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c3/qiskit/__init__.py | picbeats/c3 | 45 | 1600080 | from .c3_provider import C3Provider # noqa
__version__ = "0.1"
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tmac/models.py | Nondairy-Creamer/tmac | 0 | 15798 | <reponame>Nondairy-Creamer/tmac
import numpy as np
import torch
import time
from scipy import optimize
from scipy.stats import norm
import tmac.probability_distributions as tpd
import tmac.fourier as tfo
def tmac_ac(red_np, green_np, optimizer='BFGS', verbose=False, truncate_freq=False):
""" Implementation of the Two-channel motion artifact correction method (TMAC)
This is tmac_ac because it is the additive and circular boundary version
This code takes in imaging fluoresence data from two simultaneously recorded channels and attempts to remove
shared motion artifacts between the two channels
Args:
red_np: numpy array, [time, neurons], activity independent channel
green_np: numpy array, [time, neurons], activity dependent channel
optimizer: string, scipy optimizer
verbose: boolean, if true, outputs when inference is complete on each neuron and estimates time to finish
truncate_freq: boolean, if true truncates low amplitude frequencies in Fourier domain. This should give the same
results but may give sensitivity to the initial conditions
Returns: a dictionary containing: all the inferred parameters of the model
"""
# optimization is performed using Scipy optimize, so all tensors should stay on the CPU
device = 'cpu'
dtype = torch.float64
red_nan = np.any(np.isnan(red_np))
red_inf = np.any(np.isinf(red_np))
green_nan = np.any(np.isnan(green_np))
green_inf = np.any(np.isinf(green_np))
if red_nan or red_inf or green_nan or green_inf:
raise Exception('Input data cannot have any nan or inf')
# convert data to units of fold mean and subtract mean
red_np = red_np / np.mean(red_np, axis=0) - 1
green_np = green_np / np.mean(green_np, axis=0) - 1
# convert to tensors and fourier transform
red = torch.tensor(red_np, device=device, dtype=dtype)
green = torch.tensor(green_np, device=device, dtype=dtype)
red_fft = tfo.real_fft(red)
green_fft = tfo.real_fft(green)
# estimate all model parameters from the data
variance_r_noise_init = np.var(red_np, axis=0)
variance_g_noise_init = np.var(green_np, axis=0)
variance_a_init = np.var(green_np, axis=0)
variance_m_init = np.var(red_np, axis=0)
# initialize length scale using the autocorrelation of the data
length_scale_a_init = np.zeros(red_np.shape[1])
length_scale_m_init = np.zeros(red_np.shape[1])
for n in range(green_np.shape[1]):
# approximate as the standard deviation of a gaussian fit to the autocorrelation function
length_scale_m_init[n] = initialize_length_scale(red_np[:, n])
length_scale_a_init[n] = initialize_length_scale(green_np[:, n])
# preallocate space for all the training variables
a_trained = np.zeros(red_np.shape)
m_trained = np.zeros(red_np.shape)
variance_r_noise_trained = np.zeros(variance_r_noise_init.shape)
variance_g_noise_trained = np.zeros(variance_g_noise_init.shape)
variance_a_trained = np.zeros(variance_a_init.shape)
length_scale_a_trained = np.zeros(length_scale_a_init.shape)
variance_m_trained = np.zeros(variance_m_init.shape)
length_scale_m_trained = np.zeros(length_scale_m_init.shape)
# loop through each neuron and perform inference
start = time.time()
for n in range(red_np.shape[1]):
# get the initial values for the hyperparameters of this neuron
# All hyperparameters are positive so we fit them in log space
evidence_training_variables = np.log([variance_r_noise_init[n], variance_g_noise_init[n], variance_a_init[n],
length_scale_a_init[n], variance_m_init[n], length_scale_m_init[n]])
# define the evidence loss function. This function takes in and returns pytorch tensors
def evidence_loss_fn(training_variables):
return -tpd.tmac_evidence_and_posterior(red[:, n], red_fft[:, n], training_variables[0],
green[:, n], green_fft[:, n], training_variables[1],
training_variables[2], training_variables[3],
training_variables[4], training_variables[5],
truncate_freq=truncate_freq)
# a wrapper function of evidence that takes in and returns numpy variables
def evidence_loss_fn_np(training_variables_in):
training_variables = torch.tensor(training_variables_in, dtype=dtype, device=device)
return evidence_loss_fn(training_variables).numpy()
# wrapper function of for Jacobian of the evidence that takes in and returns numpy variables
def evidence_loss_jacobian_np(training_variables_in):
training_variables = torch.tensor(training_variables_in, dtype=dtype, device=device, requires_grad=True)
loss = evidence_loss_fn(training_variables)
return torch.autograd.grad(loss, training_variables, create_graph=False)[0].numpy()
# optimization function with Jacobian from pytorch
trained_variances = optimize.minimize(evidence_loss_fn_np, evidence_training_variables,
jac=evidence_loss_jacobian_np,
method=optimizer)
# calculate the posterior values
# The posterior is gaussian so we don't need to optimize, we find a and m in one step
trained_variance_torch = torch.tensor(trained_variances.x, dtype=dtype, device=device)
a, m = tpd.tmac_evidence_and_posterior(red[:, n], red_fft[:, n], trained_variance_torch[0], green[:, n], green_fft[:, n], trained_variance_torch[1],
trained_variance_torch[2], trained_variance_torch[3], trained_variance_torch[4], trained_variance_torch[5],
calculate_posterior=True, truncate_freq=truncate_freq)
a_trained[:, n] = a.numpy()
m_trained[:, n] = m.numpy()
variance_r_noise_trained[n] = torch.exp(trained_variance_torch[0]).numpy()
variance_g_noise_trained[n] = torch.exp(trained_variance_torch[1]).numpy()
variance_a_trained[n] = torch.exp(trained_variance_torch[2]).numpy()
length_scale_a_trained[n] = torch.exp(trained_variance_torch[3]).numpy()
variance_m_trained[n] = torch.exp(trained_variance_torch[4]).numpy()
length_scale_m_trained[n] = torch.exp(trained_variance_torch[5]).numpy()
if verbose:
decimals = 1e3
# print out timing
elapsed = time.time() - start
remaining = elapsed / (n + 1) * (red_np.shape[1] - (n + 1))
elapsed_truncated = np.round(elapsed * decimals) / decimals
remaining_truncated = np.round(remaining * decimals) / decimals
print(str(n + 1) + '/' + str(red_np.shape[1]) + ' neurons complete')
print(str(elapsed_truncated) + 's elapsed, estimated ' + str(remaining_truncated) + 's remaining')
trained_variables = {'a': a_trained,
'm': m_trained,
'variance_r_noise': variance_r_noise_trained,
'variance_g_noise': variance_g_noise_trained,
'variance_a': variance_a_trained,
'length_scale_a': length_scale_a_trained,
'variance_m': variance_m_trained,
'length_scale_m': length_scale_m_trained,
}
return trained_variables
def initialize_length_scale(y):
""" Function to fit a Gaussian to the autocorrelation of y
Args:
y: numpy vector
Returns: Standard deviation of a Gaussian fit to the autocorrelation of y
"""
x = np.arange(-len(y)/2, len(y)/2) + 0.5
y_z_score = (y - np.mean(y)) / np.std(y)
y_corr = np.correlate(y_z_score, y_z_score, mode='same')
# fit the std of a gaussian to the correlation function
def loss(p):
return p[0] * norm.pdf(x, 0, p[1]) - y_corr
p_init = np.array((np.max(y_corr), 1.0))
p_hat = optimize.leastsq(loss, p_init)[0]
# return the standard deviation
return p_hat[1]
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] |
tests/test_providers/test_cryptographic.py | Shanmugapriya03/mimesis | 1 | 66086 | <gh_stars>1-10
import re
import pytest
from mimesis import Cryptographic
from mimesis.enums import Algorithm
from mimesis.exceptions import NonEnumerableError
from . import patterns
class TestCryptographic(object):
@pytest.fixture
def crypto(self):
return Cryptographic()
def test_str(self, crypto):
assert re.match(patterns.PROVIDER_STR_REGEX, str(crypto))
def test_uuid(self, crypto):
assert re.match(patterns.UUID_REGEX, crypto.uuid())
@pytest.mark.parametrize(
'algorithm, length', [
(Algorithm.MD5, 32),
(Algorithm.SHA1, 40),
(Algorithm.SHA224, 56),
(Algorithm.SHA256, 64),
(Algorithm.SHA384, 96),
(Algorithm.SHA512, 128),
],
)
def test_hash(self, crypto, algorithm, length):
result = crypto.hash(algorithm=algorithm)
assert len(result) == length
def test_hash_non_enum(self, crypto):
with pytest.raises(NonEnumerableError):
crypto.hash(algorithm='nil')
@pytest.mark.parametrize('entropy', [32, 64, 128])
def test_token_bytes(self, crypto, entropy):
result = crypto.token_bytes(entropy=entropy)
assert len(result) == entropy
assert isinstance(result, bytes)
@pytest.mark.parametrize('entropy', [32, 64, 128])
def test_token_hex(self, crypto, entropy):
result = crypto.token_hex(entropy=entropy)
# Each byte converted to two hex digits.
assert len(result) == entropy * 2
assert isinstance(result, str)
@pytest.mark.parametrize('entropy', [32, 64, 128])
def test_token_urlsafe(self, crypto, entropy):
result = crypto.token_urlsafe(entropy=entropy)
assert len(result) > entropy
assert isinstance(result, str)
@pytest.mark.parametrize(
'length', [
8,
16,
],
)
def test_mnemonic_phrase(self, crypto, length):
result = crypto.mnemonic_phrase(length=length)
assert isinstance(result, str)
result = result.split(' ')
assert len(result) == length
class TestSeededCryptographic(object):
@pytest.fixture
def c1(self, seed):
return Cryptographic(seed=seed)
@pytest.fixture
def c2(self, seed):
return Cryptographic(seed=seed)
def test_uuid(self, c1, c2):
assert c1.uuid() == c2.uuid()
def test_hash(self, c1, c2):
assert c1.hash() == c2.hash()
assert c1.hash(algorithm=Algorithm.SHA512) == \
c2.hash(algorithm=Algorithm.SHA512)
def test_mnemonic_phrase(self, c1, c2):
assert c1.mnemonic_phrase() == c2.mnemonic_phrase()
assert c1.mnemonic_phrase(length=16) == \
c2.mnemonic_phrase(length=16)
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] |
bmsapp/views_api_v2.py | alanmitchell/bmon | 11 | 1603917 | """Version 2.x of the API. Relies on functions in API v1.
"""
import logging
from collections import Counter
import pytz
from django.http import JsonResponse
from dateutil.parser import parse
from django.views.decorators.csrf import csrf_exempt
from bmsapp import models
from bmsapp.data_util import weighted_resample_timeseries
from bmsapp.readingdb import bmsdata
from bmsapp.views_api_v1 import (
fail_payload,
invalid_query_params,
sensor_info,
check_sensor_reading_params
)
# Version number of this API
API_VERSION = 2.0
# Make a logger for this module
_logger = logging.getLogger('bms.' + __name__)
@csrf_exempt
def api_version(request):
"""API method that returns the version number of the API
"""
result = {
'status': 'success',
'data': {
'version': API_VERSION,
}
}
return JsonResponse(result)
@csrf_exempt
def sensor_readings(request):
"""API Method. Returns readings from multiple sensors, perhaps time-averaged
and filtered by a date/time range.
Parameters
----------
request: Django request object
The 'request' object can have the following query parameters:
sensor_id: The Sensor ID of a sensor to include. This parameter can occur
multiple times to request data from multiple sensors.
start_ts: (optional) A date/time indicating the earliest reading to return.
If not present, the earliest reading in the database is returned.
Format is a string date/time, interpretable by dateutil.parser.parse.
end_ts: (optional) A date/time indicating the latest reading to return.
If not present records through the latest record in the database are returned.
Format is a string date/time, interpretable by dateutil.parser.parse.
timezone: (optional) A timezone name, present in the pytz.timezone database
see https://en.wikipedia.org/wiki/List_of_tz_database_time_zones
e.g. "US/Alaska". The timestamps for the sensor readings are returned
consistent with this timezone. Also, 'start_ts' and 'end_ts' are interpreted
as being in this timezone. If this parameter is not provided, the timezone of
the first building associated with the requested sensor is used. If no
building is associated with the sensor, UTC is the assumed timezone.
averaging: (optional) If provided, sensor readings are averaged into evenly spaced
time intervals as indicated by this parameter. The 'averaging' time interval
must be provided as a string such as '4H' (4 hours), '2D' (2 days), or any interval
describable by Pandas time offset notation:
http://pandas.pydata.org/pandas-docs/stable/timeseries.html#offset-aliases
label_offset: (optional) Only used if an 'averaging' parameter is provided. This
parameter controls what point in the time averaging interval is used to produce
the timestamp for the returned reading. 'label_offset' uses the same format as
'averaging', i.e. Pandas time offset notation, and the value is the time distance
from the start of averaging interval to the location of the timestamp. For example,
a value of '30min' means place the timestamp 30 minutes after the start of the
interval.
If no 'label_offset' is provided, the 'label_offset' is assumed to be 0, i.e.
the starting edge of the averaging interval is marked by the timestamp. Note
that the convention in all of the BMON timeseries plots is to place the timestamp
at the *center* of the averaging interval; that is *not* the default in this
function because of the difficulty in automatically calculating the proper
label_offset for the middle of the interval.
Returns
-------
A JSON response containing an indicator of success or failure, the readings organized
how they would be exported from a Pandas DataFrame using the "to_json(orient='split')"
method, and the timezone of the timestamps returned.
"""
try:
db = bmsdata.BMSdata() # reading database
messages = {} # used to store input validity messages.
# get the list of requested sensors
sensor_ids = request.GET.getlist('sensor_id')
# must be at least one sensor.
if len(sensor_ids) == 0:
messages['sensor_id'] = 'There must be at least one requested sensor.'
# check to see if any are invalid
sensors_not_valid = []
for sensor_id in sensor_ids:
if not db.sensor_id_exists(sensor_id):
sensors_not_valid.append(sensor_id)
if len(sensors_not_valid):
messages['sensor_id'] = f"Sensors {', '.join(sensors_not_valid)} not present in the reading database."
# Check the input parameters and get the values
param_messages, start_ts, end_ts, timezone, averaging, label_offset = \
check_sensor_reading_params(request)
messages.update(param_messages)
# check for extra, improper query parameters
messages.update(invalid_query_params(request,
['sensor_id', 'timezone', 'start_ts', 'end_ts', 'averaging', 'label_offset']))
if messages:
# Input errors occurred
return fail_payload(messages)
# if there is no requested timezone (or an invalid one), use the
# the most common timezone from the buildings associated with the list of sensors.
if timezone is None:
timezone = pytz.timezone('UTC') # default timezone if no valid building tz present
tzs = []
for sensor in sensor_ids:
for bldg in sensor_info(sensor)['buildings']:
tzs.append(bldg['timezone'])
most_common_tz = Counter(tzs).most_common(1)
if most_common_tz:
tz_name, tz_count = most_common_tz[0]
try:
timezone = pytz.timezone(tz_name)
except:
# stick with default
pass
# record the name of the final timezone
tz_name = str(timezone)
# ---- Get the Sensor Readings
# if start and end timestamps are present, convert to Unix Epoch values
if start_ts:
ts_aware = timezone.localize(start_ts)
start_ts = ts_aware.timestamp()
if end_ts:
ts_aware = timezone.localize(end_ts)
end_ts = ts_aware.timestamp()
# get the sensor readings
df = db.dataframeForMultipleIDs(sensor_ids, start_ts=start_ts, end_ts=end_ts, tz=timezone)
# if averaging is requested, do it!
if averaging and len(df) > 0:
df = weighted_resample_timeseries(df,averaging,label_offset).dropna(how='all')
# make a dictionary that is formatted with orientation 'split', which is the most
# compact form to send the DataFrame
result = {
'status': 'success',
'data': {
'readings': df.to_dict(orient='split'),
'reading_timezone': tz_name,
}
}
return JsonResponse(result)
except Exception as e:
# A processing error occurred.
_logger.exception('Error retrieving sensor readings.')
result = {
'status': 'error',
'message': str(e)
}
return JsonResponse(result, status=500)
@csrf_exempt
def sensors(request):
"""Returns information about one or more sensors.
Parameters
----------
request: Django request object
The 'request' object can have the following query parameters:
sensor_id: The Sensor ID of a sensor to include. This parameter can occur
multiple times to request data from multiple sensors. If the sensor_id
parameter is not present, information for **all** sensors is returned.
Returns
-------
A JSON response containing an indicator of success or failure, a list of
sensors including sensor properties and building association information
if available.
"""
try:
#------ Check the query parameters
messages = invalid_query_params(request, ['sensor_id'])
# get a list of all the Sensor IDs in the reading database
db = bmsdata.BMSdata() # reading database
all_sensor_ids = db.sensor_id_list()
# determine the list of Sensor IDs requested by this call
sensor_ids = request.GET.getlist('sensor_id')
if len(sensor_ids) == 0:
# no sensors were in the request, which means this should
# return all sensors.
sensor_ids = all_sensor_ids
else:
# check to make sure all the Sensor IDs are valid.
invalid_ids = set(sensor_ids) - set(all_sensor_ids)
if len(invalid_ids):
messages['sensor_id'] = f"Invalid Sensor IDs: {', '.join(list(invalid_ids))}"
if messages:
return fail_payload(messages)
fields_to_exclude = ['_state']
def clean_sensor(s):
"""Function to clean up Sensor object property dictionary and
add some additional info.
Parameter 's' is the dictionary of the Django Sensor object, gotten
from sensor.__dict__
"""
# remove fields to exclude
for fld in fields_to_exclude:
s.pop(fld, None)
# look up the sensor units if present
unit_id = s.pop('unit_id')
if unit_id:
unit = models.Unit.objects.get(pk=unit_id)
s['unit'] = unit.label
else:
s['unit'] = ''
# Add a list of buildings that this sensor is associated with.
if s['id'] is not None:
bldgs = []
for link in models.BldgToSensor.objects.filter(sensor=s['id']):
bldgs.append(
{'bldg_id': link.building.pk,
'sensor_group': link.sensor_group.title,
'sort_order': link.sort_order}
)
s['buildings'] = bldgs
else:
# no buildings
s['buildings'] = []
return s
sensors = [] # list holding sensor information to return
# get a default dictionary to use if the Sensor ID is not in the Django model
# object list.
default_props = models.Sensor().__dict__
for sensor_id in sensor_ids:
try:
sensor = models.Sensor.objects.get(sensor_id=sensor_id)
sensor_props = sensor.__dict__
except:
# No Django sensor object yet (this is an unassigned sensor).
# Use default values
sensor_props = default_props.copy()
sensor_props['sensor_id'] = sensor_id
sensors.append(clean_sensor(sensor_props))
result = {
'status': 'success',
'data': {
'sensors': sensors,
}
}
return JsonResponse(result)
except Exception as e:
# A processing error occurred.
_logger.exception('Error retrieving sensor information')
result = {
'status': 'error',
'message': str(e)
}
return JsonResponse(result, status=500)
@csrf_exempt
def buildings(request):
"""Returns information about one or more buildings.
Parameters
----------
request: Django request object
The 'request' object can have the following query parameters:
building_id: The Building ID (Django model primary key) of a building to include.
This parameter can occur multiple times to request data from multiple buildings.
If the building_id parameter is not present, information for **all**
buildings is returned.
Returns
-------
A JSON response containing an indicator of success or failure, a list of
buildings including building properties and sensor association information
if available. For fuel_rate and electric_rate fields, associated objects
are substituted for the IDs.
"""
try:
#------ Check the query parameters
messages = invalid_query_params(request, ['building_id'])
# Make a list of all building IDs.
all_bldg_ids = [b.pk for b in models.Building.objects.all()]
# determine the list of Building IDs requested by this call
bldg_ids = request.GET.getlist('building_id')
bldg_ids = [int(i) for i in bldg_ids]
if len(bldg_ids) == 0:
# no builidings were in the request, which means this should
# return all buildings.
bldg_ids = all_bldg_ids
else:
# check to make sure all the Building IDs are valid.
invalid_ids = set(bldg_ids) - set(all_bldg_ids)
if len(invalid_ids):
invalid_ids = [str(i) for i in invalid_ids]
messages['building_id'] = f"Invalid Building IDs: {', '.join(list(invalid_ids))}"
if messages:
return fail_payload(messages)
fields_to_exclude = ['_state']
def clean_bldg(b):
"""Function to clean up Building object property dictionary and
add some additional info.
Parameter 'b' is the dictionary of the Django Building object, gotten
from building.__dict__
"""
# remove fields to exclude
for fld in fields_to_exclude:
b.pop(fld, None)
# look up the current Building mode if present
current_mode_id = b.pop('current_mode_id')
if current_mode_id:
current_mode = models.BuildingMode.objects.get(pk=current_mode_id)
b['current_mode'] = current_mode.name
else:
b['current_mode'] = ''
# Add the fuel and elecric rate objects
fuel_rate_id = b.pop('fuel_rate_id')
if fuel_rate_id:
b['fuel_rate'] = models.FuelRate.objects.get(pk=fuel_rate_id).__dict__
b['fuel_rate'].pop('_state')
else:
b['fuel_rate'] = None
electric_rate_id = b.pop('electric_rate_id')
if electric_rate_id:
b['electric_rate'] = models.ElectricRate.objects.get(pk=electric_rate_id).__dict__
b['electric_rate'].pop('_state')
else:
b['electric_rate'] = None
# Add a list of sensors that this building is associated with.
# Note that the Sensor ID here is not the Django model primay key; it
# is the sensor_id field of the Sensor object, to be consistent with the
# sensors() endpoint of this API.
sensors = []
for link in models.BldgToSensor.objects.filter(building=b['id']):
sensors.append(
{'sensor_id': link.sensor.sensor_id,
'sensor_group': link.sensor_group.title,
'sort_order': link.sort_order}
)
b['sensors'] = sensors
# Add a list of organizations that this building is associated with.
orgs = []
for org in models.Organization.objects.filter(buildings=b['id']):
orgs.append(
(org.pk, org.title)
)
b['organizations'] = orgs
return b
bldgs = [] # list holding building information to return
for bldg_id in bldg_ids:
bldg = models.Building.objects.get(pk=bldg_id)
bldg_props = bldg.__dict__
bldgs.append(clean_bldg(bldg_props))
result = {
'status': 'success',
'data': {
'buildings': bldgs,
}
}
return JsonResponse(result)
except Exception as e:
# A processing error occurred.
_logger.exception('Error retrieving building information')
result = {
'status': 'error',
'message': str(e)
}
return JsonResponse(result, status=500)
@csrf_exempt
def organizations(request):
"""Returns information about one or more organizations.
Parameters
----------
request: Django request object
The 'request' object can have the following query parameters:
organization_id: The Organization ID (Django model primary key) of a organization to include.
This parameter can occur multiple times to request data from multiple organizations.
If the organization_id parameter is not present, information for **all**
organizations is returned.
Returns
-------
A JSON response containing an indicator of success or failure, a list of
organizations including organization properties and building association information
if available.
"""
try:
#------ Check the query parameters
messages = invalid_query_params(request, ['organization_id'])
# Make a list of all organization IDs.
all_org_ids = [o.pk for o in models.Organization.objects.all()]
# determine the list of Organization IDs requested by this call
org_ids = request.GET.getlist('organization_id')
org_ids = [int(i) for i in org_ids]
if len(org_ids) == 0:
# no builidings were in the request, which means this should
# return all buildings.
org_ids = all_org_ids
else:
# check to make sure all the Organization IDs are valid.
invalid_ids = set(org_ids) - set(all_org_ids)
if len(invalid_ids):
invalid_ids = [str(i) for i in invalid_ids]
messages['organization_id'] = f"Invalid Organization IDs: {', '.join(list(invalid_ids))}"
if messages:
return fail_payload(messages)
fields_to_exclude = ['_state']
def clean_org(o):
"""Function to clean up Organization object property dictionary and
add some additional info.
Parameter 'o' is the dictionary of the Django Organization object, gotten
from organization.__dict__
"""
# remove fields to exclude
for fld in fields_to_exclude:
o.pop(fld, None)
return o
orgs = [] # list holding building information to return
for org_id in org_ids:
org = models.Organization.objects.get(pk=org_id)
org_props = org.__dict__
# Add associated buildings
bldgs = []
for bldg in org.buildings.all():
bldgs.append( (bldg.pk, bldg.title) )
org_props['buildings'] = bldgs
orgs.append(clean_org(org_props))
result = {
'status': 'success',
'data': {
'organizations': orgs,
}
}
return JsonResponse(result)
except Exception as e:
# A processing error occurred.
_logger.exception('Error retrieving organization information')
result = {
'status': 'error',
'message': str(e)
}
return JsonResponse(result, status=500)
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2914,
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4660,
29922,
29945,
29900,
29900,
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2
] |
services/dao/AutoScaleSettingDao.py | liujiage/DevOpsK8s | 1 | 80216 | from abc import ABC
from common.StrUtils import isEmpty, isAnyEmpty
from common.TimeUtils import getTimeStr
from services.dao.SqliteDao import SqliteDao
from vo.AutoScaleSettingVO import AutoScaleSettingVO
from vo.LogVO import LogVO
'''
@Author Jiage
@Date 2022-02-09
@Function query auto scale and update scale
'''
class AutoScaleSettingDao(SqliteDao):
'''
@Author Jiage
@Date 2022-02-08
@Function query deploys log
'''
def query(self, value=None) -> AutoScaleSettingVO:
records = self.fetch(
'select mini_size,max_size,mem_exc,deploy_name from auto_scale_setting')
ass = AutoScaleSettingVO()
if isEmpty(records): return ass
record = records[0]
ass.miniSize = record[0]
ass.maxSize = record[1]
ass.memExc = record[2]
ass.deployName = record[3]
return ass
'''
@Author Jiage
@Date 2022-02-08
@Function Save data into the database as a log
'''
def updateOrInsert(self, value: AutoScaleSettingVO) -> int:
print("'%d' - ,'%d' - ,'%d', - '%s')" % (value.miniSize, value.maxSize, value.memExc, value.deployName))
# first delete data
self.execute("delete from auto_scale_setting")
self.execute(
"insert into auto_scale_setting(mini_size,max_size,mem_exc,deploy_name) "
"values('%d','%d','%d', '%s')" % (value.miniSize, value.maxSize, value.memExc, value.deployName))
return 1
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] |
podcast/migrations/0029_auto_20171211_0424.py | richardcornish/django-applepodcast | 7 | 68984 | # Generated by Django 2.0 on 2017-12-11 04:24
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('podcast', '0028_auto_20171211_0424'),
]
operations = [
migrations.AlterField(
model_name='show',
name='managing_editor',
field=models.EmailField(help_text='E-mail of administrative contact', max_length=255, verbose_name='editor e-mail'),
),
]
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src/fparser/common/tests/test_base_classes.py | sturmianseq/fparser | 33 | 12881 | # -*- coding: utf-8 -*-
##############################################################################
# Copyright (c) 2017 Science and Technology Facilities Council
#
# All rights reserved.
#
# Modifications made as part of the fparser project are distributed
# under the following license:
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# 1. Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
#
# 2. Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
#
# 3. Neither the name of the copyright holder nor the names of its
# contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
# HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
##############################################################################
# Modified M.Hambley, UK Met Office
##############################################################################
'''
Test battery associated with fparser.common.base_classes package.
'''
import re
import pytest
import fparser.common.base_classes
import fparser.common.readfortran
import fparser.common.sourceinfo
import fparser.common.utils
from fparser import api
def test_statement_logging(log, monkeypatch):
'''
Tests the Statement class' logging methods.
'''
class DummyParser(object):
'''
Null parser harness.
'''
def __init__(self, reader):
self.reader = reader
reader = fparser.common.readfortran.FortranStringReader("dummy = 1")
parser = DummyParser(reader)
monkeypatch.setattr(fparser.common.base_classes.Statement,
'process_item', lambda x: None, raising=False)
unit_under_test = fparser.common.base_classes.Statement(parser, None)
unit_under_test.error('Scary biscuits')
assert(log.messages == {'critical': [],
'debug': [],
'error': ['Scary biscuits'],
'info': [],
'warning': []})
log.reset()
unit_under_test.warning('Trepidacious Cetations')
assert(log.messages == {'critical': [],
'debug': [],
'error': [],
'info': [],
'warning': ['Trepidacious Cetations']})
log.reset()
unit_under_test.info('Hilarious Ontologies')
assert(log.messages == {'critical': [],
'debug': [],
'error': [],
'info': ['Hilarious Ontologies'],
'warning': []})
def test_log_comment_mix(log):
'''
Tests that unexpected Fortran 90 comment in fixed format source is logged.
'''
class EndDummy(fparser.common.base_classes.EndStatement):
'''
Dummy EndStatement.
'''
match = re.compile(r'\s*end(\s*thing\s*\w*|)\s*\Z', re.I).match
class BeginHarness(fparser.common.base_classes.BeginStatement):
'''
Dummy BeginStatement.
'''
end_stmt_cls = EndDummy
classes = []
match = re.compile(r'\s*thing\s+(\w*)\s*\Z', re.I).match
def get_classes(self):
'''
Returns an empty list of contained statements.
'''
return []
code = ' x=1 ! Cheese'
parent = fparser.common.readfortran.FortranStringReader(
code, ignore_comments=False)
parent.set_format(fparser.common.sourceinfo.FortranFormat(False, True))
item = fparser.common.readfortran.Line(code, (1, 1), None, None, parent)
with pytest.raises(fparser.common.utils.AnalyzeError):
__ = BeginHarness(parent, item)
expected = ' 1: x=1 ! Cheese <== ' \
+ 'no parse pattern found for "x=1 ! cheese" ' \
+ "in 'BeginHarness' block, " \
+ 'trying to remove inline comment (not in Fortran 77).'
result = log.messages['warning'][0].split('\n')[1]
assert result == expected
def test_log_unexpected(log):
'''
Tests that an unexpected thing between begin and end statements logs an
event.
'''
class EndThing(fparser.common.base_classes.EndStatement):
'''
Dummy EndStatement class.
'''
isvalid = True
match = re.compile(r'\s*end(\s+thing(\s+\w+)?)?\s*$', re.I).match
class BeginThing(fparser.common.base_classes.BeginStatement):
'''
Dummy BeginStatement class.
'''
end_stmt_cls = EndThing
classes = []
match = re.compile(r'\s*thing\s+(\w+)?\s*$', re.I).match
def get_classes(self):
'''
Returns an empty list of contained classes.
'''
return []
code = [' jumper', ' end thing']
parent = fparser.common.readfortran.FortranStringReader('\n'.join(code))
parent.set_format(fparser.common.sourceinfo.FortranFormat(False, True))
item = fparser.common.readfortran.Line(code[0], (1, 1), None, None, parent)
with pytest.raises(fparser.common.utils.AnalyzeError):
__ = BeginThing(parent, item)
expected = ' 1: jumper <== no parse pattern found for "jumper" ' \
"in 'BeginThing' block."
result = log.messages['warning'][0].split('\n')[1]
assert result == expected
def test_space_after_enddo():
'''Make sure that there is no space after an 'END DO' without name,
but there is a space if there is a name after 'END DO'.
'''
# Unnamed loop:
source_str = '''\
subroutine foo
integer i, r
do i = 1,100
r = r + 1
end do
end subroutine foo
'''
tree = api.parse(source_str, isfree=True, isstrict=False)
assert "END DO " not in tree.tofortran()
# Named loop:
source_str = '''\
subroutine foo
integer i, r
loop1: do i = 1,100
r = r + 1
end do loop1
end subroutine foo
'''
tree = api.parse(source_str, isfree=True, isstrict=False)
assert "END DO loop1" in tree.tofortran()
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5447,
29889,
517,
3921,
661,
580,
13,
13,
1678,
396,
405,
2795,
2425,
29901,
13,
1678,
2752,
29918,
710,
353,
14550,
29905,
13,
1678,
1014,
14608,
457,
7953,
13,
1678,
6043,
474,
29892,
364,
13,
1678,
2425,
29896,
29901,
437,
474,
353,
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29896,
29892,
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29900,
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364,
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29896,
13,
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7953,
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13,
1678,
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353,
7882,
29889,
5510,
29898,
4993,
29918,
710,
29892,
338,
9021,
29922,
5574,
29892,
338,
710,
919,
29922,
8824,
29897,
13,
1678,
4974,
376,
11794,
11662,
2425,
29896,
29908,
297,
5447,
29889,
517,
3921,
661,
580,
13,
2
] |
T14-01/program.py | maa76/SSof-Project1920 | 2 | 1600300 | b = "mars";
a = "vasco";
a = ("hello %s world %s" % a, b)
| [
1,
289,
353,
376,
29885,
1503,
1769,
13,
29874,
353,
376,
4428,
1111,
1769,
13,
29874,
353,
4852,
12199,
1273,
29879,
3186,
1273,
29879,
29908,
1273,
263,
29892,
289,
29897,
13,
2
] |
simple_exercises/profiti/sum_of_two_matrices.py | ilante/programming_immanuela_englander | 0 | 184110 | A=[[1,2, 8], [3, 7,4]]
B=[[5,6, 9], [7,6 ,0]]
c=[]
for i in range(len(A)): #range of len gives me indecesc.
c.append([])
for j in range(len(A[i])):
sum = A[i][j]+B[i][j]
c[i].append(sum)
print(c)
# for i in range(len(A)): #range of len gives me indeces
# for j in range(len(A[i])): #again indeces
# sum = A[i][j]+B[i][j]
# rowlist.append(sum)
# print(rowlist)
# rowlist =[]
| [
1,
319,
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8999,
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396,
1596,
29898,
798,
1761,
29897,
13,
1678,
396,
1948,
1761,
353,
2636,
13,
13,
2
] |
BasicSpeechToText/app.py | AzureAdvocateBit/SpeechToTextSamples-1 | 22 | 123910 | <filename>BasicSpeechToText/app.py<gh_stars>10-100
import os
import time
from dotenv import load_dotenv
import azure.cognitiveservices.speech as speechsdk
# Load the speech key and region from the .env file
load_dotenv()
key = os.getenv("KEY")
region = os.getenv("REGION")
stop = False
# When a sentence is recognized, print it to the screen.
# If stop is said, stop the app
def recognized(args):
global stop
print(args.result.text)
if args.result.text == "Stop.":
stop = True
# Create a speech configuration using the following:
# The API key and region loaded from the .env file
# The language that will be recognized, in this example Great British English (en-GB)
#
# See https://docs.microsoft.com/en-us/azure/cognitive-services/speech-service/language-support?WT.mc_id=build2020_ca-github-jabenn
# for the list of supported languages that can be recognized
speech_config = speechsdk.SpeechConfig(subscription=key,
region=region,
speech_recognition_language="en-GB")
# Create a speech recognizer
recognizer = speechsdk.SpeechRecognizer(speech_config=speech_config)
# Connect up the recognized event
recognizer.recognized.connect(recognized)
# Start continuous recognition
# This happens in the background, so the app continues to run, hence the need for an infinite loop
recognizer.start_continuous_recognition()
print("Say something! Say stop when you are done.")
# Loop until we hear stop
while not stop:
time.sleep(0.1)
| [
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529,
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543,
264,
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13,
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29922,
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13,
29937,
14971,
701,
278,
14831,
1741,
13,
29423,
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297,
278,
3239,
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577,
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278,
817,
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385,
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13,
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681,
29918,
29423,
654,
580,
13,
13,
2158,
703,
29903,
388,
1554,
29991,
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5040,
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366,
526,
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23157,
13,
13,
29937,
21493,
2745,
591,
8293,
5040,
13,
8000,
451,
5040,
29901,
13,
1678,
931,
29889,
17059,
29898,
29900,
29889,
29896,
29897,
13,
2
] |
xldlib/exception/codes.py | Alexhuszagh/XLDiscoverer | 0 | 178336 | '''
Exceptions/codes
________________
Organized error codes for reporting errors and exceptions.
:copyright: (c) 2015 The Regents of the University of California.
:license: GNU GPL, see licenses/GNU GPLv3.txt for more details.
'''
CODES = {
"000": ("Cannot find file%(-s)s in row%(-s)s {0}."
" Deleting th%(-at)s entr%(-y)s..."),
"001": ("File%(-s)s in row%(-s)s {0} not recognized."
" Deleting th%(-at)s entr%(-y)s..."),
"002": ("Engine in row%(-s)s {0} do not match the isotope-label profile."
" Deleting th%(-at)s entr%(-y)s..."),
"003": ("Files in row%(-s)s {0} do not have matching MS2/MS3 scans. "
"Deleting those entries..."),
"004": ("Some columns are missing data.", "WARNING: Missing data"),
"005": ("The content of the clipboard is bigger than available "
"space.\nSome data loss will occur. Still want to paste?",
"WARNING: Data clipping"),
"006": ("The content of the clipboard is bigger or smaller than "
"the range selected.\nStill want to paste?",
"WARNING: Data clipping"),
"007": "Calculations are running. Are you sure you want to close?",
"008": ("Input Error", "Unequal number of files entered"),
"009": ("Truncated mod found from Protein Prospector. "
"Please check your report settings."),
"010": ("Parser Error", "Malfunctioning parser unable to match "
"scan row. Please contact {}"),
"011": ("Warning: Data for MS3 scan%(-s)s {{}} in file {} do not "
"have matching MS2 precursors. This data was removed..."),
"012": ("Input Error", "ERROR: Please select a cross-linker "
"before running Xl Discoverer."),
"013": ("Input Error", "Cannot find the path specified"),
"014": ("Gradient times are not close enough to analyze the same "
"transition over multiple files. Turning global quantitation "
"off."),
"015": ("Files in row%(-s)s {0} do not have any searchable matched "
"peptides. Deleting those entries..."),
"016": ("Input Error", "Likely truncated MS3 scan detected. "
"Invalid (blank) entry in Matched Output."),
"017": ("Input Error", "Invalid entry in Matched Output."),
"018": ("Parser Error", "Malfunctioning parser cannot parse "
"scan data. Please contact <EMAIL>"),
"019": ("Error", "An unknown error occured, please check the log file"),
"020": ("Input Error", "Selected cross-linkers do not match the "
"selected isotopic profile."),
"021": ("The sort data does not exist in the transitions "
"file and therefore cannot be sorted.", "Sorting Error"),
"022": "{0} column%(-s)s missing in current matched scans file",
"023": ("Input Error", "Could not recognize the spectral file entered."),
"024": ('Please add the chemical formula for "{}" to xlpy/matched/'
'proteome_discoverer/mods.py in MONOMERS'),
"025": ("Warning: Protease specified in matched output and was not found "
"in local protease list."),
"026": ("Some entered files do not exist", "WARNING: Missing data"),
}
| [
1,
14550,
13,
1678,
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29879,
29914,
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13,
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278,
2224,
6790,
4968,
13,
1678,
376,
29900,
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] |
sky/migrations/0008_remove_news_label.py | eethan1/IMnight2018_Backend | 0 | 26423 | # Generated by Django 2.0 on 2018-02-24 11:21
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('sky', '0007_auto_20180224_1120'),
]
operations = [
migrations.RemoveField(
model_name='news',
name='label',
),
]
| [
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] |
aoc/event2019/day19/solve.py | rjbatista/AoC | 0 | 21501 | <filename>aoc/event2019/day19/solve.py
from event2019.day13.computer_v4 import Computer_v4
########
# PART 1
computer = Computer_v4([])
computer.load_code("event2019/day19/input.txt")
def get_value(x, y):
out = []
computer.reload_code()
computer.run([x, y], out)
return out[0]
def get_area(side = 50):
area = []
min_x, width = 0, 0
for y in range(side):
row_min_x = None
x = min_x
# first '#'
while True:
val = get_value(x, y)
if val != 1:
x += 1
else:
row_min_x = x
min_x = x
break
if x == side:
break
if row_min_x != None:
# last '#'
if width > 0:
x += width - 1
while True:
val = get_value(x, y)
if val == 1:
x += 1
else:
width = x - row_min_x
break
assert x != side
area += [(row_min_x, width)]
return area
answer = sum([width for x, width in get_area() if x != None])
print("Part 1 =", answer)
assert answer == 203 # check with accepted answer
########
# PART 2
def get_top_right_in_beam(square_size = 100):
# skip ahead depending on square size
x, y = (square_size * 5, square_size * 10)
while True:
if get_value(x, y) == 1:
if get_value(x + square_size - 1, y - square_size + 1) == 1: # True implies top_left and bottom_right
return x, y - square_size + 1
y += 1
else:
x += 1
x, y = get_top_right_in_beam()
answer = 10000 * x + y
print("Part 2 =", 10000 * x + y)
assert answer == 8771057 # check with accepted answer
| [
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29955,
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29896,
29900,
29945,
29955,
396,
1423,
411,
9259,
1234,
13,
2
] |
test-crates/pyo3-mixed/test_pyo3_mixed.py | thedrow/maturin | 854 | 108932 | #!/usr/bin/env python3
import pyo3_mixed
def test_get_42():
assert pyo3_mixed.get_42() == 42
| [
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] |
pynamodb/tests/integration/config.py | augustincouette/PynamoDB | 3 | 51877 | <reponame>augustincouette/PynamoDB<filename>pynamodb/tests/integration/config.py
"""
Integration test settings
"""
DYNAMODB_HOST = 'http://localhost:8000' | [
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] |
launch_error_1.py | TheBigCharles/Saviour | 3 | 132484 | <filename>launch_error_1.py
import smtplib
from email.mime.text import MIMEText
from email.mime.image import MIMEImage
from email.mime.multipart import MIMEMultipart
from email.mime.application import MIMEApplication
fromaddr = '<EMAIL>'
password = '<PASSWORD>'
toaddrs = ['<EMAIL>']
content = 'Sorry, there is an error with the file. [FileNotFoundError]'
textApart = MIMEText(content)
m = MIMEMultipart()
m.attach(textApart)
m['Subject'] = '[FileNotFoundError]'
try:
server = smtplib.SMTP('smtp.yeah.net')
server.login(fromaddr,password)
server.sendmail(fromaddr, toaddrs, m.as_string())
server.quit()
except smtplib.SMTPException as e:
pass | [
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sina_spider/items.py | yanwen0614/Weibo | 0 | 7158 | # -*- coding: utf-8 -*-
# Define here the models for your scraped items
#
# See documentation in:
# http://doc.scrapy.org/en/latest/topics/items.html
from scrapy import Item, Field
class TweetsItem(Item):
# define the fields for your item here like:
Author = Field()
Title = Field()
Create_time = Field()
Id = Field()
Context = Field()
Source = Field()
Url = Field()
class TopicItem(Item):
Url = Field()
Title = Field()
Category = Field()
context = Field()
Id = Field()
Hotlevel = Field()
Time = Field()
def main():
item = TopicItem()
pass
if __name__ == '__main__':
main() | [
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brightness.py | darevish/scripts | 0 | 181981 | #!/usr/bin/python
# use this instead:
# http://ubuntuforums.org/showthread.php?t=2243162&p=13127246#post13127246
import sys
minBrightness = 100;
maxBrightnessFile = open("/sys/class/backlight/intel_backlight/max_brightness", "r");
maxBrightness = int(maxBrightnessFile.read());
maxBrightnessFile.close();
brightnessFile = open("/sys/class/backlight/intel_backlight/brightness", "r+")
brightness = int(brightnessFile.read())
brightnessFile.seek(0)
brightnessFile.truncate()
try:
step = int( sys.argv[1] );
except (IndexError, ValueError):
step = 0;
brightness += step
if brightness > maxBrightness:
brightness = maxBrightness
elif brightness < minBrightness:
brightness = minBrightness
brightnessFile.write( str(brightness) + "\n" );
brightnessFile.close();
| [
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python/demo_queries/volumes/treatments_by_volume.py | jocelynpender/fna-query | 0 | 193880 | <filename>python/demo_queries/volumes/treatments_by_volume.py
from src.query import *
if __name__ == '__main__':
ask_query("[[Volume::Volume 17]]", "taxa_volume_17.csv")
| [
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src/scraping/newslists_scrapers/ukrnet.py | mstrechen/news-scraper | 0 | 38971 | from queue import Queue
from datetime import datetime, timedelta
from .INewslistScraper import INewslistScraper
from .. import article
from .. import driver
class Scraper(INewslistScraper):
def __init__(self, limit: int = 100):
INewslistScraper.__init__(self, limit)
self._tag_to_url = {
"politics" : "https://www.ukr.net/news/politika.html",
"economics" : "https://www.ukr.net/news/jekonomika.html",
"accidents" : "https://www.ukr.net/news/proisshestvija.html",
"society" : "https://www.ukr.net/news/society.html",
"technologies" : "https://www.ukr.net/news/tehnologii.html",
"science" : "https://www.ukr.net/news/science.html",
"auto" : "https://www.ukr.net/news/avto.html",
"sport" : "https://www.ukr.net/news/sport.html",
"health" : "https://www.ukr.net/news/zdorove.html",
"celebrities" : "https://www.ukr.net/news/show_biznes.html",
"global" : "https://www.ukr.net/news/za_rubezhom.html",
"fun" : "https://www.ukr.net/news/kurezy.html",
"photoreport" : "https://www.ukr.net/news/fotoreportazh.html",
"video" : "https://www.ukr.net/news/video.html"
}
self.driver = driver.driver
self.xpath = {
"absolute_article_path" : '//*[@id="main"]/div/article/section'
}
self.monthshorts = [u"січ", u"лют", u"бер", u"кві", u"тра", \
u"чер", u"лип", u"сер", u"вер", u"жов", u"лис", u"гру"]
def _load_more(self):
self.driver.execute_script("window.scrollTo(0, document.body.scrollHeight);")
def _date_from_ukr_to_datetime(self, s: str, index: int):
mon = s[s.find(' ') + 1 :]
day = int(s[: s.find(' ')])
return datetime(datetime.today().year, self.monthshorts.index(mon) + 1, \
day, index // 60, index % 60)
def _convert_datetime(self, s: str, index: int):
s = s.strip()
if s.find(':') != -1:
h = int(s[:2])
m = int(s[3:])
return datetime.today() + timedelta(hours=h, minutes=m)
return self._date_from_ukr_to_datetime(s, index)
def _parse_by_tag(self, tag, url, queue: Queue):
dr = self.driver
dr.get(url)
elems = dr.find_elements_by_xpath(self.xpath["absolute_article_path"])
prev_cnt = 0
while len(elems) < self.limit and len(elems) != prev_cnt:
self._load_more()
prev_cnt = len(elems)
elems = dr.find_elements_by_xpath(self.xpath["absolute_article_path"])
for e, index in zip(elems, range(self.limit)):
dt = e.find_element_by_tag_name("time")
dt = self._convert_datetime(dt.text, index)
e = e.find_element_by_tag_name("div")
e = e.find_element_by_tag_name("div")
link = e.find_element_by_tag_name("a")
e_url = link.get_attribute("href")
e_headline = link.text
queue.put_nowait(article.Article(e_url, e_headline, dt, tags=[tag]))
def push_articles_list(self, queue: Queue):
for tag in self._tag_to_url:
self._parse_by_tag(tag, self._tag_to_url[tag], queue)
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example_problems/tutorial/piastrelle/services/eval_num_sol_server.py | romeorizzi/TALight | 4 | 122844 | <reponame>romeorizzi/TALight
#!/usr/bin/env python3
from sys import stderr, exit
from time import monotonic
from TALinputs import TALinput
from multilanguage import Env, Lang, TALcolors
from piastrelle_lib import Par
# METADATA OF THIS TAL_SERVICE:
args_list = [
('answ_modulus',int),
('goal',str),
('code_lang',str),
]
ENV =Env(args_list)
TAc =TALcolors(ENV)
LANG=Lang(ENV, TAc, lambda fstring: eval(f"f'{fstring}'"))
# START CODING YOUR SERVICE:
MAX_N_PAIRS = 14
if ENV["code_lang"]=="compiled":
MAX_N_PAIRS += 1
instances = list(range(MAX_N_PAIRS + 1))
if ENV["goal"] == "efficient":
MAX_N_PAIRS = 1000
if ENV["answ_modulus"] == 0:
MAX_N_PAIRS = 100
if ENV["code_lang"]=="compiled":
MAX_N_PAIRS *= 2
scaling_factor = 1.2
n = instances[-1]
while True:
n = 1 + int(n * scaling_factor)
if n > MAX_N_PAIRS:
break
instances.append(n)
p = Par(MAX_N_PAIRS, nums_modulus=ENV["answ_modulus"])
def one_test(n):
assert n <= MAX_N_PAIRS
risp_correct = p.num_sol(n)
TAc.print(n, "yellow", ["bold"])
start = monotonic()
risp = TALinput(int, 1, TAc=TAc)[0]
end = monotonic()
t = end - start # è un float, in secondi
if ENV["answ_modulus"] == 0:
if risp != risp_correct:
TAc.print(LANG.render_feedback("not-equal", f'# No. Your solution is NOT correct. The number of well-formed tilings of a corridor of dimension 1x {n} is:\n {risp_correct}. Not {risp}.'), "red", ["bold"])
exit(0)
elif (risp % ENV["answ_modulus"]) != (risp_correct % ENV["answ_modulus"]):
TAc.print(LANG.render_feedback("not-equiv", f'No. You solution is not correct. The number of well-formed tilings of a corridor of dimension 1x{n} is {risp_correct}. Taken modulus {ENV["answ_modulus"]} this value boils down to {risp_correct % ENV["answ_modulus"]}. Not {risp}.'), "red", ["bold"])
exit(0)
return t
for n in instances:
time = one_test(n)
print(f"#Correct! [took {time} secs on your machine]")
if time > 1:
if n > 13:
TAc.print(LANG.render_feedback("seems-correct-weak", f'# Ok. :) Your solution correctly computes the number of well formed tilings of a corridor of dimension 1x{n}.'), "green")
TAc.print(LANG.render_feedback("not-efficient", f'# No. Your solution is not efficient. Run on your machine, it took more than one second to compute the number of well-formed tilings of a corridor of dimension 1x{n} .'), "red", ["bold"])
exit(0)
TAc.print(LANG.render_feedback("seems-correct-strong", f'# Ok. :) Your solution appears to be correct (checked on several instances).'), "green")
TAc.print(LANG.render_feedback("efficient", f'# Ok. :) Your solution is efficient: its running time is logarithmic in the number of tilings it counts.'), "green")
exit(0)
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2
] |
examples/constraints.py | jbarberia/PFNET.py | 3 | 31955 | #***************************************************#
# This file is part of PFNET. #
# #
# Copyright (c) 2015, <NAME>. #
# #
# PFNET is released under the BSD 2-clause license. #
#***************************************************#
# Optimization Problems - Constraints
import sys
sys.path.append('.')
import pfnet
net = pfnet.Parser(sys.argv[1]).parse(sys.argv[1])
net.set_flags('bus',
'variable',
'any',
['voltage magnitude','voltage angle'])
print(net.num_vars == 2*net.num_buses)
constr = pfnet.Constraint('AC power balance',net)
print(constr.name == 'AC power balance')
x = net.get_var_values()
constr.analyze()
print(constr.num_extra_vars)
constr.eval(x + 0.01)
constr.eval(x)
import numpy as np
f = constr.f
print(type(f), f.shape)
print(np.linalg.norm(f,np.inf))
bus = net.get_bus(5)
Hi = constr.get_H_single(bus.dP_index)
print(type(Hi), Hi.shape, Hi.nnz)
coefficients = np.random.randn(f.size)
constr.combine_H(coefficients)
H = constr.H_combined
print(type(H), H.shape, H.nnz)
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] |
acurl/tests/test_to_curl.py | markgreene74/mite | 17 | 48313 | import pytest
from helpers import create_request
import acurl
def test_to_curl():
r = create_request("GET", "http://foo.com")
assert r.to_curl() == "curl -X GET http://foo.com"
def test_to_curl_headers():
r = create_request(
"GET", "http://foo.com", headers=("Foo: bar", "My-Header: is-awesome")
)
assert (
r.to_curl()
== "curl -X GET -H 'Foo: bar' -H 'My-Header: is-awesome' http://foo.com"
)
def test_to_curl_cookies():
r = create_request(
"GET",
"http://foo.com",
cookies=(acurl._Cookie(False, "foo.com", True, "/", False, 0, "123", "456"),),
)
assert r.to_curl() == "curl -X GET --cookie 123=456 http://foo.com"
def test_to_curl_multiple_cookies():
r = create_request(
"GET",
"http://foo.com",
cookies=(
acurl._Cookie(False, "foo.com", True, "/", False, 0, "123", "456"),
acurl._Cookie(False, "foo.com", True, "/", False, 0, "789", "abc"),
),
)
assert r.to_curl() == "curl -X GET --cookie '123=456;789=abc' http://foo.com"
@pytest.mark.skip(reason="unimplemented")
def test_to_curl_cookies_wrong_domain():
# I'm not sure if this is a valid test case...Request objects should
# probably only be constructed via Session.request, which always creates
# cookies for the domain of the request. So the case this is exercising
# won't ever happen.
r = create_request(
"GET",
"http://foo.com",
cookies=(
acurl._Cookie(
False,
"bar.com", # The domain doesn't match, the cookie should not be passed
True,
"/",
False,
0,
"123",
"456",
),
),
)
assert r.to_curl() == "curl -X GET http://foo.com"
def test_to_curl_auth():
r = create_request("GET", "http://foo.com", auth=("user", "pass"))
assert r.to_curl() == "curl -X GET --user user:pass http://foo.com"
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tests/silhouette_test.py | JesusFreke/fscad | 35 | 51505 | <gh_stars>10-100
# 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.
import adsk.fusion
from adsk.core import Point3D, Vector3D
import unittest
# note: load_tests is required for the "pattern" test filtering functionality in loadTestsFromModule in run()
from fscad.test_utils import FscadTestCase, load_tests
from fscad.fscad import *
class SilhouetteTest(FscadTestCase):
def test_orthogonal_face_silhouette(self):
rect = Rect(1, 1)
silhouette = Silhouette(rect.faces[0], adsk.core.Plane.create(
Point3D.create(0, 0, -1),
Vector3D.create(0, 0, 1)))
silhouette.create_occurrence(True)
self.assertEquals(silhouette.size().asArray(), rect.size().asArray())
def test_non_orthogonal_face_silhouette(self):
rect = Rect(1, 1)
rect.ry(45)
silhouette = Silhouette(rect.faces[0], adsk.core.Plane.create(
Point3D.create(0, 0, -1),
Vector3D.create(0, 0, 1)))
silhouette.create_occurrence(True)
self.assertEquals(silhouette.size().asArray(), (rect.size().x, rect.size().y, 0))
def test_parallel_face_silhouette(self):
rect = Rect(1, 1)
rect.ry(90)
silhouette = Silhouette(rect.faces[0], adsk.core.Plane.create(
Point3D.create(0, 0, -1),
Vector3D.create(0, 0, 1)))
silhouette.create_occurrence(True)
self.assertEquals(silhouette.size().asArray(), (0, 0, 0))
def test_body_silhouette(self):
box = Box(1, 1, 1)
box.ry(45)
silhouette = Silhouette(box.bodies[0], adsk.core.Plane.create(
Point3D.create(0, 0, -1),
Vector3D.create(0, 0, 1)))
silhouette.create_occurrence(True)
self.assertEquals(silhouette.size().asArray(), (box.size().x, box.size().y, 0))
def test_component_silhouette(self):
rect = Rect(1, 1)
rect.ry(45)
silhouette = Silhouette(rect, adsk.core.Plane.create(
Point3D.create(0, 0, -1),
Vector3D.create(0, 0, 1)))
silhouette.create_occurrence(True)
self.assertEquals(silhouette.size().asArray(), (rect.size().x, rect.size().y, 0))
def test_multiple_disjoint_faces_silhouette(self):
rect1 = Rect(1, 1)
rect2 = Rect(1, 1)
rect2.ry(45)
rect2.tx(2)
assembly = Group([rect1, rect2])
silhouette = Silhouette(assembly.faces, adsk.core.Plane.create(
Point3D.create(0, 0, -1),
Vector3D.create(0, 0, 1)))
silhouette.create_occurrence(True)
self.assertTrue(abs(silhouette.size().x - assembly.size().x) < app().pointTolerance)
self.assertTrue(abs(silhouette.size().y - assembly.size().y) < app().pointTolerance)
self.assertEquals(silhouette.size().z, 0)
def test_multiple_overlapping_faces_silhouette(self):
rect1 = Rect(1, 1)
rect2 = Rect(1, 1)
rect2.ry(45)
rect2.translate(.5, .5)
assembly = Group([rect1, rect2])
silhouette = Silhouette(assembly.faces, adsk.core.Plane.create(
Point3D.create(0, 0, -1),
Vector3D.create(0, 0, 1)))
silhouette.create_occurrence(True)
self.assertTrue(abs(silhouette.size().x - assembly.size().x) < app().pointTolerance)
self.assertTrue(abs(silhouette.size().y - assembly.size().y) < app().pointTolerance)
self.assertEquals(silhouette.size().z, 0)
def test_cylinder_silhouette(self):
cyl = Cylinder(1, 1)
silhouette = Silhouette(cyl, adsk.core.Plane.create(
Point3D.create(0, 0, -1),
Vector3D.create(0, 0, 1)))
silhouette.create_occurrence(True)
self.assertEquals(silhouette.size().asArray(), (cyl.size().x, cyl.size().y, 0))
def test_single_edge(self):
circle = Circle(1)
silhouette = Silhouette(circle.edges[0], adsk.core.Plane.create(
Point3D.create(0, 0, -1),
Vector3D.create(0, 0, 1)))
silhouette.create_occurrence(True)
self.assertEquals(silhouette.size().asArray(), circle.size().asArray())
def test_multiple_edges(self):
rect = Rect(1, 1)
hole1 = Circle(.1)
hole2 = Circle(.2)
hole1.place(
(-hole1 == -rect) + .1,
(-hole1 == -rect) + .1,
~hole1 == ~rect)
hole2.place(
(+hole2 == +rect) - .1,
(+hole2 == +rect) - .1,
~hole2 == ~rect)
assembly = Difference(rect, hole1, hole2)
silhouette = Silhouette(assembly.faces[0].outer_edges, assembly.get_plane())
silhouette.create_occurrence(True)
self.assertEquals(silhouette.size().asArray(), rect.size().asArray())
self.assertEquals(len(silhouette.edges), 4)
def test_named_edges(self):
box = Box(1, 1, 1)
silhouette = Silhouette(
box,
adsk.core.Plane.create(
Point3D.create(0, 0, -1),
Vector3D.create(0, 0, 1)),
named_edges={
"front": box.shared_edges(box.bottom, box.front),
"back": box.shared_edges(box.bottom, box.back),
"left": box.shared_edges(box.bottom, box.left),
"right": box.shared_edges(box.bottom, box.right)})
silhouette.create_occurrence(create_children=True)
edge_finder = Box(.1, .1, .1)
edge_finder.place(
~edge_finder == ~silhouette,
-edge_finder == -silhouette,
~edge_finder == ~silhouette)
found_edges = silhouette.find_edges(edge_finder)
named_edges = silhouette.named_edges("front")
self.assertEquals(len(found_edges), 1)
self.assertEquals(found_edges, named_edges)
edge_finder.place(
~edge_finder == ~silhouette,
+edge_finder == +silhouette,
~edge_finder == ~silhouette)
found_edges = silhouette.find_edges(edge_finder)
named_edges = silhouette.named_edges("back")
self.assertEquals(len(found_edges), 1)
self.assertEquals(found_edges, named_edges)
edge_finder.place(
+edge_finder == +silhouette,
~edge_finder == ~silhouette,
~edge_finder == ~silhouette)
found_edges = silhouette.find_edges(edge_finder)
named_edges = silhouette.named_edges("right")
self.assertEquals(len(found_edges), 1)
self.assertEquals(found_edges, named_edges)
edge_finder.place(
-edge_finder == -silhouette,
~edge_finder == ~silhouette,
~edge_finder == ~silhouette)
found_edges = silhouette.find_edges(edge_finder)
named_edges = silhouette.named_edges("left")
self.assertEquals(len(found_edges), 1)
self.assertEquals(found_edges, named_edges)
def run(context):
import sys
test_suite = unittest.defaultTestLoader.loadTestsFromModule(sys.modules[__name__],
#pattern="named_edges",
)
unittest.TextTestRunner(failfast=True).run(test_suite)
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ML-gane.py | HackerLion123/Machine-Learning | 1 | 176311 | from sklearn import tree;
Test_data = [[]]
| [
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scripts/matcher/utils/utils.py | jakubarendac/fingerflow | 0 | 95782 | import os
import numpy as np
def preprocess_item(filename, folder):
return np.genfromtxt(
f"{folder}/{filename}", delimiter=",")
def load_folder_data(folder):
data = []
labels = []
for _, _, files in os.walk(folder):
raw_data = [preprocess_item(filename, folder) for filename in files]
labels = [int(filename.split("_")[0]) for filename in files]
data = np.stack(raw_data)
return data, np.array(labels)
def load_dataset(dataset_path, positive=True, negative=True):
print('START: loading data')
data, labels = load_folder_data(dataset_path)
numClasses = np.max(labels) + 1
idx = [np.where(labels == i)[0] for i in range(0, numClasses)]
pairImages = []
pairLabels = []
for idxA, _ in enumerate(data):
# grab the current image and label belonging to the current
# iteration
currentImage = data[idxA]
label = labels[idxA]
# randomly pick an image that belongs to the *same* class
# label
if positive:
idxB = np.random.choice(idx[label])
posData = data[idxB]
# prepare a positive pair and update the images and labels
# lists, respectively
np.random.shuffle(currentImage)
pairImages.append([currentImage, posData])
pairLabels.append([1])
# grab the indices for each of the class labels *not* equal to
# the current label and randomly pick an image corresponding
# to a label *not* equal to the current label
# print(labels)
if negative:
negIdx = np.where(labels != label)[0]
negData = data[np.random.choice(negIdx)]
# prepare a negative pair of images and update our lists
np.random.shuffle(currentImage)
pairImages.append([currentImage, negData])
pairLabels.append([0])
# return a 2-tuple of our image pairs and labels
print('FINISH: loading data')
return (np.array(pairImages), np.array(pairLabels).astype('float32'))
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4775,
29879,
467,
579,
668,
877,
7411,
29941,
29906,
8785,
13,
2
] |
reversi.py | holishing/Othello | 0 | 75484 | #!/usr/bin/env python3
import argparse
from game.game import Game
def main():
""" Reversi game with human player vs AI player.
"""
parser = argparse.ArgumentParser()
parser.add_argument('--timeout', help="Number of seconds the brain is allowed to think before making its move",
type=int, default=1)
parser.add_argument('--text', help="Display the game in text mode", action='store_false')
parser.add_argument('--player', help="Player first", action='store_true')
parser.add_argument('--ai', help="AI first", action='store_true')
parser.add_argument('--verify', help="Verify AI using a random player", action='store_true')
args = parser.parse_args()
if args.timeout < 0:
exit()
players=['player', 'player']
if args.player:
players = ['player', 'ai']
if args.ai:
players = ['ai', 'player']
elif args.verify:
players = ['ai', 'random']
game = Game(timeout=args.timeout,
colour=args.text,
players=players)
game.run()
if __name__ == "__main__":
main()
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580,
13,
2
] |
list_albums.py | gvellut/flickr_api_utils | 0 | 85466 | <filename>list_albums.py<gh_stars>0
from datetime import datetime, timezone
from addict import Dict as Addict
from api_auth import auth_flickr
flickr = auth_flickr()
def get_albums():
return _get_album_page(1, [])
def _get_album_page(page, acc):
search_result = Addict(flickr.photosets.getList(page=page))
albums = search_result.photosets
for album in albums.photoset:
date_create = int(album.date_create)
dt_date_create = datetime.fromtimestamp(date_create, timezone.utc)
acc.append((album.title._content, dt_date_create, album.id))
if albums.page < albums.pages:
return _get_album_page(page + 1, acc)
else:
return acc
albums_with_cd = get_albums()
albums_with_cd.sort(key=lambda x: x[1], reverse=True)
for (title, date) in albums_with_cd:
print(f"{date.strftime('%Y-%m-%d')} => {title}")
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19222,
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19222,
29881,
1495,
29913,
1149,
426,
3257,
27195,
13,
2
] |
howdoyoulike/howdoyoulike/urls.py | benjamin0/how-do-you-like-them-apples | 0 | 73116 | from django.conf.urls import patterns, include, url
from django.contrib import admin
urlpatterns = patterns('',
# Examples:
url(r'^admin/', include(admin.site.urls)),
url(r'^grappelli/', include('grappelli.urls')), # grappelli URLS
url(r'^calls/$', 'calls.views.call'),
)
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] |
pyaction/__init__.py | a-maliarov/pyaction | 9 | 155831 | <gh_stars>1-10
# -*- coding: utf-8 -*-
"""
pyaction
~~~~~~~~
PyAction is a module dedicated to eliminate rewriting the same code from
project to project by providing a set of tools according to specific python
fields.
Library hierarchy (this must be set and be followed in any case):
pyaction/
field_name/
__init__.py
objects.py
utils.py
Rules:
1. An __init__ file within a field folder should provide a short description
of the field and contain imports of the main objects within this field to be
operated by the end user.
2. The file called "objects.py" should contain all the main objects of the
field to be used by the end user.
3. The file called "utils.py" should contain all the utilities to be used by
the "objects.py" and not the end user.
4. The file called "exceptions.py" should contain all the exceptions to be
used by both developers and the end users.
"""
from .general import *
from .multiprocessing_ import *
from .datetime_ import *
from .beautifulsoup_ import *
#-----------------------------------------------------------------------------
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] |
src/16/16204.py | youngdaLee/Baekjoon | 11 | 86138 | """
16204. 카드 뽑기
작성자: xCrypt0r
언어: Python 3
사용 메모리: 29,380 KB
소요 시간: 76 ms
해결 날짜: 2020년 9월 13일
"""
def main():
N, M, K = map(int, input().split())
print(min(M, K) - max(M, K) + N)
if __name__ == '__main__':
main()
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] |
src/pythonScripts/DrivePart/download.py | sahilbest999/FVS-GIT-CLONE | 0 | 25705 | <reponame>sahilbest999/FVS-GIT-CLONE
import pickle
import os
import re
import io
import response
import upload
import authenticate
from googleapiclient.errors import HttpError
from googleapiclient.discovery import build
from google_auth_oauthlib.flow import InstalledAppFlow
from google.auth.transport.requests import Request
from googleapiclient.http import MediaIoBaseDownload
import requests
from tqdm import tqdm
from tabulate import tabulate
import re
def download(file_id, destination, saveName="", service=authenticate.get_gdrive_service()):
if not os.path.exists(destination):
print(f"DESTINATION {destination} not found")
return 0
try:
file = service.files().get(fileId=file_id, fields="name, size, mimeType").execute()
print(file)
except HttpError as e:
# print(e.content)
err_code = int(e.resp['status'])
print("Error Code ", err_code)
if err_code == 404:
print(f"FILE WITH ID {file_id} NOT FOUND")
return 0
if not saveName:
saveName = file['name']
mime = file['mimeType']
if mime == 'application/vnd.google-apps.document' or mime == 'application/vnd.google-apps.spreadsheet' or mime == 'application/vnd.google-apps.presentation':
if downloadGsuit(file_id, destination, saveName, mime, service) == 1:
return 1
else: return 0
if not os.path.splitext(file['name'])[1]:
saveName += resolveExtension(file['mimeType'])
print("Save name->",saveName)
request = service.files().get_media(fileId = file_id)
fh = io.BytesIO()
downloader = MediaIoBaseDownload(fh, request)
done = False
while not done:
status, done = downloader.next_chunk()
print(f"Download {int(status.progress()*100)}")
fh.seek(0)
# destination = os.path.join(destination, saveName)
destination += saveName
newPath = checkFileAlreadyExists(destination)
print(type(newPath))
print("New File Destination -> ", newPath)
with open(newPath, "wb") as f:
f.write(fh.read())
f.close()
return 1
def checkFileAlreadyExists(path, i=1, iter=0):
if os.path.exists(path):
if iter == 0:
pos = len(path) - 1 - path[::-1].find('.')
new = path[:pos] + "("+str(i)+")" + path[pos:]
else:
pos = len(path) - 3 - path[::-1].find('.')
new = path[:pos] + str(i) + path[pos+1:]
if(os.path.exists(new)):
i+=1
iter+=1
return checkFileAlreadyExists(new, i, iter)
else:
print("Returned Value", new)
return new
else:
print("Returned Value", path)
return path
def downloadGsuit(file_id, destination, saveName, mime, service):
print("IT IS A Gsuit Document")
newMime={
"application/vnd.google-apps.document": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
"application/vnd.google-apps.spreadsheet": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
"application/vnd.google-apps.presentation": "application/vnd.openxmlformats-officedocument.presentationml.presentation",
}[mime]
request = service.files().export_media(fileId=file_id, mimeType=newMime)
fh = io.BytesIO()
downloader = MediaIoBaseDownload(fh, request)
done = False
while not done:
status, done = downloader.next_chunk()
print(f"Dowloaded {int(status.progress()*100)}")
fh.seek(0)
if not os.path.splitext(saveName)[1]:
saveName += resolveExtension(mime)
destination += saveName
destination = checkFileAlreadyExists(destination)
print(destination)
with open(destination, "wb") as f:
f.write(fh.read())
f.close()
return 1
def resolveExtension(mimeType):
return {
"audio/aac": ".aac",
"application/x-abiword": ".abw",
"application/x-freearc": ".arc",
"video/x-msvideo": ".avi",
"application/vnd.amazon.ebook": ".azw",
"application/octet-stream": ".bin",
"image/bmp": ".bmp",
"application/x-bzip": ".bz",
"application/x-bzip2": ".bz2",
"application/x-csh": ".csh",
"text/css": ".css",
"text/csv": ".csv",
"application/msword": ".doc",
"application/vnd.openxmlformats-officedocument.wordprocessingml.document": ".docx",
"application/vnd.ms-fontobject": ".eot",
"application/epub+zip": ".epub",
"application/gzip": ".gz",
"image/gif": ".gif",
"text/html": ".html",
"image/vnd.microsoft.icon": ".ico",
"text/calendar": ".ics",
"application/java-archive": ".jar",
"image/jpeg": ".jpg",
"text/javascript": ".js",
"application/json": ".json",
"application/ld+json": ".jsonld",
"audio/midi audio/x-midi": ".mid",
"text/javascript": ".mjs",
"audio/mpeg": ".mp3",
"video/mpeg": ".mpeg",
"application/vnd.apple.installer+xml": ".mpkg",
"application/vnd.oasis.opendocument.presentation": ".odp",
"application/vnd.oasis.opendocument.spreadsheet": ".ods",
"application/vnd.oasis.opendocument.text": ".odt",
"audio/ogg": ".oga",
"video/ogg": ".ogv",
"application/ogg": ".ogx",
"audio/opus": ".opus",
"font/otf": ".otf",
"image/png": ".png",
"application/pdf": ".pdf",
"application/x-httpd-php": ".php",
"application/vnd.ms-powerpoint": ".ppt",
"application/vnd.openxmlformats-officedocument.presentationml.presentation": ".pptx",
"application/vnd.rar": ".rar",
"application/rtf": ".rtf",
"application/x-sh": ".sh",
"image/svg+xml": ".svg",
"application/x-shockwave-flash": ".swf",
"application/x-tar": ".tar",
"image/tiff": ".tif.tiff",
"video/mp2t": ".ts",
"font/ttf": ".ttf",
"text/plain": ".txt",
"application/vnd.visio": ".vsd",
"audio/wav": ".wav",
"audio/webm": ".weba",
"video/webm": ".webm",
"image/webp": ".webp",
"font/woff": ".woff",
"font/woff2": ".woff2",
"application/xhtml+xml": ".xhtml",
"application/vnd.ms-excel": ".xls",
"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet": ".xlsx",
"application/xml": "xml",
"application/vnd.mozilla.xul+xml": ".xul",
"application/zip": ".zip",
"video/3gpp": ".3gp",
"video/3gpp2": ".3g2",
"application/x-7z-compressed": ".7z",
"application/vnd.google-apps.document": ".docx",
"application/vnd.google-apps.spreadsheet": ".xlsx",
"application/vnd.google-apps.presentation": ".pptx",
}[mimeType]
download("1ikrvmXBcn_ZeXR3a8A6bdSQb_PG0DXGK", "/home/uttkarsh/Pictures/Test/ht/")
#MIME TYPE:-
# google doc - application/vnd.google-apps.document
# google sheets - application/vnd.google-apps.spreadsheet
# google slides - application/vnd.google-apps.presentation
# normalFile - 1FlMtPenfHeB5GyLHwKKmrQ9omla2kk-R ------------ working
# docs - 1TLvU8TSmHONcQttjnvufVeMhr83z-FrHOhexHNdJM-Q ------------ working
# sheets - 1D6h9YFmZCdjY8WryicXODjOqSoHuJdjYBhH8DeKkn-A ------------ working
# slides - 1Eg2BjGuZG15mu-Rd_e0mZVlVv6nD9IxbVORu0KzQucU ------------ working
# folder - 1ggGA6H5ztS5IdgRxMAiQxhzDdFDSLh2A ------------ ask
# photo - 1XKNBHQG-Alq1m3kypPq0d0s9WBvvmpgV ------------ working
# video - 1ikrvmXBcn_ZeXR3a8A6bdSQb_PG0DXGK ------------ working
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AHCraft/crafter.py | Saad888/AutoHotCraft | 3 | 125423 | import time
from AHKManager import AHKManager
class Crafter:
def __init__(self, AHKObj):
""" This loop will run the expected sequence of actions required
to craft based on requested parameters"""
# Parameters for system
self.user_inturrupt = False
self.script = AHKObj
def update(self, macros, food, pot, confirm, window, escape, settings,
UIUpdate):
""" Update all keybinds internally
macros: list of tuple (hotkey: str, timer: int)
food: tuple (hotkey: str, remaining: int, timer: int)
pot: tuple (hotkey: str, remaining: int)
confirm: str with hotkey
window: str with crafting window hotkey
settings: Tuple of three Bol values:
(use_food, use_pot, use_collect)
UIUpdate: Callback function to place message on UI
"""
# Counters:
self.craft_count = 1
self.total_time = 0
self.food_used = 0
self.pots_used = 0
self.macros = macros
self.use_food, self.use_pot, self.use_collect = settings
self.hk_food = food[0] if self.use_food else None
self.food_remains = food[1] if self.use_food else None
self.food_timer = food[2] if self.use_food else None
self.hk_pot = pot[0] if self.use_pot else None
self.pot_remains = pot[1] if self.use_pot else None
self.pot_timer = 15
self.hk_craft = window
self.hk_confirm = confirm
self.hk_escape = escape
# Sequences Update:
self.sq_craft = []
for macro in self.macros:
self.sq_craft.append((macro[0], macro[1] + 1)) # Add 1 second buffer
# Start the craft
self.sq_begin_craft = [
(self.hk_confirm, 1),
(self.hk_confirm, 1),
(self.hk_confirm, 2)
]
# End Craft (from end of craft)
self.sq_end_craft = []
if self.use_collect:
self.sq_end_craft.append((confirm, 1))
self.sq_end_craft.append((confirm, 3))
# Exit Craft (from crafting window)
self.sq_exit_craft = [
(self.hk_escape, 2)
]
# Food and pots
self.sq_food = [(self.hk_food, 4)]
self.sq_pot = [(self.hk_pot, 3)]
# Restart Craft
self.sq_restart_craft = [
(self.hk_craft, 1),
(self.hk_confirm, 1),
(self.hk_confirm, 1),
(self.hk_confirm, 1),
(self.hk_confirm, 2)
]
self.UI_update = UIUpdate
def start(self, args):
""" Updates parameters and Begins separate thread for crafting loop """
self.update(*args)
self.mainloop()
def mainloop(self):
""" Runs the main crafting loop """
loop_time = time.perf_counter()
loop_start = loop_time
self.user_inturrupt = False
food_remains = self.food_remains * 60 if self.use_food else None
pot_remains = self.pot_remains * 60 if self.use_pot else None
refresh_food, refresh_pot = False, False
macro_time = 0
for macro in self.macros:
macro_time += macro[1]
while self.user_inturrupt is False:
# Main looper
sequence = []
sequence += self.macros # Add crafting macros to sequence
sequence += self.sq_end_craft
UI_text = f"Craft number {self.craft_count} ...\n"
# Sets food timers
# If food or pots need to be refreshed, do so, else start next craft
if self.use_food:
food_remains -= (time.perf_counter() - loop_time)
refresh_food = food_remains - (macro_time + 15) < 60
UI_text += f'Food: ~{food_remains / 60:0.2f} min remains'
UI_text += ', refreshing after craft' if refresh_food else ''
UI_text += '\n'
if self.use_pot:
pot_remains -= (time.perf_counter() - loop_time)
refresh_pot = pot_remains - (macro_time + 15) < 60
UI_text += f'Pot: ~{pot_remains / 60:0.2f} min remains'
UI_text += ', refreshing after craft' if refresh_pot else ''
UI_text += '\n'
if refresh_food or refresh_pot:
sequence += self.sq_exit_craft
if refresh_food:
sequence += self.sq_food
food_remains = self.food_timer * 60 + macro_time
if refresh_pot:
sequence += self.sq_pot
pot_remains = self.pot_timer * 60 + macro_time
sequence += self.sq_restart_craft
else:
sequence += self.sq_begin_craft
loop_time = time.perf_counter()
self.UI_update(UI_text)
self.run_sequence(sequence)
self.total_time = time.perf_counter() - loop_start
if self.user_inturrupt is False:
self.craft_count += 1
self.food_used += 1 if refresh_food else 0
self.pots_used += 1 if refresh_pot else 0
if self.user_inturrupt is True:
mins = int(self.total_time / 60)
secs = int(self.total_time - (mins * 60))
UI_text = f"{self.craft_count} crafts complete "
UI_text += f"in {mins}:{secs:02d} minutes\n"
if self.use_food:
UI_text += f"{self.food_used} food consumed\n"
if self.use_pot:
UI_text += f"{self.pots_used} pots consumed\n"
self.UI_update(UI_text)
def run_sequence(self, sequence):
""" Runs the sequence, provided in a list in the form (hotkey, timer)"""
for hotkey, wait in sequence:
print(f'Execute {hotkey} with delay {wait}s')
self.script.execute(hotkey)
for i in range(wait):
time.sleep(1)
if self.user_inturrupt is True:
break
if self.user_inturrupt is True:
break
if __name__ == "__main__":
print('Starting test')
AHK = AHKManager("C:\\Program Files\\AutoHotkey\\AutoHotkey.exe")
tester = Crafter(AHK)
tester.start(
macros=[("{1}", 3), ("{2}", 3), ("{3}", 3)],
food=None,
pot=None,
confirm='{C}',
window='{W}',
settings=(False, False, False)
)
""" Update all keybinds internally
macros: list of tuple (hotkey: str, timer: int)
food: tuple (hotkey: str, remaining: int, timer: int)
pot: tuple (hotkey: str, remaining: int)
confirm: str with hotkey
window: str with crafting window hotkey
settings: Tuple of three Bol values:
(use_food, use_pot, use_collect)
""" | [
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] |
sources/trmm/arcpy_trmm_custom_raster.py | SERVIR/ReferenceNode_ETL | 0 | 118334 | # Developer: SpatialDev
# Company: Spatial Development International
# standard library
import os
import sys
from datetime import datetime, timedelta
# third-party
from arcpy.sa import *
import arcpy
class TRMMCustomRasterRequest:
""" encapsulates a request to the TRMMCustomRasterCreator to create a custom raster from the TRMM raster catalog.
request_options <dict>: contains the following additional options:
factory_specifications <dict>: options for the output raster
'output_raster_fullpath' <str>: the fullpath and name of the output raster
'clip_extent' <str>: the processing extent contained within "-180.0 -50.0 180.0 50.0" and given in the same format "xMin yMin xMax yMax"
'clip_raster' <arcpy.Raster>: the fullpath to a raster to be used in clipping the TRMM output raster using arcpy.Clip_management
'CopyRaster_management_config' <dict>: config for arcpy.CopyRaster_Management
'AddColormap_management_config' <dict>: config for arcpy.AddColormap_management
input_raster_catalog_options <dict>: options for the input raster catalog
'raster_catalog_fullpath' <str>: fullpath to the source raster catalog
"raster_name_field" <str>: the field in the raster catalog that contains the names of the rasters
"datetime_field" <str>: the field in the raster catalog that contains the datetime for the rasters
'datetime_sql_cast' <str>: the DATETIME cast expression based on the underlying SQL type ex: "date"
'datetime_field_format' <str>: the format of the given datetime_field. ex: '%m-%d-%Y %I:%M:%S %p',
'start_datetime' <str>: the start datetime given in the format %Y%m%d%H with 'h' being a 24-hour. ex: "2012-02-29 at 3PM == 201202291500"
'end_datetime' <str>: the end datetime given in the format %Y%m%d%H with 'h' being a 24-hour. ex: "2012-02-29 at 3PM == 201202291500"
"""
def __init__(self, request_options):
self.factory_specifications = request_options['factory_specifications']
self.input_raster_catalog_options = request_options['input_raster_catalog_options']
self.debug_logger = request_options.get('debug_logger',lambda*a,**kwa:None)
self.exception_handler = request_options.get('exception_handler',lambda*a,**kwa:None)
def getFactorySpecifications(self):
return self.factory_specifications
def getRasterCatalogFullpath(self):
return self.input_raster_catalog_options['raster_catalog_fullpath']
def extractRastersToWorkspace(self, path_to_extract_into):
try:
rasters_to_extract_list = self._getListOfRasterNamesFromRasterCatalog()
extracted_rasters_list = self._extractRastersFromRasterCatalog(rasters_to_extract_list, path_to_extract_into)
return extracted_rasters_list
except Exception as e:
self.debug_logger("==================== EXCEPTION (extractRastersToWorkspace) ====================")
self.debug_logger(str(e), str(arcpy.GetMessages(2)))
self.exception_handler(dict(exception=str(e), messages=str(arcpy.GetMessages(2))))
def _getListOfRasterNamesFromRasterCatalog(self, additional_where_clause=""):
self.debug_logger("_getListOfRasterNamesFromRasterCatalog()")
raster_name_field = self.input_raster_catalog_options['raster_name_field']
where_clause = self._createWhereClause()
where_clause += self.input_raster_catalog_options.get('additional_where_clause',"")
rows = arcpy.SearchCursor(self.input_raster_catalog_options['raster_catalog_fullpath'], where_clause, "", raster_name_field)
try:
return [str(row.getValue(raster_name_field)) for row in rows]
finally:
del rows
def _createWhereClause(self):
start_datetime = self.input_raster_catalog_options['start_datetime']
end_datetime = self.input_raster_catalog_options['end_datetime']
datetime_field = self.input_raster_catalog_options['datetime_field']
datetime_field_format = self.input_raster_catalog_options['datetime_field_format']
datetime_sql_cast = self.input_raster_catalog_options['datetime_sql_cast']
where_clause = "%s <= %s \'%s\'" % (datetime_field, datetime_sql_cast, start_datetime.strftime(datetime_field_format))
where_clause += " AND %s >= %s \'%s\'" % (datetime_field, datetime_sql_cast, end_datetime.strftime(datetime_field_format))
self.debug_logger("where_clause",where_clause)
return where_clause
def _extractRastersFromRasterCatalog(self, rasters_to_extract_list, path_to_extract_into):
extracted_raster_list = []
joinPath = os.path.join
raster_name_field = self.input_raster_catalog_options['raster_name_field']
output_raster_catalog = self.input_raster_catalog_options['raster_catalog_fullpath']
for raster_name in rasters_to_extract_list:
extracted_raster_fullpath = joinPath(path_to_extract_into, raster_name)
self.debug_logger("processing raster...",raster_name)
if arcpy.Exists(extracted_raster_fullpath) and (raster_name not in extracted_raster_list):
extracted_raster_list.append(raster_name)
else:
where_clause = "%s = \'%s\'" % (raster_name_field, str(raster_name))
arcpy.RasterCatalogToRasterDataset_management(output_raster_catalog, raster_name, where_clause)
extracted_raster_list.append(raster_name)
return extracted_raster_list
class TRMMCustomRasterCreator:
"""creates a custom raster from a given TRMMCustomRasterRequest object.
raster_creator_options <dict>: config options for the TRMM raster creator.
'workspace_fullpath' <str>: output workspace location for the raster creation process
'remove_all_rasters_on_finish' <bool>: cleans up all raster output on finish.
'archive_options' <dict>: local extracted rasters can be kept in the workspace to allow for faster processing in future runs
'raster_name_prefix' <str>: given to differentiate between extracted rasters when deleting ex: "t_"
'local_raster_archive_days' <int>: rasters outside this number will be deleted ex: 90
'raster_name_datetime_format' <str>: to determine if a raster is outside the archive days,
each name must be in an easily convertable datetime string format. ex: "t_%Y%m%d%H"
'debug_logger' <object.method>: method that will be passes variable string arguments to display current progress and values
'exception_handler' <object.method>: method that will be variable string arguments with exception information
"""
def __init__(self, raster_creator_options):
self.raster_creator_options = raster_creator_options
self.workspace_fullpath = raster_creator_options['workspace_fullpath']
self.custom_raster_requests = []
if not os.path.isdir(self.workspace_fullpath):
os.mkdir(self.workspace_fullpath)
self.debug_logger = raster_creator_options.get('debug_logger',lambda*a,**kwa:None)
self.exception_handler = raster_creator_options.get('exception_handler',lambda*a,**kwa:None)
def addCustomRasterReuests(self, custom_raster_requests):
self.custom_raster_requests = custom_raster_requests
def createCustomRasters(self):
self.debug_logger("Starting TRMM Custom Raster Creation Process")
try:
arcpy.env.extent = arcpy.Extent(-180.0, -50.0, 180.0, 50.0) # max and min extent values a given TRMM raster
arcpy.env.workspace = self.workspace_fullpath
arcpy.env.overwriteOutput = True
arcpy.CheckOutExtension("spatial")
for custom_raster in self.custom_raster_requests:
self.debug_logger("Processing Raster")
factory_specifications = custom_raster.getFactorySpecifications()
output_raster_fullpath = factory_specifications['output_raster_fullpath']
raster_catalog_is_not_locked = arcpy.TestSchemaLock(custom_raster.getRasterCatalogFullpath())
extracted_raster_list = custom_raster.extractRastersToWorkspace(self.workspace_fullpath)
self.debug_logger("Len(extracted_raster_list)", len(extracted_raster_list))
if extracted_raster_list and raster_catalog_is_not_locked:
final_raster = self._createCumulativeRaster(extracted_raster_list, factory_specifications)
self._saveRaster(final_raster, output_raster_fullpath, factory_specifications)
self._finishCustomRasterManagment()
self.debug_logger("Finished TRMM Custom Raster Creation Process")
except Exception as e:
self.debug_logger("==================== EXCEPTION (createCustomRasters) ====================")
self.debug_logger(str(e), str(arcpy.GetMessages(2)))
self.exception_handler(dict(exception=str(e), messages=str(arcpy.GetMessages(2))))
finally:
arcpy.CheckInExtension("spatial")
self.debug_logger("checked IN spatial extension")
def _createCumulativeRaster(self, rasters_list, factory_specifications):
self.debug_logger("Creating Cumulative Raster...")
final_raster = sum([Con(IsNull(raster), 0, raster) for raster in rasters_list]) # for each raster in the list, set all NULL to 0 then SUM
final_raster = Float(final_raster)
final_raster = final_raster * 3 # multiply by 3 since each TRMM raster 3-hour period is an average not a sum
if factory_specifications.get('clip_extent', None):
self.debug_logger("Adding Clip Extent...")
output_clip_raster = os.path.join(os.path.join(sys.path[0], "scratch.gdb"),"temp_clip")
final_raster = arcpy.Clip_management(final_raster, factory_specifications['clip_extent'], output_clip_raster)
elif factory_specifications.get('clip_raster', None):
self.debug_logger("Adding Clip Raster...")
final_raster = final_raster * Raster(factory_specifications['clip_raster'])
final_raster = SetNull(final_raster == 0, final_raster) # set 0's back to NULL after all mathematical operations are peformed
self.debug_logger("SetNull(final_raster == 0, final_raster)")
return final_raster
def _saveRaster(self, raster_to_save, output_raster_fullpath, factory_specifications):
self.debug_logger("Saving Final Raster")
if factory_specifications.get('AddColormap_management_config', None):
self.debug_logger("Adding Color Map...")
color_map_config = factory_specifications['AddColormap_management_config']
r = arcpy.AddColormap_management(raster_to_save, color_map_config.get('in_template_raster',''), color_map_config['input_CLR_file'])
self.debug_logger("AddColormap_management Result", r.status)
raster_name = os.path.basename(output_raster_fullpath)
raster_to_save.save(raster_name)
local_raster_fullpath = os.path.join(self.workspace_fullpath, raster_name)
self.debug_logger("local_raster_fullpath",local_raster_fullpath)
self.debug_logger("output_raster_fullpath",output_raster_fullpath)
self._removeExistingRasterIfExists(output_raster_fullpath)
self._copyRaster(factory_specifications['CopyRaster_management_config'], local_raster_fullpath, output_raster_fullpath)
self._removeExistingRasterIfExists(local_raster_fullpath)
def _copyRaster(self, copy_raster_managment_config, local_raster_fullpath, output_raster_fullpath):
self.debug_logger("Copying Raster...", output_raster_fullpath)
r = arcpy.CopyRaster_management(local_raster_fullpath, output_raster_fullpath,
copy_raster_managment_config.get('config_keyword',''), copy_raster_managment_config.get('background_value',''),
copy_raster_managment_config.get('nodata_value',''), copy_raster_managment_config.get('onebit_to_eightbit',''),
copy_raster_managment_config.get('colormap_to_RGB',''), copy_raster_managment_config.get('pixel_type','')
)
self.debug_logger("CopyRaster_management Result", r.status)
def _removeExistingRasterIfExists(self, output_raster_fullpath):
if arcpy.Exists(output_raster_fullpath):
self.debug_logger("Deleting...", output_raster_fullpath)
r = arcpy.Delete_management(output_raster_fullpath)
self.debug_logger("Delete_management Result", r.status)
def _finishCustomRasterManagment(self):
self.debug_logger("Finishing Custom Raster Creation")
archive_options = self.raster_creator_options.get('archive_options', None)
remove_all_rasters_on_finish = self.raster_creator_options.get('remove_all_rasters_on_finish', False)
if archive_options and not remove_all_rasters_on_finish:
raster_name_prefix = archive_options.get('raster_name_prefix', None)
archive_days = archive_options.get('local_raster_archive_days', None)
raster_name_datetime_format = archive_options.get('raster_name_datetime_format', None)
if (raster_name_prefix and archive_days and raster_name_datetime_format):
archive_date = datetime.utcnow() - timedelta(days=archive_days)
local_raster_list = [r for r in arcpy.ListRasters(raster_name_prefix+"*","*") if str(r[:len(raster_name_prefix)]).lower() == str(raster_name_prefix)]
list_of_rasters_to_delete = [raster for raster in local_raster_list if datetime.strptime(str(raster), raster_name_datetime_format) < archive_date]
self._deleteRasters(list_of_rasters_to_delete)
elif remove_all_rasters_on_finish:
self.debug_logger("Removing All Rasters In Local Workspace...")
self._deleteRasters(arcpy.ListRasters("*"))
def _deleteRasters(self, list_of_rasters_to_delete):
for r in list_of_rasters_to_delete:
arcpy.Delete_management(r) | [
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] |
reader_model.py | ranjeethmahankali/BIMToVec | 0 | 128808 | from ops import *
import math
import random
ATOM_NUM = 5
ATOM_SIZE = 32
WORD_SIZE = 64
WORD_SAMPLE_SIZE = 20
ALPHABET = list("abcdefghijklmnopqrstuvwxyz")
EMBEDDINGS = loadFromFile("savedEmbeddings/embeddings.pkl")
EMBEDDING_TENSOR = tf.constant(value=EMBEDDINGS, dtype=tf.float32)
def get_char_list_vec(word):
chars = ""
if len(word) < WORD_SAMPLE_SIZE:
while len(chars) < WORD_SAMPLE_SIZE:
chars += word
if len(chars) > WORD_SAMPLE_SIZE:
chars = chars[:WORD_SAMPLE_SIZE]
# print(chars)
else:
chars = random.sample(list(word), WORD_SAMPLE_SIZE)
vec = []
for ch in chars:
vec += [(ALPHABET.index(ch)+1)/len(ALPHABET)]
return np.reshape(np.array(vec),[1,-1])
LAYERS = [(ATOM_NUM*ATOM_SIZE)+WORD_SAMPLE_SIZE, 640, 1280, 1536, 1280, 640, WORD_SIZE]
with tf.variable_scope("vars"):
weights = [
weightVariable([LAYERS[i], LAYERS[i+1]], name="w%s"%i) for i in range(len(LAYERS)-1)
]
biases = [
biasVariable([LAYERS[i+1]], name="b%s"%i) for i in range(len(LAYERS)-1)
]
atoms_placeholder = tf.placeholder(shape=[None, (ATOM_NUM*ATOM_SIZE)+WORD_SAMPLE_SIZE],
dtype = tf.float32, name="atoms")
word_true = tf.placeholder(shape=[None], dtype = tf.int64, name="word_true_index")
keep_prob = tf.placeholder(tf.float32, name = "keep_prob")
h = 0
for i in range(len(weights)):
L = atoms_placeholder if i == 0 else h
h = tf.matmul(L, weights[i])+biases[i]
h = tf.nn.tanh(h) if i == len(weights)-1 else tf.nn.relu(h)
if i == len(weights)-2:
h = tf.nn.dropout(h, keep_prob)
norm = tf.sqrt(tf.reduce_sum(tf.square(h), axis=1, keep_dims=True))
embed_predict = (h/norm)
similarity_predict = tf.matmul(embed_predict, tf.transpose(EMBEDDING_TENSOR))
sim_predict_norm = (1+tf.clip_by_value(similarity_predict, 0.01, math.inf))/2
prediction = tf.argmax(similarity_predict,axis=1)
embed_true = tf.nn.embedding_lookup(EMBEDDING_TENSOR, word_true)
similarity = tf.matmul(embed_true, tf.transpose(EMBEDDING_TENSOR))
sim_norm = (1+similarity)/2
cross_entropy = tf.reduce_mean(-tf.reduce_sum(sim_norm * tf.log(sim_predict_norm), 1))
diff_loss = tf.reduce_mean(tf.reduce_sum(tf.square(embed_predict-embed_true)))
tf.summary.scalar("cross_entropy", cross_entropy)
tf.summary.scalar("diff_loss", diff_loss)
# all_vars = tf.trainable_variables()
# vars = [v for v in all_vars if 'vars' in v.name]
# l2_loss = 0
# for v in vars:
# l2_loss += alpha*tf.nn.l2_loss(v)
#
# tf.summary.scalar("l2_loss", l2_loss)
# pred_word_index = tf.nn.embedding_lookup(EMBEDDING_TENSOR, prediction)
accuracy = 100*tf.reduce_mean(tf.cast(tf.equal(prediction, word_true),tf.float32))
# optim = tf.train.AdamOptimizer(learning_rate).minimize(cross_entropy+l2_loss-accuracy)
# optim = tf.train.GradientDescentOptimizer(0.1).minimize(cross_entropy-accuracy)
# optim = tf.train.AdamOptimizer(learning_rate).minimize(cross_entropy+l2_loss-accuracy)
optim = tf.train.AdamOptimizer(learning_rate).minimize((cross_entropy/15)+diff_loss - accuracy) | [
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searx/searx/engines/bing_videos.py | wgranados/quadbot | 3 | 106689 | """
Bing (Videos)
@website https://www.bing.com/videos
@provide-api yes (http://datamarket.azure.com/dataset/bing/search)
@using-api no
@results HTML
@stable no
@parse url, title, content, thumbnail
"""
from json import loads
from lxml import html
from searx.engines.bing_images import _fetch_supported_languages, supported_languages_url
from searx.engines.xpath import extract_text
from searx.url_utils import urlencode
from searx.utils import match_language
categories = ['videos']
paging = True
safesearch = True
time_range_support = True
number_of_results = 10
language_support = True
search_url = 'https://www.bing.com/videos/asyncv2?{query}&async=content&'\
'first={offset}&count={number_of_results}&CW=1366&CH=25&FORM=R5VR5'
time_range_string = '&qft=+filterui:videoage-lt{interval}'
time_range_dict = {'day': '1440',
'week': '10080',
'month': '43200',
'year': '525600'}
# safesearch definitions
safesearch_types = {2: 'STRICT',
1: 'DEMOTE',
0: 'OFF'}
# do search-request
def request(query, params):
offset = (params['pageno'] - 1) * 10 + 1
# safesearch cookie
params['cookies']['SRCHHPGUSR'] = \
'ADLT=' + safesearch_types.get(params['safesearch'], 'DEMOTE')
# language cookie
language = match_language(params['language'], supported_languages, language_aliases).lower()
params['cookies']['_EDGE_S'] = 'mkt=' + language + '&F=1'
# query and paging
params['url'] = search_url.format(query=urlencode({'q': query}),
offset=offset,
number_of_results=number_of_results)
# time range
if params['time_range'] in time_range_dict:
params['url'] += time_range_string.format(interval=time_range_dict[params['time_range']])
return params
# get response from search-request
def response(resp):
results = []
dom = html.fromstring(resp.text)
for result in dom.xpath('//div[@class="dg_u"]'):
url = result.xpath('./div[@class="mc_vtvc"]/a/@href')[0]
url = 'https://bing.com' + url
title = extract_text(result.xpath('./div/a/div/div[@class="mc_vtvc_title"]/@title'))
content = extract_text(result.xpath('./div/a/div/div/div/div/text()'))
thumbnail = result.xpath('./div/a/div/div/img/@src')[0]
results.append({'url': url,
'title': title,
'content': content,
'thumbnail': thumbnail,
'template': 'videos.html'})
if len(results) >= number_of_results:
break
return results
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src/core/widgets/komorebi/active_layout.py | younger-1/yasb | 53 | 151252 | import logging
from collections import deque
from PyQt6.QtWidgets import QWidget, QLabel
from PyQt6.QtCore import pyqtSignal
from core.utils.win32.utilities import get_monitor_hwnd
from core.event_service import EventService
from core.event_enums import KomorebiEvent
from core.widgets.base import BaseWidget
from core.utils.komorebi.client import KomorebiClient
from core.validation.widgets.komorebi.active_layout import VALIDATION_SCHEMA
try:
from core.utils.komorebi.event_listener import KomorebiEventListener
except ImportError:
KomorebiEventListener = None
logging.warning("Failed to load Komorebi Event Listener")
layout_cmds = {
"BSP": "bsp",
"Columns": "columns",
"Rows": "rows",
"VerticalStack": "vertical-stack",
"HorizontalStack": "horizontal-stack",
"UltrawideVerticalStack": "ultrawide-vertical-stack"
}
layout_snake_case = {
"BSP": "bsp",
"Columns": "columns",
"Rows": "rows",
"VerticalStack": "vertical_stack",
"HorizontalStack": "horizontal_stack",
"UltrawideVerticalStack": "ultrawide_vertical_stack"
}
class ActiveLayoutWidget(BaseWidget):
k_signal_connect = pyqtSignal(dict)
k_signal_disconnect = pyqtSignal()
k_signal_layout_change = pyqtSignal(dict, dict)
validation_schema = VALIDATION_SCHEMA
event_listener = KomorebiEventListener
def __init__(self, label: str, layout_icons: dict[str, str], hide_if_offline: bool, callbacks: dict[str, str]):
super().__init__(class_name="komorebi-active-layout")
self._label = label
self._layout_icons = layout_icons
self._layouts = deque([
'bsp', 'columns', 'rows', 'vertical-stack', 'horizontal-stack', 'ultrawide-vertical-stack'
])
self._hide_if_offline = hide_if_offline
self._event_service = EventService()
self._komorebic = KomorebiClient()
self._komorebi_screen = None
self._komorebi_workspaces = []
self._focused_workspace = {}
self._active_layout_text = QLabel()
self._active_layout_text.setProperty("class", "label")
self._active_layout_text.hide()
self.widget_layout.addWidget(self._active_layout_text)
self.callback_left = callbacks['on_left']
self.callback_right = callbacks['on_right']
self.callback_middle = callbacks['on_middle']
self.register_callback("next_layout", self._next_layout)
self.register_callback("prev_layout", self._prev_layout)
self.register_callback("flip_layout", self._komorebic.flip_layout)
self.register_callback("toggle_tiling", lambda: self._komorebic.toggle("tiling"))
self.register_callback("toggle_float", lambda: self._komorebic.toggle("float"))
self.register_callback("toggle_monocle", lambda: self._komorebic.toggle("monocle"))
self.register_callback("toggle_maximise", lambda: self._komorebic.toggle("maximise"))
self.register_callback("toggle_pause", lambda: self._komorebic.toggle("pause"))
self._register_signals_and_events()
def _next_layout(self):
if self._is_shift_layout_allowed():
self._layouts.rotate(1)
self._komorebic.change_layout(self._layouts[0])
def _prev_layout(self):
if self._is_shift_layout_allowed():
self._layouts.rotate(-1)
self._komorebic.change_layout(self._layouts[0])
def _is_shift_layout_allowed(self):
return not bool(
not self._focused_workspace.get('tile', False) or
self._focused_workspace.get('monocle_container', None) or
self._focused_workspace.get('maximized_window', None) or
self._komorebi_state.get('is_paused', False)
)
def _register_signals_and_events(self):
active_layout_change_event_watchlist = [
KomorebiEvent.ChangeLayout,
KomorebiEvent.TogglePause,
KomorebiEvent.ToggleTiling,
KomorebiEvent.ToggleMonocle,
KomorebiEvent.ToggleMaximise
]
self.k_signal_connect.connect(self._on_komorebi_connect_event)
self.k_signal_disconnect.connect(self._on_komorebi_disconnect_event)
self.k_signal_layout_change.connect(self._on_komorebi_layout_change_event)
self._event_service.register_event(KomorebiEvent.KomorebiConnect, self.k_signal_connect)
self._event_service.register_event(KomorebiEvent.KomorebiDisconnect, self.k_signal_disconnect)
for event_type in active_layout_change_event_watchlist:
self._event_service.register_event(event_type, self.k_signal_layout_change)
def _on_komorebi_connect_event(self, state: dict) -> None:
self._update_active_layout(state, is_connect_event=True)
def _on_komorebi_layout_change_event(self, _event: dict, state: dict) -> None:
self._update_active_layout(state)
def _on_komorebi_disconnect_event(self) -> None:
if self._hide_if_offline:
self._active_layout_text.hide()
def _update_active_layout(self, state: dict, is_connect_event=False):
try:
if self._update_komorebi_state(state):
self._focused_workspace = self._komorebic.get_focused_workspace(self._komorebi_screen)
if not self._focused_workspace:
return
layout_name, layout_icon = self._get_layout_label_info()
if is_connect_event:
conn_layout_name = self._focused_workspace['layout']['Default']
conn_layout_cmd = layout_cmds.get(conn_layout_name, 'bsp')
while self._layouts[0] != conn_layout_cmd:
self._layouts.rotate(1)
self._active_layout_text.setText(
self._label.replace("{icon}", layout_icon).replace("{layout_name}", layout_name)
)
if self._active_layout_text.isHidden():
self._active_layout_text.show()
except Exception:
logging.exception("Failed to update komorebi status and widget button state")
def _get_layout_label_info(self):
if self._komorebi_state.get('is_paused', False):
layout_name = 'Paused'
layout_icon = self._layout_icons['paused']
elif not self._focused_workspace.get('tile', False):
layout_name = 'Floating'
layout_icon = self._layout_icons['floating']
elif self._focused_workspace.get('maximized_window', None):
layout_name = 'Maximised'
layout_icon = self._layout_icons['maximised']
elif self._focused_workspace.get('monocle_container', None):
layout_name = 'Monocle'
layout_icon = self._layout_icons['monocle']
else:
layout_name = self._focused_workspace['layout']['Default']
layout_icon = self._layout_icons.get(layout_snake_case[layout_name], 'unknown layout')
return layout_name, layout_icon
def _update_komorebi_state(self, komorebi_state: dict):
try:
self._screen_hwnd = get_monitor_hwnd(int(QWidget.winId(self)))
self._komorebi_state = komorebi_state
if self._komorebi_state:
self._komorebi_screen = self._komorebic.get_screen_by_hwnd(self._komorebi_state, self._screen_hwnd)
self._komorebi_workspaces = self._komorebic.get_workspaces(self._komorebi_screen)
return True
except TypeError:
return False
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level_18/level_18random.py | hermes-jr/adventofcode-in-python | 0 | 86381 | <filename>level_18/level_18random.py
#!/usr/bin/python
import copy
import random
WIDTH = 70
HEIGHT = 46
STEPS = 1000000
lights = [[0 for x in range(WIDTH)] for x in range(HEIGHT)]
dark = '\x1b[32;40m#\x1b[0m'
bright = '\x1b[32;1m#\x1b[0m'
nocolor = '#'
random.seed()
for i in range(HEIGHT):
for j in range(WIDTH):
lights[i][j] = random.randint(0,1)
nextgen = copy.deepcopy(lights)
def neighbour_vals(x, y):
for i in range(x - 1, x + 2):
for j in range(y - 1, y + 2):
if((i in range(HEIGHT) and j in range(WIDTH)) and (x != i or y != j)): # definitely need some sleep. why the fuck OR works here instead of AND?!
yield lights[i][j]
history = list()
def animate():
global lights
global nextgen
global history
for i in range(HEIGHT):
for j in range(WIDTH):
if( lights[i][j] == 1):
if(sum(neighbour_vals(i, j)) not in (2, 3) ):
nextgen[i][j] = 0
if( lights[i][j] == 0):
if( sum(neighbour_vals(i, j)) == 3 ):
nextgen[i][j] = 1
lights = copy.deepcopy(nextgen)
if(len(history) > 7):
history.pop(0)
if(history[0] == history[6] or history[0] == history[5]):
print("Endless loop detected, I quit.")
quit()
history.append(lights)
for i in range(HEIGHT):
line = ''
for j in range(WIDTH):
if(nextgen[i][j] == 1): line += nocolor
else: line += '.'
print("{0:3d}: {1}".format(i + 1, line))
for i in range(STEPS):
if __debug__: print ("step {0:3d}".format(i + 1))
animate()
print ("original {} lights on ".format( sum(map(sum, lights)) ))
print ("nextgen {} lights on ".format( sum(map(sum, nextgen)) ))
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model-archiver/model_archiver/arg_parser.py | zmhassan/mxnet-model-server | 1 | 178623 | <reponame>zmhassan/mxnet-model-server
# Copyright 2017 Amazon.com, Inc. or its affiliates. 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.
# A copy of the License is located at
# http://www.apache.org/licenses/LICENSE-2.0
# or in the "license" file accompanying this file. This file 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.
"""
This module parses the arguments given through the mxnet-model-server command-line. This is used by model-server
at runtime.
"""
import argparse
import os
from .manifest_components.manifest import RuntimeType
# noinspection PyTypeChecker
class ArgParser(object):
"""
Argument parser for model-export-tool commands
More detailed example is available at https://github.com/awslabs/mxnet-model-server/blob/master/README.md
"""
@staticmethod
def export_model_args_parser():
""" Argument parser for mxnet-model-export
"""
parser_export = argparse.ArgumentParser(prog='model-archiver', description='Model Archiver Tool',
formatter_class=argparse.RawTextHelpFormatter)
parser_export.add_argument('--model-name',
required=True,
type=str,
default=None,
help='Exported model name. Exported file will be named as\n'
'model-name.mar and saved in current working directory if no --export-path is\n'
'specified, else it will be saved under the export path')
parser_export.add_argument('--model-path',
required=True,
type=str,
default=None,
help='Path to the folder containing model related files.')
parser_export.add_argument('--handler',
required=True,
dest="handler",
type=str,
default=None,
help='Handler path to handle custom MMS inference logic.')
parser_export.add_argument('--runtime',
required=False,
type=str,
default=RuntimeType.PYTHON.value,
choices=[s.value for s in RuntimeType],
help='The runtime specifies which language to run your inference code on.\n'
'The default runtime is "python".')
parser_export.add_argument('--export-path',
required=False,
type=str,
default=os.getcwd(),
help='Path where the exported .mar file will be saved. This is an optional\n'
'parameter. If --export-path is not specified, the file will be saved in the\n'
'current working directory. ')
parser_export.add_argument('--archive-format',
required=False,
type=str,
default="default",
choices=["tgz", "no-archive", "default"],
help='The format in which the model artifacts are archived.\n'
'"tgz": This creates the model-archive in <model-name>.tar.gz format.\n'
'If platform hosting MMS requires model-artifacts to be in ".tar.gz"\n'
'use this option.\n'
'"no-archive": This option creates an non-archived version of model artifacts\n'
'at "export-path/{model-name}" location. As a result of this choice, \n'
'MANIFEST file will be created at "export-path/{model-name}" location\n'
'without archiving these model files\n'
'"default": This creates the model-archive in <model-name>.mar format.\n'
'This is the default archiving format. Models archived in this format\n'
'will be readily hostable on native MMS.\n')
parser_export.add_argument('-f', '--force',
required=False,
action='store_true',
help='When the -f or --force flag is specified, an existing .mar file with same\n'
'name as that provided in --model-name in the path specified by --export-path\n'
'will overwritten')
parser_export.add_argument('-c', '--convert',
required=False,
action='store_true',
help='When this option is used, model-archiver looks for special files and tries\n'
'preprocesses them. For example, if this option is chosen when running\n'
'model-archiver tool on a model with ".onnx" extension, the tool will try and\n'
'convert ".onnx" model into an MXNet model.')
return parser_export
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] |
Menu.py | OaksTree1/PyPrac | 0 | 1603765 | from Database.database import dataBase
from Models.Blog import blog
class Menu(object):
def __init__(self):
self.user = raw_input("Enter your username: ")
self.user_have_blog = None
if self._user_account():
print("Welcome Back {user}".format(user = self.user))
else:
self._register_user()
def run_menu(self):
read_or_write = raw_input("Do you want to read (R) or write(W):")
if(read_or_write == "R"):
self._list_blogs()
self._view_blogs()
elif(read_or_write == "W"):
self.user_have_blog.new_post()
else:
print("Thank you for Trying")
def _user_account(self):
blogsearch = dataBase.find_one(collection='Blogs',query= {'author': self.user})
if blogsearch is not None:
self.user_have_blog = blog.From_mongo(blogsearch['id'])
return True
else:
return False
def _register_user(self):
title = raw_input("enter Post title")
description = raw_input("enter post description")
blog_write = blog(author=self.user, title = title, description = description)
blog_write.save_to_mongo()
self.user_have_blog = blog_write
def _list_blogs(self):
AllBlogs = dataBase.find(collection='Blogs', query={})
for dablog in AllBlogs:
print("ID: {id}, :Title: {title}, Author: {author}".format(id = dablog['id'], title = dablog['title'], author = dablog['author']))
def _view_blogs(self):
blog_to_see = raw_input("What is the ID of the blog you want:")
blogsee = blog.From_mongo(blog_to_see)
postsee = blogsee.get_post()
for dapost in postsee:
print("Date: {date}, Title: {title}\n\n{content}".format(date = dapost['date_created'], title = dapost['title'], content = dapost['content']))
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] |
tests/test_tokenizer.py | cd109/scrappybara | 0 | 49489 | <reponame>cd109/scrappybara
import unittest
from scrappybara.preprocessing.tokenizer import Tokenizer
_TOKENIZE = Tokenizer()
class TestTokenizer(unittest.TestCase):
# BLOCKS
# -------------------------------------------------------------------------->
def test_indirect_speech_blocks(self):
self.assertEqual('Well , he said ༺1༻'.split(), _TOKENIZE('Well, he said ༺1༻'))
self.assertEqual('⦅1⦆ Well , he said ༺1༻'.split(), _TOKENIZE('⦅1⦆ Well, he said ༺1༻'))
# SHORT TEXT
# -------------------------------------------------------------------------->
def test_split_special_words(self):
self.assertEqual('I can not do that .'.split(), _TOKENIZE('I cannot do that.'))
self.assertEqual('Can not do that !'.split(), _TOKENIZE('Cannot do that!'))
def test_links(self):
self.assertEqual('domain.com'.split(), _TOKENIZE('domain.com'))
self.assertEqual('Cellucor.com'.split(), _TOKENIZE('Cellucor.com'))
self.assertEqual('DOMAIN.COM'.split(), _TOKENIZE('DOMAIN.COM'))
self.assertEqual('sub.domain.com.au'.split(), _TOKENIZE('sub.domain.com.au'))
self.assertEqual('sub.domain123.com.au'.split(), _TOKENIZE('sub.domain123.com.au'))
self.assertEqual('<EMAIL>'.split(), _TOKENIZE('<EMAIL>'))
self.assertEqual('<EMAIL>'.split(), _TOKENIZE('<EMAIL>'))
self.assertEqual('tacos.pic.twitter.com/Q4usgzGMHq'.split(), _TOKENIZE('tacos.pic.twitter.com/Q4usgzGMHq'))
def test_dots_single_tokens_nosplit(self):
self.assertEqual('a.'.split(), _TOKENIZE('a.'))
self.assertEqual('.end'.split(), _TOKENIZE('.end'))
self.assertEqual('.End'.split(), _TOKENIZE('.End'))
self.assertEqual('1 .'.split(), _TOKENIZE('1.'))
self.assertEqual('.11'.split(), _TOKENIZE('.11'))
self.assertEqual('1.deliver'.split(), _TOKENIZE('1.deliver'))
self.assertEqual('1.Deliver'.split(), _TOKENIZE('1.Deliver'))
self.assertEqual('deliver.1'.split(), _TOKENIZE('deliver.1'))
self.assertEqual('deliveR.1'.split(), _TOKENIZE('deliveR.1'))
self.assertEqual('.deliver'.split(), _TOKENIZE('.deliver'))
self.assertEqual('.Deliver'.split(), _TOKENIZE('.Deliver'))
self.assertEqual('aaa.deliver'.split(), _TOKENIZE('aaa.deliver'))
self.assertEqual('aaA.Deliver'.split(), _TOKENIZE('aaA.Deliver'))
self.assertEqual('$1.3M'.split(), _TOKENIZE('$1.3M'))
self.assertEqual('1.1'.split(), _TOKENIZE('1.1'))
self.assertEqual('123.123'.split(), _TOKENIZE('123.123'))
self.assertEqual('123.123.1'.split(), _TOKENIZE('123.123.1'))
self.assertEqual('1.1.1.1'.split(), _TOKENIZE('1.1.1.1'))
self.assertEqual('A.B.1.C'.split(), _TOKENIZE('A.B.1.C'))
self.assertEqual('A.B.C'.split(), _TOKENIZE('A.B.C'))
self.assertEqual('A.B.C.'.split(), _TOKENIZE('A.B.C.'))
self.assertEqual('e.g.'.split(), _TOKENIZE('e.g.'))
self.assertEqual('e.g'.split(), _TOKENIZE('e.g'))
self.assertEqual('A.A'.split(), _TOKENIZE('A.A'))
self.assertEqual('U.S.'.split(), _TOKENIZE('U.S.'))
self.assertEqual('u.s.'.split(), _TOKENIZE('u.s.'))
self.assertEqual('1.A'.split(), _TOKENIZE('1.A'))
self.assertEqual('A.1'.split(), _TOKENIZE('A.1'))
self.assertEqual('I1.I0I'.split(), _TOKENIZE('I1.I0I'))
self.assertEqual('items.101'.split(), _TOKENIZE('items.101'))
self.assertEqual('items.I0I.A'.split(), _TOKENIZE('items.I0I.A'))
def test_multiple_dots_split(self):
self.assertEqual('a new ... Sentence'.split(), _TOKENIZE('a new... Sentence'))
self.assertEqual('bla ...'.split(), _TOKENIZE('bla...'))
def test_multiple_sentence_enders(self):
self.assertEqual('a new !!! Sentence'.split(), _TOKENIZE('a new!!! Sentence'))
self.assertEqual('a new ?? Sentence'.split(), _TOKENIZE('a new?? Sentence'))
self.assertEqual('a new ??! Sentence'.split(), _TOKENIZE('a new??! Sentence'))
def test_dots_split(self):
self.assertEqual('a new . Sentence'.split(), _TOKENIZE('a new.Sentence'))
self.assertEqual('December 4 . Sentence'.split(), _TOKENIZE('December 4. Sentence'))
self.assertEqual('try mindfulchef.com . And this .'.split(), _TOKENIZE('try mindfulchef.com. And this.'))
self.assertEqual('a new . Sentence'.split(), _TOKENIZE('a new. Sentence'))
self.assertEqual('Fine Arts . She'.split(), _TOKENIZE('Fine Arts. She'))
self.assertEqual('in june 1962 . Blabla'.split(), _TOKENIZE('in june 1962. Blabla'))
self.assertEqual('information etc . SVN , NN'.split(), _TOKENIZE('information etc. SVN, NN'))
def test_dots_nosplit(self):
self.assertEqual('use .NET'.split(), _TOKENIZE('use .NET'))
self.assertEqual('a new.sentence'.split(), _TOKENIZE('a new.sentence'))
self.assertEqual('a new .sentence'.split(), _TOKENIZE('a new .sentence'))
self.assertEqual('a new. sentence'.split(), _TOKENIZE('a new. sentence'))
self.assertEqual('market in 2015. includes'.split(), _TOKENIZE('market in 2015. includes'))
self.assertEqual('the 69th regt. ,'.split(), _TOKENIZE('the 69th regt.,'))
self.assertEqual('the 69th regt. :'.split(), _TOKENIZE('the 69th regt.:'))
self.assertEqual('the 69th regt. ;'.split(), _TOKENIZE('the 69th regt.;'))
self.assertEqual('the 69th regt . )'.split(), _TOKENIZE('the 69th regt.)'))
self.assertEqual('a srgt . ( born )'.split(), _TOKENIZE('a srgt. (born)'))
self.assertEqual('4. bought'.split(), _TOKENIZE('4. bought'))
self.assertEqual('4 . I bought'.split(), _TOKENIZE('4. I bought'))
self.assertEqual('A. I bought'.split(), _TOKENIZE('A. I bought'))
self.assertEqual('A. I bought A. I bought'.split(), _TOKENIZE('A. I bought A. I bought'))
self.assertEqual('1.A. I bought'.split(), _TOKENIZE('1.A. I bought'))
self.assertEqual('1.A I bought'.split(), _TOKENIZE('1.A I bought'))
self.assertEqual('( 1 . Todo Cambia )'.split(), _TOKENIZE('(1. Todo Cambia)'))
self.assertEqual('( 1. todo )'.split(), _TOKENIZE('(1. todo)'))
self.assertEqual('manuf. comm. strategies'.split(), _TOKENIZE('manuf. comm. strategies'))
self.assertEqual('tech ASP .NET'.split(), _TOKENIZE('tech ASP .NET'))
self.assertEqual('items is N. shore'.split(), _TOKENIZE('items is N. shore'))
self.assertEqual('his name is <NAME>'.split(), _TOKENIZE('his name is <NAME>'))
self.assertEqual('his name is a. gray'.split(), _TOKENIZE('his name is a. gray'))
self.assertEqual('Engage U.S. donors'.split(), _TOKENIZE('Engage U.S. donors'))
self.assertEqual('the min. is 3'.split(), _TOKENIZE('the min. is 3'))
self.assertEqual('the Bld. is'.split(), _TOKENIZE('the Bld. is'))
self.assertEqual('the BLD. is'.split(), _TOKENIZE('the BLD. is'))
self.assertEqual('he is dr. Robin'.split(), _TOKENIZE('he is dr. Robin'))
self.assertEqual('Dr. Robin'.split(), _TOKENIZE('Dr. Robin'))
self.assertEqual('13th ed. New York'.split(), _TOKENIZE('13th ed. New York'))
self.assertEqual('he is Sr. Programmer'.split(), _TOKENIZE('he is Sr. Programmer'))
self.assertEqual('bullet 1. do this'.split(), _TOKENIZE('bullet 1. do this'))
self.assertEqual('bullet 01. do this'.split(), _TOKENIZE('bullet 01. do this'))
self.assertEqual('bullet.2 do this'.split(), _TOKENIZE('bullet.2 do this'))
self.assertEqual('of .20 inch'.split(), _TOKENIZE('of .20 inch'))
self.assertEqual('a. b. ('.split(), _TOKENIZE('a. b. ('))
self.assertEqual('an n. g. :'.split(), _TOKENIZE('an n. g. :'))
self.assertEqual('in u.s. !'.split(), _TOKENIZE('in u.s. !'))
self.assertEqual(', vols. :'.split(), _TOKENIZE(', vols. :'))
self.assertEqual('a volume . "'.split(), _TOKENIZE('a volume. "'))
self.assertEqual("a volume . '".split(), _TOKENIZE("a volume. '"))
self.assertEqual('a volume . ('.split(), _TOKENIZE('a volume. ('))
self.assertEqual('a volume . )'.split(), _TOKENIZE('a volume. )'))
self.assertEqual('a volume . ['.split(), _TOKENIZE('a volume. ['))
self.assertEqual('a volume . ]'.split(), _TOKENIZE('a volume. ]'))
self.assertEqual('a volume . {'.split(), _TOKENIZE('a volume. {'))
self.assertEqual('a volume . }'.split(), _TOKENIZE('a volume. }'))
self.assertEqual('a volume . |'.split(), _TOKENIZE('a volume. |'))
self.assertEqual('a volume . *'.split(), _TOKENIZE('a volume. *'))
def test_exclamation_points_split(self):
self.assertEqual('this is you ! Omg'.split(), _TOKENIZE('this is you! Omg'))
self.assertEqual('this is you !'.split(), _TOKENIZE('this is you!'))
self.assertEqual('this is you !!!'.split(), _TOKENIZE('this is you!!!'))
self.assertEqual('my man ! - marcus'.split(), _TOKENIZE('my man! - marcus'))
def test_exclamation_points_nosplit(self):
self.assertEqual('innovate ! project'.split(), _TOKENIZE('innovate! project'))
def test_non_ambiguous_seperators(self):
self.assertEqual('this [ is ] you'.split(), _TOKENIZE('this [is] you'))
self.assertEqual('this ( is ) you'.split(), _TOKENIZE('this (is) you'))
self.assertEqual('this { is } you'.split(), _TOKENIZE('this {is} you'))
self.assertEqual('this is you ? omg'.split(), _TOKENIZE('this is you? omg'))
self.assertEqual('this is you ???'.split(), _TOKENIZE('this is you???'))
self.assertEqual(r'me \ you'.split(), _TOKENIZE(r'me\you'))
self.assertEqual('me | you'.split(), _TOKENIZE('me|you'))
self.assertEqual('the " cat " jumps'.split(), _TOKENIZE('the "cat" jumps'))
self.assertEqual('the cat ; jumps'.split(), _TOKENIZE('the cat; jumps'))
self.assertEqual('the cat : jumps'.split(), _TOKENIZE('the cat: jumps'))
self.assertEqual('failures : include'.split(), _TOKENIZE('failures :include'))
self.assertEqual('sell > 12'.split(), _TOKENIZE('sell >12'))
self.assertEqual('sell < 12'.split(), _TOKENIZE('sell <12'))
self.assertEqual('ca = breakfast'.split(), _TOKENIZE('ca=breakfast'))
self.assertEqual('targets ='.split(), _TOKENIZE('targets='))
def test_lt_gt(self):
self.assertEqual('sell <-- 12'.split(), _TOKENIZE('sell <-- 12')) # ??
self.assertEqual('sell -> 12'.split(), _TOKENIZE('sell -> 12'))
self.assertEqual('This is < me >'.split(), _TOKENIZE('This is <me>'))
self.assertEqual('Sell > 50%'.split(), _TOKENIZE('Sell >50%'))
self.assertEqual('Sell < 50%'.split(), _TOKENIZE('Sell <50%'))
def test_star(self):
self.assertEqual('discussion * integration'.split(), _TOKENIZE('discussion*integration'))
self.assertEqual('discussion * integration'.split(), _TOKENIZE('discussion****integration'))
self.assertEqual('123*123'.split(), _TOKENIZE('123*123'))
self.assertEqual('123*abc'.split(), _TOKENIZE('123*abc'))
def test_plus(self):
self.assertEqual('responsibilities + timeline'.split(), _TOKENIZE('responsibilities+timeline'))
self.assertEqual('hagen + greg + kris'.split(), _TOKENIZE('hagen+greg+kris'))
self.assertEqual('LTED + Wifi + BLE + Secret'.split(), _TOKENIZE(' LTED+Wifi+BLE+Secret '))
self.assertEqual('3+ at'.split(), _TOKENIZE('3+at'))
self.assertEqual('312+ at'.split(), _TOKENIZE('312+at'))
self.assertEqual('aa+'.split(), _TOKENIZE('aa+'))
def test_ampercases(self):
self.assertEqual('new & old'.split(), _TOKENIZE('new&old'))
self.assertEqual('New & Old'.split(), _TOKENIZE('New&Old'))
self.assertEqual('NEW&OLD'.split(), _TOKENIZE('NEW&OLD'))
self.assertEqual('t&cs'.split(), _TOKENIZE('t&cs'))
self.assertEqual('T&CS'.split(), _TOKENIZE('T&CS'))
self.assertEqual('schedule & provide'.split(), _TOKENIZE('schedule& provide'))
self.assertEqual('schedule & provide'.split(), _TOKENIZE('schedule& provide'))
self.assertEqual('invest R&D'.split(), _TOKENIZE('invest R&D'))
self.assertEqual('invest R&D'.split(), _TOKENIZE('invest R &D'))
self.assertEqual('invest R&D'.split(), _TOKENIZE('invest R& D'))
self.assertEqual('invest R&D'.split(), _TOKENIZE('invest R & D'))
self.assertEqual('invest R & 1'.split(), _TOKENIZE('invest R &1'))
self.assertEqual('invest R & DD'.split(), _TOKENIZE('invest R& DD'))
self.assertEqual('R&D lab'.split(), _TOKENIZE('R&D lab'))
self.assertEqual('R&D lab'.split(), _TOKENIZE('R& D lab'))
self.assertEqual('R&D lab'.split(), _TOKENIZE('R &D lab'))
self.assertEqual('R&D lab'.split(), _TOKENIZE('R & D lab'))
self.assertEqual('invest R&D lab'.split(), _TOKENIZE('invest R&D lab'))
self.assertEqual('invest R&D lab'.split(), _TOKENIZE('invest R &D lab'))
self.assertEqual('invest R&D lab'.split(), _TOKENIZE('invest R& D lab'))
self.assertEqual('invest R&D lab'.split(), _TOKENIZE('invest R & D lab'))
self.assertEqual('invest AR&D lab'.split(), _TOKENIZE('invest A R & D lab'))
self.assertEqual('invest R&DA lab'.split(), _TOKENIZE('invest R & D A lab'))
self.assertEqual('invest RR & R2 A lab'.split(), _TOKENIZE('invest RR & R2 A lab'))
self.assertEqual('kitchen & utility'.split(), _TOKENIZE('kitchen&utility'))
def test_slashes(self):
self.assertEqual('10/10/2010'.split(), _TOKENIZE('10/10/2010'))
self.assertEqual('b2b / b2c'.split(), _TOKENIZE('b2b/b2c'))
self.assertEqual('me / you'.split(), _TOKENIZE('me/you'))
self.assertEqual('me / you'.split(), _TOKENIZE('me /you'))
self.assertEqual('me / you'.split(), _TOKENIZE('me/ you'))
self.assertEqual('/ external'.split(), _TOKENIZE('/external'))
self.assertEqual('p/a'.split(), _TOKENIZE('p/a'))
self.assertEqual('A/B'.split(), _TOKENIZE('A/B'))
self.assertEqual('A/'.split(), _TOKENIZE('A/'))
self.assertEqual('/B'.split(), _TOKENIZE('/B'))
def test_emdashes(self):
self.assertEqual('- this'.split(), _TOKENIZE('–this'))
def test_percentage(self):
self.assertEqual('%12'.split(), _TOKENIZE('%12'))
self.assertEqual('12%'.split(), _TOKENIZE('12%'))
self.assertEqual('% savings'.split(), _TOKENIZE('%savings'))
self.assertEqual('save % savings'.split(), _TOKENIZE('save%savings'))
def test_colon(self):
self.assertEqual('example : bla'.split(), _TOKENIZE('example: bla'))
self.assertEqual('raise Q1 : Raise 1$'.split(), _TOKENIZE('raise Q1: Raise 1$'))
self.assertEqual('support : revise'.split(), _TOKENIZE('support:revise'))
self.assertEqual('payroll : hr'.split(), _TOKENIZE('payroll:hr'))
self.assertEqual('Support : Revise'.split(), _TOKENIZE('Support:Revise'))
self.assertEqual('re:invent'.split(), _TOKENIZE('re:invent'))
self.assertEqual('conduct 1:1s'.split(), _TOKENIZE('conduct 1:1s'))
self.assertEqual('ISO 123:123'.split(), _TOKENIZE('ISO 123:123'))
self.assertEqual('A:B'.split(), _TOKENIZE('A:B'))
self.assertEqual('step : 703'.split(), _TOKENIZE('step:703'))
self.assertEqual('Sell 12 :'.split(), _TOKENIZE('Sell 12:'))
self.assertEqual('Strategy : HR'.split(), _TOKENIZE('Strategy:HR'))
self.assertEqual('2 : HR'.split(), _TOKENIZE('2:HR'))
self.assertEqual('12243 : engage'.split(), _TOKENIZE('12243:engage'))
def test_arrows(self):
self.assertEqual('Sell 12->23'.split(), _TOKENIZE('Sell 12->23'))
self.assertEqual('Sell 12 > 23'.split(), _TOKENIZE('Sell 12>23'))
self.assertEqual('a => b'.split(), _TOKENIZE('a = > b'))
self.assertEqual('x >= 12.5'.split(), _TOKENIZE(' x > = 12.5'))
self.assertEqual('x <= 12.5'.split(), _TOKENIZE(' x < = 12.5'))
def test_comas(self):
self.assertEqual('hello , hi'.split(), _TOKENIZE('hello, hi'))
self.assertEqual('123 , all good'.split(), _TOKENIZE('123, all good'))
self.assertEqual('all good , 123'.split(), _TOKENIZE('all good,123'))
self.assertEqual('123,123'.split(), _TOKENIZE('123,123'))
def test_single_quotes(self):
self.assertEqual("Rocco 's blob".split(), _TOKENIZE("Rocco 's blob"))
self.assertEqual("His name is ' Rob ' bob".split(), _TOKENIZE("His name is 'Rob' bob"))
self.assertEqual("His name is Rob ' bob '".split(), _TOKENIZE("His name is Rob 'bob'"))
self.assertEqual("launch ' go live ' strategy".split(), _TOKENIZE("launch 'go live'strategy"))
self.assertEqual("james o'hare".split(), _TOKENIZE("james o'hare"))
self.assertEqual("' proposal".split(), _TOKENIZE("'proposal"))
self.assertEqual('Deliver 4ft'.split(), _TOKENIZE("Deliver 4'"))
self.assertEqual('Deliver 4in'.split(), _TOKENIZE('Deliver 4"'))
self.assertEqual('Deliver 4ft4in'.split(), _TOKENIZE('Deliver 4\'4"'))
self.assertEqual("' we will run items again '".split(), _TOKENIZE("'we will run items again'"))
self.assertEqual("ceo order ' macbook pro '".split(), _TOKENIZE("ceo order 'macbook pro'"))
self.assertEqual("rock 'n' roll".split(), _TOKENIZE("rock 'n' roll"))
self.assertEqual("rock 'n roll".split(), _TOKENIZE("rock 'n roll"))
self.assertEqual("rock n' roll".split(), _TOKENIZE("rock n' roll"))
def test_clitics(self):
self.assertEqual("Jane 's blob".split(), _TOKENIZE("Jane's blob"))
self.assertEqual("sdo 's".split(), _TOKENIZE("sdo's"))
self.assertEqual("make SOP 's today".split(), _TOKENIZE("make SOP's today"))
self.assertEqual("I 'd eat".split(), _TOKENIZE("I'd eat"))
self.assertEqual("I 'm blob".split(), _TOKENIZE("I'm blob"))
self.assertEqual("They 'll come".split(), _TOKENIZE("They'll come"))
self.assertEqual("They 're blobs".split(), _TOKENIZE("They're blobs"))
self.assertEqual("They 've eaten".split(), _TOKENIZE("They've eaten"))
self.assertEqual("They are n't blobs".split(), _TOKENIZE("They aren't blobs"))
self.assertEqual("They ca n't blobs".split(), _TOKENIZE("They can't blobs"))
self.assertEqual("They have n't blobs".split(), _TOKENIZE("They haven't blobs"))
self.assertEqual("They is n't blobs".split(), _TOKENIZE("They isn't blobs"))
self.assertEqual('ifp \'s'.split(), _TOKENIZE('ifp\'s'))
def test_multi_special_chars(self):
self.assertEqual('bla // bla'.split(), _TOKENIZE('bla // bla'))
self.assertEqual('bla {{ bla }}'.split(), _TOKENIZE('bla {{bla}}'))
self.assertEqual('bla {{ bla }}'.split(), _TOKENIZE('bla {{bla}}'))
def test_bullets(self):
self.assertEqual('year . * introduce'.split(), _TOKENIZE('year. *introduce'))
self.assertEqual('year . - introduce'.split(), _TOKENIZE('year. -introduce'))
def test_special_chars(self):
self.assertEqual('_tag #MenArePigs'.split(), _TOKENIZE('_tag #MenArePigs'))
self.assertEqual('_tag @MenArePigs'.split(), _TOKENIZE('_tag @MenArePigs'))
def test_protected_patterns(self):
self.assertEqual('visit http://bla.com.au'.split(), _TOKENIZE('visit http://bla.com.au'))
self.assertEqual('visit https://bla.com.au/'.split(), _TOKENIZE('visit https://bla.com.au/'))
self.assertEqual('visit www.bla.com.au/bla.pdf'.split(), _TOKENIZE('visit www.bla.com.au/bla.pdf'))
self.assertEqual('visit www.Bla.com and www.Bla2.com'.split(), _TOKENIZE('visit www.Bla.com and www.Bla2.com'))
def test_sentence_parts(self):
self.assertEqual('on Oct. 29 , 2017 .'.split(), _TOKENIZE('on Oct. 29, 2017.'))
self.assertEqual('involve the U.S. ?'.split(), _TOKENIZE('involve the U.S.?'))
self.assertEqual('" Jump " , he said .'.split(), _TOKENIZE('"Jump", he said.'))
self.assertEqual('" Jump . " , he said .'.split(), _TOKENIZE('"Jump.", he said.'))
self.assertEqual('" Jump . " he said .'.split(), _TOKENIZE('"Jump." he said.'))
def test_multi_dots(self):
self.assertEqual('Ms. Dean .'.split(), _TOKENIZE('Ms. Dean.'))
self.assertEqual('Ms. Dean . Mrs Dean .'.split(), _TOKENIZE('Ms. Dean. Mrs Dean.'))
self.assertEqual('Sgt. Pepp. went there'.split(), _TOKENIZE('Sgt. Pepp. went there'))
def test_smileys(self):
self.assertEqual(':-)'.split(), _TOKENIZE(':-)'))
# LONG TEXT
# -------------------------------------------------------------------------->
def test_text_1(self):
self.assertEqual('said Lt. Gov. <NAME> in a Dec. 19 press release .'.split(),
_TOKENIZE('said Lt. Gov. B<NAME> in a Dec. 19 press release.'))
def test_text_2(self):
self.assertEqual('headquarters in Ghent , Belgium . The company develops'.split(),
_TOKENIZE('headquarters in Ghent, Belgium. The company develops'))
def test_text_3(self):
self.assertEqual('The fastest in the world , by a long margin . Concentrate . Got a picture in mind ?'.split(),
_TOKENIZE('The fastest in the world, by a long margin. Concentrate. Got a picture in mind?'))
def test_text_4(self):
self.assertEqual('" I wrote , \' Making lemonade out of lemons . \' " The post marked the start .'.split(),
_TOKENIZE('"I wrote, \'Making lemonade out of lemons.\' " The post marked the start.'))
def test_text_5(self):
self.assertEqual('" I wrote , " Making lemonade out of lemons . " " The post marked the start .'.split(),
_TOKENIZE('"I wrote, "Making lemonade out of lemons." " The post marked the start.'))
def test_text_6(self):
self.assertEqual("I say , ' Why did I do that ! ' It keeps you inspired !".split(),
_TOKENIZE("I say, 'Why did I do that!' It keeps you inspired!"))
def test_text_7(self):
self.assertEqual("I say , ' Why did I do that ? ' It keeps you inspired !".split(),
_TOKENIZE("I say, 'Why did I do that?' It keeps you inspired!"))
def test_text_8(self):
self.assertEqual("They have become my online ' support ' group .".split(),
_TOKENIZE("They have become my online 'support' group."))
if __name__ == '__main__':
unittest.main()
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p240_search_a_2d_matrix_ii.py | feigaochn/leetcode | 0 | 115380 | <reponame>feigaochn/leetcode
# coding: utf-8
# author: <NAME>
#
# Search A 2d Matrix Ii
# Write an efficient algorithm that searches for a value in an m x n matrix. This matrix has the following properties:
# Integers in each row are sorted in ascending from left to right.
# Integers in each column are sorted in ascending from top to bottom.
# For example,
# Consider the following matrix:
# [
# [1, 4, 7, 11, 15],
# [2, 5, 8, 12, 19],
# [3, 6, 9, 16, 22],
# [10, 13, 14, 17, 24],
# [18, 21, 23, 26, 30]
# ]
# Given target = 5, return true.
# Given target = 20, return false.
# Subscribe to see which companies asked this question
class Solution(object):
def searchMatrix(self, matrix, target):
"""
:type matrix: List[List[int]]
:type target: int
:rtype: bool
"""
def search(row1, row2, col1, col2):
"""Search target in sub matrix[row1:row2][col1:col2]"""
# zero elements
if row1 >= row2 or col1 >= col2:
return False
if matrix[row1][col1] == target:
return True
# target less than up-left corner
if target < matrix[row1][col1]:
return False
# target greater than low-right corner
if target > matrix[row2 - 1][col2 - 1]:
return False
row3 = (row1 + row2 + 1) // 2
col3 = (col1 + col2 + 1) // 2
# print(row1, row3, row2, col1, col3, col2)
result = (search(row1, row3, col1, col3)
or search(row1, row3, col3, col2)
or search(row3, row2, col1, col3)
or search(row3, row2, col3, col2))
# print(row1, row2, col1, col2, result)
return result
return search(0, len(matrix), 0, len(matrix[0]))
def main():
solver = Solution()
tests = [
([
[1, 4, 7, 11, 15],
[2, 5, 8, 12, 19],
[3, 6, 9, 16, 22],
[10, 13, 14, 17, 24],
[18, 21, 23, 26, 30]
], 5),
([
[1, 4, 7, 11, 15],
[2, 5, 8, 12, 19],
[3, 6, 9, 16, 22],
[10, 13, 14, 17, 24],
[18, 21, 23, 26, 30]
], 20)
]
for test in tests:
print(test)
print(' ->')
result = solver.searchMatrix(*test)
print(result)
print('~' * 10)
pass
if __name__ == '__main__':
main()
pass
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tests/models/test_prodotti.py | 20tab/python-fattureincloud | 2 | 133717 | <gh_stars>1-10
from unittest import TestCase
from requests_mock import Mocker
from fattureincloud.client import FattureInCloudAPI
from tests.mocking import mocker_register_uri
class TestProdotti(TestCase):
"""Define simple test case for base client request."""
maxDiff = None
def setUp(self):
"""Set client with key and uid."""
self.client = FattureInCloudAPI(api_uid="123456", api_key="qwerty")
@Mocker()
def test_prodotti(self, mocker):
"""Test prodotti."""
mocker_register_uri(
mocker, self.client.host, "/prodotti/lista", "prodotti/prodotti.json"
)
self.assertEqual(len(self.client.prodotti.lista()), 2)
@Mocker()
def test_prodotti_2_pages(self, mocker):
"""Test prodotti with 2 pages."""
mocker_register_uri(
mocker,
self.client.host,
"/prodotti/lista",
"prodotti/prodotti_2_pages.json",
)
self.assertEqual(len(self.client.prodotti.lista()), 4)
def test_nuovo(self):
"""Test nuovo method."""
with self.assertRaises(NotImplementedError):
self.client.prodotti.nuovo()
def test_importa(self):
"""Test importa method."""
with self.assertRaises(NotImplementedError):
self.client.prodotti.importa()
def test_modifica(self):
"""Test modifica method."""
with self.assertRaises(NotImplementedError):
self.client.prodotti.modifica()
def test_elimina(self):
"""Test elimina method."""
with self.assertRaises(NotImplementedError):
self.client.prodotti.elimina()
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16853,
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295,
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580,
13,
2
] |
contact/views.py | rsHalford/xhalford-django | 2 | 21914 | from django.shortcuts import render
from django.views.generic import ListView
from contact.models import Profile
class Contact(ListView):
model = Profile
template_name = "contact.html"
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010-binarysearch.py | dasalgadoc/PythonNotes | 0 | 43666 | import random
def binary_search(data, target, low_index, high_index):
""" Binary Search recursiva """
if (low_index > high_index):
return False
mid_index = (low_index + high_index) // 2
if target == data[mid_index]:
return True
elif target < data[mid_index]:
return binary_search(data, target, low_index, mid_index - 1)
else:
return binary_search(data, target, mid_index + 1, high_index)
def loop_binary_search(data, target, low_index, high_index):
""" Binary Search Iterativa """
while(low_index < high_index):
mid_index = (low_index + high_index) // 2
if target == data[mid_index]:
return True
elif target < data[mid_index]:
high_index = (mid_index - 1)
else:
low_index = (mid_index + 1)
return False
if __name__ == "__main__":
""" Suponga un arreglo ordenado, en el cual vamos a buscar un elemento.
Optimizar una búsqueda en esta lista consiste en dividir la lista en partes e
ir comparando el número con la parte dividida, en esto consiste la búsqueda binaria.
Se implementarán dos forma en este Script"""
data = [random.randint(0,100) for i in range(10)]
data.sort()
print(data)
target = int(input("Numero a encontrar:\t"))
f = binary_search(data, target, 0, len(data) - 1)
print(f)
f = loop_binary_search(data, target, 0, len(data) - 1)
print(f)
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] |
tests/test_template_helpers.py | ramiro/flourish | 12 | 136294 | # encoding: utf-8
import pytest
from flourish import Flourish
from flourish.helpers import publication_range
class TestFlourish:
@classmethod
def setup_class(cls):
with pytest.warns(None) as warnings:
cls.flourish = Flourish('tests/source')
def test_publication_range(self):
assert u'2015–2016' == publication_range(self.flourish)
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xplainer/backend/tools/lime.py | liborvaneksw/xplainer | 4 | 44359 | import tensorflow as tf
from lime import lime_image
from skimage.segmentation import mark_boundaries
from xplainer.backend.tools.abstract_tool import AbstractTool, GeneralSettings
from xplainer.backend.utils.image import prepare_for_prediction, get_base64png
class Lime(AbstractTool):
def name(self):
return "LIME"
def category(self):
return "Local"
def description(self):
return "Local Interpretable Model-Agnostic Explanations."
def source_name(self) -> str:
return "lime"
def source_url(self) -> str:
return "https://github.com/marcotcr/lime"
def tool_parameters(self) -> dict:
return {
"list": [
{
"param": "batch_size",
"name": "Batch size",
"type": "int",
"default": 10,
"min": 1,
"step": 1,
},
{
"param": "num_features",
"name": "Features",
"type": "int",
"default": 100000,
"min": 1,
"step": 10000,
},
{
"param": "num_samples",
"name": "Samples",
"type": "int",
"default": 100,
"min": 1,
"step": 100,
},
{
"param": "positive_only",
"name": "Positive only",
"type": "bool",
"default": True,
},
{
"param": "superpixels",
"name": "Superpixels",
"type": "int",
"default": 5,
"min": 1,
"step": 1,
},
{
"param": "min_weight",
"name": "Min weight",
"type": "float",
"default": 0.0,
"min": 0.0,
"step": 0.1,
},
{"param": "hide_rest", "name": "Hide rest", "description": None, "type": "bool", "default": True,},
],
"layout": [
["batch_size", "num_features", "num_samples"],
["superpixels", "min_weight", "positive_only", "hide_rest"],
],
}
def explain(
self, model: tf.keras.Model, image_path: str, general_settings: GeneralSettings, tool_settings: dict = None
) -> list:
image = prepare_for_prediction(model, image_path)
onehot, labels = self._get_labels(model, image, general_settings)
image = tf.cast(image, dtype=tf.float64)
explainer = lime_image.LimeImageExplainer()
explanation = explainer.explain_instance(
image.numpy()[0],
model.predict,
labels=labels,
batch_size=tool_settings["batch_size"],
num_features=tool_settings["num_features"],
num_samples=tool_settings["num_samples"],
)
results = []
for label in labels:
temp, mask = explanation.get_image_and_mask(
label,
positive_only=tool_settings["positive_only"],
num_features=tool_settings["superpixels"],
min_weight=tool_settings["min_weight"],
hide_rest=tool_settings["hide_rest"],
)
result_image = mark_boundaries(temp / 2 + 0.5, mask)
result_image = tf.image.convert_image_dtype(result_image, dtype=tf.uint8, saturate=True)
image_base46 = get_base64png(result_image)
results.append(
{"label_id": int(label), "probability": float(onehot[label]), "image": image_base46,}
)
return results
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src/main/python/spec_checker/modules/cpu.py | houdinii/specCheckWithGui | 1 | 116511 | <filename>src/main/python/spec_checker/modules/cpu.py
import psutil
import pythoncom
pythoncom.CoInitialize()
class CpuRecord:
"""Holds and records the number of cores, usage, and frequency of the primary cpu
Keyword Arguments:
physical_cores -- Number of physical cores present (Default: None)
total_cores -- Total number of cores including virtual cores (Default: None)
min_frequency -- Minimum frequency (Default: None)
max_frequency -- Maximum frequency (Default: None)
current_frequency -- Current frequency (Default: None)
total_usage -- Total usage as a percent (Default: None)
"""
def __init__(self, physical_cores=0, total_cores=0, min_frequency=None,
max_frequency=None, current_frequency=None, total_usage=None):
self.physical_cores = physical_cores
self.total_cores = total_cores
self.min_frequency = min_frequency
self.max_frequency = max_frequency
self.current_frequency = current_frequency
self.total_usage = total_usage
def __repr__(self):
return f"<CpuRecord physical_cores:{self.physical_cores} total_cores:{self.total_cores}>"
def __str__(self):
return f"""
CPU Information:
Physical Cores: {self.physical_cores}
Total Cores: {self.total_cores}
Minimum Frequency: {self.min_frequency}
Maximum Frequency: {self.max_frequency}
Current Frequency: {self.current_frequency}
Total Usage Percent: {self.total_usage}"""
def test(self):
"""Performs the cpu test and records record to self
Returns: <CpuRecord>
"""
self.physical_cores = psutil.cpu_count(logical=False)
self.total_cores = psutil.cpu_count(logical=True)
self.min_frequency = f"{psutil.cpu_freq().min:.2f}Mhz"
self.max_frequency = f"{psutil.cpu_freq().max:.2f}Mhz"
self.current_frequency = f"{psutil.cpu_freq().current:.2f}Mhz"
self.total_usage = f"{psutil.cpu_percent()}%"
return self
| [
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] |
PhyTestOnline/PhyTestOnline.py | JerryLife/PhyTestOnline | 1 | 24662 | <gh_stars>1-10
# -*- coding: utf-8 -*-
# Copyright (C) 2016 <NAME>
import urllib
import urllib2
import re
import xlwt
START_PAGE = 0 # start page
ALL_PAGE = 82 # number of all pages
class PhyTestOnline(object):
"""
This class is specially for a HUST Physics Test Online providing a crawler to download
the Keys and to save them as Excel(.xls). For convenience, you can just use PhyTestOnline.main()
to finish the whole procedure.
Attention: This is a simple practice in crawler, which is only for study and communication.
It should never be used for illegal or improper ways like cheating. If so, the one who did it is
responsible for his own behavior instead of the author.
"""
def __init__(self, baseURL="http://172.16.31.10/admin/menu/query/queryandchoose/xianshi?paperNum=0"):
self.baseURL = baseURL
def getFirstPage(self, url=None):
if not url:
url = self.baseURL
try:
user_agent = 'Mozilla/5.0 (Windows NT 10.0; WOW64) ' \
'AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.99 Safari/537.36'
headers = {'User-Agent': user_agent}
data = urllib.urlencode({})
request = urllib2.Request(url, data, headers)
response = urllib2.urlopen(request, timeout=10)
content = response.read()
return content.decode('GBK')
except urllib2.URLError, e:
if hasattr(e, "reason"):
print "Fail to connect to PhysicsTestOnline:", e.reason
return None
def getText(self, url=None):
textModel = re.compile('<td width="146">([0-9]+\.jpg)')
ansModel = re.compile('<td width="41">(.*)</td>')
html = self.getFirstPage(url)
if not html:
return None
text = re.findall(textModel, html)
ans = re.findall(ansModel, html)
if len(text) == len(ans):
print "%d Got" % len(ans)
return zip(text, ans)
else:
print "Answer or picture lost!"
return None
def getAll(self, allPage=ALL_PAGE):
startPage = self.baseURL[0:-1]
ansList = []
for i in range(START_PAGE, allPage+1):
url = startPage + str(i)
ans = self.getText(url)
if not ans:
pass
else:
print "Page%d finished.%d%%" % (i, i*100/allPage)
ansList += ans
print "Program complete."
return ansList
def saveAns(self, ansList, fileName='D:\TestAnswer.xls'):
ans = xlwt.Workbook()
sheet = ans.add_sheet('Sheet1')
numOfProblems = len(ansList)
for i in range(numOfProblems):
sheet.write(i, 0, ansList[i][0])
sheet.write(i, 1, ansList[i][1])
print "Line %d saved.%d%% Finished" % (i+1, (i+1)*100/numOfProblems)
# need protect?
ans.protect = True
ans.wnd_protect = True
ans.obj_protect = True
ans.save(fileName)
print "All saved."
return None
def main(self):
ansList = self.getAll()
iSave = raw_input('Save now? y/n: ')
if iSave == 'y':
self.saveAns(ansList)
else:
return None
return True
ans = PhyTestOnline()
ans.main() | [
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] |
tests/test_search.py | chdean/usajobs | 2 | 83589 | <reponame>chdean/usajobs
import usajobs
import pytest
import requests
def test_search():
test_url = 'https://api.usa.gov/jobs/search.json?query=park+ranger&size=100'
test_data = requests.get(test_url).json()
results = usajobs.search('park ranger', step=5, as_dict=True)
assert len(results) == len(test_data) # hack
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metis/metis/__init__.py | joshblum/chronology | 0 | 139019 | <gh_stars>0
from gevent import monkey; monkey.patch_all()
import os
VERSION = (0, 1, 'alpha')
def get_version(version=None):
version = version or VERSION
assert(len(version) == 3)
return '%s.%s %s' % version
# The file path will have `metis.zip` in it if its being run on Spark workers.
# In that case we don't want to run the following initialization code because
# it can (and does) break things.
if 'metis.zip' in str(__file__):
app = None
else:
from flask import Flask
METIS_PATH = os.path.realpath(os.path.dirname(__file__))
app = Flask(__name__)
app.config.from_pyfile('%s/conf/default_settings.py' % METIS_PATH)
app.config['PATH'] = METIS_PATH
import metis.views # noqa
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mysite/urls.py | mnithya/cs3240-s15-team06-test | 0 | 26786 | from django.conf.urls import include, url
from django.contrib import admin
from django.contrib.staticfiles.urls import staticfiles_urlpatterns
urlpatterns = [
# Examples:
# url(r'^$', 'mysite.views.home', name='home'),
# url(r'^blog/', include('blog.urls')),
url(r'^$', 'polls.views.home', name='home'),
url(r'^admin/', include(admin.site.urls)),
# user auth urls
url(r'^accounts/login/$', 'polls.views.login'),
url(r'^accounts/auth/$', 'polls.views.auth_view'),
url(r'^accounts/logout/$', 'polls.views.logout'),
url(r'^accounts/loggedin/$', 'polls.views.loggedin'),
url(r'^accounts/invalid/$', 'polls.views.invalid_login'),
url(r'^accounts/register/$', 'polls.views.register_user'),
url(r'^accounts/register_success/$', 'polls.views.register_success'),
# report
url(r'^reports/new/$', 'polls.views.new_report'),
url(r'^reports/list/$', 'polls.views.user_report'),
url(r'^reports/detail/(?P<id>\d+)/$', 'polls.views.report_details'),
url(r'^reports/delete/(?P<id>\d+)/$','polls.views.delete'),
url(r'^reports/all/$','polls.views.report_all'),
url(r'^reports/edit/(?P<id>\d+)/$', 'polls.views.edit_report'),
# folder
url(r'^folder/new/$', 'polls.views.new_folder'),
#search
url(r'^search-form/$', 'polls.views.search_form'),
url(r'^search/$', 'polls.views.search'),
]
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] |
tests/test_user_model.py | Lifeistrange/flaskweb | 0 | 60613 | #!/usr/bin/env python
# coding=utf-8
import unittest
from app.domain.model import User, AnonymousUser, Permission, Role
class UserModelTestCase(unittest.TestCase):
def test_password_setter(self):
u = User(password = '<PASSWORD>')
self.assertTrue(u.password_hash is not None)
def test_no_password_getter(self):
u = User(password = '<PASSWORD>')
with self.assertRaises(AttributeError):
u.password
def test_password_verifcation(self):
u = User(password = '<PASSWORD>')
self.assertTrue(u.verify_password('<PASSWORD>'))
self.assertFalse(u.verify_password('<PASSWORD>'))
def test_password_salts_are_random(self):
u = User(password = '<PASSWORD>')
u2 = User(password = '<PASSWORD>')
self.assertTrue(u.password_hash != u2.password_hash)
def test_roles_and_permissions(self):
Role.insert_roles()
u = User(email='<EMAIL>', password="<PASSWORD>")
self.assertTrue(u.can(Permission.WRITE_ARTICLES))
self.assertFalse(u.can(Permission.MODERATE_COMMENTS))
def test_anonymous_user(self):
u = AnonymousUser()
self.assertFalse(u.can(Permission.FOLLOW))
| [
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2
] |
Minimum Index Sum of Two Lists.py | sugia/leetcode | 0 | 193714 | '''
Suppose Andy and Doris want to choose a restaurant for dinner, and they both have a list of favorite restaurants represented by strings.
You need to help them find out their common interest with the least list index sum. If there is a choice tie between answers, output all of them with no order requirement. You could assume there always exists an answer.
Example 1:
Input:
["Shogun", "Tapioca Express", "Burger King", "KFC"]
["Piatti", "The Grill at Torrey Pines", "Hungry Hunter Steakhouse", "Shogun"]
Output: ["Shogun"]
Explanation: The only restaurant they both like is "Shogun".
Example 2:
Input:
["Shogun", "Tapioca Express", "Burger King", "KFC"]
["KFC", "Shogun", "Burger King"]
Output: ["Shogun"]
Explanation: The restaurant they both like and have the least index sum is "Shogun" with index sum 1 (0+1).
Note:
The length of both lists will be in the range of [1, 1000].
The length of strings in both lists will be in the range of [1, 30].
The index is starting from 0 to the list length minus 1.
No duplicates in both lists.
'''
class Solution(object):
def findRestaurant(self, list1, list2):
"""
:type list1: List[str]
:type list2: List[str]
:rtype: List[str]
"""
if len(list1) < len(list2):
return self.findRestaurant(list2, list1)
key_to_idx = {}
for i in xrange(len(list2)):
key_to_idx[list2[i]] = i
res = []
idx_sum = float('inf')
for i in xrange(len(list1)):
if list1[i] in key_to_idx:
tmp = i + key_to_idx[list1[i]]
if tmp < idx_sum:
res = [list1[i]]
idx_sum = tmp
elif tmp == idx_sum:
res.append(list1[i])
return res
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] |
upsampling/utils/__init__.py | Giamm9998/face_detection_on_sim_events | 5 | 1614347 | <filename>upsampling/utils/__init__.py
from .dataset import Sequence
from .upsampler import Upsampler
from .utils import get_sequence_or_none
| [
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] |
efficiency_mark.py | DaCentDD/asvspoof2019 | 0 | 60950 | import os
import statistics
import librosa
import sox
from concurrent.futures import ThreadPoolExecutor
directory = "flac"
lengths = []
for file in os.listdir(directory):
print(file)
length = librosa.get_duration(filename=f"flac\\{file}")
lengths.append(length)
transform = sox.Transformer();
transform.trim(length*0.25)
transform.build_file(f"flac\\{file}", f"75%\\{file}")
lengths.append(librosa.get_duration(filename=f"75%\\{file}"))
with (open("median_length.txt", "a")) as info:
info.writelines(f"100%: {statistics.median(lengths)}")
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] |
rlil/presets/continuous/models.py | syuntoku14/pytorch-rl-il | 43 | 1601135 | <filename>rlil/presets/continuous/models.py
'''
Pytorch models for continuous control.
'''
import numpy as np
import torch
from rlil import nn
def fc_q(env, hidden1=400, hidden2=300):
return nn.Sequential(
nn.Linear(env.state_space.shape[0] +
env.action_space.shape[0], hidden1),
nn.LeakyReLU(),
nn.Linear(hidden1, hidden2),
nn.LeakyReLU(),
nn.Linear(hidden2, 1),
)
def fc_v(env, hidden1=400, hidden2=300):
return nn.Sequential(
nn.Linear(env.state_space.shape[0], hidden1),
nn.LeakyReLU(),
nn.Linear(hidden1, hidden2),
nn.LeakyReLU(),
nn.Linear(hidden2, 1),
)
def fc_deterministic_policy(env, hidden1=400, hidden2=300):
return nn.Sequential(
nn.Linear(env.state_space.shape[0], hidden1),
nn.LeakyReLU(),
nn.Linear(hidden1, hidden2),
nn.LeakyReLU(),
nn.Linear(hidden2, env.action_space.shape[0]),
)
def fc_deterministic_noisy_policy(env, hidden1=400, hidden2=300):
return nn.Sequential(
nn.NoisyFactorizedLinear(env.state_space.shape[0], hidden1),
nn.LeakyReLU(),
nn.NoisyFactorizedLinear(hidden1, hidden2),
nn.LeakyReLU(),
nn.NoisyFactorizedLinear(hidden2, env.action_space.shape[0]),
)
def fc_soft_policy(env, hidden1=400, hidden2=300):
return nn.Sequential(
nn.Linear(env.state_space.shape[0], hidden1),
nn.LeakyReLU(),
nn.Linear(hidden1, hidden2),
nn.LeakyReLU(),
nn.Linear(hidden2, env.action_space.shape[0] * 2),
)
def fc_actor_critic(env, hidden1=400, hidden2=300):
features = nn.Sequential(
nn.Linear(env.state_space.shape[0], hidden1),
nn.LeakyReLU(),
)
v = nn.Sequential(
nn.Linear(hidden1, hidden2),
nn.LeakyReLU(),
nn.Linear(hidden2, 1)
)
policy = nn.Sequential(
nn.Linear(hidden1, hidden2),
nn.LeakyReLU(),
nn.Linear(hidden2, env.action_space.shape[0] * 2)
)
return features, v, policy
def fc_discriminator(env, hidden1=400, hidden2=300):
return nn.Sequential(
nn.Linear(env.state_space.shape[0] + env.action_space.shape[0],
hidden1),
nn.LeakyReLU(),
nn.Linear(hidden1, hidden2),
nn.LeakyReLU(),
nn.Linear(hidden2, 1),
nn.Sigmoid())
def fc_bcq_encoder(env, latent_dim=32, hidden1=400, hidden2=300):
# output mean and log_var
return nn.Sequential(
nn.Linear(env.state_space.shape[0] +
env.action_space.shape[0], hidden1),
nn.LeakyReLU(),
nn.Linear(hidden1, hidden2),
nn.LeakyReLU(),
nn.Linear(hidden2, latent_dim * 2)
)
def fc_bcq_decoder(env, latent_dim=32, hidden1=300, hidden2=400):
return nn.Sequential(
nn.Linear(env.state_space.shape[0] + latent_dim, hidden1),
nn.LeakyReLU(),
nn.Linear(hidden1, hidden2),
nn.LeakyReLU(),
nn.Linear(hidden2, env.action_space.shape[0])
)
def fc_bcq_deterministic_policy(env, hidden1=400, hidden2=300):
return nn.Sequential(
nn.Linear(env.state_space.shape[0] +
env.action_space.shape[0], hidden1),
nn.LeakyReLU(),
nn.Linear(hidden1, hidden2),
nn.LeakyReLU(),
nn.Linear(hidden2, env.action_space.shape[0]),
)
def fc_reward(env, hidden1=400, hidden2=300):
return nn.Sequential(
nn.Linear(env.state_space.shape[0] +
env.action_space.shape[0], hidden1),
nn.LeakyReLU(),
nn.Linear(hidden1, hidden2),
nn.LeakyReLU(),
nn.Linear(hidden2, 1)
)
def fc_dynamics(env, hidden1=500, hidden2=500):
return nn.Sequential(
nn.Linear(env.state_space.shape[0] +
env.action_space.shape[0], hidden1),
nn.LeakyReLU(),
nn.Linear(hidden1, hidden2),
nn.LeakyReLU(),
nn.Linear(hidden2, env.state_space.shape[0]),
)
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] |
app.py | chezhia/robinhood-portfolio | 87 | 76680 | <gh_stars>10-100
import os
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import matplotlib.dates as mdates
from flask import Flask, render_template, request
from backend.backend import BackendClass
from io import BytesIO
# Initialize
MY_DPI = 96
DATAFILE = 'data/data.h5'
USERFILE = 'data/user.pkl'
sns.set_style("whitegrid")
app = Flask(__name__)
app.config['SECRET_KEY'] = 'My_l0ng_very_secure_secret_k3y'
app.config['DEBUG'] = False
app.config['TESTING'] = False
def plot_returns(data):
# Set up the matplotlib figure
f, ax = plt.subplots(figsize=(900/MY_DPI, 400/MY_DPI), dpi=MY_DPI)
x = data.index.values
y = data.values
ax.plot(x, y, linewidth=1.0, color='#2c7fb8')
ax.axhline(y=0, color='#e34a33', linestyle='-', linewidth=0.5)
ax.set_ylabel("Portfolio returns")
# format y-axis
ax.get_yaxis().set_major_formatter(
ticker.FuncFormatter(lambda x, p: '${:.0f}'.format(x)))
# format dates
# months_ticks = mdates.MonthLocator() # every month
date_fmt = mdates.DateFormatter('%b-%Y')
# ax.xaxis.set_major_locator(months_ticks)
ax.xaxis.set_major_formatter(date_fmt)
ax.grid(False, axis='both', linestyle='-', linewidth=0.5, color="#deebf7")
# saving and exporting the svg
with BytesIO() as img_svg:
f.savefig(img_svg, format='svg', dpi=MY_DPI, bbox_inches='tight')
figdata_svg =\
'<svg' + img_svg.getvalue().decode('utf-8').split('<svg')[1]
plt.close(f)
return figdata_svg
def plot_heatmap(corr):
# prepare data
corr = corr.copy()
mask = np.zeros_like(corr, dtype=np.bool)
mask[np.triu_indices_from(mask)] = True
# Set up the matplotlib figure
f, ax = plt.subplots(figsize=(900/MY_DPI, 400/MY_DPI), dpi=MY_DPI)
# Generate a custom diverging colormap
cmap = sns.diverging_palette(220, 20, n=10, as_cmap=True)
# Draw the heatmap with the mask and correct aspect ratio
ax = sns.heatmap(
corr, mask=mask, cmap=cmap, center=0,
square=False, linewidths=.5,
cbar_kws={
"shrink": .8,
'format': '%.2f'},
annot=True, fmt=".3f")
plt.setp(ax.get_yticklabels(), rotation=0)
# saving and exporting the svg
with BytesIO() as img_svg:
f.savefig(img_svg, format='svg', dpi=MY_DPI, bbox_inches='tight')
figdata_svg =\
'<svg' + img_svg.getvalue().decode('utf-8').split('<svg')[1]
plt.close(f)
return figdata_svg
# default route
@app.route('/', methods=["GET", "POST"])
def portfolio():
date_fmt = '{:%d-%b-%Y}'
# initiate backend and get all values
bc = BackendClass(DATAFILE, USERFILE)
bc = bc.calculate_all()
# create plots
plot_corr_svg = plot_heatmap(bc.stock['corr'])
plot_returns_svg = plot_returns(bc.portfolio['daily'])
# handle update of market or robinhood data
if request.method == 'POST':
if request.form['refresh'] == 'market':
bc.update_market_data()
elif request.form['refresh'] == 'robinhood':
user = request.form['inputUser']
password = request.form['inputPassword']
bc.update_robinhood_data(user, password)
bc = bc.calculate_all()
return render_template(
'pages/portfolio.html',
plot_returns_svg=plot_returns_svg,
plot_corr_svg=plot_corr_svg,
portfolio=bc.portfolio,
trades=bc.trades,
stock=bc.stock,
markowitz=bc.markowitz,
rb_dates=[date_fmt.format(x) for x in bc.user['rb_dates']],
mkt_dates=[date_fmt.format(x) for x in bc.user['mkt_dates']],
today=date_fmt.format(bc.user['today']),
)
if __name__ == '__main__':
PORT = int(os.getenv('PORT', 8080))
HOST = os.getenv('HOST', '0.0.0.0')
app.run(debug=True, host=HOST, port=PORT)
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cli/tests/awsbatch/conftest.py | jason-mccloskey/aws-parallelcluster | 1 | 1607560 | <gh_stars>1-10
"""
This module loads pytest fixtures and plugins needed by all tests.
It's very useful for fixtures that need to be shared among all tests.
"""
from __future__ import print_function
import boto3
import pytest
from botocore.stub import Stubber
from common import DEFAULT_AWSBATCHCLICONFIG_MOCK_CONFIG
@pytest.fixture
def failed_with_message(capsys):
"""Assert that the command exited with a specific error message."""
__tracebackhide__ = True
def _failed_with_message(func, message, *args, **kwargs):
__tracebackhide__ = True
with pytest.raises(SystemExit) as error:
func(*args, **kwargs)
assert error.type == SystemExit
assert error.value.code == 1
if message:
assert capsys.readouterr().err == message
return _failed_with_message
@pytest.fixture()
def test_datadir(request, datadir):
"""
Inject the datadir with resources for the specific test function.
If the test function is declared in a class then datadir is ClassName/FunctionName
otherwise it is only FunctionName.
"""
function_name = request.function.__name__
if not request.cls:
return datadir / function_name
class_name = request.cls.__name__
return datadir / "{0}/{1}".format(class_name, function_name)
@pytest.fixture()
def awsbatchcliconfig_mock(request, mocker):
"""Mock AWSBatchCliConfig object with a default mock."""
module_under_test = request.module.__name__.replace("test_", "")
mock = mocker.patch("awsbatch." + module_under_test + ".AWSBatchCliConfig", autospec=True)
for key, value in DEFAULT_AWSBATCHCLICONFIG_MOCK_CONFIG.items():
setattr(mock.return_value, key, value)
return mock
@pytest.fixture()
def convert_to_date_mock(request, mocker):
"""Mock convert_to_date function by enforcing the timezone to UTC."""
module_under_test = request.module.__name__.replace("test_", "")
def _convert_to_date_utc(*args, **kwargs):
from awsbatch.utils import convert_to_date
from dateutil import tz
# executes convert_to_date but overrides arguments so that timezone is enforced to utc
if "timezone" in kwargs:
del kwargs["timezone"]
return convert_to_date(timezone=tz.tzutc(), *args, **kwargs)
return mocker.patch("awsbatch." + module_under_test + ".convert_to_date", wraps=_convert_to_date_utc)
@pytest.fixture()
def boto3_stubber(request, mocker):
"""
Create a function to easily mock boto3 clients.
To mock a boto3 service simply pass the name of the service to mock and
the mocked requests, where mocked_requests is an object containing the method to mock,
the response to return and the expected params for the boto3 method that gets called.
The function makes use of botocore.Stubber to mock the boto3 API calls.
Multiple boto3 services can be mocked as part of the same test.
"""
__tracebackhide__ = True
created_stubbers = []
mocked_clients = {}
region = "us-east-1"
# Mock Boto3ClientFactory in the module under test.
# Use a side_effect to allow mocking multiple clients in the same test function.
module_under_test = request.module.__name__.replace("test_", "")
mocked_client_factory = mocker.patch("awsbatch." + module_under_test + ".Boto3ClientFactory", autospec=True)
mocked_client_factory.return_value.get_client.side_effect = lambda x: mocked_clients[x]
mocked_client_factory.return_value.region = region
def _boto3_stubber(service, mocked_requests):
client = boto3.client(service, region)
stubber = Stubber(client)
# Save a ref to the stubber so that we can deactivate it at the end of the test.
created_stubbers.append(stubber)
# Attach mocked requests to the Stubber and activate it.
if not isinstance(mocked_requests, list):
mocked_requests = [mocked_requests]
for mocked_request in mocked_requests:
stubber.add_response(
mocked_request.method, mocked_request.response, expected_params=mocked_request.expected_params
)
stubber.activate()
# Add stubber to the collection of mocked clients. This allows to mock multiple clients.
# Mocking twice the same client will replace the previous one.
mocked_clients[service] = client
return client
# yield allows to return the value and then continue the execution when the test is over.
# Used for resources cleanup.
yield _boto3_stubber
# Assert that all mocked requests were consumed and deactivate all stubbers.
for stubber in created_stubbers:
stubber.assert_no_pending_responses()
stubber.deactivate()
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] |
examples/interconnector_constant_loss_percentage.py | dec-heim/nempy | 24 | 77545 | <reponame>dec-heim/nempy
import pandas as pd
from nempy import markets
# The only generator is located in NSW.
unit_info = pd.DataFrame({
'unit': ['A'],
'region': ['NSW'] # MW
})
# Create a market instance.
market = markets.SpotMarket(unit_info=unit_info, market_regions=['NSW', 'VIC'])
# Volume of each bids.
volume_bids = pd.DataFrame({
'unit': ['A'],
'1': [100.0] # MW
})
market.set_unit_volume_bids(volume_bids)
# Price of each bid.
price_bids = pd.DataFrame({
'unit': ['A'],
'1': [50.0] # $/MW
})
market.set_unit_price_bids(price_bids)
# NSW has no demand but VIC has 90 MW.
demand = pd.DataFrame({
'region': ['NSW', 'VIC'],
'demand': [0.0, 90.0] # MW
})
market.set_demand_constraints(demand)
# There is one interconnector between NSW and VIC. Its nominal direction is towards VIC.
interconnectors = pd.DataFrame({
'interconnector': ['little_link'],
'to_region': ['VIC'],
'from_region': ['NSW'],
'max': [100.0],
'min': [-120.0]
})
market.set_interconnectors(interconnectors)
# The interconnector loss function. In this case losses are always 5 % of line flow.
def constant_losses(flow):
return abs(flow) * 0.05
# The loss function on a per interconnector basis. Also details how the losses should be proportioned to the
# connected regions.
loss_functions = pd.DataFrame({
'interconnector': ['little_link'],
'from_region_loss_share': [0.5], # losses are shared equally.
'loss_function': [constant_losses]
})
# The points to linearly interpolate the loss function between. In this example the loss function is linear so only
# three points are needed, but if a non linear loss function was used then more points would be better.
interpolation_break_points = pd.DataFrame({
'interconnector': ['little_link', 'little_link', 'little_link'],
'loss_segment': [1, 2, 3],
'break_point': [-120.0, 0.0, 100]
})
market.set_interconnector_losses(loss_functions, interpolation_break_points)
# Calculate dispatch.
market.dispatch()
# Return interconnector flow and losses.
print(market.get_interconnector_flows())
# interconnector flow losses
# 0 little_link 92.307692 4.615385
# Understanding the interconnector flows: Losses are modelled as extra demand
# in the regions on either side of the interconnector, in this case the losses
# are split evenly between the regions. All demand in VIC must be supplied
# across the interconnector, and losses in VIC will add to the interconnector
# flow required, so we can write the equation:
#
# flow = vic_demand + flow * loss_pct_vic
# flow - flow * loss_pct_vic = vic_demand
# flow * (1 - loss_pct_vic) = vic_demand
# flow = vic_demand / (1 - loss_pct_vic)
#
# Since interconnector losses are 5% and half occur in VIC the
# loss_pct_vic = 2.5%. Thus:
#
# flow = 90 / (1 - 0.025) = 92.31
#
# Knowing the interconnector flow we can work out total losses
#
# losses = flow * loss_pct
# losses = 92.31 * 0.05 = 4.62
# Return the total dispatch of each unit in MW.
print(market.get_unit_dispatch())
# unit service dispatch
# 0 A energy 94.615385
# Understanding dispatch results: Unit A must be dispatch to
# meet supply in VIC plus all interconnector losses, therefore
# dispatch is 90.0 + 4.62 = 94.62.
# Return the price of energy in each region.
print(market.get_energy_prices())
# region price
# 0 NSW 50.000000
# 1 VIC 52.564103
# Understanding pricing results: The marginal cost of supply in NSW is simply
# the cost of unit A's bid. However, the marginal cost of supply in VIC also
# includes the cost of paying for interconnector losses.
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src/coolbeans/utils.py | runarp/coolbeans | 5 | 150850 | <reponame>runarp/coolbeans
import typing
import pathlib
import logging
import importlib
import pprint
import yaml
logger = logging.getLogger(__name__)
def get_project_root() -> pathlib.Path:
"""Returns project root folder."""
return pathlib.Path(__file__).parent
def logging_config(config_file=None, level=logging.INFO):
if not config_file:
local_file = pathlib.Path('logging.yaml')
if local_file.exists():
config_file = local_file
# Fall back to our internal format
if not config_file:
config_file = pathlib.Path(__file__).parent.joinpath("logging.yaml")
config_file = pathlib.Path(config_file)
assert config_file.exists(), f"Unable to find {config_file}"
with config_file.open("r") as fil:
config = yaml.full_load(fil)
config.setdefault(
'loggers',
{'coolbeans': {}})['coolbeans']['level'] = level
import logging.config
logging.config.dictConfig(config)
def safe_plugin(func: typing.Callable) -> typing.Callable:
# We might want to pull the logger out of the func module?
DEBUG_CONTEXT = {}
try:
DEBUG_CONTEXT = getattr(importlib.import_module(func.__module__), 'DEBUG_CONTEXT', {})
log = importlib.import_module(func.__module__).logger
except AttributeError:
log = logger
def do_work(*args):
log.info(f"Loading Plugin {func.__name__}")
try:
return func(*args)
except Exception as e:
log.exception(f"{func.__name__} {pprint.pformat(DEBUG_CONTEXT)}")
raise
return do_work
def get_setting(key, settings):
"""Returns the first item from the setting list if only one item"""
if key in settings:
value = settings[key]
if isinstance(value, list):
if len(value) == 1:
return value[0]
else:
return value
return value
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benchmarkt/AlgoConvolv20.py | zwakrim/mastethesis | 0 | 70806 | <filename>benchmarkt/AlgoConvolv20.py
import cv2
import sys
import time
import numpy as np
import jsonlines
import datetime
import platform
def convolvimg(width , heigh, fpsArray):
video_capture = cv2.VideoCapture(camera)
video_capture.set(3,width)
video_capture.set(4,heigh)
font = cv2.FONT_HERSHEY_SIMPLEX
color = (0, 255, 0)
frames = 0
tick = 0
fps =0
i=0
global totalCalcTime
totalCalcTime=0
start = time.time()
while (time.time() - start <= timeout):
ret, frame = video_capture.read()
frames = frames +1
end = time.time()
seconds = end- start
#print(frame.shape)
if seconds-tick >= 1:
tick = tick + 1
fps = frames
fpsArray.append(fps)
#fpsArray[i]=fps
i=i+1
frames = 0
#hsv hue sat value
#hsv = cv2.cvtColor(frame,cv2.COLOR_BGR2HSV) #convert to hsv color
#lower_color= np.array([150,150,50])
#upper_color= np.array([180,255,255])
#mask = cv2.inRange(hsv,lower_color,upper_color)
#result = cv2.bitwise_and(frame,frame,mask=mask)
#blur= cv2.medianBlur(frame,5,0)
#median = cv2.medianBlur(result,15)
beginCalcTime = time.time()
kernel = np.ones((20,20),np.float32)/400
filter = cv2.filter2D(frame,-1,kernel)
endCalcTime = time.time() - beginCalcTime
totalCalcTime = totalCalcTime + endCalcTime
cv2.putText(frame, "FPS: {}" .format(fps), (15,80) ,font,1,color)
cv2.putText(filter, "FPS: {}" .format(fps), (15,80) ,font,1,color)
cv2.imshow('original',frame)
cv2.imshow('filtered',filter)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cv2.destroyAllWindows()
video_capture.release()
cascPath = sys.argv[1]
faceCascade = cv2.CascadeClassifier(cascPath)
camera= int(sys.argv[2])
timeout = int(sys.argv[3])
width= int(sys.argv[4])
height = int(sys.argv[5])
fpsArrayshared2 = []
if __name__ == '__main__':
beginTime = time.time()
convolvimg(width,height,fpsArrayshared2)
endTime = time.time() - beginTime
#print("fps,"+",".join(str(x) for x in fpsArrayshared2)+ ",")
timesnow = datetime.datetime.now().strftime('_%Y_%m_%d_%H_%M_%S')
filename = 'result/'+ "AlgoConvolution20_python_"+str(width) + str(timesnow)+ '.json'
with jsonlines.open(filename,mode='w') as outputfile:
counter =1
for item in fpsArrayshared2:
result ={}
result["algoritme"]= "Convolution20_python"
result["fps"] = item
result["Type"] = "Python"
result["Second"] = counter
result["resolution"] = width
result["ratioCalTime"] = totalCalcTime/endTime * 100
result["node"] = platform.node ()
counter = counter +1
outputfile.write(result)
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] |
py/liberliber_download.py | DavidGigli/gender-literature-ita | 1 | 173075 | import time
from selenium import webdriver
in_autori=open("/home/masterbd/progetto/autori+wiki_finito.txt","r").readlines()
in_url=open("/home/masterbd/progetto/autori_a_z.txt","r").readlines()
lista_url=[]
autori=[x.split("|") for x in in_autori]
url=[x.split("|") for x in in_url]
#join=[x+y for x in in_autori for y in in_url if (x.split("|")[1]==y.split("|")[0] and (int(x.split("|")[3].strip())>1799 and (x.split("|")[3].strip()=="italiano" or x.split("|")[3].strip()=="italiana")))]
join=[x.rstrip()+" | "+y.split("|")[1] for x in in_autori for y in in_url if (x.split("|")[1].strip()==y.split("|")[0].strip())]
italian=[x for x in join if (x.split("|")[4].strip()=="italiano" or x.split("|")[4].strip()=="italiana")]
print(italian[1])
epoc=[]
for item in italian:
if item.split("|")[3].strip()=="":
print(item)
elif int(item.split("|")[3].strip())>1799:
epoc.append(item)
print(epoc)
out_aut=open("/home/masterbd/progetto/elenco_autori.txt","w")
for item in epoc:
out_aut.write(item)
out_aut.close()
#for item in join
#join=[x.split("|")[0].strip() for x in in_autori if (int(x.split("|")[3].strip())>1799 and (x.split("|")[3].strip()=="italiano" or x.split("|")[3].strip()=="italiana"))]
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scarypi.py | 0x24elk/ScaryPi | 0 | 1604700 | <gh_stars>0
#!/usr/bin/python
"""Shows animated 'eyes' on two 8x8 LED matrices.
Matrices are driven by a MAX7219 or similar. We interface
with them through the luma.led_matrix library.
For local development without hardware try something like:
./scarypi.py -d pygame --transform=led_matx --width 16 --height 8
For actual deployment with hardware (controlled through GPIO):
./scarypi.py -d max7219 --width 16 --height 8 \
--interface spi --block-orientation=90
"""
import sys
import datetime
import random
import time
from PIL import Image
from luma.core import cmdline
from luma.core.interface.serial import spi, noop
from luma.core.render import canvas
from luma.core.virtual import viewport
class Point(object):
"""A point, because a tuple is soo yesterday."""
def __init__(self, x, y):
self.x = x
self.y = y
def __str__(self):
return "(%s, %s)" % (self.x, self.y)
class Animation(object):
"""Interface for an animation."""
def __init__(self):
"""Creates a new animation."""
self.start = None # The start time, once begun.
self.done = False
def begin(self, now):
"""Starts the animation at now milliseconds."""
self.start = now
def tick(self, now):
"""Performs a step of the animation based on the current time."""
class LinearAnimation(Animation):
"""Based class for linear animations."""
def __init__(self, duration_ms):
"""Creates a new animation of length duration_ms milliseconds."""
Animation.__init__(self)
self.duration_ms = duration_ms
def tick(self, now):
"""Performs a step of the animation based on the current time."""
Animation.tick(self, now)
dt_timedelta = (now - self.start)
dt = dt_timedelta.total_seconds() * 1000
if dt <= 0:
return # Bail if we're called too fast or going back in time.
if dt <= self.duration_ms:
self._animate(dt / self.duration_ms)
else:
self._animate(1.0)
self.done = True
def _animate(self, pct):
"""Overwrite in subclasses to performs a step, based on a percentage completion."""
class AnimationGroup(Animation):
"""Plays a group of Animations in parallel until all are done."""
def __init__(self, *args):
"""Initializes the animation with a list of animations."""
Animation.__init__(self)
self.animations = args
self.done = False
def begin(self, now):
Animation.begin(self, now)
for a in self.animations:
a.begin(now)
def tick(self, now):
Animation.tick(self, now)
all_done = True
for a in self.animations:
a.tick(now)
if not a.done:
all_done = False
self.done = all_done
class AnimationSequence(Animation):
"""Plays a set of Animations in sequence."""
def __init__(self, *args):
Animation.__init__(self)
self.animations = list(args)
self.active = None
def tick(self, now):
"""Advances the head animation in the queue, removing done ones."""
Animation.tick(self, now)
# End current animation, if done.
if self.active and self.active.done:
self.active = None
# Pop next animation from queue and start, if none.
if not self.active:
if self.animations:
self.active = self.animations.pop(0)
self.active.begin(now)
return
# No more animations => done.
if not self.active:
self.done = True
return
self.active.tick(now)
class Look(LinearAnimation):
"""An animation moving the pupil of an Eye."""
def __init__(self, eye, where, duration_ms=200):
"""Moves the eyeball to a given Point where."""
LinearAnimation.__init__(self, duration_ms)
self.eye = eye
self.origin = eye.pupil
self.dest = where
self.dx = self.dest.x - self.origin.x
self.dy = self.dest.y - self.origin.y
if self.dx == 0 and self.dy == 0:
self.done = True
def _animate(self, pct):
if self.done:
return
curr = Point(int(self.origin.x + (self.dx * pct)), int(self.origin.y + (self.dy * pct)))
self.eye._look(curr)
class Blink(LinearAnimation):
"""An animation blinking an Eye."""
def __init__(self, eye, duration_ms=500):
"""Blinks the eye in duration_ms"""
LinearAnimation.__init__(self, duration_ms)
self.eye = eye
self.eyelid = 0 # Offset of the eyelids, 0=open, 3=closed
def _animate(self, pct):
if self.done:
return
# Close eyelids 0->4 in first half of animation, then re-open.
if (pct < 0.5):
offset = 4 * (pct / 0.49) + 0.5
self.eye._eyelids(int(offset))
else:
offset = 4 - (4 * ((pct - 0.5) / 0.49) + 0.5)
self.eye._eyelids(int(offset))
# Ensure eyes fully open again at end of animation.
if pct >= 1.0:
self.eye._eyelids(-1)
return
class CrossEyes(AnimationSequence):
"""Crosses the eyes."""
def __init__(self, left, right, duration_ms=3000):
ms = duration_ms / 3
AnimationSequence.__init__(self,
AnimationGroup(left.look(Point(6, 4), ms), right.look(Point(2, 4), ms)),
Wait(ms),
AnimationGroup(left.look(Point(4, 4), ms), right.look(Point(4, 4), ms))
)
class MethEyes(AnimationSequence):
"""Inverse 'cross eyes', looking out."""
def __init__(self, left, right, duration_ms=3000):
ms = duration_ms / 3
AnimationSequence.__init__(self,
AnimationGroup(left.look(Point(2, 4), ms), right.look(Point(6, 4), ms)),
Wait(ms),
AnimationGroup(left.look(Point(4, 4), ms), right.look(Point(4, 4), ms))
)
class CrazyBlink(AnimationSequence):
"""Blinks left eye, then right."""
def __init__(self, left, right, duration_ms=1500):
ms = duration_ms / 2
AnimationSequence.__init__(self,
left.blink(ms),
right.blink(ms)
)
class LazyEye(AnimationSequence):
"""Lowers pupil of a single eye only."""
def __init__(self, eye, duration_ms=2000):
ms = duration_ms / 3
AnimationSequence.__init__(self,
eye.look(Point(4, 6), ms * 2), # Lower slowly
eye.look(Point(4, 4), ms), # Raise quickly
)
class CrazySpin(AnimationSequence):
"""'Spins' pupil horizontally with wraparound."""
def __init__(self, left, right, duration_ms=400):
times = 2
ms = duration_ms / (times*8)
a = []
# Just keep moving to the left, as the Eye class handles wrapping.
for i in range(0, times*8):
x = 4 - i
a.append(AnimationGroup(left.look(Point(x, 4), ms), right.look(Point(x, 4), ms)))
AnimationSequence.__init__(self, *a)
class RoundSpin(AnimationSequence):
"""Spins the eyeballs of both eyes in circles."""
def __init__(self, left, right, duration_ms=400):
times = 2
ms = duration_ms / (times*13 + 1)
a = [AnimationGroup(left.look(Point(6, 4), ms), right.look(Point(2, 4), ms))]
for i in range(times):
a = a + [
AnimationGroup(left.look(Point(6, 4), ms), right.look(Point(2, 4), ms)),
AnimationGroup(left.look(Point(6, 3), ms), right.look(Point(2, 3), ms)),
AnimationGroup(left.look(Point(5, 2), ms), right.look(Point(3, 2), ms)),
AnimationGroup(left.look(Point(4, 2), ms), right.look(Point(4, 2), ms)),
AnimationGroup(left.look(Point(3, 2), ms), right.look(Point(5, 2), ms)),
AnimationGroup(left.look(Point(2, 3), ms), right.look(Point(6, 3), ms)),
AnimationGroup(left.look(Point(2, 4), ms), right.look(Point(6, 4), ms)),
AnimationGroup(left.look(Point(2, 5), ms), right.look(Point(6, 5), ms)),
AnimationGroup(left.look(Point(3, 6), ms), right.look(Point(5, 6), ms)),
AnimationGroup(left.look(Point(4, 6), ms), right.look(Point(4, 6), ms)),
AnimationGroup(left.look(Point(5, 6), ms), right.look(Point(3, 6), ms)),
AnimationGroup(left.look(Point(6, 5), ms), right.look(Point(2, 5), ms)),
AnimationGroup(left.look(Point(6, 4), ms), right.look(Point(2, 4), ms))
]
AnimationSequence.__init__(self, *a)
class GlowEyes(LinearAnimation):
"""Glows the eyes; well, rather the device."""
def __init__(self, device, duration_ms=300):
"""Blinks the eye in duration_ms"""
LinearAnimation.__init__(self, duration_ms)
self.device = device
def _animate(self, pct):
if self.done:
return
# Increase contrast 30->150 in first half of animation, then bring down again.
if (pct < 0.5):
c = int(30 + 120 * (pct / 0.49))
self.device.contrast(c)
else:
c = int(150 - 120 * ((pct - 0.5) / 0.49))
self.device.contrast(c)
# Ensure eyes fully open again at end of animation.
if pct >= 1.0:
self.device.contrast(30)
class Wait(LinearAnimation):
"""An animation doing nothing."""
def __init__(self, eye, duration_ms=300):
"""Waits for duration_ms"""
LinearAnimation.__init__(self, duration_ms)
class Eye(object):
"""A single 8x8 eye we animate and draw on our LED matrix."""
# Basic eyeball template (without a pupil).
eye_ball = [
0b00111100,
0b01111110,
0b11111111,
0b11111111,
0b11111111,
0b11111111,
0b01111110,
0b00111100
]
def __init__(self):
"""Initializes the eye."""
self.pixels = bytearray(Eye.eye_ball)
# The center of the pupil, so 4,4 is looking straight ahead.
self.pupil = Point(4,4)
# The offset of the eyelid(s) from the top/bottom. < 0 for fully open.
self.eyelids = -1
def _on(self, x, y):
"""Flips the pixel at x,y on. Wraps if x/y out of bounds."""
y = y % 8
x = x % 8
self.pixels[y] = self.pixels[y] | (0b00000001 << (7 - x))
def _off(self, x, y):
"""Flips the pixel at x,y off. Wraps if x/y out of bounds."""
y = y % 8
x = x % 8
self.pixels[y] = self.pixels[y] & ~(0b00000001 << (7 - x))
def _row_on(self, y):
"""Flips the whole row at y on. Wraps if y out of bounds."""
y = y % len(self.pixels)
self.pixels[y] = 0b11111111
def _row_off(self, y):
"""Flips the whole row at y off. Wraps if y out of bounds."""
y = y % len(self.pixels)
self.pixels[y] = 0b00000000
def _look(self, pos):
"""Immediately moves the pupil of the eyeball to pos."""
self.pupil = pos
self.pupil.x = self.pupil.x % 8
self.pupil.y = self.pupil.y % 8
def _eyelids(self, offset):
"""Moves the eyelids to the given offset, -1=open, 3=closed."""
self.eyelids = max(-1, min(offset, 3))
def look(self, pos, duration_ms=300):
"""Returns an animation, moving the puil to pos in duration_ms."""
return Look(self, pos, duration_ms)
def blink(self, duration_ms=500):
"""Returns an animation, blinking the eye in duration_ms."""
return Blink(self, duration_ms)
def image(self):
"""Renders the current state of the eye into an 8x8 monochrome image."""
self.pixels = bytearray(Eye.eye_ball)
# Draw pupil
self._off(self.pupil.x-1,self.pupil.y-1)
self._off(self.pupil.x,self.pupil.y-1)
self._off(self.pupil.x-1,self.pupil.y)
self._off(self.pupil.x,self.pupil.y)
# Draw eyelids, if requested.
if self.eyelids >= 0:
for i in xrange(0, self.eyelids + 1):
self._row_off(i)
self._row_off(7-i)
return Image.frombytes('1', (8, 8), bytes(self.pixels))
def get_device(actual_args):
parser = cmdline.create_parser(description='luma.examples arguments')
args = parser.parse_args(actual_args)
if args.config:
# load config from file
config = cmdline.load_config(args.config)
args = parser.parse_args(config + actual_args)
# create device
device = cmdline.create_device(args)
return device
# General animation tick
TICK_SECONDS = 0.1
def render(left, right, device):
"""Renders the current state of the eyes on device."""
with canvas(device) as draw:
draw.bitmap((0, 0), left.image(), fill="white")
draw.bitmap((8, 0), right.image(), fill="white")
def pick_effect(device, left, right):
i = random.randint(0, 6)
if i == 0:
return CrossEyes(left, right)
if i == 1:
return CrazySpin(left, right)
if i == 2:
return MethEyes(left, right)
if i == 3:
return CrazyBlink(left, right)
if i == 4:
return LazyEye(left)
if i == 5:
return RoundSpin(left, right)
return GlowEyes(device)
def animation_loop(device):
left = Eye()
right = Eye()
main_sequence = AnimationSequence()
while(True):
start = datetime.datetime.now()
# Insert the next round of animations, if queue empty.
if main_sequence.done:
animations = []
# Look to a random point
p = Point(random.randint(2,5), random.randint(2,5))
animations.append(
AnimationGroup(left.look(p), right.look(p)))
# Wait 2.5 - 3.5s
animations.append(Wait(random.randint(5,7) * 500))
# Maybe blink
if random.randint(0, 3) == 0:
animations.append(
AnimationGroup(left.blink(), right.blink()))
# Play an effect, if desired.
if random.randint(0, 6) == 0:
animations.append(pick_effect(device, left, right))
main_sequence = AnimationSequence(*animations)
# Animate
main_sequence.tick(start)
render(left, right, device)
# Sleep if we're going too fast.
elapsed = datetime.datetime.now() - start
sleeptime = max(TICK_SECONDS - elapsed.total_seconds(), 0)
time.sleep(sleeptime)
def main():
device = get_device(sys.argv[1:])
device.contrast(30)
animation_loop(device)
if __name__ == "__main__":
try:
main()
except KeyboardInterrupt:
pass
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29889,
1032,
29872,
3032,
6914,
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13,
13,
1990,
350,
2324,
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13579,
1125,
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2744,
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382,
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6278,
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13,
13,
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29923,
3582,
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13579,
20529,
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29907,
2124,
267,
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13579,
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29933,
2324,
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4965,
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13,
1678,
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13,
13,
13,
1990,
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29891,
29923,
4099,
29898,
13579,
20529,
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29871,
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29931,
340,
414,
23449,
309,
310,
263,
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data_structures/disjoint_set/disjoint_set.py | egagraha/python-algorithm | 0 | 2233 | <gh_stars>0
"""
Disjoint set.
Reference: https://en.wikipedia.org/wiki/Disjoint-set_data_structure
"""
class Node:
def __init__(self, data: int) -> None:
self.data = data
self.rank: int
self.parent: Node
def make_set(x: Node) -> None:
"""
Make x as a set.
"""
# rank is the distance from x to its' parent
# root's rank is 0
x.rank = 0
x.parent = x
def union_set(x: Node, y: Node) -> None:
"""
Union of two sets.
set with bigger rank should be parent, so that the
disjoint set tree will be more flat.
"""
x, y = find_set(x), find_set(y)
if x == y:
return
elif x.rank > y.rank:
y.parent = x
else:
x.parent = y
if x.rank == y.rank:
y.rank += 1
def find_set(x: Node) -> Node:
"""
Return the parent of x
"""
if x != x.parent:
x.parent = find_set(x.parent)
return x.parent
def find_python_set(node: Node) -> set:
"""
Return a Python Standard Library set that contains i.
"""
sets = ({0, 1, 2}, {3, 4, 5})
for s in sets:
if node.data in s:
return s
raise ValueError(f"{node.data} is not in {sets}")
def test_disjoint_set() -> None:
"""
>>> test_disjoint_set()
"""
vertex = [Node(i) for i in range(6)]
for v in vertex:
make_set(v)
union_set(vertex[0], vertex[1])
union_set(vertex[1], vertex[2])
union_set(vertex[3], vertex[4])
union_set(vertex[3], vertex[5])
for node0 in vertex:
for node1 in vertex:
if find_python_set(node0).isdisjoint(find_python_set(node1)):
assert find_set(node0) != find_set(node1)
else:
assert find_set(node0) == find_set(node1)
if __name__ == "__main__":
test_disjoint_set()
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] |
uap/post/forms.py | Tyromancer/UAP-Application-Platform-Django | 0 | 42387 | from django import forms
from django.forms import ModelForm, CharField
from ckeditor.widgets import CKEditorWidget
from .models import URP, Application
class URPCreateForm(ModelForm):
"""Form for URP creation"""
description = CharField(widget=CKEditorWidget())
class Meta:
model = URP
fields = ['title', 'summary', 'description']
class URPUpdateForm(ModelForm):
"""Form for updating/editing URPs"""
description = CharField(widget=CKEditorWidget())
class Meta:
model = URP
fields = ['summary', 'description']
class ApplicationCreateForm(ModelForm):
"""Form for Application creation"""
class Meta:
model = Application
fields = ['description']
description = CharField()
class ApplicationManageForm(forms.Form):
"""Form for updating application status: Accept or Reject"""
ACTIONS = (
('A', "Accept"),
('R', "Reject"),
)
action = forms.ChoiceField(widget=forms.Select, choices=ACTIONS)
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] |
build/env/lib/python2.7/site-packages/ipython-0.10-py2.7.egg/IPython/platutils_dummy.py | lumanjiao/XLS_BigData | 11 | 87918 | # -*- coding: utf-8 -*-
""" Platform specific utility functions, dummy version
This has empty implementation of the platutils functions, used for
unsupported operating systems.
Authors
-------
- <NAME> <<EMAIL>>
"""
#*****************************************************************************
# Copyright (C) 2008-2009 The IPython Development Team
# Copyright (C) 2001-2007 <NAME> <<EMAIL>>
#
# Distributed under the terms of the BSD License. The full license is in
# the file COPYING, distributed as part of this software.
#*****************************************************************************
# This variable is part of the expected API of the module:
ignore_termtitle = True
def set_term_title(*args,**kw):
"""Dummy no-op."""
pass
def find_cmd(cmd):
"""Find the full path to a command using which."""
return os.popen('which %s' % cmd).read().strip()
def get_long_path_name(path):
"""Dummy no-op."""
return path
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gcn/etc/dbconfig.py | kalon33/divine | 11 | 103502 | #
# COPYRIGHT (C) 2002-2011 <NAME>
#
"""
.. module:: dbconfig
:platform: Unix, Windows, MacOSX
:synopsis: Configuration for Database connections
.. moduleauthor:: <NAME> (<EMAIL>); modified by <EMAIL>
The module defines a dictionary *DBCONFIG* that provides the parameters needed
to connect to various databases that are used in the Genome Commons Navigator.
The dictionary has as key the name of the resource for which a db connection
exist (e.g resources are REFGENE, REFMRNA). The value for each key is also
a dictionary with the following keys
- db: The database type (sqlite3, postgres, mysql, ...)
- name: Name of the database. For sqlite3 this the fully qualified
filename of the database
- host: The name (or IP Number) of the host on which the database is
deployed
- port: The port through which the database connection is available
- user: The login name for the database
- password: The password corresponding to the `user` login.
The parameters `host`, `port`, `user` and `password` may all be ignored for
sqlite3 and similar databases
"""
import os
from gcn.config import lib_config
_LOCALDIR = '/opt/db'
def set_localdir():
"""Set the local database directory from the enviornmental variable
GCN_DB_DIR"""
local = lib_config.gcn_path('GCN_DB_DIR')
if local is not None:
global _LOCALDIR
_LOCALDIR = local
set_localdir()
DBCONFIG = {
'REFMRNA': {'db': 'sqlite3',
'name': os.path.join(_LOCALDIR, 'refmrna'),
'tables':[],
'port': None,
'host': None,
'user': None,
'password': None,
},
'REFGENE': {'db': 'sqlite3',
'name': os.path.join(_LOCALDIR, 'refgene'),
'tables':[],
'port': None,
'host': None,
'user': None,
'password': None,
},
'GENEONTOLOGY': {'db': 'sqlite3',
'name': os.path.join(_LOCALDIR, 'geneontology'),
'tables':[],
'port': None,
'host': None,
'user': None,
'password': None,
},
'MIRNA': {'db': 'sqlite3',
'name': os.path.join(_LOCALDIR, 'mirna'),
'tables':[],
'port': None,
'host': None,
'user': None,
'password': None,
},
'UTRDB': {'db': 'sqlite3',
'name': os.path.join(_LOCALDIR, 'utrdb'),
'tables':[],
'port': None,
'host': None,
'user': None,
'password': None,
},
'REGULOME': {'db': 'sqlite3',
'name': os.path.join(_LOCALDIR, 'regulomedb'),
'tables':[],
'port': None,
'host': None,
'user': None,
'password': None,
},
'KGDB': {'db': 'sqlite3',
'name': os.path.join(_LOCALDIR, 'kgdb'),
'tables':[],
'port': None,
'host': None,
'user': None,
'password': None,
},
'DBSNP': {'db': 'sqlite3',
'name': os.path.join(_LOCALDIR, 'dbsnp'),
'port': None,
'host': None,
'user': None,
'password': None,
},
'ESP': {'db': 'sqlite3',
'name': os.path.join(_LOCALDIR, 'esp'),
'port': None,
'host': None,
'user': None,
'password': None,
},
'EXAC': {'db': 'sqlite3',
'name': os.path.join(_LOCALDIR, 'exac'),
'port': None,
'host': None,
'user': None,
'password': None,
},
'HGMDDB': {'db': 'sqlite3',
'name': os.path.join(_LOCALDIR, 'hgmd'),
'port': None,
'host': None,
'user': None,
'password': None,
},
'CLINVITAE': {'db': 'sqlite3',
'name': os.path.join(_LOCALDIR,'clinvitae'),
'port': None,
'host': None,
'user': None,
'password': None,
},
'COSMIC': {'db': 'sqlite3',
'name': os.path.join(_LOCALDIR,'cosmic'),
'port': None,
'host': None,
'user': None,
'password': None,
},
'CLINVARDB': {'db': 'sqlite3',
'name': os.path.join(_LOCALDIR, 'clinvardb'),
'port': None,
'host': None,
'user': None,
'password': None,
},
'CLNPHESNP': {'db': 'sqlite3',
'name': os.path.join(_LOCALDIR, 'clnphesnpdb'),
'port': None,
'host': None,
'user': None,
'password': None,
},
'OMIM': {'db': 'sqlite3',
'name': os.path.join(_LOCALDIR, 'mimdb'),
'port': None,
'host': None,
'user': None,
'password': None,
},
'NSFP': {'db': 'sqlite3',
'name': os.path.join(_LOCALDIR, 'nsfpdb'),
'port': None,
'host': None,
'user': None,
'password': None,
},
'SPLICE': {'db': 'sqlite3',
'name': os.path.join(_LOCALDIR, 'splicedb'),
'port': None,
'host': None,
'user': None,
'password': None,
},
'GENCODE': {'db': 'sqlite3',
'name': os.path.join(_LOCALDIR, 'gencode'),
'port': None,
'host': None,
'user': None,
'password': None,
},
'GENCODEMRNA': {'db': 'sqlite3',
'name': os.path.join(_LOCALDIR, 'gencodemrna'),
'port': None,
'host': None,
'user': None,
'password': None,
},
'INTERPRO': {'db': 'sqlite3',
'name': os.path.join(_LOCALDIR, 'interpro'),
'port': None,
'host': None,
'user': None,
'password': None,
},
}
def configure_db(resource, db, name, port=None, host=None, user=None,
password=None):
"""Configure a database connection.
Args:
resource (str): Name of the resource (e.g REFMRNA) for which the
database information is being configured
name (str): Name/Filename of the database
host (str): Name of the host on which the database is deployed
port (integer): Port through which the database is to be accessed
user (str): Login id to connect to the database
password (str): Password for the `<PASSWORD>` to <PASSWORD> the database
Returns:
None. Configures the database connection for the resource.
This method is useful when individual users want to use custom resources
instead of the system defaults.
"""
DBCONFIG[resource] = {'db': db, 'name': name, 'port': port,
'host': host, 'user': user, 'password': password}
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] |
covid19/segmentation/crop_bbox.py | salvacarrion/mltests | 0 | 166493 | <filename>covid19/segmentation/crop_bbox.py
import glob
import json
import os
from pathlib import Path
import cv2
import numpy as np
import pandas as pd
import tqdm
from matplotlib import pyplot as plt
def read_img(filename):
img = cv2.imread(filename, 0)
img = img.astype(np.uint8)
return img
def show_img(img, cmap="gray", title=""):
plt.imshow(img, cmap=cmap)
plt.title(title)
plt.show()
def binarize(img):
thr_val, img = cv2.threshold(img, 0, 255, cv2.THRESH_OTSU)
return img
def get_bounding_boxes(img, threshold_area=1, scaling=1.0):
# Find contours
ctrs, _ = cv2.findContours(img, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
# Clean areas
cleaned_ctrs = []
for ctr in ctrs:
area = cv2.contourArea(ctr)
if area > threshold_area:
cleaned_ctrs.append(ctr)
# Bboxes
bboxes = []
ctrs = cleaned_ctrs
for ctr in ctrs:
x, y, w, h = cv2.boundingRect(ctr)
values = [v / scaling for v in [x, y, w, h]]
bboxes.append(values)
# Concat bboxes
ctrs = np.concatenate(ctrs)
x, y, w, h = cv2.boundingRect(ctrs)
concat_bboxes = [[v / scaling for v in [x, y, w, h]]]
return bboxes, concat_bboxes
def draw_bounding_boxes(img, boxes, scaling=1.0, width=2): # 256=>w=2; 512=>w=5; large=>w=10
new_img = np.array(img)
new_img = cv2.cvtColor(new_img, cv2.COLOR_GRAY2RGB)
# Draw bounding boxes
for box in boxes:
top_left = (int(box[0] * scaling), int(box[1] * scaling))
bottom_right = (int(box[0] * scaling + box[2] * scaling), int(box[1] * scaling + box[3] * scaling))
cv2.rectangle(new_img, top_left, bottom_right, (0, 255, 0), width)
return new_img
def pad_img(img):
max_side = max(*img.shape)
img_padded = np.zeros((max_side, max_side), np.uint8)
ax, ay = (max_side - img.shape[1]) // 2, (max_side - img.shape[0]) // 2
img_padded[ay:img.shape[0] + ay, ax:ax + img.shape[1]] = img
return img_padded
def expand_bboxes(bboxes, margin_factor):
new_bboxes = []
for (x, y, w, h) in bboxes:
x, y = x * (1.0 - margin_factor), y * (1.0 - margin_factor)
w, h = w * (1.0 + margin_factor), h * (1.0 + margin_factor)
new_bboxes.append([x, y, w, h])
return new_bboxes
def get_all_masks_files(masks_dir, pred_masks_dir):
masks_files = [file for file in
glob.glob(os.path.join(masks_dir, "*.png"))]
pred_masks_files = [file for file in
glob.glob(os.path.join(pred_masks_dir, "*.png"))]
return masks_files, pred_masks_files
def main(base_path=".", target_size=512, margin_factor=0.05):
# path = os.path.join(base_path, "masks256_pred", "sub-S10880_ses-E18932_run-1.png") # Testing
# Create output not exists
images_output_path = os.path.join(base_path, f"images{target_size}_crop")
Path(images_output_path).mkdir(parents=True, exist_ok=True)
# Get files
raw_images_dir = os.path.join(base_path, "images_raw")
df = pd.read_csv(os.path.join(base_path, "bboxes.csv"))
# Process masks
for i, row in tqdm.tqdm(df.iterrows(), total=len(df)):
bboxes, interest_region = json.loads(row["bboxes"]), json.loads(row["interest_region"])
file = row["filepath"]
fname = os.path.split(file)[1]
# Read image
img = read_img(os.path.join(raw_images_dir, file))
# show_img(img)
# Pad image
max_side = max(*img.shape)
img = pad_img(img)
# show_img(img)
# Expand bboxes
bboxes = expand_bboxes(bboxes, margin_factor=margin_factor)
interest_region = expand_bboxes(interest_region, margin_factor=margin_factor)
# # Draw bboxes
# img_bboxes = draw_bounding_boxes(img, bboxes, scaling=max_side)
# show_img(img_bboxes)
# Crop
x, y, w, h = [int(v * max_side) for v in interest_region[0]]
img = img[y:y + h, x:x + w]
# show_img(img)
# Pad image (again)
img = pad_img(img)
# show_img(img)
# Resize
img = cv2.resize(img, (target_size, target_size), interpolation=cv2.INTER_LANCZOS4)
# show_img(img)
# Save image
cv2.imwrite(os.path.join(images_output_path, fname), img)
asdasd = 3
print("Done!")
if __name__ == "__main__":
BASE_PATH = "/home/scarrion/datasets/covid19/front"
# Run script
main(base_path=BASE_PATH)
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migrations/versions/1d7903bb7029_.py | fitoskalante/wetribe-backend | 0 | 189272 | """empty message
Revision ID: 1d7903bb<PASSWORD>9
Revises:
Create Date: 2019-12-16 11:35:50.692153
"""
from alembic import op
import sqlalchemy as sa, sqlalchemy_utils
# revision identifiers, used by Alembic.
revision = '<PASSWORD>'
down_revision = None
branch_labels = None
depends_on = None
def upgrade():
# ### commands auto generated by Alembic - please adjust! ###
op.create_table('categories',
sa.Column('id', sa.Integer(), nullable=False),
sa.Column('name', sa.String(), nullable=False),
sa.PrimaryKeyConstraint('id')
)
op.create_table('interests',
sa.Column('id', sa.Integer(), nullable=False),
sa.Column('name', sa.String(), nullable=True),
sa.PrimaryKeyConstraint('id')
)
op.create_table('users',
sa.Column('id', sa.Integer(), nullable=False),
sa.Column('name', sa.String(), nullable=False),
sa.Column('last_name', sa.String(), nullable=True),
sa.Column('description', sa.Text(), nullable=True),
sa.Column('email', sa.String(), nullable=True),
sa.Column('city', sa.String(), nullable=True),
sa.Column('country', sa.String(), nullable=True),
sa.Column('password', sa.String(), nullable=True),
sa.PrimaryKeyConstraint('id')
)
op.create_table('events',
sa.Column('id', sa.Integer(), nullable=False),
sa.Column('creator_id', sa.Integer(), nullable=True),
sa.Column('title', sa.String(), nullable=False),
sa.Column('description', sa.Text(), nullable=True),
sa.Column('image_url', sa.String(), nullable=True),
sa.Column('address', sa.String(), nullable=True),
sa.Column('city', sa.String(), nullable=True),
sa.Column('country', sa.String(), nullable=True),
sa.Column('time', sa.DateTime(), nullable=True),
sa.Column('date', sa.DateTime(), nullable=True),
sa.Column('created_at', sa.DateTime(), nullable=True),
sa.Column('lat', sa.Float(), nullable=True),
sa.Column('lng', sa.Float(), nullable=True),
sa.ForeignKeyConstraint(['creator_id'], ['users.id'], ),
sa.PrimaryKeyConstraint('id')
)
op.create_table('flask_dance_oauth',
sa.Column('id', sa.Integer(), nullable=False),
sa.Column('provider', sa.String(length=50), nullable=False),
sa.Column('created_at', sa.DateTime(), nullable=False),
sa.Column('token', sqlalchemy_utils.types.json.JSONType(), nullable=False),
sa.Column('provider_user_id', sa.String(length=256), nullable=False),
sa.Column('user_id', sa.Integer(), nullable=False),
sa.ForeignKeyConstraint(['user_id'], ['users.id'], ),
sa.PrimaryKeyConstraint('id'),
sa.UniqueConstraint('provider_user_id')
)
op.create_table('token',
sa.Column('id', sa.Integer(), nullable=False),
sa.Column('uuid', sa.String(), nullable=True),
sa.Column('user_id', sa.Integer(), nullable=False),
sa.ForeignKeyConstraint(['user_id'], ['users.id'], ),
sa.PrimaryKeyConstraint('id'),
sa.UniqueConstraint('uuid')
)
op.create_table('userinterests',
sa.Column('id', sa.Integer(), nullable=False),
sa.Column('user_id', sa.Integer(), nullable=True),
sa.Column('interest_id', sa.Integer(), nullable=True),
sa.ForeignKeyConstraint(['interest_id'], ['interests.id'], ),
sa.ForeignKeyConstraint(['user_id'], ['users.id'], ),
sa.PrimaryKeyConstraint('id')
)
op.create_table('attendances',
sa.Column('id', sa.Integer(), nullable=False),
sa.Column('event_id', sa.Integer(), nullable=True),
sa.Column('user_id', sa.Integer(), nullable=True),
sa.ForeignKeyConstraint(['event_id'], ['events.id'], ),
sa.ForeignKeyConstraint(['user_id'], ['users.id'], ),
sa.PrimaryKeyConstraint('id')
)
op.create_table('comments',
sa.Column('id', sa.Integer(), nullable=False),
sa.Column('body', sa.Text(), nullable=False),
sa.Column('event_id', sa.Integer(), nullable=True),
sa.Column('user_id', sa.Integer(), nullable=True),
sa.Column('created_at', sa.DateTime(), nullable=True),
sa.Column('updated_at', sa.DateTime(), server_default=sa.text('now()'), nullable=True),
sa.ForeignKeyConstraint(['event_id'], ['events.id'], ),
sa.ForeignKeyConstraint(['user_id'], ['users.id'], ),
sa.PrimaryKeyConstraint('id')
)
op.create_table('eventcategories',
sa.Column('id', sa.Integer(), nullable=False),
sa.Column('event_id', sa.Integer(), nullable=True),
sa.Column('category_id', sa.Integer(), nullable=True),
sa.ForeignKeyConstraint(['category_id'], ['categories.id'], ),
sa.ForeignKeyConstraint(['event_id'], ['events.id'], ),
sa.PrimaryKeyConstraint('id')
)
# ### end Alembic commands ###
def downgrade():
# ### commands auto generated by Alembic - please adjust! ###
op.drop_table('eventcategories')
op.drop_table('comments')
op.drop_table('attendances')
op.drop_table('userinterests')
op.drop_table('token')
op.drop_table('flask_dance_oauth')
op.drop_table('events')
op.drop_table('users')
op.drop_table('interests')
op.drop_table('categories')
# ### end Alembic commands ###
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2
] |
python全栈/day05/乘法表.py | Ringo-li/python_exercise_100 | 0 | 77801 | i = 1
while i <= 9:
j = 1
while j <= i:
print("{}x{}={}\t".format(j, i, i * j), end='')
j += 1
print()
i += 1 | [
1,
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2
] |
source/Bornholdt.py | StxGuy/Econophysics | 13 | 171921 | # -*- coding: utf-8 -*-
#!/usr/bin/env python
__author__ = """Prof. <NAME>, Ph.D. <<EMAIL>>"""
import os
os.system('clear')
print('.-------------------------------.')
print('| |#')
print('| By.: Prof. <NAME> |#')
print('| |#')
print('| 2021 |#')
print('\'-------------------------------\'#')
print(' ################################')
print('')
print('Importing Libraries:')
import numpy as np
import random as rd
import matplotlib.pyplot as pl
from math import isnan
def neig(i,j,N):
z = []
if (i > 0):
z.append([i-1,j])
if (i < N-1):
z.append([i+1,j])
if (j > 0):
z.append([i,j-1])
if (j < N-1):
z.append([i,j+1])
return np.array(z)
N = 32
J = 1.0
beta = 1.0/1.5
alpha = 4.0
S = np.array([rd.choices([1,-1],k=N) for i in range(N)])
C = np.array([rd.choices([1,-1],k=N) for i in range(N)])
Sn = np.zeros((N,N))
Cn = np.zeros((N,N))
r = []
cauda = []
M = 1
Steps = 100
for it in range(Steps):
Ml = M
M = np.average(S)
for i in range(N):
for j in range(N):
sm = 0
for x in neig(i,j,N):
sm = sm + S[x[0],x[1]]
h = J*sm - alpha*C[i,j]*M
p = 1.0/(1+np.exp(-2*beta*h))
if (rd.random() < p):
Sn[i,j] = 1
else:
Sn[i,j] = -1
if (alpha*S[i,j]*C[i,j]*sm < 0):
Cn[i,j] = -C[i,j]
else:
Cn[i,j] = C[i,j]
S = Sn
C = Cn
rt = np.log10(abs(M))-np.log10(abs(Ml))
if (abs(rt) < 100):
r = np.append(r,rt)
if (rt > 0):
cauda.append(rt)
mi = min(r)
ma = max(r)
#pl.figure(1)
#pl.plot(r)
#pl.axis([0,Steps,-0.1,0.1])
#pl.savefig('../chapters/Chapter_8/figs/src/Bornts.svg')
x = np.linspace(mi,ma,100)
y = []
for ex in x:
y.append(1.0-float(sum(cauda<ex))/len(cauda))
#pl.figure(2)
#pl.loglog(x,y,'.')
#pl.savefig('../chapters/Chapter_8/figs/src/Bornts.svg')
#pl.show()
pl.imshow(S,cmap='gray')
pl.show()
#pl.savefig('../chapters/Chapter_8/figs/src/Born1.svg')
#pl.plot(r)
#pl.axis([0,200,-0.04,0.04])
#pl.savefig('../chapters/Chapter_8/figs/src/Bornts.svg')
#pl.hist(r)
#pl.savefig('../chapters/Chapter_8/figs/src/Bornh.svg')
#pl.show()
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] |
venv/Lib/site-packages/psychopy/demos/coder/stimuli/colorPalette.py | mintzer/pupillometry-rf-back | 0 | 107570 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import absolute_import, division
from psychopy import locale_setup, visual, core
import numpy as np
from psychopy.hardware import keyboard
from psychopy import misc
def createPalette(size):
"""
Creates the color palette array in HSV and returns as RGB
"""
# Create array
hsv = np.ones([size,size,3], dtype=float)
# Set hue
hsv[:,:,0] = np.linspace(0,360, size, endpoint=False)
# Set saturation
for i in range(size):
hsv[:,i, 1] = np.linspace(0, 1, size, endpoint=False)
# Convert to RGB
rgb = misc.hsv2rgb(hsv)
# Make in range 0:1 for image stim
rgb[:][:][:] = (rgb[:][:][:] + 1) / 2
return rgb
def createValue(size):
"""
Creates the value palette array in HSV and returns as RGB
"""
# Create array
hsv = np.zeros([20,size,3], dtype=float)
# Set value
hsv[:,:,2] = np.linspace(0,1, size, endpoint=False)
# Convert to RGB
rgb = misc.hsv2rgb(hsv)
# Make in range 0:1 for image stim
rgb[:][:][:] = (rgb[:][:][:] + 1) / 2
return rgb
# Setup the Window
win = visual.Window(size=[1920, 1080], fullscr=False, units='height')
colorPalette = visual.ImageStim(win=win,name='colorPalette', units='pix',
image=None, mask=None,
texRes=64, depth=0.0)
valuePalette = visual.ImageStim(win=win, name='valuePalette', units='pix',
pos=(0, -250), depth=-1.0)
hueSlider = visual.Slider(win=win, name='hueSlider',
size=(.37, .02), pos=(0, 0.2),
labels=None, ticks=(0, 360), style=['rating'])
satSlider = visual.Slider(win=win, name='satSlider',
size=(.02, .37), pos=(0.2, 0),
labels=None, ticks=(0, 1), style=['rating'])
valSlider = visual.Slider(win=win, name='valSlider',
size=(.37, .02), pos=(0, -0.25),
labels=None, ticks=(0,1), style=['rating'])
visualFeedback = visual.Rect(win=win, name='visualFeedback',
width=(0.15, 0.15)[0], height=(0.15, 0.15)[1],
pos=(0, 0.35),fillColor=[0,0,0], fillColorSpace='hsv',
depth=-6.0)
hsvText = visual.TextStim(win=win, name='hsvText',
text=None, font='Arial',
pos=(.4, 0), height=0.03)
instText = visual.TextStim(win=win, name='instText',
text=("Use the sliders to change:\n---hue (top)\n---"
"saturation (right)\n---value (bottom)"),
font='Arial',
pos=(-.3, 0), height=0.03, wrapWidth=.4,
alignText='left', anchorHoriz='right')
quitText = visual.TextStim(win=win, name='quitText',
text='Press escape to quit to continue',
font='Arial',
pos=(0, -.35), height=0.025, depth=-8.0,
wrapWidth=.4)
paletteSize = 400 # in pixels
valRGB = createValue(paletteSize)
colPalRGB = createPalette(paletteSize)
hueSlider.reset()
satSlider.reset()
valSlider.reset()
colorPalette.setSize([paletteSize,paletteSize])
colorPalette.setImage(colPalRGB)
valuePalette.setSize((paletteSize, 20))
valuePalette.setImage(valRGB)
key_resp = keyboard.Keyboard()
while True:
h = hueSlider.getRating() or 0
s = satSlider.getRating() or 0
v = valSlider.getRating() or 0.5
visualFeedback.fillColor = [h,s,v]
hsvText.text = "Hue: {h:.0f}\nSat: {s:.2f}\nVal: {v:.2f}".format(h=h, s=s, v=v)
colorPalette.draw()
valuePalette.draw()
hueSlider.draw()
satSlider.draw()
valSlider.draw()
visualFeedback.draw()
instText.draw()
hsvText.draw()
quitText.draw()
theseKeys = key_resp.getKeys(keyList=['escape'], waitRelease=False)
if len(theseKeys):
theseKeys = theseKeys[0] # at least one key was pressed
# check for quit:
if "escape" == theseKeys:
win.close()
core.quit()
win.flip() | [
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train_ids.py | Huanzhuo/IA-Net | 2 | 57912 | import os
import torch
import argparse
import datetime
import numpy as np
import torch.optim as optim
from models.resnet import resnet50, Model, resnet50_1d
from losses.loss import ContrastiveLoss_
from torch.optim import lr_scheduler
from torch.utils.data import DataLoader
from dataset.industry_dataset_identify import IndustryDatasetIdentifyDiff, IndustryDatasetIdentify
from sklearn.model_selection import train_test_split
from torch.cuda.amp.grad_scaler import GradScaler
from torch.cuda.amp import autocast
nowTime = datetime.datetime.now().strftime('%Y-%m-%d-%H')
result_dir = './results/pump_slider_fan_valve/all_ids/{}'.format(nowTime)
if not os.path.exists(result_dir):
os.makedirs(result_dir)
def save_model(model, optimizer, step, path):
if len(os.path.dirname(path)) > 0 and not os.path.exists(os.path.dirname(path)):
os.makedirs(os.path.dirname(path))
torch.save({
'model': model,
'model_state_dict': model.state_dict(),
'optimizer_state_dict': optimizer.state_dict(),
'step': step,
# 'amp': amp.state_dict(),
}, path)
def load_model(model, optimizer, path):
checkpoint = torch.load(path)
model.load_state_dict(checkpoint['model_state_dict'])
if optimizer is not None:
checkpoint['optimizer_state_dict']['param_groups'][0]['lr'] = 0.001
optimizer.load_state_dict(checkpoint['optimizer_state_dict'])
step = checkpoint['step']
return step
def valiadate(model, criterion, val_loader):
model.eval()
with torch.no_grad():
total_loss = 0.0
for i, (mix, mix_, status) in enumerate(val_loader):
mix = mix.cuda()
mix_ = mix_.cuda()
status = status.cuda()
features, features_ = model(mix, mix_)
loss = criterion(features, features_, status)
total_loss += loss.item()
return total_loss
def get_files(path):
wav_files = []
for _, _, files in os.walk(path):
for f in files:
if f.split('.')[-1] == 'wav':
wav_files.append(f)
return wav_files
def get_ids(total_path):
train_normal_ids_files = []
val_normal_ids_files = []
for dir in os.listdir(total_path):
if dir.split('_')[0] != "id":
continue
normal_path = total_path + dir + '/normal'
normal_files = get_files(normal_path)
train_normals, val_normal = train_test_split(normal_files, random_state=42, test_size=0.2)
train_normal_ids_files.append(train_normals)
val_normal_ids_files.append(val_normal)
return train_normal_ids_files, val_normal_ids_files
def main(args):
print(args)
# dataset and dataloader
s1_path = '../MIMII/pump/'
s2_path = '../MIMII/slider/'
s3_path = '../MIMII/fan/'
s4_path = '../MIMII/valve/'
sources_path = [s1_path, s2_path, s3_path, s4_path]
train_s1_normal_ids_files, val_s1_normal_ids_files = get_ids(s1_path)
train_s2_normal_ids_files, val_s2_normal_ids_files = get_ids(s2_path)
train_s3_normal_ids_files, val_s3_normal_ids_files = get_ids(s3_path)
train_s4_normal_ids_files, val_s4_normal_ids_files = get_ids(s4_path)
train_normals = [train_s1_normal_ids_files, train_s2_normal_ids_files, train_s3_normal_ids_files, train_s4_normal_ids_files]
val_normals = [val_s1_normal_ids_files, val_s2_normal_ids_files, val_s3_normal_ids_files, val_s4_normal_ids_files]
train_dataset = IndustryDatasetIdentifyDiff(sources_path, train_normals)
val_dataset = IndustryDatasetIdentifyDiff(sources_path, val_normals, n=320)
train_loader = DataLoader(train_dataset, batch_size=args.batch_size, shuffle=True)
val_loader = DataLoader(val_dataset, batch_size=args.batch_size, shuffle=False)
# generate the model
if args.load:
print("Continuing training full model from checkpoint " + str(args.load_model))
model = torch.load('./result_identify/pump_fan_valve/all_ids/model_best.pt')['model']
# model = torch.load('./result/2020-08-20-01/model_best.pt')['model']
else:
model = resnet50_1d(n_spk=4)
model = model.cuda()
# generate optimizer and learning rate scheduler
optimizer = optim.Adam(model.parameters(), lr=args.lr, betas=(0.9, 0.999), weight_decay=5e-4)
clr = lr_scheduler.CosineAnnealingLR(optimizer, 5, eta_min=1e-5)
# use mix precision training, may reduce the accuracy but increase the training speed
# model, optimizer = amp.initialize(model, optimizer, opt_level="O1")
criterion = ContrastiveLoss_()
scaler = GradScaler()
# criterion = CosLoss()
# Set up training state dict that will also be saved into checkpoints
state = {"worse_epochs": 0,
"epochs": 0,
"best_loss": np.Inf,
'step': 0}
print('Start training...')
for i in range(args.epochs):
print("Training one epoch from iteration " + str(state["epochs"]))
model.train()
train_loss = 0.0
for i, (mix, mix_, status) in enumerate(train_loader):
mix = mix.cuda()
mix_ = mix_.cuda()
status = status.cuda()
cur_lr = optimizer.state_dict()['param_groups'][0]['lr']
optimizer.zero_grad()
with autocast():
features, features_ = model(mix, mix_)
loss = criterion(features, features_, status)
train_loss += loss.item()
scaler.scale(loss).backward()
scaler.step(optimizer)
scaler.update()
state['step'] += 1
if i % 20 == 0:
print("{:4d}/{:4d} --- Loss: {:.6f} with learnig rate {:.6f}".format(i, len(train_dataset) // args.batch_size, loss.item(), cur_lr))
clr.step()
val_loss = valiadate(model, criterion, val_loader)
train_loss = train_loss
val_loss = val_loss
print("Validation loss" + str(val_loss))
# EARLY STOPPING CHECK
checkpoint_path = args.model_path + str(state['epochs']) + '.pth'
print("Saving model...")
if val_loss >= state["best_loss"]:
state["worse_epochs"] += 1
else:
print("MODEL IMPROVED ON VALIDATION SET!")
state["worse_epochs"] = 0
state["best_loss"] = val_loss
state["best_checkpoint"] = checkpoint_path
best_checkpoint_path = args.model_path + 'best.pt'
best_state_dict_path = args.model_path + 'best_state_dict.pt'
save_model(model, optimizer, state, best_checkpoint_path)
torch.save(model.state_dict(), best_state_dict_path)
print(state)
state["epochs"] += 1
if state["worse_epochs"] > args.hold_step:
break
last_model = args.model_path + 'last_model.pt'
save_model(model, optimizer, state, last_model)
print("Training finished")
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--model_path', type=str, default='{}/model_'.format(result_dir),
help='Path to save model')
parser.add_argument('--lr', type=float, default=1e-4,
help='initial learning rate')
parser.add_argument('--batch_size', type=int, default=16)
parser.add_argument('--output_size', type=float, default=2.0,
help='Output duration')
parser.add_argument('--sr', type=int, default=16000,
help='Sampling rate')
parser.add_argument('--channels', type=int, default=1,
help="Input channel, mono or sterno, default mono")
parser.add_argument('--load_model', type=str, default='',
help="Path of hdf5 file")
parser.add_argument("--load", type=bool, default=False)
parser.add_argument("--epochs", type=int, default=200,
help="Epochs of half lr")
parser.add_argument("--hold_step", type=int, default=20,
help="Epochs of hold step")
args = parser.parse_args()
main(args)
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] |
vkontakte_photos/parser.py | Andertaker/django-vkontakte-photos | 0 | 148200 | # -*- coding: utf-8 -*-
from datetime import datetime
from vkontakte_api.parser import VkontakteParser, VkontakteParseError
import re
class VkontaktePhotosParser(VkontakteParser):
pass
# def parse_container_date(self, container):
#
# text = container.find('span', {'class': re.compile('^rel_date')})
# if text:
# text = text.text
# else:
# raise VkontakteParseError("Impossible to find date container in %s" % container)
# return datetime(1970,1,1)
#
# return self.parse_date(text)
# def parse_comment(self, content, wall_owner=None):
# from models import Comment
# from vkontakte_users.models import User
#
# remote_id = content['id'][4:]
# try:
# instance = Comment.objects.get(remote_id=remote_id)
# except Comment.DoesNotExist:
# instance = Comment(remote_id=remote_id)
#
# comment_text = content.find('div', {'class': 'fw_reply_text'})
# if comment_text:
# instance.text = comment_text.text
#
# # date
# instance.date = self.parse_container_date(content)
# # likes
# instance.likes = self.parse_container_likes(content, 'like_count fl_l')
#
# # author
# users = content.findAll('a', {'class': 'fw_reply_author'})
# slug = users[0]['href'][1:]
# if wall_owner and wall_owner.screen_name == slug:
# instance.author = wall_owner
# else:
# avatar = content.find('a', {'class': 'fw_reply_thumb'}).find('img')['src']
# name_parts = users[0].text.split(' ')
#
# user = User.remote.get_by_slug(slug)
# if user:
# user.first_name = name_parts[0]
# if len(name_parts) > 1:
# user.last_name = name_parts[1]
# user.photo = avatar
# user.save()
# instance.author = user
#
# if len(users) == 2:
# # this comment is answer
# slug = users[1]['href'][1:]
# if wall_owner and wall_owner.screen_name == slug:
# instance.reply_for = wall_owner
# else:
# instance.reply_for = User.remote.get_by_slug(slug)
# # имя в падеже, аватара нет
# # чтобы получть текст и ID родительского коммента нужно отправить:
# #http://vk.com/al_wall.php
# #act:post_tt
# #al:1
# #post:-16297716_126263
# #reply:1
#
# instance.fetched = datetime.now()
# return instance | [
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353,
12865,
29889,
3707,
580,
13,
29937,
4706,
736,
2777,
2
] |
Python2/Modulo_3_exe_pratico.py | Belaschich/SoulON | 0 | 54623 | <filename>Python2/Modulo_3_exe_pratico.py
"""
1. Crie uma base de dados chamada sistema_escolar_soul_on
2. Crie uma tabela alunos com os campos id, nome, matricula, turma.
3. Alimente a tabela com os seguintes dados:
"""
import mysql.connector
db = mysql.connector.connect(
host = "localhost",
user = "root",
password = "",
database = "sistema_escolar_soul_on"
)
mycursor = db.cursor()
#mycursor.execute("CREATE DATABASE sistema_escolar_soul_on")
#print("Database criada com sucesso!")
#mycursor.execute("CREATE TABLE alunos(id INT AUTO_INCREMENT PRIMARY KEY, name VARCHAR(255), matricula VARCHAR(255), turma VARCHAR(255))")
#print("Tabela criada com sucesso!")
#adicionar = "INSERT INTO alunos (name, matricula, turma) VALUES(%s, %s, %s)"
#val = [
# ("<NAME>", "MAT90551", "BCW22"),
# ("<NAME>", "MAT90552", "BCW22"),
# ("<NAME>", "MAT90553", "BCW22"),
# ("<NAME>", "MAT90554", "BCW23"),
# ("<NAME>", "MAT90555", "BCW23"),
# ("<NAME>", "MAT90556", "BCW24"),
# ("<NAME>", "MAT90557", "BCW25")
#]
#mycursor.executemany(adicionar, val)
#print(mycursor.rowcount, "linha(s) alterada(s)!")
#db.commit()
"""4. Faça as seguintes consultas:
• Liste todos os registros de sua tabela.
• Liste apenas nome e matrícula dos alunos do BCW23.
• Liste apenas o nome dos alunos que tiverem o sobrenome Lima.
"""
#mycursor.execute("SELECT * FROM alunos")
#mycursor.execute("SELECT name FROM alunos WHERE turma = 'BCW23' ")
#adicionar = "SELECT name FROM alunos WHERE name LIKE '%Lima%'"
#mycursor.execute(adicionar)
#myresult = mycursor.fetchall()
#for x in myresult:
# print(x)
'''
5. O aluno <NAME> está na turma errada. Matricule o mesmo no BCW25.
6. O aluno <NAME> desistiu do curso, ele deve ser excluído do sistema.
'''
#adicionar = "UPDATE alunos SET turma = 'BCW25' WHERE name = '<NAME>'"
adicionar = "DELETE FROM alunos WHERE name = '<NAME>'"
mycursor.execute(adicionar)
#db.commit()
print(mycursor.rowcount, "Linha(s) afetada(s)")
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] |
jupyterlab2pymolpysnips/Selection/duplicateObject.py | MooersLab/pymolpysnips | 0 | 162429 | """
cmd.do('create ${1:t4l}, ${2:1lw9};')
"""
cmd.do('create t4l, 1lw9;')
# Description: Duplicate object.
# Source: placeHolder
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1,
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molecool/io/__init__.py | aatishpr/molecool | 0 | 166691 | """
IO sub-package
"""
from .pdb import open_pdb
from .xyz import open_xyz, write_xyz
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1,
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] |
ppq/IR/quantize.py | openppl-public/ppq | 100 | 90660 | <reponame>openppl-public/ppq
from typing import Any, List, Tuple
from ppq.core import (OperationQuantizationConfig, QuantizationStates,
TargetPlatform, TensorQuantizationConfig,
convert_any_to_torch_tensor)
from ppq.quantization.qfunction import BaseQuantFunction
from .base.command import (GraphCommand, GraphCommandType,
QuantizeOperationCommand, ReplaceOperationCommand,
ReplaceVariableCommand)
from .base.graph import Operation, Variable
from .processer import GraphCommandProcessor
class QuantableOperation(Operation):
def __init__(
self,
convert_from: Operation,
quantize_config: OperationQuantizationConfig,
platform: TargetPlatform
):
# Simply copy all attributes from fp32 operation
# inputs, outputs will be created by QuantableGraph
super().__init__(
op_type = convert_from.type,
inputs = convert_from.inputs.copy(),
outputs = convert_from.outputs.copy(),
attributes = convert_from.attributes,
name = convert_from.name,
platform = platform
)
self._config = quantize_config
# meta data is a crucial attribute for quantization
self._meta = convert_from.meta_data
self._dequantized = False
@ property
def config(self) -> OperationQuantizationConfig:
return self._config
@ config.setter
def set_config(self, config):
"""we will update variable's during this function.
Args:
config ([type]): [description]
Raises:
TypeError: [description]
ExecError: [description]
Returns:
[type]: [description]
"""
if not isinstance(config, OperationQuantizationConfig):
raise TypeError(f'object {str(config)}({type(config)}) is not a acceptable config for operation {self.name}')
self._config = config
def baking_parameters(self, quant_func: BaseQuantFunction):
for config, var in self.config_with_variable:
if var.is_parameter and config.state in {QuantizationStates.ACTIVATED, QuantizationStates.PASSIVE}:
assert isinstance(var, QuantableVariable)
assert len(var.dest_ops) == 1, f', Parameter {var.name} has {len(var.dest_ops)} destinations, '\
'Baking parameter that has more than 1 destinations will incur unexpected problems, '\
'PPQ does not support parameters with more than 1 related operation, reform your graph first.'
var.value = quant_func(var.value, config)
if config.state == QuantizationStates.ACTIVATED:
config.state = QuantizationStates.BAKED
if config.state == QuantizationStates.PASSIVE:
config.state = QuantizationStates.PASSIVE_BAKED
return self
def store_parameter_value(self):
for var, _ in zip(self.inputs + self.outputs,
self.config.input_quantization_config + self.config.output_quantization_config):
if var.is_parameter:
assert isinstance(var, QuantableVariable), 'Unexpected error.'
# convert var.value to torch.Tensor
# notice here we set device = None, this conversion will not change var.value.device anyway.
# so that we can use var.value.device as a deploy device for stored_value
var.stored_value = convert_any_to_torch_tensor(var.value, device='cpu')
return self
def dequantize(self, parameter_only: bool = False, expire_device: str = 'cpu'):
if self._dequantized: return self
for var, quant_config in zip(self.inputs + self.outputs,
self.config.input_quantization_config + self.config.output_quantization_config):
if parameter_only and not var.is_parameter: continue
quant_config.detail['Stored State'] = quant_config.state
assert isinstance(var, QuantableVariable), f'Unexpected error with variable {var.name}.'
if var.is_parameter:
# convert var.value to torch.Tensor
# notice here we set device = None, this conversion will not change var.value.device anyway.
# so that we can use var.value.device as a deploy device for stored_value
stored_value = convert_any_to_torch_tensor(var.value, device=expire_device)
var.value = convert_any_to_torch_tensor(var.value, device=None)
var.value = convert_any_to_torch_tensor(var.stored_value, device=var.value.device)
var.stored_value = stored_value
quant_config.state = QuantizationStates.DEQUANTIZED
self._dequantized = True
return self
def restore_quantize_state(self, expire_device: str = 'cpu'):
if not self._dequantized: return self
for var, quant_config in zip(self.inputs + self.outputs,
self.config.input_quantization_config + self.config.output_quantization_config):
if 'Stored State' in quant_config.detail:
quant_config.state = quant_config.detail['Stored State']
quant_config.detail.pop('Stored State')
if var.is_parameter:
assert isinstance(var, QuantableVariable), 'Unexpected error.'
# convert var.value to torch.Tensor
# notice here we set device = None, this conversion will not change var.value.device anyway.
# so that we can use var.value.device as a deploy device for stored_value
stored_value = convert_any_to_torch_tensor(var.value, device=expire_device)
var.value = convert_any_to_torch_tensor(var.value, device=None)
var.value = convert_any_to_torch_tensor(var.stored_value, device=var.value.device)
var.stored_value = stored_value
self._dequantized = False
return self
@ property
def config_with_variable(self) -> List[Tuple[TensorQuantizationConfig, Variable]]:
"""Just a helper function, This function will list all related config
and variable with current operation.
Returns:
List[Tuple[TensorQuantizationConfig, Variable]]: [description]
"""
ret = []
for cfg, var in zip(self.config.input_quantization_config, self.inputs):
ret.append((cfg, var))
for cfg, var in zip(self.config.output_quantization_config, self.outputs):
ret.append((cfg, var))
return ret
class QuantableVariable(Variable):
def __init__(self, convert_from: Variable) -> None:
super().__init__(
name = convert_from.name,
dest_ops = convert_from.dest_ops.copy(),
source_op = convert_from.source_op,
value = convert_from.value,
is_parameter = convert_from.is_parameter)
self._fp32_value = None
if convert_from.value is not None:
self._fp32_value = convert_any_to_torch_tensor(convert_from.value, device='cpu')
@ property
def stored_value(self) -> Any:
return self._fp32_value
@ stored_value.setter
def stored_value(self, value: Any):
self._fp32_value = value
@ property
def dest_op_configs(self) -> List[TensorQuantizationConfig]:
_dest_op_configs, _dest_idx = [], self.dest_idx
for idx, op in enumerate(self.dest_ops):
if isinstance(op, QuantableOperation):
_dest_op_configs.append(op.config.input_quantization_config[_dest_idx[idx]])
else: _dest_op_configs.append(None)
return _dest_op_configs
@ property
def dest_op_platfroms(self) -> List[TargetPlatform]:
_dest_op_platforms = []
for op in self.dest_ops:
if op is not None:
_dest_op_platforms.append(op.platform)
else: _dest_op_platforms.append(TargetPlatform.FP32)
return _dest_op_platforms
@ property
def source_op_config(self) -> TensorQuantizationConfig:
if self.source_op is not None:
if isinstance(self.source_op, QuantableOperation):
return self.source_op.config.output_quantization_config[self.src_idx]
else: return None
return None
@ property
def source_op_platform(self) -> TargetPlatform:
if self.source_op is None:
return TargetPlatform.FP32
else: return self.source_op.platform
class DeviceSwitchOP(Operation):
"""DeviceSwitch is a PPQ internal operation. This operation is inserted at
platfrom's boundary for transferring data between devices.
Args:
Operation ([type]): [description]
"""
def __init__(self, name: str,
inputs: List[Variable] = None,
outputs: List[Variable] = None) -> None:
super().__init__(
attributes={},
name=name, op_type='PPQDeviceSwitch',
platform=TargetPlatform.UNSPECIFIED,
inputs=inputs, outputs=outputs)
class QuantableGraph(GraphCommandProcessor):
def process(self, command: GraphCommand) -> Any:
if command.command_type == GraphCommandType.QUANTIZE_OPERATION:
assert isinstance(command, QuantizeOperationCommand)
return self.quantize_operation(
command.op_name, command.target_platform, command.config)
def _acceptable_command_types(self) -> List[GraphCommandType]:
return [
GraphCommandType.QUANTIZE_OPERATION,
]
def quantize_operation(
self,
operation_name: str,
target_platform: TargetPlatform,
quantization_config: OperationQuantizationConfig
) -> QuantableOperation:
if operation_name not in self.graph.operations:
raise KeyError(f'Operation {operation_name} is not in your graph, Please check your input.')
if not TargetPlatform.is_quantized_platform(target_platform):
raise ValueError(
f'You are trying to quantize a operation({operation_name})'\
f' to target platform {target_platform}, however it is an non-quantized platform.')
operation = self._graph.operations[operation_name]
quantized_operation = QuantableOperation(
convert_from=operation,
quantize_config=quantization_config,
platform=target_platform,
)
# calling other chain responder to replace operation with quantized one.
if self._next_command_processor is None:
raise RuntimeError(
'To replace a operation, your processor chain must have a GraphMorpher Processor.')
self._next_command_processor(ReplaceOperationCommand(operation_name, quantized_operation))
# replace all related variable with quantable one.
for var in quantized_operation.inputs + quantized_operation.outputs:
if isinstance(var, QuantableVariable): continue
self._next_command_processor(
ReplaceVariableCommand(
var_name=var.name,
replace_to=QuantableVariable(convert_from=var)
)
)
quantized_operation.store_parameter_value()
def dequantize_operation(
self,
operation_name: str
) -> Operation:
if operation_name not in self.graph.operations:
raise KeyError(f'Operation {operation_name} is not in your graph, Please check your input.')
operation = self._graph.operations[operation_name]
if not isinstance(operation, QuantableOperation): return operation
else: return operation.dequantize()
def dequantize_graph(self):
"""一个方便懒人的函数."""
for operation in self.graph.operations.values():
if isinstance(operation, QuantableOperation):
operation.dequantize()
def restore_quantize_state(self):
"""一个方便懒人的函数."""
for operation in self.graph.operations.values():
if isinstance(operation, QuantableOperation):
operation.restore_quantize_state()
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src/access.py | zimingd/packer-rstudio | 0 | 37398 | #!/usr/bin/env python3
import jwt
import requests
import base64
import json
import boto3
import time
import functools
import os
from mod_python import apache
region = json.loads(requests.get('http://169.254.169.254/latest/dynamic/instance-identity/document').text)['region']
ssm_parameter_name_env_var = 'SYNAPSE_TOKEN_AWS_SSM_PARAMETER_NAME'
kms_alias_env_var = 'KMS_KEY_ALIAS'
def headerparserhandler(req):
jwt_str = req.headers_in['x-amzn-oidc-data'] #proxy.conf ensures this header exists
try:
payload = jwt_payload(jwt_str)
if payload['userid'] == approved_user() and payload['exp'] > time.time():
store_to_ssm(req.headers_in['x-amzn-oidc-accesstoken'])
return apache.OK
else:
return apache.HTTP_UNAUTHORIZED #the userid claim does not match the userid tag
except Exception:
# if the JWT playload is invalid
return apache.HTTP_UNAUTHORIZED
def approved_user():
instance_id = requests.get('http://169.254.169.254/latest/meta-data/instance-id').text
ec2 = boto3.resource('ec2',region)
vm = ec2.Instance(instance_id)
#TODO handle exception on multiple tags in this list
for tags in vm.tags:
if tags["Key"] == 'Protected/AccessApprovedCaller':
approved_caller = tags["Value"]
return approved_caller.split(':')[1] #return userid portion of tag
# taking advantage of lru cache to avoid re-putting the same access token to
# SSM Parameter Store.
# According to functools source code, arguments (i.e. the access token) are hashed,
# not stored as-is in memory
@functools.lru_cache(maxsize=1)
def store_to_ssm(access_token):
parameter_name = os.environ.get(ssm_parameter_name_env_var)
kms_key_alias = os.environ.get(kms_alias_env_var)
if not (parameter_name):
# just exit early if the parameter name to store in SSM is not found
return
ssm_client = boto3.client('ssm', region)
kms_client = boto3.client('kms', region)
key_id = kms_client.describe_key(KeyId=kms_key_alias)['KeyMetadata']['KeyId']
ssm_client.put_parameter(
Name=parameter_name,
Type='SecureString',
Value=access_token,
KeyId=key_id,
Overwrite=True
)
def jwt_payload(encoded_jwt):
# The x-amzn-oid-data header is a base64-encoded JWT signed by the ALB
# validating the signature of the JWT means the payload is authentic
# per http://docs.aws.amazon.com/elasticloadbalancing/latest/application/listener-authenticate-users.html
# Step 1: Get the key id from JWT headers (the kid field)
#encoded_jwt = headers.dict['x-amzn-oidc-data']
jwt_headers = encoded_jwt.split('.')[0]
decoded_jwt_headers = base64.b64decode(jwt_headers).decode("utf-8")
decoded_json = json.loads(decoded_jwt_headers)
kid = decoded_json['kid']
# Step 2: Get the public key from regional endpoint
pub_key = get_aws_elb_public_key(region, kid)
# Step 3: Get the payload
return jwt.decode(encoded_jwt, pub_key, algorithms=['ES256'])
@functools.lru_cache()
def get_aws_elb_public_key(region, key_id):
url = f'https://public-keys.auth.elb.{region}.amazonaws.com/{key_id}'
return requests.get(url).text
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src/eos/transaction.py | Remmeauth/gimmeremmetokensbot | 3 | 71172 | """
Provide implementation of transaction.
"""
import os
from eosiopy.eosioparams import EosioParams
from eosiopy.nodenetwork import NodeNetwork
from eosiopy.rawinputparams import RawinputParams
from eosiopy import eosio_config
MASTER_WALLET_PRIVATE_KEY = os.environ.get('MASTER_WALLET_PRIVATE_KEY')
NODEOS_HOST = os.environ.get('NODEOS_HOST')
NODEOS_PORT = os.environ.get('NODEOS_PORT')
eosio_config.url = f'https://{NODEOS_HOST}'
eosio_config.port = int(NODEOS_PORT)
class Transaction:
"""
Transaction implementation.
"""
def send(self, account_from_name, account_to_name, amount, symbol) -> str:
"""
Send transaction.
"""
raw_input_params = RawinputParams('transfer', {
'from': account_from_name,
'memo': 'Remme Protocol transaction.',
'quantity': f'{amount}.0000 {symbol}',
'to': account_to_name,
}, 'eosio.token', f'{account_from_name}@active')
eosio_params = EosioParams(raw_input_params.params_actions_list, MASTER_WALLET_PRIVATE_KEY)
transaction = NodeNetwork.push_transaction(eosio_params.trx_json)
return transaction.get('transaction_id')
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] |
tests/test_adapters.py | ScreenPyHQ/screenpy | 8 | 52230 | <filename>tests/test_adapters.py
import logging
from screenpy.narration.adapters.stdout_adapter import StdOutAdapter, StdOutManager
def prop():
"""The revolver in the foyer!"""
pass
class TestStdOutManager:
def test__outdent(self):
manager = StdOutManager()
manager.depth = []
manager._outdent()
manager._outdent()
manager._outdent()
assert len(manager.depth) == 0
def test__indent(self):
manager = StdOutManager()
with manager._indent():
assert len(manager.depth) == 1
# context persists until manager._outdent is called
assert len(manager.depth) == 1
def test_step(self, caplog):
manager = StdOutManager()
test_message = "Wow. I’m Mr. Manager."
with caplog.at_level(logging.INFO):
with manager.log_context(test_message):
assert len(caplog.records) == 1
assert caplog.records[0].message == test_message
class TestStdOutAdapter:
def test_act(self, caplog):
adapter = StdOutAdapter()
act_name = "test act"
test_func = adapter.act(prop, act_name, None)
with caplog.at_level(logging.INFO):
next(test_func)()
assert len(caplog.records) == 1
assert caplog.records[0].message == f"ACT {act_name.upper()}"
def test_scene(self, caplog):
adapter = StdOutAdapter()
scene_name = "test scene"
test_func = adapter.scene(prop, scene_name, None)
with caplog.at_level(logging.INFO):
next(test_func)()
assert len(caplog.records) == 1
assert caplog.records[0].message == f"Scene: {scene_name.title()}"
def test_beat(self, caplog):
adapter = StdOutAdapter()
beat_line = "test beat"
test_func = adapter.beat(prop, beat_line)
with caplog.at_level(logging.INFO):
next(test_func)()
assert len(caplog.records) == 1
assert caplog.records[0].message == beat_line
def test_indentation(self, caplog):
adapter = StdOutAdapter()
with caplog.at_level(logging.INFO):
for func1 in adapter.beat(prop, "1"):
for func2 in adapter.beat(func1, "2"):
for func3 in adapter.beat(func2, "3"):
func3()
assert len(caplog.records) == 3
assert caplog.records[0].message == "1"
assert caplog.records[1].message == " 2"
assert caplog.records[2].message == " 3"
def test_aside(self, caplog):
adapter = StdOutAdapter()
aside_line = "test aside"
test_func = adapter.aside(prop, aside_line)
with caplog.at_level(logging.INFO):
next(test_func)()
assert len(caplog.records) == 1
assert caplog.records[0].message == aside_line
def test_aside_in_a_beat(self, caplog):
adapter = StdOutAdapter()
with caplog.at_level(logging.INFO):
for func1 in adapter.aside(prop, "beat"):
for func2 in adapter.beat(func1, "aside"):
func2()
assert len(caplog.records) == 2
assert caplog.records[0].message == "beat"
assert caplog.records[1].message == " aside"
def test_error(self, caplog):
adapter = StdOutAdapter()
expected_exception = ValueError("Snakes. Why is it always snakes?")
with caplog.at_level(logging.INFO):
adapter.error(expected_exception)
assert len(caplog.records) == 1
assert expected_exception.__class__.__name__ in caplog.records[0].message
assert str(expected_exception) in caplog.records[0].message
def test_attach(self, caplog):
test_filepath = "freakazoid/documents/freak_in.png"
adapter = StdOutAdapter()
with caplog.at_level(logging.INFO):
adapter.attach(test_filepath)
assert len(caplog.records) == 1
assert test_filepath in caplog.records[0].message
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src/main/python/tokenizeExtended.py | DFKI-MLT/TransIns | 3 | 132918 | import re
from six import text_type
from sacremoses import MosesTokenizer, MosesDetokenizer
class MosesTokenizerExtended(MosesTokenizer):
"""
Extended Moses tokenizer with Catalan support
"""
CA_MIDDLE_DOT = r"([^{}\s\.'\`\,\-·])".format(MosesTokenizer.IsAlnum), r" \1 "
CA_MIDDLE_DOT_NO_LOWER_FOLLOW = r"(·)([^a-z])", r"\1 · \2"
def tokenize(
self,
text,
aggressive_dash_splits=False,
return_str=False,
escape=True,
protected_patterns=None,
):
"""
Python port of the Moses tokenizer.
:param tokens: A single string, i.e. sentence text.
:type tokens: str
:param aggressive_dash_splits: Option to trigger dash split rules .
:type aggressive_dash_splits: bool
"""
# Converts input string into unicode.
text = text_type(text)
# De-duplicate spaces and clean ASCII junk
for regexp, substitution in [self.DEDUPLICATE_SPACE, self.ASCII_JUNK]:
text = re.sub(regexp, substitution, text)
if protected_patterns:
# Find the tokens that needs to be protected.
protected_tokens = [
match.group()
for protected_pattern in protected_patterns
for match in re.finditer(protected_pattern, text, re.IGNORECASE)
]
# Apply the protected_patterns.
for i, token in enumerate(protected_tokens):
substituition = "THISISPROTECTED" + str(i).zfill(3)
text = text.replace(token, substituition)
# Strips heading and trailing spaces.
text = text.strip()
# FIXME!!!
'''
# For Finnish and Swedish, seperate out all "other" special characters.
if self.lang in ["fi", "sv"]:
# In Finnish and Swedish, the colon can be used inside words
# as an apostrophe-like character:
# USA:n, 20:een, EU:ssa, USA:s, S:t
regexp, substitution = self.FI_SV_COLON_APOSTROPHE
text = re.sub(regexp, substitution, text)
# If a colon is not immediately followed by lower-case characters,
# separate it out anyway.
regexp, substitution = self.FI_SV_COLON_NO_LOWER_FOLLOW
text = re.sub(regexp, substitution, text)
else:
'''
if self.lang in ["ca"]:
# In Catalan, the middle dot can be used inside words:
# il·lusio
regexp, substitution = self.CA_MIDDLE_DOT
text = re.sub(regexp, substitution, text)
# If a middle dot is not immediately followed by lower-case characters,
# separate it out anyway.
regexp, substitution = self.CA_MIDDLE_DOT_NO_LOWER_FOLLOW
text = re.sub(regexp, substitution, text)
else:
# Separate special characters outside of IsAlnum character set.
regexp, substitution = self.PAD_NOT_ISALNUM
text = re.sub(regexp, substitution, text)
# Aggressively splits dashes
if aggressive_dash_splits:
regexp, substitution = self.AGGRESSIVE_HYPHEN_SPLIT
text = re.sub(regexp, substitution, text)
# Replaces multidots with "DOTDOTMULTI" literal strings.
text = self.replace_multidots(text)
# Separate out "," except if within numbers e.g. 5,300
for regexp, substitution in [
self.COMMA_SEPARATE_1,
self.COMMA_SEPARATE_2,
self.COMMA_SEPARATE_3,
]:
text = re.sub(regexp, substitution, text)
# (Language-specific) apostrophe tokenization.
if self.lang == "en":
for regexp, substitution in self.ENGLISH_SPECIFIC_APOSTROPHE:
text = re.sub(regexp, substitution, text)
elif self.lang in ["fr", "it", "ca"]:
for regexp, substitution in self.FR_IT_SPECIFIC_APOSTROPHE:
text = re.sub(regexp, substitution, text)
# FIXME!!!
##elif self.lang == "so":
## for regexp, substitution in self.SO_SPECIFIC_APOSTROPHE:
## text = re.sub(regexp, substitution, text)
else:
regexp, substitution = self.NON_SPECIFIC_APOSTROPHE
text = re.sub(regexp, substitution, text)
# Handles nonbreaking prefixes.
text = self.handles_nonbreaking_prefixes(text)
# Cleans up extraneous spaces.
regexp, substitution = self.DEDUPLICATE_SPACE
text = re.sub(regexp, substitution, text).strip()
# Split trailing ".'".
regexp, substituition = self.TRAILING_DOT_APOSTROPHE
text = re.sub(regexp, substituition, text)
# Restore the protected tokens.
if protected_patterns:
for i, token in enumerate(protected_tokens):
substituition = "THISISPROTECTED" + str(i).zfill(3)
text = text.replace(substituition, token)
# Restore multidots.
text = self.restore_multidots(text)
if escape:
# Escape XML symbols.
text = self.escape_xml(text)
return text if return_str else text.split()
class MosesDetokenizerExtended(MosesDetokenizer):
"""
Extended Moses detokenizer with Catalan support
"""
def detokenize(self, tokens, return_str=True, unescape=True):
if self.lang == 'ca':
# simulate Catalan detokenization by first applying the French detokenizer
# and then the Spanish detokenizer
self.lang = 'fr'
detokenized_text = self.tokenize(tokens, return_str, unescape)
tokens = detokenized_text.split(" ")
self.lang = 'es'
detokenized_text = self.tokenize(tokens, return_str, unescape)
self.lang = 'ca'
return detokenized_text
else:
return self.tokenize(tokens, return_str, unescape)
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app/components/OpenLogger/open_logger.py | Eksno/DevOps_Flask_Login | 1 | 147015 | import os
import errno
import logging
from datetime import datetime
from logging.handlers import TimedRotatingFileHandler
def make_sure_path_exists(path):
try:
os.makedirs(path)
except OSError as exception:
if exception.errno != errno.EEXIST:
raise
def create_handlers(log_fname=None, c_level=logging.INFO, f_level=logging.DEBUG):
f_handler = None
if log_fname is not None:
# Create handlers
f_handler = TimedRotatingFileHandler(log_fname)
f_handler.setLevel(f_level)
# Create formatters and add it to handlers
f_format = logging.Formatter(
"[%(asctime)s] {%(pathname)s:%(lineno)d} %(name)s - %(levelname)s - %(message)s"
)
# Apply formatter
f_handler.setFormatter(f_format)
# Create handler
c_handler = logging.StreamHandler()
c_handler.setLevel(c_level)
# Create formatter and add it to handler
c_format = logging.Formatter("%(name)s - %(levelname)s - %(message)s")
# Apply formatter
c_handler.setFormatter(c_format)
return c_handler, f_handler
def configure_logger(
logger, log_to_file=False, console_level=logging.INFO, file_level=logging.DEBUG
):
# Create log dir
root_dir = os.path.normpath(os.getcwd() + os.sep)
root_log_dir = root_dir
make_sure_path_exists(os.path.join(root_log_dir, "logs"))
log_dir = os.path.join(root_log_dir, "logs")
now = datetime.now()
logger.setLevel(logging.DEBUG)
if log_to_file:
# Create path
make_sure_path_exists(os.path.join(log_dir, now.strftime("%Y")))
log_year_dir = os.path.join(log_dir, now.strftime("%Y"))
make_sure_path_exists(os.path.join(log_year_dir, now.strftime("%B")))
log_month_dir = os.path.join(log_year_dir, now.strftime("%B"))
make_sure_path_exists(os.path.join(log_month_dir, now.strftime("%d")))
log_day_dir = os.path.join(log_month_dir, now.strftime("%d"))
log_fname = os.path.join(
log_day_dir, "{}.log".format(now.strftime("%b-%d-%Y_%H-%M-%S"))
)
# Create Handlers
c_handler, f_handler = create_handlers(log_fname)
logger.addHandler(c_handler)
logger.addHandler(f_handler)
else:
c_handler, _ = create_handlers()
logger.addHandler(c_handler)
logging.info("logging configured")
def configure_loggers(
loggers, log_to_file=False, console_level=logging.INFO, file_level=logging.DEBUG
):
for logger in loggers:
configure_logger(logger, log_to_file, console_level, file_level)
if __name__ == "__main__":
logger = logging.getLogger()
configure_logger(logger)
logging.debug(
"Debug Test Log - Detailed information, typically of interest only when diagnosing problems."
)
logging.info("Info Test Log - Confirmation that things are working as expected.")
logging.warning(
"Warining Test Log - An indication that something unexpected happened, or indicative of some problem in the near future (e.g. ‘disk space low’). The software is still working as expected."
)
logging.error(
"Error Test Log - Due to a more serious problem, the software has not been able to perform some function."
)
logging.critical(
"Critical Test Log - A serious error, indicating that the program itself may be unable to continue running."
)
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SelfPractice&Tutorial/12_Histogram.py | Omer-sync/ComputerVision_Studies | 0 | 1617079 | <filename>SelfPractice&Tutorial/12_Histogram.py
import cv2 as cv
import numpy as np
import matplotlib.pyplot as plt
img = cv.imread("D:/Programming/Python_Projects/Computer_Vision/ROV/FishSize/Source/" + "samplefromvideo_1.png")
cv.imshow('Park',img)
# Grayscale Histogram
gray = cv.cvtColor(img,cv.COLOR_BGR2GRAY)
gray_hist = cv.calcHist([gray],[0],None,[256],[0,256])
plt.figure()
plt.title("GrayScale Histogram")
plt.xlabel('Bins')
plt.ylabel('# of pixels')
plt.plot(gray_hist)
plt.xlim([0,256])
plt.show()
# Masked Grayscale Histogram
# blank = np.zeros(img.shape[0:2],dtype='uint8')
# gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
# cv.imshow('Gray', gray)
#
# mask = cv.circle(blank, (img.shape[1]//2,img.shape[0]//2), 100, 255, -1)
#
# masked = cv.bitwise_and(gray,gray,mask=mask)
# cv.imshow('Mask', masked)
# gray_hist = cv.calcHist([gray], [0], mask, [256], [0,256] )
# plt.figure()
# plt.title("GrayScale Histogram")
# plt.xlabel('Bins')
# plt.ylabel('# of pixels')
# plt.plot(gray_hist)
# plt.xlim([0,256])
# plt.show()
# Colorful Histogram
blank = np.zeros(img.shape[0:2],dtype='uint8')
mask = cv.circle(blank, (img.shape[1]//2,img.shape[0]//2), 100, 255, -1)
masked = cv.bitwise_and(img,img,mask=mask)
cv.imshow('Mask', masked)
plt.figure()
plt.title('Colour Histogram')
plt.xlabel('Bins')
plt.ylabel('# of pixels')
colors = ('b', 'g', 'r')
for i,col in enumerate(colors):
hist = cv.calcHist([img], [i], mask, [256], [0,256])
plt.plot(hist, color=col)
plt.xlim([0,256])
plt.show()
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connect4/Connect4Tree.py | dl4184/alpha-zero-general | 0 | 169703 | import numpy as np
from numba import njit, b1, i1, int64, float64
@njit(b1(i1[:, :], i1, i1))
def was_winning_move(board, row, col):
if col == -1:
return False
player = board[row, col]
player_pieces = board == player
win_len = 4
row_win = player_pieces[row, :]
for i in range(row_win.size - win_len + 1):
if row_win[i: i + win_len].all():
return True
diag_win1 = np.diag(player_pieces, col - row)
for i in range(diag_win1.size - win_len + 1):
if diag_win1[i: i + win_len].all():
return True
new_col = 6 - col
diag_win2 = np.diag(player_pieces[:, ::-1], new_col - row)
for i in range(diag_win2.size - win_len + 1):
if diag_win2[i: i + win_len].all():
return True
if row < 3:
col_win = player_pieces[row:, col]
for i in range(col_win.size - win_len + 1):
if col_win[i: i + win_len].all():
return True
return False
"""
@njit(i1[:, :](i1[:, :], i1, i1, i1))
def add_stone(board, row, col, player):
# available_idx = np.argmin(board[:, column] == 0) - 1
#new_board = board.copy()
board[row][col] = player
return board
@njit(b1[:](i1[:, :]))
def valid_moves(board):
return board[0] == 0
@njit(i1(i1[:, :], i1))
def playable_row(board, col):
return np.where(board[:, col] == 0)[0][-1]
"""
@njit(float64(i1[:, :], int64, int64, int64, float64, float64, int64, float64[:, :]))
def minimax(board, move_row, move_col, depth, alpha, beta, player, result):
if was_winning_move(board, move_row, move_col):
return -player
moves = np.where(board[0] == 0)[0] # we get columns (moves) we can play
if depth == 0 or moves.size == 0:
return 0
if player == 1:
best_val = -np.inf
else:
best_val = np.inf
for i in range(moves.size):
col = moves[i]
row = np.where(board[:, col] == 0)[0][-1] # np.argmin(board[:, col] == 0) - 1
board[row][col] = player # we play the move
# child_node = Node(new_board, row, col)
value = minimax(board, row, col, depth - 1, alpha, beta, -player, result)
board[row][col] = 0 # undo the move this way is faster than just copying board
if move_row == -1 and move_col == -1: # if we are in root "node" we want best child and the move we played
result[col, 0] = 1 # we played this move
result[col, 1] = value # value we obtained
# move/col is an index of result
if player == 1:
best_val = max(best_val, value)
alpha = max(alpha, best_val)
else:
best_val = min(best_val, value)
alpha = min(alpha, best_val)
if beta <= alpha:
break
return best_val
# @njit(int64(i1[:, :], int64))
def best_move_alpha_beta(board, depth):
board = board.astype(np.int8)
# root = Node(board, -1, -1)
result = np.zeros((7, 2))
v = minimax(board, -1, -1, depth, -np.inf, np.inf, 1, result) # board is in canonical form
moves = []
for move in range(7):
searched, value = result[move, :]
if searched and value == v:
moves.append(move)
return np.random.choice(moves)
if __name__ == "__main__":
import time
b = np.zeros((6, 7))
b[5][3] = 1
b[5][2] = 1
# b[5][1] = 1
b[4][3] = -1
b = np.array([
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, -1, 0, 0, 0, 0],
[0, 0, 1, 1, 0, 0, 0]])
b = b.astype(np.int8)
b = b * -1
# b[4][2] = -1
# b[4][1] = -1
# print(was_winning_move(b, 2,1))
print(b)
t = time.time()
print(best_move_alpha_beta(b, 9))
print(time.time() - t)
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src/restfuls/apps/v1/apis/auth.py | Qinnnnnn/Watero_DataCenter | 0 | 115300 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
File : certify.py
Author : <NAME>
CreateDate : 2018-12-16 10:00:00
LastModifiedDate : 2018-12-16 10:00:00
Note : Agent认证接口，GET
"""
from flask_restful import Resource
from flask_restful import fields
from flask_restful import marshal_with
from flask_restful import reqparse
from src.restfuls.apps.db_model import AgentRegisterLogs
from src.restfuls.apps.db_model import db
from src.restfuls.utils import abort
from src.restfuls.utils.certify import Certify
class AgentAuth(Resource):
"""
Agent认证接口
"""
get_resp_template = {
'status': fields.Integer,
'state': fields.String,
'message': fields.Nested(
{'access_token': fields.String}
)
}
def __init__(self):
"""
初始化
"""
self.get_parser = reqparse.RequestParser()
self.get_parser.add_argument('mac_addr', required=True, type=str, help='mac_addr required')
@marshal_with(get_resp_template)
def get(self):
"""
GET方法
:return:
"""
# 参数验证
args = self.get_parser.parse_args()
mac_addr = args.get('mac_addr')
rt = db.session.query(AgentRegisterLogs).filter(AgentRegisterLogs.mac_addr == mac_addr).first()
if rt and rt.status == 1:
rt.access_token = Certify.generate_token(mac_addr)
db.session.commit()
return {'status': 1, 'state': 'success', 'message': rt}
else:
msg = 'Access denied'
abort.abort_with_msg(403, -1, 'error', msg)
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525,
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742,
10191,
29897,
13,
2
] |
test/functional/omni_graceperiod.py | fiscalobject/uniasset | 39 | 38814 | <filename>test/functional/omni_graceperiod.py
#!/usr/bin/env python3
# Copyright (c) 2017-2018 The Bitcoin Core developers
# Distributed under the MIT software license, see the accompanying
# file COPYING or http://www.opensource.org/licenses/mit-license.php.
"""Test grace period."""
from test_framework.test_framework import BitcoinTestFramework
from test_framework.util import assert_equal
class OmniGracePeriod(BitcoinTestFramework):
def set_test_params(self):
self.num_nodes = 1
self.setup_clean_chain = True
self.extra_args = [['-omniactivationallowsender=any']]
def sendactivation(self, address, coinbase_address, heights, expected):
# Min client version for feature activation
minClientVersion = 0
for height in heights:
activation_block = self.nodes[0].getblockcount() + height + 1
txid = self.nodes[0].omni_sendactivation(address, 3, activation_block, minClientVersion)
self.nodes[0].generatetoaddress(1, coinbase_address)
# Checking the transaction was valid...
result = self.nodes[0].omni_gettransaction(txid)
assert_equal(result['valid'], expected)
def run_test(self):
self.log.info("test grace period")
# Preparing some mature Bitcoins
coinbase_address = self.nodes[0].getnewaddress()
self.nodes[0].generatetoaddress(101, coinbase_address)
# Obtaining a master address to work with
address = self.nodes[0].getnewaddress()
# Funding the address with some testnet BTC for fees
self.nodes[0].sendtoaddress(address, 0.1)
self.nodes[0].generatetoaddress(1, coinbase_address)
# A relative activation height of blocks is smaller than the grace period and not allowed
self.sendactivation(address, coinbase_address, [-100, 0, 1, 2, 4], False)
# A relative activation height of blocks is too far in the future and not allowed
self.sendactivation(address, coinbase_address, [11, 288, 12289, 999999], False)
# A relative activation height of blocks is within the grace period and accepted
activationMinBlocks = 5
activationMaxBlocks = 10
self.sendactivation(address, coinbase_address, [activationMinBlocks, activationMinBlocks + 1, activationMaxBlocks - 1, activationMaxBlocks], True)
if __name__ == '__main__':
OmniGracePeriod().main()
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repl/repl.py | JesterOrNot/MathLang | 2 | 91447 | import sys
import tty
import re
import os
def syntax_highlight(input, keywords: dict):
i = 0
splitted = input.split(" ")
for f in splitted:
for keyword in keywords.keys():
if re.match(keyword, f):
splitted[i] = keywords.get(
keyword) + re.findall(keyword, f)[0] + u"\u001b[0m"
i += 1
return " ".join(splitted)
def command_line(keywords: dict):
tty.setraw(sys.stdin)
input = ""
index = 0
sys.stdout.write("\n")
sys.stdout.write(u"\u001b[1000D")
sys.stdout.write(u"\u001b[0K")
do_print = True
while True:
if do_print:
sys.stdout.write(">>> ")
do_print = False
sys.stdout.flush()
char = sys.stdin.read(1)
if char == ":":
sys.stdout.write("\n")
sys.stdout.write(u"\u001b[1000D")
sys.stdout.write(u"\u001b[0K")
return ""
if 32 <= ord(char) <= 126:
input += char
if ord(char) == 127:
input = input[:index-1]
if ord(char) in {10, 13}:
sys.stdout.write("\n")
sys.stdout.write(u"\u001b[1000D")
sys.stdout.write(u"\u001b[0K")
sys.stdout.flush()
with open("/tmp/.mlangrepl.temp", "w+") as f:
f.write(input)
os.system("mathlang /tmp/.mlangrepl.temp")
input = ""
sys.stdout.write("\n")
sys.stdout.write(u"\u001b[1000D")
sys.stdout.write(u"\u001b[0K")
sys.stdout.flush()
do_print = True
continue
sys.stdout.write(u"\u001b[1000D")
sys.stdout.write(u"\u001b[4C")
sys.stdout.write(u"\u001b[0K")
sys.stdout.write(syntax_highlight(input, keywords))
if index > 0:
sys.stdout.write(u"\u001b[" + str(index) + "C")
sys.stdout.flush()
return input
command_line({"sqrt": "\u001b[38;5;198m",
"log": "\u001b[38;5;198m",
"say": "\u001b[38;5;198m",
"sin": "\u001b[38;5;198m",
"cos": "\u001b[38;5;198m",
"tan": "\u001b[38;5;198m",
"cbrt": "\u001b[38;5;198m",
"asin": "\u001b[38;5;198m",
"acos": "\u001b[38;5;198m",
"atan": "\u001b[38;5;198m",
"\d+": "\u001b[38;2;214;119;119m",
"\+": "\u001b[38;2;112;112;112m",
"-": "\u001b[38;2;112;112;112m",
"\*\*?": "\u001b[38;2;112;112;112m",
"/": "\u001b[38;2;112;112;112m",
"%": "\u001b[38;2;112;112;112m",
"\".*\"": "\u001b[38;2;26;166;228m",
})
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] |
projects/projects/__init__.py | fgoettel/knx | 0 | 155995 | <gh_stars>0
"""Import, export, compare different project exports."""
__author__ = """<NAME>"""
__email__ = "<EMAIL>"
__version__ = "0.3.0"
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digitalocean/Tags.py | SuleAlOthman/digitalocean | 2 | 1604992 | from .reqmethods import Req, Arrange
class Tags(Req, Arrange):
slug = 'tags'
def __init__(self, token):
self.setToken(token)
def storeTags(self, tag):
body = {"name":f'{tag}'}
data = self.post(self.slug, body)
return data
def getTag(self, tag):
data = self.get(f'{self.slug}/{tag}')
return self.arrangeData(data)
def getAllTags(self):
data = self.get(self.slug)
return self.arrangeData(data)
def deleteTag(self, tag):
body = {"name":f'{tag}'}
data = self.delete(f'{self.slug}/{tag}')
return data | [
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CPAC/AWS/aws_utils.py | danlurie/C-PAC | 0 | 105674 | # CPAC/AWS/aws_utils.py
#
# Contributing authors:
# <NAME>
'''
This module contains functions which assist in interacting with AWS
services, including uploading/downloading data and file checking.
'''
# Build and download a subject list
def build_download_sublist(bucket, bucket_prefix, local_prefix, sub_list):
'''
Function to build and download a subject list from S3
Parameters
----------
bucket : boto.s3.bucket.Bucket instance
an instance of the boto S3 bucket class to download from
bucket_prefix : string
the bucket prefix where all of the file keys are located
local_prefix : string
the local disk prefix where all of the files should be downloaded to
sub_list : list (dict)
the C-PAC subject list that has inputs in local_prefix
Returns
-------
None
this function does not return a value, it downloads the subjects from
the C-PAC subject list to disk from S3
'''
# Import packages
import os
# Init variables
local_list = []
for sub_dict in sub_list:
local_list.append(sub_dict['anat'])
local_list.extend([v for v in sub_dict['rest'].values()])
# Substitute the prefixes to build S3 list to download from
s3_list = [l.replace(local_prefix, bucket_prefix) for l in local_list]
# Check already-existing files and remove from download lists
local_rm = []
s3_rm = []
# Build remove-lists
for i in range(len(local_list)):
l = local_list[i]
s = s3_list[i]
if os.path.exists(l):
local_rm.append(l)
s3_rm.append(s)
# Go through remove lists and remove files
for l, s in zip(local_rm, s3_rm):
local_list.remove(l)
s3_list.remove(s)
# Download the data to the local prefix
s3_download(bucket, s3_list, local_prefix, bucket_prefix=bucket_prefix)
# Check to see they all downloaded successfully
for l in local_list:
l_path = os.path.abspath(l)
if not os.path.exists(l_path):
raise IOError('S3 files were not all downloaded.\n'\
'Could not find: %s' % l_path)
# Collect all files in directory as the source list
def collect_subject_files(prefix_star, sub_id):
'''
Function to collect all of the files in a directory into a list of
full paths
Parameters
----------
prefix_star : string
filepath to the folder, in which, all of the sub-files are
collected; this filepath should have a wildcard character of
'*' so that glob can collect the files via the pattern given
sub_id : string
the subject id to look for in the output folder
Returns
-------
src_list : list [str]
a list of filepaths (as strings)
'''
# Import packages
import glob
import os
# Init variables
bases = glob.glob(prefix_star)
src_list = []
# For each pipeline
for base in bases:
# Iterate through directory
for root, dirs, files in os.walk(base):
# If it's in the subject's folder and there are files
if sub_id in root and files:
src_list.extend([os.path.join(root, f) for f in files])
# Return the list
return src_list
# Get the MD5 sums of files on S3
def md5_sum(bucket, prefix='', filt_str=''):
'''
Function to get the filenames and MD5 checksums of files stored in
an S3 bucket and return this as a dictionary.
Parameters
----------
bucket : boto.s3.bucket.Bucket instance
an instance of the boto S3 bucket class to download from
prefix : string (optional), default=''
the bucket prefix where all of the file keys are located
filt_str : string (optional), defualt=''
a string to filter the filekeys of interest;
e.g. 'matrix_data' will only return filekeys with the string
'matrix_data' in their filepath name
Returns
-------
md5_dict : dictionary {str : str}
a dictionary where the keys are the S3 filename and the values
are the MD5 checksum values
'''
# Init variables
blist = bucket.list(prefix)
md5_dict = {}
# And iterate over keys to copy over new ones
for fkey in blist:
filename = str(fkey.key)
if filt_str in filename:
md5_sum = str(fkey.etag).strip('"')
md5_dict[filename] = md5_sum
print 'filename: %s' % filename
print 'md5_sum: %s' % md5_sum
# Return the dictionary
return md5_dict
# Rename s3 keys from src_list to dst_list
def s3_rename(bucket, src_list, dst_list,
keep_old=False, overwrite=False, make_public=False):
'''
Function to rename files from an AWS S3 bucket via a copy and delete
process. Uses all keys in src_list as the original names and renames
the them to the corresponding keys in the dst_list.
(e.g. src_list[9] --> dst_list[9])
Parameters
----------
bucket : boto.s3.bucket.Bucket instance
an instance of the boto S3 bucket class to download from
src_list : list (str)
a list of relative paths of the files to delete from the bucket
dst_list : list (str)
a list of relative paths of the files to delete from the bucket
keep_old : boolean (optional), default=False
flag indicating whether to keep the src_list files
overwrite : boolean (optional), default=False
flag indicated whether to overwrite the files in dst_list
make_public : boolean (optional), default=False
set to True if files should be publically available on S3
Returns
-------
None
The function doesn't return any value, it deletes data from
S3 and prints its progress and a 'done' message upon completion
'''
# Check list lengths are equal
if len(src_list) != len(dst_list):
raise ValueError('src_list and dst_list are different lengths!')
# Init variables
i = 0
no_files = len(src_list)
# And iterate over keys to copy over new ones
for f in src_list:
src_key = bucket.get_key(f)
if not src_key:
print 'source file %s doesnt exist, skipping...' % f
continue
dst_key = dst_list[i]
dst_exists = bucket.get_key(dst_key)
if not dst_exists or overwrite:
print 'copying source: ', str(src_key.key)
print 'to destination: ', dst_key
src_key.copy(bucket.name, dst_key)
if make_public:
print 'making public...'
dk = bucket.get_key(dst_key)
dk.make_public()
if not keep_old:
src_key.delete()
else:
print '%s exists and not overwriting' % dst_key
i += 1
per = 100*(float(i)/no_files)
print 'Done renaming %d/%d\n%f%% complete' % (i, no_files, per)
# Delete s3 keys based on input list
def s3_delete(bucket, in_list):
'''
Method to delete files from an AWS S3 bucket that have the same
names as those of an input list to a local directory.
Parameters
----------
bucket : boto.s3.bucket.Bucket instance
an instance of the boto S3 bucket class to download from
in_list : list (str)
a list of relative paths of the files to delete from the bucket
Returns
-------
None
The function doesn't return any value, it deletes data from
S3 and prints its progress and a 'done' message upon completion
'''
# Init variables
no_files = len(in_list)
i = 0
# Iterate over list and delete S3 items
for f in in_list:
i += 1
try:
print 'attempting to delete %s from %s...' % (f, bucket.name)
k = bucket.get_key(f)
k.delete()
per = 100*(float(i)/no_files)
print 'Done deleting %d/%d\n%f%% complete' % (i, no_files, per)
except AttributeError:
print 'No key found for %s on bucket %s' % (f, bucket.name)
# Done iterating through list
print 'done!'
# Download files from AWS S3 to local machine
def s3_download(bucket, in_list, local_prefix, bucket_prefix=''):
'''
Method to download files from an AWS S3 bucket that have the same
names as those of an input list to a local directory.
Parameters
----------
bucket : boto.s3.bucket.Bucket instance
an instance of the boto S3 bucket class to download from
in_list : list (str)
a list of relative paths of the files to download from the bucket
local_prefix : string
local directory prefix to store the downloaded data
bucket_prefix : string (optional)
bucket_prefix, if specified, will be substituted with
local_prefix; otherwise, the local_prefix will only prepend the
downloaded files
Returns
-------
None
The function doesn't return any value, it downloads data from
S3 and prints its progress and a 'done' message upon completion
'''
# Impor packages
import os
# Init variables
no_files = len(in_list)
i = 0
# Check for trailing '/'
if not local_prefix.endswith('/'):
local_prefix = local_prefix + '/'
if bucket_prefix and not bucket_prefix.endswith('/'):
bucket_prefix = bucket_prefix + '/'
# For each item in the list, try to download it
for f in in_list:
i += 1
remote_filename = bucket.name + ': ' + f
if bucket_prefix:
local_filename = f.replace(bucket_prefix, local_prefix)
else:
local_filename = os.path.join(local_prefix, f)
# Check to see if the local folder setup exists or not
local_folders = os.path.dirname(local_filename)
if not os.path.isdir(local_folders):
print 'creating %s on local machine' % local_folders
os.makedirs(local_folders)
# Attempt to download the file
print 'attempting to download %s to %s...' % (remote_filename,
local_filename)
try:
if not os.path.exists(local_filename):
k = bucket.get_key(f)
k.get_contents_to_filename(local_filename)
per = 100*(float(i)/no_files)
print 'Done downloading %d/%d\n%f%% complete' % (i, no_files, per)
else:
print 'File %s already exists, skipping...' % local_filename
except AttributeError:
print 'No key found for %s on bucket %s' % (f, bucket.name)
# Done iterating through list
print 'done!'
# Upload files to AWS S3
def s3_upload(bucket, src_list, dst_list, make_public=False, overwrite=False):
'''
Function to upload a list of data to an S3 bucket
Parameters
----------
bucket : boto.s3.bucket.Bucket instance
an instance of the boto S3 bucket class to download from
src_list : list (str)
list of filepaths as strings to upload to S3
dst_list : list (str)
list of filepaths as strings coinciding with src_list, such
that src_list[1] gets uploaded to S3 with the S3 path given in
dst_list[1]
make_public : boolean (optional), default=False
set to True if files should be publically available on S3
overwrite : boolean (optional), default=False
set to True if the uploaded files should overwrite what is
already there
Returns
-------
None
The function doesn't return any value, it uploads data to S3
and prints its progress and a 'done' message upon completion
'''
# Callback function for upload progress update
def callback(complete, total):
'''
Method to illustrate file uploading and progress updates
'''
# Import packages
import sys
# Write ...'s to the output for loading progress
sys.stdout.write('.')
sys.stdout.flush()
# Init variables
no_files = len(src_list)
i = 0
# Check if the list lengths match
if no_files != len(dst_list):
raise RuntimeError, 'src_list and dst_list must be the same length!'
# For each source file, upload
for src_file in src_list:
# Get destination path
dst_file = dst_list[i]
# Print status
print 'Uploading %s to S3 bucket %s as %s' % \
(src_file, bucket.name, dst_file)
# Create a new key from the bucket and set its contents
k = bucket.new_key(dst_file)
if k.exists() and not overwrite:
print 'key %s already exists, skipping...' % dst_file
else:
k.set_contents_from_filename(src_file, cb=callback, replace=True)
# Make file public if set to True
if make_public:
print 'make public()'
k.make_public()
i += 1
per = 100*(float(i)/no_files)
print 'finished file %d/%d\n%f%% complete\n' % \
(i, no_files, per)
# Print when finished
print 'Done!'
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src/coniql/plugin.py | thomascobb/coniql | 3 | 151771 | <reponame>thomascobb/coniql
import os
from pathlib import Path
from typing import AsyncIterator, Dict, List, Tuple, Union
import numpy as np
from coniql.device_config import ChannelConfig, DeviceConfig, DeviceInstance, walk
from coniql.types import Channel
PutValue = Union[bool, int, float, str, List[str], np.ndarray]
class Plugin:
transport: str
async def get_channel(
self, pv: str, timeout: float, config: ChannelConfig
) -> Channel:
"""Get the current structure of a Channel"""
raise NotImplementedError(self)
async def put_channels(
self, pvs: List[str], values: List[PutValue], timeout: float
):
"""Put a value to a channel, returning the structure after put"""
raise NotImplementedError(self)
async def subscribe_channel(
self, pv: str, config: ChannelConfig
) -> AsyncIterator[Channel]:
"""Subscribe to the structure of the Channel, yielding structures
where only changing top level fields are filled in"""
raise NotImplementedError(self)
yield
class PluginStore:
def __init__(self):
# {transport: plugin}
self.plugins: Dict[str, Plugin] = {}
# {device_id: device_config}
self.devices: Dict[str, DeviceConfig] = {}
# {fully_qualified_channel_id: channel_config}
self.channels: Dict[str, ChannelConfig] = {}
def add_plugin(self, transport: str, plugin: Plugin, set_default=False):
self.plugins[transport] = plugin
plugin.transport = transport
if set_default:
self.plugins[""] = plugin
def transport_pv(self, channel_id: str) -> Tuple[str, str]:
"""Take a channel_id with an optional transport prefix and
return the transport and pv components"""
split = channel_id.split("://", 1)
if len(split) == 1:
transport, pv = self.plugins[""].transport, channel_id
else:
transport, pv = split
return transport, pv
def add_device_config(self, path: Path, device_id="", macros=None):
"""Load a top level .coniql.yaml file with devices in it"""
device_config = DeviceConfig.from_yaml(path, macros)
if device_id:
self.devices[device_id] = device_config
# Relative paths are relative to the path being loaded, so go there
cwd = Path.cwd()
os.chdir(path.resolve().parent)
try:
for child in walk(device_config.children):
if isinstance(child, ChannelConfig):
# TODO: selectively update channel if already exists
transport, pv = self.transport_pv(child.write_pv or child.read_pv)
self.channels[f"{transport}://{pv}"] = child
elif isinstance(child, DeviceInstance):
# recursively load child devices
if child.id is None:
if device_id:
child.id = device_id + "." + child.name
else:
child.id = child.name
self.add_device_config(child.file, child.id, child.macros)
finally:
os.chdir(cwd)
return device_config
def plugin_config_id(self, channel_id: str) -> Tuple[Plugin, ChannelConfig, str]:
transport, pv = self.transport_pv(channel_id)
channel_id = f"{transport}://{pv}"
plugin = self.plugins[transport]
config = self.channels.get(channel_id, None)
if config is None:
# None exists, make a RW config
config = ChannelConfig(name="", read_pv=channel_id, write_pv=channel_id)
return plugin, config, channel_id
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] |
vows/transformer_test_data.py | wking/thumbor | 0 | 1612999 | #!/usr/bin/python
# -*- coding: utf-8 -*-
# thumbor imaging service
# https://github.com/thumbor/thumbor/wiki
# Licensed under the MIT license:
# http://www.opensource.org/licenses/mit-license
# Copyright (c) 2011 globo.com <EMAIL>
from thumbor.point import FocalPoint as fp
from thumbor.context import Context, RequestParameters
from thumbor.config import Config
from thumbor.importer import Importer
from thumbor.detectors import BaseDetector
from thumbor.storages.no_storage import Storage as NoStorage
class MockEngine(object):
def __init__(self, size):
self.size = size
self.calls = {
'resize': [],
'crop': [],
'vertical_flip': 0,
'horizontal_flip': 0,
'cover': 0,
}
self.focal_points = None
def resize(self, width, height):
self.calls['resize'].append({
'width': width,
'height': height
})
def crop(self, left, top, right, bottom):
self.calls['crop'].append({
'left': left,
'top': top,
'right': right,
'bottom': bottom
})
def flip_horizontally(self):
self.calls['horizontal_flip'] += 1
def flip_vertically(self):
self.calls['vertical_flip'] += 1
def get_proportional_width(self, new_height):
width, height = self.size
return float(new_height) * width / height
def get_proportional_height(self, new_width):
width, height = self.size
return float(new_width) * height / width
def focus(self, focal_points):
self.focal_points = focal_points
def extract_cover(self):
self.calls['cover'] += 1
class MockSyncDetector(BaseDetector):
def detect(self, callback):
callback([])
class MockErrorSyncDetector(BaseDetector):
def detect(self, callback):
raise Exception('x')
class TestData(object):
def __init__(
self,
source_width, source_height,
target_width, target_height,
halign, valign, focal_points,
crop_left, crop_top, crop_right, crop_bottom,
fit_in=False, adaptive=False, full=False, meta=False):
self.source_width = source_width
self.source_height = source_height
self.target_width = target_width
self.target_height = target_height
self.halign = halign
self.valign = valign
self.focal_points = focal_points
self.crop_left = crop_left
self.crop_top = crop_top
self.crop_right = crop_right
self.crop_bottom = crop_bottom
self.fit_in = fit_in
self.adaptive = adaptive
self.full = full
self.meta = meta
def __repr__(self):
return self.__str__()
def __unicode__(self):
return self.__str__()
def __str__(self):
crop_message = ""
if self.crop_left is not None:
crop_message = "it should crop %dx%d-%dx%d and " % (
self.crop_left, self.crop_top,
self.crop_right, self.crop_bottom
)
return "For an image of %dx%d resizing to %sx%s, %sit should resize to %sx%s" % (
self.source_width, self.source_height,
self.target_width, self.target_height,
crop_message,
self.target_width, self.target_height
)
def to_context(self, detectors=[], ignore_detector_error=False):
self.engine = MockEngine((self.source_width, self.source_height))
flip_horizontally = self.target_width < 0
flip_vertically = self.target_height < 0
self.target_width = self.target_width == "orig" and "orig" or abs(self.target_width)
self.target_height = self.target_height == "orig" and "orig" or abs(self.target_height)
importer = Importer(None)
importer.detectors = detectors
importer.storage = NoStorage
config = Config()
config.IGNORE_SMART_ERRORS = ignore_detector_error
ctx = Context(server=None, config=config, importer=importer)
ctx.modules.engine = self.engine
ctx.request = RequestParameters(
buffer=None,
debug=False,
meta=self.meta,
crop={
'left': self.crop_left,
'top': self.crop_top,
'right': self.crop_right,
'bottom': self.crop_bottom
},
adaptive=self.adaptive,
full=self.full,
fit_in=self.fit_in,
horizontal_flip=flip_horizontally,
vertical_flip=flip_vertically,
width=self.target_width,
height=self.target_height,
halign=self.halign,
valign=self.valign,
focal_points=self.focal_points,
smart=True,
extension="JPEG",
filters=[],
quality=80,
image="some.jpeg"
)
ctx.request.engine = self.engine
ctx.request.engine.extension = ".jpeg"
return ctx
@property
def resize_error_message(self):
message = "The engine resize should have been called with %sx%s" % (self.target_width, self.target_height)
if not self.engine.calls['resize']:
return "%s, but was never called" % message
else:
last_resize = self.engine.calls['resize'][0]
return "%s, but was called with %sx%s" % (message, last_resize['width'], last_resize['height'])
def has_resized_properly(self):
if not self.target_width and not self.target_height:
return True
if (self.target_width == self.source_width and self.target_height == self.source_height) or \
(self.target_width == self.source_width and self.target_height == "orig") or \
(self.target_width == "orig" and self.target_height == self.source_height) or \
(self.target_width == "orig" and self.target_height == "orig"):
return True
assert self.engine.calls['resize'], self.resize_error_message
if not self.target_width:
assert \
self.engine.calls['resize'][0]['width'] == float(self.source_width) * self.target_height / self.source_height, \
self.resize_error_message
assert self.engine.calls['resize'][0]['height'] == self.target_height, self.resize_error_message
return True
if not self.target_height:
assert self.engine.calls['resize'][0]['width'] == self.target_width, self.resize_error_message
assert \
self.engine.calls['resize'][0]['height'] == float(self.source_height) * self.target_width / self.source_width, \
self.resize_error_message
return True
assert self.engine.calls['resize'][0]['width'] == \
(self.target_width == "orig" and self.source_width or self.target_width), self.resize_error_message
assert self.engine.calls['resize'][0]['height'] == \
(self.target_height == "orig" and self.source_height or self.target_height), self.resize_error_message
return True
@property
def crop_error_message(self):
message = "The engine crop should have been called with %dx%d %dx%d" % (
self.crop_left, self.crop_top, self.crop_right, self.crop_bottom
)
if not self.engine.calls['crop']:
return "%s, but was never called" % message
else:
last_crop = self.engine.calls['crop'][0]
return "%s, but was called with %dx%d %dx%d" % (
message, last_crop['left'], last_crop['top'], last_crop['right'], last_crop['bottom']
)
def has_cropped_properly(self):
if self.crop_left is None:
assert not self.engine.calls['crop'], \
'The engine crop should NOT have been called but was with %(left)dx%(top)d %(right)dx%(bottom)d' % (
self.engine.calls['crop'][0]
)
return True
assert self.engine.calls['crop'], self.crop_error_message
assert self.engine.calls['crop'][0]['left'] == self.crop_left, self.crop_error_message
assert self.engine.calls['crop'][0]['top'] == self.crop_top, self.crop_error_message
assert self.engine.calls['crop'][0]['right'] == self.crop_right, self.crop_error_message
assert self.engine.calls['crop'][0]['bottom'] == self.crop_bottom, self.crop_error_message
return True
TESTITEMS = [
TestData(
source_width=800, source_height=600,
target_width=400, target_height=150,
halign="center", valign="middle",
focal_points=[],
crop_left=0, crop_top=75, crop_right=800, crop_bottom=375
),
TestData(
source_width=600, source_height=800,
target_width=150, target_height=400,
halign="center", valign="middle",
focal_points=[],
crop_left=150, crop_top=0, crop_right=450, crop_bottom=800
),
TestData(
source_width=600, source_height=800,
target_width=300, target_height=400,
halign="center", valign="middle",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=800, source_height=600,
target_width=0, target_height=0,
halign="center", valign="middle",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=800, source_height=600,
target_width=400, target_height=0,
halign="center", valign="middle",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=200, source_height=140,
target_width=180, target_height=100,
halign="center", valign="middle",
focal_points=[],
crop_left=0, crop_top=3, crop_right=200, crop_bottom=114
),
# tests with focal points
TestData(
source_width=200, source_height=200,
target_width=100, target_height=100,
halign="center", valign="middle",
focal_points=[fp(100, 100, 1)],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=400, source_height=200,
target_width=100, target_height=100,
halign="center", valign="middle",
focal_points=[fp(100, 100, 1)],
crop_left=50.0, crop_top=0, crop_right=250.0, crop_bottom=200
),
TestData(
source_width=400, source_height=200,
target_width=100, target_height=200,
halign="center", valign="middle",
focal_points=[fp(100, 50, 1), fp(300, 50, 1)],
crop_left=150.0, crop_top=0, crop_right=250.0, crop_bottom=200
),
TestData(
source_width=400, source_height=200,
target_width=100, target_height=200,
halign="center", valign="middle",
focal_points=[fp(100, 150, 1), fp(300, 150, 1)],
crop_left=150.0, crop_top=0, crop_right=250.0, crop_bottom=200
),
TestData(
source_width=400, source_height=200,
target_width=100, target_height=200,
halign="center", valign="middle",
focal_points=[fp(100, 50, 1), fp(100, 150, 1)],
crop_left=75.0, crop_top=0, crop_right=175.0, crop_bottom=200
),
TestData(
source_width=400, source_height=200,
target_width=100, target_height=200,
halign="center", valign="middle",
focal_points=[fp(300, 50, 1), fp(300, 150, 1)],
crop_left=225.0, crop_top=0, crop_right=325.0, crop_bottom=200
),
TestData(
source_width=200, source_height=400,
target_width=100, target_height=200,
halign="center", valign="middle",
focal_points=[fp(100, 50, 1), fp(300, 50, 1)],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=200, source_height=400,
target_width=100, target_height=200,
halign="center", valign="middle",
focal_points=[fp(100, 150, 1), fp(300, 150, 1)],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=200, source_height=400,
target_width=100, target_height=200,
halign="center", valign="middle",
focal_points=[fp(100, 50, 1), fp(100, 150, 1)],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=200, source_height=400,
target_width=100, target_height=200,
halign="center", valign="middle",
focal_points=[fp(300, 50, 1), fp(300, 150, 1)],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=400, source_height=200,
target_width=100, target_height=100,
halign="center", valign="middle",
focal_points=[fp(50, 100, 1), fp(50, 300, 1), fp(150, 100, 1), fp(150, 300, 1)],
crop_left=50.0, crop_top=0, crop_right=250.0, crop_bottom=200
),
# Larger Width
TestData(
source_width=800, source_height=600,
target_width=400, target_height=300,
halign="center", valign="bottom",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=700, source_height=300,
target_width=150, target_height=300,
halign="center", valign="bottom",
focal_points=[],
crop_left=275, crop_top=0, crop_right=425, crop_bottom=300
),
TestData(
source_width=700, source_height=300,
target_width=300, target_height=150,
halign="right", valign="bottom",
focal_points=[],
crop_left=100, crop_top=0, crop_right=700, crop_bottom=300
),
TestData(
source_width=700, source_height=300,
target_width=300, target_height=150,
halign="left", valign="bottom",
focal_points=[],
crop_left=0, crop_top=0, crop_right=600, crop_bottom=300
),
TestData(
source_width=700, source_height=300,
target_width=150, target_height=300,
halign="center", valign="bottom",
focal_points=[],
crop_left=275, crop_top=0, crop_right=425, crop_bottom=300
),
TestData(
source_width=700, source_height=300,
target_width=150, target_height=300,
halign="left", valign="bottom",
focal_points=[],
crop_left=0, crop_top=0, crop_right=150, crop_bottom=300
),
TestData(
source_width=700, source_height=300,
target_width=150, target_height=300,
halign="right", valign="bottom",
focal_points=[],
crop_left=550, crop_top=0, crop_right=700, crop_bottom=300
),
# Larger Height
TestData(
source_width=300, source_height=800,
target_width=200, target_height=300,
halign="center", valign="bottom",
focal_points=[],
crop_left=0, crop_top=251, crop_right=300, crop_bottom=701
),
TestData(
source_width=300, source_height=800,
target_width=200, target_height=300,
halign="left", valign="bottom",
focal_points=[],
crop_left=0, crop_top=251, crop_right=300, crop_bottom=701
),
TestData(
source_width=300, source_height=800,
target_width=200, target_height=300,
halign="right", valign="bottom",
focal_points=[],
crop_left=0, crop_top=251, crop_right=300, crop_bottom=701
),
TestData(
source_width=500, source_height=600,
target_width=300, target_height=250,
halign="center", valign="bottom",
focal_points=[],
crop_left=0, crop_top=119, crop_right=500, crop_bottom=536
),
TestData(
source_width=500, source_height=600,
target_width=300, target_height=250,
halign="left", valign="bottom",
focal_points=[],
crop_left=0, crop_top=119, crop_right=500, crop_bottom=536
),
TestData(
source_width=500, source_height=600,
target_width=300, target_height=250,
halign="right", valign="bottom",
focal_points=[],
crop_left=0, crop_top=119, crop_right=500, crop_bottom=536
),
# Proportional Height
TestData(
source_width=600, source_height=800,
target_width=300, target_height=0,
halign="right", valign="bottom",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=600, source_height=800,
target_width=300, target_height=0,
halign="center", valign="bottom",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=600, source_height=800,
target_width=300, target_height=0,
halign="left", valign="bottom",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=600, source_height=800,
target_width=250, target_height=0,
halign="left", valign="bottom",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=600, source_height=800,
target_width=250, target_height=0,
halign="right", valign="bottom",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=600, source_height=800,
target_width=250, target_height=0,
halign="center", valign="bottom",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
# Proportional Width
TestData(
source_width=600, source_height=800,
target_width=0, target_height=400,
halign="right", valign="bottom",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=600, source_height=800,
target_width=0, target_height=400,
halign="left", valign="bottom",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=600, source_height=800,
target_width=0, target_height=400,
halign="center", valign="bottom",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=600, source_height=800,
target_width=0, target_height=350,
halign="center", valign="bottom",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=600, source_height=800,
target_width=0, target_height=350,
halign="left", valign="bottom",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=600, source_height=800,
target_width=0, target_height=350,
halign="right", valign="bottom",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=800, source_height=600,
target_width=400, target_height=150,
halign="center", valign="middle",
focal_points=[],
crop_left=0, crop_top=75, crop_right=800, crop_bottom=375
),
TestData(
source_width=800, source_height=300,
target_width=400, target_height=150,
halign="center", valign="middle",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=800, source_height=300,
target_width=400, target_height=150,
halign="right", valign="middle",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=800, source_height=300,
target_width=400, target_height=150,
halign="left", valign="middle",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=700, source_height=300,
target_width=300, target_height=150,
halign="center", valign="middle",
focal_points=[],
crop_left=50, crop_top=0, crop_right=650, crop_bottom=300
),
TestData(
source_width=700, source_height=300,
target_width=300, target_height=150,
halign="left", valign="middle",
focal_points=[],
crop_left=0, crop_top=0, crop_right=600, crop_bottom=300
),
TestData(
source_width=700, source_height=300,
target_width=300, target_height=150,
halign="right", valign="middle",
focal_points=[],
crop_left=100, crop_top=0, crop_right=700, crop_bottom=300
),
TestData(
source_width=700, source_height=300,
target_width=150, target_height=300,
halign="center", valign="middle",
focal_points=[],
crop_left=275, crop_top=0, crop_right=425, crop_bottom=300
),
TestData(
source_width=700, source_height=300,
target_width=150, target_height=300,
halign="left", valign="middle",
focal_points=[],
crop_left=0, crop_top=0, crop_right=150, crop_bottom=300
),
TestData(
source_width=700, source_height=300,
target_width=150, target_height=300,
halign="right", valign="middle",
focal_points=[],
crop_left=550, crop_top=0, crop_right=700, crop_bottom=300
),
TestData(
source_width=350, source_height=700,
target_width=200, target_height=600,
halign="left", valign="middle",
focal_points=[],
crop_left=0, crop_top=0, crop_right=234, crop_bottom=700
),
TestData(
source_width=350, source_height=700,
target_width=200, target_height=600,
halign="center", valign="middle",
focal_points=[],
crop_left=58, crop_top=0, crop_right=292, crop_bottom=700
),
TestData(
source_width=350, source_height=700,
target_width=200, target_height=600,
halign="right", valign="middle",
focal_points=[],
crop_left=116, crop_top=0, crop_right=350, crop_bottom=700
),
TestData(
source_width=500, source_height=600,
target_width=300, target_height=250,
halign="left", valign="middle",
focal_points=[],
crop_left=0, crop_top=27, crop_right=500, crop_bottom=444
),
TestData(
source_width=500, source_height=600,
target_width=300, target_height=250,
halign="center", valign="middle",
focal_points=[],
crop_left=0, crop_top=27, crop_right=500, crop_bottom=444
),
TestData(
source_width=500, source_height=600,
target_width=300, target_height=250,
halign="right", valign="middle",
focal_points=[],
crop_left=0, crop_top=27, crop_right=500, crop_bottom=444
),
TestData(
source_width=1, source_height=1,
target_width=0, target_height=0,
halign="left", valign="middle",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=1, source_height=1,
target_width=0, target_height=0,
halign="center", valign="middle",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=1, source_height=1,
target_width=0, target_height=0,
halign="right", valign="middle",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=200, source_height=400,
target_width=0, target_height=1,
halign="left", valign="middle",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=200, source_height=200,
target_width=16, target_height=16,
halign="left", valign="middle",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
# Regular
TestData(
source_width=800, source_height=600,
target_width=400, target_height=150,
halign="left", valign="top",
focal_points=[],
crop_left=0, crop_top=0, crop_right=800, crop_bottom=300
),
TestData(
source_width=800, source_height=600,
target_width=400, target_height=150,
halign="center", valign="top",
focal_points=[],
crop_left=0, crop_top=0, crop_right=800, crop_bottom=300
),
TestData(
source_width=800, source_height=600,
target_width=400, target_height=150,
halign="right", valign="top",
focal_points=[],
crop_left=0, crop_top=0, crop_right=800, crop_bottom=300
),
# Inverted
TestData(
source_width=600, source_height=800,
target_width=150, target_height=400,
halign="left", valign="top",
focal_points=[],
crop_left=0, crop_top=0, crop_right=300, crop_bottom=800
),
TestData(
source_width=600, source_height=800,
target_width=150, target_height=400,
halign="center", valign="top",
focal_points=[],
crop_left=150, crop_top=0, crop_right=450, crop_bottom=800
),
TestData(
source_width=600, source_height=800,
target_width=150, target_height=400,
halign="right", valign="top",
focal_points=[],
crop_left=300, crop_top=0, crop_right=600, crop_bottom=800
),
# Wide and Small Height
TestData(
source_width=800, source_height=60,
target_width=400, target_height=15,
halign="left", valign="top",
focal_points=[],
crop_left=0, crop_top=0, crop_right=800, crop_bottom=30
),
TestData(
source_width=800, source_height=60,
target_width=400, target_height=15,
halign="center", valign="top",
focal_points=[],
crop_left=0, crop_top=0, crop_right=800, crop_bottom=30
),
TestData(
source_width=800, source_height=60,
target_width=400, target_height=15,
halign="right", valign="top",
focal_points=[],
crop_left=0, crop_top=0, crop_right=800, crop_bottom=30
),
# Tall and Small Width
TestData(
source_width=60, source_height=800,
target_width=15, target_height=400,
halign="left", valign="top",
focal_points=[],
crop_left=0, crop_top=0, crop_right=30, crop_bottom=800
),
TestData(
source_width=60, source_height=800,
target_width=15, target_height=400,
halign="center", valign="top",
focal_points=[],
crop_left=15, crop_top=0, crop_right=45, crop_bottom=800
),
TestData(
source_width=60, source_height=800,
target_width=15, target_height=400,
halign="right", valign="top",
focal_points=[],
crop_left=30, crop_top=0, crop_right=60, crop_bottom=800
),
# Small Values
TestData(
source_width=8, source_height=6,
target_width=4, target_height=2,
halign="left", valign="top",
focal_points=[],
crop_left=0, crop_top=0, crop_right=8, crop_bottom=4
),
TestData(
source_width=8, source_height=6,
target_width=4, target_height=2,
halign="center", valign="top",
focal_points=[],
crop_left=0, crop_top=0, crop_right=8, crop_bottom=4
),
TestData(
source_width=8, source_height=6,
target_width=4, target_height=2,
halign="right", valign="top",
focal_points=[],
crop_left=0, crop_top=0, crop_right=8, crop_bottom=4
),
# Inverted Small Values
TestData(
source_width=6, source_height=8,
target_width=2, target_height=4,
halign="left", valign="top",
focal_points=[],
crop_left=0, crop_top=0, crop_right=4, crop_bottom=8
),
TestData(
source_width=6, source_height=8,
target_width=2, target_height=4,
halign="center", valign="top",
focal_points=[],
crop_left=1, crop_top=0, crop_right=5, crop_bottom=8
),
TestData(
source_width=6, source_height=8,
target_width=2, target_height=4,
halign="right", valign="top",
focal_points=[],
crop_left=2, crop_top=0, crop_right=6, crop_bottom=8
),
# Proportional Values
TestData(
source_width=800, source_height=600,
target_width=400, target_height=300,
halign="left", valign="top",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=800, source_height=600,
target_width=400, target_height=300,
halign="center", valign="top",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=800, source_height=600,
target_width=400, target_height=300,
halign="right", valign="top",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
# Equal Values
TestData(
source_width=800, source_height=600,
target_width=800, target_height=600,
halign="left", valign="top",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=800, source_height=600,
target_width=800, target_height=600,
halign="center", valign="top",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=800, source_height=600,
target_width=800, target_height=600,
halign="right", valign="top",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None
),
TestData(
source_width=800, source_height=400,
target_width=400, target_height="orig",
halign="middle", valign="middle",
focal_points=[],
crop_left=200, crop_top=0, crop_right=600, crop_bottom=400
),
TestData(
source_width=800, source_height=400,
target_width="orig", target_height=100,
halign="middle", valign="middle",
focal_points=[],
crop_left=200, crop_top=0, crop_right=600, crop_bottom=400
),
TestData(
source_width=800, source_height=400,
target_width="orig", target_height="orig",
halign="middle", valign="middle",
focal_points=[],
crop_left=200, crop_top=0, crop_right=600, crop_bottom=400
)
]
FIT_IN_CROP_DATA = [
(TestData(
source_width=800, source_height=400,
target_width=400, target_height=100,
halign="middle", valign="middle",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None,
fit_in=True
), (200, 100, 1)),
(TestData(
source_width=1000, source_height=250,
target_width=500, target_height=200,
halign="middle", valign="middle",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None,
fit_in=True
), (500, 125, 1)),
(TestData(
source_width=200, source_height=250,
target_width=500, target_height=400,
halign="middle", valign="middle",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None,
fit_in=True
), (200, 250, 0)),
(TestData(
source_width=800, source_height=400,
target_width=100, target_height=400,
halign="middle", valign="middle",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None,
fit_in=True, adaptive=True
), (200, 100, 1)),
(TestData(
source_width=800, source_height=400,
target_width=400, target_height=100,
halign="middle", valign="middle",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None,
fit_in=True, full=True
), (400, 200, 1)),
(TestData(
source_width=200, source_height=250,
target_width=500, target_height=400,
halign="middle", valign="middle",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None,
fit_in=True, full=True
), (500, 625, 1)),
(TestData(
source_width=800, source_height=400,
target_width=100, target_height=400,
halign="middle", valign="middle",
focal_points=[],
crop_left=None, crop_top=None, crop_right=None, crop_bottom=None,
fit_in=True, adaptive=True, full=True
), (400, 200, 1))
]
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tests/test_library.py | movermeyer/mopidy-oe1 | 9 | 46572 | from __future__ import unicode_literals
import unittest
from mock import Mock
from mopidy.models import Ref
from mopidy_oe1.library import OE1LibraryProvider, OE1LibraryUri, OE1UriType
class OE1LibraryUriTest(unittest.TestCase):
def test_parse_root_uri(self):
uri = 'oe1:directory'
result = OE1LibraryUri.parse(uri)
self.assertEqual(result.uri_type, OE1UriType.ROOT)
def test_parse_live_uri(self):
uri = 'oe1:live'
result = OE1LibraryUri.parse(uri)
self.assertEqual(result.uri_type, OE1UriType.LIVE)
def test_parse_campus_uri(self):
uri = 'oe1:campus'
result = OE1LibraryUri.parse(uri)
self.assertEqual(result.uri_type, OE1UriType.CAMPUS)
def test_parse_archive_uri(self):
uri = 'oe1:archive'
result = OE1LibraryUri.parse(uri)
self.assertEqual(result.uri_type, OE1UriType.ARCHIVE)
def test_parse_day_uri(self):
uri = 'oe1:archive:20140914'
result = OE1LibraryUri.parse(uri)
self.assertEqual(result.uri_type, OE1UriType.ARCHIVE_DAY)
self.assertEqual(result.day_id, '20140914')
def test_parse_invalid_uri(self):
uri = 'foo:bar'
self.assertRaises(TypeError, OE1LibraryUri.parse, uri)
def test_parse_item_uri(self):
uri = 'oe1:archive:20140914:382176'
result = OE1LibraryUri.parse(uri)
self.assertEqual(result.uri_type, OE1UriType.ARCHIVE_ITEM)
self.assertEqual(result.day_id, '20140914')
self.assertEqual(result.item_id, '382176')
def test_create_root_uri(self):
parsed_uri = OE1LibraryUri(OE1UriType.ROOT)
self.assertEqual(str(parsed_uri), 'oe1:directory')
def test_create_live_uri(self):
parsed_uri = OE1LibraryUri(OE1UriType.LIVE)
self.assertEqual(str(parsed_uri), 'oe1:live')
def test_create_campus_uri(self):
parsed_uri = OE1LibraryUri(OE1UriType.CAMPUS)
self.assertEqual(str(parsed_uri), 'oe1:campus')
def test_create_archive_uri(self):
parsed_uri = OE1LibraryUri(OE1UriType.ARCHIVE)
self.assertEqual(str(parsed_uri), 'oe1:archive')
def test_create_day_uri(self):
parsed_uri = OE1LibraryUri(OE1UriType.ARCHIVE_DAY, '20140914')
self.assertEqual(str(parsed_uri), 'oe1:archive:20140914')
def test_create_item_uri(self):
parsed_uri = OE1LibraryUri(OE1UriType.ARCHIVE_ITEM,
'20140914', '382176')
self.assertEqual(str(parsed_uri), 'oe1:archive:20140914:382176')
class OE1LibraryProviderTest(unittest.TestCase):
def setUp(self):
self.client_mock = Mock()
self.client_mock.get_days = Mock(
return_value=[
{'id': '1', 'label': 'Day1'},
{'id': '2', 'label': 'Day2'}
]
)
self.client_mock.get_day = Mock(
return_value={
'items': [
{'id': '1', 'time': '01:00', 'title': 'Item1'},
{'id': '2', 'time': '02:00', 'title': 'Item2'},
{'id': '3', 'time': '03:00', 'title': 'Item3'}
]
}
)
self.client_mock.get_item = Mock(
return_value={'id': '1', 'time': '01:00', 'title': 'Item1'}
)
self.library = OE1LibraryProvider(None, client=self.client_mock)
def test_browse_invalid_uri(self):
uri = 'foo:bar'
result = self.library.browse(uri)
self.assertEqual(result, [])
def test_browse_unbrowsable_uri(self):
uri = str(OE1LibraryUri(OE1UriType.LIVE))
result = self.library.browse(uri)
self.assertEqual(result, [])
def test_browse_root(self):
uri = str(OE1LibraryUri(OE1UriType.ROOT))
result = self.library.browse(uri)
self.assertEqual(len(result), 3)
def test_browse_archive(self):
uri = str(OE1LibraryUri(OE1UriType.ARCHIVE))
result = self.library.browse(uri)
self.assertEqual(len(result), 2)
self.assertEqual(result[0].type, Ref.DIRECTORY)
self.assertEqual(result[0].uri, 'oe1:archive:1')
self.assertEqual(result[0].name, 'Day1')
def test_browse_archive_day(self):
uri = str(OE1LibraryUri(OE1UriType.ARCHIVE_DAY, '20140914'))
result = self.library.browse(uri)
self.client_mock.get_day.assert_called_once_with('20140914')
self.assertEqual(len(result), 3)
self.assertEqual(result[0].type, Ref.TRACK)
self.assertEqual(result[0].uri, 'oe1:archive:20140914:1')
self.assertEqual(result[0].name, '01:00: Item1')
def test_lookup_invalid_uri(self):
uri = 'foo:bar'
result = self.library.lookup(uri)
self.assertEqual(result, [])
def test_browse_unlookable_uri(self):
uri = str(OE1LibraryUri(OE1UriType.ROOT))
result = self.library.lookup(uri)
self.assertEqual(result, [])
def test_lookup_live(self):
uri = str(OE1LibraryUri(OE1UriType.LIVE))
result = self.library.lookup(uri)
self.assertEqual(len(result), 1)
self.assertEqual(result[0].uri, uri)
self.assertEqual(result[0].name, 'Live')
def test_lookup_campus(self):
uri = str(OE1LibraryUri(OE1UriType.CAMPUS))
result = self.library.lookup(uri)
self.assertEqual(len(result), 1)
self.assertEqual(result[0].uri, uri)
self.assertEqual(result[0].name, 'Campus')
def test_lookup_archive_day(self):
uri = str(OE1LibraryUri(OE1UriType.ARCHIVE_DAY, '20140914'))
result = self.library.lookup(uri)
self.client_mock.get_day.assert_called_once_with('20140914')
self.assertEqual(len(result), 3)
self.assertEqual(result[0].type, Ref.TRACK)
self.assertEqual(result[0].uri, 'oe1:archive:20140914:1')
self.assertEqual(result[0].name, '01:00: Item1')
def test_lookup_archive_item(self):
uri = str(OE1LibraryUri(OE1UriType.ARCHIVE_ITEM,
'20140914', '1234567'))
result = self.library.lookup(uri)
self.client_mock.get_item.assert_called_once_with(
'20140914', '1234567')
self.assertEqual(len(result), 1)
self.assertEqual(result[0].uri, 'oe1:archive:20140914:1')
self.assertEqual(result[0].name, '01:00: Item1')
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10976,
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2
] |
Cursoemvideo/desafios/desafio008.py | gentildf/Python | 1 | 9161 | #Escreva um programa que leia um valor em metros e o exiba convertido em centimetros e milimetros.
n = float(input('\033[32mDigite o numero:\033[m'))
print('O número digitado é \033[33m{0:.0f}m\033[m.\n'
'Ele apresentado em centimetros fica \033[33m{0:.2f}cm\033[m.\n'
'Apresentado em milímetros fica \033[33m{0:.3f}mm\033[m'
.format(n))
#print('O número em metros é {0}.\n
# O número em convertido para centimetros é {1}.\n
# O número convertido para milimetros é {2}'
# .format(n, n/100, n/1000))
| [
1,
396,
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1037,
1564,
1922,
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712,
454,
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429,
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4830,
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302,
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29900,
29900,
29892,
302,
29914,
29896,
29900,
29900,
29900,
876,
13,
2
] |
versions/3.0/karma/python/uri_manipulation.py | Lituta/dig-alignment | 5 | 161364 | from urllib import quote
import re
import uuid
class UM(object):
def __init__(self):
self.name = "Uri Manipulation"
@staticmethod
def uuid_uri(prefix):
"""Construct a URI using a UUID"""
return prefix + str(uuid.uuid1())
@staticmethod
def uuid_uri_or_empty(prefix, value):
"""Construct a URI using a UUID, but return empty if value is empty"""
if value is None or value == '':
return ''
else:
return prefix + str(uuid.uuid1())
@staticmethod
def phone_uri(x):
"""Return the uri for a phone
as countrycode-phone
Use 'x-' as country code if not present in the number
"""
x = PM.clean_phone(x)
if len(x) > 0:
dash_idx = x.find('-')
if dash_idx != -1:
return "phonenumber/" + x[1:]
return "phonenumber/x-" + x
return ''
@staticmethod
def email_uri(email):
c = SM.clean_email(email)
if len(c) > 0:
qc = quote(c, safe='')
return "email/" + qc
return ''
@staticmethod
def uri_from_fields(prefix, *fields):
"""Construct a URI out of the fields, concatenating them after removing offensive characters.
When all the fields are empty, return empty"""
string = '_'.join(SM.alpha_numeric(f.strip().lower(), '') for f in fields)
if len(string) == len(fields)-1:
return ''
return prefix + string
@staticmethod
def country_uri(x):
"""Return a URI for a country given its name."""
x = re.sub('[^A-Za-z0-9]+', '', x)
return x.lower()
@staticmethod
def person_name_uri(x):
"""Return a URI for a person name."""
x = re.sub('[^A-Za-z0-9]+', '', x.strip())
return x.lower()
| [
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363,
263,
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13,
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353,
337,
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1491,
877,
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29899,
29999,
29874,
29899,
29920,
29900,
29899,
29929,
10062,
742,
15516,
921,
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13,
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736,
921,
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13609,
580,
13,
13,
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732,
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5696,
13,
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822,
2022,
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978,
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1125,
13,
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263,
23539,
363,
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921,
29889,
17010,
3101,
13,
4706,
736,
921,
29889,
13609,
580,
13,
2
] |
syncgateway/__init__.py | ecordell/syncgateway-admin-client | 0 | 16952 | __author__ = '<NAME>'
__copyright__ = 'Copyright 2012-2015 Localmed, Inc.'
__version__ = "0.1.6"
__version_info__ = tuple(__version__.split('.'))
__short_version__ = __version__
| [
1,
4770,
8921,
1649,
353,
12801,
5813,
16299,
13,
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8552,
1266,
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13,
2
] |
setup.py | cedwards036/JHUHandshakeDataTools | 0 | 59524 | <reponame>cedwards036/JHUHandshakeDataTools
import pathlib
from setuptools import setup, find_packages
from jhu_handshake_data_tools import __version__, __author__, __email__
HERE = pathlib.Path(__file__).parent
README = (HERE / "README.md").read_text()
setup(
name="jhu_handshake_data_tools",
version=__version__,
description="A library for cleaning and working with majors from JHU's Handshake environment",
long_description=README,
url="https://github.com/cedwards036/JHUHandshakeDataTools",
author=__author__,
author_email=__email__,
license="MIT",
classifiers=[
"License :: OSI Approved :: MIT License",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.7",
],
packages=find_packages(),
include_package_data=True
)
| [
1,
529,
276,
1112,
420,
29958,
1133,
2935,
29900,
29941,
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3481,
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1296,
1469,
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13,
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13,
13,
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abstract_models/bisim/pick_puck.py | ondrejba/discrete_abstractions | 6 | 58894 | <filename>abstract_models/bisim/pick_puck.py
import numpy as np
class BisimPickPuckModel:
@classmethod
def get_state_block(cls, hand, layers, action_grid):
num_positions = action_grid.shape[0] * action_grid.shape[1]
action_grid = np.reshape(action_grid, (-1, 2))
if hand is not None:
return num_positions
else:
puck = layers[0][0]
index = cls.get_coords(action_grid, puck.x, puck.y)
return index
@staticmethod
def get_coords(action_grid, x, y):
return np.where(np.sum(action_grid == [x, y], axis=1) == 2)[0][0]
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