', '47_7', 10), ('QVIDAM', 5016, 'quidam', '', '', '47_8', 8), ('SENATVS', 5017, 'senatus', '', '', '47_8', 13), ('CONCORDIA', 5018, 'concordiae', '', '', '47_8', 1), ('CONSVLO', 5019, 'consulam', '', '', '47_8', 3), ('SI/2', 5020, 'si', '', '', '47_8', 62), ('AVCTORITAS', 5021, 'auctoritas', '', '', '47_8', 7), ('DECRETVM', 5022, 'decretorum', '', '', '47_9', 1), ('VESTER', 5023, 'uestrorum', '', '', '47_9', 11), ('CONSTANTIA', 5024, 'constantiam', '', '', '47_9', 1), ('ORDO', 5025, 'ordinis', '', '', '47_9', 16), ('IN', 5026, 'in', '', '', '47_9', 99), ('IDEM', 5027, 'eodem', '', '', '47_9', 27), ('ORNO', 5028, 'ornando', '', '', '47_9', 6), ('IMPERATOR', 5029, 'imperatore', '', '', '47_10', 14), ('SERVO', 5030, 'seruabo', '', '', '47_10', 5), ('SI/2', 5031, 'si', '', '', '47_10', 62), ('PERPETVVS', 5032, 'perpetua', '', '', '47_10', 3), ('RATIO', 5033, 'ratio', '', '', '47_10', 11), ('GALLICVS/A', 5034, 'Gallici', '', '', '47_10', 5), ('BELLVM', 5035, 'belli', '', '', '47_10', 23), ('RESPVBLICA', 5036, 'rei publicae', '', '', '47_11', 44), ('PROVIDEO', 5037, 'prouidebo', '', '', '47_11', 4), ('SI/2', 5038, 'si', '', '', '47_11', 62), ('ALIQVIS', 5039, 'aliquod', '', '', '47_11', 11), ('MEVS', 5040, 'meum', '', '', '47_11', 36), ('PRIVATVS', 5041, 'priuatum', '', '', '47_11', 1), ('OFFICIVM', 5042, 'officium', '', '', '47_11', 3), ('EGO', 5043, 'me', '', '', '47_11', 88), ('NON', 5044, 'non', '', '', '47_12', 106), ('INGRATVS', 5045, 'ingratum', '', '', '47_12', 2), ('SVM/1', 5046, 'esse', '', '', '47_12', 200), ('PRAESTO/1', 5047, 'praestabo', '', '', '47_12', 2), ('ATQVE/1', 5048, 'atque', '', '', '47_12', 36), ('HIC/1', 5049, 'hoc', '', '', '47_12', 69), ('VOLO/3', 5050, 'uelim', '', '', '47_12', 17), ('PROBO', 5051, 'probare', '', '', '47_12', 5), ('OMNIS', 5052, 'omnibus', '', '', '47_13', 36), ('PATER', 5053, 'patres', '', '', '47_13', 17), ('CONSCRIBO', 5054, 'conscripti', '', '', '47_13', 15), ('SED', 5055, 'sed', '', '', '47_13', 42), ('LEVITER', 5056, 'leuissime', '', '', '47_13', 1), ('FERO', 5057, 'feram', '', '', '47_13', 8), ('SI/2', 5058, 'si', '', '', '47_13', 62), ('FORTE', 5059, 'forte', '', '', '47_13', 1), ('AVT', 5060, 'aut', '', '', '47_13', 35), ('IS', 5061, 'iis', '', '', '47_14', 77), ('PARVM/2', 5062, 'minus', '', '', '47_14', 7), ('PROBO', 5063, 'probaro', '', '', '47_14', 5), ('QVI/1', 5064, 'qui', '', '', '47_14', 172), ('MEVS', 5065, 'meum', '', '', '47_14', 36), ('INIMICVS/1', 5066, 'inimicum', '', '', '47_14', 12), ('REPVGNO', 5067, 'repugnante', '', '', '47_14', 1), ('VESTER', 5068, 'uestra', '', '', '47_14', 11), ('AVCTORITAS', 5069, 'auctoritate', '', '', '47_15', 7), ('TEGO', 5070, 'texerunt', '', '', '47_15', 2), ('AVT', 5071, 'aut', '', '', '47_15', 35), ('IS', 5072, 'iis', '', '', '47_15', 77), ('SI/2', 5073, 'si', '', '', '47_15', 62), ('QVIS/2', 5074, 'qui', '', '', '47_15', 6), ('MEVS', 5075, 'meum', '', '', '47_15', 36), ('CVM/2', 5076, 'cum', '', '', '47_15', 33), ('INIMICVS/1', 5077, 'inimico', '', '', '47_15', 12), ('SVVS', 5078, 'suo', '', '', '47_15', 22), ('REDITVS', 5079, 'reditum', '', '', '47_16', 2), ('IN', 5080, 'in', '', '', '47_16', 99), ('GRATIA', 5081, 'gratiam', '', '', '47_16', 9), ('VITVPERO/2', 5082, 'uituperabunt', '', '', '47_16', 1), ('CVM/3', 5083, 'cum', '', '', '47_16', 29), ('IPSE', 5084, 'ipsi', '', '', '47_16', 33), ('ET/2', 5085, 'et', '', '', '47_16', 110), ('CVM/2', 5086, 'cum', '', '', '47_16', 33), ('MEVS', 5087, 'meo', '', '', '47_16', 36), ('ET/2', 5088, 'et', '', '', '47_16', 110), ('CVM/2', 5089, 'cum', '', '', '47_17', 33), ('SVVS', 5090, 'suo', '', '', '47_17', 22), ('INIMICVS/1', 5091, 'inimico', '', '', '47_17', 12), ('IN', 5092, 'in', '', '', '47_17', 99), ('GRATIA', 5093, 'gratiam', '', '', '47_17', 9), ('NON', 5094, 'non', '', '', '47_17', 106), ('DVBITO', 5095, 'dubitarint', '', '', '47_17', 3), ('REDEO/1', 5096, 'redire', '', '', '47_17', 6)]
section_list ={'1.1': 'start', '1.2': '1.1', '1.3': '1.2', '1.4': '1.3', '1.5': '1.4', '1.6': '1.5', '1.7': '1.6', '1.8': '1.7', '1.9': '1.8', '1.10': '1.9', '1.11': '1.10', '1.12': '1.11', '1.13': '1.12', '1.14': '1.13', '2.1': '1.14', '2.2': '2.1', '2.3': '2.2', '2.4': '2.3', '2.5': '2.4', '2.6': '2.5', '2.7': '2.6', '2.8': '2.7', '2.9': '2.8', '2.10': '2.9', '2.11': '2.10', '2.12': '2.11', '2.13': '2.12', '2.14': '2.13', '3.1': '2.14', '3.2': '3.1', '3.3': '3.2', '3.4': '3.3', '3.5': '3.4', '3.6': '3.5', '3.7': '3.6', '3.8': '3.7', '3.9': '3.8', '3.10': '3.9', '3.11': '3.10', '3.12': '3.11', '4.1': '3.12', '4.2': '4.1', '4.3': '4.2', '4.4': '4.3', '4.5': '4.4', '4.6': '4.5', '4.7': '4.6', '4.8': '4.7', '4.9': '4.8', '4.10': '4.9', '4.11': '4.10', '4.12': '4.11', '4.13': '4.12', '4.14': '4.13', '4.15': '4.14', '4.16': '4.15', '5.1': '4.16', '5.2': '5.1', '5.3': '5.2', '5.4': '5.3', '5.5': '5.4', '5.6': '5.5', '5.7': '5.6', '5.8': '5.7', '5.9': '5.8', '5.10': '5.9', '5.11': '5.10', '5.12': '5.11', '5.13': '5.12', '5.14': '5.13', '5.15': '5.14', '5.16': '5.15', '5.17': '5.16', '5.18': '5.17', '5.19': '5.18', '5.20': '5.19', '5.21': '5.20', '6.1': '5.21', '6.2': '6.1', '6.3': '6.2', '6.4': '6.3', '6.5': '6.4', '6.6': '6.5', '6.7': '6.6', '6.8': '6.7', '6.9': '6.8', '6.10': '6.9', '6.11': '6.10', '6.12': '6.11', '6.13': '6.12', '6.14': '6.13', '6.15': '6.14', '7.1': '6.15', '7.2': '7.1', '7.3': '7.2', '7.4': '7.3', '7.5': '7.4', '7.6': '7.5', '7.7': '7.6', '7.8': '7.7', '7.9': '7.8', '7.10': '7.9', '7.11': '7.10', '7.12': '7.11', '7.13': '7.12', '7.14': '7.13', '8.1': '7.14', '8.2': '8.1', '8.3': '8.2', '8.4': '8.3', '8.5': '8.4', '8.6': '8.5', '8.7': '8.6', '8.8': '8.7', '8.9': '8.8', '8.10': '8.9', '8.11': '8.10', '8.12': '8.11', '8.13': '8.12', '9.1': '8.13', '9.2': '9.1', '9.3': '9.2', '9.4': '9.3', '9.5': '9.4', '9.6': '9.5', '9.7': '9.6', '9.8': '9.7', '9.9': '9.8', '9.10': '9.9', '9.11': '9.10', '10.1': '9.11', '10.2': '10.1', '10.3': '10.2', '10.4': '10.3', '10.5': '10.4', '10.6': '10.5', '10.7': '10.6', '10.8': '10.7', '10.9': '10.8', '10.10': '10.9', '10.11': '10.10', '11.1': '10.11', '11.2': '11.1', '11.3': '11.2', '11.4': '11.3', '11.5': '11.4', '11.6': '11.5', '11.7': '11.6', '11.8': '11.7', '11.9': '11.8', '11.10': '11.9', '12.1': '11.10', '12.2': '12.1', '12.3': '12.2', '12.4': '12.3', '12.5': '12.4', '12.6': '12.5', '12.7': '12.6', '12.8': '12.7', '12.9': '12.8', '12.10': '12.9', '12.11': '12.10', '12.12': '12.11', '12.13': '12.12', '13.1': '12.13', '13.2': '13.1', '13.3': '13.2', '13.4': '13.3', '13.5': '13.4', '13.6': '13.5', '13.7': '13.6', '13.8': '13.7', '13.9': '13.8', '13.10': '13.9', '14.1': '13.10', '14.2': '14.1', '14.3': '14.2', '14.4': '14.3', '14.5': '14.4', '14.6': '14.5', '14.7': '14.6', '14.8': '14.7', '14.9': '14.8', '14.10': '14.9', '14.11': '14.10', '14.12': '14.11', '14.13': '14.12', '14.14': '14.13', '14.15': '14.14', '14.16': '14.15', '14.17': '14.16', '15.1': '14.17', '15.2': '15.1', '15.3': '15.2', '15.4': '15.3', '15.5': '15.4', '15.6': '15.5', '15.7': '15.6', '15.8': '15.7', '15.9': '15.8', '15.10': '15.9', '15.11': '15.10', '15.12': '15.11', '15.13': '15.12', '15.14': '15.13', '16.1': '15.14', '16.2': '16.1', '16.3': '16.2', '16.4': '16.3', '16.5': '16.4', '16.6': '16.5', '17.1': '16.6', '17.2': '17.1', '17.3': '17.2', '17.4': '17.3', '17.5': '17.4', '17.6': '17.5', '17.7': '17.6', '17.8': '17.7', '17.9': '17.8', '17.10': '17.9', '17.11': '17.10', '17.12': '17.11', '17.13': '17.12', '17.14': '17.13', '17.15': '17.14', '17.16': '17.15', '18.1': '17.16', '18.2': '18.1', '18.3': '18.2', '18.4': '18.3', '18.5': '18.4', '18.6': '18.5', '18.7': '18.6', '18.8': '18.7', '18.9': '18.8', '18.10': '18.9', '18.11': '18.10', '18.12': '18.11', '18.13': '18.12', '18.14': '18.13', '18.15': '18.14', '18.16': '18.15', '18.17': '18.16', '18.18': '18.17', '19.1': '18.18', '19.2': '19.1', '19.3': '19.2', '19.4': '19.3', '19.5': '19.4', '19.6': '19.5', '19.7': '19.6', '19.8': '19.7', '19.9': '19.8', '19.10': '19.9', '19.11': '19.10', '19.12': '19.11', '19.13': '19.12', '19.14': '19.13', '20.1': '19.14', '20.2': '20.1', '20.3': '20.2', '20.4': '20.3', '20.5': '20.4', '20.6': '20.5', '20.7': '20.6', '20.8': '20.7', '20.9': '20.8', '20.10': '20.9', '20.11': '20.10', '21.1': '20.11', '21.2': '21.1', '21.3': '21.2', '21.4': '21.3', '22.1': '21.4', '22.2': '22.1', '22.3': '22.2', '22.4': '22.3', '22.5': '22.4', '22.6': '22.5', '22.7': '22.6', '22.8': '22.7', '22.9': '22.8', '22.10': '22.9', '22.11': '22.10', '22.12': '22.11', '22.13': '22.12', '23.1': '22.13', '23.2': '23.1', '23.3': '23.2', '23.4': '23.3', '23.5': '23.4', '23.6': '23.5', '23.7': '23.6', '23.8': '23.7', '23.9': '23.8', '24.1': '23.9', '24.2': '24.1', '24.3': '24.2', '24.4': '24.3', '24.5': '24.4', '24.6': '24.5', '24.7': '24.6', '24.8': '24.7', '24.9': '24.8', '24.10': '24.9', '24.11': '24.10', '24.12': '24.11', '24.13': '24.12', '24.14': '24.13', '25.1': '24.14', '25.2': '25.1', '25.3': '25.2', '25.4': '25.3', '25.5': '25.4', '25.6': '25.5', '25.7': '25.6', '25.8': '25.7', '25.9': '25.8', '25.10': '25.9', '25.11': '25.10', '25.12': '25.11', '25.13': '25.12', '25.14': '25.13', '25.15': '25.14', '25.16': '25.15', '25.17': '25.16', '26.1': '25.17', '26.2': '26.1', '26.3': '26.2', '26.4': '26.3', '26.5': '26.4', '26.6': '26.5', '26.7': '26.6', '26.8': '26.7', '27.1': '26.8', '27.2': '27.1', '27.3': '27.2', '27.4': '27.3', '27.5': '27.4', '27.6': '27.5', '27.7': '27.6', '27.8': '27.7', '27.9': '27.8', '27.10': '27.9', '27.11': '27.10', '27.12': '27.11', '27.13': '27.12', '27.14': '27.13', '28.1': '27.14', '28.2': '28.1', '28.3': '28.2', '28.4': '28.3', '28.5': '28.4', '28.6': '28.5', '28.7': '28.6', '28.8': '28.7', '28.9': '28.8', '28.10': '28.9', '28.11': '28.10', '28.12': '28.11', '28.13': '28.12', '29.1': '28.13', '29.2': '29.1', '29.3': '29.2', '29.4': '29.3', '29.5': '29.4', '29.6': '29.5', '29.7': '29.6', '29.8': '29.7', '29.9': '29.8', '29.10': '29.9', '29.11': '29.10', '29.12': '29.11', '29.13': '29.12', '29.14': '29.13', '29.15': '29.14', '29.16': '29.15', '29.17': '29.16', '29.18': '29.17', '29.19': '29.18', '29.20': '29.19', '30.1': '29.20', '30.2': '30.1', '30.3': '30.2', '30.4': '30.3', '30.5': '30.4', '30.6': '30.5', '30.7': '30.6', '30.8': '30.7', '30.9': '30.8', '31.1': '30.9', '31.2': '31.1', '31.3': '31.2', '31.4': '31.3', '31.5': '31.4', '31.6': '31.5', '31.7': '31.6', '31.8': '31.7', '31.9': '31.8', '31.10': '31.9', '31.11': '31.10', '31.12': '31.11', '32.1': '31.12', '32.2': '32.1', '32.3': '32.2', '32.4': '32.3', '32.5': '32.4', '32.6': '32.5', '32.7': '32.6', '32.8': '32.7', '32.9': '32.8', '32.10': '32.9', '32.11': '32.10', '32.12': '32.11', '32.13': '32.12', '32.14': '32.13', '32.15': '32.14', '32.16': '32.15', '33.1': '32.16', '33.2': '33.1', '33.3': '33.2', '33.4': '33.3', '33.5': '33.4', '33.6': '33.5', '33.7': '33.6', '33.8': '33.7', '33.9': '33.8', '33.10': '33.9', '33.11': '33.10', '33.12': '33.11', '33.13': '33.12', '33.14': '33.13', '33.15': '33.14', '33.16': '33.15', '33.17': '33.16', '34.1': '33.17', '34.2': '34.1', '34.3': '34.2', '34.4': '34.3', '34.5': '34.4', '34.6': '34.5', '34.7': '34.6', '34.8': '34.7', '34.9': '34.8', '34.10': '34.9', '34.11': '34.10', '34.12': '34.11', '35.1': '34.12', '35.2': '35.1', '35.3': '35.2', '35.4': '35.3', '35.5': '35.4', '35.6': '35.5', '35.7': '35.6', '35.8': '35.7', '35.9': '35.8', '35.10': '35.9', '35.11': '35.10', '35.12': '35.11', '35.13': '35.12', '35.14': '35.13', '35.15': '35.14', '35.16': '35.15', '36.1': '35.16', '36.2': '36.1', '36.3': '36.2', '36.4': '36.3', '36.5': '36.4', '36.6': '36.5', '36.7': '36.6', '36.8': '36.7', '36.9': '36.8', '36.10': '36.9', '36.11': '36.10', '36.12': '36.11', '36.13': '36.12', '36.14': '36.13', '37.1': '36.14', '37.2': '37.1', '37.3': '37.2', '37.4': '37.3', '37.5': '37.4', '37.6': '37.5', '37.7': '37.6', '38.1': '37.7', '38.2': '38.1', '38.3': '38.2', '38.4': '38.3', '38.5': '38.4', '38.6': '38.5', '38.7': '38.6', '38.8': '38.7', '38.9': '38.8', '38.10': '38.9', '38.11': '38.10', '38.12': '38.11', '38.13': '38.12', '38.14': '38.13', '38.15': '38.14', '38.16': '38.15', '38.17': '38.16', '38.18': '38.17', '38.19': '38.18', '38.20': '38.19', '39.1': '38.20', '39.2': '39.1', '39.3': '39.2', '39.4': '39.3', '39.5': '39.4', '39.6': '39.5', '39.7': '39.6', '39.8': '39.7', '39.9': '39.8', '39.10': '39.9', '39.11': '39.10', '39.12': '39.11', '39.13': '39.12', '39.14': '39.13', '39.15': '39.14', '39.16': '39.15', '39.17': '39.16', '39.18': '39.17', '39.19': '39.18', '40.1': '39.19', '40.2': '40.1', '40.3': '40.2', '40.4': '40.3', '40.5': '40.4', '40.6': '40.5', '40.7': '40.6', '40.8': '40.7', '40.9': '40.8', '40.10': '40.9', '40.11': '40.10', '41.1': '40.11', '41.2': '41.1', '41.3': '41.2', '41.4': '41.3', '41.5': '41.4', '41.6': '41.5', '41.7': '41.6', '41.8': '41.7', '41.9': '41.8', '41.10': '41.9', '41.11': '41.10', '41.12': '41.11', '41.13': '41.12', '41.14': '41.13', '41.15': '41.14', '41.16': '41.15', '41.17': '41.16', '41.18': '41.17', '41.19': '41.18', '42.1': '41.19', '42.2': '42.1', '42.3': '42.2', '42.4': '42.3', '42.5': '42.4', '42.6': '42.5', '42.7': '42.6', '42.8': '42.7', '42.9': '42.8', '42.10': '42.9', '43.1': '42.10', '43.2': '43.1', '43.3': '43.2', '43.4': '43.3', '43.5': '43.4', '43.6': '43.5', '43.7': '43.6', '43.8': '43.7', '43.9': '43.8', '43.10': '43.9', '43.11': '43.10', '43.12': '43.11', '43.13': '43.12', '43.14': '43.13', '43.15': '43.14', '43.16': '43.15', '43.17': '43.16', '43.18': '43.17', '43.19': '43.18', '44.1': '43.19', '44.2': '44.1', '44.3': '44.2', '44.4': '44.3', '44.5': '44.4', '44.6': '44.5', '44.7': '44.6', '44.8': '44.7', '44.9': '44.8', '44.10': '44.9', '44.11': '44.10', '44.12': '44.11', '44.13': '44.12', '45.1': '44.13', '45.2': '45.1', '45.3': '45.2', '45.4': '45.3', '45.5': '45.4', '45.6': '45.5', '45.7': '45.6', '45.8': '45.7', '45.9': '45.8', '45.10': '45.9', '45.11': '45.10', '45.12': '45.11', '45.13': '45.12', '45.14': '45.13', '45.15': '45.14', '45.16': '45.15', '45.17': '45.16', '45.18': '45.17', '45.19': '45.18', '46.1': '45.19', '46.2': '46.1', '46.3': '46.2', '46.4': '46.3', '46.5': '46.4', '46.6': '46.5', '46.7': '46.6', '46.8': '46.7', '46.9': '46.8', '46.10': '46.9', '46.11': '46.10', '46.12': '46.11', '46.13': '46.12', '46.14': '46.13', '47.1': '46.14', '47.2': '47.1', '47.3': '47.2', '47.4': '47.3', '47.5': '47.4', '47.6': '47.5', '47.7': '47.6', '47.8': '47.7', '47.9': '47.8', '47.10': '47.9', '47.11': '47.10', '47.12': '47.11', '47.13': '47.12', '47.14': '47.13', '47.15': '47.14', '47.16': '47.15', '47.17': '47.16', 'end': '47.17', 'start': 'start'}
title = "Cicero, De Provinciis Consularibus"
section_level = 2
language = "Latin"
book = text.Text(title, section_words, the_text, section_list, section_level, language, False, False) | [
"[email protected]"
] | |
2627bc5bee346deeab204fa6ec44e5c9cc13abfc | 8b9e9de996cedd31561c14238fe655c202692c39 | /hackerrank/hackerrank_AntiPalindromic_Strings.py | e118373c79db90167cc964fa3d7cbc28599314dd | [] | no_license | monkeylyf/interviewjam | 0049bc1d79e6ae88ca6d746b05d07b9e65bc9983 | 33c623f226981942780751554f0593f2c71cf458 | refs/heads/master | 2021-07-20T18:25:37.537856 | 2021-02-19T03:26:16 | 2021-02-19T03:26:16 | 6,741,986 | 59 | 31 | null | null | null | null | UTF-8 | Python | false | false | 1,030 | py | """hackerrank_AntiPalindromic_Strings.py
https://www.hackerrank.com/contests/101hack19/challenges/antipalindromic-strings
"""
def main():
"""if n == 1, then there is m antipalindromic string.
if n == 2, then there is m * (m - 1) antipalindromic string
if n >= 3, then there is m * (m - 1) * (m - 1)...
Then all you need to do is to implement pow with mod and multi with mod.
"""
t = int(raw_input())
for _ in xrange(t):
n, m = map(int, raw_input().split())
if n == 1:
print m
elif n == 2:
print multi_mod(m, m - 1)
else:
print multi_mod(multi_mod(m, m - 1), pow_mod(m - 2, n - 2))
def multi_mod(a, b, mod=10**9+7):
return ((a % mod) * (b % mod)) % mod
def pow_mod(a, n, mod=10**9+7):
if n == 0:
return 1
base = a
ret = 1
while n:
if n % 2 == 1:
ret = (ret *base) % mod
base = (base * base) % mod
n /= 2
return ret
if __name__ == '__main__':
main()
| [
"[email protected]"
] | |
fd9051b479df526f24d4937d65fc91e13c2b0021 | 837fcd0d7e40de15f52c73054709bd40264273d2 | /More_exercise-master/Repeated_element_list.py | db01da889fb9c8d678166fab52513a0e563108a2 | [] | no_license | NEHAISRANI/Python_Programs | dee9e05ac174a4fd4dd3ae5e96079e10205e18f9 | aa108a56a0b357ca43129e59377ac35609919667 | refs/heads/master | 2020-11-25T07:20:00.484973 | 2020-03-08T12:17:39 | 2020-03-08T12:17:39 | 228,554,399 | 0 | 1 | null | 2020-10-01T06:41:20 | 2019-12-17T07:04:31 | Python | UTF-8 | Python | false | false | 477 | py | list1 = [1, 342, 75, 23, 98]
list2 = [75, 23, 98, 12, 78, 10, 1]
index=0
new=[]
while index<len(list1):
if list1[index] in list2:
new.append(list1[index])
index=index+1
new.sort()
print new
#"-------------------"
# without in operator
index=0
new=[]
while index<len(list1):
var1=0
while var1<len(list2):
if list1[index]==list2[var1]:
new.append(list1[index])
var1=var1+1
index=index+1
new.sort()
print new | [
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] | |
e6c242f7656466c344365678cdf6869daa23683b | 8dbb2a3e2286c97b1baa3ee54210189f8470eb4d | /kubernetes-stubs/client/models/v2beta2_metric_target.pyi | e58a49afa7ff802b89fffd13f6b7a5441e8e92a4 | [] | no_license | foodpairing/kubernetes-stubs | e4b0f687254316e6f2954bacaa69ff898a88bde4 | f510dc3d350ec998787f543a280dd619449b5445 | refs/heads/master | 2023-08-21T21:00:54.485923 | 2021-08-25T03:53:07 | 2021-08-25T04:45:17 | 414,555,568 | 0 | 0 | null | 2021-10-07T10:26:08 | 2021-10-07T10:26:08 | null | UTF-8 | Python | false | false | 694 | pyi | import datetime
import typing
import kubernetes.client
class V2beta2MetricTarget:
average_utilization: typing.Optional[int]
average_value: typing.Optional[str]
type: str
value: typing.Optional[str]
def __init__(
self,
*,
average_utilization: typing.Optional[int] = ...,
average_value: typing.Optional[str] = ...,
type: str,
value: typing.Optional[str] = ...
) -> None: ...
def to_dict(self) -> V2beta2MetricTargetDict: ...
class V2beta2MetricTargetDict(typing.TypedDict, total=False):
averageUtilization: typing.Optional[int]
averageValue: typing.Optional[str]
type: str
value: typing.Optional[str]
| [
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] | |
9f4ade293e4deed7bf08590e33fecbb9a8b287d9 | 35b58dedc97622b1973456d907ede6ab86c0d966 | /Test/2020年4月29日/001.py | c8895768d64c6ebb9f086308a28346ccff33c6e5 | [] | no_license | GithubLucasSong/PythonProject | 7bb2bcc8af2de725b2ed9cc5bfedfd64a9a56635 | e3602b4cb8af9391c6dbeaebb845829ffb7ab15f | refs/heads/master | 2022-11-23T05:32:44.622532 | 2020-07-24T08:27:12 | 2020-07-24T08:27:12 | 282,165,132 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 595 | py | # import re
# import json
# sss = '{"testfan-token": "${neeo_001>data>data}$"}'
#
# find = re.findall('\${.*?}\$',sss)
#
# for i in find:
# find = i
# print(find)
#
# print(re.sub(find,'1',sss))
import requests
# response = requests.request(method='get', url='http://www.neeo.cc:6002/pinter/bank/api/query2',params={"userName": "admin"},headers={"testfan-token": "c818ced87fb94411a5c1db99672ec3d7"})
# print(response.json())
response = requests.request(method='post', url='http://www.neeo.cc:6002/pinter/bank/api/login',data={"userName": "admin", "password": "1234"})
print(response.j) | [
"[email protected]"
] | |
f373f7fb41cef8b368430594ebbdee6e8ea6d030 | 30ab9750e6ca334941934d1727c85ad59e6b9c8a | /zentral/contrib/nagios/events/__init__.py | 32a043fbbf1aebc95d5d5f0da9196c0e025d5d16 | [
"Apache-2.0"
] | permissive | ankurvaishley/zentral | 57e7961db65278a0e614975e484927f0391eeadd | a54769f18305c3fc71bae678ed823524aaa8bb06 | refs/heads/main | 2023-05-31T02:56:40.309854 | 2021-07-01T07:51:31 | 2021-07-01T14:15:34 | 382,346,360 | 1 | 0 | Apache-2.0 | 2021-07-02T12:55:47 | 2021-07-02T12:55:47 | null | UTF-8 | Python | false | false | 1,158 | py | import logging
from zentral.core.events import event_cls_from_type, register_event_type
from zentral.core.events.base import BaseEvent
logger = logging.getLogger('zentral.contrib.nagios.events')
ALL_EVENTS_SEARCH_DICT = {"tag": "nagios"}
class NagiosEvent(BaseEvent):
tags = ["nagios"]
class NagiosHostEvent(NagiosEvent):
event_type = "nagios_host_event"
register_event_type(NagiosHostEvent)
class NagiosServiceEvent(NagiosEvent):
event_type = "nagios_service_event"
register_event_type(NagiosServiceEvent)
def post_nagios_event(nagios_instance, user_agent, ip, data):
event_type = data.pop("event_type", None)
if not event_type:
logger.warning("Missing event_type in nagios event payload")
return
elif event_type not in ['nagios_host_event', 'nagios_service_event']:
logger.warning("Wrong event_type %s in nagios event payload", event_type)
return
data["nagios_instance"] = {"id": nagios_instance.id,
"url": nagios_instance.url}
event_cls = event_cls_from_type(event_type)
event_cls.post_machine_request_payloads(None, user_agent, ip, [data])
| [
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] | |
a5febbe7a5eedfbbabe6af1b6c0a253823fdc6b5 | 16b389c8dcace7f7d010c1fcf57ae0b3f10f88d3 | /docs/jnpr_healthbot_swagger/test/test_topic_schema_variable.py | d8cf50a23cf30844a79d2a6d4c4d3e87e9c010c1 | [
"Apache-2.0"
] | permissive | Juniper/healthbot-py-client | e4e376b074920d745f68f19e9309ede0a4173064 | 0390dc5d194df19c5845b73cb1d6a54441a263bc | refs/heads/master | 2023-08-22T03:48:10.506847 | 2022-02-16T12:21:04 | 2022-02-16T12:21:04 | 210,760,509 | 10 | 5 | Apache-2.0 | 2022-05-25T05:48:55 | 2019-09-25T05:12:35 | Python | UTF-8 | Python | false | false | 955 | py | # coding: utf-8
"""
Healthbot APIs
API interface for Healthbot application # noqa: E501
OpenAPI spec version: 3.1.0
Contact: [email protected]
Generated by: https://github.com/swagger-api/swagger-codegen.git
"""
from __future__ import absolute_import
import unittest
import swagger_client
from swagger_client.models.topic_schema_variable import TopicSchemaVariable # noqa: E501
from swagger_client.rest import ApiException
class TestTopicSchemaVariable(unittest.TestCase):
"""TopicSchemaVariable unit test stubs"""
def setUp(self):
pass
def tearDown(self):
pass
def testTopicSchemaVariable(self):
"""Test TopicSchemaVariable"""
# FIXME: construct object with mandatory attributes with example values
# model = swagger_client.models.topic_schema_variable.TopicSchemaVariable() # noqa: E501
pass
if __name__ == '__main__':
unittest.main()
| [
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] | |
60154971e033303df3ec37c5af4870bd330cbc8c | aabcf7b509608af70ce9fa6e7665837f6b6984b0 | /bincrafters_envy/main.py | 14ef7546bb5c5216fd5a45f5e21aae151fb2df3d | [
"MIT"
] | permissive | bincrafters/bincrafters-envy | 2573177e83c8ec0687eff9c76cbc0c79b1a4135c | 584ea39c16927ca3d1ffc68b32ec8d77627c27e0 | refs/heads/develop | 2023-06-08T10:55:37.920810 | 2019-07-26T08:35:48 | 2019-07-26T08:35:48 | 113,282,817 | 1 | 0 | MIT | 2023-06-01T12:24:40 | 2017-12-06T07:21:00 | Python | UTF-8 | Python | false | false | 266 | py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import sys
if sys.version_info.major == 3:
from bincrafters_envy import bincrafters_envy
else:
import bincrafters_envy
def run():
bincrafters_envy.main(sys.argv[1:])
if __name__ == '__main__':
run()
| [
"[email protected]"
] | |
c867e8178c3e307027a310c680b5dc60c0a7aeba | 7395af9906200bb7135201ede8e238c0afb46c65 | /public_api/api_requests/create_transaction.py | 6edaac4ade0a40754dce2345e1b754c36cfb54fa | [] | no_license | bellomusodiq/public-api | 6fd21d91f9df4e1ef75d2f43f3d2ad59afc1f30c | 20b59ecc67ac6c969a9c47991f385e538762c2a6 | refs/heads/master | 2023-01-02T05:30:53.797873 | 2020-10-27T20:19:51 | 2020-10-27T20:19:51 | 305,782,966 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,364 | py | import requests
import json
import random
import string
from .config import base_url
def generate_random_string():
choices = string.ascii_letters + string.digits
string_ = ''
for _ in range(20):
string_ += random.choice(choices)
return string_
url = "{}/test/transactions".format(base_url)
def create_transaction(access_token, investor_id, instructions,
trade_date_limit, trade_action, trade_price_limit, trade_effective_date,
trade_units, stock_code):
payload = {
"investor_id":investor_id,
"transaction_ref":"s-{}".format(generate_random_string()),
"cscs_number": "67393940",
"instructions": instructions,
"trade_date_limit": trade_date_limit,
"trade_effective_date": trade_effective_date,
"trade_action": trade_action,
"trade_price_limit": str(trade_price_limit),
"trade_units": str(trade_units),
"stock_code": stock_code,
"trade_account_type":"INVESTOR"
}
headers = {
'authorization': 'Bearer {}'.format(access_token),
'content-type': 'application/json'
}
response = requests.request("POST", url, headers=headers, data = json.dumps(payload))
return response.json()
"""
b'{"status":200,"message":"success","trade_status":"Success","transaction_ref":"s-x12daeadvd"}'
b'{"status":400,"errors":["This Investor does not exist"]}'
"""
| [
"[email protected]"
] | |
77c35e61da685b86d7d099062b817c4d4650011c | aee144770c8f4ec5987777aebe5b064e558fc474 | /doc/integrations/pytorch/parlai/tasks/mnist_qa/agents.py | df1f01e28be9434fde8528ad3cb0ea9b583c46d5 | [
"CC-BY-SA-3.0",
"MIT",
"Apache-2.0",
"AGPL-3.0-only"
] | permissive | adgang/cortx | 1d8e6314643baae0e6ee93d4136013840ead9f3b | a73e1476833fa3b281124d2cb9231ee0ca89278d | refs/heads/main | 2023-04-22T04:54:43.836690 | 2021-05-11T00:39:34 | 2021-05-11T00:39:34 | 361,394,462 | 1 | 0 | Apache-2.0 | 2021-04-25T10:12:59 | 2021-04-25T10:12:59 | null | UTF-8 | Python | false | false | 2,362 | py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
This is a simple question answering task on the MNIST dataset. In each episode, agents
are presented with a number, which they are asked to identify.
Useful for debugging and checking that one's image model is up and running.
"""
from parlai.core.teachers import DialogTeacher
from parlai.utils.io import PathManager
from .build import build
import json
import os
def _path(opt):
build(opt)
dt = opt['datatype'].split(':')[0]
labels_path = os.path.join(opt['datapath'], 'mnist', dt, 'labels.json')
image_path = os.path.join(opt['datapath'], 'mnist', dt)
return labels_path, image_path
class MnistQATeacher(DialogTeacher):
"""
This version of MNIST inherits from the core Dialog Teacher, which just requires it
to define an iterator over its data `setup_data` in order to inherit basic metrics,
a `act` function, and enables Hogwild training with shared memory with no extra
work.
"""
def __init__(self, opt, shared=None):
self.datatype = opt['datatype'].split(':')[0]
labels_path, self.image_path = _path(opt)
opt['datafile'] = labels_path
self.id = 'mnist_qa'
self.num_strs = [
'zero',
'one',
'two',
'three',
'four',
'five',
'six',
'seven',
'eight',
'nine',
]
super().__init__(opt, shared)
def label_candidates(self):
return [str(x) for x in range(10)] + self.num_strs
def setup_data(self, path):
print('loading: ' + path)
with PathManager.open(path) as labels_file:
self.labels = json.load(labels_file)
self.question = 'Which number is in the image?'
episode_done = True
for i in range(len(self.labels)):
img_path = os.path.join(self.image_path, '%05d.bmp' % i)
label = [self.labels[i], self.num_strs[int(self.labels[i])]]
yield (self.question, label, None, None, img_path), episode_done
class DefaultTeacher(MnistQATeacher):
pass
| [
"[email protected]"
] | |
0be675f1f85ba5f732fc877fca398ee196184613 | 52b5773617a1b972a905de4d692540d26ff74926 | /.history/fibo_20200709155400.py | 3b16f98c3d18b786e0d8adc98afc754847029ae4 | [] | no_license | MaryanneNjeri/pythonModules | 56f54bf098ae58ea069bf33f11ae94fa8eedcabc | f4e56b1e4dda2349267af634a46f6b9df6686020 | refs/heads/master | 2022-12-16T02:59:19.896129 | 2020-09-11T12:05:22 | 2020-09-11T12:05:22 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 191 | py | # solving the fibonaci sequence using recursion and dynamic programming
# Recursion
# Base case if n = 1 || n == 2 then fibo is 1
def fibo(n):
if n == 1:
result = 1
| [
"[email protected]"
] | |
d6f72acbd5a87945e02e30a1fbc7fa53ce292903 | 724317c256e3c57e8573f74334be31f39ba34eb9 | /scripts/graphquestions/insert_to_db.py | 08cadc30d76f276e8821af87e44558d87e2df6ee | [
"Apache-2.0"
] | permissive | pkumar2618/UDepLambda | a36662014fc23465aff587761810b986e4dad6dd | 08f00b7dc99bb06c6912e9e83f47c32ebdd38eff | refs/heads/master | 2022-11-25T09:22:41.444891 | 2020-08-01T08:56:52 | 2020-08-01T08:56:52 | 282,916,873 | 0 | 0 | Apache-2.0 | 2020-07-27T14:09:32 | 2020-07-27T14:09:32 | null | UTF-8 | Python | false | false | 474 | py | #!/usr/bin/python
import MySQLdb
# connect
db = MySQLdb.connect(host="rudisha.inf.ed.ac.uk", user="root", passwd="ammuma1234", db="gq_german")
cursor = db.cursor()
# execute SQL select statement
cursor.execute("SELECT * FROM sentences")
# commit your changes
db.commit()
# get the number of rows in the resultset
numrows = int(cursor.rowcount)
# get and display one row at a time.
for x in range(0,numrows):
row = cursor.fetchone()
print row[0], "-->", row[1]
| [
"[email protected]"
] | |
e019f16db7ba4fbd11cc190bd1425769fda97daa | 9d5b0bcc105f7a99e545dd194d776a8f37b08501 | /tf_quant_finance/math/integration/simpson.py | d011b774ef2f030af974719aec196bfd567db508 | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla",
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause"
] | permissive | priyalorha/tf-quant-finance | ab082a9bd6d22fd3ea9a3adcf67a35dc23460588 | 72ce8231340b27b047279012ffe97aeb79117cdf | refs/heads/master | 2023-02-23T11:08:30.161283 | 2021-02-01T13:57:43 | 2021-02-01T13:58:14 | 334,980,881 | 1 | 0 | Apache-2.0 | 2021-02-01T14:45:14 | 2021-02-01T14:45:14 | null | UTF-8 | Python | false | false | 3,828 | py | # Lint as: python3
# Copyright 2019 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Composite Simpson's algorithm for numeric integration."""
import tensorflow.compat.v2 as tf
def simpson(func, lower, upper, num_points=1001, dtype=None, name=None):
"""Evaluates definite integral using composite Simpson's 1/3 rule.
Integrates `func` using composite Simpson's 1/3 rule [1].
Evaluates function at points of evenly spaced grid of `num_points` points,
then uses obtained values to interpolate `func` with quadratic polynomials
and integrates these polynomials.
#### References
[1] Weisstein, Eric W. "Simpson's Rule." From MathWorld - A Wolfram Web
Resource. http://mathworld.wolfram.com/SimpsonsRule.html
#### Example
```python
f = lambda x: x*x
a = tf.constant(0.0)
b = tf.constant(3.0)
integrate(f, a, b, num_points=1001) # 9.0
```
Args:
func: Python callable representing a function to be integrated. It must be a
callable of a single `Tensor` parameter and return a `Tensor` of the same
shape and dtype as its input. It will be called with a `Tesnor` of shape
`lower.shape + [n]` (where n is integer number of points) and of the same
`dtype` as `lower`.
lower: `Tensor` or Python float representing the lower limits of
integration. `func` will be integrated between each pair of points defined
by `lower` and `upper`.
upper: `Tensor` of the same shape and dtype as `lower` or Python float
representing the upper limits of intergation.
num_points: Scalar int32 `Tensor`. Number of points at which function `func`
will be evaluated. Must be odd and at least 3.
Default value: 1001.
dtype: Optional `tf.Dtype`. If supplied, the dtype for the `lower` and
`upper`. Result will have the same dtype.
Default value: None which maps to dtype of `lower`.
name: Python str. The name to give to the ops created by this function.
Default value: None which maps to 'integrate_simpson_composite'.
Returns:
`Tensor` of shape `func_batch_shape + limits_batch_shape`, containing
value of the definite integral.
"""
with tf.compat.v1.name_scope(
name, default_name='integrate_simpson_composite', values=[lower, upper]):
lower = tf.convert_to_tensor(lower, dtype=dtype, name='lower')
dtype = lower.dtype
upper = tf.convert_to_tensor(upper, dtype=dtype, name='upper')
num_points = tf.convert_to_tensor(
num_points, dtype=tf.int32, name='num_points')
assertions = [
tf.debugging.assert_greater_equal(num_points, 3),
tf.debugging.assert_equal(num_points % 2, 1),
]
with tf.compat.v1.control_dependencies(assertions):
dx = (upper - lower) / (tf.cast(num_points, dtype=dtype) - 1)
dx_expand = tf.expand_dims(dx, -1)
lower_exp = tf.expand_dims(lower, -1)
grid = lower_exp + dx_expand * tf.cast(tf.range(num_points), dtype=dtype)
weights_first = tf.constant([1.0], dtype=dtype)
weights_mid = tf.tile(
tf.constant([4.0, 2.0], dtype=dtype), [(num_points - 3) // 2])
weights_last = tf.constant([4.0, 1.0], dtype=dtype)
weights = tf.concat([weights_first, weights_mid, weights_last], axis=0)
return tf.reduce_sum(func(grid) * weights, axis=-1) * dx / 3
| [
"[email protected]"
] | |
46914611421331bc8c3b99a2f18da0e2a7b11766 | eb3c6e228a05e773fad89b42da0f54a1febbd096 | /plenum/bls/bls_bft_utils.py | 67d709cfdbd21e7a593db606e4930394d7383904 | [
"Apache-2.0"
] | permissive | amitkumarj441/indy-plenum | 1f45e0c095b9aa27e8306e29c896aa1441a20229 | 7cbcdecd5e6e290530fe0d5e02d9ea70ab1c9516 | refs/heads/master | 2021-07-21T02:19:24.219993 | 2017-10-27T08:48:03 | 2017-10-27T08:48:03 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 204 | py |
def create_full_root_hash(root_hash, pool_root_hash):
"""
Utility method for creating full root hash that then can be signed
by multi signature
"""
return root_hash + pool_root_hash
| [
"[email protected]"
] | |
5f3ef402e43e381527b710f81ee8970f9ac7c5a1 | aaa204ad7f134b526593c785eaa739bff9fc4d2a | /tests/system/providers/google/marketing_platform/example_analytics.py | 0d8f94ec38e552ad8bfc9ef564376ae17a7b7d4e | [
"Apache-2.0",
"BSD-3-Clause",
"MIT"
] | permissive | cfei18/incubator-airflow | 913b40efa3d9f1fdfc5e299ce2693492c9a92dd4 | ffb2078eb5546420864229cdc6ee361f89cab7bd | refs/heads/master | 2022-09-28T14:44:04.250367 | 2022-09-19T16:50:23 | 2022-09-19T16:50:23 | 88,665,367 | 0 | 1 | Apache-2.0 | 2021-02-05T16:29:42 | 2017-04-18T20:00:03 | Python | UTF-8 | Python | false | false | 3,724 | py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
"""
Example Airflow DAG that shows how to use Google Analytics 360.
"""
from __future__ import annotations
import os
from datetime import datetime
from airflow import models
from airflow.providers.google.marketing_platform.operators.analytics import (
GoogleAnalyticsDataImportUploadOperator,
GoogleAnalyticsDeletePreviousDataUploadsOperator,
GoogleAnalyticsGetAdsLinkOperator,
GoogleAnalyticsListAccountsOperator,
GoogleAnalyticsModifyFileHeadersDataImportOperator,
GoogleAnalyticsRetrieveAdsLinksListOperator,
)
ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
DAG_ID = "example_google_analytics"
ACCOUNT_ID = os.environ.get("GA_ACCOUNT_ID", "123456789")
BUCKET = os.environ.get("GMP_ANALYTICS_BUCKET", "test-airflow-analytics-bucket")
BUCKET_FILENAME = "data.csv"
WEB_PROPERTY_ID = os.environ.get("GA_WEB_PROPERTY", "UA-12345678-1")
WEB_PROPERTY_AD_WORDS_LINK_ID = os.environ.get("GA_WEB_PROPERTY_AD_WORDS_LINK_ID", "rQafFTPOQdmkx4U-fxUfhj")
DATA_ID = "kjdDu3_tQa6n8Q1kXFtSmg"
with models.DAG(
DAG_ID,
schedule='@once', # Override to match your needs,
start_date=datetime(2021, 1, 1),
catchup=False,
tags=["example", "analytics"],
) as dag:
# [START howto_marketing_platform_list_accounts_operator]
list_account = GoogleAnalyticsListAccountsOperator(task_id="list_account")
# [END howto_marketing_platform_list_accounts_operator]
# [START howto_marketing_platform_get_ads_link_operator]
get_ad_words_link = GoogleAnalyticsGetAdsLinkOperator(
web_property_ad_words_link_id=WEB_PROPERTY_AD_WORDS_LINK_ID,
web_property_id=WEB_PROPERTY_ID,
account_id=ACCOUNT_ID,
task_id="get_ad_words_link",
)
# [END howto_marketing_platform_get_ads_link_operator]
# [START howto_marketing_platform_retrieve_ads_links_list_operator]
list_ad_words_link = GoogleAnalyticsRetrieveAdsLinksListOperator(
task_id="list_ad_link", account_id=ACCOUNT_ID, web_property_id=WEB_PROPERTY_ID
)
# [END howto_marketing_platform_retrieve_ads_links_list_operator]
upload = GoogleAnalyticsDataImportUploadOperator(
task_id="upload",
storage_bucket=BUCKET,
storage_name_object=BUCKET_FILENAME,
account_id=ACCOUNT_ID,
web_property_id=WEB_PROPERTY_ID,
custom_data_source_id=DATA_ID,
)
delete = GoogleAnalyticsDeletePreviousDataUploadsOperator(
task_id="delete",
account_id=ACCOUNT_ID,
web_property_id=WEB_PROPERTY_ID,
custom_data_source_id=DATA_ID,
)
transform = GoogleAnalyticsModifyFileHeadersDataImportOperator(
task_id="transform",
storage_bucket=BUCKET,
storage_name_object=BUCKET_FILENAME,
)
upload >> [delete, transform]
from tests.system.utils import get_test_run # noqa: E402
# Needed to run the example DAG with pytest (see: tests/system/README.md#run_via_pytest)
test_run = get_test_run(dag)
| [
"[email protected]"
] | |
f706c41962f21c4b764b0b4ccea05a2eed8290b9 | 881ca022fb16096610b4c7cec84910fbd304f52b | /libs/scapy/contrib/__init__.py | d1ce31ce09076bfc086bfb4b8be14c6235ba16f5 | [] | no_license | mdsakibur192/esp32_bluetooth_classic_sniffer | df54a898c9b4b3e2b5d85b1c00dd597d52844d9f | 7e8be27455f1d271fb92c074cb5118cc43854561 | refs/heads/master | 2023-07-31T14:29:22.989311 | 2021-09-08T11:18:21 | 2021-09-08T11:18:21 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 272 | py | # This file is part of Scapy
# See http://www.secdev.org/projects/scapy for more information
# Copyright (C) Philippe Biondi <[email protected]>
# This program is published under a GPLv2 license
"""
Package of contrib modules that have to be loaded explicitly.
"""
| [
"[email protected]"
] | |
a693f848a13454a6cfa0984f201bdd2971733ff4 | a39d0d1f0e257d0fff5de58e3959906dafb45347 | /PythonTricks/DataStructures/arays.py | 4dd812657bd50c08d6dda6321c7d0a1f08ba79a0 | [] | no_license | Twishar/Python | 998d7b304070b621ca7cdec548156ca7750ef38e | 1d1afa79df1aae7b48ac690d9b930708767b6d41 | refs/heads/master | 2021-09-23T14:18:36.195494 | 2018-09-24T12:33:36 | 2018-09-24T12:33:36 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 768 | py | import array
arr = ['one', 'two', 'three']
print(arr[0])
print(arr)
# Lists are mutable:
arr[1] = 'hello'
print(arr)
del arr[1]
print(arr)
# Lists can hold arbitrary data types:
arr.append(23)
print(arr)
# Tuple - immutable containers
arr = 'one', 'two', 'three'
print(arr[0])
print(arr)
# arr[1] = 'hello'
# del arr[1]
# Tuples can hold arbitrary data types:
# Adding elements creates a copy of the tuple
print(arr + (23,))
arr = array.array('f', (1.0, 1.5, 2.0, 2.5))
print(arr[1])
arr[1] = 23.9
print(arr)
del arr[1]
arr.append(42.94)
# Arrays are "typed"
# arr[1] = 'hello'
# STR
arr = 'abcd'
# string are immutable
print(list('abcd'))
# bytes - immutable Arrays of Single Bytes
arr_b = bytes((0, 1, 2, 3))
print(arr_b)
# arr[1] = 23
# del arr[1]
| [
"[email protected]"
] | |
f704cf61cb51810d863d902fd775d9cbbf0da782 | ca7aa979e7059467e158830b76673f5b77a0f5a3 | /Python_codes/p02238/s136410577.py | efae5c2b562906dd438512222d9cbfb70501d96a | [] | no_license | Aasthaengg/IBMdataset | 7abb6cbcc4fb03ef5ca68ac64ba460c4a64f8901 | f33f1c5c3b16d0ea8d1f5a7d479ad288bb3f48d8 | refs/heads/main | 2023-04-22T10:22:44.763102 | 2021-05-13T17:27:22 | 2021-05-13T17:27:22 | 367,112,348 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 744 | py | #coding: utf-8
n = int(input())
color = ["white" for i in range(n)]
d = [[] for i in range(n)]
global t
t = 0
M = [[False for i in range(n)] for j in range(n)]
for i in range(n):
data = list(map(int,input().split()))
u = data[0]
k = data[1]
if i == 0:
start = u
for v in data[2:2+k]:
M[u-1][v-1] = True
def search(u,t):
t += 1
color[u-1] = "gray"
d[u-1].append(t)
for v in range(1,n+1):
if M[u-1][v-1] and color[v-1] == "white":
t = search(v,t)
color[u-1] = "black"
t += 1
d[u-1].append(t)
return t
t = search(start, t)
for i in range(1,n+1):
if color[i-1] == "white":
t = search(i, t)
for i in range(n):
print(i+1, d[i][0], d[i][1])
| [
"[email protected]"
] | |
aa4a7a7bec6c8d765c3e813b46ac392fb2f243d9 | 98032c5363d0904ba44e1b5c1b7aa0d31ed1d3f2 | /Chapter10/ch10/race_with_lock.py | 5b939cb8db37805feba1ecc83d58524902c0916b | [
"MIT"
] | permissive | PacktPublishing/Learn-Python-Programming-Second-Edition | 7948b309f6e8b146a5eb5e8690b7865cb76136d5 | 54fee44ff1c696df0c7da1e3e84a6c2271a78904 | refs/heads/master | 2023-05-12T08:56:52.868686 | 2023-01-30T09:59:05 | 2023-01-30T09:59:05 | 138,018,499 | 65 | 44 | MIT | 2023-02-15T20:04:34 | 2018-06-20T10:41:13 | Jupyter Notebook | UTF-8 | Python | false | false | 576 | py | import threading
from time import sleep
from random import random
counter = 0
randsleep = lambda: sleep(0.1 * random())
def incr(n):
global counter
for count in range(n):
with incr_lock:
current = counter
randsleep()
counter = current + 1
randsleep()
n = 5
incr_lock = threading.Lock()
t1 = threading.Thread(target=incr, args=(n, ))
t2 = threading.Thread(target=incr, args=(n, ))
t1.start()
t2.start()
t1.join()
t2.join()
print(f'Counter: {counter}')
"""
$ python race.py
Counter: 10 # every time
"""
| [
"[email protected]"
] | |
d448574fb3725a8d6dc5fef6401a51fda2584702 | 70fa6468c768d4ec9b4b14fc94fa785da557f1b5 | /lib/googlecloudsdk/command_lib/error_reporting/exceptions.py | 0ff475910503910e5c0b0a043a2e41e2f0aa50de | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | permissive | kylewuolle/google-cloud-sdk | d43286ef646aec053ecd7eb58566ab2075e04e76 | 75f09ebe779e99fdc3fd13b48621fe12bfaa11aa | refs/heads/master | 2020-04-20T22:10:41.774132 | 2019-01-26T09:29:26 | 2019-01-26T09:29:26 | 169,131,028 | 0 | 0 | NOASSERTION | 2019-02-04T19:04:40 | 2019-02-04T18:58:36 | Python | UTF-8 | Python | false | false | 1,036 | py | # -*- coding: utf-8 -*- #
# Copyright 2016 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Exceptions for the error-reporting surface."""
from __future__ import absolute_import
from __future__ import division
from __future__ import unicode_literals
from googlecloudsdk.core import exceptions
class CannotOpenFileError(exceptions.Error):
"""Cannot open file."""
def __init__(self, f, e):
super(CannotOpenFileError, self).__init__(
'Failed to open file [{f}]: {e}'.format(f=f, e=e))
| [
"[email protected]"
] | |
9ca578dfa4481209f802f09fe1f2d284c66c4342 | 86fc644c327a8d6ea66fd045d94c7733c22df48c | /scripts/managed_cpe_services/customer/single_cpe_site/single_cpe_site_services/cpe_lan/end_points/end_points.py | c1ba06f6470036abac86a2fa5229dae0de42c9a8 | [] | no_license | lucabrasi83/anutacpedeployment | bfe703657fbcf0375c92bcbe7560051817f1a526 | 96de3a4fd4adbbc0d443620f0c53f397823a1cad | refs/heads/master | 2021-09-24T16:44:05.305313 | 2018-10-12T02:41:18 | 2018-10-12T02:41:18 | 95,190,459 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 16,803 | py | #
# This computer program is the confidential information and proprietary trade
# secret of Anuta Networks, Inc. Possessions and use of this program must
# conform strictly to the license agreement between the user and
# Anuta Networks, Inc., and receipt or possession does not convey any rights
# to divulge, reproduce, or allow others to use this program without specific
# written authorization of Anuta Networks, Inc.
#
# Copyright (c) 2015-2016 Anuta Networks, Inc. All Rights Reserved.
#
#
#DO NOT EDIT THIS FILE ITS AUTOGENERATED ONE
#ALL THE CUSTOMIZATIONS REGARDING DATAPROCESSING SHOULD BE WRITTEN INTO service_customization.py FILE
#
"""
Tree Structure of Handled XPATH:
services
|
managed-cpe-services
|
customer
|
single-cpe-site
|
single-cpe-site-services
|
cpe-lan
|
end-points
Schema Representation:
/services/managed-cpe-services/customer/single-cpe-site/single-cpe-site-services/cpe-lan/end-points
"""
from servicemodel import util
from servicemodel import yang
from servicemodel import devicemgr
from cpedeployment.cpedeployment_lib import getLocalObject
from cpedeployment.cpedeployment_lib import getDeviceObject
from cpedeployment.cpedeployment_lib import getCurrentObjectConfig
from cpedeployment.cpedeployment_lib import getPreviousObjectConfig
from cpedeployment.cpedeployment_lib import ServiceModelContext
from cpedeployment.cpedeployment_lib import getParentObject
from cpedeployment.cpedeployment_lib import log
import service_customization
class EndPoints(yang.AbstractYangServiceHandler):
_instance = None
def __init__(self):
self.delete_pre_processor = service_customization.DeletePreProcessor()
self.create_pre_processor = service_customization.CreatePreProcessor()
def create(self, id, sdata):
sdata.getSession().addYangSessionPreReserveProcessor(self.create_pre_processor)
#Fetch Local Config Object
config = getCurrentObjectConfig(id, sdata, 'end_points')
#Fetch Service Model Context Object
smodelctx = None
#Fetch Parent Object
parentobj = None
dev = None
devbindobjs={}
inputdict = {}
# START OF FETCHING THE LEAF PARAMETERS
inputdict['profile_name'] = config.get_field_value('profile_name')
inputdict['endpoint_name'] = config.get_field_value('endpoint_name')
inputdict['device_ip'] = config.get_field_value('device_ip')
inputdict['vrf'] = config.get_field_value('vrf')
inputdict['interface_type'] = config.get_field_value('interface_type')
inputdict['interface_name'] = config.get_field_value('interface_name')
inputdict['vlan_id'] = config.get_field_value('vlan_id')
inputdict['interface_ip'] = config.get_field_value('interface_ip')
inputdict['interface_description'] = config.get_field_value('interface_description')
inputdict['pbr_policy'] = config.get_field_value('pbr_policy')
inputdict['dps'] = config.get_field_value('dps')
inputdict['ospf'] = config.get_field_value('ospf')
inputdict['priority'] = config.get_field_value('priority')
inputdict['cost'] = config.get_field_value('cost')
inputdict['fast_hello'] = config.get_field_value('fast_hello')
inputdict['hello_multiplier'] = config.get_field_value('hello_multiplier')
inputdict['hello_interval'] = config.get_field_value('hello_interval')
inputdict['dead_interval'] = config.get_field_value('dead_interval')
inputdict['ospf_id'] = config.get_field_value('ospf_id')
inputdict['area'] = config.get_field_value('area')
inputdict['inbound_acl'] = config.get_field_value('inbound_acl')
inputdict['global_inbound_acl'] = config.get_field_value('global_inbound_acl')
inputdict['site_inbound_acl'] = config.get_field_value('site_inbound_acl')
inputdict['outbound_acl'] = config.get_field_value('outbound_acl')
inputdict['global_outbound_acl'] = config.get_field_value('global_outbound_acl')
inputdict['site_outbound_acl'] = config.get_field_value('site_outbound_acl')
inputdict['nat_inside'] = config.get_field_value('nat_inside')
inputdict['nat_outside'] = config.get_field_value('nat_outside')
inputdict['delay'] = config.get_field_value('delay')
inputdict['mace_enable'] = config.get_field_value('mace_enable')
inputdict['tcp_mss'] = config.get_field_value('tcp_mss')
inputdict['bandwidth'] = config.get_field_value('bandwidth')
inputdict['bfd'] = config.get_field_value('bfd')
inputdict['bfd_interval'] = config.get_field_value('bfd_interval')
inputdict['bfd_min_rx'] = config.get_field_value('bfd_min_rx')
inputdict['bfd_multiplier'] = config.get_field_value('bfd_multiplier')
inputdict['nbar_discovery'] = config.get_field_value('nbar_discovery')
# END OF FETCHING THE LEAF PARAMETERS
#Fetch Device Object
dev = getDeviceObject(config.get_field_value('device_ip'), sdata)
inputkeydict = {}
# START OF FETCHING THE PARENT KEY LEAF PARAMETERS
inputkeydict['managed_cpe_services_customer_single_cpe_site_single_cpe_site_services_site_name'] = sdata.getRcPath().split('/')[-3].split('=')[1]
inputkeydict['managed_cpe_services_customer_name'] = sdata.getRcPath().split('/')[-5].split('=')[1]
# END OF FETCHING THE PARENT KEY LEAF PARAMETERS
#Use the custom methods to process the data
service_customization.ServiceDataCustomization.process_service_create_data(smodelctx, sdata, dev, parentobj=parentobj, inputdict=inputdict, config=config)
#Use the custom method to process/create payload
service_customization.ServiceDataCustomization.process_service_device_bindings(smodelctx, sdata, dev, inputdict=inputdict, parentobj=parentobj, config=config, devbindobjs=devbindobjs)
def update(self, id, sdata):
#Fetch Local Config Object
config = getCurrentObjectConfig(id, sdata, 'end_points')
pconfig = getPreviousObjectConfig(id, sdata, 'end_points')
#Fetch Service Model Context Object
smodelctx = None
#Fetch Parent Object
parentobj = None
#Fetch Device Object
prevconfig = util.parseXmlString(sdata.getPreviousPayload())
prevconfig = prevconfig.end_points
inputdict = {}
pinputdict = {}
# START OF FETCHING THE LEAF PARAMETERS
inputdict['profile_name'] = config.get_field_value('profile_name')
inputdict['endpoint_name'] = config.get_field_value('endpoint_name')
inputdict['device_ip'] = config.get_field_value('device_ip')
inputdict['vrf'] = config.get_field_value('vrf')
inputdict['interface_type'] = config.get_field_value('interface_type')
inputdict['interface_name'] = config.get_field_value('interface_name')
inputdict['vlan_id'] = config.get_field_value('vlan_id')
inputdict['interface_ip'] = config.get_field_value('interface_ip')
inputdict['interface_description'] = config.get_field_value('interface_description')
inputdict['pbr_policy'] = config.get_field_value('pbr_policy')
inputdict['dps'] = config.get_field_value('dps')
inputdict['ospf'] = config.get_field_value('ospf')
inputdict['priority'] = config.get_field_value('priority')
inputdict['cost'] = config.get_field_value('cost')
inputdict['fast_hello'] = config.get_field_value('fast_hello')
inputdict['hello_multiplier'] = config.get_field_value('hello_multiplier')
inputdict['hello_interval'] = config.get_field_value('hello_interval')
inputdict['dead_interval'] = config.get_field_value('dead_interval')
inputdict['ospf_id'] = config.get_field_value('ospf_id')
inputdict['area'] = config.get_field_value('area')
inputdict['inbound_acl'] = config.get_field_value('inbound_acl')
inputdict['global_inbound_acl'] = config.get_field_value('global_inbound_acl')
inputdict['site_inbound_acl'] = config.get_field_value('site_inbound_acl')
inputdict['outbound_acl'] = config.get_field_value('outbound_acl')
inputdict['global_outbound_acl'] = config.get_field_value('global_outbound_acl')
inputdict['site_outbound_acl'] = config.get_field_value('site_outbound_acl')
inputdict['nat_inside'] = config.get_field_value('nat_inside')
inputdict['nat_outside'] = config.get_field_value('nat_outside')
inputdict['delay'] = config.get_field_value('delay')
inputdict['mace_enable'] = config.get_field_value('mace_enable')
inputdict['tcp_mss'] = config.get_field_value('tcp_mss')
inputdict['bandwidth'] = config.get_field_value('bandwidth')
inputdict['bfd'] = config.get_field_value('bfd')
inputdict['bfd_interval'] = config.get_field_value('bfd_interval')
inputdict['bfd_min_rx'] = config.get_field_value('bfd_min_rx')
inputdict['bfd_multiplier'] = config.get_field_value('bfd_multiplier')
inputdict['nbar_discovery'] = config.get_field_value('nbar_discovery')
# END OF FETCHING THE LEAF PARAMETERS
# START OF FETCHING THE PREVIOUS LEAF PARAMETERS
pinputdict['profile_name'] = pconfig.get_field_value('profile_name')
pinputdict['endpoint_name'] = pconfig.get_field_value('endpoint_name')
pinputdict['device_ip'] = pconfig.get_field_value('device_ip')
pinputdict['vrf'] = pconfig.get_field_value('vrf')
pinputdict['interface_type'] = pconfig.get_field_value('interface_type')
pinputdict['interface_name'] = pconfig.get_field_value('interface_name')
pinputdict['vlan_id'] = pconfig.get_field_value('vlan_id')
pinputdict['interface_ip'] = pconfig.get_field_value('interface_ip')
pinputdict['interface_description'] = pconfig.get_field_value('interface_description')
pinputdict['pbr_policy'] = pconfig.get_field_value('pbr_policy')
pinputdict['dps'] = pconfig.get_field_value('dps')
pinputdict['ospf'] = pconfig.get_field_value('ospf')
pinputdict['priority'] = pconfig.get_field_value('priority')
pinputdict['cost'] = pconfig.get_field_value('cost')
pinputdict['fast_hello'] = pconfig.get_field_value('fast_hello')
pinputdict['hello_multiplier'] = pconfig.get_field_value('hello_multiplier')
pinputdict['hello_interval'] = pconfig.get_field_value('hello_interval')
pinputdict['dead_interval'] = pconfig.get_field_value('dead_interval')
pinputdict['ospf_id'] = pconfig.get_field_value('ospf_id')
pinputdict['area'] = pconfig.get_field_value('area')
pinputdict['inbound_acl'] = pconfig.get_field_value('inbound_acl')
pinputdict['global_inbound_acl'] = pconfig.get_field_value('global_inbound_acl')
pinputdict['site_inbound_acl'] = pconfig.get_field_value('site_inbound_acl')
pinputdict['outbound_acl'] = pconfig.get_field_value('outbound_acl')
pinputdict['global_outbound_acl'] = pconfig.get_field_value('global_outbound_acl')
pinputdict['site_outbound_acl'] = pconfig.get_field_value('site_outbound_acl')
pinputdict['nat_inside'] = pconfig.get_field_value('nat_inside')
pinputdict['nat_outside'] = pconfig.get_field_value('nat_outside')
pinputdict['delay'] = pconfig.get_field_value('delay')
pinputdict['mace_enable'] = pconfig.get_field_value('mace_enable')
pinputdict['tcp_mss'] = pconfig.get_field_value('tcp_mss')
pinputdict['bandwidth'] = pconfig.get_field_value('bandwidth')
pinputdict['bfd'] = pconfig.get_field_value('bfd')
pinputdict['bfd_interval'] = pconfig.get_field_value('bfd_interval')
pinputdict['bfd_min_rx'] = pconfig.get_field_value('bfd_min_rx')
pinputdict['bfd_multiplier'] = pconfig.get_field_value('bfd_multiplier')
pinputdict['nbar_discovery'] = pconfig.get_field_value('nbar_discovery')
# END OF FETCHING THE LEAF PARAMETERS
dev = getDeviceObject(prevconfig.get_field_value('device_ip'), sdata)
#Use the custom method to process the data
service_customization.ServiceDataCustomization.process_service_update_data(smodelctx, sdata, dev=dev, parentobj=parentobj, config=config, inputdict=inputdict, pinputdict=pinputdict, pconfig=pconfig)
def delete(self, id, sdata):
sdata.getSession().addYangSessionPreReserveProcessor(self.delete_pre_processor)
#Fetch Local Config Object
config = getCurrentObjectConfig(id, sdata, 'end_points')
#Fetch Service Model Context Object
smodelctx = None
#Fetch Parent Object
parentobj = None
inputdict = {}
# START OF FETCHING THE LEAF PARAMETERS
inputdict['profile_name'] = config.get_field_value('profile_name')
inputdict['endpoint_name'] = config.get_field_value('endpoint_name')
inputdict['device_ip'] = config.get_field_value('device_ip')
inputdict['vrf'] = config.get_field_value('vrf')
inputdict['interface_type'] = config.get_field_value('interface_type')
inputdict['interface_name'] = config.get_field_value('interface_name')
inputdict['vlan_id'] = config.get_field_value('vlan_id')
inputdict['interface_ip'] = config.get_field_value('interface_ip')
inputdict['interface_description'] = config.get_field_value('interface_description')
inputdict['pbr_policy'] = config.get_field_value('pbr_policy')
inputdict['dps'] = config.get_field_value('dps')
inputdict['ospf'] = config.get_field_value('ospf')
inputdict['priority'] = config.get_field_value('priority')
inputdict['cost'] = config.get_field_value('cost')
inputdict['fast_hello'] = config.get_field_value('fast_hello')
inputdict['hello_multiplier'] = config.get_field_value('hello_multiplier')
inputdict['hello_interval'] = config.get_field_value('hello_interval')
inputdict['dead_interval'] = config.get_field_value('dead_interval')
inputdict['ospf_id'] = config.get_field_value('ospf_id')
inputdict['area'] = config.get_field_value('area')
inputdict['inbound_acl'] = config.get_field_value('inbound_acl')
inputdict['global_inbound_acl'] = config.get_field_value('global_inbound_acl')
inputdict['site_inbound_acl'] = config.get_field_value('site_inbound_acl')
inputdict['outbound_acl'] = config.get_field_value('outbound_acl')
inputdict['global_outbound_acl'] = config.get_field_value('global_outbound_acl')
inputdict['site_outbound_acl'] = config.get_field_value('site_outbound_acl')
inputdict['nat_inside'] = config.get_field_value('nat_inside')
inputdict['nat_outside'] = config.get_field_value('nat_outside')
inputdict['delay'] = config.get_field_value('delay')
inputdict['mace_enable'] = config.get_field_value('mace_enable')
inputdict['tcp_mss'] = config.get_field_value('tcp_mss')
inputdict['bandwidth'] = config.get_field_value('bandwidth')
inputdict['bfd'] = config.get_field_value('bfd')
inputdict['bfd_interval'] = config.get_field_value('bfd_interval')
inputdict['bfd_min_rx'] = config.get_field_value('bfd_min_rx')
inputdict['bfd_multiplier'] = config.get_field_value('bfd_multiplier')
inputdict['nbar_discovery'] = config.get_field_value('nbar_discovery')
# END OF FETCHING THE LEAF PARAMETERS
#Fetch Device Object
dev = getDeviceObject(config.get_field_value('device_ip'), sdata)
#Use the custom method to process the data
service_customization.ServiceDataCustomization.process_service_delete_data(smodelctx, sdata, dev=dev, parentobj=parentobj, config=config)
@staticmethod
def getInstance():
if(EndPoints._instance == None):
EndPoints._instance = EndPoints()
return EndPoints._instance
#def rollbackCreate(self, id, sdata):
# log('rollback: id = %s, sdata = %s' % (id, sdata))
# self.delete(id,sdata)
| [
"[email protected]"
] | |
91b849e900044ed54bf41ef89839d496d7edea56 | 9743d5fd24822f79c156ad112229e25adb9ed6f6 | /xai/brain/wordbase/nouns/_gunslinger.py | 05089d95d9ae89b34ed5d0ce0aaa83ee93969be4 | [
"MIT"
] | permissive | cash2one/xai | de7adad1758f50dd6786bf0111e71a903f039b64 | e76f12c9f4dcf3ac1c7c08b0cc8844c0b0a104b6 | refs/heads/master | 2021-01-19T12:33:54.964379 | 2017-01-28T02:00:50 | 2017-01-28T02:00:50 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 414 | py |
#calss header
class _GUNSLINGER():
def __init__(self,):
self.name = "GUNSLINGER"
self.definitions = [u'especially in the past in North America, someone who is good at shooting guns and is employed for protection or to kill people']
self.parents = []
self.childen = []
self.properties = []
self.jsondata = {}
self.specie = 'nouns'
def run(self, obj1 = [], obj2 = []):
return self.jsondata
| [
"[email protected]"
] | |
748ba57cf89dcdd66b898d345938928ec78c11b0 | 523f8f5febbbfeb6d42183f2bbeebc36f98eadb5 | /32_best.py | 99e35e658b452b484a3f56877cf8d1ea52efde61 | [] | no_license | saleed/LeetCode | 655f82fdfcc3000400f49388e97fc0560f356af0 | 48b43999fb7e2ed82d922e1f64ac76f8fabe4baa | refs/heads/master | 2022-06-15T21:54:56.223204 | 2022-05-09T14:05:50 | 2022-05-09T14:05:50 | 209,430,056 | 2 | 0 | null | null | null | null | UTF-8 | Python | false | false | 594 | py | class Solution(object):
def longestValidParentheses(self, s):
"""
:type s: str
:rtype: int
"""
if len(s) == 0:
return 0
dp = [0] * len(s)
for i in range(len(s)):
if s[i] == "(":
dp[i] = 0
else:
if i - 1 >= 0 and i - 1 - dp[i - 1] >= 0 and s[i - 1 - dp[i - 1]] == "(":
dp[i] = 2 + dp[i - 1]
if i - 1 - dp[i - 1] - 1 >= 0:
dp[i] += dp[i - 1 - dp[i - 1] - 1]
print(dp)
return max(dp)
| [
"[email protected]"
] | |
4888153745ea34d4c15768a4a8e942d57823c159 | 71e324d2e7c9557a9cfec01997a44a66539ac2e6 | /Chapter_08/object_3_seperate.py | bc01ecd017f07f5efe52cb0fb90a2fb4a449db82 | [] | no_license | ulillilu/Python_Practice | 2706a72b22243f4d76bf239f552bd7da2615c1ef | f2b238176f7e68b3fa0674ce4951aaa4206c15d3 | refs/heads/master | 2022-11-29T17:58:52.035022 | 2020-08-13T17:01:49 | 2020-08-13T17:01:49 | 287,334,050 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,047 | py | #객체를 처리하는 함수
def create_student(name, korean, math, english, science):
return{
"name": name,
"korean": korean,
"math": math,
"english": english,
"science": science
}
def student_get_sum(student):
return student["korean"] + student["math"] + student["english"] + student["science"]
def student_get_average(student):
return student_get_sum(student) / 4
def student_to_string(student):
return "{}\t{}\t{}".format(
student["name"],
student_get_sum(student),
student_get_average(student)
)
students = [
create_student("윤인성", 87, 98, 88, 95),
create_student("연하진", 92, 98, 96, 98),
create_student("구지연", 76, 96, 94, 90),
create_student("나선주", 98, 92, 96, 92),
create_student("윤아린", 95, 98, 98, 98),
create_student("윤명월", 94, 88, 92, 92)
]
print ("이름", "총점", "평균", sep="\t")
for student in students:
print(student_to_string(student)) | [
"[email protected]"
] | |
d0fb24f28c2ec27cd9e6e2a7952e61012fa0dc50 | 1fe0b680ce53bb3bb9078356ea2b25e572d9cfdc | /venv/lib/python2.7/site-packages/ansible/modules/cloud/azure/azure_rm_routetable.py | 1dc6180ba8335b5645e02e1f39d13a54a3e496bc | [
"MIT"
] | permissive | otus-devops-2019-02/devopscourses_infra | 1929c4a9eace3fdb0eb118bf216f3385fc0cdb1c | e42e5deafce395af869084ede245fc6cff6d0b2c | refs/heads/master | 2020-04-29T02:41:49.985889 | 2019-05-21T06:35:19 | 2019-05-21T06:35:19 | 175,780,457 | 0 | 1 | MIT | 2019-05-21T06:35:20 | 2019-03-15T08:35:54 | HCL | UTF-8 | Python | false | false | 6,015 | py | #!/usr/bin/python
#
# Copyright (c) 2018 Yuwei Zhou, <[email protected]>
#
# GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
from __future__ import absolute_import, division, print_function
__metaclass__ = type
ANSIBLE_METADATA = {'metadata_version': '1.1',
'status': ['preview'],
'supported_by': 'community'}
DOCUMENTATION = '''
---
module: azure_rm_routetable
version_added: "2.7"
short_description: Manage Azure route table resource.
description:
- Create, update or delete a route table.
options:
resource_group:
description:
- name of resource group.
required: true
name:
description:
- name of the route table.
required: true
state:
description:
- Assert the state of the route table. Use C(present) to create or update and
C(absent) to delete.
default: present
choices:
- absent
- present
disable_bgp_route_propagation:
description:
- Specified whether to disable the routes learned by BGP on that route table.
type: bool
default: False
location:
description:
- Region of the resource.
- Derived from C(resource_group) if not specified
extends_documentation_fragment:
- azure
- azure_tags
author:
- "Yuwei Zhou (@yuwzho)"
'''
EXAMPLES = '''
- name: Create a route table
azure_rm_routetable:
resource_group: myResourceGroup
name: myRouteTable
disable_bgp_route_propagation: False
tags:
purpose: testing
- name: Delete a route table
azure_rm_routetable:
resource_group: myResourceGroup
name: myRouteTable
state: absent
'''
RETURN = '''
changed:
description: Whether the resource is changed.
returned: always
type: bool
id:
description: resource id.
returned: success
type: str
'''
try:
from msrestazure.azure_exceptions import CloudError
except ImportError:
# This is handled in azure_rm_common
pass
from ansible.module_utils.azure_rm_common import AzureRMModuleBase, normalize_location_name
class AzureRMRouteTable(AzureRMModuleBase):
def __init__(self):
self.module_arg_spec = dict(
resource_group=dict(type='str', required=True),
name=dict(type='str', required=True),
state=dict(type='str', default='present', choices=['present', 'absent']),
location=dict(type='str'),
disable_bgp_route_propagation=dict(type='bool', default=False)
)
self.resource_group = None
self.name = None
self.state = None
self.location = None
self.tags = None
self.disable_bgp_route_propagation = None
self.results = dict(
changed=False
)
super(AzureRMRouteTable, self).__init__(self.module_arg_spec,
supports_check_mode=True)
def exec_module(self, **kwargs):
for key in list(self.module_arg_spec.keys()) + ['tags']:
setattr(self, key, kwargs[key])
resource_group = self.get_resource_group(self.resource_group)
if not self.location:
# Set default location
self.location = resource_group.location
self.location = normalize_location_name(self.location)
result = dict()
changed = False
result = self.get_table()
if self.state == 'absent' and result:
changed = True
if not self.check_mode:
self.delete_table()
elif self.state == 'present':
if not result:
changed = True # create new route table
else: # check update
update_tags, self.tags = self.update_tags(result.tags)
if update_tags:
changed = True
if self.disable_bgp_route_propagation != result.disable_bgp_route_propagation:
changed = True
if changed:
result = self.network_models.RouteTable(location=self.location,
tags=self.tags,
disable_bgp_route_propagation=self.disable_bgp_route_propagation)
if not self.check_mode:
result = self.create_or_update_table(result)
self.results['id'] = result.id if result else None
self.results['changed'] = changed
return self.results
def create_or_update_table(self, param):
try:
poller = self.network_client.route_tables.create_or_update(self.resource_group, self.name, param)
return self.get_poller_result(poller)
except Exception as exc:
self.fail("Error creating or updating route table {0} - {1}".format(self.name, str(exc)))
def delete_table(self):
try:
poller = self.network_client.route_tables.delete(self.resource_group, self.name)
result = self.get_poller_result(poller)
return result
except Exception as exc:
self.fail("Error deleting virtual network {0} - {1}".format(self.name, str(exc)))
def get_table(self):
try:
return self.network_client.route_tables.get(self.resource_group, self.name)
except CloudError as cloud_err:
# Return None iff the resource is not found
if cloud_err.status_code == 404:
self.log('{0}'.format(str(cloud_err)))
return None
self.fail('Error: failed to get resource {0} - {1}'.format(self.name, str(cloud_err)))
except Exception as exc:
self.fail('Error: failed to get resource {0} - {1}'.format(self.name, str(exc)))
def main():
AzureRMRouteTable()
if __name__ == '__main__':
main()
| [
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] | |
afc8f2bf08df0703f759b13e99e9b4c3ff9e26a4 | e2255da9f41a3ca592f5042c96ec8dc1f5ceba21 | /google/appengine/ext/mapreduce/api/map_job/__init__.py | 9347a8bdc947888f6886b093371cbbe34aac3d61 | [
"Apache-2.0"
] | permissive | KronnyEC/cliques | 2a2b1eb0063017f3dbe7de6a42a98d21a7cffb37 | 2fd66c4c4ea4552ab8ef6d738613f618a1a74fc7 | refs/heads/master | 2021-01-24T05:05:49.142434 | 2014-08-18T06:30:32 | 2014-08-18T06:42:41 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 853 | py | #!/usr/bin/env python
#
# Copyright 2007 Google Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
"""Map job package."""
from .map_job_config import JobConfig
from .map_job_context import JobContext
from .map_job_context import ShardContext
from .map_job_context import SliceContext
from .map_job_control import Job
from .mapper import Mapper
| [
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] | |
8c18a2515beac0972d4760bcf73d68aec9f59e15 | ca7aa979e7059467e158830b76673f5b77a0f5a3 | /Python_codes/p02702/s763305864.py | c1f2a064512072f127149a2d43913b8cc8dc8cd7 | [] | no_license | Aasthaengg/IBMdataset | 7abb6cbcc4fb03ef5ca68ac64ba460c4a64f8901 | f33f1c5c3b16d0ea8d1f5a7d479ad288bb3f48d8 | refs/heads/main | 2023-04-22T10:22:44.763102 | 2021-05-13T17:27:22 | 2021-05-13T17:27:22 | 367,112,348 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 370 | py | S = input()
dp = [0]*(len(S)+1)
cur = int(S[len(S)-1])
mod_10 = 1
count_num = [0]*2019
count_num[0] += 1
for i in range(len(S)):
dp[len(S)-i-1] = cur
count_num[cur] += 1
mod_10 = (mod_10*10)%2019
if i <= len(S)-2:
cur = (cur+int(S[len(S)-i-2])*(mod_10))%2019
ans = 0
for i in range(2019):
ans += (count_num[i]*(count_num[i]-1))//2
print(ans)
| [
"[email protected]"
] | |
e13fe5af3a9acaff486417fedd87270c31830d4c | 396f93d8e73c419ef82a94174815a2cecbb8334b | /.history/tester2_20200321232603.py | 3011254a2f67dbc34040fee7f27f648bd06eec26 | [] | no_license | mirfarzam/ArtificialIntelligence-HeuristicAlgorithm-TabuSearch | 8c73d9448b916009c9431526864a4441fdeb682a | 90b2dca920c85cddd7c1b3335344ac7b10a9b061 | refs/heads/master | 2021-03-26T21:16:42.561068 | 2020-04-17T21:44:26 | 2020-04-17T21:44:26 | 247,750,502 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,912 | py | import os
import subprocess
import re
from datetime import datetime
import time
from statistics import mean
numberOfTests = 10
tabuIteration = '10'
tabuDuration = '0'
numberOfCities = '50'
final_solution = []
list_coverage = []
print(f"\n\nTest for Tabu Search with this config: \n\tIterations : {tabuIteration} \n\tDuration(Tabu Memory): {tabuDuration} \n\tNumber of Cities: {numberOfCities}")
for i in range(0, numberOfTests):
process = subprocess.Popen(['./algo_tabou.exe', tabuIteration, tabuDuration, numberOfCities, 'distances_entre_villes_{}.txt'.format(numberOfCities)],stdout=subprocess.PIPE,stderr=subprocess.PIPE)
stdout, stderr = process.communicate()
result = stdout
result = re.sub(r'\s', ' ', str(result))
solution = (re.findall(r'([0-9]{4}) km', result))[-1]
final_solution.append(int(solution))
coverage = re.findall(r'On est dans un minimum local a l\'iteration ([0-9]+) ->', result)
if coverage != []:
coverage = int(coverage[0])+ 1
else:
coverage = 5
number_of_solution_before_coverage = coverage
list_coverage.append(coverage)
print('best found solution is {} and found in interation {}, number of solutions before coverage : {}'.format(solution, coverage, number_of_solution_before_coverage))
time.sleep( 1 )
print("Summery:")
optimum_result = len(list(filter(lambda x: x == 5644, final_solution)))
print(f'number of optimum solution found is {optimum_result}, so in {numberOfTests} runs of test we faced {(optimum_result/numberOfTests)*100}% coverage')
print(f'in average this test shows that we found the global optimum solution in iteration {mean(list_coverage)}\nand in worst we found it in iteration {max(list_coverage)} \nand in best case in iteration {max(list_coverage)}')
print(f'Totally, {sum(list_coverage)} cities visited before finding the global optimum in {numberOfTests} runs of this test\n\n\n') | [
"[email protected]"
] | |
10d81e12691ea7edbbac63eee7f183d1e0842d8a | fc746b644a2f4d07508e84b0d162c0f2ef07076d | /build/orocos_kinematics_dynamics/catkin_generated/generate_cached_setup.py | 174396b513f66f2b974b95d28716ad2d3160a197 | [] | no_license | andreatitti97/thesis_ws | d372146246b8c9b74d25e1310e6e79f9e0270cc4 | c59d380abe7be47ea2d7812e416dee7298c20db8 | refs/heads/main | 2023-03-16T12:26:17.676403 | 2021-03-15T13:22:59 | 2021-03-15T13:22:59 | 340,458,689 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,352 | py | # -*- coding: utf-8 -*-
from __future__ import print_function
import os
import stat
import sys
# find the import for catkin's python package - either from source space or from an installed underlay
if os.path.exists(os.path.join('/opt/ros/kinetic/share/catkin/cmake', 'catkinConfig.cmake.in')):
sys.path.insert(0, os.path.join('/opt/ros/kinetic/share/catkin/cmake', '..', 'python'))
try:
from catkin.environment_cache import generate_environment_script
except ImportError:
# search for catkin package in all workspaces and prepend to path
for workspace in '/home/andrea/thesis_ws/devel;/opt/ros/kinetic'.split(';'):
python_path = os.path.join(workspace, 'lib/python2.7/dist-packages')
if os.path.isdir(os.path.join(python_path, 'catkin')):
sys.path.insert(0, python_path)
break
from catkin.environment_cache import generate_environment_script
code = generate_environment_script('/home/andrea/thesis_ws/devel/.private/orocos_kinematics_dynamics/env.sh')
output_filename = '/home/andrea/thesis_ws/build/orocos_kinematics_dynamics/catkin_generated/setup_cached.sh'
with open(output_filename, 'w') as f:
# print('Generate script for cached setup "%s"' % output_filename)
f.write('\n'.join(code))
mode = os.stat(output_filename).st_mode
os.chmod(output_filename, mode | stat.S_IXUSR)
| [
"[email protected]"
] | |
60fb4c4eb6e60fca24c3bb874dd487c384022e84 | e811662c890217c77b60aa2e1295dd0f5b2d4591 | /src/problem_145.py | da0952c5573f00aae6e48903d71a6426d47dd221 | [] | no_license | rewonderful/MLC | 95357f892f8cf76453178875bac99316c7583f84 | 7012572eb192c29327ede821c271ca082316ff2b | refs/heads/master | 2022-05-08T05:24:06.929245 | 2019-09-24T10:35:22 | 2019-09-24T10:35:22 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,256 | py | #!/usr/bin/env python
# _*_ coding:utf-8 _*_
from TreeNode import TreeNode
def postorderTraversal(self, root):
"""
记住得了= =
就访问当前root，然后左子树入栈，右子树入栈，最后逆序一下就好了，return output[::-1]
相当于是这么个思路：
目标：左右根
那么我就先求出来根右左，先根遍历是好访问的，根右左的话，因为是栈，所以先访问根，然后左孩子节点入栈，
再右孩子节点入栈，这样出栈的顺序就是跟右左了，其实可以联想一下，其实左右只是人为设定和规定的嘛，就像二分类要用10，也可以看成是01
一个道理，那就调换左右顺序呗，这样就可以根右左的访问
最后再将【根右左】遍历得到的结果逆序，不就是左右根了，比较讨巧
"""
if root is None:
return []
stack, output = [root, ], []
while stack:
root = stack.pop()
output.append(root.val)
if root.left is not None:
stack.append(root.left)
if root.right is not None:
stack.append(root.right)
return output[::-1]
def postorderTraversal2(self, root):
"""
:type root: TreeNode
:rtype: List[int]
"""
if not root:
return []
ans = []
visited = set()
stack = [root]
while stack:
top = stack[-1]
if top in visited:
ans.append(stack.pop().val)
else:
if top.right:
stack.append(top.right)
if top.left:
stack.append(top.left)
visited.add(top)
return ans
def postorderTraversal1(self, root):
"""
算法：递归遍历
"""
return [] if root == None else self.postorderTraversal(root.left) + self.postorderTraversal(root.right) + [root.val]
if __name__ == '__main__':
#1,2,3,4,5,6,7
t1 = TreeNode(1)
t2 = TreeNode(2)
t3 = TreeNode(3)
t4 = TreeNode(4)
t5 = TreeNode(5)
t6 = TreeNode(6)
t7 = TreeNode(7)
# t1.left = t2
# t1.right = t3
# t2.left = t4
# t2.right = t5
# t3.left = t6
# t3.right = t7
t1.right =t2
t2.left = t3
print(postorderTraversal(t1))
| [
"[email protected]"
] | |
4a69e480891dda49ef8586ab48e9e957f44d391d | 327981aeef801fec08305d70270deab6f08bc122 | /19.网络编程/TCP编程/2.客户端与服务器端的数据交互/client.py | 659f33d99bf8eb92f58accb100300281589e8207 | [] | no_license | AWangHe/Python-basis | 2872db82187b169226271c509778c0798b151f50 | 2e3e9eb6da268f765c7ba04f1aefc644d50c0a29 | refs/heads/master | 2020-03-20T12:15:44.491323 | 2018-06-15T08:24:19 | 2018-06-15T08:24:19 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 381 | py | # -*- coding: utf-8 -*-
import socket
client = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
client.connect(('192.168.43.240', 8083))
count = 0
while True:
count += 1
data = input("请输入给服务器发送的数据：")
client.send(data.encode("utf-8"))
info = client.recv(1024)
print("服务器说：", info.decode("utf-8"))
| [
"[email protected]"
] | |
95282fad8921847fbce1b8d8cf3e6b80655c0234 | d2f71636c17dc558e066d150fe496343b9055799 | /eventi/receipts/urls.py | adc4aac61ed9506ad430a00c7e224d076c9b8818 | [
"MIT"
] | permissive | klebercode/lionsclub | 9d8d11ad6083d25f6d8d92bfbae9a1bbfa6d2106 | 60db85d44214561d20f85673e8f6c047fab07ee9 | refs/heads/master | 2020-06-11T19:45:39.974945 | 2015-04-05T01:11:57 | 2015-04-05T01:11:57 | 33,409,707 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 206 | py | # coding: utf-8
from django.conf.urls import patterns, url
urlpatterns = patterns(
'eventi.receipts.views',
url(r'^$', 'receipt', name='receipt'),
url(r'^(\d+)/$', 'detail', name='detail'),
)
| [
"[email protected]"
] | |
777ff814dd92fd8c87e5d20a934a54207ca894cf | d3b7a7a922eb9999f22c99c0cc3908d7289ca27e | /tests/multi_processing/multi_process_queue.py | 907844ddda04cef496883f0bd2b010512fd7341b | [
"Apache-2.0"
] | permissive | g3l0o/plaso | b668203c2c7cf8799a1c12824ee1bdc8befd3980 | ae29d853a6bcdd1530ce9320a3af7b3f122941ac | refs/heads/master | 2020-12-25T20:31:08.928709 | 2016-07-22T20:00:33 | 2016-07-22T20:00:33 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 997 | py | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""Tests the multi-processing queue."""
import unittest
from plaso.multi_processing import multi_process_queue
from tests import test_lib as shared_test_lib
from tests.engine import test_lib as engine_test_lib
class MultiProcessingQueueTest(shared_test_lib.BaseTestCase):
"""Tests the multi-processing queue object."""
_ITEMS = frozenset([u'item1', u'item2', u'item3', u'item4'])
def testPushPopItem(self):
"""Tests the PushItem and PopItem functions."""
# A timeout is used to prevent the multi processing queue to close and
# stop blocking the current process
test_queue = multi_process_queue.MultiProcessingQueue(timeout=0.1)
for item in self._ITEMS:
test_queue.PushItem(item)
test_queue_consumer = engine_test_lib.TestQueueConsumer(test_queue)
test_queue_consumer.ConsumeItems()
self.assertEqual(test_queue_consumer.number_of_items, len(self._ITEMS))
if __name__ == '__main__':
unittest.main()
| [
"[email protected]"
] | |
b183fd247237298655d932c09b777a7f4625b802 | e6208febf7e34d4108422c6da54453373733a421 | /sdks/python/client/argo_workflows/model/io_argoproj_events_v1alpha1_open_whisk_trigger.py | b73ce18a83ef1645a3a1956f8785cb123ff59e8a | [
"Apache-2.0"
] | permissive | wreed4/argo | 05889e5bb7738d534660c58a7ec71c454e6ac9bb | 41f94310b0f7fee1ccd533849bb3af7f1ad4f672 | refs/heads/master | 2023-01-22T05:32:12.254485 | 2022-01-27T21:24:45 | 2022-01-27T22:02:22 | 233,143,964 | 0 | 0 | Apache-2.0 | 2023-01-17T19:04:43 | 2020-01-10T22:56:25 | Go | UTF-8 | Python | false | false | 13,500 | py | """
Argo Server API
You can get examples of requests and responses by using the CLI with `--gloglevel=9`, e.g. `argo list --gloglevel=9` # noqa: E501
The version of the OpenAPI document: VERSION
Generated by: https://openapi-generator.tech
"""
import re # noqa: F401
import sys # noqa: F401
from argo_workflows.model_utils import ( # noqa: F401
ApiTypeError,
ModelComposed,
ModelNormal,
ModelSimple,
cached_property,
change_keys_js_to_python,
convert_js_args_to_python_args,
date,
datetime,
file_type,
none_type,
validate_get_composed_info,
)
from ..model_utils import OpenApiModel
from argo_workflows.exceptions import ApiAttributeError
def lazy_import():
from argo_workflows.model.io_argoproj_events_v1alpha1_trigger_parameter import IoArgoprojEventsV1alpha1TriggerParameter
from argo_workflows.model.secret_key_selector import SecretKeySelector
globals()['IoArgoprojEventsV1alpha1TriggerParameter'] = IoArgoprojEventsV1alpha1TriggerParameter
globals()['SecretKeySelector'] = SecretKeySelector
class IoArgoprojEventsV1alpha1OpenWhiskTrigger(ModelNormal):
"""NOTE: This class is auto generated by OpenAPI Generator.
Ref: https://openapi-generator.tech
Do not edit the class manually.
Attributes:
allowed_values (dict): The key is the tuple path to the attribute
and the for var_name this is (var_name,). The value is a dict
with a capitalized key describing the allowed value and an allowed
value. These dicts store the allowed enum values.
attribute_map (dict): The key is attribute name
and the value is json key in definition.
discriminator_value_class_map (dict): A dict to go from the discriminator
variable value to the discriminator class name.
validations (dict): The key is the tuple path to the attribute
and the for var_name this is (var_name,). The value is a dict
that stores validations for max_length, min_length, max_items,
min_items, exclusive_maximum, inclusive_maximum, exclusive_minimum,
inclusive_minimum, and regex.
additional_properties_type (tuple): A tuple of classes accepted
as additional properties values.
"""
allowed_values = {
}
validations = {
}
@cached_property
def additional_properties_type():
"""
This must be a method because a model may have properties that are
of type self, this must run after the class is loaded
"""
lazy_import()
return (bool, date, datetime, dict, float, int, list, str, none_type,) # noqa: E501
_nullable = False
@cached_property
def openapi_types():
"""
This must be a method because a model may have properties that are
of type self, this must run after the class is loaded
Returns
openapi_types (dict): The key is attribute name
and the value is attribute type.
"""
lazy_import()
return {
'action_name': (str,), # noqa: E501
'auth_token': (SecretKeySelector,), # noqa: E501
'host': (str,), # noqa: E501
'namespace': (str,), # noqa: E501
'parameters': ([IoArgoprojEventsV1alpha1TriggerParameter],), # noqa: E501
'payload': ([IoArgoprojEventsV1alpha1TriggerParameter],), # noqa: E501
'version': (str,), # noqa: E501
}
@cached_property
def discriminator():
return None
attribute_map = {
'action_name': 'actionName', # noqa: E501
'auth_token': 'authToken', # noqa: E501
'host': 'host', # noqa: E501
'namespace': 'namespace', # noqa: E501
'parameters': 'parameters', # noqa: E501
'payload': 'payload', # noqa: E501
'version': 'version', # noqa: E501
}
read_only_vars = {
}
_composed_schemas = {}
@classmethod
@convert_js_args_to_python_args
def _from_openapi_data(cls, *args, **kwargs): # noqa: E501
"""IoArgoprojEventsV1alpha1OpenWhiskTrigger - a model defined in OpenAPI
Keyword Args:
_check_type (bool): if True, values for parameters in openapi_types
will be type checked and a TypeError will be
raised if the wrong type is input.
Defaults to True
_path_to_item (tuple/list): This is a list of keys or values to
drill down to the model in received_data
when deserializing a response
_spec_property_naming (bool): True if the variable names in the input data
are serialized names, as specified in the OpenAPI document.
False if the variable names in the input data
are pythonic names, e.g. snake case (default)
_configuration (Configuration): the instance to use when
deserializing a file_type parameter.
If passed, type conversion is attempted
If omitted no type conversion is done.
_visited_composed_classes (tuple): This stores a tuple of
classes that we have traveled through so that
if we see that class again we will not use its
discriminator again.
When traveling through a discriminator, the
composed schema that is
is traveled through is added to this set.
For example if Animal has a discriminator
petType and we pass in "Dog", and the class Dog
allOf includes Animal, we move through Animal
once using the discriminator, and pick Dog.
Then in Dog, we will make an instance of the
Animal class but this time we won't travel
through its discriminator because we passed in
_visited_composed_classes = (Animal,)
action_name (str): Name of the action/function.. [optional] # noqa: E501
auth_token (SecretKeySelector): [optional] # noqa: E501
host (str): Host URL of the OpenWhisk.. [optional] # noqa: E501
namespace (str): Namespace for the action. Defaults to \"_\". +optional.. [optional] # noqa: E501
parameters ([IoArgoprojEventsV1alpha1TriggerParameter]): [optional] # noqa: E501
payload ([IoArgoprojEventsV1alpha1TriggerParameter]): Payload is the list of key-value extracted from an event payload to construct the request payload.. [optional] # noqa: E501
version (str): [optional] # noqa: E501
"""
_check_type = kwargs.pop('_check_type', True)
_spec_property_naming = kwargs.pop('_spec_property_naming', False)
_path_to_item = kwargs.pop('_path_to_item', ())
_configuration = kwargs.pop('_configuration', None)
_visited_composed_classes = kwargs.pop('_visited_composed_classes', ())
self = super(OpenApiModel, cls).__new__(cls)
if args:
raise ApiTypeError(
"Invalid positional arguments=%s passed to %s. Remove those invalid positional arguments." % (
args,
self.__class__.__name__,
),
path_to_item=_path_to_item,
valid_classes=(self.__class__,),
)
self._data_store = {}
self._check_type = _check_type
self._spec_property_naming = _spec_property_naming
self._path_to_item = _path_to_item
self._configuration = _configuration
self._visited_composed_classes = _visited_composed_classes + (self.__class__,)
for var_name, var_value in kwargs.items():
if var_name not in self.attribute_map and \
self._configuration is not None and \
self._configuration.discard_unknown_keys and \
self.additional_properties_type is None:
# discard variable.
continue
setattr(self, var_name, var_value)
return self
required_properties = set([
'_data_store',
'_check_type',
'_spec_property_naming',
'_path_to_item',
'_configuration',
'_visited_composed_classes',
])
@convert_js_args_to_python_args
def __init__(self, *args, **kwargs): # noqa: E501
"""IoArgoprojEventsV1alpha1OpenWhiskTrigger - a model defined in OpenAPI
Keyword Args:
_check_type (bool): if True, values for parameters in openapi_types
will be type checked and a TypeError will be
raised if the wrong type is input.
Defaults to True
_path_to_item (tuple/list): This is a list of keys or values to
drill down to the model in received_data
when deserializing a response
_spec_property_naming (bool): True if the variable names in the input data
are serialized names, as specified in the OpenAPI document.
False if the variable names in the input data
are pythonic names, e.g. snake case (default)
_configuration (Configuration): the instance to use when
deserializing a file_type parameter.
If passed, type conversion is attempted
If omitted no type conversion is done.
_visited_composed_classes (tuple): This stores a tuple of
classes that we have traveled through so that
if we see that class again we will not use its
discriminator again.
When traveling through a discriminator, the
composed schema that is
is traveled through is added to this set.
For example if Animal has a discriminator
petType and we pass in "Dog", and the class Dog
allOf includes Animal, we move through Animal
once using the discriminator, and pick Dog.
Then in Dog, we will make an instance of the
Animal class but this time we won't travel
through its discriminator because we passed in
_visited_composed_classes = (Animal,)
action_name (str): Name of the action/function.. [optional] # noqa: E501
auth_token (SecretKeySelector): [optional] # noqa: E501
host (str): Host URL of the OpenWhisk.. [optional] # noqa: E501
namespace (str): Namespace for the action. Defaults to \"_\". +optional.. [optional] # noqa: E501
parameters ([IoArgoprojEventsV1alpha1TriggerParameter]): [optional] # noqa: E501
payload ([IoArgoprojEventsV1alpha1TriggerParameter]): Payload is the list of key-value extracted from an event payload to construct the request payload.. [optional] # noqa: E501
version (str): [optional] # noqa: E501
"""
_check_type = kwargs.pop('_check_type', True)
_spec_property_naming = kwargs.pop('_spec_property_naming', False)
_path_to_item = kwargs.pop('_path_to_item', ())
_configuration = kwargs.pop('_configuration', None)
_visited_composed_classes = kwargs.pop('_visited_composed_classes', ())
if args:
raise ApiTypeError(
"Invalid positional arguments=%s passed to %s. Remove those invalid positional arguments." % (
args,
self.__class__.__name__,
),
path_to_item=_path_to_item,
valid_classes=(self.__class__,),
)
self._data_store = {}
self._check_type = _check_type
self._spec_property_naming = _spec_property_naming
self._path_to_item = _path_to_item
self._configuration = _configuration
self._visited_composed_classes = _visited_composed_classes + (self.__class__,)
for var_name, var_value in kwargs.items():
if var_name not in self.attribute_map and \
self._configuration is not None and \
self._configuration.discard_unknown_keys and \
self.additional_properties_type is None:
# discard variable.
continue
setattr(self, var_name, var_value)
if var_name in self.read_only_vars:
raise ApiAttributeError(f"`{var_name}` is a read-only attribute. Use `from_openapi_data` to instantiate "
f"class with read only attributes.")
| [
"[email protected]"
] | |
bd309d0b656942f65a5f6031b1475317b8f6cf1f | 79661312d54643ce9dcfe3474058f514b01bfbe6 | /ScikitLearn/ElasticNet_1f.py | 9591fda25cf74ca65630946558d5e9573e4ea026 | [] | no_license | davis-9fv/Project | 5c4c8ac03f5bf9db28704e63de9b004f56a52f10 | f2bd22b3ac440b91d1d1defc8da9e2ba2e67265e | refs/heads/master | 2020-03-20T22:24:07.244521 | 2019-02-28T16:58:04 | 2019-02-28T16:58:04 | 137,796,517 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 965 | py | # http://scikit-learn.org/stable/modules/generated/sklearn.linear_model.ElasticNet.html#sklearn.linear_model.ElasticNet
from sklearn import linear_model
from sklearn.linear_model import ElasticNet
import numpy as np
from pandas import read_csv
from sklearn.metrics import mean_squared_error
from sklearn.model_selection import train_test_split
from math import sqrt
series = read_csv('../tests/shampoo-sales3.csv', header=0)
raw_data = series.values
X_train, X_test, y_train, y_test = train_test_split(raw_data[:, 0], raw_data[:, 1], test_size=0.33, random_state=9)
X_train = X_train.reshape(X_train.shape[0], 1)
X_test = X_test.reshape(X_test.shape[0], 1)
regr = ElasticNet(random_state=0)
regr.fit(X_train, y_train)
print(regr.coef_)
print(regr.intercept_)
y_predicted = regr.predict(X_test)
print('y_test: ')
print(y_test)
print('y_predicted: ')
print(y_predicted)
rmse = sqrt(mean_squared_error(y_test, y_predicted))
print('Test RMSE: %.7f' % (rmse))
| [
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] | |
872970618a04f2ca7f58bc8040f04ba42271524b | d8fd7f56537d3c4ad4c99965a0a451c5442b704f | /endlesshandsome/wsgi.py | 29a7d6b605fc1118dfa24a6ccc1d6d200ee9a31b | [] | no_license | EndlessHandsome/endless-handsome | 8febdc5edbaed973922b7c31d903d19d4361dc32 | 59f1c3e52bd43c765177288ced755b081db0c746 | refs/heads/master | 2020-04-06T06:57:24.027547 | 2016-08-19T03:51:55 | 2016-08-19T03:51:55 | 65,613,177 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 408 | py | """
WSGI config for endlesshandsome project.
It exposes the WSGI callable as a module-level variable named ``application``.
For more information on this file, see
https://docs.djangoproject.com/en/1.10/howto/deployment/wsgi/
"""
import os
from django.core.wsgi import get_wsgi_application
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "endlesshandsome.settings")
application = get_wsgi_application()
| [
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] | |
38d04cc7afed1c10a20297dcc8cab9f85f307ec5 | 6d37c05de7d73e04f87c6ed796c77144cd8fa187 | /Chapter5/Challenge6.py | 736c77478dd0b59baddd2cfa380dc27017fe4e3b | [] | no_license | eizin6389/The-Self-Taught-Programmer | edc37ed6d95e8b24f590a6cbb9c75c0e5bd4e2e3 | 9c23612dfb11d5302cb26a359d02c88886cf986c | refs/heads/master | 2022-12-08T06:47:37.541256 | 2020-08-30T07:16:01 | 2020-08-30T07:16:01 | 286,423,906 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 131 | py | s= {"百",100,(0,1,2)}
print(s)
print(len(s))
s.add("二百")
print(s)
s.discard(100)
print(s)
s.pop()
print(s)
s.clear()
print(s)
| [
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] | |
4a865beed91c9a8e8b4658315602570354bd4770 | f4b011992dd468290d319d078cbae4c015d18338 | /Array/counting_element_in_two_array.py | f63a8421ab898a5ab3b5dcbed4c726b0b2a93aef | [] | no_license | Neeraj-kaushik/Geeksforgeeks | deca074ca3b37dcb32c0136b96f67beb049f9592 | c56de368db5a6613d59d9534de749a70b9530f4c | refs/heads/master | 2023-08-06T05:00:43.469480 | 2021-10-07T13:37:33 | 2021-10-07T13:37:33 | 363,420,292 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 371 | py | def counting_element(li, li1):
li3 = []
for i in range(len(li)):
count = 0
for j in range(len(li1)):
if li[i] >= li1[j]:
count = count+1
li3.append(count)
print(li3)
n = int(input())
m = int(input())
li = [int(x) for x in input().split()]
li1 = [int(x) for x in input().split()]
counting_element(li, li1)
| [
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] | |
8cb9fad16805ff1eef128d7408246c8350a45bdf | 5b683c7f0cc23b1a2b8927755f5831148f4f7e1c | /Python_Study/DataStructureAndAlgorithm/剑指Offer/Solution21py | 129b991defc62a3357595192e3b5ddc9ee1ac835 | [] | no_license | Shmilyqjj/Shmily-py | 970def5a53a77aa33b93404e18c57130f134772a | 770fc26607ad3e05a4d7774a769bc742582c7b64 | refs/heads/master | 2023-09-02T04:43:39.192052 | 2023-08-31T03:28:39 | 2023-08-31T03:28:39 | 199,372,223 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 306 | #!/usr/bin/env python
# encoding: utf-8
"""
:Description:剑指Offer 21
:Author: 佳境Shmily
:Create Time: 2020/4/29 11:59
:File: Solution21
:Site: shmily-qjj.top
"""
class Solution:
def jumpFloor(self, number):
# write code here
pass
if __name__ == '__main__':
s = Solution()
| [
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] | ||
d7857e8040c986cb578fcb3f8736cbe77f1ee7cb | d8cbc94a4207337d709a64447acb9c8fe501c75a | /evaluation/code/utils/checkpoint.py | 0ce4488ec35b22f34e1d615616e0b445ee73a941 | [
"MIT"
] | permissive | sripathisridhar/acav100m | 6f672384fa723a637d94accbbe11a9a962f5f87f | 13b438b6ce46d09ba6f79aebb84ad31dfa3a8e6f | refs/heads/master | 2023-09-06T01:05:21.188822 | 2021-11-18T08:08:08 | 2021-11-18T08:08:08 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,887 | py | import os
import shutil
from collections import OrderedDict
import torch
import utils.logging as logging
logger = logging.get_logger(__name__)
def load_checkpoint(model, state_dict, data_parallel=False):
"""
Load the trained weights from the checkpoint.
Args:
model (model): model to load the weights from the checkpoint.
state_dict (OrderedDict): checkpoint.
data_parallel (bool): if true, model is wrapped by
torch.nn.parallel.DistributedDataParallel.
"""
ms = model.module if data_parallel else model
ms.load_state_dict(state_dict)
def load_pretrained_checkpoint(model, state_dict, data_parallel=False):
"""
Load the pretrained weights from the checkpoint.
Args:
model (model): model to load the weights from the checkpoint.
state_dict (OrderedDict): checkpoint.
data_parallel (bool): if true, model is wrapped by
torch.nn.parallel.DistributedDataParallel.
"""
ms = model.module if data_parallel else model
model_dict = ms.state_dict()
partial_dict = OrderedDict()
for key in state_dict.keys():
if 'visual_conv' in key and 'head' not in key:
partial_dict[key] = state_dict[key]
if 'audio_conv' in key and 'head' not in key:
partial_dict[key] = state_dict[key]
update_dict = {k: v for k, v in partial_dict.items() if k in model_dict}
ms.load_state_dict(update_dict, strict=False)
def save_checkpoint(state, is_best=False, filename='checkpoint.pyth'):
"""
Save the model weights to the checkpoint.
Args:
state (Dict): model states
is_best (bool): whether the model has achieved the best performance so far.
filename (str): path to the checkpoint to save.
"""
torch.save(state, filename)
if is_best:
shutil.copyfile(filename, 'model_best.pyth')
| [
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] | |
702e2678b812860fd99d5d5961d919bb4fd981e8 | 6b033e3dddc280417bb97500f72e68d7378c69d6 | /V. Algorithm/ii. Site/D. BOJ/Dynamic Programming/2193.py | 4b960384965a4371013ee1182733e2531ed328a8 | [] | no_license | inyong37/Study | e5cb7c23f7b70fbd525066b6e53b92352a5f00bc | e36252a89b68a5b05289196c03e91291dc726bc1 | refs/heads/master | 2023-08-17T11:35:01.443213 | 2023-08-11T04:02:49 | 2023-08-11T04:02:49 | 128,149,085 | 11 | 0 | null | 2022-10-07T02:03:09 | 2018-04-05T02:17:17 | Jupyter Notebook | UTF-8 | Python | false | false | 267 | py | # n = 0: cnt = 0
# n = 1: 1 cnt = 1
# n = 2: 10 cnt = 1
# n = 3: 100, 101 cnt = 2
# n = 4: 1010, 1001, 1000 cnt =3
# n = 5: 10000, 10001, 10010, 10101, 10100 cnt =5
n = int(input())
dp = [0, 1, 1]
for i in range(3, n+1):
dp.append(dp[i-2] + dp[i-1])
print(dp[n])
| [
"[email protected]"
] | |
28d3d1162f07d7328b3463ee4a62994322b6de5c | dfc827bf144be6edf735a8b59b000d8216e4bb00 | /CODE/experimentcode/Thesis/Forced/GaussianBumpoverPeriodicBed/o3fix/Run.py | 9587f565efe9f1d699e85365195fd1c81d45552c | [] | no_license | jordanpitt3141/ALL | c5f55e2642d4c18b63b4226ddf7c8ca492c8163c | 3f35c9d8e422e9088fe096a267efda2031ba0123 | refs/heads/master | 2020-07-12T16:26:59.684440 | 2019-05-08T04:12:26 | 2019-05-08T04:12:26 | 94,275,573 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 19,675 | py | from scipy import *
from pylab import plot, show, legend,xlim,ylim,savefig,title,xlabel,ylabel,clf, loglog
import csv
import os
from Serre3 import *
from numpy.linalg import norm
from time import time
from scipy.special import erf
def copyarraytoC(a):
n = len(a)
b = mallocPy(n)
for i in range(n):
writetomem(b,i,a[i])
return b
def copyarrayfromC(a,n):
b = [0]*n
for i in range(n):
b[i] = readfrommem(a,i)
return b
def TDMApy(a,b,c,d):
n = len(d)
alpha = []
beta = []
x = [0]*n
alpha.append((1.0*c[0])/b[0])
beta.append((1.0*d[0])/b[0] )
for i in range(1,n-1):
m = 1.0 / (b[i] - a[i-1]*alpha[i-1])
alpha.append(c[i]* m)
beta.append((d[i] - a[i-1]*beta[i-1]) * m)
m = 1.0 / (b[n-1] - a[n-2]*alpha[n-2])
beta.append((d[n-1] - a[n-2]*beta[n-2]) * m)
x[n-1] = beta[n-1]
for i in range(n-2,-1,-1):
x[i] = beta[i] - alpha[i]*x[i+1]
return array(x)
#Tested from CFD forum post
def pentadiagsolve(e,a,d,c,f,B):
n = len(d)
X = zeros(n)
for i in range(1,n-1):
xmult = float(a[i-1]) / d[i-1]
d[i] = d[i] - xmult*c[i-1]
c[i] = c[i] - xmult*f[i-1]
B[i] = B[i] - xmult*B[i-1]
xmult = float(e[i-1]) /d[i-1]
a[i] = a[i] - xmult*c[i-1]
d[i+1] = d[i+1] - xmult*f[i-1]
B[i+1] = B[i+1] - xmult*B[i-1]
xmult = float(a[n-2]) / d[n-2]
d[n-1] = d[n-1] - xmult*c[n-2]
X[n-1] = (B[n-1] - xmult*B[n-2]) / float(d[n-1])
X[n-2] = (B[n-2] - c[n-2]*X[n-1]) / float(d[n-2])
for i in range(n-3,-1,-1):
X[i] = (B[i] - f[i]*X[i+2] - c[i]*X[i+1])/float(d[i])
return X
def makevar(sx,ex,dx,st,et,dt):
x = arange(sx, ex, dx)
t = arange(st, et, dt)
return x,t
def midpointtocellaverages(mq,dx):
#no BC required, assumes that the averages and midpoints at the boundaries are the same
idx = 1.0/dx
i24 = 1.0 / 24.0
n = len(mq)
a = zeros(n-1)
b = zeros(n)
c = zeros(n-1)
for i in range(1,n-1):
ai = -i24
bi = 26*i24
ci = -i24
a[i-1] = ai
b[i] = bi
c[i] = ci
#i = 0
i = 0
ai =0.0 #-i24
bi =1.0 #26*i24
ci =0.0 #-i24
b[i] = bi
c[i] = ci
#mq[i] = mq[i] - ai*qbeg[0]
#i = 0
i = n-1
ai =0.0# -i24
bi =1.0# 26*i24
ci =0.0# -i24
a[i-1] = ai
b[i] = bi
#mq[i] = mq[i] - ci*qend[0]
q = TDMApy(a,b,c,mq)
return q
def cellaveragestomidpoints(q,dx):
#no BC required, assumes that the averages and midpoints at the boundaries are the same
i24 = 1.0 / 24.0
n = len(q)
mq = zeros(n)
for i in range(1,n-1):
#iterate over the cell midpoints, there are 2 edge values for each (except the first and last cell)
#variables
#ai = (q[i+1] - 2*q[i] + q[i-1])*0.5*idx*idx
#bi = (q[i+1] - q[i-1])*0.5*idx
ci = i24*(-q[i+1] + 26*q[i] -q[i-1])
mq[i] = ci
#i = 0
i = 0
ci = q[i] #i24*(-q[i+1] + 26*q[i] - qbeg[0])
mq[i] = ci
#i = n-1
i = n-1
ci = q[i]#i24*(-qend[0] + 26*q[i] - q[i-1])
mq[i] = ci
return mq
def hI(x,t,a0,a1,a2,a3,a4,a5,a6,a7):
return a0*x - a1*sqrt(a4)*sqrt(pi/2.)*erf((a3 + a2*t - x)/(sqrt(2)*sqrt(a4)))
def hA(xi1,xi2,t,a0,a1,a2,a3,a4,a5,a6,a7):
hxi1 = hI(xi1,t,a0,a1,a2,a3,a4,a5,a6,a7)
hxi2 = hI(xi2,t,a0,a1,a2,a3,a4,a5,a6,a7)
hAv = (hxi2 - hxi1)/(xi2 - xi1)
return hAv
def uI(x,t,a0,a1,a2,a3,a4,a5,a6,a7):
return - a5*sqrt(a4)*sqrt(pi/2.)*erf((a3 + a2*t - x)/(sqrt(2)*sqrt(a4)))
def uA(xi1,xi2,t,a0,a1,a2,a3,a4,a5,a6,a7):
uxi1 = uI(xi1,t,a0,a1,a2,a3,a4,a5,a6,a7)
uxi2 = uI(xi2,t,a0,a1,a2,a3,a4,a5,a6,a7)
uAv = (uxi2 - uxi1)/(xi2 - xi1)
return uAv
def GI(x,t,a0,a1,a2,a3,a4,a5,a6,a7):
return (a5*(2*pow(e,((a3 + a2*t)*x)/a4)*pow(a1*pow(e,((a3 + a2*t)*x)/a4) + a0*pow(e,(pow(a3,2) + 2*a2*a3*t + pow(a2,2)*pow(t,2) + pow(x,2))/(2.*a4)),3)*(-a3 - a2*t + x) + \
3*a1*pow(a4,1.5)*pow(e,(2*(pow(a3,2) + 2*a2*a3*t + pow(a2,2)*pow(t,2) + pow(x,2)))/a4)*sqrt(pi)*erf((-a3 - a2*t + x)/sqrt(a4)) + \
3*a0*pow(a4,1.5)*pow(e,(2*(pow(a3,2) + 2*a2*a3*t + pow(a2,2)*pow(t,2) + pow(x,2)))/a4)*sqrt(2*pi)*erf((-a3 - a2*t + x)/(sqrt(2)*sqrt(a4)))))/(6.*a4*pow(e,(2*(pow(a3 + a2*t,2) + pow(x,2)))/a4))
def GA(xi1,xi2,t,a0,a1,a2,a3,a4,a5,a6,a7):
Gxi1 = GI(xi1,t,a0,a1,a2,a3,a4,a5,a6,a7)
Gxi2 = GI(xi2,t,a0,a1,a2,a3,a4,a5,a6,a7)
GAv = (Gxi2 - Gxi1)/ (xi2 - xi1)
return GAv
def ForcedbedA(x,t,a0,a1,a2,a3,a4,a5,a6,a7,g,dx):
n = len(x)
ha = zeros(n)
ua = zeros(n)
Ga = zeros(n)
for i in range(n):
xi1 = x[i] - 0.5*dx
xi2 = x[i] + 0.5*dx
ha[i] = hA(xi1,xi2,t,a0,a1,a2,a3,a4,a5,a6,a7)
ua[i] = uA(xi1,xi2,t,a0,a1,a2,a3,a4,a5,a6,a7)
Ga[i] = GA(xi1,xi2,t,a0,a1,a2,a3,a4,a5,a6,a7)
return ha,ua,Ga
def ForcedbedM(x,t,a0,a1,a2,a3,a4,a5,a6,a7,g,dx):
n = len(x)
h = zeros(n)
u = zeros(n)
G = zeros(n)
for i in range(n):
phi = x[i] - a2*t
h[i] = a0 + a1*exp(-(phi - a3)**2/(2*a4))
u[i] = a5*exp(-(phi - a3)**2/(2*a4))
hxi = -a1/a4*(phi - a3)*exp(-(phi - a3)**2/(2*a4))
uxi = -a5/a4*(phi - a3)*exp(-(phi - a3)**2/(2*a4))
uxxi = -a5/(a4**2)*exp(-(phi - a3)**2/(2*a4))*(a4 - ((phi) - a3)**2)
G[i] = u[i]*h[i] - h[i]*h[i]*hxi*uxi - h[i]*h[i]*h[i]/3.0*uxxi
return h,u,G
def solveGfromuh(u,h,hbeg,hend,ubeg,uend,dx):
#takes midpoint values of u,h and gives midpoint values of G
idx = 1.0 / dx
i12 = 1.0 / 12.0
i3 = 1.0 / 3.0
n = len(u)
G = zeros(n)
for i in range(2,n-2):
th = h[i]
thx = i12*idx*(-h[i+2] + 8*h[i+1] - 8*h[i-1] + h[i-2] )
ai = -(i12*idx)*(th*th*thx) +(i12*idx*idx)*(i3*th*th*th) #ui-2
bi = (8*i12*idx)*(th*th*thx) - (16*i12*idx*idx)*(i3*th*th*th) #ui-1
ci = th + (30*i12*idx*idx)*(i3*th*th*th)
di = -(8*i12*idx)*(th*th*thx) - (16*i12*idx*idx)*(i3*th*th*th) #ui+1
ei = (i12*idx)*(th*th*thx) + (i12*idx*idx)*(i3*th*th*th) #ui+2
G[i] = ai*u[i-2] + bi*u[i-1] + ci*u[i] + di*u[i+1] + ei*u[i+2]
#boundary
#i=0
i=0
th = h[i]
thx = i12*idx*(-h[i+2] + 8*h[i+1] - 8*hbeg[-1] + hbeg[-2] )
ai = -(i12*idx)*(th*th*thx) +(i12*idx*idx)*(i3*th*th*th) #ui-2
bi = (8*i12*idx)*(th*th*thx) - (16*i12*idx*idx)*(i3*th*th*th) #ui-1
ci = th + (30*i12*idx*idx)*(i3*th*th*th)
di = -(8*i12*idx)*(th*th*thx) - (16*i12*idx*idx)*(i3*th*th*th) #ui+1
ei = (i12*idx)*(th*th*thx) + (i12*idx*idx)*(i3*th*th*th) #ui+2
G[i] = ai*ubeg[-2] + bi*ubeg[-1] + ci*u[i] + di*u[i+1] + ei*u[i+2]
#i=1
i=1
th = h[i]
thx = i12*idx*(-h[i+2] + 8*h[i+1] - 8*h[i-1] + hbeg[-1] )
ai = -(i12*idx)*(th*th*thx) +(i12*idx*idx)*(i3*th*th*th) #ui-2
bi = (8*i12*idx)*(th*th*thx) - (16*i12*idx*idx)*(i3*th*th*th) #ui-1
ci = th + (30*i12*idx*idx)*(i3*th*th*th)
di = -(8*i12*idx)*(th*th*thx) - (16*i12*idx*idx)*(i3*th*th*th) #ui+1
ei = (i12*idx)*(th*th*thx) + (i12*idx*idx)*(i3*th*th*th) #ui+2
G[i] = ai*ubeg[-1] + bi*u[i-1] + ci*u[i] + di*u[i+1] + ei*u[i+2]
#boundary
#i=n-2
i=n-2
th = h[i]
thx = i12*idx*(-hend[0] + 8*h[i+1] - 8*h[i-1] + h[i-2] )
ai = -(i12*idx)*(th*th*thx) +(i12*idx*idx)*(i3*th*th*th) #ui-2
bi = (8*i12*idx)*(th*th*thx) - (16*i12*idx*idx)*(i3*th*th*th) #ui-1
ci = th + (30*i12*idx*idx)*(i3*th*th*th)
di = -(8*i12*idx)*(th*th*thx) - (16*i12*idx*idx)*(i3*th*th*th) #ui+1
ei = (i12*idx)*(th*th*thx) + (i12*idx*idx)*(i3*th*th*th) #ui+2
G[i] = ai*u[i-2] + bi*u[i-1] + ci*u[i] + di*u[i+1] + ei*uend[0]
#i=n-1
i=n-1
th = h[i]
thx = i12*idx*(-hend[1] + 8*hend[0] - 8*h[i-1] + h[i-2] )
ai = -(i12*idx)*(th*th*thx) +(i12*idx*idx)*(i3*th*th*th) #ui-2
bi = (8*i12*idx)*(th*th*thx) - (16*i12*idx*idx)*(i3*th*th*th) #ui-1
ci = th + (30*i12*idx*idx)*(i3*th*th*th)
di = -(8*i12*idx)*(th*th*thx) - (16*i12*idx*idx)*(i3*th*th*th) #ui+1
ei = (i12*idx)*(th*th*thx) + (i12*idx*idx)*(i3*th*th*th) #ui+2
G[i] = ai*u[i-2] + bi*u[i-1] + ci*u[i] + di*uend[0] + ei*uend[1]
return G
def sech2 (x):
a = 2./(exp(x) + exp(-x))
return a*a
def soliton (x,t,g,a0,a1):
c = sqrt(g*(a0 + a1))
phi = x - c*t;
k = sqrt(3.0*a1) / (2.0*a0 *sqrt(a0 + a1))
return a0 + a1*sech2(k*phi)
def solitoninit(n,a0,a1,g,x,t0,dx):
h = zeros(n)
u = zeros(n)
c = sqrt(g*(a0 + a1))
for i in range(n):
h[i] = soliton(x[i],t0,g,a0,a1)
u[i] = c* ((h[i] - a0) / h[i])
return h,u
#Forcing Problem
wdir = "../../../../../../../data/raw/Forced/FDVM3NoBed/GaussBedAll/EvotBest3/"
if not os.path.exists(wdir):
os.makedirs(wdir)
for j in range(4,15):
g =9.81
a0 = 1
a1 = 0.2
a2 = 1.3
a3 = 0.4
a4 = 1.5
a5 = 0.1
a6 = 0
a7 = 0.1
width = 20.0
g = 9.81
dx = width / (2.0)**(j)
l = 0.5 / (a5 + sqrt(g*(a0 + a1)))
dt = l*dx
startx = -width/2
endx = width/2
startt = 0.0
endt = 1
t = startt
#number of boundary conditions (one side)
nfcBC = 4 #for flux calculation
nGsBC = 2 #for solving G from u,h
niBC = nGsBC + nfcBC #total
#x,t = makevar(startx,endx +0.1*dx,dx,startt,endt,dt)
x = arange(startx,endx +0.1*dx, dx)
xmbeg = arange(startx - niBC*dx ,x[0], dx)
xmend = arange(x[-1] + dx ,x[-1] + (niBC+ 0.1)*dx, dx)
ts = []
n = len(x)
theta = 2
gap = int(1.0/dt)
hm,um,Gm = ForcedbedM(x,t,a0,a1,a2,a3,a4,a5,a6,a7,g,dx)
#bM = cos(a5*x)
print(t)
hmbeg,umbeg,Gmbeg = ForcedbedM(xmbeg,t,a0,a1,a2,a3,a4,a5,a6,a7,g,dx)
hmend,umend,Gmend = ForcedbedM(xmend,t,a0,a1,a2,a3,a4,a5,a6,a7,g,dx)
cnBC = niBC - nGsBC
umbc = concatenate([umbeg[-cnBC:],um,umend[:cnBC]])
hmbc = concatenate([hmbeg[-cnBC:],hm,hmend[:cnBC]])
Gmbc = concatenate([Gmbeg[-cnBC:],Gm,Gmend[:cnBC]])
#calculate averages
Gabc = midpointtocellaverages(Gmbc,dx)
habc = midpointtocellaverages(hmbc,dx)
uabc = midpointtocellaverages(umbc,dx)
Gabeg = Gabc[:cnBC]
Ga = Gabc[cnBC:-cnBC]
Gaend = Gabc[-cnBC:]
habeg = habc[:cnBC]
ha = habc[cnBC:-cnBC]
haend = habc[-cnBC:]
uabeg = uabc[:cnBC]
ua = uabc[cnBC:-cnBC]
uaend = uabc[-cnBC:]
Ga_c = copyarraytoC(Ga)
Gabeg_c = copyarraytoC(Gabeg)
Gaend_c = copyarraytoC(Gaend)
ha_c = copyarraytoC(ha)
habeg_c = copyarraytoC(habeg)
haend_c = copyarraytoC(haend)
uabeg_c = copyarraytoC(uabeg)
uaend_c = copyarraytoC(uaend)
hmbeg_c = copyarraytoC(hmbeg)
hmend_c = copyarraytoC(hmend)
umbeg_c = copyarraytoC(umbeg)
umend_c = copyarraytoC(umend)
u_c = mallocPy(n)
G_c = mallocPy(n)
h_c = mallocPy(n)
x_c = copyarraytoC(x)
ts.append(t)
#Just an FEM solve here
while t < endt:
evolvewrap(Ga_c,ha_c,Gabeg_c,Gaend_c,habeg_c,haend_c,hmbeg_c,hmend_c,uabeg_c,uaend_c,umbeg_c,umend_c,nfcBC,nGsBC,g,dx,dt,n,cnBC,niBC,x_c,t,a0,a1,a2,a3,a4,a5,a6,a7)
t = t + dt
ts.append(t)
print(t)
ca2midpt(ha_c,dx,n,h_c)
ca2midpt(Ga_c,dx,n,G_c)
GaC = copyarrayfromC(Ga_c,n)
haC = copyarrayfromC(ha_c,n)
GC = copyarrayfromC(G_c,n)
hC = copyarrayfromC(h_c,n)
ufromGh(G_c,h_c,hmbeg_c,hmend_c,umbeg_c,umend_c,dx,n,niBC, u_c)
uC = copyarrayfromC(u_c,n)
haA,uaA,GaA = ForcedbedA(x,t,a0,a1,a2,a3,a4,a5,a6,a7,g,dx)
hmA,umA,GmA = ForcedbedM(x,t,a0,a1,a2,a3,a4,a5,a6,a7,g,dx)
hnorm = norm(haC - haA, ord=2)/ norm(haA, ord=2)
unorm = norm(uC - umA, ord=2)/ norm(umA, ord=2)
Gnorm = norm(GaC - GaA, ord=2)/ norm(GaA, ord=2)
s = wdir + "h.dat"
with open(s,'a') as file1:
s ="%3.8f%5s%1.20f\n" %(dx," ",hnorm)
file1.write(s)
s = wdir + "G.dat"
with open(s,'a') as file1:
s ="%3.8f%5s%1.20f\n" %(dx," ",Gnorm)
file1.write(s)
s = wdir + "u.dat"
with open(s,'a') as file1:
s ="%3.8f%5s%1.20f\n" %(dx," ",unorm)
file1.write(s)
deallocPy(ha_c)
deallocPy(Ga_c)
deallocPy(h_c)
deallocPy(G_c)
deallocPy(u_c)
deallocPy(hmbeg_c)
deallocPy(umbeg_c)
deallocPy(hmend_c)
deallocPy(umend_c)
deallocPy(habeg_c)
deallocPy(Gabeg_c)
deallocPy(uabeg_c)
deallocPy(haend_c)
deallocPy(Gaend_c)
deallocPy(uaend_c)
"""
##Accuracy Test
### Soliton Accuracy ################
wdir = "../../../../../../../data/raw/Forced/FDVM3NoBed/GaussBedAll/Soliton1/"
if not os.path.exists(wdir):
os.makedirs(wdir)
s = wdir + "savenorms.txt"
with open(s,'a') as file1:
writefile = csv.writer(file1, delimiter = ',', quotechar='|', quoting=csv.QUOTE_MINIMAL)
writefile.writerow(['dx','Normalised L1-norm Difference Height', ' Normalised L1-norm Difference Velocity','Hamiltonian Difference'])
for k in range(6,21):
dx = 100.0 / (2**k)
a0 = 1.0
a1 = 0.7
g = 9.81
#g = 1.0
Cr = 0.5
l = 1.0 / (sqrt(g*(a0 + a1)))
dt = Cr*l*dx
startx = -250.0
endx = 250.0 + dx
startt = 0.0
endt = 1 + dt
print(dx,dt)
szoomx = startx
ezoomx = endx
#number of boundary conditions (one side)
nfcBC = 4 #for flux calculation
nGsBC = 2 #for solving G from u,h
niBC = nGsBC + nfcBC #total
wdatadir = wdir+ str(k) + "/"
if not os.path.exists(wdatadir):
os.makedirs(wdatadir)
gap =int(10.0/dt)
x,t = makevar(startx,endx,dx,startt,endt,dt)
n = len(x)
t0 = 0.0
hm,um = solitoninit(n,a0,a1,g,x,t0,dx)
umbeg = um[0]*ones(niBC)
umend = um[-1]*ones(niBC)
hmbeg = hm[0]*ones(niBC)
hmend = hm[-1]*ones(niBC)
#calculate G midpoint
cnBC = niBC - nGsBC
umbc = concatenate([umbeg[-cnBC:],um,umend[0:cnBC]])
hmbc = concatenate([hmbeg[-cnBC:],hm,hmend[0:cnBC]])
Gmbc = solveGfromuh(umbc,hmbc,hmbeg[0:-cnBC],hmend[-cnBC:],umbeg[0:-cnBC],umend[-cnBC:],dx)
#calculate averages
Gabc = midpointtocellaverages(Gmbc,dx)
habc = midpointtocellaverages(hmbc,dx)
uabc = midpointtocellaverages(umbc,dx)
#so we can just go from here with Ga ang ha?
Gabeg = Gabc[0:cnBC]
Ga = Gabc[cnBC:-cnBC]
Gaend = Gabc[-cnBC:]
habeg = habc[0:cnBC]
ha = habc[cnBC:-cnBC]
haend = habc[-cnBC:]
uabeg = uabc[0:cnBC]
ua = uabc[cnBC:-cnBC]
uaend = uabc[-cnBC:]
Ga_c = copyarraytoC(Ga)
Gabeg_c = copyarraytoC(Gabeg)
Gaend_c = copyarraytoC(Gaend)
ha_c = copyarraytoC(ha)
habeg_c = copyarraytoC(habeg)
haend_c = copyarraytoC(haend)
uabeg_c = copyarraytoC(uabeg)
uaend_c = copyarraytoC(uaend)
hmbeg_c = copyarraytoC(hmbeg)
hmend_c = copyarraytoC(hmend)
umbeg_c = copyarraytoC(umbeg)
umend_c = copyarraytoC(umend)
u_c = mallocPy(n)
G_c = mallocPy(n)
h_c = mallocPy(n)
xbeg = arange(startx - niBC*dx,startx,dx)
xend = arange(endx + dx,endx + (niBC+1)*dx)
xbc = concatenate([xbeg,x,xend])
x_c = copyarraytoC(x)
xbc_c = copyarraytoC(xbc)
hbc_c = mallocPy(n + 2*niBC)
ubc_c = mallocPy(n + 2*niBC)
Evals = []
for i in range(1,len(t)):
if(i % gap == 0 or i ==1):
ca2midpt(ha_c,dx,n,h_c)
ca2midpt(Ga_c,dx,n,G_c)
ufromGh(G_c,h_c,hmbeg_c,hmend_c,umbeg_c,umend_c,dx,n,niBC, u_c)
conc(hmbeg_c , h_c,hmend_c,niBC,n ,niBC , hbc_c)
conc(umbeg_c , u_c,umend_c,niBC,n ,niBC , ubc_c)
Eval =1
#Eval = HankEnergyall(xbc_c,hbc_c,ubc_c,g,n + 2*niBC,niBC,dx)
Evals.append(Eval)
u = copyarrayfromC(u_c,n)
G = copyarrayfromC(G_c,n)
h = copyarrayfromC(h_c,n)
c = sqrt(g*(a0 + a1))
htrue = zeros(n)
utrue = zeros(n)
for j in range(n):
he = soliton(x[j],t[i],g,a0,a1)
htrue[j] = he
utrue[j] = c* ((he - a0) / he)
s = wdatadir + "saveoutputts" + str(i) + ".txt"
print t[i]
print(h[3],G[3])
with open(s,'a') as file2:
writefile2 = csv.writer(file2, delimiter = ',', quotechar='|', quoting=csv.QUOTE_MINIMAL)
writefile2.writerow(['dx' ,'dt','time','xi','Eval', 'height(m)', 'G' , 'u(m/s)','true height', 'true velocity' ])
for j in range(n):
writefile2.writerow([str(dx),str(dt),str(t[i]),str(x[j]),str(Eval), str(h[j]) , str(G[j]) , str(u[j]), str(htrue[j]), str(utrue[j])])
evolvewrap(Ga_c,ha_c,Gabeg_c,Gaend_c,habeg_c,haend_c,hmbeg_c,hmend_c,uabeg_c,uaend_c,umbeg_c,umend_c,nfcBC,nGsBC,g,dx,dt,n,cnBC,niBC,x_c,t[i-1],0.0,0.0,1,1,1,0.0,1,1)
#evolvewrap(Ga_c,ha_c,Gabeg_c,Gaend_c,habeg_c,haend_c,hmbeg_c,hmend_c,uabeg_c,uaend_c,umbeg_c,umend_c,nfcBC,nGsBC,g,dx,dt,n,cnBC,niBC)
print t[i]
print(h[3],G[3])
ca2midpt(ha_c,dx,n,h_c)
ca2midpt(Ga_c,dx,n,G_c)
ufromGh(G_c,h_c,hmbeg_c,hmend_c,umbeg_c,umend_c,dx,n,niBC, u_c)
conc(hmbeg_c , h_c,hmend_c,niBC,n ,niBC , hbc_c)
conc(umbeg_c , u_c,umend_c,niBC,n ,niBC , ubc_c)
Eval = 1
Evals.append(Eval)
u = copyarrayfromC(u_c,n)
G = copyarrayfromC(G_c,n)
h = copyarrayfromC(h_c,n)
c = sqrt(g*(a0 + a1))
htrue = zeros(n)
utrue = zeros(n)
for j in range(n):
he = soliton(x[j],t[i],g,a0,a1)
htrue[j] = he
utrue[j] = c* ((he - a0) / he)
s = wdatadir + "saveoutputtslast.txt"
with open(s,'a') as file2:
writefile2 = csv.writer(file2, delimiter = ',', quotechar='|', quoting=csv.QUOTE_MINIMAL)
writefile2.writerow(['dx' ,'dt','time','xi','Eval', 'height(m)', 'G' , 'u(m/s)','true height', 'true velocity' ])
for j in range(n):
writefile2.writerow([str(dx),str(dt),str(t[i]),str(x[j]),str(Eval), str(h[j]) , str(G[j]) , str(u[j]), str(htrue[j]), str(utrue[j])])
normhdiffi = norm(h - htrue,ord=1) / norm(htrue,ord=1)
normudiffi = norm(u -utrue,ord=1) / norm(utrue,ord=1)
normHamdiff = (Evals[-1] - Evals[0])/ Evals[0]
s = wdir + "savenorms.txt"
with open(s,'a') as file1:
writefile = csv.writer(file1, delimiter = ',', quotechar='|', quoting=csv.QUOTE_MINIMAL)
writefile.writerow([str(dx),str(normhdiffi), str(normudiffi),str(normHamdiff)])
s = wdir + "h.dat"
with open(s,'a') as file1:
s ="%3.8f%5s%1.20f\n" %(dx," ",normhdiffi)
file1.write(s)
s = wdir + "u.dat"
with open(s,'a') as file1:
s ="%3.8f%5s%1.20f\n" %(dx," ",normudiffi)
file1.write(s)
"""
| [
"[email protected]"
] | |
0bac063d3a631ce56e9092d9b9ec1bbbc00858ec | 6ab31b5f3a5f26d4d534abc4b197fe469a68e8e5 | /katas/kyu_7/zip_it.py | 733c9415236cc72574804bc9a23e8b2577159867 | [
"MIT"
] | permissive | mveselov/CodeWars | e4259194bfa018299906f42cd02b8ef4e5ab6caa | 1eafd1247d60955a5dfb63e4882e8ce86019f43a | refs/heads/master | 2021-06-09T04:17:10.053324 | 2017-01-08T06:36:17 | 2017-01-08T06:36:17 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 61 | py | def lstzip(a, b, fn):
return [fn(*c) for c in zip(a, b)]
| [
"[email protected]"
] | |
ef0fde3342528da0960d780262d15269aad0afbf | bbffa308bee71735e27987be37a574a38694d3a1 | /ex08/ex08.py | 52fbeae895a4ee9c1a5535ab3b30ad4db9603f7c | [] | no_license | jppiri1/16PF-C-jppiri1-2- | 03414b545bc4f1e05e92d6ccbc5ba326a9725277 | 68afbe01a5f8a1e55a114bd38f5ea2a4a2fb6595 | refs/heads/master | 2021-01-21T04:47:22.266089 | 2016-06-07T03:58:14 | 2016-06-07T03:58:14 | 54,304,826 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 353 | py | formatter = "%r %r %r %r"
print formatter % (1, 2, 3, 4)
print formatter % ("one", "two", "three", "four")
print formatter % (True, False, False, True)
print formatter % (formatter, formatter, formatter, formatter)
print formatter % (
"I had this thing.",
"That you could type up right.",
"But it didn`t sing.",
"So I said goodnight."
) | [
"CAD Client"
] | CAD Client |
6d6ea4a6da71a4dd55b9827ed63099c095f2893a | 70fa6468c768d4ec9b4b14fc94fa785da557f1b5 | /lib/surface/config/configurations/list.py | 31105c5866eaeddb88a441350c50f64724d0caa9 | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | permissive | kylewuolle/google-cloud-sdk | d43286ef646aec053ecd7eb58566ab2075e04e76 | 75f09ebe779e99fdc3fd13b48621fe12bfaa11aa | refs/heads/master | 2020-04-20T22:10:41.774132 | 2019-01-26T09:29:26 | 2019-01-26T09:29:26 | 169,131,028 | 0 | 0 | NOASSERTION | 2019-02-04T19:04:40 | 2019-02-04T18:58:36 | Python | UTF-8 | Python | false | false | 2,213 | py | # -*- coding: utf-8 -*- #
# Copyright 2015 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Command to list named configuration."""
from __future__ import absolute_import
from __future__ import division
from __future__ import unicode_literals
from googlecloudsdk.calliope import base
from googlecloudsdk.core import properties
from googlecloudsdk.core.configurations import named_configs
from googlecloudsdk.core.configurations import properties_file
import six
class List(base.ListCommand):
"""Lists existing named configurations."""
detailed_help = {
'DESCRIPTION': """\
{description}
Run `$ gcloud topic configurations` for an overview of named
configurations.
""",
'EXAMPLES': """\
To list all available configurations, run:
$ {command}
""",
}
@staticmethod
def Args(parser):
base.PAGE_SIZE_FLAG.RemoveFromParser(parser)
base.URI_FLAG.RemoveFromParser(parser)
parser.display_info.AddFormat("""table(
name,
is_active,
properties.core.account,
properties.core.project,
properties.compute.zone:label=DEFAULT_ZONE,
properties.compute.region:label=DEFAULT_REGION)
""")
def Run(self, args):
configs = named_configs.ConfigurationStore.AllConfigs()
for _, config in sorted(six.iteritems(configs)):
props = properties.VALUES.AllValues(
list_unset=True,
properties_file=properties_file.PropertiesFile([config.file_path]),
only_file_contents=True)
yield {
'name': config.name,
'is_active': config.is_active,
'properties': props,
}
| [
"[email protected]"
] | |
b72639fefb186348b900a58c7e765b4f198fea4c | f8d0e0358cfc7774e2ade30fb041a7227f72f696 | /Project/MNIST/Actual_Picture/mnist_generate_dataset.py | 7fad26b687d9e1f1ecda401e1fd57dbd54d78c55 | [] | no_license | KimDaeUng/DeepLearningPractice | e01c99d868e7a472ca5ec9c863990e0ab4b48529 | 811f26e0859f0f7cb73d9a0ce3529fb8db867442 | refs/heads/master | 2023-04-01T02:26:14.670687 | 2021-04-03T14:08:48 | 2021-04-03T14:08:48 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,470 | py | import tensorflow as tf
import numpy as np
from PIL import Image
import os
# Generate standard tfrecord of training or testing set
image_train_path = './mnist_data_jpg/mnist_train_jpg_60000/'
label_train_path = './mnist_data_jpg/mnist_train_jpg_60000.txt'
image_test_path = './mnist_data_jpg/mnist_test_jpg_10000/'
label_test_path = './mnist_data_jpg/mnist_test_jpg_10000.txt'
data_path = './data/'
tfRecord_train = './data/mnist_train.tfrecords'
tfRecord_test = './data/mnist_test.tfrecords'
resize_height = 28; resize_width = 28
# Generate tfRecord file
def write_tfRecord(tfRecordName, image_path, label_path):
writer = tf.python_io.TFRecordWriter(tfRecordName) # Create a writer
with open(label_path, 'r') as label_file:
picfile_label_pair = label_file.readlines()
for num, content in enumerate(picfile_label_pair):
# Construct picture path
picfile, label = content.split()
pic_path = image_path + picfile
img = Image.open(pic_path)
img_raw = img.tobytes() # Transfer image into bytes
# One-hot encode: transfer label e.g. 3 -> 0001000000
labels = [0] * 10
labels[int(label)] = 1
# Create an example
example = tf.train.Example(features=tf.train.Features(feature={
'img_raw': tf.train.Feature(bytes_list=tf.train.BytesList(value=[img_raw])),
'label': tf.train.Feature(int64_list=tf.train.Int64List(value=labels))
})) # warp image and label data
writer.write(example.SerializeToString()) # serialize the example
#print("finish processing number of picture: ", num + 1)
writer.close()
#print("write tfRecord successfully")
def generate_tfRecord():
if not os.path.exists(data_path):
# if the folder doesn't exist then mkdir
os.makedirs(data_path)
else:
print("Directory has already existed")
# Generate training set
print("Generating training set...")
write_tfRecord(tfRecord_train, image_train_path, label_train_path)
# Generate test set
print("Generating test set...")
write_tfRecord(tfRecord_test, image_test_path, label_test_path)
def read_tfRecord(tfRecord_path):
filename_queue = tf.train.string_input_producer([tfRecord_path])
# TFRecordReader has been deprecated
reader = tf.TFRecordReader() # Create a reader
serialized_example = reader.read(filename_queue)[1] # store samples
features = tf.parse_single_example(serialized_example, features={
'label': tf.FixedLenFeature([10], tf.int64),
'img_raw': tf.FixedLenFeature([], tf.string)
})
img = tf.decode_raw(features['img_raw'], tf.uint8) # Decode img_raw into unsigned int
img.set_shape([784]) # Reshape image into a row of 784 pixel
img = tf.cast(img, tf.float32) * (1/255) # Normalize image into float
label = tf.cast(features['label'], tf.float32) # Transfer label into float
return img, label
# Construct a batcher (generator)
def get_tfRecord(num, getTrain=True):
if getTrain:
tfRecord_path = tfRecord_train
else:
tfRecord_path = tfRecord_test
img, label = read_tfRecord(tfRecord_path)
# Shuffle the image order
img_batch, label_batch = tf.train.shuffle_batch([img, label], batch_size=num, num_threads=2, capacity=1000, min_after_dequeue=700)
return img_batch, label_batch
def main():
generate_tfRecord()
if __name__ == '__main__':
main()
| [
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] | |
de2a5e9123899c4d2aa008f270bed4e1523f7c76 | 2ba65a65140e818787ab455ca374f99348ade844 | /hashmap_and_heap/q004_longest_consecutive_sequence.py | 30fea9fc4eba2b9a20ea220cdbe5bcb49156643d | [] | no_license | samyakjain101/DSA | 9e917f817a1cf69553b5f8ca5b739bc6f0c81307 | 632a605150704ceb5238cb77289785eb5a58201c | refs/heads/main | 2023-05-06T06:31:09.401315 | 2021-06-01T13:37:59 | 2021-06-01T13:37:59 | 340,645,897 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,033 | py | def longest_consecutive_sequence(arr: list):
hashmap = dict()
for num in arr:
hashmap[num] = True
for key in hashmap.keys():
if key - 1 in hashmap:
hashmap[key] = False
max_streak_start_point = 0
max_streak = 0
for key, value in hashmap.items():
if value:
temp_streak_start_point = key
temp_streak = 1
while temp_streak_start_point + temp_streak in hashmap:
temp_streak += 1
if temp_streak > max_streak:
max_streak = temp_streak
max_streak_start_point = temp_streak_start_point
return [
i for i in range(max_streak_start_point, max_streak_start_point + max_streak)
]
if __name__ == "__main__":
array = [
12,
5,
1,
2,
10,
2,
13,
7,
11,
8,
9,
11,
8,
9,
5,
6,
11,
]
print(longest_consecutive_sequence(array))
| [
"[email protected]"
] | |
a52be340b6e6941cb775fd9f43ea853958806772 | f0a44b63a385e1c0f1f5a15160b446c2a2ddd6fc | /examples/render/show_all_std_line_types.py | e9df274fed178676f291164a7d5210d8cc1bb535 | [
"MIT"
] | permissive | triroakenshield/ezdxf | 5652326710f2a24652605cdeae9dd6fc58e4f2eb | 82e964a574bcb86febc677bd63f1626318f51caf | refs/heads/master | 2023-08-17T12:17:02.583094 | 2021-10-09T08:23:36 | 2021-10-09T08:23:36 | 415,426,069 | 1 | 0 | MIT | 2021-10-09T21:31:25 | 2021-10-09T21:31:25 | null | UTF-8 | Python | false | false | 726 | py | # Copyright (c) 2019-2021, Manfred Moitzi
# License: MIT License
import ezdxf
from ezdxf.math import Vec3
from ezdxf.tools.standards import linetypes
doc = ezdxf.new("R2007", setup=True)
msp = doc.modelspace()
# How to change the global linetype scaling:
doc.header["$LTSCALE"] = 0.5
p1 = Vec3(0, 0)
p2 = Vec3(9, 0)
delta = Vec3(0, -1)
text_offset = Vec3(0, 0.1)
for lt in linetypes():
name = lt[0]
msp.add_line(p1, p2, dxfattribs={"linetype": name, "lineweight": 25})
msp.add_text(
name, dxfattribs={"style": "OpenSansCondensed-Light", "height": 0.25}
).set_pos(p1 + text_offset)
p1 += delta
p2 += delta
doc.set_modelspace_vport(25, center=(5, -10))
doc.saveas("all_std_line_types.dxf")
| [
"[email protected]"
] | |
2765443d9dab3cb470fb4a2a844eff84e6645762 | 3a51e7173c1b5a5088ac57f668ecb531e514e0fe | /m11_feature_importances5_diabets.py | e18b4753ce0bb3c9ed11c5bde334cc898d0c903c | [] | no_license | marattang/ml_basic | 83a167324317178701ae0ee0e2e2046293eafacc | e8e6b8c9ab7d866377eb01e50ac94ff5b1ea7a73 | refs/heads/main | 2023-07-05T03:30:24.663574 | 2021-08-22T07:06:58 | 2021-08-22T07:06:58 | 394,574,251 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,744 | py | # 피처 = 컬럼 = 열
from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor
from sklearn.datasets import load_iris, load_boston, load_diabetes
from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor
from sklearn.model_selection import train_test_split
import matplotlib.pyplot as plt
import numpy as np
# 1. 데이터
datasets = load_diabetes()
x_train, x_test, y_train, y_test = train_test_split(
datasets.data, datasets.target, train_size=0.8, random_state=66
)
# 2. 모델
# model = DecisionTreeRegressor(max_depth=3)
model = RandomForestRegressor()
# 3. 훈련
model.fit(x_train, y_train)
# 4. 평가 예측
r2 = model.score(x_test, y_test)
print('r2 : ', r2)
print(model.feature_importances_) # [0.0125026 0. 0.53835801 0.44913938]
# 트리계열에서는 모델 자체가 성능도 괜찮지만, feature importance라는 기능이 있다. 아이리스는 컬럼이 4개라서 4개 수치가 나온다.
# 4개의 컬럼이 훈련에 대한 영향도 두번째 컬럼같은 경우는 0이 나왔기 때문에 크게 중요하지 않은 컬럼이다. => 절대적이지 않고 상대적
# '의사결정트리'에서 사용했을 때 2번째 컬럼이 크게 도움이 안된다는 얘기
def plot_feature_importances_datasets(model):
n_features = datasets.data.shape[1]
plt.barh(np.arange(n_features), model.feature_importances_,
align='center')
plt.yticks(np.arange(n_features), datasets.feature_names)
plt.xlabel("Feature Importances")
plt.ylabel("Features")
plt.ylim(-1, n_features)
plot_feature_importances_datasets(model)
plt.show()
# DecisionTreeRegressor
# r2 : 0.3139678308823193
# # RandomForestRegressor
# r2 : 0.38347482197285554 | [
"[email protected]"
] | |
fcbd61892093b56028d5617ccab23d3aca729c0a | ed12b604e0626c1393406d3495ef5bbaef136e8a | /Iniciante/Python/exercises from 1000 to 1099/exercise_1038.py | 8acf7316aa83808418ceec78f9e872c26c2019c0 | [] | no_license | NikolasMatias/urionlinejudge-exercises | 70200edfd2f9fc3889e024dface2579b7531ba65 | ca658ee8b2100e2b687c3a081555fa0770b86198 | refs/heads/main | 2023-09-01T20:33:53.150414 | 2023-08-21T07:07:32 | 2023-08-21T07:07:32 | 361,160,388 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 689 | py | class Lanche:
def __init__(self, codigo, especificacao, preco):
self.codigo = codigo
self.especificacao = especificacao
self.preco = preco
def getCodigo(self):
return self.codigo
def totalPorQtde(self, qtde):
return self.preco*qtde
lanches = [
Lanche(1, 'Cachorro Quente', 4.00),
Lanche(2, 'X-Salada', 4.50),
Lanche(3, 'X-Bacon', 5.00),
Lanche(4, 'Torrada simples', 2.00),
Lanche(5, 'Refrigerante', 1.50)
]
codigo, qtde = [int(x) for x in input().split()]
for lanche in lanches:
if codigo == lanche.getCodigo():
print(''.join(['Total: R$ ', "{:.2f}".format(lanche.totalPorQtde(qtde))]))
break | [
"[email protected]"
] | |
cd7e960b609e7bd09f05f15573c42dcc430c91db | da1721d2783ea4d67ff4e73cee6eee71292f2ef7 | /otp/speedchat/SCConstants.py | 2be1e5050c9f147748d69e0013a2c2d587f0b00e | [
"BSD-3-Clause"
] | permissive | open-toontown/open-toontown | bbdeb1b7bf0fb2861eba2df5483738c0112090ca | 464c2d45f60551c31397bd03561582804e760b4a | refs/heads/develop | 2023-07-07T01:34:31.959657 | 2023-05-30T23:49:10 | 2023-05-30T23:49:10 | 219,221,570 | 143 | 104 | BSD-3-Clause | 2023-09-11T09:52:34 | 2019-11-02T22:24:38 | Python | UTF-8 | Python | false | false | 59 | py | SCMenuFinalizePriority = 48
SCElementFinalizePriority = 47
| [
"[email protected]"
] | |
a4c0f7cac515fab2dde43dae019bf1f9f9359d98 | e000416c89725db514ed5c01d7b9ef8e37c5355f | /backend/wallet/migrations/0001_initial.py | 42f6e380119fb0d9602b441bb339d9aa4929f923 | [] | no_license | crowdbotics-apps/click-time-28533 | 376f4d34b10ca3050fde3f43df51233e5b612c2d | 89f4f7e05bf04623b2822899677b6c3606968151 | refs/heads/master | 2023-06-19T06:37:55.564153 | 2021-07-07T06:12:26 | 2021-07-07T06:12:26 | 383,692,230 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,875 | py | # Generated by Django 2.2.20 on 2021-07-07 06:12
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
('taxi_profile', '0001_initial'),
]
operations = [
migrations.CreateModel(
name='UserWallet',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('balance', models.FloatField()),
('expiration_date', models.DateTimeField()),
('user', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, related_name='userwallet_user', to='taxi_profile.UserProfile')),
],
),
migrations.CreateModel(
name='PaymentMethod',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('account_token', models.CharField(max_length=255)),
('payment_account', models.CharField(max_length=10)),
('timestamp_created', models.DateTimeField(auto_now_add=True)),
('wallet', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='paymentmethod_wallet', to='wallet.UserWallet')),
],
),
migrations.CreateModel(
name='DriverWallet',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('balance', models.FloatField()),
('expiration_date', models.DateTimeField()),
('driver', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, related_name='driverwallet_driver', to='taxi_profile.DriverProfile')),
],
),
]
| [
"[email protected]"
] | |
df398393aea5d0bd7445abc5140d3c360b258e60 | 973713f993166b1d0c2063f6e84361f05803886d | /Day01-15/02_variableTest_3.py | 0a1660b15ed013535066fbed5471a61876d4a6c4 | [
"MIT"
] | permissive | MaoningGuan/Python-100-Days | 20ad669bcc0876b5adfbf2c09b4d25fd4691061a | d36e49d67a134278455438348efc41ffb28b778a | refs/heads/master | 2022-11-17T12:24:45.436100 | 2020-07-18T02:24:42 | 2020-07-18T02:24:42 | 275,157,107 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 589 | py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
使用input()函数获取键盘输入(字符串)
使用int()函数将输入的字符串转换成整数
使用print()函数输出带占位符的字符串
"""
a = int(input('a = '))
b = int(input('b = '))
print('%d + %d = %d' % (a, b, a + b)) # 加
print('%d - %d = %d' % (a, b, a - b)) # 减
print('%d * %d = %d' % (a, b, a * b)) # 乘
print('%d / %d = %f' % (a, b, a / b)) # 除
print('%d // %d = %d' % (a, b, a // b)) # 取商
print('%d %% %d = %d' % (a, b, a % b)) # 取余
print('%d ** %d = %d' % (a, b, a ** b)) # a的b次方
| [
"[email protected]"
] | |
76932cd1b6b43895415a527d17b4c0e8cb38af66 | 832852c679816673f708860929a36a20ca8d3e32 | /Configurations/ssww/wz_2016/aliases.py | a756db225a536ee8ec45575ec6dd07cef7eb15b0 | [] | no_license | UniMiBAnalyses/PlotsConfigurations | c4ec7376e2757b838930dfb2615e1dc99a64e542 | 578fe518cfc608169d3418bcb63a8342d3a24390 | refs/heads/master | 2023-08-31T17:57:45.396325 | 2022-09-01T10:13:14 | 2022-09-01T10:13:14 | 172,092,793 | 0 | 13 | null | 2023-04-27T10:26:52 | 2019-02-22T15:52:44 | Python | UTF-8 | Python | false | false | 12,366 | py | import inspect
configurations = os.path.realpath(inspect.getfile(inspect.currentframe())) # this file
configurations = os.path.dirname(configurations) # Full2017
configurations = os.path.dirname(configurations) # ggH
configurations = os.path.dirname(configurations) # Configurations
#aliases = {}
bAlgo = 'DeepB'
bWP = '0.4941'
mc = [skey for skey in samples if skey not in ('Fake_lep_2016','Fake_lep_2017','Fake_lep_2018','Fake_lep','DATA_2016', 'DATA_2017', 'DATA_2018','DATA')]
# fiducial
aliases['wzinc'] = {
'linesToAdd': ['.L %s/ssww/wz_2016/wzinc.cc+' % configurations],
'class': 'Wzinc',
}
aliases['zz'] = {
'linesToAdd': ['.L %s/ssww/wz_2016/zz.cc+' % configurations],
'class': 'Zz',
}
aliases['gstarLow'] = {
'expr': 'Gen_ZGstar_mass >0 && Gen_ZGstar_mass < 4',
'samples': ['VgS','VgS1','VgS2']
}
aliases['gstarHigh'] = {
'expr': 'Gen_ZGstar_mass <0 || Gen_ZGstar_mass > 4',
'samples': ['VgS','VgS1','VgS2']
}
# tau veto
aliases['softmuon_veto']={
'expr':'(Sum$(abs(Muon_dxy)<0.02 && abs(Muon_dz)<0.1 && Muon_softId && Muon_pt>5 && abs(Muon_eta)<2.4 && sqrt( pow(Muon_eta - Lepton_eta[0], 2) + pow(abs(abs(Muon_phi - Lepton_phi[0])-pi)-pi, 2) ) >= 0.4 && sqrt( pow(Muon_eta - Lepton_eta[1], 2) + pow(abs(abs(Muon_phi - Lepton_phi[1])-pi)-pi, 2) ) >= 0.4 && sqrt( pow(Muon_eta - Lepton_eta[2], 2) + pow(abs(abs(Muon_phi - Lepton_phi[2])-pi)-pi, 2) ) >= 0.4)==0)'
}
# lepton sf
#eleWP = 'mvaFall17V2Iso_WP90_SS'
eleWP = 'cut_WP_Tight80X_SS'
muWP = 'cut_Tight80x'
aliases['LepWPCut'] = {
'expr': 'LepCut3l__ele_'+eleWP+'__mu_'+muWP,
'samples': mc + ['DATA']
}
# Fake leptons transfer factor
aliases['fakeW'] = {
#'expr': 'fakeW2l_ele_'+eleWP+'_mu_'+muWP,
'expr': 'fakeW_ele_'+eleWP+'_mu_'+muWP+'_3l',
'samples': ['Fake_lep']
}
# And variations - already divided by central values in formulas !
aliases['fakeWEleUp'] = {
#'expr': 'fakeW2l_ele_'+eleWP+'_mu_'+muWP+'_EleUp',
'expr': 'fakeW_ele_'+eleWP+'_mu_'+muWP+'_3lElUp',
'samples': ['Fake_lep']
}
aliases['fakeWEleDown'] = {
#'expr': 'fakeW2l_ele_'+eleWP+'_mu_'+muWP+'_EleDown',
'expr': 'fakeW_ele_'+eleWP+'_mu_'+muWP+'_3lElDown',
'samples': ['Fake_lep']
}
aliases['fakeWMuUp'] = {
#'expr': 'fakeW2l_ele_'+eleWP+'_mu_'+muWP+'_MuUp',
'expr': 'fakeW_ele_'+eleWP+'_mu_'+muWP+'_3lMuUp',
'samples': ['Fake_lep']
}
aliases['fakeWMuDown'] = {
#'expr': 'fakeW2l_ele_'+eleWP+'_mu_'+muWP+'_MuDown',
'expr': 'fakeW_ele_'+eleWP+'_mu_'+muWP+'_3lMuDown',
'samples': ['Fake_lep']
}
aliases['fakeWStatEleUp'] = {
#'expr': 'fakeW2l_ele_'+eleWP+'_mu_'+muWP+'_statEleUp',
'expr': 'fakeW_ele_'+eleWP+'_mu_'+muWP+'_3lstatElUp',
'samples': ['Fake_lep']
}
aliases['fakeWStatEleDown'] = {
#'expr': 'fakeW2l_ele_'+eleWP+'_mu_'+muWP+'_statEleDown',
'expr': 'fakeW_ele_'+eleWP+'_mu_'+muWP+'_3lstatElDown',
'samples': ['Fake_lep']
}
aliases['fakeWStatMuUp'] = {
#'expr': 'fakeW2l_ele_'+eleWP+'_mu_'+muWP+'_statMuUp',
'expr': 'fakeW_ele_'+eleWP+'_mu_'+muWP+'_3lstatMuUp',
'samples': ['Fake_lep']
}
aliases['fakeWStatMuDown'] = {
#'expr': 'fakeW2l_ele_'+eleWP+'_mu_'+muWP+'_statMuDown',
'expr': 'fakeW_ele_'+eleWP+'_mu_'+muWP+'_3lstatMuDown',
'samples': ['Fake_lep']
}
# gen-matching to prompt only (GenLepMatch2l matches to *any* gen lepton)
aliases['PromptGenLepMatch3l'] = {
'expr': 'Alt$(Lepton_promptgenmatched[0]*Lepton_promptgenmatched[1]*Lepton_promptgenmatched[2], 0)',
'samples': mc
}
aliases['Top_pTrw'] = {
'expr': '(topGenPt * antitopGenPt > 0.) * (TMath::Sqrt(TMath::Exp(0.0615 - 0.0005 * topGenPt) * TMath::Exp(0.0615 - 0.0005 * antitopGenPt))) + (topGenPt * antitopGenPt <= 0.)',
'samples': ['top']
}
#bjet
# No jet with pt > 30 GeV
aliases['zeroJet'] = {
'expr': 'Alt$(CleanJet_pt[0], 0) < 30.'
}
# ==1 jet with pt > 30 GeV
aliases['oneJet'] = {
'expr': 'Alt$(CleanJet_pt[0], 0) >= 30. && Alt$(CleanJet_pt[1], 0) < 30.'
}
# ==2 jets with pt > 30 GeV
aliases['twoJet'] = {
'expr': 'Alt$(CleanJet_pt[0], 0) >= 30. && Alt$(CleanJet_pt[1], 0) >= 30. && Alt$(CleanJet_pt[2], 0) < 30.'
}
# >=2 jets with pt > 30 GeV
aliases['twoJetOrMore'] = {
'expr': 'Alt$(CleanJet_pt[0], 0) >= 30. && Alt$(CleanJet_pt[1], 0) >= 30.'
}
aliases['bVeto'] = {
'expr': 'Sum$(CleanJet_pt > 30. && abs(CleanJet_eta) < 2.5 && Jet_btagDeepB[CleanJet_jetIdx] > 0.6321) == 0'
}
aliases['bReq'] = {
'expr': 'Sum$(CleanJet_pt > 30. && abs(CleanJet_eta) < 2.5 && Jet_btagDeepB[CleanJet_jetIdx] > 0.8953) >= 1'
}
aliases['btag0'] = {
'expr': 'zeroJet && !bVeto'
}
aliases['btag1'] = {
'expr': 'oneJet && bReq'
}
aliases['btag2'] = {
'expr': 'twoJet && bReq'
}
# lepton eta range
aliases['lep0eta']={
'expr': '((abs(Alt$(Lepton_pdgId[0],-9999))==11 && abs(Alt$(Lepton_eta[0],-9999.)) <2.5) || (abs(Alt$(Lepton_pdgId[0],-9999))==13 && abs(Alt$(Lepton_eta[0],-9999.)) <2.4))'
}
aliases['lep1eta']={
'expr': '((abs(Alt$(Lepton_pdgId[1],-9999))==11 && abs(Alt$(Lepton_eta[1],-9999.)) <2.5) || (abs(Alt$(Lepton_pdgId[1],-9999))==13 && abs(Alt$(Lepton_eta[1],-9999.)) <2.4))'
}
aliases['lep2eta']={
'expr': '((abs(Alt$(Lepton_pdgId[2],-9999))==11 && abs(Alt$(Lepton_eta[2],-9999.)) <2.5) || (abs(Alt$(Lepton_pdgId[2],-9999))==13 && abs(Alt$(Lepton_eta[2],-9999.)) <2.4))'
}
aliases['lep3eta']={
'expr': '((abs(Alt$(Lepton_pdgId[3],-9999))==11 && abs(Alt$(Lepton_eta[3],-9999.)) <2.5) || (abs(Alt$(Lepton_pdgId[3],-9999))==13 && abs(Alt$(Lepton_eta[3],-9999.)) <2.4))'
}
aliases['jetpt30']={
'expr': 'Alt$(CleanJet_pt[0],-9999.) >30 && Alt$(CleanJet_pt[1],-9999.) >30'
}
aliases['jetpt50']={
'expr': 'Alt$(CleanJet_pt[0],-9999.) >50 && Alt$(CleanJet_pt[1],-9999.) >50'
}
aliases['leppt0']={
'expr': 'Alt$(Lepton_pt[0],-9999.) >25 && Alt$(Lepton_pt[1],-9999.) >20'
}
aliases['leppt30']={
'expr': 'Alt$(Lepton_pt[0],-9999.) >30 && Alt$(Lepton_pt[1],-9999.) >30'
}
aliases['leppt25_wz']={
'expr': 'Alt$(Lepton_pt[0],-9999.) >25 && Alt$(Lepton_pt[1],-9999.) >25 && Alt$(Lepton_pt[2],-9999.) >10 && Alt$(Lepton_pt[3],-9999.) <10'#Alt$(Lepton_pt[2],-9999.) >10'
}
aliases['leppt30_wz']={
'expr': 'Alt$(Lepton_pt[0],-9999.) >30 && Alt$(Lepton_pt[1],-9999.) >30 && Alt$(Lepton_pt[2],-9999.) >10 && Alt$(Lepton_pt[3],-9999.) <10'#Alt$(Lepton_pt[2],-9999.) >10'
}
aliases['jet_cuts']={
'expr': 'nCleanJet >1 && abs(detajj) > 2.5 && abs(Alt$(CleanJet_eta[0],-9999.)) < 4.7&& abs(Alt$(CleanJet_eta[1],-9999.)) < 4.7'
}
aliases['EEE']={
'expr': 'abs(Alt$(Lepton_pdgId[0],0)*Alt$(Lepton_pdgId[1],0)*Alt$(Lepton_pdgId[2],0))==11*11*11'
}
aliases['MEE']={
'expr': 'abs(Alt$(Lepton_pdgId[0],0)*Alt$(Lepton_pdgId[1],0)*Alt$(Lepton_pdgId[2],0))==13*11*11'
}
aliases['MME']={
'expr': 'abs(Alt$(Lepton_pdgId[0],0)*Alt$(Lepton_pdgId[1],0)*Alt$(Lepton_pdgId[2],0))==13*13*11'
}
aliases['MMM']={
'expr': 'abs(Alt$(Lepton_pdgId[0],0)*Alt$(Lepton_pdgId[1],0)*Alt$(Lepton_pdgId[2],0))==13*13*13'
}
# wz region
aliases['ztag_wz']={
'expr': '((Alt$(Lepton_pdgId[0],-9999) + Alt$(Lepton_pdgId[1],-9999)==0 && abs(mll-91.1876)<15)||(Alt$(Lepton_pdgId[0],-9999) + Alt$(Lepton_pdgId[2],-9999)==0 && abs(mllOneThree-91.1876)<15)||(Alt$(Lepton_pdgId[1],-9999) + Alt$(Lepton_pdgId[2],-9999)==0 && abs(mllTwoThree-91.1876)<15))' # bjet pt zlep
}
aliases['mll_cut_wz']={
'expr': '((Alt$(Lepton_pdgId[0],-9999)*Alt$(Lepton_pdgId[1],-9999)>0 || mll>4)&&(Alt$(Lepton_pdgId[0],-9999)*Alt$(Lepton_pdgId[2],-9999)>0 || mllOneThree>4)&&(Alt$(Lepton_pdgId[1],-9999)*Alt$(Lepton_pdgId[2],-9999)>0|| mllTwoThree>4))' # bjet pt zlep
}
aliases['pid_wz']={
'expr': 'abs(Alt$(Lepton_pdgId[0],-9999) + Alt$(Lepton_pdgId[1],-9999)+Alt$(Lepton_pdgId[2],-9999)) < 33'
}
aliases['zlep_wz']={
'expr': 'abs((Alt$(Lepton_eta[0],-9999.) - (Alt$(CleanJet_eta[0],-9999.)+Alt$(CleanJet_eta[1],-9999.))/2)/detajj) < 0.75 && abs((Alt$(Lepton_eta[1],-9999.) - (Alt$(CleanJet_eta[0],-9999.)+Alt$(CleanJet_eta[1],-9999.))/2)/detajj) < 0.75'# && abs((Alt$(Lepton_eta[2],-9999.) - (Alt$(CleanJet_eta[0],-9999.)+Alt$(CleanJet_eta[1],-9999.))/2)/detajj) <0.5'
}
aliases['wz_region']={
'expr': 'nLepton>2 && MET_pt>30 && lep0eta && lep1eta && lep2eta && ztag_wz && softmuon_veto' # bjet pt
}
# B tag scale factors
btagSFSource = '%s/src/PhysicsTools/NanoAODTools/data/btagSF/DeepCSV_2016LegacySF_V1.csv' % os.getenv('CMSSW_BASE')
aliases['Jet_btagSF_shapeFix'] = {
'linesToAdd': [
'gSystem->Load("libCondFormatsBTauObjects.so");',
'gSystem->Load("libCondToolsBTau.so");',
'gSystem->AddIncludePath("-I%s/src");' % os.getenv('CMSSW_RELEASE_BASE'),
'.L %s/patches/btagsfpatch.cc+' % configurations
],
'class': 'BtagSF',
'args': (btagSFSource,),
'samples': mc
}
aliases['bVetoSF'] = {
#'expr': 'TMath::Exp(Sum$(TMath::Log((CleanJet_pt>20 && abs(CleanJet_eta)<2.5)*Jet_btagSF_shape[CleanJet_jetIdx]+1*(CleanJet_pt<20 || abs(CleanJet_eta)>2.5))))',
'expr': 'TMath::Exp(Sum$(TMath::Log((CleanJet_pt>20 && abs(CleanJet_eta)<2.5)*Jet_btagSF_shapeFix[CleanJet_jetIdx]+1*(CleanJet_pt<20 || abs(CleanJet_eta)>2.5))))',
'samples': mc
}
aliases['btag0SF'] = {
#'expr': 'TMath::Exp(Sum$(TMath::Log((CleanJet_pt>20 && CleanJet_pt<30 && abs(CleanJet_eta)<2.5)*Jet_btagSF_shape[CleanJet_jetIdx]+1*(CleanJet_pt<20 || CleanJet_pt>30 || abs(CleanJet_eta)>2.5))))',
'expr': 'TMath::Exp(Sum$(TMath::Log((CleanJet_pt>20 && CleanJet_pt<30 && abs(CleanJet_eta)<2.5)*Jet_btagSF_shapeFix[CleanJet_jetIdx]+1*(CleanJet_pt<20 || CleanJet_pt>30 || abs(CleanJet_eta)>2.5))))',
'samples': mc
}
aliases['btagnSF'] = {
#'expr': 'TMath::Exp(Sum$(TMath::Log((CleanJet_pt>30 && abs(CleanJet_eta)<2.5)*Jet_btagSF_shape[CleanJet_jetIdx] + (CleanJet_pt<30 || abs(CleanJet_eta)>2.5))))',
'expr': 'TMath::Exp(Sum$(TMath::Log((CleanJet_pt>30 && abs(CleanJet_eta)<2.5)*Jet_btagSF_shapeFix[CleanJet_jetIdx] + (CleanJet_pt<30 || abs(CleanJet_eta)>2.5))))',
'samples': mc
}
aliases['btagSF'] = {
'expr': 'bVetoSF*bVeto + btag0SF*btag0 + btagnSF*(btag1 + btag2) + (!bVeto && !btag0 && !btag1 && !btag2)',
'samples': mc
}
for shift in ['jes','lf','hf','lfstats1','lfstats2','hfstats1','hfstats2','cferr1','cferr2']:
aliases['Jet_btagSF_shapeFix_up_%s' % shift] = {
'class': 'BtagSF',
'args': (btagSFSource, 'up_' + shift),
'samples': mc
}
aliases['Jet_btagSF_shapeFix_down_%s' % shift] = {
'class': 'BtagSF',
'args': (btagSFSource, 'down_' + shift),
'samples': mc
}
for targ in ['bVeto', 'btag0', 'btagn']:
alias = aliases['%sSF%sup' % (targ, shift)] = copy.deepcopy(aliases['%sSF' % targ])
#alias['expr'] = alias['expr'].replace('btagSF_shape', 'btagSF_shape_up_%s' % shift)
alias['expr'] = alias['expr'].replace('btagSF_shapeFix', 'btagSF_shapeFix_up_%s' % shift)
alias = aliases['%sSF%sdown' % (targ, shift)] = copy.deepcopy(aliases['%sSF' % targ])
#alias['expr'] = alias['expr'].replace('btagSF_shape', 'btagSF_shape_down_%s' % shift)
alias['expr'] = alias['expr'].replace('btagSF_shapeFix', 'btagSF_shapeFix_down_%s' % shift)
aliases['btagSF%sup' % shift] = {
'expr': 'bVetoSF{shift}up*bVeto + btag0SF{shift}up*btag0 + btagnSF{shift}up*(btag1 + btag2) + (!bVeto && !btag0 && !btag1 && !btag2)'.format(shift = shift),
'samples': mc
}
aliases['btagSF%sdown' % shift] = {
'expr': 'bVetoSF{shift}down*bVeto + btag0SF{shift}down*btag0 + btagnSF{shift}down*(btag1 + btag2) + (!bVeto && !btag0 && !btag1 && !btag2)'.format(shift = shift),
'samples': mc
}
# data/MC scale factors
aliases['SFweight'] = {
#'expr': ' * '.join(['SFweight2l', 'LepSF2l__ele_' + eleWP + '__mu_' + muWP, 'LepWPCut', 'btagSF', 'PrefireWeight']),
'expr': ' * '.join(['SFweight3l','LepSF3l__ele_' + eleWP + '__mu_' + muWP, 'LepWPCut','PrefireWeight','XSWeight','METFilter_MC','btagSF']),
#'expr': ' * '.join(['LepWPCut','XSWeight']),
'samples': mc
}
# variations
aliases['SFweightEleUp'] = {
'expr': 'LepSF3l__ele_'+eleWP+'__Up',
'samples': mc
}
aliases['SFweightEleDown'] = {
'expr': 'LepSF3l__ele_'+eleWP+'__Do',
'samples': mc
}
aliases['SFweightMuUp'] = {
'expr': 'LepSF3l__mu_'+muWP+'__Up',
'samples': mc
}
aliases['SFweightMuDown'] = {
'expr': 'LepSF3l__mu_'+muWP+'__Do',
'samples': mc
}
| [
"[email protected]"
] | |
ed02706c8203b78c812b8159c71208e1e7196960 | 597b888dca4e9add7acdf449f8c3d8d716826ff2 | /gui/demos/listbox.py | 105c3d631bc9eb579543eeadf5002fcfc4aee71b | [
"MIT"
] | permissive | alsor62/micropython-micro-gui | a7cad669d69358599feb84011c23ac5d767adfda | 5c7d6c96b30e4936a2a4315b09e98a730f14c6db | refs/heads/main | 2023-09-04T09:54:10.946964 | 2021-11-09T11:46:59 | 2021-11-09T11:46:59 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,401 | py | # listbox.py micro-gui demo of Listbox class
# Released under the MIT License (MIT). See LICENSE.
# Copyright (c) 2021 Peter Hinch
# hardware_setup must be imported before other modules because of RAM use.
from hardware_setup import ssd # Create a display instance
from gui.core.ugui import Screen
from gui.core.writer import CWriter
from gui.core.colors import *
from gui.widgets.listbox import Listbox
from gui.widgets.buttons import CloseButton
import gui.fonts.freesans20 as font
class BaseScreen(Screen):
def __init__(self):
def cb(lb, s):
print('Gas', s)
def cb_radon(lb, s): # Yeah, Radon is a gas too...
print('Radioactive', s)
super().__init__()
wri = CWriter(ssd, font, GREEN, BLACK, verbose=False)
els = (('Hydrogen', cb, ('H',)),
('Helium', cb, ('He',)),
('Neon', cb, ('Ne',)),
('Xenon', cb, ('Xe',)),
('Radon', cb_radon, ('Ra',)),
('Uranium', cb_radon, ('U',)),
('Plutonium', cb_radon, ('Pu',)),
('Actinium', cb_radon, ('Ac',)),
)
Listbox(wri, 2, 2,
elements = els, dlines=5, bdcolor=RED, value=1, also=Listbox.ON_LEAVE)
#bdcolor = RED, fgcolor=RED, fontcolor = YELLOW, select_color=BLUE, value=1)
CloseButton(wri)
Screen.change(BaseScreen)
| [
"[email protected]"
] | |
0d0ffda577ccb37780d4868464ca1a94879b1103 | 0a0e622f955b548e23bf5f974c58b5a6dde714d1 | /tensorflow_estimator/python/estimator/canned/linear.py | 3ebd5d8cb98f65d917286769627a53af1050eae3 | [
"Apache-2.0"
] | permissive | brettkoonce/estimator | 7a4172542d9ec67359147c07df252632ea1c2a4e | ba2f4a069bc0ee4a96f87f4d1c1688fb9121e297 | refs/heads/master | 2020-04-09T05:18:47.974913 | 2018-12-02T00:16:26 | 2018-12-02T00:16:46 | 160,059,700 | 0 | 0 | null | 2018-12-02T15:11:38 | 2018-12-02T15:11:38 | null | UTF-8 | Python | false | false | 48,684 | py | # Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Linear Estimators."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import math
import six
from tensorflow.python.feature_column import feature_column
from tensorflow.python.feature_column import feature_column_lib
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import nn
from tensorflow.python.ops import partitioned_variables
from tensorflow.python.ops import resource_variable_ops
from tensorflow.python.ops import variable_scope
from tensorflow.python.ops import variables as variable_ops
from tensorflow.python.ops.losses import losses
from tensorflow.python.summary import summary
from tensorflow.python.training import ftrl
from tensorflow.python.training import session_run_hook
from tensorflow.python.training import training
from tensorflow.python.util import nest
from tensorflow.python.util.tf_export import estimator_export
from tensorflow_estimator.python.estimator import estimator
from tensorflow_estimator.python.estimator import model_fn
from tensorflow_estimator.python.estimator.canned import head as head_lib
from tensorflow_estimator.python.estimator.canned import optimizers
from tensorflow_estimator.python.estimator.canned.linear_optimizer.python.utils import sdca_ops
from tensorflow_estimator.python.estimator.head import regression_head
# The default learning rate of 0.2 is a historical artifact of the initial
# implementation, but seems a reasonable choice.
_LEARNING_RATE = 0.2
@estimator_export('estimator.experimental.LinearSDCA')
class LinearSDCA(object):
"""Stochastic Dual Coordinate Ascent helper for linear estimators.
Objects of this class are intended to be provided as the optimizer argument
(though LinearSDCA objects do not implement the tf.train.Optimizer interface)
when creating tf.estimator.LinearClassifier or tf.estimator.LinearRegressor.
SDCA can only be used with LinearClassifier and LinearRegressor under the
following conditions:
- Feature columns are of type V2.
- Multivalent categorical columns are not normalized. In other words the
`sparse_combiner` argument in the estimator constructor should be "sum".
- For classification: binary label.
- For regression: one-dimensional label.
Example usage:
```python
real_feature_column = numeric_column(...)
sparse_feature_column = categorical_column_with_hash_bucket(...)
linear_sdca = tf.estimator.experimental.LinearSDCA(
example_id_column='example_id',
num_loss_partitions=1,
num_table_shards=1,
symmetric_l2_regularization=2.0)
classifier = tf.estimator.LinearClassifier(
feature_columns=[real_feature_column, sparse_feature_column],
weight_column=...,
optimizer=linear_sdca)
classifier.train(input_fn_train, steps=50)
classifier.evaluate(input_fn=input_fn_eval)
```
Here the expectation is that the `input_fn_*` functions passed to train and
evaluate return a pair (dict, label_tensor) where dict has `example_id_column`
as `key` whose value is a `Tensor` of shape [batch_size] and dtype string.
num_loss_partitions defines sigma' in eq (11) of [3]. Convergence of (global)
loss is guaranteed if `num_loss_partitions` is larger or equal to the product
`(#concurrent train ops/per worker) x (#workers)`. Larger values for
`num_loss_partitions` lead to slower convergence. The recommended value for
`num_loss_partitions` in `tf.estimator` (where currently there is one process
per worker) is the number of workers running the train steps. It defaults to 1
(single machine).
`num_table_shards` defines the number of shards for the internal state
table, typically set to match the number of parameter servers for large
data sets.
The SDCA algorithm was originally introduced in [1] and it was followed by
the L1 proximal step [2], a distributed version [3] and adaptive sampling [4].
[1] www.jmlr.org/papers/volume14/shalev-shwartz13a/shalev-shwartz13a.pdf
[2] https://arxiv.org/pdf/1309.2375.pdf
[3] https://arxiv.org/pdf/1502.03508.pdf
[4] https://arxiv.org/pdf/1502.08053.pdf
Details specific to this implementation are provided in:
https://github.com/tensorflow/estimator/tree/master/tensorflow_estimator/python/estimator/canned/linear_optimizer/doc/sdca.ipynb
"""
def __init__(self,
example_id_column,
num_loss_partitions=1,
num_table_shards=None,
symmetric_l1_regularization=0.0,
symmetric_l2_regularization=1.0,
adaptive=False):
"""Construct a new SDCA optimizer for linear estimators.
Args:
example_id_column: The column name contraining the example ids.
num_loss_partitions: Number of workers.
num_table_shards: Number of shards of the internal state table, typically
set to match the number of parameter servers.
symmetric_l1_regularization: A float value, must be greater than or
equal to zero.
symmetric_l2_regularization: A float value, must be greater than zero and
should typically be greater than 1.
adaptive: A boolean indicating whether to use adaptive sampling.
"""
self._example_id_column = example_id_column
self._num_loss_partitions = num_loss_partitions
self._num_table_shards = num_table_shards
self._symmetric_l1_regularization = symmetric_l1_regularization
self._symmetric_l2_regularization = symmetric_l2_regularization
self._adaptive = adaptive
def _prune_and_unique_sparse_ids(self, id_weight_pair):
"""Remove duplicate and negative ids in a sparse tendor."""
id_tensor = id_weight_pair.id_tensor
if id_weight_pair.weight_tensor:
weight_tensor = id_weight_pair.weight_tensor.values
else:
weight_tensor = array_ops.ones(
[array_ops.shape(id_tensor.indices)[0]], dtypes.float32)
example_ids = array_ops.reshape(id_tensor.indices[:, 0], [-1])
flat_ids = math_ops.to_int64(array_ops.reshape(id_tensor.values, [-1]))
# Prune invalid IDs (< 0) from the flat_ids, example_ids, and
# weight_tensor. These can come from looking up an OOV entry in the
# vocabulary (default value being -1).
is_id_valid = math_ops.greater_equal(flat_ids, 0)
flat_ids = array_ops.boolean_mask(flat_ids, is_id_valid)
example_ids = array_ops.boolean_mask(example_ids, is_id_valid)
weight_tensor = array_ops.boolean_mask(weight_tensor, is_id_valid)
projection_length = math_ops.reduce_max(flat_ids) + 1
# project ids based on example ids so that we can dedup ids that
# occur multiple times for a single example.
projected_ids = projection_length * example_ids + flat_ids
# Remove any redundant ids.
ids, idx = array_ops.unique(projected_ids)
# Keep only one example id per duplicated ids.
example_ids_filtered = math_ops.unsorted_segment_min(
example_ids, idx,
array_ops.shape(ids)[0])
# reproject ids back feature id space.
reproject_ids = (ids - projection_length * example_ids_filtered)
weights = array_ops.reshape(
math_ops.unsorted_segment_sum(weight_tensor, idx,
array_ops.shape(ids)[0]), [-1])
return sdca_ops._SparseFeatureColumn( # pylint: disable=protected-access
example_ids_filtered, reproject_ids, weights)
def get_train_step(self, state_manager, weight_column_name, loss_type,
feature_columns, features, targets, bias_var, global_step):
"""Returns the training operation of an SdcaModel optimizer."""
batch_size = array_ops.shape(targets)[0]
cache = feature_column_lib.FeatureTransformationCache(features)
# Iterate over all feature columns and create appropriate lists for dense
# and sparse features as well as dense and sparse weights (variables) for
# SDCA.
dense_features, dense_feature_weights = [], []
sparse_feature_with_values, sparse_feature_with_values_weights = [], []
for column in sorted(feature_columns, key=lambda x: x.name):
if isinstance(column, feature_column_lib.CategoricalColumn):
id_weight_pair = column.get_sparse_tensors(cache, state_manager)
sparse_feature_with_values.append(
self._prune_and_unique_sparse_ids(id_weight_pair))
# If a partitioner was used during variable creation, we will have a
# list of Variables here larger than 1.
sparse_feature_with_values_weights.append(
state_manager.get_variable(column, 'weights'))
elif isinstance(column, feature_column_lib.DenseColumn):
if column.variable_shape.ndims != 1:
raise ValueError('Column %s has rank %d, larger than 1.' % (
type(column).__name__, column.variable_shape.ndims))
dense_features.append(column.get_dense_tensor(cache, state_manager))
# For real valued columns, the variables list contains exactly one
# element.
dense_feature_weights.append(
state_manager.get_variable(column, 'weights'))
else:
raise ValueError('LinearSDCA does not support column type %s.' %
type(column).__name__)
# Add the bias column
dense_features.append(array_ops.ones([batch_size, 1]))
dense_feature_weights.append(bias_var)
example_weights = array_ops.reshape(
features[weight_column_name],
shape=[-1]) if weight_column_name else array_ops.ones([batch_size])
example_ids = features[self._example_id_column]
training_examples = dict(
sparse_features=sparse_feature_with_values,
dense_features=dense_features,
example_labels=math_ops.to_float(
array_ops.reshape(targets, shape=[-1])),
example_weights=example_weights,
example_ids=example_ids)
training_variables = dict(
sparse_features_weights=sparse_feature_with_values_weights,
dense_features_weights=dense_feature_weights)
sdca_model = sdca_ops._SDCAModel( # pylint: disable=protected-access
examples=training_examples,
variables=training_variables,
options=dict(
symmetric_l1_regularization=self._symmetric_l1_regularization,
symmetric_l2_regularization=self._symmetric_l2_regularization,
adaptive=self._adaptive,
num_loss_partitions=self._num_loss_partitions,
num_table_shards=self._num_table_shards,
loss_type=loss_type))
train_op = sdca_model.minimize(global_step=global_step)
return sdca_model, train_op
def _get_default_optimizer(feature_columns):
learning_rate = min(_LEARNING_RATE, 1.0 / math.sqrt(len(feature_columns)))
return ftrl.FtrlOptimizer(learning_rate=learning_rate)
def _get_expanded_variable_list(var_list):
"""Given an iterable of variables, expands them if they are partitioned.
Args:
var_list: An iterable of variables.
Returns:
A list of variables where each partitioned variable is expanded to its
components.
"""
returned_list = []
for variable in var_list:
if (isinstance(variable, variable_ops.Variable) or
resource_variable_ops.is_resource_variable(variable)):
returned_list.append(variable) # Single variable case.
else: # Must be a PartitionedVariable, so convert into a list.
returned_list.extend(list(variable))
return returned_list
# TODO(rohanj): Consider making this a public utility method.
def _compute_fraction_of_zero(variables):
"""Given a linear variables list, compute the fraction of zero weights.
Args:
variables: A list or list of list of variables
Returns:
The fraction of zeros (sparsity) in the linear model.
"""
with ops.name_scope('zero_fraction'):
variables = nest.flatten(variables)
with ops.name_scope('total_size'):
sizes = [array_ops.size(x, out_type=dtypes.int64) for x in variables]
total_size_int64 = math_ops.add_n(sizes)
with ops.name_scope('total_zero'):
total_zero_float32 = math_ops.add_n([
control_flow_ops.cond(
math_ops.equal(size, constant_op.constant(0, dtype=dtypes.int64)),
true_fn=lambda: constant_op.constant(0, dtype=dtypes.float32),
false_fn=lambda: nn.zero_fraction(x) * math_ops.to_float(size),
name='zero_count')
for x, size in zip(variables, sizes)
])
with ops.name_scope('compute'):
total_size_float32 = math_ops.cast(
total_size_int64, dtype=dtypes.float32, name='float32_size')
zero_fraction_or_nan = total_zero_float32 / total_size_float32
zero_fraction_or_nan = array_ops.identity(
zero_fraction_or_nan, name='zero_fraction_or_nan')
return zero_fraction_or_nan
@estimator_export('estimator.experimental.linear_logit_fn_builder')
def linear_logit_fn_builder(units, feature_columns, sparse_combiner='sum'):
"""Function builder for a linear logit_fn.
Args:
units: An int indicating the dimension of the logit layer.
feature_columns: An iterable containing all the feature columns used by
the model.
sparse_combiner: A string specifying how to reduce if a categorical column
is multivalent. One of "mean", "sqrtn", and "sum".
Returns:
A logit_fn (see below).
"""
def linear_logit_fn(features):
"""Linear model logit_fn.
Args:
features: This is the first item returned from the `input_fn`
passed to `train`, `evaluate`, and `predict`. This should be a
single `Tensor` or `dict` of same.
Returns:
A `Tensor` representing the logits.
"""
if feature_column_lib.is_feature_column_v2(feature_columns):
linear_model = feature_column_lib.LinearModel(
feature_columns=feature_columns,
units=units,
sparse_combiner=sparse_combiner,
name='linear_model')
logits = linear_model(features)
bias = linear_model.bias
# We'd like to get all the non-bias variables associated with this
# LinearModel.
# TODO(rohanj): Figure out how to get shared embedding weights variable
# here.
variables = linear_model.variables
variables.remove(bias)
# Expand (potential) Partitioned variables
bias = _get_expanded_variable_list([bias])
else:
linear_model = feature_column._LinearModel( # pylint: disable=protected-access
feature_columns=feature_columns,
units=units,
sparse_combiner=sparse_combiner,
name='linear_model')
logits = linear_model(features)
cols_to_vars = linear_model.cols_to_vars()
bias = cols_to_vars.pop('bias')
variables = cols_to_vars.values()
variables = _get_expanded_variable_list(variables)
if units > 1:
summary.histogram('bias', bias)
else:
# If units == 1, the bias value is a length-1 list of a scalar Tensor,
# so we should provide a scalar summary.
summary.scalar('bias', bias[0][0])
summary.scalar('fraction_of_zero_weights',
_compute_fraction_of_zero(variables))
return logits
return linear_logit_fn
def _sdca_model_fn(features, labels, mode, head, feature_columns, optimizer):
"""A model_fn for linear models that use the SDCA optimizer.
Args:
features: dict of `Tensor`.
labels: `Tensor` of shape `[batch_size]`.
mode: Defines whether this is training, evaluation or prediction.
See `ModeKeys`.
head: A `Head` instance.
feature_columns: An iterable containing all the feature columns used by
the model.
optimizer: a `LinearSDCA` instance.
Returns:
An `EstimatorSpec` instance.
Raises:
ValueError: mode or params are invalid, or features has the wrong type.
"""
assert feature_column_lib.is_feature_column_v2(feature_columns)
if isinstance(head, head_lib._BinaryLogisticHeadWithSigmoidCrossEntropyLoss): # pylint: disable=protected-access
loss_type = 'logistic_loss'
elif isinstance(head, regression_head.RegressionHead): # pylint: disable=protected-access
assert head.logits_dimension == 1
loss_type = 'squared_loss'
else:
raise ValueError('Unsupported head type: {}'.format(head))
linear_model = feature_column_lib.LinearModel(
feature_columns=feature_columns, units=1, sparse_combiner='sum')
logits = linear_model(features)
bias = linear_model.bias
# We'd like to get all the non-bias variables associated with this
# LinearModel.
# TODO(rohanj): Figure out how to get shared embedding weights variable
# here.
variables = linear_model.variables
variables.remove(bias)
# Expand (potential) Partitioned variables
bias = _get_expanded_variable_list([bias])
variables = _get_expanded_variable_list(variables)
summary.scalar('bias', bias[0][0])
summary.scalar('fraction_of_zero_weights',
_compute_fraction_of_zero(variables))
if mode == model_fn.ModeKeys.TRAIN:
sdca_model, train_op = optimizer.get_train_step(
linear_model.layer._state_manager, # pylint: disable=protected-access
head._weight_column, # pylint: disable=protected-access
loss_type,
feature_columns,
features,
labels,
linear_model.bias,
training.get_global_step())
update_weights_hook = _SDCAUpdateWeightsHook(sdca_model, train_op)
model_fn_ops = head.create_estimator_spec(
features=features,
mode=mode,
labels=labels,
train_op_fn=lambda unused_loss_fn: train_op,
logits=logits)
return model_fn_ops._replace(training_chief_hooks=(
model_fn_ops.training_chief_hooks + (update_weights_hook,)))
else:
return head.create_estimator_spec(
features=features,
mode=mode,
labels=labels,
logits=logits)
class _SDCAUpdateWeightsHook(session_run_hook.SessionRunHook):
"""SessionRunHook to update and shrink SDCA model weights."""
def __init__(self, sdca_model, train_op):
self._sdca_model = sdca_model
self._train_op = train_op
def begin(self):
"""Construct the update_weights op.
The op is implicitly added to the default graph.
"""
self._update_op = self._sdca_model.update_weights(self._train_op)
def before_run(self, run_context):
"""Return the update_weights op so that it is executed during this run."""
return session_run_hook.SessionRunArgs(self._update_op)
def _linear_model_fn(features, labels, mode, head, feature_columns, optimizer,
partitioner, config, sparse_combiner='sum'):
"""A model_fn for linear models that use a gradient-based optimizer.
Args:
features: dict of `Tensor`.
labels: `Tensor` of shape `[batch_size, logits_dimension]`.
mode: Defines whether this is training, evaluation or prediction.
See `ModeKeys`.
head: A `Head` instance.
feature_columns: An iterable containing all the feature columns used by
the model.
optimizer: string, `Optimizer` object, or callable that defines the
optimizer to use for training. If `None`, will use a FTRL optimizer.
partitioner: Partitioner for variables.
config: `RunConfig` object to configure the runtime settings.
sparse_combiner: A string specifying how to reduce if a categorical column
is multivalent. One of "mean", "sqrtn", and "sum".
Returns:
An `EstimatorSpec` instance.
Raises:
ValueError: mode or params are invalid, or features has the wrong type.
"""
if not isinstance(features, dict):
raise ValueError('features should be a dictionary of `Tensor`s. '
'Given type: {}'.format(type(features)))
num_ps_replicas = config.num_ps_replicas if config else 0
partitioner = partitioner or (
partitioned_variables.min_max_variable_partitioner(
max_partitions=num_ps_replicas,
min_slice_size=64 << 20))
with variable_scope.variable_scope(
'linear',
values=tuple(six.itervalues(features)),
partitioner=partitioner):
if isinstance(optimizer, LinearSDCA):
assert sparse_combiner == 'sum'
return _sdca_model_fn(
features, labels, mode, head, feature_columns, optimizer)
else:
logit_fn = linear_logit_fn_builder(
units=head.logits_dimension, feature_columns=feature_columns,
sparse_combiner=sparse_combiner,
)
logits = logit_fn(features=features)
optimizer = optimizers.get_optimizer_instance(
optimizer or _get_default_optimizer(feature_columns),
learning_rate=_LEARNING_RATE)
return head.create_estimator_spec(
features=features,
mode=mode,
labels=labels,
optimizer=optimizer,
logits=logits)
def _init_linear_classifier(
feature_columns,
n_classes,
weight_column,
label_vocabulary,
optimizer,
partitioner,
loss_reduction,
sparse_combiner):
"""Helper function for the initialization of LinearClassifier."""
if isinstance(optimizer, LinearSDCA):
if sparse_combiner != 'sum':
raise ValueError('sparse_combiner must be "sum" when optimizer '
'is a LinearSDCA object.')
if not feature_column_lib.is_feature_column_v2(feature_columns):
raise ValueError('V2 feature columns required when optimizer '
'is a LinearSDCA object.')
if n_classes > 2:
raise ValueError('LinearSDCA cannot be used in a multi-class setting.')
if n_classes == 2:
head = head_lib._binary_logistic_head_with_sigmoid_cross_entropy_loss( # pylint: disable=protected-access
weight_column=weight_column,
label_vocabulary=label_vocabulary,
loss_reduction=loss_reduction)
else:
head = head_lib._multi_class_head_with_softmax_cross_entropy_loss( # pylint: disable=protected-access
n_classes, weight_column=weight_column,
label_vocabulary=label_vocabulary,
loss_reduction=loss_reduction)
def _model_fn(features, labels, mode, config):
"""Call the defined shared _linear_model_fn."""
return _linear_model_fn(
features=features,
labels=labels,
mode=mode,
head=head,
feature_columns=tuple(feature_columns or []),
optimizer=optimizer,
partitioner=partitioner,
config=config,
sparse_combiner=sparse_combiner)
return _model_fn
@estimator_export('estimator.LinearClassifier', v1=[])
class LinearClassifierV2(estimator.EstimatorV2):
"""Linear classifier model.
Train a linear model to classify instances into one of multiple possible
classes. When number of possible classes is 2, this is binary classification.
Example:
```python
categorical_column_a = categorical_column_with_hash_bucket(...)
categorical_column_b = categorical_column_with_hash_bucket(...)
categorical_feature_a_x_categorical_feature_b = crossed_column(...)
# Estimator using the default optimizer.
estimator = LinearClassifier(
feature_columns=[categorical_column_a,
categorical_feature_a_x_categorical_feature_b])
# Or estimator using the FTRL optimizer with regularization.
estimator = LinearClassifier(
feature_columns=[categorical_column_a,
categorical_feature_a_x_categorical_feature_b],
optimizer=tf.train.FtrlOptimizer(
learning_rate=0.1,
l1_regularization_strength=0.001
))
# Or estimator using an optimizer with a learning rate decay.
estimator = LinearClassifier(
feature_columns=[categorical_column_a,
categorical_feature_a_x_categorical_feature_b],
optimizer=lambda: tf.train.FtrlOptimizer(
learning_rate=tf.exponential_decay(
learning_rate=0.1,
global_step=tf.get_global_step(),
decay_steps=10000,
decay_rate=0.96))
# Or estimator with warm-starting from a previous checkpoint.
estimator = LinearClassifier(
feature_columns=[categorical_column_a,
categorical_feature_a_x_categorical_feature_b],
warm_start_from="/path/to/checkpoint/dir")
# Input builders
def input_fn_train:
# Returns tf.data.Dataset of (x, y) tuple where y represents label's class
# index.
pass
def input_fn_eval:
# Returns tf.data.Dataset of (x, y) tuple where y represents label's class
# index.
pass
def input_fn_predict:
# Returns tf.data.Dataset of (x, None) tuple.
pass
estimator.train(input_fn=input_fn_train)
metrics = estimator.evaluate(input_fn=input_fn_eval)
predictions = estimator.predict(input_fn=input_fn_predict)
```
Input of `train` and `evaluate` should have following features,
otherwise there will be a `KeyError`:
* if `weight_column` is not `None`, a feature with `key=weight_column` whose
value is a `Tensor`.
* for each `column` in `feature_columns`:
- if `column` is a `SparseColumn`, a feature with `key=column.name`
whose `value` is a `SparseTensor`.
- if `column` is a `WeightedSparseColumn`, two features: the first with
`key` the id column name, the second with `key` the weight column name.
Both features' `value` must be a `SparseTensor`.
- if `column` is a `RealValuedColumn`, a feature with `key=column.name`
whose `value` is a `Tensor`.
Loss is calculated by using softmax cross entropy.
@compatibility(eager)
Estimators can be used while eager execution is enabled. Note that `input_fn`
and all hooks are executed inside a graph context, so they have to be written
to be compatible with graph mode. Note that `input_fn` code using `tf.data`
generally works in both graph and eager modes.
@end_compatibility
"""
def __init__(self,
feature_columns,
model_dir=None,
n_classes=2,
weight_column=None,
label_vocabulary=None,
optimizer='Ftrl',
config=None,
partitioner=None,
warm_start_from=None,
loss_reduction=losses.Reduction.SUM_OVER_BATCH_SIZE,
sparse_combiner='sum'):
"""Construct a `LinearClassifier` estimator object.
Args:
feature_columns: An iterable containing all the feature columns used by
the model. All items in the set should be instances of classes derived
from `FeatureColumn`.
model_dir: Directory to save model parameters, graph and etc. This can
also be used to load checkpoints from the directory into a estimator
to continue training a previously saved model.
n_classes: number of label classes. Default is binary classification.
Note that class labels are integers representing the class index (i.e.
values from 0 to n_classes-1). For arbitrary label values (e.g. string
labels), convert to class indices first.
weight_column: A string or a `_NumericColumn` created by
`tf.feature_column.numeric_column` defining feature column representing
weights. It is used to down weight or boost examples during training. It
will be multiplied by the loss of the example. If it is a string, it is
used as a key to fetch weight tensor from the `features`. If it is a
`_NumericColumn`, raw tensor is fetched by key `weight_column.key`,
then weight_column.normalizer_fn is applied on it to get weight tensor.
label_vocabulary: A list of strings represents possible label values. If
given, labels must be string type and have any value in
`label_vocabulary`. If it is not given, that means labels are
already encoded as integer or float within [0, 1] for `n_classes=2` and
encoded as integer values in {0, 1,..., n_classes-1} for `n_classes`>2 .
Also there will be errors if vocabulary is not provided and labels are
string.
optimizer: An instance of `tf.Optimizer` or
`tf.estimator.experimental.LinearSDCA` used to train the model. Can
also be a string (one of 'Adagrad', 'Adam', 'Ftrl', 'RMSProp', 'SGD'),
or callable. Defaults to FTRL optimizer.
config: `RunConfig` object to configure the runtime settings.
partitioner: Optional. Partitioner for input layer.
warm_start_from: A string filepath to a checkpoint to warm-start from, or
a `WarmStartSettings` object to fully configure warm-starting. If the
string filepath is provided instead of a `WarmStartSettings`, then all
weights and biases are warm-started, and it is assumed that vocabularies
and Tensor names are unchanged.
loss_reduction: One of `tf.losses.Reduction` except `NONE`. Describes how
to reduce training loss over batch. Defaults to `SUM_OVER_BATCH_SIZE`.
sparse_combiner: A string specifying how to reduce if a categorical column
is multivalent. One of "mean", "sqrtn", and "sum" -- these are
effectively different ways to do example-level normalization, which can
be useful for bag-of-words features. for more details, see
`tf.feature_column.linear_model`.
Returns:
A `LinearClassifier` estimator.
Raises:
ValueError: if n_classes < 2.
"""
linear_classifier_model_fn = _init_linear_classifier(
feature_columns=feature_columns,
n_classes=n_classes,
weight_column=weight_column,
label_vocabulary=label_vocabulary,
optimizer=optimizer,
partitioner=partitioner,
loss_reduction=loss_reduction,
sparse_combiner=sparse_combiner)
super(LinearClassifierV2, self).__init__(
model_fn=linear_classifier_model_fn,
model_dir=model_dir,
config=config,
warm_start_from=warm_start_from)
@estimator_export(v1=['estimator.LinearClassifier']) # pylint: disable=missing-docstring
class LinearClassifier(estimator.Estimator):
__doc__ = LinearClassifierV2.__doc__.replace('SUM_OVER_BATCH_SIZE', 'SUM')
def __init__(self,
feature_columns,
model_dir=None,
n_classes=2,
weight_column=None,
label_vocabulary=None,
optimizer='Ftrl',
config=None,
partitioner=None,
warm_start_from=None,
loss_reduction=losses.Reduction.SUM,
sparse_combiner='sum'):
linear_classifier_model_fn = _init_linear_classifier(
feature_columns=feature_columns,
n_classes=n_classes,
weight_column=weight_column,
label_vocabulary=label_vocabulary,
optimizer=optimizer,
partitioner=partitioner,
loss_reduction=loss_reduction,
sparse_combiner=sparse_combiner)
super(LinearClassifier, self).__init__(
model_fn=linear_classifier_model_fn,
model_dir=model_dir,
config=config,
warm_start_from=warm_start_from)
# TODO(b/117517419): Update these contrib references once head moves to core.
# Also references to the "_Head" class need to be replaced with "Head".
@estimator_export('estimator.LinearEstimator', v1=[])
class LinearEstimatorV2(estimator.EstimatorV2):
"""An estimator for TensorFlow linear models with user-specified head.
Example:
```python
categorical_column_a = categorical_column_with_hash_bucket(...)
categorical_column_b = categorical_column_with_hash_bucket(...)
categorical_feature_a_x_categorical_feature_b = crossed_column(...)
# Estimator using the default optimizer.
estimator = LinearEstimator(
head=tf.contrib.estimator.multi_label_head(n_classes=3),
feature_columns=[categorical_column_a,
categorical_feature_a_x_categorical_feature_b])
# Or estimator using an optimizer with a learning rate decay.
estimator = LinearEstimator(
head=tf.contrib.estimator.multi_label_head(n_classes=3),
feature_columns=[categorical_column_a,
categorical_feature_a_x_categorical_feature_b],
optimizer=lambda: tf.train.FtrlOptimizer(
learning_rate=tf.exponential_decay(
learning_rate=0.1,
global_step=tf.get_global_step(),
decay_steps=10000,
decay_rate=0.96))
# Or estimator using the FTRL optimizer with regularization.
estimator = LinearEstimator(
head=tf.contrib.estimator.multi_label_head(n_classes=3),
feature_columns=[categorical_column_a,
categorical_feature_a_x_categorical_feature_b])
optimizer=tf.train.FtrlOptimizer(
learning_rate=0.1,
l1_regularization_strength=0.001
))
def input_fn_train:
# Returns tf.data.Dataset of (x, y) tuple where y represents label's class
# index.
pass
def input_fn_eval:
# Returns tf.data.Dataset of (x, y) tuple where y represents label's class
# index.
pass
def input_fn_predict:
# Returns tf.data.Dataset of (x, None) tuple.
pass
estimator.train(input_fn=input_fn_train, steps=100)
metrics = estimator.evaluate(input_fn=input_fn_eval, steps=10)
predictions = estimator.predict(input_fn=input_fn_predict)
```
Input of `train` and `evaluate` should have following features,
otherwise there will be a `KeyError`:
* if `weight_column` is not `None`, a feature with `key=weight_column` whose
value is a `Tensor`.
* for each `column` in `feature_columns`:
- if `column` is a `_CategoricalColumn`, a feature with `key=column.name`
whose `value` is a `SparseTensor`.
- if `column` is a `_WeightedCategoricalColumn`, two features: the first
with `key` the id column name, the second with `key` the weight column
name. Both features' `value` must be a `SparseTensor`.
- if `column` is a `_DenseColumn`, a feature with `key=column.name`
whose `value` is a `Tensor`.
Loss and predicted output are determined by the specified head.
@compatibility(eager)
Estimators can be used while eager execution is enabled. Note that `input_fn`
and all hooks are executed inside a graph context, so they have to be written
to be compatible with graph mode. Note that `input_fn` code using `tf.data`
generally works in both graph and eager modes.
@end_compatibility
"""
def __init__(self,
head,
feature_columns,
model_dir=None,
optimizer='Ftrl',
config=None,
partitioner=None,
sparse_combiner='sum'):
"""Initializes a `LinearEstimator` instance.
Args:
head: A `_Head` instance constructed with a method such as
`tf.contrib.estimator.multi_label_head`.
feature_columns: An iterable containing all the feature columns used by
the model. All items in the set should be instances of classes derived
from `FeatureColumn`.
model_dir: Directory to save model parameters, graph and etc. This can
also be used to load checkpoints from the directory into a estimator
to continue training a previously saved model.
optimizer: An instance of `tf.Optimizer` used to train the model. Can also
be a string (one of 'Adagrad', 'Adam', 'Ftrl', 'RMSProp', 'SGD'), or
callable. Defaults to FTRL optimizer.
config: `RunConfig` object to configure the runtime settings.
partitioner: Optional. Partitioner for input layer.
sparse_combiner: A string specifying how to reduce if a categorical column
is multivalent. One of "mean", "sqrtn", and "sum" -- these are
effectively different ways to do example-level normalization, which can
be useful for bag-of-words features. for more details, see
`tf.feature_column.linear_model`.
"""
def _model_fn(features, labels, mode, config):
return _linear_model_fn(
features=features,
labels=labels,
mode=mode,
head=head,
feature_columns=tuple(feature_columns or []),
optimizer=optimizer,
partitioner=partitioner,
config=config,
sparse_combiner=sparse_combiner)
super(LinearEstimatorV2, self).__init__(
model_fn=_model_fn, model_dir=model_dir, config=config)
@estimator_export(v1=['estimator.LinearEstimator']) # pylint: disable=missing-docstring
class LinearEstimator(estimator.Estimator):
__doc__ = LinearEstimatorV2.__doc__
def __init__(self,
head,
feature_columns,
model_dir=None,
optimizer='Ftrl',
config=None,
partitioner=None,
sparse_combiner='sum'):
"""Initializes a `LinearEstimator` instance.
Args:
head: A `_Head` instance constructed with a method such as
`tf.contrib.estimator.multi_label_head`.
feature_columns: An iterable containing all the feature columns used by
the model. All items in the set should be instances of classes derived
from `FeatureColumn`.
model_dir: Directory to save model parameters, graph and etc. This can
also be used to load checkpoints from the directory into a estimator
to continue training a previously saved model.
optimizer: An instance of `tf.Optimizer` used to train the model. Can also
be a string (one of 'Adagrad', 'Adam', 'Ftrl', 'RMSProp', 'SGD'), or
callable. Defaults to FTRL optimizer.
config: `RunConfig` object to configure the runtime settings.
partitioner: Optional. Partitioner for input layer.
sparse_combiner: A string specifying how to reduce if a categorical column
is multivalent. One of "mean", "sqrtn", and "sum" -- these are
effectively different ways to do example-level normalization, which can
be useful for bag-of-words features. for more details, see
`tf.feature_column.linear_model`.
"""
def _model_fn(features, labels, mode, config):
return _linear_model_fn(
features=features,
labels=labels,
mode=mode,
head=head,
feature_columns=tuple(feature_columns or []),
optimizer=optimizer,
partitioner=partitioner,
config=config,
sparse_combiner=sparse_combiner)
super(LinearEstimator, self).__init__(
model_fn=_model_fn, model_dir=model_dir, config=config)
def _validate_linear_sdca_optimizer(
feature_columns,
label_dimension,
optimizer,
sparse_combiner):
"""Helper function for the initialization of LinearRegressor."""
if isinstance(optimizer, LinearSDCA):
if sparse_combiner != 'sum':
raise ValueError('sparse_combiner must be "sum" when optimizer '
'is a LinearSDCA object.')
if not feature_column_lib.is_feature_column_v2(feature_columns):
raise ValueError('V2 feature columns required when optimizer '
'is a LinearSDCA object.')
if label_dimension > 1:
raise ValueError('LinearSDCA can only be used with one-dimensional '
'label.')
@estimator_export('estimator.LinearRegressor', v1=[])
class LinearRegressorV2(estimator.EstimatorV2):
"""An estimator for TensorFlow Linear regression problems.
Train a linear regression model to predict label value given observation of
feature values.
Example:
```python
categorical_column_a = categorical_column_with_hash_bucket(...)
categorical_column_b = categorical_column_with_hash_bucket(...)
categorical_feature_a_x_categorical_feature_b = crossed_column(...)
# Estimator using the default optimizer.
estimator = LinearRegressor(
feature_columns=[categorical_column_a,
categorical_feature_a_x_categorical_feature_b])
# Or estimator using the FTRL optimizer with regularization.
estimator = LinearRegressor(
feature_columns=[categorical_column_a,
categorical_feature_a_x_categorical_feature_b],
optimizer=tf.train.FtrlOptimizer(
learning_rate=0.1,
l1_regularization_strength=0.001
))
# Or estimator using an optimizer with a learning rate decay.
estimator = LinearRegressor(
feature_columns=[categorical_column_a,
categorical_feature_a_x_categorical_feature_b],
optimizer=lambda: tf.train.FtrlOptimizer(
learning_rate=tf.exponential_decay(
learning_rate=0.1,
global_step=tf.get_global_step(),
decay_steps=10000,
decay_rate=0.96))
# Or estimator with warm-starting from a previous checkpoint.
estimator = LinearRegressor(
feature_columns=[categorical_column_a,
categorical_feature_a_x_categorical_feature_b],
warm_start_from="/path/to/checkpoint/dir")
# Input builders
def input_fn_train:
# Returns tf.data.Dataset of (x, y) tuple where y represents label's class
# index.
pass
def input_fn_eval:
# Returns tf.data.Dataset of (x, y) tuple where y represents label's class
# index.
pass
def input_fn_predict:
# Returns tf.data.Dataset of (x, None) tuple.
pass
estimator.train(input_fn=input_fn_train)
metrics = estimator.evaluate(input_fn=input_fn_eval)
predictions = estimator.predict(input_fn=input_fn_predict)
```
Input of `train` and `evaluate` should have following features,
otherwise there will be a KeyError:
* if `weight_column` is not `None`, a feature with `key=weight_column` whose
value is a `Tensor`.
* for each `column` in `feature_columns`:
- if `column` is a `SparseColumn`, a feature with `key=column.name`
whose `value` is a `SparseTensor`.
- if `column` is a `WeightedSparseColumn`, two features: the first with
`key` the id column name, the second with `key` the weight column name.
Both features' `value` must be a `SparseTensor`.
- if `column` is a `RealValuedColumn`, a feature with `key=column.name`
whose `value` is a `Tensor`.
Loss is calculated by using mean squared error.
@compatibility(eager)
Estimators can be used while eager execution is enabled. Note that `input_fn`
and all hooks are executed inside a graph context, so they have to be written
to be compatible with graph mode. Note that `input_fn` code using `tf.data`
generally works in both graph and eager modes.
@end_compatibility
"""
def __init__(self,
feature_columns,
model_dir=None,
label_dimension=1,
weight_column=None,
optimizer='Ftrl',
config=None,
partitioner=None,
warm_start_from=None,
loss_reduction=losses.Reduction.SUM_OVER_BATCH_SIZE,
sparse_combiner='sum'):
"""Initializes a `LinearRegressor` instance.
Args:
feature_columns: An iterable containing all the feature columns used by
the model. All items in the set should be instances of classes derived
from `FeatureColumn`.
model_dir: Directory to save model parameters, graph and etc. This can
also be used to load checkpoints from the directory into a estimator to
continue training a previously saved model.
label_dimension: Number of regression targets per example. This is the
size of the last dimension of the labels and logits `Tensor` objects
(typically, these have shape `[batch_size, label_dimension]`).
weight_column: A string or a `_NumericColumn` created by
`tf.feature_column.numeric_column` defining feature column representing
weights. It is used to down weight or boost examples during training. It
will be multiplied by the loss of the example. If it is a string, it is
used as a key to fetch weight tensor from the `features`. If it is a
`_NumericColumn`, raw tensor is fetched by key `weight_column.key`, then
weight_column.normalizer_fn is applied on it to get weight tensor.
optimizer: An instance of `tf.Optimizer` or
`tf.estimator.experimental.LinearSDCA` used to train the model. Can also
be a string (one of 'Adagrad', 'Adam', 'Ftrl', 'RMSProp', 'SGD'), or
callable. Defaults to FTRL optimizer.
config: `RunConfig` object to configure the runtime settings.
partitioner: Optional. Partitioner for input layer.
warm_start_from: A string filepath to a checkpoint to warm-start from, or
a `WarmStartSettings` object to fully configure warm-starting. If the
string filepath is provided instead of a `WarmStartSettings`, then all
weights and biases are warm-started, and it is assumed that vocabularies
and Tensor names are unchanged.
loss_reduction: One of `tf.losses.Reduction` except `NONE`. Describes how
to reduce training loss over batch. Defaults to `SUM`.
sparse_combiner: A string specifying how to reduce if a categorical column
is multivalent. One of "mean", "sqrtn", and "sum" -- these are
effectively different ways to do example-level normalization, which can
be useful for bag-of-words features. for more details, see
`tf.feature_column.linear_model`.
"""
_validate_linear_sdca_optimizer(
feature_columns=feature_columns,
label_dimension=label_dimension,
optimizer=optimizer,
sparse_combiner=sparse_combiner)
head = regression_head.RegressionHead(
label_dimension=label_dimension,
weight_column=weight_column,
loss_reduction=loss_reduction)
def _model_fn(features, labels, mode, config):
"""Call the defined shared _linear_model_fn."""
return _linear_model_fn(
features=features,
labels=labels,
mode=mode,
head=head,
feature_columns=tuple(feature_columns or []),
optimizer=optimizer,
partitioner=partitioner,
config=config,
sparse_combiner=sparse_combiner)
super(LinearRegressorV2, self).__init__(
model_fn=_model_fn,
model_dir=model_dir,
config=config,
warm_start_from=warm_start_from)
@estimator_export(v1=['estimator.LinearRegressor']) # pylint: disable=missing-docstring
class LinearRegressor(estimator.Estimator):
__doc__ = LinearRegressorV2.__doc__.replace('SUM_OVER_BATCH_SIZE', 'SUM')
def __init__(self,
feature_columns,
model_dir=None,
label_dimension=1,
weight_column=None,
optimizer='Ftrl',
config=None,
partitioner=None,
warm_start_from=None,
loss_reduction=losses.Reduction.SUM,
sparse_combiner='sum'):
_validate_linear_sdca_optimizer(
feature_columns=feature_columns,
label_dimension=label_dimension,
optimizer=optimizer,
sparse_combiner=sparse_combiner)
head = head_lib._regression_head( # pylint: disable=protected-access
label_dimension=label_dimension,
weight_column=weight_column,
loss_reduction=loss_reduction)
def _model_fn(features, labels, mode, config):
"""Call the defined shared _linear_model_fn."""
return _linear_model_fn(
features=features,
labels=labels,
mode=mode,
head=head,
feature_columns=tuple(feature_columns or []),
optimizer=optimizer,
partitioner=partitioner,
config=config,
sparse_combiner=sparse_combiner)
super(LinearRegressor, self).__init__(
model_fn=_model_fn,
model_dir=model_dir,
config=config,
warm_start_from=warm_start_from)
| [
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] | |
0cc430d7621bfaae1f6b6a655566642dd758c4bf | 1333a965058e926649652ea55154bd73b6f05edd | /4_advanced/modules/userinput.py | bf7135098c2c79a045d6ce0bbf207f42b97ecacc | [
"MIT"
] | permissive | grecoe/teals | 42ebf114388b9f3f1580a41d5d03da39eb083082 | ea00bab4e90d3f71e3ec2d202ce596abcf006f37 | refs/heads/main | 2021-06-21T20:12:03.108427 | 2021-05-10T19:34:40 | 2021-05-10T19:34:40 | 223,172,099 | 0 | 2 | null | null | null | null | UTF-8 | Python | false | false | 2,085 | py | '''
This file allows you to hide all of the implementation details of asking
a user for input for your program. It will verify that the correct data is
returned.
Externally, we want to expose the getUserInput().
'''
'''
__parseInt
Parameters
userInput : Input string from user
error : Error to display if not a int
Returns:
Int if non error, None otherwise
'''
def __parseInt(userInput, error):
returnVal = None
try:
returnVal = int(userInput)
except Exception as ex:
returnVal = None
print(error)
return returnVal
'''
__parseFloat
Parameters
userInput : Input string from user
error : Error to display if not a float
Returns:
Float if non error, None otherwise
'''
def __parseFloat(userInput, error):
returnVal = None
try:
returnVal = float(userInput)
except Exception as ex:
returnVal = None
print(error)
return returnVal
'''
getUserInput:
Parameters:
prompt : Prompt to show to the user
error: Error to show to the user if expected type not input.
classInfo: Class info of type to collect
retries: Number of times to allow user to get it right.
Returns:
Expected value type if retries isn't exceeded
'''
def getUserInput(prompt, retries, error, classInfo):
userValue = None
className = classInfo.__name__
currentRetries = 0
while True:
currentRetries += 1
userInput = input(prompt)
if className == 'int':
userValue = __parseInt(userInput, error)
elif className == 'float':
userValue = __parseFloat(userInput, error)
else:
userValue = userInput
# If we have a value, get out
if userValue is not None:
break
# If we've exhausted our retries, get out.
if currentRetries >= retries:
print("You have exhausted your attempts to enter a ", className)
break
return userValue
| [
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] | |
1ebb7382e258c4abf52348f5f8cdcbf3ae69437d | 1500fe9ea062152becc85a01577cced0465cde52 | /landacademy/urls.py | d6983faca141d85dce6130a0e3056d9ab11c126d | [] | no_license | Xednom/gpg-ams | afe4da92384f2de1b7b69ce28e13becb103009b3 | 7c87ab639b140873dfc90ac43c7aec349aec6436 | refs/heads/master | 2022-11-06T15:22:34.761321 | 2021-05-11T03:48:08 | 2021-05-11T03:48:08 | 239,904,632 | 0 | 1 | null | 2022-11-03T02:21:18 | 2020-02-12T01:50:16 | JavaScript | UTF-8 | Python | false | false | 465 | py | from django.urls import path
from . import views
app_name="landacademy"
urlpatterns = [
path('add-land-academy-inventory', views.AddLandAcademyView.as_view(), name="add_landacademy"),
path('view-land-academy-inventory', views.LandAcademyView.as_view(), name="view_landacademy"),
path('view-o2o-smart-pricing', views.SmartPricingView.as_view(), name="view_o2o"),
path('add-o2o-smart-pricing', views.AddSmartPricingView.as_view(), name="add_o2o"),
] | [
"[email protected]"
] | |
27104a744c874c71d5916e37b398277acf2b845a | 0c427b2b8b7960bf3c1e727984532c6731328066 | /APP/forms.py | 1e073b90096a2c7b3a8ab029ca583f02c05bf928 | [] | no_license | Master-cai/flask_library | c7c3910c6f989b7f0f90a3b32eb53d421b7f431d | ebc86cbfbac67b199d06a3ec1e789b0d3fec1488 | refs/heads/master | 2020-11-24T03:34:42.063453 | 2019-12-20T09:30:01 | 2019-12-20T09:30:01 | 227,948,428 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,996 | py | from flask_wtf import FlaskForm
from wtforms import StringField, SubmitField, SelectField, TextAreaField, ValidationError, HiddenField, \
BooleanField, PasswordField, IntegerField, DateTimeField, DateField
from wtforms.validators import DataRequired, Email, Length, Optional, URL, EqualTo
class LoginForm(FlaskForm):
ReaderID = StringField('ReaderID', validators=[DataRequired(), Length(1, 20)])
password = PasswordField('Password', validators=[DataRequired(), Length(6, 20)])
remember = BooleanField('Remember me')
submit = SubmitField('Log in')
class RegisterForm(FlaskForm):
RID = StringField('RID', validators=[DataRequired(), Length(1, 20)])
rName = StringField('readerName', validators=[DataRequired()])
password = PasswordField('Password', validators=[DataRequired(),
Length(1, 20),
EqualTo('password_confirm', message='password doesn`t match')])
password_confirm = PasswordField('Password_confirm', validators=[DataRequired()])
department = StringField('Department', validators=[DataRequired(), Length(1, 20)])
major = StringField('Department', validators=[DataRequired(), Length(1, 20)])
submit = SubmitField('Register')
class SearchInfo(FlaskForm):
# SearchType = StringField('SearchType', validators=[DataRequired(), Length(1, 20)])
typeChoices = ['BID', 'BookName', 'Category', 'Press', 'Author']
SearchType = SelectField('SearchType', choices=[(t, t) for t in typeChoices])
SearchInfo = StringField('SearchInfo', validators=[DataRequired(), Length(1, 20)])
submit = SubmitField('Search')
class newBookForm(FlaskForm):
BID = StringField('BID', validators=[DataRequired(), Length(1, 20)])
bName = StringField('bName', validators=[DataRequired()])
Category = StringField('Category', validators=[DataRequired(), Length(1, 20)])
ISBN = StringField('ISBN', validators=[DataRequired(), Length(1, 20)])
author = StringField('author', validators=[DataRequired(), Length(1, 20)])
publicationDate = DateField('publicationDate', validators=[DataRequired()])
press = StringField('press', validators=[DataRequired(), Length(1, 40)])
sum = IntegerField('sum', validators=[DataRequired()])
currNum = IntegerField('currNum', validators=[DataRequired()])
submit = SubmitField('submit')
class ReturnBookForm(FlaskForm):
RID = StringField('RID', validators=[DataRequired(), Length(1, 20)])
BID = StringField('BID', validators=[DataRequired(), Length(1, 20)])
submit = SubmitField('Return')
class ReaderInfoForm(FlaskForm):
# SearchType = StringField('SearchType', validators=[DataRequired(), Length(1, 20)])
typeChoices = ['RID', 'rName', 'department']
SearchType = SelectField('SearchType', choices=[(t, t) for t in typeChoices])
SearchInfo = StringField('SearchInfo', validators=[DataRequired(), Length(1, 20)])
submit = SubmitField('Search')
| [
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] | |
dc93b89f7e841b512d47ecff109941a4fd9c59cb | a7a13ca32072bb27ce2dceb87c414767b3751ec5 | /src/gthnk/__init__.py | f8ee1ab5a2ed24607ff10461411e9f764b139904 | [] | no_license | SocioProphet/gthnk | 36e50338d5f3df19f84620ff9a337f3cf8e9e362 | fc3d21090c2de10cfd74650436536999e5c65d7c | refs/heads/master | 2022-12-13T18:55:00.610073 | 2020-09-14T14:50:21 | 2020-09-14T14:50:21 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 179 | py | from flask_sqlalchemy import SQLAlchemy
from flask_login import LoginManager
from flask_bcrypt import Bcrypt
db = SQLAlchemy()
login_manager = LoginManager()
bcrypt = Bcrypt()
| [
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] | |
5ad1c174ef11481211eccd3c9a071aaebf6e217e | 15f321878face2af9317363c5f6de1e5ddd9b749 | /solutions_python/Problem_200/1268.py | 9e45fefd2245fc74e784ff57dba4a16de3dd55a5 | [] | no_license | dr-dos-ok/Code_Jam_Webscraper | c06fd59870842664cd79c41eb460a09553e1c80a | 26a35bf114a3aa30fc4c677ef069d95f41665cc0 | refs/heads/master | 2020-04-06T08:17:40.938460 | 2018-10-14T10:12:47 | 2018-10-14T10:12:47 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,019 | py | def read_case(line):
return int(line)
def read_input(path):
f = open(path, 'r')
g = open(path + '_res.txt', 'w')
T = int(f.readline())
for i in xrange(T):
line = f.readline()
g.write('Case #%d: ' % (i+1))
n = read_case(line)
g.write(str(solve(n)))
g.write('\n')
g.close()
f.close()
def first_untidy(n):
res = 0
while n > 0:
if n%10 < (n/10)%10:
return res
res += 1
n /= 10
return -1
def is_units_tidy(n):
u = n % 10
while n > 0:
n /= 10
if n % 10 > u:
return False
return True
def solve_after_first(n):
if n < 10:
return n
if not is_units_tidy(n):
n -= n % 10 + 1
return solve_after_first(n/10)*10 + n%10
def solve(n):
k = first_untidy(n)
if k == -1:
return n
n -= n % 10**(k+1) + 1
return solve_after_first(n)
read_input('B-small-attempt1.in')
| [
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] | |
00a7d4bb8e564e8e4d36756ce801d18ce4fdfecc | b87389aa0d6595c8b649ac899e8ade4226309739 | /manage.py | f53d707f83062edaaf89cd56b7fde370fb63af16 | [] | no_license | bussiere/ImageIp | be3797d2fdd57b78d35de2111eb67b269f7df104 | bc3e7b3d4edabde5353f9fadfc46253b7407ba5a | refs/heads/master | 2020-12-24T15:23:03.255370 | 2013-08-23T10:52:46 | 2013-08-23T10:52:46 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 250 | py | #!/usr/bin/env python
import os
import sys
if __name__ == "__main__":
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "imageip.settings")
from django.core.management import execute_from_command_line
execute_from_command_line(sys.argv)
| [
"[email protected]"
] | |
b22c006c066846d679904ece442ff35ffce2ff2c | 0e114f7df2b112511785e21626bb6bdb220b5a6c | /ModelImporter/readers.py | 53245dcc930049f51e32b8c1183b280b6d1439f3 | [] | no_license | monkeyman192/NMSDK | 020c580bc7b0517bdef5b28d167924fde51dfa7f | c94bb9071e576fd16650f0b26fc5d681181976af | refs/heads/master | 2023-08-09T09:08:40.453170 | 2023-07-26T23:28:53 | 2023-07-26T23:28:53 | 73,231,820 | 25 | 6 | null | 2023-07-26T23:10:29 | 2016-11-08T22:13:48 | Python | UTF-8 | Python | false | false | 12,902 | py | from collections import namedtuple
import struct
from typing import Tuple
# TODO: move to the serialization folder?
from ..serialization.utils import (read_list_header, read_string, # noqa pylint: disable=relative-beyond-top-level
bytes_to_quat, read_bool)
from ..serialization.list_header import ListHeader # noqa pylint: disable=relative-beyond-top-level
from ..NMS.LOOKUPS import DIFFUSE, MASKS, NORMAL # noqa pylint: disable=relative-beyond-top-level
from ..utils.utils import exml_to_dict # noqa pylint: disable=relative-beyond-top-level
gstream_info = namedtuple(
'gstream_info',
['vert_size', 'vert_off', 'idx_size', 'idx_off', 'dbl_buff']
)
gstream_info_old = namedtuple(
'gstream_info',
['vert_size', 'vert_off', 'idx_size', 'idx_off']
)
def read_anim(fname):
""" Reads an anim file. """
anim_data = dict()
with open(fname, 'rb') as f:
f.seek(0x60)
# get the counts and offsets of all the info
frame_count, node_count = struct.unpack('<II', f.read(0x8))
anim_data['FrameCount'] = frame_count
anim_data['NodeCount'] = node_count
anim_data['NodeData'] = list()
# NodeData
with ListHeader(f) as node_data:
for _ in range(node_data.count):
node_name = read_string(f, 0x40)
# Skip 'can_compress'
f.seek(0x4, 1)
rot_index, trans_index, scale_index = struct.unpack(
'<III', f.read(0xC))
data = {'Node': node_name,
'RotIndex': rot_index,
'TransIndex': trans_index,
'ScaleIndex': scale_index}
anim_data['NodeData'].append(data)
# AnimFrameData
anim_data['AnimFrameData'] = list()
with ListHeader(f) as anim_frame_data:
for _ in range(anim_frame_data.count):
frame_data = dict()
with ListHeader(f) as rot_data:
rot_data_lst = list()
for _ in range(int(rot_data.count // 3)):
rot_data_lst.append(bytes_to_quat(f))
frame_data['Rotation'] = rot_data_lst # reads 0x6 bytes
with ListHeader(f) as trans_data:
trans_data_lst = list()
for _ in range(trans_data.count):
trans_data_lst.append(
struct.unpack('<ffff', f.read(0x10)))
frame_data['Translation'] = trans_data_lst
with ListHeader(f) as scale_data:
scale_data_lst = list()
for _ in range(scale_data.count):
scale_data_lst.append(
struct.unpack('<ffff', f.read(0x10)))
frame_data['Scale'] = scale_data_lst
anim_data['AnimFrameData'].append(frame_data)
# StillFrameData
still_frame_data = dict()
with ListHeader(f) as rot_data:
rot_data_lst = list()
for _ in range(int(rot_data.count // 3)):
rot_data_lst.append(bytes_to_quat(f)) # reads 0x6 bytes
still_frame_data['Rotation'] = rot_data_lst
with ListHeader(f) as trans_data:
trans_data_lst = list()
for _ in range(trans_data.count):
trans_data_lst.append(
struct.unpack('<ffff', f.read(0x10)))
still_frame_data['Translation'] = trans_data_lst
with ListHeader(f) as scale_data:
scale_data_lst = list()
for _ in range(scale_data.count):
scale_data_lst.append(
struct.unpack('<ffff', f.read(0x10)))
still_frame_data['Scale'] = scale_data_lst
anim_data['StillFrameData'] = still_frame_data
return anim_data
def read_entity_animation_data(fname: str) -> dict:
""" Read an entity file.
This will currently only support reading the animation data from the
entity file as it's all we care about right now...
Returns
-------
anim_data
List of dictionaries containing the path and name of the contained
animation data.
"""
anim_data = dict()
with open(fname, 'rb') as f:
f.seek(0x60)
has_anims = False
# Scan the list of components to see if we have a
# TkAnimationComponentData struct present.
with ListHeader(f) as components:
for _ in range(components.count):
return_offset = f.tell()
offset = struct.unpack('<Q', f.read(0x8))[0]
struct_name = read_string(f, 0x40)
if struct_name == 'cTkAnimationComponentData':
has_anims = True
break
# Read the nameHash but ignore it...
f.read(0x8)
# If no animation data is found, return.
if not has_anims:
return anim_data
# Jump to the start of the struct
f.seek(return_offset + offset)
_anim_data = read_TkAnimationData(f)
idle_anim_name = _anim_data.pop('Anim') or 'IDLE'
anim_data[idle_anim_name] = _anim_data
with ListHeader(f) as anims:
for _ in range(anims.count):
_anim_data = read_TkAnimationData(f)
anim_data[_anim_data.pop('Anim')] = _anim_data
return anim_data
def read_material(fname):
""" Reads the textures and types from a material file.
Returns
-------
data : dict
Mapping between the texture type (one of DIFFUSE, MASKS, NORMAL) and
the path to the texture
"""
data = dict()
# Read the data directly from the mbin
with open(fname, 'rb') as f:
f.seek(0x60)
# get name
data['Name'] = read_string(f, 0x80)
# get metamaterial, introduced in 2.61
data['Metamaterial'] = read_string(f, 0x100)
# get class
data['Class'] = read_string(f, 0x20)
# get whether it casts a shadow
f.seek(0x4, 1)
data['CastShadow'] = read_bool(f)
# save pointer for Flags Uniforms Samplers list headers
list_header_first = f.tell() + 0x1 + 0x80 + 0x80 + 0x2
# get material flags
data['Flags'] = list()
f.seek(list_header_first)
list_offset, list_count = read_list_header(f)
f.seek(list_offset, 1)
for i in range(list_count):
data['Flags'].append(struct.unpack('<I', f.read(0x4))[0])
# get uniforms
data['Uniforms'] = dict()
f.seek(list_header_first + 0x10)
list_offset, list_count = read_list_header(f)
f.seek(list_offset, 1)
for i in range(list_count):
name = read_string(f, 0x20)
value = struct.unpack('<ffff', f.read(0x10))
data['Uniforms'][name] = value
f.seek(0x10, 1)
# get samplers (texture paths)
data['Samplers'] = dict()
f.seek(list_header_first + 0x20)
list_offset, list_count = read_list_header(f)
f.seek(list_offset, 1)
for i in range(list_count):
name = read_string(f, 0x20)
Map = read_string(f, 0x80)
data['Samplers'][name] = Map
if i != list_count - 1:
f.seek(0x38, 1)
return data
def read_mesh_binding_data(fname):
""" Read the data relating to mesh/joint bindings from the geometry file.
Returns
-------
data : dict
All the relevant data from the geometry file
"""
data = dict()
with open(fname, 'rb') as f:
# First, check that there is data to read. If not, then return nothing
f.seek(0x78)
if struct.unpack('<I', f.read(0x4))[0] == 0:
return
# Read joint binding data
f.seek(0x70)
data['JointBindings'] = list()
with ListHeader(f) as JointBindings:
for _ in range(JointBindings.count):
jb_data = dict()
fmt = '<' + 'f' * 0x10
jb_data['InvBindMatrix'] = struct.unpack(fmt, f.read(0x40))
jb_data['BindTranslate'] = struct.unpack('<fff', f.read(0xC))
jb_data['BindRotate'] = struct.unpack('<ffff', f.read(0x10))
jb_data['BindScale'] = struct.unpack('<fff', f.read(0xC))
data['JointBindings'].append(jb_data)
# skip to the skin matrix layout data
f.seek(0xB0)
with ListHeader(f) as SkinMatrixLayout:
fmt = '<' + 'I' * SkinMatrixLayout.count
data_size = 4 * SkinMatrixLayout.count
data['SkinMatrixLayout'] = struct.unpack(fmt, f.read(data_size))
# skip to the MeshBaseSkinMat data
f.seek(0x100)
with ListHeader(f) as MeshBaseSkinMat:
fmt = '<' + 'I' * MeshBaseSkinMat.count
data_size = 4 * MeshBaseSkinMat.count
data['MeshBaseSkinMat'] = struct.unpack(fmt, f.read(data_size))
return data
def read_metadata(fname):
""" Reads all the metadata from the gstream file.
Returns
-------
data : dict (str: namedtuple)
Mapping between the names of the meshes and their metadata
"""
data = dict()
old_fmt = False
with open(fname, 'rb') as f:
# Let's get the GUID to see what version we are looking at.
f.seek(0x10)
guid = struct.unpack('<Q', f.read(0x8))[0]
# Let's check what it is. The current is 0x71E36E603CED2E6E
# Ones before this we will consider "old format".
if guid == 0xCD49AC37B4729513:
old_fmt = True
# move to the start of the StreamMetaDataArray header
f.seek(0x190)
# find how far to jump
list_offset, list_count = read_list_header(f)
f.seek(list_offset, 1)
for _ in range(list_count):
# read the ID in and strip it to be just the string and no padding.
string = read_string(f, 0x80).upper()
# skip the hash
f.seek(0x8, 1)
# read in the actual data we want
if not old_fmt:
read_data = struct.unpack('<IIII?', f.read(0x11))
# Skip the last 7 padding bytes (0xFE's)
f.seek(0x7, 1)
gstream_info_ = gstream_info
else:
read_data = struct.unpack('<IIII', f.read(0x10))
gstream_info_ = gstream_info_old
if string not in data:
data[string] = gstream_info_(*read_data)
else:
data[string] = [data[string]]
data[string].append(gstream_info_(*read_data))
return data
def read_gstream(fname: str, info: namedtuple) -> Tuple[bytes, bytes]:
""" Read the requested info from the gstream file.
Parameters
----------
fname
File path to the ~.GEOMETRY.DATA.MBIN.PC file.
info
namedtupled containing the vertex sizes and offset, and index sizes and
offsets.
Returns
-------
verts
Raw vertex data.
indexes
Raw index data.
"""
with open(fname, 'rb') as f:
f.seek(info.vert_off)
verts = f.read(info.vert_size)
f.seek(info.idx_off)
indexes = f.read(info.idx_size)
return verts, indexes
def read_TkAnimationData(f) -> dict:
""" Extract the animation name and path from the entity file. """
data = dict()
data['Anim'] = read_string(f, 0x10)
data['Filename'] = read_string(f, 0x80)
# Move the pointer to the end of the TkAnimationComponentData struct
f.seek(0xA8, 1)
return data
def read_TkModelDescriptorList(data: dict) -> dict:
""" Take a dictionary of the model descriptor data and extract recursively
just the useful info. """
ret_data = dict()
for d in data:
desc_data = []
for desc in d['Descriptors']:
sub_desc_data = {
'Id': desc['Id'],
'Name': desc['Name'],
'ReferencePaths': desc['ReferencePaths'],
'Children': [read_TkModelDescriptorList(
x['List']) for x in desc['Children']]}
desc_data.append(sub_desc_data)
ret_data[d['TypeId']] = desc_data
return ret_data
def read_descriptor(fname: str) -> dict:
""" Take a file path to a descriptor and process it, returning a dict
containing the necessary data.
Parameters
----------
fname
Full path to the descriptor file to be parsed.
Returns
-------
data
A dictionary with the required data.
"""
with open(fname) as f:
# The top level is always a list, let's just extract it immediately.
data = exml_to_dict(f)['List']
data = read_TkModelDescriptorList(data)
return data
| [
"[email protected]"
] | |
e6ed56fd3df5070e61ae811df3ed3d5638f8db41 | e1312afff90dbe1cdcd500541e29097da19fee97 | /inference/infer_with_pb_1capture.py | 83e9ad60c4b8ca47ef4676152e1dd42c7059bd70 | [] | no_license | andreiqv/github_detector_scale | af6115caff6ca6c73c934dc1fa6673ccd69b71fa | 329d32a4d26b2bfb2f902f876bb9b8eb35bd9e2a | refs/heads/master | 2020-04-08T12:30:36.966069 | 2019-01-30T22:21:34 | 2019-01-30T22:21:34 | 159,350,198 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,509 | py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# Using TF for inference, and TensorRT for compress a graph.
import sys
import os
import argparse
import tensorflow as tf
import numpy as np
from tensorflow.python.platform import gfile
from PIL import Image
import timer
from time import sleep
import io
from picamera import PiCamera
camera = PiCamera()
stream = io.BytesIO()
#import tensorflow.contrib.tensorrt as trt
use_hub_model = False
if True:
FROZEN_FPATH = '/home/pi/work/pb/model_first_3-60-1.000-1.000[0.803].pb'
#FROZEN_FPATH = '/home/pi/work/pb/model_resnet50-97-0.996-0.996[0.833].pb'
ENGINE_FPATH = 'saved_model_full_2.plan'
INPUT_SIZE = [3, 128, 128]
INPUT_NODE = 'input_1'
OUTPUT_NODE = 'dense_1/Sigmoid'
#OUTPUT_NODE = 'dense/Sigmoid'
input_output_placeholders = [INPUT_NODE + ':0', OUTPUT_NODE + ':0']
def get_image_as_array(image_file):
# Read the image & get statstics
image = Image.open(image_file)
#img.show()
#shape = [299, 299]
shape = tuple(INPUT_SIZE[1:])
#image = tf.image.resize_images(img, shape, method=tf.image.ResizeMethod.BICUBIC)
image = image.resize(shape, Image.ANTIALIAS)
image_arr = np.array(image, dtype=np.float32) / 255.0
return image_arr
def get_labels(labels_file):
with open(labels_file) as f:
labels = f.readlines()
labels = [x.strip() for x in labels]
print(labels)
#sys.exit(0)
return labels
def get_frozen_graph(pb_file):
# We load the protobuf file from the disk and parse it to retrive the unserialized graph_drf
with gfile.FastGFile(pb_file,'rb') as f:
graph_def = tf.GraphDef()
graph_def.ParseFromString(f.read())
#sess.graph.as_default() #new line
return graph_def
def compress_graph_with_trt(graph_def, precision_mode):
output_node = input_output_placeholders[1]
if precision_mode==0:
return graph_def
trt_graph = trt.create_inference_graph(
graph_def,
[output_node],
max_batch_size=1,
max_workspace_size_bytes=2<<20,
precision_mode=precision_mode)
return trt_graph
def inference_with_graph(graph_def, image):
""" Predict for single images
"""
with tf.Graph().as_default() as graph:
with tf.Session() as sess:
# Import a graph_def into the current default Graph
print("import graph")
input_, predictions = tf.import_graph_def(graph_def, name='',
return_elements=input_output_placeholders)
camera.start_preview()
camera.resolution = (640, 480)
camera.framerate = 32
timer.timer('predictions.eval')
time_res = []
for i in range(10):
camera.capture(stream, format='jpeg')
stream.seek(0)
image = Image.open(stream)
shape = tuple(INPUT_SIZE[1:])
image = image.resize(shape, Image.ANTIALIAS)
image_arr = np.array(image, dtype=np.float32) / 255.0
pred_val = predictions.eval(feed_dict={input_: [image_arr]})
print(pred_val)
timer.timer()
#time_res.append(0)
#print('index={0}, label={1}'.format(index, label))
camera.stop_preview()
print(camera.resolution)
#print('mean time = {0}'.format(np.mean(time_res)))
#return index
def inference_images_with_graph(graph_def, filenames):
""" Process list of files of images.
"""
images = [get_image_as_array(filename) for filename in filenames]
with tf.Graph().as_default() as graph:
with tf.Session() as sess:
# Import a graph_def into the current default Graph
print("import graph")
input_, predictions = tf.import_graph_def(graph_def, name='',
return_elements=input_output_placeholders)
camera.start_preview()
for i in range(len(filenames)):
filename = filenames[i]
image = images[i]
p_val = predictions.eval(feed_dict={input_: [image]})
index = np.argmax(p_val)
label = labels[index]
print('{0}: prediction={1}'.format(filename, label))
camera.stop_preview()
def createParser ():
"""ArgumentParser
"""
parser = argparse.ArgumentParser()
parser.add_argument('-i', '--input', default=None, type=str,\
help='input')
parser.add_argument('-dir', '--dir', default="../images", type=str,\
help='input')
parser.add_argument('-pb', '--pb', default="saved_model.pb", type=str,\
help='input')
parser.add_argument('-o', '--output', default="logs/1/", type=str,\
help='output')
return parser
if __name__ == '__main__':
parser = createParser()
arguments = parser.parse_args(sys.argv[1:])
pb_file = arguments.pb
if arguments.input is not None:
filenames = [arguments.input]
#image = get_image_as_array(filename)
#images = [(image]
else:
filenames = []
src_dir = arguments.dir
listdir = os.listdir(src_dir)
for f in listdir:
filenames.append(src_dir + '/' + f)
assert type(filenames) is list and filenames != []
#labels = get_labels('labels.txt')
pb_file = FROZEN_FPATH
graph_def = get_frozen_graph(pb_file)
#modes = ['FP32', 'FP16', 0]
#precision_mode = modes[2]
#pb_file_name = 'saved_model.pb' # output_graph.pb
# no compress
image_file = '/home/pi/work/images/img_1_0_2018-08-04-09-37-300672_5.jpg'
image = get_image_as_array(image_file)
inference_with_graph(graph_def, image)
#inference_images_with_graph(graph_def, filenames)
"""
for mode in modes*2:
print('\nMODE: {0}'.format(mode))
graph_def = compress_graph_with_trt(graph_def, mode)
inference_with_graph(graph_def, images, labels)
"""
"""
0.0701 sec. (total time 1.72) - model_first_3-60-1.000-1.000[0.803].pb
0.7628 sec. -- model_resnet50-97-0.996-0.996[0.833].pb
---
capture pict from cam:
1024x768 (def.) - 0.7612 sec.
""" | [
"[email protected]"
] | |
f3ad29a421a0cf868288fc6682c1a2f1460652b8 | 61ce57892c172f71286a39c8c863aa8a7b29484b | /stampede_results/efficiency.py | 819f43b7bee082e404a72cda5a0ee62105cfe01a | [] | no_license | bd-j/cetus | cfbb46aa2d94fdf982a7906bc8bdcbe9375df67c | c9f7e0972184a0c2fcc7add6e766733b7a46b149 | refs/heads/master | 2021-05-01T00:06:10.518322 | 2015-02-17T16:49:46 | 2015-02-17T16:49:46 | 21,367,348 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,067 | py | import sys, os, glob
import numpy as np
import matplotlib.pyplot as pl
import bsfh.read_results as bread
def process_run(mcmc_file, model_file):
result, pr, model = bread.read_pickles(mcmc_file, model_file=model_file)
nburn = np.sum(result['run_params']['nburn'])
nw, niter, ndim = result['chain'].shape
time = result['sampling_duration']
free_params = model.theta_labels()
return [nw, nburn, niter], time, free_params
mcfiles = glob.glob('*dmock*_mcmc')
speed, ncpu, hasgp = [], [], []
for i,f in enumerate(mcfiles):
dims, dur, params = process_run(f, f.replace('_mcmc','_model'))
print(f+'\n')
s = dims[0] * (dims[1] + dims[2]) / dur
speed += [s]
nc = dims[0]/2 + 1
ncpu += [nc]
print(dims[0], dims[2], dur, s, nc, 'gp_jitter' in params)
hasgp += ['gp_jitter' in params]
color = ['b','r']
fig, axes = pl.subplots()
clr =np.array(color)[np.array(hasgp).astype(int)]
axes.scatter(ncpu, speed/ncpu, marker ='o', c=clr)
axes.set_xlabel('cores')
axes.set_ylabel('Likelihood calculations/sec/core')
| [
"[email protected]"
] | |
ea9cb6af6472d76c58d80685599298f8e4a6f15e | 439cda44ba6d5d8061a134875736a9efcd4bf22c | /trakt_tools/tasks/profile/backup/create/handlers/playback.py | 746491bfc433fc6a3dc4ee210ef1164e29330dbc | [] | no_license | fuzeman/trakt-tools | 28a0fcb2c2efe88371bba1892777be75236fdc5c | 8bdcb117b6092733cc50f87d4f943fc23340da90 | refs/heads/master | 2023-01-07T06:16:46.716517 | 2022-12-27T22:57:03 | 2022-12-27T22:57:03 | 68,256,616 | 31 | 4 | null | 2022-12-27T22:41:57 | 2016-09-15T01:11:54 | Python | UTF-8 | Python | false | false | 801 | py | from __future__ import print_function
import logging
log = logging.getLogger(__name__)
class PlaybackHandler(object):
def run(self, backup, profile):
print('Playback Progress')
# Request ratings
response = profile.get('/sync/playback')
if response.status_code != 200:
print('Invalid response returned')
return False
# Retrieve items
items = response.json()
print(' - Received %d item(s)' % len(items))
# Write playback progress to disk
print(' - Writing to "playback.json"...')
try:
return backup.write('playback.json', items)
except Exception as ex:
log.error('Unable to write playback progress to disk: %s', ex, exc_info=True)
return False
| [
"[email protected]"
] | |
5cdd8442cd814d0483be06189f1baa90c42bb382 | d2c92cfe95a60a12660f1a10c0b952f0df3f0e8e | /adminasto/adminasto/tongji.py | 698ac53c3172a4fe3beefb1a1fcf538a722beb21 | [] | no_license | snamper/zzpython | 71bf70ec3762289bda4bba80525c15a63156a3ae | 20415249fa930ccf66849abb5edca8ae41c81de6 | refs/heads/master | 2021-12-21T16:12:22.190085 | 2017-09-30T06:26:05 | 2017-09-30T06:26:05 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,040 | py | from sphinxapi import *
import os
import MySQLdb
import datetime
nowpath=os.path.dirname(__file__)
execfile("conn.py")
#产品数量
def getproductnum(nowday):
format="%Y-%m-%d";
nowday=strtodatetime(nowday,format)
oneday=datetime.timedelta(days=1)
sql="select count(0) from products where gmt_created>'"+str(nowday)+"' and gmt_created<='"+str(nowday+oneday)+"'"
cursor.execute(sql)
offerlist=cursor.fetchone()
if offerlist:
return offerlist[0]
else:
return 0
#数据统计
def tongji(request):
fromday="2013-8-1";
format="%Y-%m-%d";
fromday=strtodatetime(fromday,format)
oneday=datetime.timedelta(days=1)
num=30
listall=[]
for i in range(0,num):
fromday=fromday-oneday
postnum=0
postnum=getproductnum(datetostr(fromday))
leavewordsnum=0
#leavewordsnum=getleavewordsnum(datetostr(fromday))
list={'date':datetostr(fromday),'postnum':postnum,'leavewordsnum':leavewordsnum}
listall.append(list)
return render_to_response('tongji.html',locals())
closeconn() | [
"[email protected]"
] | |
2a1ed3b591771dcef576f456adcb8a35894e6e42 | 7a3757a341fb1c5a06482e2e5cb066a967a6eff5 | /tests/apis/test_htmls.py | 8a62ed922151fdb0fb4d2da11af953142cdb52d2 | [
"MIT"
] | permissive | ninoseki/uzen | 4bff6080b9c0677dcf25abc0f104eca3fb92ed8a | 2a0065aa57fe3891c46e1174c1dc9aab673e52a8 | refs/heads/master | 2023-09-02T01:59:18.893712 | 2022-08-28T09:49:12 | 2022-08-28T09:49:12 | 241,092,872 | 87 | 9 | MIT | 2023-06-01T01:08:05 | 2020-02-17T11:37:59 | Python | UTF-8 | Python | false | false | 568 | py | from typing import List
from fastapi.testclient import TestClient
from app import models
def test_html(client: TestClient, snapshots: List[models.Snapshot]):
id_ = snapshots[0].id
response = client.get(f"/api/snapshots/{id_}")
snapshot = response.json()
sha256 = snapshot.get("html", {}).get("sha256", "")
response = client.get(f"/api/htmls/{sha256}")
assert response.status_code == 200
sha256 = snapshot.get("html", {}).get("sha256", "")
response = client.get(f"/api/htmls/{sha256}/text")
assert response.status_code == 200
| [
"[email protected]"
] | |
685279deb51b82c7913268989efa1ce91cda2791 | ebd5c4632bb5f85c9e3311fd70f6f1bf92fae53f | /P.O.R.-master/pirates/effects/ShipSinkSplashes.py | 4efffec5639f34902279a1a506fbbbf5ba52d62c | [] | no_license | BrandonAlex/Pirates-Online-Retribution | 7f881a64ec74e595aaf62e78a39375d2d51f4d2e | 980b7448f798e255eecfb6bd2ebb67b299b27dd7 | refs/heads/master | 2020-04-02T14:22:28.626453 | 2018-10-24T15:33:17 | 2018-10-24T15:33:17 | 154,521,816 | 2 | 1 | null | null | null | null | UTF-8 | Python | false | false | 6,226 | py | from pandac.PandaModules import *
from direct.interval.IntervalGlobal import *
from direct.particles import ParticleEffect
from direct.particles import Particles
from direct.particles import ForceGroup
from EffectController import EffectController
from PooledEffect import PooledEffect
import random
class ShipSinkSplashes(PooledEffect, EffectController):
card2Scale = 64.0
cardScale = 64.0
def __init__(self, parent = None):
PooledEffect.__init__(self)
EffectController.__init__(self)
self.setDepthWrite(0)
self.setLightOff()
self.setBin('fixed', 50)
self.effectScale = 1.0
self.f = ParticleEffect.ParticleEffect('ShipSinkSplashes')
self.f.reparentTo(self)
model = loader.loadModel('models/effects/particleMaps')
self.card = model.find('**/particleWhiteSteam')
self.card2 = model.find('**/particleSplash')
self.p0 = Particles.Particles('particles-1')
self.p0.setFactory('PointParticleFactory')
self.p0.setRenderer('SpriteParticleRenderer')
self.p0.setEmitter('DiscEmitter')
self.p1 = Particles.Particles('particles-2')
self.p1.setFactory('PointParticleFactory')
self.p1.setRenderer('SpriteParticleRenderer')
self.p1.setEmitter('DiscEmitter')
self.f.addParticles(self.p1)
self.p0.setPoolSize(128)
self.p0.setBirthRate(0.14999999999999999)
self.p0.setLitterSize(10)
self.p0.setLitterSpread(0)
self.p0.setSystemLifespan(0.0)
self.p0.setLocalVelocityFlag(1)
self.p0.setSystemGrowsOlderFlag(0)
self.p0.factory.setLifespanBase(2.5)
self.p0.factory.setLifespanSpread(0.5)
self.p0.factory.setMassBase(1.0)
self.p0.factory.setMassSpread(0.0)
self.p0.factory.setTerminalVelocityBase(400.0)
self.p0.factory.setTerminalVelocitySpread(0.0)
self.p0.renderer.setAlphaMode(BaseParticleRenderer.PRALPHAINOUT)
self.p0.renderer.setUserAlpha(0.5)
self.p0.renderer.setFromNode(self.card)
self.p0.renderer.setColor(Vec4(1.0, 1.0, 1.0, 1.0))
self.p0.renderer.setXScaleFlag(1)
self.p0.renderer.setYScaleFlag(1)
self.p0.renderer.setAnimAngleFlag(0)
self.p0.renderer.setNonanimatedTheta(0.0)
self.p0.renderer.setAlphaBlendMethod(BaseParticleRenderer.PPBLENDLINEAR)
self.p0.renderer.setAlphaDisable(0)
self.p0.renderer.getColorInterpolationManager().addLinear(0.25, 1.0, Vec4(1.0, 1.0, 1.0, 1.0), Vec4(1.0, 1.0, 1.0, 0.0), 1)
self.p0.emitter.setEmissionType(BaseParticleEmitter.ETRADIATE)
self.p0.emitter.setAmplitude(1.0)
self.p0.emitter.setAmplitudeSpread(0.0)
self.p0.emitter.setOffsetForce(Vec3(0.0, -2.0, 10.0))
self.p0.emitter.setExplicitLaunchVector(Vec3(1.0, 0.0, 0.0))
self.p0.emitter.setRadiateOrigin(Point3(0.0, 0.0, 0.0))
self.p1.setPoolSize(128)
self.p1.setBirthRate(0.01)
self.p1.setLitterSize(3)
self.p1.setLitterSpread(1)
self.p1.setSystemLifespan(0.0)
self.p1.setLocalVelocityFlag(1)
self.p1.setSystemGrowsOlderFlag(0)
self.p1.setFloorZ(-50)
self.p1.factory.setLifespanBase(0.5)
self.p1.factory.setLifespanSpread(0.14999999999999999)
self.p1.factory.setMassBase(1.0)
self.p1.factory.setMassSpread(0.0)
self.p1.factory.setTerminalVelocityBase(400.0)
self.p1.factory.setTerminalVelocitySpread(0.0)
self.p1.renderer.setAlphaMode(BaseParticleRenderer.PRALPHAOUT)
self.p1.renderer.setUserAlpha(0.25)
self.p1.renderer.setFromNode(self.card2)
self.p1.renderer.setColor(Vec4(1.0, 1.0, 1.0, 1.0))
self.p1.renderer.setXScaleFlag(1)
self.p1.renderer.setYScaleFlag(1)
self.p1.renderer.setAnimAngleFlag(0)
self.p1.renderer.setNonanimatedTheta(0.0)
self.p1.renderer.setAlphaBlendMethod(BaseParticleRenderer.PPBLENDLINEAR)
self.p1.renderer.setAlphaDisable(0)
self.p1.emitter.setEmissionType(BaseParticleEmitter.ETRADIATE)
self.p1.emitter.setAmplitude(0.0)
self.p1.emitter.setAmplitudeSpread(0.5)
self.p1.emitter.setExplicitLaunchVector(Vec3(1.0, 0.0, 0.0))
self.p1.emitter.setRadiateOrigin(Point3(0.0, 0.0, 0.0))
def createTrack(self):
self.setEffectScale(self.effectScale)
shrink = LerpFunctionInterval(self.resize, 2.5, fromData = 1.0, toData = 0.25)
self.startEffect = Sequence(Func(self.p0.setBirthRate, 0.10000000000000001), Func(self.p0.clearToInitial), Func(self.p1.setBirthRate, 0.01), Func(self.p1.clearToInitial), Func(self.f.start, self, self.particleDummy), Func(self.f.reparentTo, self))
self.endEffect = Sequence(shrink, Func(self.p0.setBirthRate, 100.0), Func(self.p1.setBirthRate, 100.0), Wait(2.0), Func(self.cleanUpEffect))
self.track = Sequence(self.startEffect, Wait(7.0), self.endEffect)
def setEffectScale(self, scale):
self.effectScale = scale
self.p0.renderer.setInitialXScale(0.14999999999999999 * self.cardScale * scale)
self.p0.renderer.setFinalXScale(0.40000000000000002 * self.cardScale * scale)
self.p0.renderer.setInitialYScale(0.14999999999999999 * self.cardScale * scale)
self.p0.renderer.setFinalYScale(0.40000000000000002 * self.cardScale * scale)
self.p0.emitter.setRadius(20.0 * scale)
self.p1.renderer.setInitialXScale(0.050000000000000003 * self.card2Scale * scale)
self.p1.renderer.setFinalXScale(0.20000000000000001 * self.card2Scale * scale)
self.p1.renderer.setInitialYScale(0.10000000000000001 * self.card2Scale * scale)
self.p1.renderer.setFinalYScale(0.14999999999999999 * self.card2Scale * scale)
self.p1.emitter.setOffsetForce(Vec3(0.0, 0.0, 16.0 * scale))
self.p1.emitter.setRadius(20.0 * scale)
def resize(self, t):
self.setEffectScale(self.effectScale * t)
def cleanUpEffect(self):
EffectController.cleanUpEffect(self)
self.checkInEffect(self)
def destroy(self):
EffectController.destroy(self)
PooledEffect.destroy(self)
| [
"[email protected]"
] | |
f29845b4a7e41fd25e8f0aaf3a5e1216fa204a11 | 1db2e2238b4ef9c1b6ca3b99508693ee254d6904 | /develop/analyse_2D_matrix/analyse_2D_matrix.py | f46d66c680efd95275086ab37592a63a94f4224e | [] | no_license | pgreisen/pythonscripts | 8674e08095f76edf08ef2059300349218079724c | 0aadf8f96d19b306c1bc44a772e766a06fe3408b | refs/heads/master | 2021-07-06T23:54:57.774342 | 2021-06-08T19:36:36 | 2021-06-08T19:36:36 | 22,017,192 | 3 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,186 | py | from numpy import mean,sqrt,var
import sys
from collections import defaultdict
from collections import OrderedDict
import os,shutil,sys,argparse
class Analyse2D:
def __init__(self):
self.scores = defaultdict(list)
self.scores_position_two = {}
self.aa = ['ALA','ARG','ASN','ASP','CYS','GLN','GLU','GLY','HIS','ILE','LEU','LYS','MET','PHE','PRO','SER','THR','TRP','TYR','VAL']
self.aa_single_letter = ['A','R','N','D','C','Q','E','G','H','I','L','K','M','F','P','S','T','W','Y','V']
self.aa_values = []
# times above mean
self.factor = 1
self.score_term = "total_score"
self.score_term_position = 0
# A_D_resfile_scores
self.baseline_value = -552.660
def get_sorted_hashtable(self, hashtable):
return OrderedDict(sorted(hashtable.items(), key=lambda x: x[1],reverse=True)) #[0:maxvalue])
def set_matrix(self,filename):
tmp_variable = True
tmp_variable2 = False
with open(filename,'r') as f:
for line in f:
tmp_line = line.split()
if( line[0:4] == "SEQU" ):
continue
elif ( line[0:4] == "SCOR" and tmp_variable == True):
for t in range( len(tmp_line) ):
if (tmp_line[t] == self.score_term):
self.score_term_position = t
tmp_variable = False
elif( tmp_variable == False):
aa_tmp = filename.split('_')
tmp_value = round(float( tmp_line[self.score_term_position] ) - self.baseline_value,3)
self.scores[ str(aa_tmp[0]) ].append( (aa_tmp[1], str( tmp_value ) ) )
# works
#self.scores[ str(aa_tmp[0]) ].append( (aa_tmp[1], tmp_line[self.score_term_position] - self.baseline_value) )
##print aa_tmp[1] , tmp_line[self.score_term_position]
##self.scores[ str(aa_tmp[0]) ].append( scores_position_two[ aa_tmp[1] ] = tmp_line[self.score_term_position] )
#self.scores_position_two = { aa_tmp[1] : tmp_line[self.score_term_position] }
#tmp_variable2 = True
#elif( tmp_variable2 == True):
#self.scores[ str(aa_tmp[0]) ].append( self.scores_position_two )
def write_matrix_to_file(self):
with open("2Dscan.csv",'w') as f:
f.write("AA(203/233),")
for key in self.aa_single_letter:
f.write(key+",")
f.write("\n")
#assert 1 == 0
# print self.scores
for key in self.aa_single_letter:
f.write(key+",")
##print key
##assert 1 == 0
tmp_dic = self.scores[ key ]
for key in self.aa_single_letter:
for i in range(len(tmp_dic) ):
if(key == tmp_dic[i][0]):
# continue
# print key, tmp_dic[i]
f.write(tmp_dic[i][1]+",")
f.write("\n")
def main(self):
parser = argparse.ArgumentParser(description="Generate 2D matrix from multiple rosetta output files")
# get the initial rosetta design as input
parser.add_argument("-s","--score_term", dest="score_term", help="Which score term to analyse (Default total_score )", default="total_score")
# parser.add_argument("-b", "--bundles", dest="helical_bundle", help="Four chains helical bundle with four chains is set to true", action="store_true", default=False )
path = "./"
files = os.listdir( path )
args_dict = vars( parser.parse_args() )
for item in args_dict:
setattr(self, item, args_dict[item])
for fl in files:
# assumes that the pachdock file ends with .out
if( os.path.isfile(fl) and fl.endswith("scores") ):
self.set_matrix( fl )
self.write_matrix_to_file()
if __name__ == "__main__":
run = Analyse2D()
run.main()
| [
"[email protected]"
] | |
127340c6f50c34bb02f1678ec7d9f12c7ce76d64 | 04c41aca1f78ac617fe1573818b10fb0e12fbe40 | /tests/schemas/users/snapshots/snap_test_queries.py | 85793ffecaf3ec9d16884144152f71578d6c90f8 | [] | no_license | telephoneorg/orka-api | 619489ae17dfd850c74aa2c950e0d4385ba059d9 | 5693aff776b7a7649617915a0a8e0942d1228c24 | refs/heads/master | 2022-01-10T15:28:21.277746 | 2019-05-16T19:06:40 | 2019-05-16T19:06:40 | 186,914,929 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,718 | py | # -*- coding: utf-8 -*-
# snapshottest: v1 - https://goo.gl/zC4yUc
from __future__ import unicode_literals
from snapshottest import Snapshot
snapshots = Snapshot()
snapshots['test_get_me_query 1'] = {
'data': {
'me': {
'cellPhone': '+14153334444',
'contexts': {
'count': 2,
'edges': [
{
'cursor': 'YXJyYXljb25uZWN0aW9uOjA=',
'node': {
'__typename': 'ParticipantContext',
'id': 'UGFydGljaXBhbnRDb250ZXh0OjE=',
'profile': {
'avatar': 'https://example.com/images/me.jpg',
'bio': '''Hey!
What are you looking at?''',
'displayName': 'Johnny',
'id': 'UHJvZmlsZTox'
},
'status': 'CREATED'
}
},
{
'cursor': 'YXJyYXljb25uZWN0aW9uOjE=',
'node': {
'__typename': 'FacilitatorContext',
'availability': '[{"isoWeekDay": 1, "start": "14:49:31.947740", "end": "22:49:31.947749"}, {"isoWeekDay": 2, "start": "14:49:31.947758", "end": "22:49:31.947760"}, {"isoWeekDay": 3, "start": "14:49:31.947765", "end": "22:49:31.947766"}, {"isoWeekDay": 4, "start": "14:49:31.947770", "end": "22:49:31.947772"}, {"isoWeekDay": 5, "start": "14:49:31.947776", "end": "22:49:31.947777"}, {"isoWeekDay": 6, "start": "14:49:31.947781", "end": "22:49:31.947782"}, {"isoWeekDay": 7, "start": "14:49:31.947786", "end": "22:49:31.947788"}]',
'id': 'RmFjaWxpdGF0b3JDb250ZXh0OjI=',
'licenses': {
'edges': [
{
'cursor': 'YXJyYXljb25uZWN0aW9uOjA=',
'node': {
'expiry': '2022-02-08',
'id': 'RmFjaWxpdGF0b3JMaWNlbnNlOjE=',
'number': 'xpii23420e90',
'type': 'TBD',
'usState': 'NY'
}
},
{
'cursor': 'YXJyYXljb25uZWN0aW9uOjE=',
'node': {
'expiry': None,
'id': 'RmFjaWxpdGF0b3JMaWNlbnNlOjI=',
'number': 'xpn342300309e8',
'type': 'TBD',
'usState': None
}
},
{
'cursor': 'YXJyYXljb25uZWN0aW9uOjI=',
'node': {
'expiry': '2016-02-08',
'id': 'RmFjaWxpdGF0b3JMaWNlbnNlOjM=',
'number': 'expired',
'type': 'TBD',
'usState': 'NY'
}
}
],
'pageInfo': {
'endCursor': 'YXJyYXljb25uZWN0aW9uOjI=',
'hasNextPage': False,
'hasPreviousPage': False,
'startCursor': 'YXJyYXljb25uZWN0aW9uOjA='
}
},
'npi': 'nc2394jt98ddeesd',
'profile': {
'avatar': 'https://dr-smith.com/photos/dr-smith.jpg',
'bio': '''I don't know how to put this but I'm kind of a big deal.
People know me. I'm very important.
I have many leather-bound books and my apartment smells of rich mahogany.''',
'displayName': 'Dr. Smith',
'id': 'UHJvZmlsZToy'
},
'status': 'CREATED'
}
}
],
'pageInfo': {
'endCursor': 'YXJyYXljb25uZWN0aW9uOjE=',
'hasNextPage': False,
'hasPreviousPage': False,
'startCursor': 'YXJyYXljb25uZWN0aW9uOjA='
}
},
'dob': '1980-01-04',
'email': '[email protected]',
'firstName': 'John',
'id': 'VXNlcjox',
'lastName': 'Smith',
'notificationPolicy': {
'allowEmail': True,
'allowMarketing': False,
'allowSms': True,
'id': 'Tm90aWZpY2F0aW9uUG9saWN5OjE='
}
}
}
}
snapshots['test_get_profile_query 1'] = {
'data': {
'profile': {
'avatar': 'https://example.com/images/me.jpg',
'bio': '''Hey!
What are you looking at?''',
'displayName': 'Johnny',
'id': 'UHJvZmlsZTox'
}
}
}
| [
"[email protected]"
] | |
c90363d9aca9321afb65fac2b14bdd26eeb19ed0 | aea20c0fe77e54e2c6a69d785c4b40507b1df851 | /inspect_platform.py | a3ba97a93c960cbcd0df7919306b95fc4f28144f | [
"MIT"
] | permissive | ShackleSlayer/cython-vst-loader | 6f219b8f97fe9e1db22b603ae9f7dd9b683ed658 | f24f2090a836b3cb739daf403f0ca5135f44d233 | refs/heads/master | 2023-06-04T20:18:20.479810 | 2021-03-27T14:22:53 | 2021-03-27T14:22:53 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 100 | py | import os
from sys import platform
print("sys.platform: " + platform)
print("os.name: " + os.name)
| [
"[email protected]"
] | |
ed7b59ea529505c039c84632f0c762b6e7687cd5 | de24f83a5e3768a2638ebcf13cbe717e75740168 | /moodledata/vpl_data/29/usersdata/149/9337/submittedfiles/atividade.py | a129ae25b27b8413697e0322686088d89dc72a89 | [] | no_license | rafaelperazzo/programacao-web | 95643423a35c44613b0f64bed05bd34780fe2436 | 170dd5440afb9ee68a973f3de13a99aa4c735d79 | refs/heads/master | 2021-01-12T14:06:25.773146 | 2017-12-22T16:05:45 | 2017-12-22T16:05:45 | 69,566,344 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,309 | py | # -*- coding: utf-8 -*-
from __future__ import division
import math
print('não sei de nada) | [
"[email protected]"
] | |
d83d17593a23cc734d5f3a70eba905a6d4cec639 | d780df6e068ab8a0f8007acb68bc88554a9d5b50 | /python/g1/asyncs/kernels/g1/asyncs/kernels/__init__.py | 14f907bb3747de8bcda48ebf1fa4c851b89d6562 | [
"MIT"
] | permissive | clchiou/garage | ed3d314ceea487b46568c14b51e96b990a50ed6f | 1d72863d3a5f5d620b170f4dd36f605e6b72054f | refs/heads/master | 2023-08-27T13:57:14.498182 | 2023-08-15T07:09:57 | 2023-08-15T19:53:52 | 32,647,497 | 3 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,425 | py | __all__ = [
'KernelTimeout',
'call_with_kernel',
'get_kernel',
'run',
'with_kernel',
]
import contextlib
import contextvars
import functools
import logging
from . import contexts
from . import kernels
# Re-export errors.
from .errors import KernelTimeout
logging.getLogger(__name__).addHandler(logging.NullHandler())
def with_kernel(func):
"""Wrap ``func`` that it is called within a kernel context."""
@functools.wraps(func)
def wrapper(*args, **kwargs):
return call_with_kernel(func, *args, **kwargs)
return wrapper
def call_with_kernel(func, *args, **kwargs):
"""Call ``func`` within a kernel context.
The kernel object is closed on return.
"""
def caller():
# Do not create nested kernels; this seems to make more sense.
# In general, I think it is easier to work with when there is
# always at most one global kernel object per thread.
if contexts.get_kernel(None) is None:
kernel = kernels.Kernel()
contexts.set_kernel(kernel)
cm = contextlib.closing(kernel)
else:
cm = contextlib.nullcontext()
with cm:
return func(*args, **kwargs)
return contextvars.copy_context().run(caller)
def run(awaitable=None, timeout=None):
return contexts.get_kernel().run(awaitable, timeout)
def get_kernel():
return contexts.get_kernel(None)
| [
"[email protected]"
] | |
750b855466580ca336ef851454d85be2d5325ce7 | 5c099927aedc6fdbc515f40ff543c65b3bf4ec67 | /algorithms/find-and-replace-pattern/src/Solution2.py | 3baef0faeceac6fc78a718b61d8201ae9e97cf0a | [] | no_license | bingzhong-project/leetcode | 7a99cb6af1adfbd9bb1996a7f66a65679053c478 | ba82e7d94840b3fec272e4c5f82e3a2cfe4b0505 | refs/heads/master | 2020-04-15T09:27:33.979519 | 2020-03-10T03:43:07 | 2020-03-10T03:43:07 | 164,550,933 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 723 | py | class Solution:
def findAndReplacePattern(self, words: list, pattern: str) -> list:
def match(word, pattern):
word_map = {}
pattern_map = {}
for i in range(len(pattern)):
if pattern[i] not in pattern_map:
pattern_map[pattern[i]] = word[i]
if word[i] not in word_map:
word_map[word[i]] = pattern[i]
if (pattern_map[pattern[i]],
word_map[word[i]]) != (word[i], pattern[i]):
return False
return True
res = []
for word in words:
if match(word, pattern):
res.append(word)
return res
| [
"[email protected]"
] | |
f95818b00f5f0d66c4279b5d1bba2ce0634bbc30 | 87209058bd5dd05ff0b3bd3ce2e5b5ed12671410 | /jiaoyu/apps/organizations/forms.py | 7fd39c13a1a60aab869309800b2a5a8761931593 | [] | no_license | keepingoner/django-Projects | 2a8a245b702a507efc27b4b5c6fb669bcf7d1846 | 8ca94559a31f82951a05dd8749c37d7595a8e298 | refs/heads/master | 2022-01-24T09:08:27.384731 | 2019-07-23T02:48:20 | 2019-07-23T02:48:20 | 109,779,078 | 3 | 1 | null | null | null | null | UTF-8 | Python | false | false | 190 | py | from django import forms
from operations.models import UserAsk
class UserAskForm(forms.ModelForm):
class Meta:
model = UserAsk
fields = ['name', 'mobile', 'coursename']
| [
"[email protected]"
] | |
d247e69e2008ceb52000bf94a9c402b65030dfbb | c84cee1abce6372a71314d28ca6a8681a6ad5cb5 | /chat/forms.py | adc3810f9a97a850edc84266b4d97bcd84337a87 | [] | no_license | SergeyLebidko/ChannelsTraining | 441477a14c6fe424ea11ba2e05aac0fef90151bc | 845a9b27f1d0bdb9424407c68e5051ec06d06cc9 | refs/heads/master | 2023-06-09T09:32:21.049921 | 2021-06-22T13:42:44 | 2021-06-22T13:42:44 | 376,584,019 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 862 | py | from django import forms
from django.core.exceptions import ValidationError
from django.contrib.auth.models import User
from django.contrib.auth.password_validation import validate_password
class RegisterForm(forms.Form):
username = forms.CharField(label='Имя пользователя', required=True)
password = forms.CharField(label='Пароль', widget=forms.PasswordInput, required=True)
def clean_password(self):
password = self.cleaned_data['password']
validate_password(password)
return password
def clean_username(self):
username = self.cleaned_data['username']
user_exists = User.objects.filter(username=username).exists()
if user_exists:
raise ValidationError('Пользователь с таким именем уже существует')
return username
| [
"[email protected]"
] | |
9c16879a60050ea6fcfd7fbdb38f04f0059b0a5e | 45c142c3e3dc8d3211a86c77385ecfdd10d28fb9 | /dstore/engine/procedures/im_SearchProductTreeNodes_Pu_pb2.py | e8477e582833c1a15b21f596409f099d300fbbfe | [] | no_license | dstore-io/dstore-sdk-python | 945d64995c8892af18fab26c90117245abec64a4 | 8494d12ac77c3c3cc6dd59026407ef514ad179fc | refs/heads/master | 2020-06-14T13:07:08.181547 | 2017-01-26T11:19:39 | 2017-01-26T11:19:39 | 75,177,794 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | true | 36,707 | py | # Generated by the protocol buffer compiler. DO NOT EDIT!
# source: dstore/engine/procedures/im_SearchProductTreeNodes_Pu.proto
import sys
_b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
from google.protobuf import descriptor_pb2
# @@protoc_insertion_point(imports)
_sym_db = _symbol_database.Default()
from dstore import values_pb2 as dstore_dot_values__pb2
from dstore.engine import engine_pb2 as dstore_dot_engine_dot_engine__pb2
DESCRIPTOR = _descriptor.FileDescriptor(
name='dstore/engine/procedures/im_SearchProductTreeNodes_Pu.proto',
package='dstore.engine.im_SearchProductTreeNodes_Pu',
syntax='proto3',
serialized_pb=_b('\n;dstore/engine/procedures/im_SearchProductTreeNodes_Pu.proto\x12*dstore.engine.im_SearchProductTreeNodes_Pu\x1a\x13\x64store/values.proto\x1a\x1a\x64store/engine/engine.proto\"\x8c\x10\n\nParameters\x12\x38\n\x13\x64omain_tree_node_id\x18\x01 \x01(\x0b\x32\x1b.dstore.values.IntegerValue\x12!\n\x18\x64omain_tree_node_id_null\x18\xe9\x07 \x01(\x08\x12;\n\x17node_characteristic_ids\x18\x02 \x01(\x0b\x32\x1a.dstore.values.StringValue\x12%\n\x1cnode_characteristic_ids_null\x18\xea\x07 \x01(\x08\x12)\n\x05value\x18\x03 \x01(\x0b\x32\x1a.dstore.values.StringValue\x12\x13\n\nvalue_null\x18\xeb\x07 \x01(\x08\x12,\n\x07is_like\x18\x04 \x01(\x0b\x32\x1b.dstore.values.BooleanValue\x12\x15\n\x0cis_like_null\x18\xec\x07 \x01(\x08\x12\x36\n\x11include_inherited\x18\x05 \x01(\x0b\x32\x1b.dstore.values.BooleanValue\x12\x1f\n\x16include_inherited_null\x18\xed\x07 \x01(\x08\x12\x34\n\x0fstart_at_row_no\x18\x06 \x01(\x0b\x32\x1b.dstore.values.IntegerValue\x12\x1d\n\x14start_at_row_no_null\x18\xee\x07 \x01(\x08\x12.\n\trow_count\x18\x07 \x01(\x0b\x32\x1b.dstore.values.IntegerValue\x12\x17\n\x0erow_count_null\x18\xef\x07 \x01(\x08\x12:\n\x15include_value_details\x18\x08 \x01(\x0b\x32\x1b.dstore.values.BooleanValue\x12#\n\x1ainclude_value_details_null\x18\xf0\x07 \x01(\x08\x12\x35\n\x10include_variants\x18\t \x01(\x0b\x32\x1b.dstore.values.BooleanValue\x12\x1e\n\x15include_variants_null\x18\xf1\x07 \x01(\x08\x12?\n\x1amaintain_search_item_lacks\x18\n \x01(\x0b\x32\x1b.dstore.values.BooleanValue\x12(\n\x1fmaintain_search_item_lacks_null\x18\xf2\x07 \x01(\x08\x12\x43\n\x1e\x62inary_characteristic_value_id\x18\x0b \x01(\x0b\x32\x1b.dstore.values.IntegerValue\x12,\n#binary_characteristic_value_id_null\x18\xf3\x07 \x01(\x08\x12@\n\x1b\x66ilter_by_characteristic_id\x18\x0c \x01(\x0b\x32\x1b.dstore.values.IntegerValue\x12)\n filter_by_characteristic_id_null\x18\xf4\x07 \x01(\x08\x12:\n\x16\x66ilter_by_charac_value\x18\r \x01(\x0b\x32\x1a.dstore.values.StringValue\x12$\n\x1b\x66ilter_by_charac_value_null\x18\xf5\x07 \x01(\x08\x12+\n\x07\x63ountry\x18\x0e \x01(\x0b\x32\x1a.dstore.values.StringValue\x12\x15\n\x0c\x63ountry_null\x18\xf6\x07 \x01(\x08\x12<\n\x17negate_filter_by_params\x18\x0f \x01(\x0b\x32\x1b.dstore.values.BooleanValue\x12%\n\x1cnegate_filter_by_params_null\x18\xf7\x07 \x01(\x08\x12*\n\x05\x63ount\x18\x10 \x01(\x0b\x32\x1b.dstore.values.IntegerValue\x12\x13\n\ncount_null\x18\xf8\x07 \x01(\x08\x12\x42\n\x1esort_by_characteristic_id_list\x18\x11 \x01(\x0b\x32\x1a.dstore.values.StringValue\x12,\n#sort_by_characteristic_id_list_null\x18\xf9\x07 \x01(\x08\x12\x34\n\x10sort_option_list\x18\x12 \x01(\x0b\x32\x1a.dstore.values.StringValue\x12\x1e\n\x15sort_option_list_null\x18\xfa\x07 \x01(\x08\x12=\n\x19inherit_depth_option_list\x18\x13 \x01(\x0b\x32\x1a.dstore.values.StringValue\x12\'\n\x1einherit_depth_option_list_null\x18\xfb\x07 \x01(\x08\x12\x44\n recursive_evaluation_option_list\x18\x14 \x01(\x0b\x32\x1a.dstore.values.StringValue\x12.\n%recursive_evaluation_option_list_null\x18\xfc\x07 \x01(\x08\x12\x43\n\x1eget_values_for_sort_by_characs\x18\x15 \x01(\x0b\x32\x1b.dstore.values.BooleanValue\x12,\n#get_values_for_sort_by_characs_null\x18\xfd\x07 \x01(\x08\x12\x37\n\x12output_into_one_id\x18\x16 \x01(\x0b\x32\x1b.dstore.values.IntegerValue\x12 \n\x17output_into_one_id_null\x18\xfe\x07 \x01(\x08\"\x84\x07\n\x08Response\x12\x38\n\x10meta_information\x18\x02 \x03(\x0b\x32\x1e.dstore.engine.MetaInformation\x12\'\n\x07message\x18\x03 \x03(\x0b\x32\x16.dstore.engine.Message\x12\x45\n\x03row\x18\x04 \x03(\x0b\x32\x38.dstore.engine.im_SearchProductTreeNodes_Pu.Response.Row\x12*\n\x05\x63ount\x18\x65 \x01(\x0b\x32\x1b.dstore.values.IntegerValue\x1a\xa1\x05\n\x03Row\x12\x0f\n\x06row_id\x18\x90N \x01(\x05\x12+\n\x06value2\x18\x91N \x01(\x0b\x32\x1a.dstore.values.StringValue\x12+\n\x06value3\x18\x92N \x01(\x0b\x32\x1a.dstore.values.StringValue\x12+\n\x06value1\x18\x93N \x01(\x0b\x32\x1a.dstore.values.StringValue\x12\x33\n\x0ematching_value\x18\x94N \x01(\x0b\x32\x1a.dstore.values.StringValue\x12\x34\n\x0e\x62inary_code_id\x18\x95N \x01(\x0b\x32\x1b.dstore.values.IntegerValue\x12\x32\n\x0ctree_node_id\x18\x96N \x01(\x0b\x32\x1b.dstore.values.IntegerValue\x12-\n\x07node_id\x18\x97N \x01(\x0b\x32\x1b.dstore.values.IntegerValue\x12\x41\n\x1cpre_predecessors_description\x18\x98N \x01(\x0b\x32\x1a.dstore.values.StringValue\x12,\n\x07product\x18\x99N \x01(\x0b\x32\x1a.dstore.values.StringValue\x12\x43\n\x1dpre_predecessors_tree_node_id\x18\x9aN \x01(\x0b\x32\x1b.dstore.values.IntegerValue\x12?\n\x19predecessors_tree_node_id\x18\x9bN \x01(\x0b\x32\x1b.dstore.values.IntegerValue\x12=\n\x18predecessors_description\x18\x9cN \x01(\x0b\x32\x1a.dstore.values.StringValueB]\n\x1bio.dstore.engine.proceduresZ>gosdk.dstore.de/engine/procedures/im_SearchProductTreeNodes_Pub\x06proto3')
,
dependencies=[dstore_dot_values__pb2.DESCRIPTOR,dstore_dot_engine_dot_engine__pb2.DESCRIPTOR,])
_sym_db.RegisterFileDescriptor(DESCRIPTOR)
_PARAMETERS = _descriptor.Descriptor(
name='Parameters',
full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='domain_tree_node_id', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.domain_tree_node_id', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='domain_tree_node_id_null', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.domain_tree_node_id_null', index=1,
number=1001, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='node_characteristic_ids', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.node_characteristic_ids', index=2,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='node_characteristic_ids_null', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.node_characteristic_ids_null', index=3,
number=1002, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='value', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.value', index=4,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='value_null', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.value_null', index=5,
number=1003, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='is_like', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.is_like', index=6,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='is_like_null', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.is_like_null', index=7,
number=1004, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='include_inherited', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.include_inherited', index=8,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='include_inherited_null', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.include_inherited_null', index=9,
number=1005, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='start_at_row_no', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.start_at_row_no', index=10,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='start_at_row_no_null', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.start_at_row_no_null', index=11,
number=1006, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='row_count', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.row_count', index=12,
number=7, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='row_count_null', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.row_count_null', index=13,
number=1007, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='include_value_details', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.include_value_details', index=14,
number=8, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='include_value_details_null', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.include_value_details_null', index=15,
number=1008, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='include_variants', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.include_variants', index=16,
number=9, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='include_variants_null', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.include_variants_null', index=17,
number=1009, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='maintain_search_item_lacks', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.maintain_search_item_lacks', index=18,
number=10, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='maintain_search_item_lacks_null', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.maintain_search_item_lacks_null', index=19,
number=1010, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='binary_characteristic_value_id', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.binary_characteristic_value_id', index=20,
number=11, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='binary_characteristic_value_id_null', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.binary_characteristic_value_id_null', index=21,
number=1011, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='filter_by_characteristic_id', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.filter_by_characteristic_id', index=22,
number=12, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='filter_by_characteristic_id_null', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.filter_by_characteristic_id_null', index=23,
number=1012, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='filter_by_charac_value', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.filter_by_charac_value', index=24,
number=13, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='filter_by_charac_value_null', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.filter_by_charac_value_null', index=25,
number=1013, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='country', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.country', index=26,
number=14, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='country_null', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.country_null', index=27,
number=1014, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='negate_filter_by_params', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.negate_filter_by_params', index=28,
number=15, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='negate_filter_by_params_null', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.negate_filter_by_params_null', index=29,
number=1015, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='count', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.count', index=30,
number=16, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='count_null', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.count_null', index=31,
number=1016, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='sort_by_characteristic_id_list', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.sort_by_characteristic_id_list', index=32,
number=17, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='sort_by_characteristic_id_list_null', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.sort_by_characteristic_id_list_null', index=33,
number=1017, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='sort_option_list', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.sort_option_list', index=34,
number=18, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='sort_option_list_null', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.sort_option_list_null', index=35,
number=1018, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='inherit_depth_option_list', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.inherit_depth_option_list', index=36,
number=19, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='inherit_depth_option_list_null', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.inherit_depth_option_list_null', index=37,
number=1019, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='recursive_evaluation_option_list', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.recursive_evaluation_option_list', index=38,
number=20, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='recursive_evaluation_option_list_null', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.recursive_evaluation_option_list_null', index=39,
number=1020, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_values_for_sort_by_characs', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.get_values_for_sort_by_characs', index=40,
number=21, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_values_for_sort_by_characs_null', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.get_values_for_sort_by_characs_null', index=41,
number=1021, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='output_into_one_id', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.output_into_one_id', index=42,
number=22, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='output_into_one_id_null', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Parameters.output_into_one_id_null', index=43,
number=1022, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
],
extensions=[
],
nested_types=[],
enum_types=[
],
options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=157,
serialized_end=2217,
)
_RESPONSE_ROW = _descriptor.Descriptor(
name='Row',
full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Response.Row',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='row_id', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Response.Row.row_id', index=0,
number=10000, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='value2', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Response.Row.value2', index=1,
number=10001, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='value3', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Response.Row.value3', index=2,
number=10002, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='value1', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Response.Row.value1', index=3,
number=10003, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='matching_value', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Response.Row.matching_value', index=4,
number=10004, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='binary_code_id', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Response.Row.binary_code_id', index=5,
number=10005, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='tree_node_id', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Response.Row.tree_node_id', index=6,
number=10006, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='node_id', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Response.Row.node_id', index=7,
number=10007, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='pre_predecessors_description', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Response.Row.pre_predecessors_description', index=8,
number=10008, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='product', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Response.Row.product', index=9,
number=10009, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='pre_predecessors_tree_node_id', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Response.Row.pre_predecessors_tree_node_id', index=10,
number=10010, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='predecessors_tree_node_id', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Response.Row.predecessors_tree_node_id', index=11,
number=10011, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='predecessors_description', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Response.Row.predecessors_description', index=12,
number=10012, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
],
extensions=[
],
nested_types=[],
enum_types=[
],
options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2447,
serialized_end=3120,
)
_RESPONSE = _descriptor.Descriptor(
name='Response',
full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Response',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='meta_information', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Response.meta_information', index=0,
number=2, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='message', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Response.message', index=1,
number=3, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='row', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Response.row', index=2,
number=4, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='count', full_name='dstore.engine.im_SearchProductTreeNodes_Pu.Response.count', index=3,
number=101, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
],
extensions=[
],
nested_types=[_RESPONSE_ROW, ],
enum_types=[
],
options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2220,
serialized_end=3120,
)
_PARAMETERS.fields_by_name['domain_tree_node_id'].message_type = dstore_dot_values__pb2._INTEGERVALUE
_PARAMETERS.fields_by_name['node_characteristic_ids'].message_type = dstore_dot_values__pb2._STRINGVALUE
_PARAMETERS.fields_by_name['value'].message_type = dstore_dot_values__pb2._STRINGVALUE
_PARAMETERS.fields_by_name['is_like'].message_type = dstore_dot_values__pb2._BOOLEANVALUE
_PARAMETERS.fields_by_name['include_inherited'].message_type = dstore_dot_values__pb2._BOOLEANVALUE
_PARAMETERS.fields_by_name['start_at_row_no'].message_type = dstore_dot_values__pb2._INTEGERVALUE
_PARAMETERS.fields_by_name['row_count'].message_type = dstore_dot_values__pb2._INTEGERVALUE
_PARAMETERS.fields_by_name['include_value_details'].message_type = dstore_dot_values__pb2._BOOLEANVALUE
_PARAMETERS.fields_by_name['include_variants'].message_type = dstore_dot_values__pb2._BOOLEANVALUE
_PARAMETERS.fields_by_name['maintain_search_item_lacks'].message_type = dstore_dot_values__pb2._BOOLEANVALUE
_PARAMETERS.fields_by_name['binary_characteristic_value_id'].message_type = dstore_dot_values__pb2._INTEGERVALUE
_PARAMETERS.fields_by_name['filter_by_characteristic_id'].message_type = dstore_dot_values__pb2._INTEGERVALUE
_PARAMETERS.fields_by_name['filter_by_charac_value'].message_type = dstore_dot_values__pb2._STRINGVALUE
_PARAMETERS.fields_by_name['country'].message_type = dstore_dot_values__pb2._STRINGVALUE
_PARAMETERS.fields_by_name['negate_filter_by_params'].message_type = dstore_dot_values__pb2._BOOLEANVALUE
_PARAMETERS.fields_by_name['count'].message_type = dstore_dot_values__pb2._INTEGERVALUE
_PARAMETERS.fields_by_name['sort_by_characteristic_id_list'].message_type = dstore_dot_values__pb2._STRINGVALUE
_PARAMETERS.fields_by_name['sort_option_list'].message_type = dstore_dot_values__pb2._STRINGVALUE
_PARAMETERS.fields_by_name['inherit_depth_option_list'].message_type = dstore_dot_values__pb2._STRINGVALUE
_PARAMETERS.fields_by_name['recursive_evaluation_option_list'].message_type = dstore_dot_values__pb2._STRINGVALUE
_PARAMETERS.fields_by_name['get_values_for_sort_by_characs'].message_type = dstore_dot_values__pb2._BOOLEANVALUE
_PARAMETERS.fields_by_name['output_into_one_id'].message_type = dstore_dot_values__pb2._INTEGERVALUE
_RESPONSE_ROW.fields_by_name['value2'].message_type = dstore_dot_values__pb2._STRINGVALUE
_RESPONSE_ROW.fields_by_name['value3'].message_type = dstore_dot_values__pb2._STRINGVALUE
_RESPONSE_ROW.fields_by_name['value1'].message_type = dstore_dot_values__pb2._STRINGVALUE
_RESPONSE_ROW.fields_by_name['matching_value'].message_type = dstore_dot_values__pb2._STRINGVALUE
_RESPONSE_ROW.fields_by_name['binary_code_id'].message_type = dstore_dot_values__pb2._INTEGERVALUE
_RESPONSE_ROW.fields_by_name['tree_node_id'].message_type = dstore_dot_values__pb2._INTEGERVALUE
_RESPONSE_ROW.fields_by_name['node_id'].message_type = dstore_dot_values__pb2._INTEGERVALUE
_RESPONSE_ROW.fields_by_name['pre_predecessors_description'].message_type = dstore_dot_values__pb2._STRINGVALUE
_RESPONSE_ROW.fields_by_name['product'].message_type = dstore_dot_values__pb2._STRINGVALUE
_RESPONSE_ROW.fields_by_name['pre_predecessors_tree_node_id'].message_type = dstore_dot_values__pb2._INTEGERVALUE
_RESPONSE_ROW.fields_by_name['predecessors_tree_node_id'].message_type = dstore_dot_values__pb2._INTEGERVALUE
_RESPONSE_ROW.fields_by_name['predecessors_description'].message_type = dstore_dot_values__pb2._STRINGVALUE
_RESPONSE_ROW.containing_type = _RESPONSE
_RESPONSE.fields_by_name['meta_information'].message_type = dstore_dot_engine_dot_engine__pb2._METAINFORMATION
_RESPONSE.fields_by_name['message'].message_type = dstore_dot_engine_dot_engine__pb2._MESSAGE
_RESPONSE.fields_by_name['row'].message_type = _RESPONSE_ROW
_RESPONSE.fields_by_name['count'].message_type = dstore_dot_values__pb2._INTEGERVALUE
DESCRIPTOR.message_types_by_name['Parameters'] = _PARAMETERS
DESCRIPTOR.message_types_by_name['Response'] = _RESPONSE
Parameters = _reflection.GeneratedProtocolMessageType('Parameters', (_message.Message,), dict(
DESCRIPTOR = _PARAMETERS,
__module__ = 'dstore.engine.procedures.im_SearchProductTreeNodes_Pu_pb2'
# @@protoc_insertion_point(class_scope:dstore.engine.im_SearchProductTreeNodes_Pu.Parameters)
))
_sym_db.RegisterMessage(Parameters)
Response = _reflection.GeneratedProtocolMessageType('Response', (_message.Message,), dict(
Row = _reflection.GeneratedProtocolMessageType('Row', (_message.Message,), dict(
DESCRIPTOR = _RESPONSE_ROW,
__module__ = 'dstore.engine.procedures.im_SearchProductTreeNodes_Pu_pb2'
# @@protoc_insertion_point(class_scope:dstore.engine.im_SearchProductTreeNodes_Pu.Response.Row)
))
,
DESCRIPTOR = _RESPONSE,
__module__ = 'dstore.engine.procedures.im_SearchProductTreeNodes_Pu_pb2'
# @@protoc_insertion_point(class_scope:dstore.engine.im_SearchProductTreeNodes_Pu.Response)
))
_sym_db.RegisterMessage(Response)
_sym_db.RegisterMessage(Response.Row)
DESCRIPTOR.has_options = True
DESCRIPTOR._options = _descriptor._ParseOptions(descriptor_pb2.FileOptions(), _b('\n\033io.dstore.engine.proceduresZ>gosdk.dstore.de/engine/procedures/im_SearchProductTreeNodes_Pu'))
import grpc
from grpc.beta import implementations as beta_implementations
from grpc.beta import interfaces as beta_interfaces
from grpc.framework.common import cardinality
from grpc.framework.interfaces.face import utilities as face_utilities
# @@protoc_insertion_point(module_scope)
| [
"[email protected]"
] | |
91d8dc9cb2b95ee091580cbe4da673fa4fb4185c | 9c36503027aa6fc2fa2f841d60f70f2697ae60be | /pygraphc/similarity/LogTextSimilarity.py | 59263ee4a8088fff29f3a4c0e97edc18e48e95c9 | [
"MIT"
] | permissive | studiawan/pygraphc | bd5517478a6e1ad04220c13fa9f7aea6546225ac | 436aca13cfbb97e7543da61d38c8462da64343b5 | refs/heads/master | 2021-01-23T21:29:41.151025 | 2018-05-17T07:54:54 | 2018-05-17T07:54:54 | 58,362,965 | 2 | 2 | null | null | null | null | UTF-8 | Python | false | false | 3,451 | py | from pygraphc.preprocess.PreprocessLog import PreprocessLog
from pygraphc.similarity.StringSimilarity import StringSimilarity
from itertools import combinations
import csv
import multiprocessing
class LogTextSimilarity(object):
"""A class for calculating cosine similarity between a log pair. This class is intended for
non-graph based clustering method.
"""
def __init__(self, mode, logtype, logs, clusters, cosine_file=''):
"""The constructor of class LogTextSimilarity.
Parameters
----------
mode : str
Mode of operation, i.e., text and text-h5
logtype : str
Type for event log, e.g., auth, syslog, etc.
logs : list
List of every line of original logs.
clusters : dict
Dictionary of clusters. Key: cluster_id, value: list of log line id.
"""
self.mode = mode
self.logtype = logtype
self.logs = logs
self.clusters = clusters
self.events = {}
self.cosine_file = cosine_file
def __call__(self, node):
return self.__write_cosine_csv(node)
def __write_cosine_csv(self, node):
csv_file = self.cosine_file + str(node) + '.csv'
f = open(csv_file, 'wb')
writer = csv.writer(f)
for cluster_id, cluster in self.clusters.iteritems():
row = []
for c in cluster:
if node != c:
similarity = StringSimilarity.get_cosine_similarity(self.events[node]['tf-idf'],
self.events[c]['tf-idf'],
self.events[node]['length'],
self.events[c]['length'])
if similarity > 0:
row.append(1 - similarity)
if row:
row.append(cluster_id)
writer.writerow(row)
f.close()
def get_cosine_similarity(self):
"""Get cosine similarity from a pair of log lines in a file.
Returns
-------
cosine_similarity : dict
Dictionary of cosine similarity in non-graph clustering. Key: (log_id1, log_id2),
value: cosine similarity distance.
"""
preprocess = PreprocessLog(self.logtype)
preprocess.preprocess_text(self.logs)
self.events = preprocess.events_text
cosines_similarity = {}
if self.mode == 'text':
# calculate cosine similarity
for log_pair in combinations(range(preprocess.loglength), 2):
cosines_similarity[log_pair] = \
StringSimilarity.get_cosine_similarity(self.events[log_pair[0]]['tf-idf'],
self.events[log_pair[1]]['tf-idf'],
self.events[log_pair[0]]['length'],
self.events[log_pair[1]]['length'])
return cosines_similarity
elif self.mode == 'text-csv':
# write cosine similarity to csv files
nodes = range(preprocess.loglength)
pool = multiprocessing.Pool(processes=3)
pool.map(self, nodes)
pool.close()
pool.join()
| [
"[email protected]"
] | |
7997978962821fe9981f1e5e1415740d920bddbb | f0d713996eb095bcdc701f3fab0a8110b8541cbb | /ENJTPoWCyEGgnXYjM_7.py | 6804f1adebe40875f04f9577628db7907b57414a | [] | no_license | daniel-reich/turbo-robot | feda6c0523bb83ab8954b6d06302bfec5b16ebdf | a7a25c63097674c0a81675eed7e6b763785f1c41 | refs/heads/main | 2023-03-26T01:55:14.210264 | 2021-03-23T16:08:01 | 2021-03-23T16:08:01 | 350,773,815 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,060 | py | """
Create a function that calculates what percentage of the box is filled in.
Give your answer as a string percentage rounded to the nearest integer.
### Examples
percent_filled([
"####",
"# #",
"#o #",
"####"
]) ➞ "25%"
# One element out of four spaces.
percent_filled([
"#######",
"#o oo #",
"#######"
]) ➞ "60%"
# Three elements out of five spaces.
percent_filled([
"######",
"#ooo #",
"#oo #",
"# #",
"# #",
"######"
]) ➞ "31%"
# Five elements out of sixteen spaces.
### Notes
* Only "o" will fill the box and also "o" will not be found outside of the box.
* Don't focus on how much physical space an element takes up, pretend that each element occupies one whole unit (which you can judge according to the number of "#" on the sides).
"""
def percent_filled(box):
frase = ''.join(box)
a = frase.count(' ')
b = frase.count('o')
return str(int((b / (a + b)) * 100)) + '%'
| [
"[email protected]"
] | |
b7b79b8c36d18d972a46f2208026d965dae2afbd | 09cead98874a64d55b9e5c84b369d3523c890442 | /py210110d_python3a/day10_210314/homework/stem1403a_hw_9_0307_KevinLiu.py | b6e041e3e82b381854c864f058043ff9a5dc02eb | [] | no_license | edu-athensoft/stem1401python_student | f12b404d749286036a090e941c0268381ce558f8 | baad017d4cef2994855b008a756758d7b5e119ec | refs/heads/master | 2021-08-29T15:01:45.875136 | 2021-08-24T23:03:51 | 2021-08-24T23:03:51 | 210,029,080 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,496 | py | """
Date: 2021-03-08
1. Write a GUI program of clock
Requirements:
(Function)
Show current time in the pattern of HH:mm:ss.aaa
i.e.
10:12:45.369
(UI)
Display a title, main area for clock, and footer for the date
Due date: by the end of next Friday
Hint:
import datetime
strftime
"""
"""
score:
perfect
"""
# tkinter module
from tkinter import *
from tkinter.ttk import Separator
import datetime
# function
def run_clock():
current_time.configure(text=datetime.datetime.now().strftime("%H:%M:%S.%f")[:12])
current_time.after(1, run_clock)
# widget
root = Tk()
root.title('Python GUI - pack fill')
w_width = 640
w_height = 450
sw = root.winfo_screenwidth(); sh = root.winfo_screenheight()
top_left_x = int(sw/2 - w_width/2); top_left_y = int(sh/2 - w_height/2)
root.geometry(f"{w_width}x{w_height}+{top_left_x}+{top_left_y}")
# header
header = Label(text="System Time", fg="Black", font=("Helvetica", 28))
header.pack(padx=15, pady=15)
# separator 1
sep = Separator(root, orient=HORIZONTAL)
sep.pack(fill=X)
# current time label
time = datetime.datetime.now().strftime("%H:%M:%S.%f")[:-3]
current_time = Label(text=time, bg="green", fg="White", font=("Helvetica", 36), width=15, height=5)
current_time.pack(padx=15, pady=15)
# separator 2
sep2 = Separator(root, orient=HORIZONTAL)
sep2.pack(fill=X)
# footer
footer = Label(text="Version 1, Kevin Liu, 12 March 2021", fg="Black", font=("Helvetica", 28))
footer.pack(padx=15, pady=15)
# main program
run_clock()
root.mainloop()
| [
"[email protected]"
] | |
0ed0a470b8e20c51b15783399801293e4c38342f | 8fa1999cb8a973937d6629c553feca60dd3a73d7 | /Atividade E/fabio01_q06.py | 2f76792ccd7c7f87b12dc795ab7900fe3e71545e | [] | no_license | Isaias301/IFPI-ads2018.1 | 16cddbb278336a3e06738f9dc21d2d11053dcec4 | 026fe5c2ffbc8aed55c478b7544472c46b357e69 | refs/heads/master | 2020-03-22T20:15:13.789014 | 2018-08-09T03:14:48 | 2018-08-09T03:14:48 | 140,585,300 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 387 | py | """ Questão: Lista E 06
Descrição: Leia uma velocidade em km/h, calcule e escreva esta velocidade em m/s.
"""
def main():
# entrada
velocidade_em_km = float(input("Digite uma uma velocidade em Km/h: "))
# calculos, operacoes, processamento
velocidade_em_ms = velocidade_em_km * 3.6
# saida
print('Resultado: %.2f m/s' % velocidade_em_ms)
if __name__ == '__main__':
main() | [
"[email protected]"
] |
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