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setup.py | liudongliangHI/ProLIF | 123 | 11122489 | <filename>setup.py
from setuptools import setup
import versioneer
import re
# manually check RDKit version
try:
from rdkit import __version__ as rdkit_version
except ImportError:
raise ImportError("ProLIF requires RDKit but it is not installed")
else:
if re.match(r"^20[0-1][0-9]\.", rdkit_version):
raise ValueError("ProLIF requires a version of RDKit >= 2020")
setup(version=versioneer.get_version()) |
DQM/RPCMonitorClient/python/RPCEventSummary_cfi.py | ckamtsikis/cmssw | 852 | 11122541 | import FWCore.ParameterSet.Config as cms
from DQMServices.Core.DQMEDHarvester import DQMEDHarvester
rpcEventSummary = DQMEDHarvester("RPCEventSummary",
EventInfoPath = cms.untracked.string('RPC/EventInfo'),
PrescaleFactor = cms.untracked.int32(5),
MinimumRPCEvents = cms.untracked.int32(10000),
NumberOfEndcapDisks = cms.untracked.int32(4),
EnableEndcapSummary = cms.untracked.bool(True),
OfflineDQM = cms.untracked.bool(True),
RecHitTypeFolder = cms.untracked.string("AllHits")
)
|
yabgp/message/attribute/nlri/ipv6_flowspec.py | mengjunyi/yabgp | 203 | 11122561 | # Copyright 2015 Cisco Systems, Inc.
# All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
"""IPv6 Flowspec NLRI
"""
from __future__ import division
from builtins import range
import binascii
import math
import struct
import netaddr
from yabgp.common import constants as bgp_cons
from yabgp.message.attribute.nlri import NLRI
class IPv6FlowSpec(NLRI):
"""ipv6 flow nlri process
"""
@classmethod
def parse(cls, value):
"""
parse IPv6 flowspec NLRI
:param value:
:return:
"""
# +------------------------------+
# | length (0xnn or 0xfn nn) |
# +------------------------------+
# | NLRI value (variable) |
# +------------------------------+
nlri_dict = {}
while value:
offset = 0
flowspec_type = ord(value[0:1])
offset += 1
# decode all kinds of flow spec
if flowspec_type in [bgp_cons.BGPNLRI_FSPEC_DST_PFIX, bgp_cons.BGPNLRI_FSPEC_SRC_PFIX]:
prefix, offset_tmp = cls.parse_prefix(value[offset:])
offset += offset_tmp
nlri_dict[flowspec_type] = prefix
value = value[offset:]
elif flowspec_type in [bgp_cons.BGPNLRI_FSPEC_IP_PROTO, bgp_cons.BGPNLRI_FSPEC_DST_PORT,
bgp_cons.BGPNLRI_FSPEC_SRC_PORT, bgp_cons.BGPNLRI_FSPEC_ICMP_TP,
bgp_cons.BGPNLRI_FSPEC_ICMP_CD, bgp_cons.BGPNLRI_FSPEC_DSCP,
bgp_cons.BGPNLRI_FSPEC_PCK_LEN]:
operator_list, offset = cls.parse_operators(value[offset:])
nlri_dict[flowspec_type] = cls.operator_dict_to_str(operator_list)
value = value[offset:]
else:
operator_list, offset = cls.parse_operators(value[offset:])
nlri_dict[flowspec_type] = cls.operator_dict_to_str(operator_list)
value = value[offset:]
return nlri_dict
@classmethod
def construct(cls, value):
nlri_hex = b''
for nlri in value:
nlri_hex += cls.construct_nlri(nlri)
return nlri_hex
@classmethod
def construct_nlri(cls, data):
""" Construct NLRI """
# there may have many filters in each nlri
data = dict([(int(l), r) for (l, r) in data.items()])
nlri_tmp = b''
for type_tmp in [bgp_cons.BGPNLRI_IPV6_FSPEC_DST_PFIX, bgp_cons.BGPNLRI_IPV6_FSPEC_SRC_PFIX]:
if data.get(type_tmp):
nlri_tmp += struct.pack('!B', type_tmp) + cls.construct_prefix(data[type_tmp])
for type_tmp in [bgp_cons.BGPNLRI_IPV6_FSPEC_NEXT_HEADER, bgp_cons.BGPNLRI_IPV6_FSPEC_PORT,
bgp_cons.BGPNLRI_IPV6_FSPEC_DST_PORT, bgp_cons.BGPNLRI_IPV6_FSPEC_SRC_PORT,
bgp_cons.BGPNLRI_IPV6_FSPEC_ICMP_TP, bgp_cons.BGPNLRI_IPV6_FSPEC_ICMP_CD,
bgp_cons.BGPNLRI_IPV6_FSPEC_TCP_FLAGS, bgp_cons.BGPNLRI_IPV6_FSPEC_PCK_LEN,
bgp_cons.BGPNLRI_IPV6_FSPEC_DSCP, bgp_cons.BGPNLRI_IPV6_FSPEC_FRAGMENT,
bgp_cons.BGPNLRI_IPV6_FSPEC_FLOW_LABLE]:
if not data.get(type_tmp):
continue
# translate from expression to binary
nlri_tmp += struct.pack('!B', type_tmp) + cls.construct_operators(data[type_tmp])
if len(nlri_tmp) >= 240:
return struct.pack('!H', len(nlri_tmp)) + nlri_tmp
elif nlri_tmp:
return struct.pack('!B', len(nlri_tmp)) + nlri_tmp
@staticmethod
def parse_prefix(data):
"""
Prefixes are encoded as in BGP UPDATE messages, a length in bits is followed by
enough octets to contain the prefix information.
Encoding: <prefix-length (1 octet), prefix>
"""
prefix_len = ord(data[0:1])
octet_len = int(math.ceil(prefix_len / 8))
tmp = data[1:octet_len + 1]
if isinstance(tmp[0], int):
prefix_data = [i for i in tmp]
else:
prefix_data = [ord(i) for i in tmp]
prefix_data = prefix_data + list(str(0)) * 4
prefix = "%s.%s.%s.%s" % (tuple(prefix_data[0:4])) + '/' + str(prefix_len)
return prefix, octet_len + 1
@classmethod
def construct_prefix(cls, prefix):
"""
construct a prefix string from '1.1.1.0/24' to '\x18\x01\x01\x01'
"""
prefix_value = prefix.get('prefix')
ip, masklen = prefix_value.split('/')
ip_hex = netaddr.IPAddress(ip).packed
offset = prefix.get('offset')
masklen = int(masklen)
# lenght
ip_hex = ip_hex[: math.ceil(masklen / 8)]
# offset
ip_hex = ip_hex[math.floor(offset / 8):]
# ip_hex = ip_hex[]
return struct.pack('!B', masklen) + struct.pack('!B', offset) + ip_hex
@classmethod
def parse_operators(cls, data):
offset = 0
parse_operator_list = []
while data:
operator = cls.parse_operator_flag(ord(data[0:1]))
# print(operator)
offset += 1
operator_value = int(binascii.b2a_hex(data[1:1 + operator['LEN']]), 16)
offset += operator['LEN']
parse_operator_list.append([operator, operator_value])
# the end of the list
data = data[1 + operator['LEN']:]
if operator['EOL']:
break
return parse_operator_list, offset + 1
@staticmethod
def parse_operator_flag(data):
"""
The operator byte is encoded as:
0 1 2 3 4 5 6 7
+---+---+---+---+---+---+---+---+
|EOL|AND| LEN |RES|LT |GT |EQ |
+---+---+---+---+---+---+---+---+
"""
bit_list = []
for i in range(8):
bit_list.append((data >> i) & 1)
bit_list.reverse()
result = {
'EOL': bit_list[0],
'AND': bit_list[1],
'LEN': 1 << (bit_list[2] * 2 + bit_list[3]),
'LT': bit_list[5],
'GT': bit_list[6],
'EQ': bit_list[7]
}
return result
@staticmethod
def construct_operator_flag(data):
"""construct operator flag from dict to binary
"""
opt_dict = {
'EOL': 0x80,
'AND': 0x40,
'LEN': {
1: 0x00,
2: 0x10,
4: 0x20,
6: 0x30
},
'RES': 0x00,
'LT': 0x04,
'GT': 0x02,
'EQ': 0x01
}
b_data = 0x00
for opt in opt_dict:
if opt in data and opt != 'LEN':
if data[opt] == 1:
b_data += opt_dict[opt]
elif opt == 'LEN' and data[opt]:
b_data += opt_dict['LEN'][data['LEN']]
return b_data
@staticmethod
def operator_dict_to_str(data):
"""
from
[
[
{'AND': 0, 'GT': 0, 'LEN': 1, 'EOL': 0, 'LT': 0, 'EQ': 1},
254
],
[
{'AND': 0, 'GT': 1, 'LEN': 1, 'EOL': 0, 'LT': 0, 'EQ': 1},
254
],
[
{'AND': 1, 'GT': 0, 'LEN': 2, 'EOL': 1, 'LT': 1, 'EQ': 1},
300
]
]
to
=254|>=254&<=300
:param data: dict
:return: string format
"""
return_str = ''
for item in data:
operator_dict, value = item
if operator_dict['AND']:
return_str += '&'
else:
if return_str != '':
return_str += '|'
if operator_dict['GT']:
return_str += '>'
if operator_dict['LT']:
return_str += '<'
if operator_dict['EQ']:
return_str += '='
return_str += str(value)
return return_str
@classmethod
def construct_operators(cls, data):
"""
from "=254|>=254&<=300" to binary data
:param data:
:return:
"""
data_bin = b''
data_list = data.split('|')
eol = 0
for i, data in enumerate(data_list):
if i == len(data_list) - 1:
eol = 1
if '&' not in data:
flag_dict = {'EOL': eol}
if data[0] == '=':
off_set = 1
flag_dict['EQ'] = 1
elif '>=' in data:
off_set = 2
flag_dict['EQ'] = 1
flag_dict['GT'] = 1
elif '<=' in data:
off_set = 2
flag_dict['EQ'] = 1
flag_dict['LT'] = 1
elif '>' in data:
off_set = 1
flag_dict['GT'] = 1
elif '<' in data:
off_set = 1
flag_dict['LT'] = 1
hex_str = hex(int(data[off_set:]))[2:]
if len(hex_str) % 2 == 1:
hex_str = '0' + hex_str
value_hex = bytearray.fromhex(hex_str)
flag_dict['LEN'] = len(value_hex)
opt_flag_bin = cls.construct_operator_flag(flag_dict)
data_bin += struct.pack('!B', opt_flag_bin)
data_bin += value_hex
return data_bin
|
hata/discord/activity/activity_types.py | Multiface24111/hata | 173 | 11122592 | <reponame>Multiface24111/hata<filename>hata/discord/activity/activity_types.py
__all__ = ()
__doc__ = """
A module, which contains the activity types' discord side value.
+-----------+-------+
| Name | Value |
+===========+=======+
| game | 0 |
+-----------+-------+
| stream | 1 |
+-----------+-------+
| spotify | 2 |
+-----------+-------+
| watching | 3 |
+-----------+-------+
| custom | 4 |
+-----------+-------+
| competing | 5 |
+-----------+-------+
"""
game = 0
stream = 1
spotify = 2
watching = 3
custom = 4
competing = 5
|
Python/orangeHello.py | saurabhcommand/Hello-world | 1,428 | 11122602 | def helloName(name):
print ("Hello " + name)
helloName("John")
|
evalml/utils/update_checker.py | Mahesh1822/evalml | 454 | 11122603 | <reponame>Mahesh1822/evalml<filename>evalml/utils/update_checker.py
"""Check if EvalML has updated since the user installed."""
from pkg_resources import iter_entry_points
for entry_point in iter_entry_points("alteryx_open_src_initialize"):
try:
method = entry_point.load()
if callable(method):
method("evalml")
except Exception:
pass
|
grove/alpha/fermion_transforms/tests/test_bravyi_kitaev.py | mkeshita/grove | 229 | 11122635 | import numpy as np
import pytest
from grove.alpha.fermion_transforms.bktransform import BKTransform
from grove.alpha.fermion_transforms.jwtransform import JWTransform
"""
Some tests inspired by:
https://github.com/ProjectQ-Framework/FermiLib/blob/develop/src/fermilib/transforms/_bravyi_kitaev_test.py
"""
def test_hardcoded_transform():
n_qubits = 16
bkt = BKTransform(n_qubits)
x = bkt.kill(9)
y = bkt.create(9)
assert str(x) == '(0.5+0j)*X9*Z7*Z8*X11*X15 + 0.5j*Y9*X11*X15*Z7'
assert str(y) == '(0.5+0j)*X9*Z7*Z8*X11*X15 + -0.5j*Y9*X11*X15*Z7'
def test_term_length():
# create/kill operators are two-term
n_qubits = 16
bkt = BKTransform(n_qubits)
assert len(bkt.create(3)) == 2
assert len(bkt.kill(3)) == 2
n_qubits = 7
bkt = BKTransform(n_qubits)
assert len(bkt.create(3)) == 2
assert len(bkt.kill(3)) == 2
def test_throw_errors():
# throw error when creation outside qubit range
n_qubits = 16
bkt = BKTransform(n_qubits)
with pytest.raises(IndexError):
bkt.kill(-1)
with pytest.raises(IndexError):
bkt.kill(16)
with pytest.raises(IndexError):
bkt.kill(17)
def test_locality_invariant():
# for n_qubits = 2**d, c_j Majorana is always log2(N) + 1 local
n_qubits = 16
bkt = BKTransform(n_qubits)
invariant = np.log2(n_qubits) + 1
for index in range(n_qubits):
op = bkt.kill(index)
op_terms = op.terms
for term in op_terms:
coeff = term.coefficient
# Identify the c Majorana terms by real
# coefficients and check their length.
if not isinstance(coeff, complex):
assert len(term) == invariant
@pytest.mark.skip(reason="pyQuil Pauli needs matrix operator / eigenspectrum "
"functionality")
def test_eigenspectrum():
# Jordan-Wigner and Bravyi-Kitaev operators should give same eigenspectrum
# single number operator
n_qubits = 16
bkt = BKTransform(n_qubits)
op_BK = bkt.create(3) * bkt.kill(3)
jwt = JWTransform()
op_JW = jwt.create(3) * jwt.kill(3)
assert np.sort(np.linalg.eigvals(op_BK.matrix())) == \
np.sort(np.linalg.eigvals(op_JW.matrix()))
# sum of number operators
op_BK = 0
op_JW = 0
for i in [1, 3, 5]:
op_BK += bkt.create(i) * bkt.kill(i)
op_JW += jwt.create(i) * jwt.kill(i)
assert np.sort(np.linalg.eigvals(op_BK.matrix())) == \
np.sort(np.linalg.eigvals(op_JW.matrix()))
# scaled number operator
op_BK = 3 * bkt.create(3) * bkt.kill(3)
op_JW = 3 * jwt.create(3) * jwt.kill(3)
assert np.sort(np.linalg.eigvals(op_BK.matrix())) == \
np.sort(np.linalg.eigvals(op_JW.matrix()))
|
director/migrations/versions/05cf96d6fcae_add_task_result.py | apikay/celery-director | 351 | 11122646 | """Add task result
Revision ID: 05cf96d6fcae
Revises: <PASSWORD>
Create Date: 2020-03-20 19:16:48.520652
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "<KEY>e"
down_revision = "<PASSWORD>"
branch_labels = None
depends_on = None
def upgrade():
op.add_column("tasks", sa.Column("result", sa.PickleType(), nullable=True))
def downgrade():
op.drop_column("tasks", "result")
|
qtl/src/ase_aggregate_by_individual.py | richardslab/gtex-pipeline | 247 | 11122769 | # Author: <NAME>
import numpy as np
import scipy.stats
import pandas as pd
import argparse
import pyBigWig
import os
import subprocess
import io
import gzip
import pickle
def padjust_bh(p):
"""
Benjamini-Hochberg ajdusted p-values
Replicates p.adjust(p, method="BH") from R
"""
n = len(p)
i = np.arange(n,0,-1)
o = np.argsort(p)[::-1]
ro = np.argsort(o)
return np.minimum(1, np.minimum.accumulate(np.float(n)/i * np.array(p)[o]))[ro]
parser = argparse.ArgumentParser(description='ASE')
parser.add_argument('read_count_file_list', help='Read count file list (one per sample); [sample_id, tissue_site_detail, file_path]')
parser.add_argument('het_vcf')
parser.add_argument('vep_dict')
parser.add_argument('simulation_bias_file', help='?')
parser.add_argument('mappability_bigwig', help='Mappability track in bigWig format')
parser.add_argument('tissue_abbreviations', help='File mapping tissue_site_detail to abbreviation')
parser.add_argument('lamp_values', help='Table with foreign allele frequency per individual')
parser.add_argument('individual_id', help='individual_id')
parser.add_argument('--coverage_cutoff', default=8, type=int, help='')
parser.add_argument('--other_ratio_cutoff', default=0.05, type=float, help='')
parser.add_argument('--mono_cutoff', default=0.01, type=float, help='')
parser.add_argument('-o', '--output_dir', default='.')
args = parser.parse_args()
print('Parsing inputs')
tissue2abrv = pd.read_csv(args.tissue_abbreviations, sep='\t', index_col=0, squeeze=True).to_dict()
readcount_file_df = pd.read_csv(args.read_count_file_list, sep='\t', index_col=0)
df = pd.read_csv(args.simulation_bias_file, sep='\t', header=None, dtype=str)
simulation_bias_set = set(df[0]+':'+df[1])
print('Parsing read count files')
readcount_df_list = []
for i,rfile in enumerate(readcount_file_df['ase_readcount_file']):
readcount_df = pd.read_csv(rfile, sep='\t', index_col=2)
readcount_df = readcount_df[['contig', 'position', 'refAllele', 'altAllele', 'refCount', 'altCount', 'totalCount', 'otherBases']]
readcount_df = readcount_df.rename(columns={'contig':'chr', 'position':'coord', 'refAllele':'ref', 'altAllele':'alt',
'refCount':'refcount', 'altCount':'altcount', 'totalCount':'totalcount', 'otherBases':'othercount'})
readcount_df = readcount_df[readcount_df['totalcount']>=args.coverage_cutoff]
readcount_df['refratio'] = readcount_df['refcount']/readcount_df['totalcount']
readcount_df['otherratio'] = readcount_df['othercount'] / (readcount_df['othercount'] + readcount_df['totalcount'])
readcount_df['otherflag'] = (readcount_df['otherratio']>=args.other_ratio_cutoff)*1
readcount_df['allcount'] = readcount_df['totalcount'] + readcount_df['othercount']
sample_id = readcount_file_df.index[i]
readcount_df['sampid'] = sample_id
readcount_df['subjid'] = '-'.join(sample_id.split('-')[:2])
readcount_df['tissue'] = readcount_file_df.loc[sample_id, 'tissue_site_detail']
readcount_df['tissueabrv'] = tissue2abrv[readcount_file_df.loc[sample_id, 'tissue_site_detail']]
readcount_df['covflag'] = 0 # covflag is never 1, since filtered above (coverage_cutoff)
readcount_df_list.append(readcount_df)
print('Loading VCF')
vcf_df = pd.read_csv(args.het_vcf, sep='\t', comment='#', header=None,
names=['chr', 'pos', 'id', 'ref', 'alt', 'qual', 'filter', 'info', 'format', 'genotype'], dtype=str,
usecols=['chr', 'pos', 'id', 'info','format', 'genotype'], index_col=2)
vcf_snp_id_df = pd.DataFrame(index=vcf_df.index, columns=['chr', 'coord', 'genotype', 'ensg', 'vtype', 'mapbias', 'mapflag', 'monoflag', 'mono_refcount', 'mono_altcount', 'mono_totalcount', 'mono_othercount'])
vcf_snp_id_df[['chr', 'coord']] = vcf_df[['chr', 'pos']]
vcf_snp_id_df['genotype'] = vcf_df['format']+';'+vcf_df['genotype']
print('Adding VEP annotation')
with open(args.vep_dict, 'rb') as f:
vep_dict = pickle.load(f)
ensg = []
vtype = []
for i in vcf_df.index:
gene_name, vep = vep_dict.get(i, ('NA','NA'))
ensg.append(gene_name)
vtype.append(vep)
vcf_snp_id_df['ensg'] = ensg
vcf_snp_id_df['vtype'] = vtype
vep_dict = None
print('Adding mappability')
mp = []
bw = pyBigWig.open(args.mappability_bigwig)
for c,p in zip(vcf_df['chr'], vcf_df['pos']):
mp.append((bw.stats(c, int(p)-1, int(p), exact=True)[0]!=1) * 1) # BED coordinates, 0-indexed; input must be int (not numpy)
bw.close()
vcf_snp_id_df['mapbias'] = [1 if i in simulation_bias_set else 0 for i in vcf_snp_id_df['chr']+':'+vcf_snp_id_df['coord']]
vcf_snp_id_df['mapflag'] = mp
vcf_snp_id_df['monoflag'] = 0
vcf_snp_id_df['mono_refcount'] = 0
vcf_snp_id_df['mono_altcount'] = 0
vcf_snp_id_df['mono_totalcount'] = 0
vcf_snp_id_df['mono_othercount'] = 0
for readcount_df in readcount_df_list:
# combine read counts for each variant
vcf_snp_id_df.loc[readcount_df.index, 'mono_refcount'] += readcount_df['refcount']
vcf_snp_id_df.loc[readcount_df.index, 'mono_altcount'] += readcount_df['altcount']
vcf_snp_id_df.loc[readcount_df.index, 'mono_totalcount'] += readcount_df['totalcount']
vcf_snp_id_df.loc[readcount_df.index, 'mono_othercount'] += readcount_df['othercount']
print('Calculating statistics')
lamp = pd.read_csv(args.lamp_values, sep='\t', index_col=0, squeeze=True).median()
ref = vcf_snp_id_df['mono_refcount']
tot = vcf_snp_id_df['mono_totalcount']
monop_list = scipy.stats.binom.cdf(tot-ref, tot, 1-lamp) + scipy.stats.binom.cdf(ref, tot, 1-lamp) # monoallelic_p
monop_adj_list = padjust_bh(monop_list)
vcf_snp_id_df['monoflag'] = (monop_adj_list > args.mono_cutoff) * 1
indiv_cov75_counts = []
for readcount_df in readcount_df_list:
readcount_df['GENOTYPE_WARNING'] = vcf_snp_id_df.loc[readcount_df.index, 'monoflag']
idx = (vcf_snp_id_df.loc[readcount_df.index, ['monoflag', 'mapbias', 'mapflag']].sum(axis=1)==0) & (readcount_df['otherflag']==0)
indiv_cov75_counts.extend(list(readcount_df.loc[idx, 'totalcount']))
cov75 = np.percentile(indiv_cov75_counts, 75)
print('Calculating bias')
genomewide_bias = [0.0, 0.0, 0]
for readcount_df in readcount_df_list:
idx = (readcount_df[['covflag', 'otherflag']].sum(axis=1) + vcf_snp_id_df.loc[readcount_df.index, ['mapbias', 'mapflag', 'monoflag']].sum(axis=1)) == 0
refcountcov = readcount_df.loc[idx, 'refcount']
altcountcov = readcount_df.loc[idx, 'altcount']
totcountcov = refcountcov + altcountcov
bias_keys = readcount_df.loc[idx, 'ref']+'/'+readcount_df.loc[idx, 'alt']
idx2 = (refcountcov+altcountcov) > cov75
refcountcov[idx2] = cov75*(refcountcov[idx2]/totcountcov[idx2])
altcountcov[idx2] = cov75 - refcountcov[idx2]
totcountcov[idx2] = cov75
genomewide_bias[0] += refcountcov.sum()
genomewide_bias[1] += totcountcov.sum()
genomewide_bias[2] += refcountcov.shape[0]
genomewide_bias_value = float(genomewide_bias[0]) / genomewide_bias[1]
print('Calculating binomial tests, adjusted p-values')
for readcount_df in readcount_df_list:
readcount_df['binom_p'] = [scipy.stats.binom_test(i, j, genomewide_bias_value) for i,j in zip(readcount_df['refcount'], readcount_df['totalcount'])]
readcount_df['nullratio'] = genomewide_bias_value
idx = (readcount_df[['covflag', 'otherflag']].sum(axis=1) + vcf_snp_id_df.loc[readcount_df.index, ['mapbias', 'mapflag', 'monoflag']].sum(axis=1))==0
readcount_df.loc[idx, 'binom_p_adj'] = padjust_bh(readcount_df.loc[idx, 'binom_p'])
readcount_df.loc[~idx, 'binom_p_adj'] = 'NA'
print('Writing output')
with gzip.open(os.path.join(args.output_dir, args.individual_id+'.ase_table.tsv.gz'), 'wt') as f:
f.write('\t'.join([
'CHR',
'POS',
'VARIANT_ID',
'REF_ALLELE',
'ALT_ALLELE',
'SAMPLE_ID',
'SUBJECT_ID',
'TISSUE_ID',
'REF_COUNT',
'ALT_COUNT',
'TOTAL_COUNT',
'REF_RATIO',
'OTHER_ALLELE_COUNT',
'NULL_RATIO',
'BINOM_P',
'BINOM_P_ADJUSTED',
'MAMBA_POST_SINGLETIS',
'MAMBA_POST_MULTITIS',
'GENOTYPE',
'VARIANT_ANNOTATION',
'GENE_ID',
'LOW_MAPABILITY',
'MAPPING_BIAS_SIM',
'GENOTYPE_WARNING'])+'\n')
merged_df = []
for readcount_df in readcount_df_list:
readcount_df['id'] = readcount_df.index
readcount_df['blank'] = 'NA'
out_df = readcount_df[['chr', 'coord', 'id', 'ref', 'alt', 'sampid', 'subjid', 'tissueabrv', 'refcount', 'altcount', 'totalcount', 'refratio', 'othercount', 'nullratio',
'binom_p', 'binom_p_adj', 'blank', 'blank']]
merged_df.append(pd.concat([out_df, vcf_snp_id_df.loc[readcount_df.index, ['genotype', 'vtype', 'ensg', 'mapflag', 'mapbias']], readcount_df['GENOTYPE_WARNING']], axis=1))
merged_df = pd.concat(merged_df, axis=0)
merged_df = merged_df.sort_values(['chr', 'coord', 'tissueabrv'])
merged_df.to_csv(f, sep='\t', index=False, header=False, float_format='%.6g')
print('Done')
|
tests/functional/api/views/route_by_content_test.py | hypothesis/via | 113 | 11122864 | <gh_stars>100-1000
from urllib.parse import quote_plus
import httpretty
import pytest
from h_matchers import Any
from tests.conftest import assert_cache_control
class TestRouteByContent:
DEFAULT_OPTIONS = {
"via.client.ignoreOtherConfiguration": "1",
"via.client.openSidebar": "1",
"via.external_link_mode": "new-tab",
}
@pytest.mark.usefixtures("html_response", "checkmate_pass")
def test_proxy_html(self, test_app):
target_url = "http://example.com"
response = test_app.get(f"/route?url={target_url}")
assert response.status_code == 302
query = dict(self.DEFAULT_OPTIONS)
assert response.location == Any.url.matching(
f"https://viahtml.hypothes.is/proxy/{target_url}/"
).with_query(query)
@pytest.mark.usefixtures("pdf_response", "checkmate_pass")
def test_proxy_pdf(self, test_app):
target_url = "http://example.com"
response = test_app.get(f"/route?url={target_url}")
assert response.status_code == 302
query = dict(self.DEFAULT_OPTIONS)
query["via.sec"] = Any.string()
query["url"] = target_url
assert response.location == Any.url.matching(
f"http://localhost/pdf?url={quote_plus(target_url)}"
).with_query(query)
assert_cache_control(
response.headers, ["public", "max-age=300", "stale-while-revalidate=86400"]
)
@pytest.fixture
def html_response(self):
httpretty.register_uri(
httpretty.GET,
"http://example.com",
status=204,
adding_headers={"Content-Type": "text/html"},
)
@pytest.fixture
def pdf_response(self):
httpretty.register_uri(
httpretty.GET,
"http://example.com",
status=204,
adding_headers={"Content-Type": "application/pdf"},
)
|
observations/r/wong.py | hajime9652/observations | 199 | 11122869 | <gh_stars>100-1000
# -*- coding: utf-8 -*-
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import csv
import numpy as np
import os
import sys
from observations.util import maybe_download_and_extract
def wong(path):
"""Post-Coma Recovery of IQ
The `Wong` data frame has 331 row and 7 columns. The observations are
longitudinal data on recovery of IQ after comas of varying duration for
200 subjects.
This data frame contains the following columns:
`id`
patient ID number.
`days`
number of days post coma at which IQs were measured.
`duration`
duration of the coma in days.
`sex`
a factor with levels `Female` and `Male`.
`age`
in years at the time of injury.
`piq`
performance (i.e., mathematical) IQ.
`viq`
verbal IQ.
<NAME>., <NAME>., and <NAME>. (2001) Mathematical models
of cognitive recovery. *Brain Injury*, **15**, 519–530.
Args:
path: str.
Path to directory which either stores file or otherwise file will
be downloaded and extracted there.
Filename is `wong.csv`.
Returns:
Tuple of np.ndarray `x_train` with 331 rows and 7 columns and
dictionary `metadata` of column headers (feature names).
"""
import pandas as pd
path = os.path.expanduser(path)
filename = 'wong.csv'
if not os.path.exists(os.path.join(path, filename)):
url = 'http://dustintran.com/data/r/car/Wong.csv'
maybe_download_and_extract(path, url,
save_file_name='wong.csv',
resume=False)
data = pd.read_csv(os.path.join(path, filename), index_col=0,
parse_dates=True)
x_train = data.values
metadata = {'columns': data.columns}
return x_train, metadata
|
fastapi_contrib/auth/permissions.py | mumtozvalijonov/fastapi_contrib | 504 | 11122882 | <reponame>mumtozvalijonov/fastapi_contrib<filename>fastapi_contrib/auth/permissions.py<gh_stars>100-1000
from starlette.requests import Request
from starlette import status
from fastapi_contrib.permissions import BasePermission
class IsAuthenticated(BasePermission):
"""
Permission that checks if the user has been authenticated (by middleware)
Use it as an argument to `PermissionsDependency` as follows:
.. code-block:: python
app = FastAPI()
@app.get(
"/user/",
dependencies=[Depends(PermissionsDependency([IsAuthenticated]))]
)
async def user(request: Request) -> dict:
return request.scope["user"].dict()
"""
error_msg = "Not authenticated."
status_code = status.HTTP_401_UNAUTHORIZED
error_code = status.HTTP_401_UNAUTHORIZED
def has_required_permissions(self, request: Request) -> bool:
return request.user is not None
|
messaging/api/views.py | maznu/peering-manager | 127 | 11122891 | <gh_stars>100-1000
from rest_framework.routers import APIRootView
from messaging.api.serializers import (
ContactAssignmentSerializer,
ContactRoleSerializer,
ContactSerializer,
EmailSerializer,
)
from messaging.filters import (
ContactAssignmentFilterSet,
ContactFilterSet,
ContactRoleFilterSet,
EmailFilterSet,
)
from messaging.models import Contact, ContactAssignment, ContactRole, Email
from peering_manager.api.views import ModelViewSet
class MessagingRootView(APIRootView):
def get_view_name(self):
return "Messaging"
class ContactRoleViewSet(ModelViewSet):
queryset = ContactRole.objects.all()
serializer_class = ContactRoleSerializer
filterset_class = ContactRoleFilterSet
class ContactViewSet(ModelViewSet):
queryset = Contact.objects.all()
serializer_class = ContactSerializer
filterset_class = ContactFilterSet
class ContactAssignmentViewSet(ModelViewSet):
queryset = ContactAssignment.objects.prefetch_related("object", "contact", "role")
serializer_class = ContactAssignmentSerializer
filterset_class = ContactAssignmentFilterSet
class EmailViewSet(ModelViewSet):
queryset = Email.objects.all()
serializer_class = EmailSerializer
filterset_class = EmailFilterSet
|
skidl/libs/xilinx_sklib.py | arjenroodselaar/skidl | 700 | 11122908 | <filename>skidl/libs/xilinx_sklib.py
from skidl import SKIDL, TEMPLATE, Part, Pin, SchLib
SKIDL_lib_version = '0.0.1'
xilinx = SchLib(tool=SKIDL).add_parts(*[
Part(name='4003APG120',dest=TEMPLATE,tool=SKIDL,do_erc=True,aliases=['4003PG120']),
Part(name='4003HPQ208',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='4005HMQ240',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='4013PQ240',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='XC1736APD8',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='XC18V01SO20',dest=TEMPLATE,tool=SKIDL,ref_prefix='U',num_units=1,do_erc=True,pins=[
Pin(num='1',name='D0',func=Pin.OUTPUT,do_erc=True),
Pin(num='2',name='D2',func=Pin.OUTPUT,do_erc=True),
Pin(num='3',name='CLK',do_erc=True),
Pin(num='4',name='TDI',do_erc=True),
Pin(num='5',name='TMS',do_erc=True),
Pin(num='6',name='TCK',do_erc=True),
Pin(num='7',name='D4/CF',func=Pin.OPENCOLL,do_erc=True),
Pin(num='8',name='OE/RESET',do_erc=True),
Pin(num='9',name='D6',func=Pin.OUTPUT,do_erc=True),
Pin(num='10',name='CE',do_erc=True),
Pin(num='20',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='11',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='12',name='D7',func=Pin.OUTPUT,do_erc=True),
Pin(num='13',name='CEO',func=Pin.OUTPUT,do_erc=True),
Pin(num='14',name='D5',func=Pin.OUTPUT,do_erc=True),
Pin(num='15',name='D3',func=Pin.OUTPUT,do_erc=True),
Pin(num='16',name='D1',func=Pin.OUTPUT,do_erc=True),
Pin(num='17',name='TDO',func=Pin.OPENCOLL,do_erc=True),
Pin(num='18',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='19',name='VCCO',func=Pin.PWRIN,do_erc=True)]),
Part(name='XC2018-PC68',dest=TEMPLATE,tool=SKIDL,do_erc=True,aliases=['XC2064-PC68']),
Part(name='XC2018-PC84',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='XC2C256-TQ144',dest=TEMPLATE,tool=SKIDL,keywords='CPLD',description='CoolRunner-II CPLD, 256 macrocells',ref_prefix='U',num_units=1,fplist=['TQFP*20x20mm*Pitch0.5mm*'],do_erc=True,pins=[
Pin(num='1',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='2',name='GTS2',func=Pin.BIDIR,do_erc=True),
Pin(num='3',name='GTS3',func=Pin.BIDIR,do_erc=True),
Pin(num='4',name='P4',func=Pin.BIDIR,do_erc=True),
Pin(num='5',name='GTS0',func=Pin.BIDIR,do_erc=True),
Pin(num='6',name='GTS1',func=Pin.BIDIR,do_erc=True),
Pin(num='7',name='P7',func=Pin.BIDIR,do_erc=True),
Pin(num='8',name='VCCAUX',func=Pin.PWRIN,do_erc=True),
Pin(num='9',name='P9',func=Pin.BIDIR,do_erc=True),
Pin(num='10',name='P10',func=Pin.BIDIR,do_erc=True),
Pin(num='20',name='P20',func=Pin.BIDIR,do_erc=True),
Pin(num='30',name='GCK0',func=Pin.BIDIR,do_erc=True),
Pin(num='40',name='P40',func=Pin.BIDIR,do_erc=True),
Pin(num='50',name='P50',func=Pin.BIDIR,do_erc=True),
Pin(num='60',name='P60',func=Pin.BIDIR,do_erc=True),
Pin(num='70',name='P70',func=Pin.BIDIR,do_erc=True),
Pin(num='80',name='P80',func=Pin.BIDIR,do_erc=True),
Pin(num='90',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='11',name='P11',func=Pin.BIDIR,do_erc=True),
Pin(num='21',name='P21',func=Pin.BIDIR,do_erc=True),
Pin(num='31',name='P31',func=Pin.BIDIR,do_erc=True),
Pin(num='41',name='P41',func=Pin.BIDIR,do_erc=True),
Pin(num='51',name='P51',func=Pin.BIDIR,do_erc=True),
Pin(num='61',name='P61',func=Pin.BIDIR,do_erc=True),
Pin(num='71',name='P71',func=Pin.BIDIR,do_erc=True),
Pin(num='81',name='P81',func=Pin.BIDIR,do_erc=True),
Pin(num='91',name='P91',func=Pin.BIDIR,do_erc=True),
Pin(num='12',name='P12',func=Pin.BIDIR,do_erc=True),
Pin(num='22',name='P22',func=Pin.BIDIR,do_erc=True),
Pin(num='32',name='GCK1',func=Pin.BIDIR,do_erc=True),
Pin(num='42',name='P42',func=Pin.BIDIR,do_erc=True),
Pin(num='52',name='P52',func=Pin.BIDIR,do_erc=True),
Pin(num='62',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='72',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='82',name='P82',func=Pin.BIDIR,do_erc=True),
Pin(num='92',name='P92',func=Pin.BIDIR,do_erc=True),
Pin(num='13',name='P13',func=Pin.BIDIR,do_erc=True),
Pin(num='23',name='P23',func=Pin.BIDIR,do_erc=True),
Pin(num='33',name='P33',func=Pin.BIDIR,do_erc=True),
Pin(num='43',name='P43',func=Pin.BIDIR,do_erc=True),
Pin(num='53',name='P53',func=Pin.BIDIR,do_erc=True),
Pin(num='63',name='TDI',func=Pin.BIDIR,do_erc=True),
Pin(num='73',name='VCCIO1',func=Pin.PWRIN,do_erc=True),
Pin(num='83',name='P83',func=Pin.BIDIR,do_erc=True),
Pin(num='93',name='VCCIO1',func=Pin.PWRIN,do_erc=True),
Pin(num='14',name='P14',func=Pin.BIDIR,do_erc=True),
Pin(num='24',name='P24',func=Pin.BIDIR,do_erc=True),
Pin(num='34',name='P34',func=Pin.BIDIR,do_erc=True),
Pin(num='44',name='P44',func=Pin.BIDIR,do_erc=True),
Pin(num='54',name='P54',func=Pin.BIDIR,do_erc=True),
Pin(num='64',name='P64',func=Pin.BIDIR,do_erc=True),
Pin(num='74',name='P74',func=Pin.BIDIR,do_erc=True),
Pin(num='84',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='94',name='P94',func=Pin.BIDIR,do_erc=True),
Pin(num='15',name='P15',func=Pin.BIDIR,do_erc=True),
Pin(num='25',name='P25',func=Pin.BIDIR,do_erc=True),
Pin(num='35',name='CDRST',func=Pin.BIDIR,do_erc=True),
Pin(num='45',name='P45',func=Pin.BIDIR,do_erc=True),
Pin(num='55',name='VCCIO1',func=Pin.PWRIN,do_erc=True),
Pin(num='65',name='TMS',func=Pin.BIDIR,do_erc=True),
Pin(num='75',name='P75',func=Pin.BIDIR,do_erc=True),
Pin(num='85',name='P85',func=Pin.BIDIR,do_erc=True),
Pin(num='95',name='P95',func=Pin.BIDIR,do_erc=True),
Pin(num='16',name='P16',func=Pin.BIDIR,do_erc=True),
Pin(num='26',name='P26',func=Pin.BIDIR,do_erc=True),
Pin(num='36',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='46',name='P46',func=Pin.BIDIR,do_erc=True),
Pin(num='56',name='P56',func=Pin.BIDIR,do_erc=True),
Pin(num='66',name='P66',func=Pin.BIDIR,do_erc=True),
Pin(num='76',name='P76',func=Pin.BIDIR,do_erc=True),
Pin(num='86',name='P86',func=Pin.BIDIR,do_erc=True),
Pin(num='96',name='P96',func=Pin.BIDIR,do_erc=True),
Pin(num='17',name='P17',func=Pin.BIDIR,do_erc=True),
Pin(num='27',name='VCCIO1',func=Pin.PWRIN,do_erc=True),
Pin(num='37',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='47',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='57',name='P57',func=Pin.BIDIR,do_erc=True),
Pin(num='67',name='TCK',func=Pin.BIDIR,do_erc=True),
Pin(num='77',name='P77',func=Pin.BIDIR,do_erc=True),
Pin(num='87',name='P87',func=Pin.BIDIR,do_erc=True),
Pin(num='97',name='P97',func=Pin.BIDIR,do_erc=True),
Pin(num='18',name='P18',func=Pin.BIDIR,do_erc=True),
Pin(num='28',name='P28',func=Pin.BIDIR,do_erc=True),
Pin(num='38',name='GCK2',func=Pin.BIDIR,do_erc=True),
Pin(num='48',name='P48',func=Pin.BIDIR,do_erc=True),
Pin(num='58',name='P58',func=Pin.BIDIR,do_erc=True),
Pin(num='68',name='P68',func=Pin.BIDIR,do_erc=True),
Pin(num='78',name='P78',func=Pin.BIDIR,do_erc=True),
Pin(num='88',name='P88',func=Pin.BIDIR,do_erc=True),
Pin(num='98',name='P98',func=Pin.BIDIR,do_erc=True),
Pin(num='19',name='P19',func=Pin.BIDIR,do_erc=True),
Pin(num='29',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='39',name='DGE',func=Pin.BIDIR,do_erc=True),
Pin(num='49',name='P49',func=Pin.BIDIR,do_erc=True),
Pin(num='59',name='P59',func=Pin.BIDIR,do_erc=True),
Pin(num='69',name='P69',func=Pin.BIDIR,do_erc=True),
Pin(num='79',name='P79',func=Pin.BIDIR,do_erc=True),
Pin(num='89',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='99',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='100',name='P100',func=Pin.BIDIR,do_erc=True),
Pin(num='110',name='P110',func=Pin.BIDIR,do_erc=True),
Pin(num='120',name='P120',func=Pin.BIDIR,do_erc=True),
Pin(num='130',name='P130',func=Pin.BIDIR,do_erc=True),
Pin(num='140',name='P140',func=Pin.BIDIR,do_erc=True),
Pin(num='101',name='P101',func=Pin.BIDIR,do_erc=True),
Pin(num='111',name='P111',func=Pin.BIDIR,do_erc=True),
Pin(num='121',name='P121',func=Pin.BIDIR,do_erc=True),
Pin(num='131',name='P131',func=Pin.BIDIR,do_erc=True),
Pin(num='141',name='VCCIO2',func=Pin.PWRIN,do_erc=True),
Pin(num='102',name='P102',func=Pin.BIDIR,do_erc=True),
Pin(num='112',name='P112',func=Pin.BIDIR,do_erc=True),
Pin(num='122',name='TDO',func=Pin.BIDIR,do_erc=True),
Pin(num='132',name='P132',func=Pin.BIDIR,do_erc=True),
Pin(num='142',name='P142',func=Pin.BIDIR,do_erc=True),
Pin(num='103',name='P103',func=Pin.BIDIR,do_erc=True),
Pin(num='113',name='P113',func=Pin.BIDIR,do_erc=True),
Pin(num='123',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='133',name='P133',func=Pin.BIDIR,do_erc=True),
Pin(num='143',name='GSR',func=Pin.BIDIR,do_erc=True),
Pin(num='104',name='P104',func=Pin.BIDIR,do_erc=True),
Pin(num='114',name='P114',func=Pin.BIDIR,do_erc=True),
Pin(num='124',name='P124',func=Pin.BIDIR,do_erc=True),
Pin(num='134',name='P134',func=Pin.BIDIR,do_erc=True),
Pin(num='144',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='105',name='P105',func=Pin.BIDIR,do_erc=True),
Pin(num='115',name='P115',func=Pin.BIDIR,do_erc=True),
Pin(num='125',name='P125',func=Pin.BIDIR,do_erc=True),
Pin(num='135',name='P135',func=Pin.BIDIR,do_erc=True),
Pin(num='106',name='P106',func=Pin.BIDIR,do_erc=True),
Pin(num='116',name='P116',func=Pin.BIDIR,do_erc=True),
Pin(num='126',name='P126',func=Pin.BIDIR,do_erc=True),
Pin(num='136',name='P136',func=Pin.BIDIR,do_erc=True),
Pin(num='107',name='P107',func=Pin.BIDIR,do_erc=True),
Pin(num='117',name='P117',func=Pin.BIDIR,do_erc=True),
Pin(num='127',name='VCCIO2',func=Pin.PWRIN,do_erc=True),
Pin(num='137',name='P137',func=Pin.BIDIR,do_erc=True),
Pin(num='108',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='118',name='P118',func=Pin.BIDIR,do_erc=True),
Pin(num='128',name='P128',func=Pin.BIDIR,do_erc=True),
Pin(num='138',name='P138',func=Pin.BIDIR,do_erc=True),
Pin(num='109',name='VCCIO2',func=Pin.PWRIN,do_erc=True),
Pin(num='119',name='P119',func=Pin.BIDIR,do_erc=True),
Pin(num='129',name='P129',func=Pin.BIDIR,do_erc=True),
Pin(num='139',name='P139',func=Pin.BIDIR,do_erc=True)]),
Part(name='XC2C256-VQ100',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='XC2S100TQ144',dest=TEMPLATE,tool=SKIDL,keywords='FPGA',description='spartan 2',ref_prefix='U',num_units=1,do_erc=True,pins=[
Pin(num='1',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='2',name='TCK',do_erc=True),
Pin(num='3',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='4',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='5',name='IO/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='6',name='IO/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='7',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='8',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='9',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='10',name='IO7P10',func=Pin.BIDIR,do_erc=True),
Pin(num='20',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='30',name='/WR',func=Pin.BIDIR,do_erc=True),
Pin(num='40',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='50',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='60',name='IO/D5',func=Pin.BIDIR,do_erc=True),
Pin(num='70',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='80',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='90',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='11',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='21',name='IO/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='31',name='/CS',func=Pin.BIDIR,do_erc=True),
Pin(num='41',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='51',name='IO/IRDY',func=Pin.BIDIR,do_erc=True),
Pin(num='61',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='71',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='81',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='91',name='I/GCK1',do_erc=True),
Pin(num='12',name='IO/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='22',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='32',name='TDI',do_erc=True),
Pin(num='42',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='52',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='62',name='IO/D6',func=Pin.BIDIR,do_erc=True),
Pin(num='72',name='DONE',func=Pin.OPENCOLL,do_erc=True),
Pin(num='82',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='13',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='23',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='33',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='43',name='IO/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='53',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='63',name='IO/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='73',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='83',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='93',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='14',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='24',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='34',name='TDO',func=Pin.OUTPUT,do_erc=True),
Pin(num='44',name='IO/D1',func=Pin.BIDIR,do_erc=True),
Pin(num='54',name='IO/TRDY',func=Pin.BIDIR,do_erc=True),
Pin(num='64',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='74',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='84',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='94',name='IO/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='15',name='I/GCK3',do_erc=True),
Pin(num='25',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='35',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='45',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='65',name='IO/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='75',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='85',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='95',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='16',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='26',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='36',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='46',name='IO/D2',func=Pin.BIDIR,do_erc=True),
Pin(num='56',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='66',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='76',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='86',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='96',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='17',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='27',name='IO/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='37',name='CCLK',do_erc=True),
Pin(num='47',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='57',name='IO/D4',func=Pin.BIDIR,do_erc=True),
Pin(num='67',name='IO/D7',func=Pin.BIDIR,do_erc=True),
Pin(num='77',name='IO/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='87',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='18',name='I/GCK2',do_erc=True),
Pin(num='28',name='IO/REF',func=Pin.BIDIR,do_erc=True),
Pin(num='38',name='BUSY/DOUT',func=Pin.OUTPUT,do_erc=True),
Pin(num='48',name='IO/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='58',name='IO/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='68',name='INIT/IO',func=Pin.BIDIR,do_erc=True),
Pin(num='78',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='88',name='I/CCK0',do_erc=True),
Pin(num='98',name='GND',func=Pin.PASSIVE,do_erc=True),
Pin(num='19',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='29',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='39',name='D0/DIN',func=Pin.BIDIR,do_erc=True),
Pin(num='49',name='IO/D3',func=Pin.BIDIR,do_erc=True),
Pin(num='59',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='69',name='PROG',do_erc=True),
Pin(num='79',name='IO/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='89',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='99',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='100',name='IO/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='110',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='120',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='130',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='140',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='101',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='111',name='M1',do_erc=True),
Pin(num='121',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='131',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='141',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='102',name='IO/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='112',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='122',name='IO/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='132',name='IO/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='142',name='TMS',do_erc=True),
Pin(num='103',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='113',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='123',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='133',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='143',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='114',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='124',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='134',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='144',name='VCCO',func=Pin.PASSIVE,do_erc=True),
Pin(num='115',name='IO/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='125',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='135',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='106',name='M2',do_erc=True),
Pin(num='116',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='126',name='IO/TRDY',func=Pin.BIDIR,do_erc=True),
Pin(num='136',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='107',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='117',name='IO/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='127',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='137',name='139/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='108',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='118',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='128',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='138',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='109',name='M0',do_erc=True),
Pin(num='119',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='129',name='IO/IRDY',func=Pin.BIDIR,do_erc=True),
Pin(num='139',name='IO/VREF',func=Pin.BIDIR,do_erc=True)]),
Part(name='XC2S150PQ208',dest=TEMPLATE,tool=SKIDL,keywords='FPGA',ref_prefix='U',num_units=1,do_erc=True,pins=[
Pin(num='1',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='2',name='TMS',func=Pin.BIDIR,do_erc=True),
Pin(num='3',name='IO7P3',func=Pin.BIDIR,do_erc=True),
Pin(num='4',name='IO7P4',func=Pin.BIDIR,do_erc=True),
Pin(num='5',name='IO7P5',func=Pin.BIDIR,do_erc=True),
Pin(num='6',name='IO7VRP6',func=Pin.BIDIR,do_erc=True),
Pin(num='7',name='IO7P7',func=Pin.BIDIR,do_erc=True),
Pin(num='8',name='IO7P8',func=Pin.BIDIR,do_erc=True),
Pin(num='9',name='IO7P9',func=Pin.BIDIR,do_erc=True),
Pin(num='10',name='IO7P10',func=Pin.BIDIR,do_erc=True),
Pin(num='20',name='IO7VRP20',func=Pin.BIDIR,do_erc=True),
Pin(num='30',name='IO6P30',func=Pin.BIDIR,do_erc=True),
Pin(num='40',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='50',name='M1',do_erc=True),
Pin(num='60',name='IO5P60',func=Pin.BIDIR,do_erc=True),
Pin(num='70',name='IO5P70',func=Pin.BIDIR,do_erc=True),
Pin(num='80',name='GCK0',do_erc=True),
Pin(num='90',name='IO4P90',func=Pin.BIDIR,do_erc=True),
Pin(num='11',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='21',name='IO7P21',func=Pin.BIDIR,do_erc=True),
Pin(num='31',name='IO6VRP31',func=Pin.BIDIR,do_erc=True),
Pin(num='41',name='IO6P41',func=Pin.BIDIR,do_erc=True),
Pin(num='51',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='61',name='IO5P61',func=Pin.BIDIR,do_erc=True),
Pin(num='71',name='IO5P71',func=Pin.BIDIR,do_erc=True),
Pin(num='81',name='IO4P81',func=Pin.BIDIR,do_erc=True),
Pin(num='91',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='12',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='22',name='IO7P22',func=Pin.BIDIR,do_erc=True),
Pin(num='32',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='42',name='IO6P42',func=Pin.BIDIR,do_erc=True),
Pin(num='52',name='M0',do_erc=True),
Pin(num='62',name='IO5P62',func=Pin.BIDIR,do_erc=True),
Pin(num='72',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='82',name='IO4P82',func=Pin.BIDIR,do_erc=True),
Pin(num='92',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='13',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='23',name='IO7P23',func=Pin.BIDIR,do_erc=True),
Pin(num='33',name='IO6P33',func=Pin.BIDIR,do_erc=True),
Pin(num='43',name='IO6P43',func=Pin.BIDIR,do_erc=True),
Pin(num='53',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='63',name='IO5P63',func=Pin.BIDIR,do_erc=True),
Pin(num='73',name='IO5VRP73',func=Pin.BIDIR,do_erc=True),
Pin(num='83',name='IO4P83',func=Pin.BIDIR,do_erc=True),
Pin(num='93',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='14',name='IO7P14',func=Pin.BIDIR,do_erc=True),
Pin(num='24',name='IRDY7',func=Pin.BIDIR,do_erc=True),
Pin(num='34',name='IO6P34',func=Pin.BIDIR,do_erc=True),
Pin(num='44',name='IO6P44',func=Pin.BIDIR,do_erc=True),
Pin(num='54',name='M2',do_erc=True),
Pin(num='64',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='74',name='IO5P74',func=Pin.BIDIR,do_erc=True),
Pin(num='84',name='IO4VRP84',func=Pin.BIDIR,do_erc=True),
Pin(num='94',name='IO4P94',func=Pin.BIDIR,do_erc=True),
Pin(num='15',name='IO7P15',func=Pin.BIDIR,do_erc=True),
Pin(num='25',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='35',name='IO6P35',func=Pin.BIDIR,do_erc=True),
Pin(num='45',name='IO6VRP45',func=Pin.BIDIR,do_erc=True),
Pin(num='65',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='85',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='95',name='IO4P95',func=Pin.BIDIR,do_erc=True),
Pin(num='16',name='IO7P16',func=Pin.BIDIR,do_erc=True),
Pin(num='26',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='36',name='IO6P36',func=Pin.BIDIR,do_erc=True),
Pin(num='46',name='IO6P46',func=Pin.BIDIR,do_erc=True),
Pin(num='66',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='76',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='86',name='IO4P86',func=Pin.BIDIR,do_erc=True),
Pin(num='96',name='IO4P96',func=Pin.BIDIR,do_erc=True),
Pin(num='17',name='IO7P17',func=Pin.BIDIR,do_erc=True),
Pin(num='27',name='TRDY6',func=Pin.BIDIR,do_erc=True),
Pin(num='37',name='IO6P37',func=Pin.BIDIR,do_erc=True),
Pin(num='47',name='IO6P47',func=Pin.BIDIR,do_erc=True),
Pin(num='57',name='IO5P57',func=Pin.BIDIR,do_erc=True),
Pin(num='67',name='IO5P67',func=Pin.BIDIR,do_erc=True),
Pin(num='77',name='GCK1',do_erc=True),
Pin(num='87',name='IO4P87',func=Pin.BIDIR,do_erc=True),
Pin(num='97',name='IO4P97',func=Pin.BIDIR,do_erc=True),
Pin(num='18',name='IO7P18',func=Pin.BIDIR,do_erc=True),
Pin(num='28',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='38',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='48',name='IO6P48',func=Pin.BIDIR,do_erc=True),
Pin(num='58',name='IO5P58',func=Pin.BIDIR,do_erc=True),
Pin(num='68',name='IO5P68',func=Pin.BIDIR,do_erc=True),
Pin(num='78',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='88',name='IO4P88',func=Pin.BIDIR,do_erc=True),
Pin(num='98',name='IO4VRP98',func=Pin.BIDIR,do_erc=True),
Pin(num='19',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='29',name='IO6P29',func=Pin.BIDIR,do_erc=True),
Pin(num='39',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='49',name='IO6P49',func=Pin.BIDIR,do_erc=True),
Pin(num='59',name='IO5VRP59',func=Pin.BIDIR,do_erc=True),
Pin(num='69',name='IO5P69',func=Pin.BIDIR,do_erc=True),
Pin(num='79',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='89',name='IO4P89',func=Pin.BIDIR,do_erc=True),
Pin(num='99',name='IO4P99',func=Pin.BIDIR,do_erc=True),
Pin(num='100',name='IO4P100',func=Pin.BIDIR,do_erc=True),
Pin(num='200',name='IO0P200',func=Pin.BIDIR,do_erc=True),
Pin(num='110',name='IO3P110',func=Pin.BIDIR,do_erc=True),
Pin(num='120',name='IO3P120',func=Pin.BIDIR,do_erc=True),
Pin(num='130',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='140',name='IO2P140',func=Pin.BIDIR,do_erc=True),
Pin(num='150',name='IO2VRP150',func=Pin.BIDIR,do_erc=True),
Pin(num='160',name='/CS',func=Pin.BIDIR,do_erc=True),
Pin(num='170',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='180',name='IO1P180',func=Pin.BIDIR,do_erc=True),
Pin(num='190',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='101',name='IO4P101',func=Pin.BIDIR,do_erc=True),
Pin(num='201',name='IO0P201',func=Pin.BIDIR,do_erc=True),
Pin(num='111',name='IO3VRP111',func=Pin.BIDIR,do_erc=True),
Pin(num='121',name='IO3P121',func=Pin.BIDIR,do_erc=True),
Pin(num='131',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='141',name='IO2P141',func=Pin.BIDIR,do_erc=True),
Pin(num='151',name='IO2P151',func=Pin.BIDIR,do_erc=True),
Pin(num='161',name='/WR',func=Pin.BIDIR,do_erc=True),
Pin(num='171',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='181',name='IO1P181',func=Pin.BIDIR,do_erc=True),
Pin(num='191',name='IO0P191',func=Pin.BIDIR,do_erc=True),
Pin(num='102',name='IO4P102',func=Pin.BIDIR,do_erc=True),
Pin(num='202',name='IO0P202',func=Pin.BIDIR,do_erc=True),
Pin(num='112',name='IO3P112',func=Pin.BIDIR,do_erc=True),
Pin(num='122',name='IO3P122',func=Pin.BIDIR,do_erc=True),
Pin(num='132',name='IRDY2',func=Pin.BIDIR,do_erc=True),
Pin(num='142',name='IO2/D2P142',func=Pin.BIDIR,do_erc=True),
Pin(num='152',name='IO2P152',func=Pin.BIDIR,do_erc=True),
Pin(num='162',name='IO1P162',func=Pin.BIDIR,do_erc=True),
Pin(num='172',name='IO1P172',func=Pin.BIDIR,do_erc=True),
Pin(num='182',name='GCK2',do_erc=True),
Pin(num='192',name='IO0P192',func=Pin.BIDIR,do_erc=True),
Pin(num='103',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='203',name='IO0VRP203',func=Pin.BIDIR,do_erc=True),
Pin(num='113',name='IO3P113',func=Pin.BIDIR,do_erc=True),
Pin(num='123',name='IO3P123',func=Pin.BIDIR,do_erc=True),
Pin(num='133',name='IO2P133',func=Pin.BIDIR,do_erc=True),
Pin(num='143',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='153',name='D0/DIN',func=Pin.BIDIR,do_erc=True),
Pin(num='163',name='IO1P163',func=Pin.BIDIR,do_erc=True),
Pin(num='173',name='IO1P173',func=Pin.BIDIR,do_erc=True),
Pin(num='183',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='193',name='IO0P193',func=Pin.BIDIR,do_erc=True),
Pin(num='104',name='DONE',func=Pin.BIDIR,do_erc=True),
Pin(num='204',name='IO0P204',func=Pin.BIDIR,do_erc=True),
Pin(num='114',name='IO3P114',func=Pin.BIDIR,do_erc=True),
Pin(num='124',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='134',name='IO2P134',func=Pin.BIDIR,do_erc=True),
Pin(num='144',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='154',name='BUSY/DOUT',func=Pin.BIDIR,do_erc=True),
Pin(num='164',name='IO1VRP164',func=Pin.BIDIR,do_erc=True),
Pin(num='174',name='IO1P174',func=Pin.BIDIR,do_erc=True),
Pin(num='184',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='194',name='IO0P194',func=Pin.BIDIR,do_erc=True),
Pin(num='105',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='205',name='IO0P205',func=Pin.BIDIR,do_erc=True),
Pin(num='115',name='IO3/D6P115',func=Pin.BIDIR,do_erc=True),
Pin(num='125',name='IO3VRP125',func=Pin.BIDIR,do_erc=True),
Pin(num='135',name='IO2/D3P135',func=Pin.BIDIR,do_erc=True),
Pin(num='145',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='155',name='CCLK',func=Pin.BIDIR,do_erc=True),
Pin(num='165',name='IO1P165',func=Pin.BIDIR,do_erc=True),
Pin(num='175',name='IO1P175',func=Pin.BIDIR,do_erc=True),
Pin(num='185',name='GCK3',do_erc=True),
Pin(num='195',name='IO0P195',func=Pin.BIDIR,do_erc=True),
Pin(num='106',name='/PROG',do_erc=True),
Pin(num='206',name='IO0P206',func=Pin.BIDIR,do_erc=True),
Pin(num='116',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='126',name='IO3/D4P126',func=Pin.BIDIR,do_erc=True),
Pin(num='136',name='IO2VRP136',func=Pin.BIDIR,do_erc=True),
Pin(num='146',name='IO2/D1P46',func=Pin.BIDIR,do_erc=True),
Pin(num='156',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='166',name='IO1P166',func=Pin.BIDIR,do_erc=True),
Pin(num='176',name='IO1P176',func=Pin.BIDIR,do_erc=True),
Pin(num='186',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='196',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='107',name='/INIT',func=Pin.BIDIR,do_erc=True),
Pin(num='207',name='TCK',func=Pin.BIDIR,do_erc=True),
Pin(num='117',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='127',name='IO3P127',func=Pin.BIDIR,do_erc=True),
Pin(num='137',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='147',name='IO2P147',func=Pin.BIDIR,do_erc=True),
Pin(num='157',name='TDO',func=Pin.BIDIR,do_erc=True),
Pin(num='167',name='IO1P167',func=Pin.BIDIR,do_erc=True),
Pin(num='177',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='187',name='IO0P187',func=Pin.BIDIR,do_erc=True),
Pin(num='197',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='108',name='IO3/D7P108',func=Pin.BIDIR,do_erc=True),
Pin(num='208',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='118',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='128',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='138',name='IO2P138',func=Pin.BIDIR,do_erc=True),
Pin(num='148',name='IO2P148',func=Pin.BIDIR,do_erc=True),
Pin(num='158',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='168',name='IO1P168',func=Pin.BIDIR,do_erc=True),
Pin(num='178',name='IO1VRP178',func=Pin.BIDIR,do_erc=True),
Pin(num='188',name='IO0P188',func=Pin.BIDIR,do_erc=True),
Pin(num='198',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='109',name='IO3P109',func=Pin.BIDIR,do_erc=True),
Pin(num='119',name='IO3/D5P119',func=Pin.BIDIR,do_erc=True),
Pin(num='129',name='TRDY3',func=Pin.BIDIR,do_erc=True),
Pin(num='139',name='IO2P139',func=Pin.BIDIR,do_erc=True),
Pin(num='149',name='IO2P149',func=Pin.BIDIR,do_erc=True),
Pin(num='159',name='TDI',func=Pin.BIDIR,do_erc=True),
Pin(num='169',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='179',name='IO1P179',func=Pin.BIDIR,do_erc=True),
Pin(num='189',name='IO0VRP189',func=Pin.BIDIR,do_erc=True),
Pin(num='199',name='IO0P199',func=Pin.BIDIR,do_erc=True)]),
Part(name='XC2S200PQ208',dest=TEMPLATE,tool=SKIDL,keywords='FPGA',ref_prefix='U',num_units=1,do_erc=True,pins=[
Pin(num='1',name='GND',func=Pin.PASSIVE,do_erc=True),
Pin(num='2',name='TMS',func=Pin.BIDIR,do_erc=True),
Pin(num='3',name='IO7P3',func=Pin.BIDIR,do_erc=True),
Pin(num='4',name='IO7VRP4',func=Pin.BIDIR,do_erc=True),
Pin(num='5',name='IO7P5',func=Pin.BIDIR,do_erc=True),
Pin(num='6',name='IO7VRP6',func=Pin.BIDIR,do_erc=True),
Pin(num='7',name='IO7P7',func=Pin.BIDIR,do_erc=True),
Pin(num='8',name='IO7P8',func=Pin.BIDIR,do_erc=True),
Pin(num='9',name='IO7VRP9',func=Pin.BIDIR,do_erc=True),
Pin(num='10',name='IO7P10',func=Pin.BIDIR,do_erc=True),
Pin(num='20',name='IO7VRP20',func=Pin.BIDIR,do_erc=True),
Pin(num='30',name='IO6P30',func=Pin.BIDIR,do_erc=True),
Pin(num='40',name='GND',func=Pin.PASSIVE,do_erc=True),
Pin(num='50',name='M1',do_erc=True),
Pin(num='60',name='IO5P60',func=Pin.BIDIR,do_erc=True),
Pin(num='70',name='IO5P70',func=Pin.BIDIR,do_erc=True),
Pin(num='80',name='GCK0',do_erc=True),
Pin(num='90',name='IO4P90',func=Pin.BIDIR,do_erc=True),
Pin(num='11',name='GND',func=Pin.PASSIVE,do_erc=True),
Pin(num='21',name='IO7P21',func=Pin.BIDIR,do_erc=True),
Pin(num='31',name='IO6VRP31',func=Pin.BIDIR,do_erc=True),
Pin(num='41',name='IO6P41',func=Pin.BIDIR,do_erc=True),
Pin(num='51',name='GND',func=Pin.PASSIVE,do_erc=True),
Pin(num='61',name='IO5P61',func=Pin.BIDIR,do_erc=True),
Pin(num='71',name='IO5P71',func=Pin.BIDIR,do_erc=True),
Pin(num='81',name='IO4P81',func=Pin.BIDIR,do_erc=True),
Pin(num='91',name='VCCINT',func=Pin.PASSIVE,do_erc=True),
Pin(num='12',name='VCCO',func=Pin.PASSIVE,do_erc=True),
Pin(num='22',name='IO7P22',func=Pin.BIDIR,do_erc=True),
Pin(num='32',name='GND',func=Pin.PASSIVE,do_erc=True),
Pin(num='42',name='IO6VRP42',func=Pin.BIDIR,do_erc=True),
Pin(num='52',name='M0',do_erc=True),
Pin(num='62',name='IO5VRP62',func=Pin.BIDIR,do_erc=True),
Pin(num='72',name='GND',func=Pin.PASSIVE,do_erc=True),
Pin(num='82',name='IO4P82',func=Pin.BIDIR,do_erc=True),
Pin(num='92',name='VCCO',func=Pin.PASSIVE,do_erc=True),
Pin(num='13',name='VCCINT',func=Pin.PASSIVE,do_erc=True),
Pin(num='23',name='IO7P23',func=Pin.BIDIR,do_erc=True),
Pin(num='33',name='IO6P33',func=Pin.BIDIR,do_erc=True),
Pin(num='43',name='IO6P43',func=Pin.BIDIR,do_erc=True),
Pin(num='53',name='VCCO',func=Pin.PASSIVE,do_erc=True),
Pin(num='63',name='IO5P63',func=Pin.BIDIR,do_erc=True),
Pin(num='73',name='IO5VRP73',func=Pin.BIDIR,do_erc=True),
Pin(num='83',name='IO4P83',func=Pin.BIDIR,do_erc=True),
Pin(num='93',name='GND',func=Pin.PASSIVE,do_erc=True),
Pin(num='14',name='IO7P14',func=Pin.BIDIR,do_erc=True),
Pin(num='24',name='IRDY7',func=Pin.BIDIR,do_erc=True),
Pin(num='34',name='IO6P34',func=Pin.BIDIR,do_erc=True),
Pin(num='44',name='IO6P44',func=Pin.BIDIR,do_erc=True),
Pin(num='54',name='M2',do_erc=True),
Pin(num='64',name='GND',func=Pin.PASSIVE,do_erc=True),
Pin(num='74',name='IO5P74',func=Pin.BIDIR,do_erc=True),
Pin(num='84',name='IO4VRP84',func=Pin.BIDIR,do_erc=True),
Pin(num='94',name='IO4P94',func=Pin.BIDIR,do_erc=True),
Pin(num='15',name='IO7P15',func=Pin.BIDIR,do_erc=True),
Pin(num='25',name='GND',func=Pin.PASSIVE,do_erc=True),
Pin(num='35',name='IO6P35',func=Pin.BIDIR,do_erc=True),
Pin(num='45',name='IO6VRP45',func=Pin.BIDIR,do_erc=True),
Pin(num='65',name='VCCO',func=Pin.PASSIVE,do_erc=True),
Pin(num='75',name='IO5P75',func=Pin.BIDIR,do_erc=True),
Pin(num='85',name='GND',func=Pin.PASSIVE,do_erc=True),
Pin(num='95',name='IO4VRP95',func=Pin.BIDIR,do_erc=True),
Pin(num='16',name='IO7P16',func=Pin.BIDIR,do_erc=True),
Pin(num='26',name='VCCO',func=Pin.PASSIVE,do_erc=True),
Pin(num='36',name='IO6P36',func=Pin.BIDIR,do_erc=True),
Pin(num='46',name='IO6P46',func=Pin.BIDIR,do_erc=True),
Pin(num='66',name='VCCINT',func=Pin.PASSIVE,do_erc=True),
Pin(num='76',name='VCCINT',func=Pin.PASSIVE,do_erc=True),
Pin(num='86',name='IO4P86',func=Pin.BIDIR,do_erc=True),
Pin(num='96',name='IO4P96',func=Pin.BIDIR,do_erc=True),
Pin(num='17',name='IO7P17',func=Pin.BIDIR,do_erc=True),
Pin(num='27',name='TRDY6',func=Pin.BIDIR,do_erc=True),
Pin(num='37',name='IO6P37',func=Pin.BIDIR,do_erc=True),
Pin(num='47',name='IO6VRP47',func=Pin.BIDIR,do_erc=True),
Pin(num='57',name='IO5VRP57',func=Pin.BIDIR,do_erc=True),
Pin(num='67',name='IO5P67',func=Pin.BIDIR,do_erc=True),
Pin(num='77',name='GCK1',do_erc=True),
Pin(num='87',name='IO4P87',func=Pin.BIDIR,do_erc=True),
Pin(num='97',name='IO4P97',func=Pin.BIDIR,do_erc=True),
Pin(num='18',name='IO7P18',func=Pin.BIDIR,do_erc=True),
Pin(num='28',name='VCCINT',func=Pin.PASSIVE,do_erc=True),
Pin(num='38',name='VCCINT',func=Pin.PASSIVE,do_erc=True),
Pin(num='48',name='IO6P48',func=Pin.BIDIR,do_erc=True),
Pin(num='58',name='IO5P58',func=Pin.BIDIR,do_erc=True),
Pin(num='68',name='IO5P68',func=Pin.BIDIR,do_erc=True),
Pin(num='78',name='VCCO',func=Pin.PASSIVE,do_erc=True),
Pin(num='88',name='IO4P88',func=Pin.BIDIR,do_erc=True),
Pin(num='98',name='IO4VRP98',func=Pin.BIDIR,do_erc=True),
Pin(num='19',name='GND',func=Pin.PASSIVE,do_erc=True),
Pin(num='29',name='IO6P29',func=Pin.BIDIR,do_erc=True),
Pin(num='39',name='VCCO',func=Pin.PASSIVE,do_erc=True),
Pin(num='49',name='IO6P49',func=Pin.BIDIR,do_erc=True),
Pin(num='59',name='IO5VRP59',func=Pin.BIDIR,do_erc=True),
Pin(num='69',name='IO5P69',func=Pin.BIDIR,do_erc=True),
Pin(num='79',name='GND',func=Pin.PASSIVE,do_erc=True),
Pin(num='89',name='IO4P89',func=Pin.BIDIR,do_erc=True),
Pin(num='99',name='IO4P99',func=Pin.BIDIR,do_erc=True),
Pin(num='100',name='IO4VRP100',func=Pin.BIDIR,do_erc=True),
Pin(num='200',name='IO0VRP200',func=Pin.BIDIR,do_erc=True),
Pin(num='110',name='IO3P110',func=Pin.BIDIR,do_erc=True),
Pin(num='120',name='IO3P120',func=Pin.BIDIR,do_erc=True),
Pin(num='130',name='VCCO',func=Pin.PASSIVE,do_erc=True),
Pin(num='140',name='IO2P140',func=Pin.BIDIR,do_erc=True),
Pin(num='150',name='IO2VRP150',func=Pin.BIDIR,do_erc=True),
Pin(num='160',name='/CS',func=Pin.BIDIR,do_erc=True),
Pin(num='170',name='VCCO',func=Pin.PASSIVE,do_erc=True),
Pin(num='180',name='IO1P180',func=Pin.BIDIR,do_erc=True),
Pin(num='190',name='GND',func=Pin.PASSIVE,do_erc=True),
Pin(num='101',name='IO4P101',func=Pin.BIDIR,do_erc=True),
Pin(num='201',name='IO0P201',func=Pin.BIDIR,do_erc=True),
Pin(num='111',name='IO3VRP111',func=Pin.BIDIR,do_erc=True),
Pin(num='121',name='IO3P121',func=Pin.BIDIR,do_erc=True),
Pin(num='131',name='GND',func=Pin.PASSIVE,do_erc=True),
Pin(num='141',name='IO2P141',func=Pin.BIDIR,do_erc=True),
Pin(num='151',name='IO2P151',func=Pin.BIDIR,do_erc=True),
Pin(num='161',name='/WR',func=Pin.BIDIR,do_erc=True),
Pin(num='171',name='VCCINT',func=Pin.PASSIVE,do_erc=True),
Pin(num='181',name='IO1P181',func=Pin.BIDIR,do_erc=True),
Pin(num='191',name='IO0P191',func=Pin.BIDIR,do_erc=True),
Pin(num='102',name='IO4P102',func=Pin.BIDIR,do_erc=True),
Pin(num='202',name='IO0P202',func=Pin.BIDIR,do_erc=True),
Pin(num='112',name='IO3P112',func=Pin.BIDIR,do_erc=True),
Pin(num='122',name='IO3P122',func=Pin.BIDIR,do_erc=True),
Pin(num='132',name='IRDY2',func=Pin.BIDIR,do_erc=True),
Pin(num='142',name='IO2/D2P142',func=Pin.BIDIR,do_erc=True),
Pin(num='152',name='IO2VRP152',func=Pin.BIDIR,do_erc=True),
Pin(num='162',name='IO1VRP162',func=Pin.BIDIR,do_erc=True),
Pin(num='172',name='IO1P172',func=Pin.BIDIR,do_erc=True),
Pin(num='182',name='GCK2',do_erc=True),
Pin(num='192',name='IO0P192',func=Pin.BIDIR,do_erc=True),
Pin(num='103',name='GND',func=Pin.PASSIVE,do_erc=True),
Pin(num='203',name='IO0VRP203',func=Pin.BIDIR,do_erc=True),
Pin(num='113',name='IO3P113',func=Pin.BIDIR,do_erc=True),
Pin(num='123',name='IO3P123',func=Pin.BIDIR,do_erc=True),
Pin(num='133',name='IO2P133',func=Pin.BIDIR,do_erc=True),
Pin(num='143',name='VCCINT',func=Pin.PASSIVE,do_erc=True),
Pin(num='153',name='D0/DIN',func=Pin.BIDIR,do_erc=True),
Pin(num='163',name='IO1P163',func=Pin.BIDIR,do_erc=True),
Pin(num='173',name='IO1P173',func=Pin.BIDIR,do_erc=True),
Pin(num='183',name='GND',func=Pin.PASSIVE,do_erc=True),
Pin(num='193',name='IO0P193',func=Pin.BIDIR,do_erc=True),
Pin(num='104',name='DONE',func=Pin.BIDIR,do_erc=True),
Pin(num='204',name='IO0P204',func=Pin.BIDIR,do_erc=True),
Pin(num='114',name='IO3VRP114',func=Pin.BIDIR,do_erc=True),
Pin(num='124',name='GND',func=Pin.PASSIVE,do_erc=True),
Pin(num='134',name='IO2P134',func=Pin.BIDIR,do_erc=True),
Pin(num='144',name='VCCO',func=Pin.PASSIVE,do_erc=True),
Pin(num='154',name='BUSY/DOUT',func=Pin.BIDIR,do_erc=True),
Pin(num='164',name='IO1VRP164',func=Pin.BIDIR,do_erc=True),
Pin(num='174',name='IO1P174',func=Pin.BIDIR,do_erc=True),
Pin(num='184',name='VCCO',func=Pin.PASSIVE,do_erc=True),
Pin(num='194',name='IO0P194',func=Pin.BIDIR,do_erc=True),
Pin(num='105',name='VCCO',func=Pin.PASSIVE,do_erc=True),
Pin(num='205',name='IO0VRP205',func=Pin.BIDIR,do_erc=True),
Pin(num='115',name='IO3/D6P115',func=Pin.BIDIR,do_erc=True),
Pin(num='125',name='IO3VRP125',func=Pin.BIDIR,do_erc=True),
Pin(num='135',name='IO2/D3P135',func=Pin.BIDIR,do_erc=True),
Pin(num='145',name='GND',func=Pin.PASSIVE,do_erc=True),
Pin(num='155',name='CCLK',func=Pin.BIDIR,do_erc=True),
Pin(num='165',name='IO1P165',func=Pin.BIDIR,do_erc=True),
Pin(num='175',name='IO1P175',func=Pin.BIDIR,do_erc=True),
Pin(num='185',name='GCK3',do_erc=True),
Pin(num='195',name='IO0P195',func=Pin.BIDIR,do_erc=True),
Pin(num='106',name='/PROG',do_erc=True),
Pin(num='206',name='IO0P206',func=Pin.BIDIR,do_erc=True),
Pin(num='116',name='GND',func=Pin.PASSIVE,do_erc=True),
Pin(num='126',name='IO3/D4P126',func=Pin.BIDIR,do_erc=True),
Pin(num='136',name='IO2VRP136',func=Pin.BIDIR,do_erc=True),
Pin(num='146',name='IO2/D1P46',func=Pin.BIDIR,do_erc=True),
Pin(num='156',name='VCCO',func=Pin.PASSIVE,do_erc=True),
Pin(num='166',name='IO1P166',func=Pin.BIDIR,do_erc=True),
Pin(num='176',name='IO1P176',func=Pin.BIDIR,do_erc=True),
Pin(num='186',name='VCCINT',func=Pin.PASSIVE,do_erc=True),
Pin(num='196',name='VCCINT',func=Pin.PASSIVE,do_erc=True),
Pin(num='107',name='/INIT',func=Pin.BIDIR,do_erc=True),
Pin(num='207',name='TCK',func=Pin.BIDIR,do_erc=True),
Pin(num='117',name='VCCO',func=Pin.PASSIVE,do_erc=True),
Pin(num='127',name='IO3P127',func=Pin.BIDIR,do_erc=True),
Pin(num='137',name='GND',func=Pin.PASSIVE,do_erc=True),
Pin(num='147',name='IO2VRP147',func=Pin.BIDIR,do_erc=True),
Pin(num='157',name='TDO',func=Pin.BIDIR,do_erc=True),
Pin(num='167',name='IO1VRP167',func=Pin.BIDIR,do_erc=True),
Pin(num='177',name='GND',func=Pin.PASSIVE,do_erc=True),
Pin(num='187',name='IO0P187',func=Pin.BIDIR,do_erc=True),
Pin(num='197',name='VCCO',func=Pin.PASSIVE,do_erc=True),
Pin(num='108',name='IO3/D7P108',func=Pin.BIDIR,do_erc=True),
Pin(num='208',name='VCCO',func=Pin.PASSIVE,do_erc=True),
Pin(num='118',name='VCCINT',func=Pin.PASSIVE,do_erc=True),
Pin(num='128',name='VCCINT',func=Pin.PASSIVE,do_erc=True),
Pin(num='138',name='IO2P138',func=Pin.BIDIR,do_erc=True),
Pin(num='148',name='IO2P148',func=Pin.BIDIR,do_erc=True),
Pin(num='158',name='GND',func=Pin.PASSIVE,do_erc=True),
Pin(num='168',name='IO1P168',func=Pin.BIDIR,do_erc=True),
Pin(num='178',name='IO1VRP178',func=Pin.BIDIR,do_erc=True),
Pin(num='188',name='IO0P188',func=Pin.BIDIR,do_erc=True),
Pin(num='198',name='GND',func=Pin.PASSIVE,do_erc=True),
Pin(num='109',name='IO3VRP109',func=Pin.BIDIR,do_erc=True),
Pin(num='119',name='IO3/D5P119',func=Pin.BIDIR,do_erc=True),
Pin(num='129',name='TRDY3',func=Pin.BIDIR,do_erc=True),
Pin(num='139',name='IO2P139',func=Pin.BIDIR,do_erc=True),
Pin(num='149',name='IO2P149',func=Pin.BIDIR,do_erc=True),
Pin(num='159',name='TDI',func=Pin.BIDIR,do_erc=True),
Pin(num='169',name='GND',func=Pin.PASSIVE,do_erc=True),
Pin(num='179',name='IO1P179',func=Pin.BIDIR,do_erc=True),
Pin(num='189',name='IO0VRP189',func=Pin.BIDIR,do_erc=True),
Pin(num='199',name='IO0P199',func=Pin.BIDIR,do_erc=True)]),
Part(name='XC2S300PQ208',dest=TEMPLATE,tool=SKIDL,ref_prefix='U',num_units=1,do_erc=True,pins=[
Pin(num='1',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='2',name='TMS',func=Pin.BIDIR,do_erc=True),
Pin(num='3',name='IO7P3',func=Pin.BIDIR,do_erc=True),
Pin(num='4',name='IO7VRP4',func=Pin.BIDIR,do_erc=True),
Pin(num='5',name='IO7P5',func=Pin.BIDIR,do_erc=True),
Pin(num='6',name='IO7VRP6',func=Pin.BIDIR,do_erc=True),
Pin(num='7',name='IO7P7',func=Pin.BIDIR,do_erc=True),
Pin(num='8',name='IO7P8',func=Pin.BIDIR,do_erc=True),
Pin(num='9',name='IO7VRP9',func=Pin.BIDIR,do_erc=True),
Pin(num='10',name='IO7VRP10',func=Pin.BIDIR,do_erc=True),
Pin(num='20',name='IO7VRP20',func=Pin.BIDIR,do_erc=True),
Pin(num='30',name='IO6P30',func=Pin.BIDIR,do_erc=True),
Pin(num='40',name='IO6P40',func=Pin.BIDIR,do_erc=True),
Pin(num='50',name='M1',do_erc=True),
Pin(num='60',name='IO5P60',func=Pin.BIDIR,do_erc=True),
Pin(num='70',name='IO5P70',func=Pin.BIDIR,do_erc=True),
Pin(num='80',name='GCK0',do_erc=True),
Pin(num='90',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='11',name='IO7P11',func=Pin.BIDIR,do_erc=True),
Pin(num='21',name='IO7P21',func=Pin.BIDIR,do_erc=True),
Pin(num='31',name='IO6VRP31',func=Pin.BIDIR,do_erc=True),
Pin(num='41',name='IO6VRP41',func=Pin.BIDIR,do_erc=True),
Pin(num='51',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='61',name='IO5P61',func=Pin.BIDIR,do_erc=True),
Pin(num='71',name='IO5P71',func=Pin.BIDIR,do_erc=True),
Pin(num='81',name='IO4P81',func=Pin.BIDIR,do_erc=True),
Pin(num='91',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='12',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='22',name='IO7P22',func=Pin.BIDIR,do_erc=True),
Pin(num='32',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='42',name='IO6P42',func=Pin.BIDIR,do_erc=True),
Pin(num='52',name='M0',do_erc=True),
Pin(num='62',name='IO5P62',func=Pin.BIDIR,do_erc=True),
Pin(num='72',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='82',name='IO4P82',func=Pin.BIDIR,do_erc=True),
Pin(num='92',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='13',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='23',name='IO7P23',func=Pin.BIDIR,do_erc=True),
Pin(num='33',name='IO6P33',func=Pin.BIDIR,do_erc=True),
Pin(num='43',name='IO6P43',func=Pin.BIDIR,do_erc=True),
Pin(num='53',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='63',name='IO5VRP63',func=Pin.BIDIR,do_erc=True),
Pin(num='73',name='IO5VRP73',func=Pin.BIDIR,do_erc=True),
Pin(num='83',name='IO4P83',func=Pin.BIDIR,do_erc=True),
Pin(num='93',name='IO4P93',func=Pin.BIDIR,do_erc=True),
Pin(num='14',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='24',name='IRDY7',func=Pin.BIDIR,do_erc=True),
Pin(num='34',name='IO6P34',func=Pin.BIDIR,do_erc=True),
Pin(num='44',name='IO6P44',func=Pin.BIDIR,do_erc=True),
Pin(num='54',name='M2',do_erc=True),
Pin(num='64',name='IO5P64',func=Pin.BIDIR,do_erc=True),
Pin(num='74',name='IO5P74',func=Pin.BIDIR,do_erc=True),
Pin(num='84',name='IO4VRP84',func=Pin.BIDIR,do_erc=True),
Pin(num='94',name='IO4VRP94',func=Pin.BIDIR,do_erc=True),
Pin(num='15',name='IO7P15',func=Pin.BIDIR,do_erc=True),
Pin(num='25',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='35',name='IO6P35',func=Pin.BIDIR,do_erc=True),
Pin(num='45',name='IO6VRP45',func=Pin.BIDIR,do_erc=True),
Pin(num='55',name='IO5P55',func=Pin.BIDIR,do_erc=True),
Pin(num='65',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='75',name='IO5P75',func=Pin.BIDIR,do_erc=True),
Pin(num='85',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='95',name='IO4P95',func=Pin.BIDIR,do_erc=True),
Pin(num='16',name='IO7P16',func=Pin.BIDIR,do_erc=True),
Pin(num='26',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='36',name='IO6P36',func=Pin.BIDIR,do_erc=True),
Pin(num='46',name='IO6P46',func=Pin.BIDIR,do_erc=True),
Pin(num='56',name='IO5P56',func=Pin.BIDIR,do_erc=True),
Pin(num='66',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='76',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='86',name='IO4P86',func=Pin.BIDIR,do_erc=True),
Pin(num='96',name='IO4P96',func=Pin.BIDIR,do_erc=True),
Pin(num='17',name='IO7P17',func=Pin.BIDIR,do_erc=True),
Pin(num='27',name='TRDY6',func=Pin.BIDIR,do_erc=True),
Pin(num='37',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='47',name='IO6VRP47',func=Pin.BIDIR,do_erc=True),
Pin(num='57',name='IO5VRP57',func=Pin.BIDIR,do_erc=True),
Pin(num='67',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='77',name='GCK1',do_erc=True),
Pin(num='87',name='IO4P87',func=Pin.BIDIR,do_erc=True),
Pin(num='97',name='IO4P97',func=Pin.BIDIR,do_erc=True),
Pin(num='18',name='IO7P18',func=Pin.BIDIR,do_erc=True),
Pin(num='28',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='38',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='48',name='IO6P48',func=Pin.BIDIR,do_erc=True),
Pin(num='58',name='IO5P58',func=Pin.BIDIR,do_erc=True),
Pin(num='68',name='IO5P68',func=Pin.BIDIR,do_erc=True),
Pin(num='78',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='88',name='IO4P88',func=Pin.BIDIR,do_erc=True),
Pin(num='98',name='IO4VRP98',func=Pin.BIDIR,do_erc=True),
Pin(num='19',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='29',name='IO6P29',func=Pin.BIDIR,do_erc=True),
Pin(num='39',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='49',name='IO6P49',func=Pin.BIDIR,do_erc=True),
Pin(num='59',name='IO5VRP59',func=Pin.BIDIR,do_erc=True),
Pin(num='69',name='IO5P69',func=Pin.BIDIR,do_erc=True),
Pin(num='79',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='89',name='IO4P89',func=Pin.BIDIR,do_erc=True),
Pin(num='99',name='IO4P99',func=Pin.BIDIR,do_erc=True),
Pin(num='100',name='IO4VRP100',func=Pin.BIDIR,do_erc=True),
Pin(num='200',name='IO0P200',func=Pin.BIDIR,do_erc=True),
Pin(num='110',name='IO3P110',func=Pin.BIDIR,do_erc=True),
Pin(num='120',name='IO3/D5P120',func=Pin.BIDIR,do_erc=True),
Pin(num='130',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='140',name='IO2P140',func=Pin.BIDIR,do_erc=True),
Pin(num='150',name='IO2VRP150',func=Pin.BIDIR,do_erc=True),
Pin(num='160',name='/CS',func=Pin.BIDIR,do_erc=True),
Pin(num='170',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='180',name='IO1P180',func=Pin.BIDIR,do_erc=True),
Pin(num='190',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='101',name='IO4P101',func=Pin.BIDIR,do_erc=True),
Pin(num='201',name='IO0P201',func=Pin.BIDIR,do_erc=True),
Pin(num='111',name='IO3VRP111',func=Pin.BIDIR,do_erc=True),
Pin(num='121',name='IO3P121',func=Pin.BIDIR,do_erc=True),
Pin(num='131',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='141',name='IO2/D2P141',func=Pin.BIDIR,do_erc=True),
Pin(num='151',name='IO2P151',func=Pin.BIDIR,do_erc=True),
Pin(num='161',name='/WR',func=Pin.BIDIR,do_erc=True),
Pin(num='171',name='VCCO',func=Pin.PASSIVE,do_erc=True),
Pin(num='181',name='IO1P181',func=Pin.BIDIR,do_erc=True),
Pin(num='191',name='IO0P191',func=Pin.BIDIR,do_erc=True),
Pin(num='102',name='IO4P102',func=Pin.BIDIR,do_erc=True),
Pin(num='202',name='IO0P202',func=Pin.BIDIR,do_erc=True),
Pin(num='112',name='IO3P112',func=Pin.BIDIR,do_erc=True),
Pin(num='122',name='IO3P122',func=Pin.BIDIR,do_erc=True),
Pin(num='132',name='IRDY2',func=Pin.BIDIR,do_erc=True),
Pin(num='142',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='152',name='IO2VRP152',func=Pin.BIDIR,do_erc=True),
Pin(num='162',name='IO1VRP162',func=Pin.BIDIR,do_erc=True),
Pin(num='172',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='182',name='GCK2',do_erc=True),
Pin(num='192',name='IO0P192',func=Pin.BIDIR,do_erc=True),
Pin(num='103',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='203',name='IO0VRP203',func=Pin.BIDIR,do_erc=True),
Pin(num='113',name='IO3P113',func=Pin.BIDIR,do_erc=True),
Pin(num='123',name='IO3P123',func=Pin.BIDIR,do_erc=True),
Pin(num='133',name='IO2P133',func=Pin.BIDIR,do_erc=True),
Pin(num='143',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='153',name='D0/DIN',func=Pin.BIDIR,do_erc=True),
Pin(num='163',name='IO1P163',func=Pin.BIDIR,do_erc=True),
Pin(num='173',name='IO1P173',func=Pin.BIDIR,do_erc=True),
Pin(num='183',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='193',name='IO0P193',func=Pin.BIDIR,do_erc=True),
Pin(num='104',name='DONE',func=Pin.BIDIR,do_erc=True),
Pin(num='204',name='IO0P204',func=Pin.BIDIR,do_erc=True),
Pin(num='114',name='IO3P114',func=Pin.BIDIR,do_erc=True),
Pin(num='124',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='134',name='IO2P134',func=Pin.BIDIR,do_erc=True),
Pin(num='144',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='154',name='BUSY/DOUT',func=Pin.BIDIR,do_erc=True),
Pin(num='164',name='IO1VRP164',func=Pin.BIDIR,do_erc=True),
Pin(num='174',name='IO1P174',func=Pin.BIDIR,do_erc=True),
Pin(num='184',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='194',name='IO0P194',func=Pin.BIDIR,do_erc=True),
Pin(num='105',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='205',name='IO0VRP205',func=Pin.BIDIR,do_erc=True),
Pin(num='115',name='IO3VRP115',func=Pin.BIDIR,do_erc=True),
Pin(num='125',name='IO3VRP125',func=Pin.BIDIR,do_erc=True),
Pin(num='135',name='IO2/D3P135',func=Pin.BIDIR,do_erc=True),
Pin(num='145',name='IO2/D1P145',func=Pin.BIDIR,do_erc=True),
Pin(num='155',name='CCLK',func=Pin.BIDIR,do_erc=True),
Pin(num='165',name='IO1P165',func=Pin.BIDIR,do_erc=True),
Pin(num='175',name='IO1P175',func=Pin.BIDIR,do_erc=True),
Pin(num='185',name='GCK3',do_erc=True),
Pin(num='195',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='106',name='/PROG',do_erc=True),
Pin(num='206',name='IO0P206',func=Pin.BIDIR,do_erc=True),
Pin(num='116',name='IO3/D6P116',func=Pin.BIDIR,do_erc=True),
Pin(num='126',name='IO3/D4P126',func=Pin.BIDIR,do_erc=True),
Pin(num='136',name='IO2VRP136',func=Pin.BIDIR,do_erc=True),
Pin(num='146',name='IO2VRP146',func=Pin.BIDIR,do_erc=True),
Pin(num='156',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='166',name='IO1P166',func=Pin.BIDIR,do_erc=True),
Pin(num='176',name='IO1P176',func=Pin.BIDIR,do_erc=True),
Pin(num='186',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='196',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='107',name='/INIT',func=Pin.BIDIR,do_erc=True),
Pin(num='207',name='TCK',func=Pin.BIDIR,do_erc=True),
Pin(num='117',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='127',name='IO3P127',func=Pin.BIDIR,do_erc=True),
Pin(num='137',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='147',name='IO2P147',func=Pin.BIDIR,do_erc=True),
Pin(num='157',name='TDO',func=Pin.BIDIR,do_erc=True),
Pin(num='167',name='IO1P167',func=Pin.BIDIR,do_erc=True),
Pin(num='177',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='187',name='IO0P187',func=Pin.BIDIR,do_erc=True),
Pin(num='197',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='108',name='IO3/D7P108',func=Pin.BIDIR,do_erc=True),
Pin(num='208',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='118',name='VCCO',func=Pin.PWRIN,do_erc=True),
Pin(num='128',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='138',name='IO2P138',func=Pin.BIDIR,do_erc=True),
Pin(num='148',name='IO2P148',func=Pin.BIDIR,do_erc=True),
Pin(num='158',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='168',name='IO1VRP168',func=Pin.BIDIR,do_erc=True),
Pin(num='178',name='IO1VRP178',func=Pin.BIDIR,do_erc=True),
Pin(num='188',name='IO0P188',func=Pin.BIDIR,do_erc=True),
Pin(num='198',name='IO0P198',func=Pin.BIDIR,do_erc=True),
Pin(num='109',name='IO3VRP109',func=Pin.BIDIR,do_erc=True),
Pin(num='119',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='129',name='TRDY3',func=Pin.BIDIR,do_erc=True),
Pin(num='139',name='IO2P139',func=Pin.BIDIR,do_erc=True),
Pin(num='149',name='IO2P149',func=Pin.BIDIR,do_erc=True),
Pin(num='159',name='TDI',func=Pin.BIDIR,do_erc=True),
Pin(num='169',name='IO1P169',func=Pin.BIDIR,do_erc=True),
Pin(num='179',name='IO1P179',func=Pin.BIDIR,do_erc=True),
Pin(num='189',name='IO0VRP189',func=Pin.BIDIR,do_erc=True),
Pin(num='199',name='IO0VRP199',func=Pin.BIDIR,do_erc=True)]),
Part(name='XC2S400FT256',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='XC2S50-PQ208',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='XC2S64A-xQFG48',dest=TEMPLATE,tool=SKIDL,description='Xilinx CoolRunner',ref_prefix='U',num_units=1,do_erc=True,pins=[
Pin(num='1',name='GTS0',func=Pin.BIDIR,do_erc=True),
Pin(num='2',name='GTS1',func=Pin.BIDIR,do_erc=True),
Pin(num='3',name='VCCjtag',func=Pin.PWRIN,do_erc=True),
Pin(num='4',name='A3',func=Pin.BIDIR,do_erc=True),
Pin(num='5',name='A2',func=Pin.BIDIR,do_erc=True),
Pin(num='6',name='B1',func=Pin.BIDIR,do_erc=True),
Pin(num='7',name='B2',func=Pin.BIDIR,do_erc=True),
Pin(num='8',name='B3',func=Pin.BIDIR,do_erc=True),
Pin(num='9',name='B4',func=Pin.PASSIVE,do_erc=True),
Pin(num='10',name='B5',func=Pin.BIDIR,do_erc=True),
Pin(num='20',name='D7',func=Pin.BIDIR,do_erc=True),
Pin(num='30',name='D16',func=Pin.BIDIR,do_erc=True),
Pin(num='40',name='TDO',func=Pin.OUTPUT,do_erc=True),
Pin(num='11',name='GCK0',func=Pin.PASSIVE,do_erc=True),
Pin(num='21',name='TDI',do_erc=True),
Pin(num='31',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='41',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='12',name='GCK1',func=Pin.BIDIR,do_erc=True),
Pin(num='22',name='TMS',do_erc=True),
Pin(num='32',name='C15',func=Pin.BIDIR,do_erc=True),
Pin(num='42',name='VCCio2',func=Pin.PWRIN,do_erc=True),
Pin(num='13',name='GCK2',func=Pin.BIDIR,do_erc=True),
Pin(num='23',name='TCK',do_erc=True),
Pin(num='33',name='C14',func=Pin.BIDIR,do_erc=True),
Pin(num='43',name='C3',func=Pin.BIDIR,do_erc=True),
Pin(num='14',name='B12',func=Pin.BIDIR,do_erc=True),
Pin(num='24',name='D10',func=Pin.BIDIR,do_erc=True),
Pin(num='34',name='C12',func=Pin.BIDIR,do_erc=True),
Pin(num='44',name='C2',func=Pin.BIDIR,do_erc=True),
Pin(num='15',name='B13',func=Pin.BIDIR,do_erc=True),
Pin(num='25',name='D11',func=Pin.BIDIR,do_erc=True),
Pin(num='35',name='C11',func=Pin.BIDIR,do_erc=True),
Pin(num='45',name='C1',func=Pin.BIDIR,do_erc=True),
Pin(num='16',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='26',name='D12',func=Pin.BIDIR,do_erc=True),
Pin(num='36',name='C10',func=Pin.BIDIR,do_erc=True),
Pin(num='46',name='GSR',func=Pin.BIDIR,do_erc=True),
Pin(num='17',name='D1',func=Pin.BIDIR,do_erc=True),
Pin(num='27',name='D13',func=Pin.BIDIR,do_erc=True),
Pin(num='37',name='C9',func=Pin.BIDIR,do_erc=True),
Pin(num='47',name='GTS2',func=Pin.BIDIR,do_erc=True),
Pin(num='18',name='D2',func=Pin.BIDIR,do_erc=True),
Pin(num='28',name='D13',func=Pin.BIDIR,do_erc=True),
Pin(num='38',name='C6',func=Pin.BIDIR,do_erc=True),
Pin(num='48',name='GTS3',func=Pin.BIDIR,do_erc=True),
Pin(num='19',name='VCCio1',func=Pin.PWRIN,do_erc=True),
Pin(num='29',name='VCCint',func=Pin.PWRIN,do_erc=True),
Pin(num='39',name='C5',func=Pin.BIDIR,do_erc=True)]),
Part(name='XC3020-PC68',dest=TEMPLATE,tool=SKIDL,do_erc=True,aliases=['XC3030-PC68']),
Part(name='XC3030-PC44',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='XC3030-PC84',dest=TEMPLATE,tool=SKIDL,do_erc=True,aliases=['XC3042-PC84']),
Part(name='XC3030-VQ100',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='XC3042-VQ100',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='XC3S1400A/FG484',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='XC3S200AN/FT256',dest=TEMPLATE,tool=SKIDL,description='BGA256/1mm',ref_prefix='U',num_units=1,fplist=['BGA256'],do_erc=True,pins=[
Pin(num='A1',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='B1',name='TDI',do_erc=True),
Pin(num='C1',name='IO_L01N_3',func=Pin.BIDIR,do_erc=True),
Pin(num='D1',name='IO_L03P_3',func=Pin.BIDIR,do_erc=True),
Pin(num='E1',name='IO_L03N_3',func=Pin.BIDIR,do_erc=True),
Pin(num='F1',name='IO_L08P_3',func=Pin.BIDIR,do_erc=True),
Pin(num='G1',name='IO_L08N_3/VREF_3',func=Pin.BIDIR,do_erc=True),
Pin(num='H1',name='IO_L11N_3/LHCLK1',func=Pin.BIDIR,do_erc=True),
Pin(num='J1',name='IO_L14N_3/LHCLK5',func=Pin.BIDIR,do_erc=True),
Pin(num='K1',name='IO_L15N_3/LHCLK7',func=Pin.BIDIR,do_erc=True),
Pin(num='L1',name='IO_L16P_3/VREF_3',func=Pin.BIDIR,do_erc=True),
Pin(num='M1',name='IO_L20P_3',func=Pin.BIDIR,do_erc=True),
Pin(num='N1',name='IO_L20N_3',func=Pin.BIDIR,do_erc=True),
Pin(num='P1',name='IO_L22N_3',func=Pin.BIDIR,do_erc=True),
Pin(num='R1',name='IO_L23P_3',func=Pin.BIDIR,do_erc=True),
Pin(num='T1',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='A2',name='/PROG',func=Pin.BIDIR,do_erc=True),
Pin(num='B2',name='TMS',do_erc=True),
Pin(num='C2',name='IO_L01P_3',func=Pin.BIDIR,do_erc=True),
Pin(num='D2',name='VCCO3',func=Pin.PASSIVE,do_erc=True),
Pin(num='E2',name='IO_L05N_3',func=Pin.BIDIR,do_erc=True),
Pin(num='F2',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='G2',name='IO_L11P_3/LHCLK0',func=Pin.BIDIR,do_erc=True),
Pin(num='H2',name='VCCO3',func=Pin.PWRIN,do_erc=True),
Pin(num='J2',name='IO_L14P_3/LHCLK4',func=Pin.BIDIR,do_erc=True),
Pin(num='K2',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='L2',name='IO_L16N_3',func=Pin.BIDIR,do_erc=True),
Pin(num='M2',name='VCCO3',func=Pin.PWRIN,do_erc=True),
Pin(num='N2',name='IO_L22P_3',func=Pin.BIDIR,do_erc=True),
Pin(num='P2',name='IO_L23N_3',func=Pin.BIDIR,do_erc=True),
Pin(num='R2',name='IO_L02P_2/M2',func=Pin.BIDIR,do_erc=True),
Pin(num='T2',name='IO_L02N_2/CSO_B',func=Pin.BIDIR,do_erc=True),
Pin(num='A3',name='IO_L19P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='B3',name='IO_L19N_0',func=Pin.BIDIR,do_erc=True),
Pin(num='C3',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='D3',name='IO_L02N_3',func=Pin.BIDIR,do_erc=True),
Pin(num='E3',name='IO_L05P_3',func=Pin.BIDIR,do_erc=True),
Pin(num='F3',name='IO_L07P_3',func=Pin.BIDIR,do_erc=True),
Pin(num='G3',name='IO_L09P_3',func=Pin.BIDIR,do_erc=True),
Pin(num='H3',name='IO_L12P_3/LHCLK2',func=Pin.BIDIR,do_erc=True),
Pin(num='J3',name='IO_L12N_3/IRDY2/LHCLK3',func=Pin.BIDIR,do_erc=True),
Pin(num='K3',name='IO_L15P_3/TRDY2/LHCLK6',func=Pin.BIDIR,do_erc=True),
Pin(num='L3',name='IO_L18N_3',func=Pin.BIDIR,do_erc=True),
Pin(num='M3',name='IO_L19P_3',func=Pin.BIDIR,do_erc=True),
Pin(num='N3',name='IO_L24P_3',func=Pin.BIDIR,do_erc=True),
Pin(num='P3',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='R3',name='IO_L03P_2/RDWR_B',func=Pin.BIDIR,do_erc=True),
Pin(num='T3',name='IO_L03N_2/VS2',func=Pin.BIDIR,do_erc=True),
Pin(num='A4',name='IO_L18P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='B4',name='IO_L18N_0',func=Pin.BIDIR,do_erc=True),
Pin(num='C4',name='IO_L20P_0/VREF_0',func=Pin.BIDIR,do_erc=True),
Pin(num='D4',name='IO_L02P_3',func=Pin.BIDIR,do_erc=True),
Pin(num='E4',name='IP_L04P_3',do_erc=True),
Pin(num='F4',name='IP_L04N_3/VREF_3',do_erc=True),
Pin(num='G4',name='IO_L07N_3',func=Pin.BIDIR,do_erc=True),
Pin(num='H4',name='IO_L09N_3',func=Pin.BIDIR,do_erc=True),
Pin(num='J4',name='IO_L17P_3',func=Pin.BIDIR,do_erc=True),
Pin(num='K4',name='IO_L18P_3',func=Pin.BIDIR,do_erc=True),
Pin(num='L4',name='IO_L19N_3',func=Pin.BIDIR,do_erc=True),
Pin(num='M4',name='IO_L24N_3',func=Pin.BIDIR,do_erc=True),
Pin(num='N4',name='IO_L01P_2/M1',func=Pin.BIDIR,do_erc=True),
Pin(num='P4',name='IO_L01N_2/M0',func=Pin.BIDIR,do_erc=True),
Pin(num='R4',name='VCCO2',func=Pin.PWRIN,do_erc=True),
Pin(num='T4',name='IO_L05P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='A5',name='IO_L17P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='B5',name='VCCO0',func=Pin.PWRIN,do_erc=True),
Pin(num='C5',name='IO_L17N_0',func=Pin.BIDIR,do_erc=True),
Pin(num='D5',name='IO_L20N_0/PUDC_B',func=Pin.BIDIR,do_erc=True),
Pin(num='E5',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='F5',name='VCCAUX',func=Pin.PWRIN,do_erc=True),
Pin(num='G5',name='IP_L06N_3/VREF_3',do_erc=True),
Pin(num='H5',name='IO_L10N_3',func=Pin.BIDIR,do_erc=True),
Pin(num='J5',name='VCCO3',func=Pin.PWRIN,do_erc=True),
Pin(num='K5',name='IP_L21P_3',do_erc=True),
Pin(num='L5',name='IP_L25P_3',do_erc=True),
Pin(num='M5',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='N5',name='IP_2/VREF_2',do_erc=True),
Pin(num='P5',name='IO_L04N_2/VS0',func=Pin.BIDIR,do_erc=True),
Pin(num='R5',name='IO_L05N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='T5',name='IO_L06P_2/D7',func=Pin.BIDIR,do_erc=True),
Pin(num='A6',name='IO_L15P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='B6',name='IO_L15N_0',func=Pin.BIDIR,do_erc=True),
Pin(num='C6',name='IO_L16N_0',func=Pin.BIDIR,do_erc=True),
Pin(num='D6',name='IP_0',do_erc=True),
Pin(num='E6',name='IP_0',do_erc=True),
Pin(num='F6',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='G6',name='IP_L06P_3',do_erc=True),
Pin(num='H6',name='IO_L10P_3',func=Pin.BIDIR,do_erc=True),
Pin(num='J6',name='IO_L17N_3',func=Pin.BIDIR,do_erc=True),
Pin(num='K6',name='IP_L21N_3',do_erc=True),
Pin(num='L6',name='IP_L25N_3/VREF_3',do_erc=True),
Pin(num='M6',name='VCCAUX',func=Pin.PWRIN,do_erc=True),
Pin(num='N6',name='IO_L04P_2/VS1',func=Pin.BIDIR,do_erc=True),
Pin(num='P6',name='IO_L07N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='R6',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='T6',name='IO_L06N_2/D6',func=Pin.BIDIR,do_erc=True),
Pin(num='A7',name='IO_L13P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='B7',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='C7',name='IO_L13N_0',func=Pin.BIDIR,do_erc=True),
Pin(num='D7',name='IO_L16P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='E7',name='IO_L14N_0/VREF_0',func=Pin.BIDIR,do_erc=True),
Pin(num='F7',name='IP_0',do_erc=True),
Pin(num='G7',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='H7',name='IP_L13P_3',do_erc=True),
Pin(num='J7',name='IP_L13N_3',do_erc=True),
Pin(num='K7',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='L7',name='IP_2',do_erc=True),
Pin(num='M7',name='IP_2/VREF_2',do_erc=True),
Pin(num='N7',name='IO_L07P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='P7',name='IO_L08P_2/D5',func=Pin.BIDIR,do_erc=True),
Pin(num='R7',name='IO_L09P_2/GCLK12',func=Pin.BIDIR,do_erc=True),
Pin(num='T7',name='IO_L09N_2/GCLK13',func=Pin.BIDIR,do_erc=True),
Pin(num='A8',name='IO_L12P_0/GCLK10',func=Pin.BIDIR,do_erc=True),
Pin(num='B8',name='IO_L12N_0/GCLK11',func=Pin.BIDIR,do_erc=True),
Pin(num='C8',name='IO_L11P_0/GCLK8',func=Pin.BIDIR,do_erc=True),
Pin(num='D8',name='IO_L11N_0/GCLK9',func=Pin.BIDIR,do_erc=True),
Pin(num='E8',name='VCCO0',func=Pin.PWRIN,do_erc=True),
Pin(num='F8',name='IO_L14P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='G8',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='H8',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='J8',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='K8',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='L8',name='IP_2',do_erc=True),
Pin(num='M8',name='IP_2/VREF_2',do_erc=True),
Pin(num='N8',name='IO_L08N_2/D4',func=Pin.BIDIR,do_erc=True),
Pin(num='P8',name='IO_L10P_2/GCLK14',func=Pin.BIDIR,do_erc=True),
Pin(num='R8',name='VCCO2',func=Pin.PWRIN,do_erc=True),
Pin(num='T8',name='IO_L10N_2/GCLK15',func=Pin.BIDIR,do_erc=True),
Pin(num='A9',name='IO_L10N_0/GCLK7',func=Pin.BIDIR,do_erc=True),
Pin(num='B9',name='VCCO0',func=Pin.PWRIN,do_erc=True),
Pin(num='C9',name='IO_L10P_0/GCLK6',func=Pin.BIDIR,do_erc=True),
Pin(num='D9',name='IO_L09N_0/GCLK5',func=Pin.BIDIR,do_erc=True),
Pin(num='E9',name='IP_0/VREF_0',do_erc=True),
Pin(num='F9',name='IP_0',do_erc=True),
Pin(num='G9',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='H9',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='J9',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='K9',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='L9',name='IP_2/VREF_2',do_erc=True),
Pin(num='M9',name='VCCO2',func=Pin.PWRIN,do_erc=True),
Pin(num='N9',name='IO_L11P_2/GCLK0',func=Pin.BIDIR,do_erc=True),
Pin(num='P9',name='IO_L11N_2/GCLK1',func=Pin.BIDIR,do_erc=True),
Pin(num='R9',name='IO_L12P_2/GCLK2',func=Pin.BIDIR,do_erc=True),
Pin(num='T9',name='IO_L12N_2/GCLK3',func=Pin.BIDIR,do_erc=True),
Pin(num='A10',name='IO_L08N_0',func=Pin.BIDIR,do_erc=True),
Pin(num='B10',name='IO_L08P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='C10',name='IO_L09P_0/GCLK4',func=Pin.BIDIR,do_erc=True),
Pin(num='D10',name='IO_L06P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='E10',name='IO_L06N_0/VREF_0',func=Pin.BIDIR,do_erc=True),
Pin(num='F10',name='IP_0',do_erc=True),
Pin(num='G10',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='H10',name='IP_L13P_1',do_erc=True),
Pin(num='J10',name='IP_L09P_1/VREF_1',do_erc=True),
Pin(num='K10',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='L10',name='IP_2/VREF_2',do_erc=True),
Pin(num='M10',name='IO_L13N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='N10',name='IO_L13P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='P10',name='IO_L14N_2/MOSI/CSI_B',func=Pin.BIDIR,do_erc=True),
Pin(num='R10',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='T10',name='IO_L14P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='A11',name='IO_L07N_0',func=Pin.BIDIR,do_erc=True),
Pin(num='B11',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='C11',name='IO_L07P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='D11',name='IO_L03N_0',func=Pin.BIDIR,do_erc=True),
Pin(num='E11',name='VCCAUX',func=Pin.PWRIN,do_erc=True),
Pin(num='F11',name='IP_L25N_1',do_erc=True),
Pin(num='G11',name='IP_L21N_1',do_erc=True),
Pin(num='H11',name='IP_L13N_1',do_erc=True),
Pin(num='J11',name='IP_L09N_1',do_erc=True),
Pin(num='K11',name='IP_L04P_1',do_erc=True),
Pin(num='L11',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='M11',name='IP_2/VREF_2',do_erc=True),
Pin(num='N11',name='IO_L16N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='P11',name='IO_L16P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='R11',name='IO_L15N_2/DOUT',func=Pin.BIDIR,do_erc=True),
Pin(num='T11',name='IO_L15P_2/AWAKE',func=Pin.BIDIR,do_erc=True),
Pin(num='A12',name='IO_L05N_0',func=Pin.BIDIR,do_erc=True),
Pin(num='B12',name='IO_L05P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='C12',name='IO_L03P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='D12',name='IP_0',do_erc=True),
Pin(num='E12',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='F12',name='IP_L25P_1/VREF_1',do_erc=True),
Pin(num='G12',name='IP_L21P_1/VREF_1',do_erc=True),
Pin(num='H12',name='VCCO1',func=Pin.PWRIN,do_erc=True),
Pin(num='J12',name='IO_L10P_1/A8',func=Pin.BIDIR,do_erc=True),
Pin(num='K12',name='IP_L04N_1/VREF_1',do_erc=True),
Pin(num='L12',name='VCCAUX',func=Pin.PWRIN,do_erc=True),
Pin(num='M12',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='N12',name='IO_L19P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='P12',name='IO_L17N_2/D3',func=Pin.BIDIR,do_erc=True),
Pin(num='R12',name='VCCO2',func=Pin.PWRIN,do_erc=True),
Pin(num='T12',name='IO_L17P_2/INIT_B',func=Pin.BIDIR,do_erc=True),
Pin(num='A13',name='IO_L04N_0',func=Pin.BIDIR,do_erc=True),
Pin(num='B13',name='VCCO0',func=Pin.PWRIN,do_erc=True),
Pin(num='C13',name='IO_L01N_0',func=Pin.BIDIR,do_erc=True),
Pin(num='D13',name='IO_L01P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='E13',name='IO_L23P_1/A22',func=Pin.BIDIR,do_erc=True),
Pin(num='F13',name='IO_L20N_1/A19',func=Pin.BIDIR,do_erc=True),
Pin(num='G13',name='IO_L19P_1/A16',func=Pin.BIDIR,do_erc=True),
Pin(num='H13',name='IO_L17P_1/A12',func=Pin.BIDIR,do_erc=True),
Pin(num='J13',name='IO_L10N_1/A9',func=Pin.BIDIR,do_erc=True),
Pin(num='K13',name='IO_L06N_1/A3',func=Pin.BIDIR,do_erc=True),
Pin(num='L13',name='IO_L06P_1/A2',func=Pin.BIDIR,do_erc=True),
Pin(num='M13',name='IO_L05P_1',func=Pin.BIDIR,do_erc=True),
Pin(num='N13',name='IO_L01P_1/HDC',func=Pin.BIDIR,do_erc=True),
Pin(num='P13',name='IO_L19N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='R13',name='IO_L18N_2/D1',func=Pin.BIDIR,do_erc=True),
Pin(num='T13',name='IO_L18P_2/D2',func=Pin.BIDIR,do_erc=True),
Pin(num='A14',name='IO_L04P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='B14',name='IO_L02N_0',func=Pin.BIDIR,do_erc=True),
Pin(num='C14',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='D14',name='IO_L23N_1/A23',func=Pin.BIDIR,do_erc=True),
Pin(num='E14',name='IO_L20P_1/A18',func=Pin.BIDIR,do_erc=True),
Pin(num='F14',name='IO_L19N_1/A17',func=Pin.BIDIR,do_erc=True),
Pin(num='G14',name='IO_L17N_1/A13',func=Pin.BIDIR,do_erc=True),
Pin(num='H14',name='IO_L14N_1/RHCLK5',func=Pin.BIDIR,do_erc=True),
Pin(num='J14',name='IO_L14P_1/RHCLK4',func=Pin.BIDIR,do_erc=True),
Pin(num='K14',name='IO_L11N_1/RHCLK1',func=Pin.BIDIR,do_erc=True),
Pin(num='L14',name='IO_L08P_1/A6',func=Pin.BIDIR,do_erc=True),
Pin(num='M14',name='IO_L05N_1/VREF_1',func=Pin.BIDIR,do_erc=True),
Pin(num='N14',name='IO_L01N_1/LDC2',func=Pin.BIDIR,do_erc=True),
Pin(num='P14',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='R14',name='IO_L20N_2/CCLK',func=Pin.BIDIR,do_erc=True),
Pin(num='T14',name='IO_L20P_2/D0/DIN/MISO',func=Pin.BIDIR,do_erc=True),
Pin(num='A15',name='TCK',do_erc=True),
Pin(num='B15',name='IO_L02P_0/VREF_0',func=Pin.BIDIR,do_erc=True),
Pin(num='C15',name='IO_L24N_1/A25',func=Pin.BIDIR,do_erc=True),
Pin(num='D15',name='IO_L22N_1/A21',func=Pin.BIDIR,do_erc=True),
Pin(num='E15',name='VCCO1',func=Pin.PWRIN,do_erc=True),
Pin(num='F15',name='IO_L18N_1/A15',func=Pin.BIDIR,do_erc=True),
Pin(num='G15',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='H15',name='IO_L15P_1/IRDY1/RHCLK6',func=Pin.BIDIR,do_erc=True),
Pin(num='J15',name='VCCO1',func=Pin.PWRIN,do_erc=True),
Pin(num='K15',name='IO_L11P_1/RHCLK0',func=Pin.BIDIR,do_erc=True),
Pin(num='L15',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='M15',name='IO_L07P_1/A4',func=Pin.BIDIR,do_erc=True),
Pin(num='N15',name='VCCO1',func=Pin.PWRIN,do_erc=True),
Pin(num='P15',name='IO_L02N_1/LDC0',func=Pin.BIDIR,do_erc=True),
Pin(num='R15',name='IO_L02P_1/LDC1',func=Pin.BIDIR,do_erc=True),
Pin(num='T15',name='DONE',func=Pin.BIDIR,do_erc=True),
Pin(num='A16',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='B16',name='TDO',func=Pin.OUTPUT,do_erc=True),
Pin(num='C16',name='IO_L24P_1/A24',func=Pin.BIDIR,do_erc=True),
Pin(num='D16',name='IO_L22P_1/A20',func=Pin.BIDIR,do_erc=True),
Pin(num='E16',name='IO_L18P_1/A14',func=Pin.BIDIR,do_erc=True),
Pin(num='F16',name='IO_L16N_1/A11',func=Pin.BIDIR,do_erc=True),
Pin(num='G16',name='IO_L16P_1/A10',func=Pin.BIDIR,do_erc=True),
Pin(num='H16',name='IO_L15N_1/RHCLK7',func=Pin.BIDIR,do_erc=True),
Pin(num='J16',name='IO_L12N_1/TRDY1/RHCLK3',func=Pin.BIDIR,do_erc=True),
Pin(num='K16',name='IO_L12P_1/RHCLK2',func=Pin.BIDIR,do_erc=True),
Pin(num='L16',name='IO_L08N_1/A7',func=Pin.BIDIR,do_erc=True),
Pin(num='M16',name='IO_L07N_1/A5',func=Pin.BIDIR,do_erc=True),
Pin(num='N16',name='IO_L03N_1/A1',func=Pin.BIDIR,do_erc=True),
Pin(num='P16',name='IO_L03P_1/A0',func=Pin.BIDIR,do_erc=True),
Pin(num='R16',name='SUSPEND',do_erc=True),
Pin(num='T16',name='GND',func=Pin.PWRIN,do_erc=True)]),
Part(name='XC3S400-FG320',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='XC3S400-PQ208',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='XC3S50-VQ100',dest=TEMPLATE,tool=SKIDL,keywords='FPGA',description='spartan 2',ref_prefix='U',num_units=1,do_erc=True,pins=[
Pin(num='1',name='IO-VRN',func=Pin.BIDIR,do_erc=True),
Pin(num='2',name='IO-VRP',func=Pin.BIDIR,do_erc=True),
Pin(num='3',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='4',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='5',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='6',name='VCCO_7',func=Pin.PWRIN,do_erc=True),
Pin(num='7',name='VCCAUX(2.5V)',func=Pin.PWRIN,do_erc=True),
Pin(num='8',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='9',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='10',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='20',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='30',name='IO/D7',func=Pin.BIDIR,do_erc=True),
Pin(num='40',name='IO/DOUT/BUSY',func=Pin.BIDIR,do_erc=True),
Pin(num='60',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='70',name='VCCO_2',func=Pin.PWRIN,do_erc=True),
Pin(num='80',name='IO-VRP',func=Pin.BIDIR,do_erc=True),
Pin(num='90',name='IO/GCK7',func=Pin.BIDIR,do_erc=True),
Pin(num='11',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='21',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='31',name='VCCO_5',func=Pin.PWRIN,do_erc=True),
Pin(num='41',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='51',name='DONE',func=Pin.OPENCOLL,do_erc=True),
Pin(num='61',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='71',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='81',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='91',name='IO/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='12',name='IO/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='22',name='IO-VRN',func=Pin.BIDIR,do_erc=True),
Pin(num='32',name='IO/D6',func=Pin.BIDIR,do_erc=True),
Pin(num='42',name='IO/INIT',func=Pin.BIDIR,do_erc=True),
Pin(num='52',name='CCLK',do_erc=True),
Pin(num='62',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='72',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='82',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='92',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='13',name='IO-VREF',do_erc=True),
Pin(num='23',name='IO-VRP',func=Pin.BIDIR,do_erc=True),
Pin(num='33',name='VCCAUX(2.5V)',func=Pin.PWRIN,do_erc=True),
Pin(num='43',name='IO/D3',func=Pin.BIDIR,do_erc=True),
Pin(num='53',name='IO-VRN',func=Pin.BIDIR,do_erc=True),
Pin(num='63',name='IO/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='73',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='83',name='VCCO_1',func=Pin.PASSIVE,do_erc=True),
Pin(num='93',name='VCCINT(1.2V)',func=Pin.PWRIN,do_erc=True),
Pin(num='14',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='24',name='M1',do_erc=True),
Pin(num='34',name='IO/D5',func=Pin.BIDIR,do_erc=True),
Pin(num='44',name='IO/D2',func=Pin.BIDIR,do_erc=True),
Pin(num='54',name='IO-VRP',func=Pin.BIDIR,do_erc=True),
Pin(num='64',name='IO/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='74',name='IO-VRN',func=Pin.BIDIR,do_erc=True),
Pin(num='84',name='VCCAUX(2.5V)',func=Pin.PWRIN,do_erc=True),
Pin(num='94',name='VCCO_0',func=Pin.PASSIVE,do_erc=True),
Pin(num='15',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='25',name='M0',do_erc=True),
Pin(num='35',name='IO/D4',func=Pin.BIDIR,do_erc=True),
Pin(num='45',name='VCCINT(1.2V)',func=Pin.PWRIN,do_erc=True),
Pin(num='55',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='65',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='75',name='IO-VRP',func=Pin.BIDIR,do_erc=True),
Pin(num='85',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='95',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='16',name='IO/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='26',name='M2',do_erc=True),
Pin(num='36',name='IO/GCK2',func=Pin.BIDIR,do_erc=True),
Pin(num='46',name='VCCO_4',func=Pin.PWRIN,do_erc=True),
Pin(num='66',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='76',name='TDO',func=Pin.OUTPUT,do_erc=True),
Pin(num='86',name='IO/VREF',func=Pin.BIDIR,do_erc=True),
Pin(num='96',name='IO-VRN',func=Pin.BIDIR,do_erc=True),
Pin(num='17',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='27',name='IO/CS',func=Pin.BIDIR,do_erc=True),
Pin(num='37',name='IO/GCK3',func=Pin.BIDIR,do_erc=True),
Pin(num='47',name='IO/D1',func=Pin.BIDIR,do_erc=True),
Pin(num='57',name='VCCO_3',func=Pin.PWRIN,do_erc=True),
Pin(num='67',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='77',name='TCK',do_erc=True),
Pin(num='87',name='IO/GCLK4',func=Pin.BIDIR,do_erc=True),
Pin(num='97',name='IO-VRP',func=Pin.BIDIR,do_erc=True),
Pin(num='18',name='VCCINT(1.2V)',func=Pin.PWRIN,do_erc=True),
Pin(num='28',name='IO/RDWR',func=Pin.BIDIR,do_erc=True),
Pin(num='38',name='IO/GCK0',func=Pin.BIDIR,do_erc=True),
Pin(num='48',name='IO/D0/DIN',func=Pin.BIDIR,do_erc=True),
Pin(num='58',name='VCCAUX(2.5V)',func=Pin.PWRIN,do_erc=True),
Pin(num='68',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='78',name='TMS',do_erc=True),
Pin(num='88',name='IO/GCLK5',func=Pin.BIDIR,do_erc=True),
Pin(num='98',name='HSWAP_EN',func=Pin.BIDIR,do_erc=True),
Pin(num='19',name='VCCO_6',func=Pin.PWRIN,do_erc=True),
Pin(num='29',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='39',name='IO/GCK1',func=Pin.BIDIR,do_erc=True),
Pin(num='59',name='IO',func=Pin.BIDIR,do_erc=True),
Pin(num='69',name='VCCINT(1.2V)',func=Pin.PWRIN,do_erc=True),
Pin(num='79',name='IO-VRN',func=Pin.BIDIR,do_erc=True),
Pin(num='89',name='IO/GCK6',func=Pin.BIDIR,do_erc=True),
Pin(num='99',name='PROG',do_erc=True),
Pin(num='100',name='TDI',do_erc=True)]),
Part(name='XC3S50AN/TQG144',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='XC4003-PC84',dest=TEMPLATE,tool=SKIDL,do_erc=True,aliases=['XC4005-PC84']),
Part(name='XC4003-VQ100',dest=TEMPLATE,tool=SKIDL,ref_prefix='U',num_units=1,do_erc=True,pins=[
Pin(num='1',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='2',name='PGCK1',func=Pin.PASSIVE,do_erc=True),
Pin(num='3',name='P/A17',func=Pin.PASSIVE,do_erc=True),
Pin(num='4',name='P/TDI',func=Pin.PASSIVE,do_erc=True),
Pin(num='5',name='P/TCK',func=Pin.PASSIVE,do_erc=True),
Pin(num='6',name='P/A3',func=Pin.PASSIVE,do_erc=True),
Pin(num='7',name='P7',func=Pin.PASSIVE,do_erc=True),
Pin(num='8',name='P8',func=Pin.PASSIVE,do_erc=True),
Pin(num='9',name='P/A15',func=Pin.PASSIVE,do_erc=True),
Pin(num='10',name='P/A4',func=Pin.PASSIVE,do_erc=True),
Pin(num='20',name='P20',func=Pin.PASSIVE,do_erc=True),
Pin(num='30',name='P/LDC',func=Pin.PASSIVE,do_erc=True),
Pin(num='40',name='P40',func=Pin.PASSIVE,do_erc=True),
Pin(num='50',name='DONE',func=Pin.OPENCOLL,do_erc=True),
Pin(num='60',name='P60',func=Pin.PASSIVE,do_erc=True),
Pin(num='70',name='P70',func=Pin.PASSIVE,do_erc=True),
Pin(num='80',name='P80',func=Pin.PASSIVE,do_erc=True),
Pin(num='90',name='P90',func=Pin.BIDIR,do_erc=True),
Pin(num='11',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='21',name='SGCK2',func=Pin.PASSIVE,do_erc=True),
Pin(num='31',name='P31',func=Pin.PASSIVE,do_erc=True),
Pin(num='41',name='P41',func=Pin.PASSIVE,do_erc=True),
Pin(num='51',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='61',name='P61',func=Pin.PASSIVE,do_erc=True),
Pin(num='71',name='P71/RDY',func=Pin.PASSIVE,do_erc=True),
Pin(num='81',name='P81',func=Pin.PASSIVE,do_erc=True),
Pin(num='91',name='P91',func=Pin.PASSIVE,do_erc=True),
Pin(num='12',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='22',name='M1/RD',do_erc=True),
Pin(num='32',name='P32',func=Pin.PASSIVE,do_erc=True),
Pin(num='42',name='P42',func=Pin.PASSIVE,do_erc=True),
Pin(num='52',name='PROG',do_erc=True),
Pin(num='62',name='P62',func=Pin.PASSIVE,do_erc=True),
Pin(num='72',name='DIN',func=Pin.PASSIVE,do_erc=True),
Pin(num='82',name='P82',func=Pin.PASSIVE,do_erc=True),
Pin(num='92',name='P92',func=Pin.PASSIVE,do_erc=True),
Pin(num='13',name='P13',func=Pin.BIDIR,do_erc=True),
Pin(num='23',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='33',name='P33',func=Pin.PASSIVE,do_erc=True),
Pin(num='43',name='P43',func=Pin.PASSIVE,do_erc=True),
Pin(num='53',name='P53',func=Pin.BIDIR,do_erc=True),
Pin(num='63',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='73',name='DOUT/SGCK4',func=Pin.PASSIVE,do_erc=True),
Pin(num='83',name='P83',func=Pin.PASSIVE,do_erc=True),
Pin(num='93',name='P93',func=Pin.PASSIVE,do_erc=True),
Pin(num='14',name='P14',func=Pin.PASSIVE,do_erc=True),
Pin(num='24',name='M0/RT',do_erc=True),
Pin(num='34',name='P34',func=Pin.PASSIVE,do_erc=True),
Pin(num='44',name='P44',func=Pin.PASSIVE,do_erc=True),
Pin(num='54',name='PGCK3',func=Pin.BIDIR,do_erc=True),
Pin(num='64',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='74',name='CCLK',do_erc=True),
Pin(num='84',name='P84',func=Pin.PASSIVE,do_erc=True),
Pin(num='94',name='P94',func=Pin.PASSIVE,do_erc=True),
Pin(num='15',name='P15',func=Pin.PASSIVE,do_erc=True),
Pin(num='25',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='35',name='P35',func=Pin.PASSIVE,do_erc=True),
Pin(num='45',name='P45',func=Pin.PASSIVE,do_erc=True),
Pin(num='55',name='P55',func=Pin.PASSIVE,do_erc=True),
Pin(num='65',name='P65',func=Pin.PASSIVE,do_erc=True),
Pin(num='75',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='85',name='P85',func=Pin.PASSIVE,do_erc=True),
Pin(num='95',name='P91',func=Pin.PASSIVE,do_erc=True),
Pin(num='16',name='P16',func=Pin.PASSIVE,do_erc=True),
Pin(num='26',name='M2',func=Pin.PASSIVE,do_erc=True),
Pin(num='36',name='P36/INIT',func=Pin.PASSIVE,do_erc=True),
Pin(num='46',name='P46',func=Pin.PASSIVE,do_erc=True),
Pin(num='56',name='P56',func=Pin.BIDIR,do_erc=True),
Pin(num='66',name='P66',func=Pin.PASSIVE,do_erc=True),
Pin(num='76',name='TDO',func=Pin.OUTPUT,do_erc=True),
Pin(num='86',name='P86',func=Pin.PASSIVE,do_erc=True),
Pin(num='96',name='P96',func=Pin.PASSIVE,do_erc=True),
Pin(num='17',name='P17',func=Pin.PASSIVE,do_erc=True),
Pin(num='27',name='PGCK2',func=Pin.PASSIVE,do_erc=True),
Pin(num='37',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='47',name='P47',func=Pin.PASSIVE,do_erc=True),
Pin(num='57',name='P57',func=Pin.PASSIVE,do_erc=True),
Pin(num='67',name='P67',func=Pin.PASSIVE,do_erc=True),
Pin(num='77',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='87',name='P87',func=Pin.PASSIVE,do_erc=True),
Pin(num='97',name='P97',func=Pin.PASSIVE,do_erc=True),
Pin(num='18',name='P18',func=Pin.PASSIVE,do_erc=True),
Pin(num='28',name='P/HDC',func=Pin.PASSIVE,do_erc=True),
Pin(num='38',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='48',name='SGCK3',func=Pin.PASSIVE,do_erc=True),
Pin(num='58',name='P58',func=Pin.PASSIVE,do_erc=True),
Pin(num='68',name='P68',func=Pin.PASSIVE,do_erc=True),
Pin(num='78',name='P78',func=Pin.PASSIVE,do_erc=True),
Pin(num='88',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='98',name='P98',func=Pin.BIDIR,do_erc=True),
Pin(num='19',name='P19',func=Pin.PASSIVE,do_erc=True),
Pin(num='29',name='P29',func=Pin.PASSIVE,do_erc=True),
Pin(num='39',name='P39',func=Pin.PASSIVE,do_erc=True),
Pin(num='49',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='59',name='P59',func=Pin.PASSIVE,do_erc=True),
Pin(num='69',name='P69',func=Pin.PASSIVE,do_erc=True),
Pin(num='79',name='PGCK4',func=Pin.PASSIVE,do_erc=True),
Pin(num='89',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='99',name='SGCK1',func=Pin.BIDIR,do_erc=True),
Pin(num='100',name='VCC',func=Pin.PWRIN,do_erc=True)]),
Part(name='XC4004-PQ160',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='XC4005-PG156',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='XC4005-PQ100',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='XC4005-PQ160',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='XC6SLX25T-BG484',dest=TEMPLATE,tool=SKIDL,description='SPARTAN-6 FG484',ref_prefix='U',num_units=3,do_erc=True,pins=[
Pin(num='A2',name='IO_L3N_0',func=Pin.BIDIR,do_erc=True),
Pin(num='B2',name='IO_L3P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='A3',name='IO_L5N_0',func=Pin.BIDIR,do_erc=True),
Pin(num='B3',name='IO_L5P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='C3',name='IO_L1P_HSWAPEN_0',func=Pin.BIDIR,do_erc=True),
Pin(num='D3',name='IO_L1N_VREF_0',func=Pin.BIDIR,do_erc=True),
Pin(num='A4',name='IO_L6N_0',func=Pin.BIDIR,do_erc=True),
Pin(num='B4',name='VCCO_0',func=Pin.PWRIN,do_erc=True),
Pin(num='C4',name='IO_L6P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='D4',name='IO_L2P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='A5',name='IO_L8N_VREF_0',func=Pin.BIDIR,do_erc=True),
Pin(num='C5',name='IO_L8P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='D5',name='IO_L2N_0',func=Pin.BIDIR,do_erc=True),
Pin(num='E5',name='IO_L4P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='A6',name='MGTTXN0_101',func=Pin.OUTPUT,do_erc=True),
Pin(num='B6',name='MGTTXP0_101',func=Pin.OUTPUT,do_erc=True),
Pin(num='E6',name='IO_L4N_0',func=Pin.BIDIR,do_erc=True),
Pin(num='F6',name='VCCO_0',func=Pin.PWRIN,do_erc=True),
Pin(num='A7',name='MGTAVTTTX_101',func=Pin.PASSIVE,do_erc=True),
Pin(num='C7',name='MGTRXN0_101',do_erc=True),
Pin(num='D7',name='MGTRXP0_101',do_erc=True),
Pin(num='F7',name='IO_L7P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='A8',name='MGTTXN1_101',func=Pin.OUTPUT,do_erc=True),
Pin(num='B8',name='MGTTXP1_101',func=Pin.OUTPUT,do_erc=True),
Pin(num='D8',name='MGTAVTTRX_101',func=Pin.PASSIVE,do_erc=True),
Pin(num='E8',name='MGTAVTTRCAL_101',func=Pin.PASSIVE,do_erc=True),
Pin(num='F8',name='IO_L7N_0',func=Pin.BIDIR,do_erc=True),
Pin(num='G8',name='IO_L32P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='B9',name='MGTAVCCPLL0_101',func=Pin.PASSIVE,do_erc=True),
Pin(num='C9',name='MGTRXN1_101',do_erc=True),
Pin(num='D9',name='MGTRXP1_101',do_erc=True),
Pin(num='E9',name='MGTRREF_101',do_erc=True),
Pin(num='F9',name='IO_L32N_0',func=Pin.BIDIR,do_erc=True),
Pin(num='G9',name='IO_L34P_GCLK19_0',func=Pin.BIDIR,do_erc=True),
Pin(num='A10',name='MGTREFCLK0P_101',do_erc=True),
Pin(num='B10',name='MGTREFCLK0N_101',do_erc=True),
Pin(num='C10',name='MGTAVCC_101',func=Pin.PASSIVE,do_erc=True),
Pin(num='F10',name='IO_L34N_GCLK18_0',func=Pin.BIDIR,do_erc=True),
Pin(num='G10',name='VCCO_0',func=Pin.PWRIN,do_erc=True),
Pin(num='H10',name='IO_L33P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='A20',name='IO_L65N_SCP2_0',func=Pin.BIDIR,do_erc=True),
Pin(num='B20',name='IO_L65P_SCP3_0',func=Pin.BIDIR,do_erc=True),
Pin(num='C20',name='IO_L20P_1',func=Pin.BIDIR,do_erc=True),
Pin(num='D20',name='TMS',do_erc=True),
Pin(num='E20',name='IO_L32P_A17_M1A8_1',func=Pin.BIDIR,do_erc=True),
Pin(num='F20',name='IO_L29N_A22_M1A14_1',func=Pin.BIDIR,do_erc=True),
Pin(num='G20',name='IO_L35P_A11_M1A7_1',func=Pin.BIDIR,do_erc=True),
Pin(num='H20',name='IO_L33N_A14_M1A4_1',func=Pin.BIDIR,do_erc=True),
Pin(num='J20',name='IO_L39P_M1A3_1',func=Pin.BIDIR,do_erc=True),
Pin(num='K20',name='IO_L38P_A5_M1CLK_1',func=Pin.BIDIR,do_erc=True),
Pin(num='L20',name='IO_L43P_GCLK5_M1DQ4_1',func=Pin.BIDIR,do_erc=True),
Pin(num='M20',name='IO_L40P_GCLK11_M1A5_1',func=Pin.BIDIR,do_erc=True),
Pin(num='N20',name='IO_L45P_A1_M1LDQS_1',func=Pin.BIDIR,do_erc=True),
Pin(num='P20',name='IO_L42P_GCLK7_M1UDM_1',func=Pin.BIDIR,do_erc=True),
Pin(num='R20',name='IO_L47P_FWE_B_M1DQ0_1',func=Pin.BIDIR,do_erc=True),
Pin(num='T20',name='IO_L59N_1',func=Pin.BIDIR,do_erc=True),
Pin(num='U20',name='IO_L49P_M1DQ10_1',func=Pin.BIDIR,do_erc=True),
Pin(num='V20',name='IO_L74N_DOUT_BUSY_1',func=Pin.BIDIR,do_erc=True),
Pin(num='W20',name='IO_L51P_M1DQ12_1',func=Pin.BIDIR,do_erc=True),
Pin(num='C11',name='MGTREFCLK1P_101',do_erc=True),
Pin(num='D11',name='MGTREFCLK1N_101',do_erc=True),
Pin(num='G11',name='IO_L35N_GCLK16_0',func=Pin.BIDIR,do_erc=True),
Pin(num='H11',name='IO_L33N_0',func=Pin.BIDIR,do_erc=True),
Pin(num='A21',name='TCK',do_erc=True),
Pin(num='C21',name='VCCO_1',func=Pin.PWRIN,do_erc=True),
Pin(num='F21',name='IO_L31P_A19_M1CKE_1',func=Pin.BIDIR,do_erc=True),
Pin(num='G21',name='VCCO_1',func=Pin.PWRIN,do_erc=True),
Pin(num='H21',name='IO_L37P_A7_M1A0_1',func=Pin.BIDIR,do_erc=True),
Pin(num='K21',name='IO_L41P_GCLK9_IRDY1_M1RASN_1',func=Pin.BIDIR,do_erc=True),
Pin(num='L21',name='VCCO_1',func=Pin.PWRIN,do_erc=True),
Pin(num='M21',name='IO_L44P_A3_M1DQ6_1',func=Pin.BIDIR,do_erc=True),
Pin(num='P21',name='IO_L46P_FCS_B_M1DQ2_1',func=Pin.BIDIR,do_erc=True),
Pin(num='R21',name='VCCO_1',func=Pin.PWRIN,do_erc=True),
Pin(num='T21',name='IO_L48P_HDC_M1DQ8_1',func=Pin.BIDIR,do_erc=True),
Pin(num='V21',name='IO_L50P_M1UDQS_1',func=Pin.BIDIR,do_erc=True),
Pin(num='W21',name='VCCO_1',func=Pin.PWRIN,do_erc=True),
Pin(num='Y21',name='IO_L52P_M1DQ14_1',func=Pin.BIDIR,do_erc=True),
Pin(num='D12',name='MGTAVCCPLL1_101',func=Pin.PASSIVE,do_erc=True),
Pin(num='H12',name='IO_L35P_GCLK17_0',func=Pin.BIDIR,do_erc=True),
Pin(num='C22',name='IO_L20N_1',func=Pin.BIDIR,do_erc=True),
Pin(num='E22',name='IO_L32N_A16_M1A9_1',func=Pin.BIDIR,do_erc=True),
Pin(num='F22',name='IO_L31N_A18_M1A12_1',func=Pin.BIDIR,do_erc=True),
Pin(num='G22',name='IO_L35N_A10_M1A2_1',func=Pin.BIDIR,do_erc=True),
Pin(num='H22',name='IO_L37N_A6_M1A1_1',func=Pin.BIDIR,do_erc=True),
Pin(num='J22',name='IO_L39N_M1ODT_1',func=Pin.BIDIR,do_erc=True),
Pin(num='K22',name='IO_L41N_GCLK8_M1CASN_1',func=Pin.BIDIR,do_erc=True),
Pin(num='L22',name='IO_L43N_CLK4_M1DQ5_1',func=Pin.BIDIR,do_erc=True),
Pin(num='M22',name='IO_L44N_A2_M1DQ7_1',func=Pin.BIDIR,do_erc=True),
Pin(num='N22',name='IO_L45N_A0_M1LDQSN_1',func=Pin.BIDIR,do_erc=True),
Pin(num='P22',name='IO_L46N_FOE_B_M1DQ3_1',func=Pin.BIDIR,do_erc=True),
Pin(num='R22',name='IO_L47N_LDC_M1DQ1_1',func=Pin.BIDIR,do_erc=True),
Pin(num='T22',name='IO_L48N_M1DQ9_1',func=Pin.BIDIR,do_erc=True),
Pin(num='U22',name='IO_L49N_M1DQ11_1',func=Pin.BIDIR,do_erc=True),
Pin(num='V22',name='IO_L50N_M1UDQSN_1',func=Pin.BIDIR,do_erc=True),
Pin(num='W22',name='IO_L51N_M1DQ13_1',func=Pin.BIDIR,do_erc=True),
Pin(num='Y22',name='IO_L52N_M1DQ15_1',func=Pin.BIDIR,do_erc=True),
Pin(num='G13',name='IO_L38N_VREF_0',func=Pin.BIDIR,do_erc=True),
Pin(num='H13',name='IO_L38P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='F14',name='IO_L36P_GCLK15_0',func=Pin.BIDIR,do_erc=True),
Pin(num='G14',name='VCCO_0',func=Pin.PWRIN,do_erc=True),
Pin(num='H14',name='IO_L49P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='F15',name='IO_L36N_GCLK14_0',func=Pin.BIDIR,do_erc=True),
Pin(num='G15',name='IO_L49N_0',func=Pin.BIDIR,do_erc=True),
Pin(num='E16',name='IO_L37P_GCLK13_0',func=Pin.BIDIR,do_erc=True),
Pin(num='F16',name='IO_L37N_GCLK12_0',func=Pin.BIDIR,do_erc=True),
Pin(num='G16',name='IO_L51P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='J16',name='IO_L19P_1',func=Pin.BIDIR,do_erc=True),
Pin(num='L16',name='VCCO_1',func=Pin.PWRIN,do_erc=True),
Pin(num='N16',name='IO_L60P_1',func=Pin.BIDIR,do_erc=True),
Pin(num='P16',name='IO_L60N_1',func=Pin.BIDIR,do_erc=True),
Pin(num='A17',name='IO_L50N_0',func=Pin.BIDIR,do_erc=True),
Pin(num='C17',name='IO_L50P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='D17',name='IO_L66P_SCP1_0',func=Pin.BIDIR,do_erc=True),
Pin(num='E17',name='VCCO_0',func=Pin.PWRIN,do_erc=True),
Pin(num='F17',name='IO_L51N_0',func=Pin.BIDIR,do_erc=True),
Pin(num='G17',name='TDO',func=Pin.OUTPUT,do_erc=True),
Pin(num='J17',name='IO_L19N_1',func=Pin.BIDIR,do_erc=True),
Pin(num='K17',name='IO_L36P_A9_M1BA0_1',do_erc=True),
Pin(num='L17',name='IO_L36N_A8_M1BA1_1',func=Pin.BIDIR,do_erc=True),
Pin(num='M17',name='IO_L61P_1',func=Pin.BIDIR,do_erc=True),
Pin(num='A18',name='IO_L63N_SCP6_0',func=Pin.BIDIR,do_erc=True),
Pin(num='B18',name='IO_L63P_SCP7_0',func=Pin.BIDIR,do_erc=True),
Pin(num='C18',name='IO_L66N_SCP0_0',func=Pin.BIDIR,do_erc=True),
Pin(num='D18',name='IO_L62P_0',func=Pin.BIDIR,do_erc=True),
Pin(num='E18',name='TDI',do_erc=True),
Pin(num='F18',name='IO_L1P_A25_1',func=Pin.BIDIR,do_erc=True),
Pin(num='H18',name='IO_L30P_A21_M1RESET_1',func=Pin.BIDIR,do_erc=True),
Pin(num='J18',name='VCCO_1',func=Pin.PWRIN,do_erc=True),
Pin(num='K18',name='IO_L34N_A12_M1BA2_1',func=Pin.BIDIR,do_erc=True),
Pin(num='M18',name='IO_L61N_1',func=Pin.BIDIR,do_erc=True),
Pin(num='N18',name='VCCO_1',func=Pin.PWRIN,do_erc=True),
Pin(num='U18',name='VCCO_1',func=Pin.PWRIN,do_erc=True),
Pin(num='A19',name='IO_L46N_SCP4_0',func=Pin.BIDIR,do_erc=True),
Pin(num='B19',name='VCCO_0',func=Pin.PWRIN,do_erc=True),
Pin(num='C19',name='IO_L64P_SCP5_0',func=Pin.BIDIR,do_erc=True),
Pin(num='D19',name='IO_L62N_VREF_0',func=Pin.BIDIR,do_erc=True),
Pin(num='E19',name='VCCO_1',func=Pin.PWRIN,do_erc=True),
Pin(num='F19',name='IO_L1N_A24_VREF_1',func=Pin.BIDIR,do_erc=True),
Pin(num='G19',name='IO_L29P_A23_M1A13_1',func=Pin.BIDIR,do_erc=True),
Pin(num='H19',name='IO_L30N_A20_M1A11_1',func=Pin.BIDIR,do_erc=True),
Pin(num='J19',name='IO_L33P_A15_M1A10_1',func=Pin.BIDIR,do_erc=True),
Pin(num='K19',name='IO_L34P_A13_M1WE_1',func=Pin.BIDIR,do_erc=True),
Pin(num='L19',name='IO_L38N_A4_M1CLKN_1',func=Pin.BIDIR,do_erc=True),
Pin(num='M19',name='IO_L40N_GCLK10_M1A6_1',func=Pin.BIDIR,do_erc=True),
Pin(num='N19',name='IO_L42N_GCLK6_TRDY1_M1LDM_1',func=Pin.BIDIR,do_erc=True),
Pin(num='P19',name='IO_L53P_1',func=Pin.BIDIR,do_erc=True),
Pin(num='R19',name='IO_L53N_VREF_1',func=Pin.BIDIR,do_erc=True),
Pin(num='U19',name='IO_L59P_1',func=Pin.BIDIR,do_erc=True),
Pin(num='V19',name='IO_L74P_AWAKE_1',func=Pin.BIDIR,do_erc=True),
Pin(num='B1',name='IO_L83N_VREF_3',func=Pin.BIDIR,do_erc=True),
Pin(num='C1',name='IO_L83P_3',func=Pin.BIDIR,do_erc=True),
Pin(num='D1',name='IO_L59N_3',func=Pin.BIDIR,do_erc=True),
Pin(num='E1',name='IO_L54N_M3A11_3',func=Pin.BIDIR,do_erc=True),
Pin(num='F1',name='IO_L53N_M3A12_3',func=Pin.BIDIR,do_erc=True),
Pin(num='G1',name='IO_L52N_M3A9_3',func=Pin.BIDIR,do_erc=True),
Pin(num='H1',name='IO_L50N_M3BA2_3',func=Pin.BIDIR,do_erc=True),
Pin(num='J1',name='IO_L48N_M3BA1_3',func=Pin.BIDIR,do_erc=True),
Pin(num='K1',name='IO_L47N_M3A1_3',func=Pin.BIDIR,do_erc=True),
Pin(num='L1',name='IO_L41N_GCLK26_M3DQ5_3',func=Pin.BIDIR,do_erc=True),
Pin(num='M1',name='IO_L40N_M3DQ7_3',func=Pin.BIDIR,do_erc=True),
Pin(num='N1',name='IO_L39N_M3LDQSN_3',func=Pin.BIDIR,do_erc=True),
Pin(num='P1',name='IO_L38N_M3DQ3_3',func=Pin.BIDIR,do_erc=True),
Pin(num='R1',name='IO_L37N_M3DQ1_3',func=Pin.BIDIR,do_erc=True),
Pin(num='T1',name='IO_L36N_M3DQ9_3',func=Pin.BIDIR,do_erc=True),
Pin(num='U1',name='IO_L35N_M3DQ11_3',func=Pin.BIDIR,do_erc=True),
Pin(num='V1',name='IO_L34N_M3UDQSN_3',func=Pin.BIDIR,do_erc=True),
Pin(num='W1',name='IO_L33N_M3DQ13_3',func=Pin.BIDIR,do_erc=True),
Pin(num='Y1',name='IO_L32N_M3DQ15_3',func=Pin.BIDIR,do_erc=True),
Pin(num='C2',name='VCCO_3',func=Pin.PWRIN,do_erc=True),
Pin(num='D2',name='IO_L59P_3',func=Pin.BIDIR,do_erc=True),
Pin(num='F2',name='IO_L53P_M3CKE_3',func=Pin.BIDIR,do_erc=True),
Pin(num='G2',name='VCCO_3',func=Pin.PWRIN,do_erc=True),
Pin(num='H2',name='IO_L50P_M3WE_3',func=Pin.BIDIR,do_erc=True),
Pin(num='K2',name='IO_L47P_M3A0_3',func=Pin.BIDIR,do_erc=True),
Pin(num='L2',name='VCCO_3',func=Pin.PWRIN,do_erc=True),
Pin(num='M2',name='IO_L40P_M3DQ6_3',func=Pin.BIDIR,do_erc=True),
Pin(num='P2',name='IO_L38P_M3DQ2_3',func=Pin.BIDIR,do_erc=True),
Pin(num='R2',name='VCCO_3',func=Pin.PWRIN,do_erc=True),
Pin(num='T2',name='IO_L36P_M3DQ8_3',func=Pin.BIDIR,do_erc=True),
Pin(num='V2',name='IO_L34P_M3UDQS_3',func=Pin.BIDIR,do_erc=True),
Pin(num='W2',name='VCCO_3',func=Pin.PWRIN,do_erc=True),
Pin(num='Y2',name='IO_L32P_M3DQ14_3',func=Pin.BIDIR,do_erc=True),
Pin(num='E3',name='IO_L54P_M3RESET_3',func=Pin.BIDIR,do_erc=True),
Pin(num='F3',name='IO_L60P_3',func=Pin.BIDIR,do_erc=True),
Pin(num='G3',name='IO_L52P_M3A8_3',func=Pin.BIDIR,do_erc=True),
Pin(num='H3',name='IO_L51N_M3A4_3',func=Pin.BIDIR,do_erc=True),
Pin(num='J3',name='IO_L48P_M3BA0_3',func=Pin.BIDIR,do_erc=True),
Pin(num='K3',name='IO_L46N_M3CLKN_3',func=Pin.BIDIR,do_erc=True),
Pin(num='L3',name='IO_L41P_GCLK27_M3DQ4_3',func=Pin.BIDIR,do_erc=True),
Pin(num='M3',name='IO_L44P_GCLK21_M3A5_3',func=Pin.BIDIR,do_erc=True),
Pin(num='N3',name='IO_L39P_M3LDQS_3',func=Pin.BIDIR,do_erc=True),
Pin(num='P3',name='IO_L42P_GCLK25_TRDY2_M3UDM_3',func=Pin.BIDIR,do_erc=True),
Pin(num='R3',name='IO_L37P_M3DQ0_3',func=Pin.BIDIR,do_erc=True),
Pin(num='U3',name='IO_L35P_M3DQ10_3',func=Pin.BIDIR,do_erc=True),
Pin(num='W3',name='IO_L33P_M3DQ12_3',func=Pin.BIDIR,do_erc=True),
Pin(num='Y3',name='IO_L2N_3',func=Pin.BIDIR,do_erc=True),
Pin(num='E4',name='IO_L60N_3',func=Pin.BIDIR,do_erc=True),
Pin(num='F4',name='VCCO_3',func=Pin.PWRIN,do_erc=True),
Pin(num='J4',name='IO_L51P_M3A10_3',func=Pin.BIDIR,do_erc=True),
Pin(num='K4',name='IO_L46P_M3CLK_3',func=Pin.BIDIR,do_erc=True),
Pin(num='L4',name='IO_L44N_GCLK207_M3A6_3',func=Pin.BIDIR,do_erc=True),
Pin(num='M4',name='IO_L43N_GCLK22_TRDY2_M3CASN_3',func=Pin.BIDIR,do_erc=True),
Pin(num='N4',name='IO_L42N_GCLK24_M3LDM_3',func=Pin.BIDIR,do_erc=True),
Pin(num='P4',name='IO_L9N_3',func=Pin.BIDIR,do_erc=True),
Pin(num='W4',name='IO_L2P_3',func=Pin.BIDIR,do_erc=True),
Pin(num='Y4',name='IO_L65P_INIT_B_2',func=Pin.BIDIR,do_erc=True),
Pin(num='H5',name='IO_L55N_M3A14_3',func=Pin.BIDIR,do_erc=True),
Pin(num='J5',name='VCCO_3',func=Pin.PWRIN,do_erc=True),
Pin(num='K5',name='IO_L49N_M3A2_3',func=Pin.BIDIR,do_erc=True),
Pin(num='M5',name='IO_L43P_GCLK23_M3RASN_3',func=Pin.BIDIR,do_erc=True),
Pin(num='N5',name='VCCO_3',func=Pin.PWRIN,do_erc=True),
Pin(num='P5',name='IO_L9P_3',func=Pin.BIDIR,do_erc=True),
Pin(num='U5',name='VCCO_3',func=Pin.PWRIN,do_erc=True),
Pin(num='W5',name='VCCO_2',func=Pin.PWRIN,do_erc=True),
Pin(num='Y5',name='IO_L62P_D5_2',func=Pin.BIDIR,do_erc=True),
Pin(num='J6',name='IO_L55P_M3A13_3',func=Pin.BIDIR,do_erc=True),
Pin(num='K6',name='IO_L49P_M3A7_3',func=Pin.BIDIR,do_erc=True),
Pin(num='L6',name='IO_L45N_M3ODT_3',func=Pin.BIDIR,do_erc=True),
Pin(num='M6',name='IO_L45P_M3A3_3',func=Pin.BIDIR,do_erc=True),
Pin(num='U6',name='IO_L64N_D9_2',func=Pin.BIDIR,do_erc=True),
Pin(num='W6',name='IO_L60P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='Y6',name='IO_L60N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='L7',name='VCCO_3',func=Pin.PWRIN,do_erc=True),
Pin(num='M7',name='IO_L31P_3',func=Pin.BIDIR,do_erc=True),
Pin(num='R7',name='IO_L1P_3',func=Pin.BIDIR,do_erc=True),
Pin(num='T7',name='IO_L64P_D8_2',func=Pin.BIDIR,do_erc=True),
Pin(num='V7',name='IO_L58P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='Y7',name='IO_L47P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='M8',name='IO_L31N_VREF_3',func=Pin.BIDIR,do_erc=True),
Pin(num='P8',name='IO_L1N_VREF_3',func=Pin.BIDIR,do_erc=True),
Pin(num='R8',name='IO_L59N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='T8',name='IO_L57P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='U8',name='IO_L57N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='V8',name='VCCO_2',func=Pin.PWRIN,do_erc=True),
Pin(num='W8',name='IO_L58N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='Y8',name='IO_L48N_RDWR_B_VREF_2',func=Pin.BIDIR,do_erc=True),
Pin(num='R9',name='IO_L59P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='T9',name='VCCO_2',func=Pin.PWRIN,do_erc=True),
Pin(num='U9',name='IO_L50P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='V9',name='IO_L50N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='W9',name='IO_L48P_D7_2',func=Pin.BIDIR,do_erc=True),
Pin(num='Y9',name='IO_L43P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='T10',name='IO_L46P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='U10',name='IO_L46N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='W10',name='IO_L44P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='Y10',name='IO_L44N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='Y20',name='IO_L1P_CCLK_2',func=Pin.BIDIR,do_erc=True),
Pin(num='V11',name='IO_L42P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='W11',name='IO_L42N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='Y11',name='IO_L32P_GCLK29_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AA1',name='IO_L10N_3',func=Pin.BIDIR,do_erc=True),
Pin(num='T12',name='IO_L29P_GCLK3_2',func=Pin.BIDIR,do_erc=True),
Pin(num='U12',name='IO_L29N_GCLK2_2',func=Pin.BIDIR,do_erc=True),
Pin(num='V12',name='VCCO_2',func=Pin.PWRIN,do_erc=True),
Pin(num='W12',name='IO_L40P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='Y12',name='IO_L40N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AA2',name='IO_L10P_3',func=Pin.BIDIR,do_erc=True),
Pin(num='AB2',name='PROGRAM_B_2',do_erc=True),
Pin(num='R13',name='IO_L12P_D1_MISO2_2',func=Pin.BIDIR,do_erc=True),
Pin(num='T13',name='VCCO_2',func=Pin.PWRIN,do_erc=True),
Pin(num='U13',name='IO_L16N_VREF_2',func=Pin.BIDIR,do_erc=True),
Pin(num='V13',name='IO_L18P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='W13',name='IO_L18N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='Y13',name='IO_L30P_GCLK1_D13_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AA3',name='IO_L65N_CSO_B_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AB3',name='VCCO_2',func=Pin.PWRIN,do_erc=True),
Pin(num='T14',name='IO_L12N_D2_MISO3_2',func=Pin.BIDIR,do_erc=True),
Pin(num='U14',name='IO_L16P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='W14',name='IO_L20P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='Y14',name='IO_L20N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AA4',name='IO_L63P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AB4',name='IO_L63N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='W15',name='IO_L17N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='Y15',name='IO_L21P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AB5',name='IO_L62N_D6_2',func=Pin.BIDIR,do_erc=True),
Pin(num='V16',name='VCCO_2',func=Pin.PWRIN,do_erc=True),
Pin(num='Y16',name='IO_L17P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AA6',name='IO_L49P_D3_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AB6',name='IO_L49N_D4_2',func=Pin.BIDIR,do_erc=True),
Pin(num='V17',name='IO_L2P_CMPCLK_2',func=Pin.BIDIR,do_erc=True),
Pin(num='W17',name='IO_L5P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='Y17',name='IO_L15P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AA7',name='VCCO_2',func=Pin.PWRIN,do_erc=True),
Pin(num='AB7',name='IO_L47N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='V18',name='CMPCS_B_2',do_erc=True),
Pin(num='W18',name='IO_L2N_CMPMOSI_2',func=Pin.BIDIR,do_erc=True),
Pin(num='Y18',name='IO_L5N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AA8',name='IO_L45P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AB8',name='IO_L45N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='Y19',name='IO_L13P_M1_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AB9',name='IO_L43N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AA10',name='IO_L41P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AB10',name='IO_L41N_VREF_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AA20',name='IO_L3P_D0_DIN_MISO_MISO1_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AB20',name='IO_L3N_MOSI_CSI_B_MISO0_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AA11',name='VCCO_2',func=Pin.PWRIN,do_erc=True),
Pin(num='AB11',name='IO_L32N_GCLK28_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AA21',name='IO_L1N_M0_CMPMISO_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AB21',name='DONE_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AA12',name='IO_L31P_GCLK31_D14_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AB12',name='IO_L31N_GCLK30_D15_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AA22',name='SUSPEND',do_erc=True),
Pin(num='AB13',name='IO_L30N_GCLK0_USERCCLK_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AA14',name='IO_L6P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AB14',name='IO_L6N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AA15',name='VCCO_2',func=Pin.PWRIN,do_erc=True),
Pin(num='AB15',name='IO_L21N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AA16',name='IO_L19P_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AB16',name='IO_L19N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AB17',name='IO_L15N_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AA18',name='IO_L14P_D11_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AB18',name='IO_L14N_D12_2',func=Pin.BIDIR,do_erc=True),
Pin(num='AA19',name='VCCO_2',func=Pin.PWRIN,do_erc=True),
Pin(num='AB19',name='IO_L13N_D10_2',func=Pin.BIDIR,do_erc=True),
Pin(num='A1',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='E2',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='J2',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='N2',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='U2',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='V4',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='B5',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='G5',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='L5',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='R5',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='C6',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='D6',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='R6',name='VCCAUX',func=Pin.PWRIN,do_erc=True),
Pin(num='V6',name='VCCAUX',func=Pin.PWRIN,do_erc=True),
Pin(num='B7',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='E7',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='H7',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='U7',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='W7',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='C8',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='J8',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='L8',name='VCCAUX',func=Pin.PWRIN,do_erc=True),
Pin(num='N8',name='VCCAUX',func=Pin.PWRIN,do_erc=True),
Pin(num='A9',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='H9',name='VCCAUX',func=Pin.PWRIN,do_erc=True),
Pin(num='J9',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='K9',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='L9',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='M9',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='N9',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='P9',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='D10',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='J10',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='K10',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='L10',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='M10',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='N10',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='P10',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='R10',name='VCCAUX',func=Pin.PWRIN,do_erc=True),
Pin(num='V10',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='A11',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='B11',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='E11',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='F11',name='VCCAUX',func=Pin.PWRIN,do_erc=True),
Pin(num='J11',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='K11',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='L11',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='M11',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='N11',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='P11',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='U11',name='VCCAUX',func=Pin.PWRIN,do_erc=True),
Pin(num='E21',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='J21',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='N21',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='U21',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='AB1',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='C12',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='G12',name='VCCAUX',func=Pin.PWRIN,do_erc=True),
Pin(num='J12',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='K12',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='L12',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='M12',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='N12',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='P12',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='R12',name='VCCAUX',func=Pin.PWRIN,do_erc=True),
Pin(num='A22',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='A13',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='F13',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='J13',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='K13',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='L13',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='M13',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='N13',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='P13',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='C14',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='E14',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='J14',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='K14',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='L14',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='M14',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='N14',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='P14',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='R14',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='V14',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='B15',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='E15',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='H15',name='VCCAUX',func=Pin.PWRIN,do_erc=True),
Pin(num='J15',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='K15',name='VCCAUX',func=Pin.PWRIN,do_erc=True),
Pin(num='M15',name='VCCAUX',func=Pin.PWRIN,do_erc=True),
Pin(num='AA5',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='C16',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='D16',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='W16',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='B17',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='N17',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='G18',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='L18',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='R18',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='W19',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='AA9',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='AB22',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='AA13',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='AA17',name='GND',func=Pin.PWRIN,do_erc=True)]),
Part(name='XC7336',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='XC95108PC84',dest=TEMPLATE,tool=SKIDL,ref_prefix='U',num_units=1,do_erc=True,pins=[
Pin(num='1',name='P1',func=Pin.BIDIR,do_erc=True),
Pin(num='2',name='P2',func=Pin.BIDIR,do_erc=True),
Pin(num='3',name='P3',func=Pin.BIDIR,do_erc=True),
Pin(num='4',name='P4',func=Pin.BIDIR,do_erc=True),
Pin(num='5',name='P5',func=Pin.BIDIR,do_erc=True),
Pin(num='6',name='P6',func=Pin.BIDIR,do_erc=True),
Pin(num='7',name='P7',func=Pin.BIDIR,do_erc=True),
Pin(num='8',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='9',name='I/O/GCK1',func=Pin.BIDIR,do_erc=True),
Pin(num='10',name='I/O/GCK2',func=Pin.BIDIR,do_erc=True),
Pin(num='20',name='P20',func=Pin.BIDIR,do_erc=True),
Pin(num='30',name='TCK',do_erc=True),
Pin(num='40',name='P40',func=Pin.BIDIR,do_erc=True),
Pin(num='50',name='P50',func=Pin.BIDIR,do_erc=True),
Pin(num='60',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='70',name='P70',func=Pin.BIDIR,do_erc=True),
Pin(num='80',name='P80',func=Pin.BIDIR,do_erc=True),
Pin(num='11',name='P11',func=Pin.BIDIR,do_erc=True),
Pin(num='21',name='P21',func=Pin.BIDIR,do_erc=True),
Pin(num='31',name='P31',func=Pin.BIDIR,do_erc=True),
Pin(num='41',name='P41',func=Pin.BIDIR,do_erc=True),
Pin(num='51',name='P51',func=Pin.BIDIR,do_erc=True),
Pin(num='61',name='P61',func=Pin.BIDIR,do_erc=True),
Pin(num='71',name='P71',func=Pin.BIDIR,do_erc=True),
Pin(num='81',name='P81',func=Pin.BIDIR,do_erc=True),
Pin(num='12',name='I/O/GCK3',func=Pin.BIDIR,do_erc=True),
Pin(num='22',name='VCCIO',func=Pin.PWRIN,do_erc=True),
Pin(num='32',name='P32',func=Pin.BIDIR,do_erc=True),
Pin(num='42',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='52',name='P52',func=Pin.BIDIR,do_erc=True),
Pin(num='62',name='P62',func=Pin.BIDIR,do_erc=True),
Pin(num='72',name='P72',func=Pin.BIDIR,do_erc=True),
Pin(num='82',name='P82',func=Pin.BIDIR,do_erc=True),
Pin(num='13',name='P13',func=Pin.BIDIR,do_erc=True),
Pin(num='23',name='P23',func=Pin.BIDIR,do_erc=True),
Pin(num='33',name='P33',func=Pin.BIDIR,do_erc=True),
Pin(num='43',name='P43',func=Pin.BIDIR,do_erc=True),
Pin(num='53',name='P53',func=Pin.BIDIR,do_erc=True),
Pin(num='63',name='P63',func=Pin.BIDIR,do_erc=True),
Pin(num='73',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='83',name='P83',func=Pin.BIDIR,do_erc=True),
Pin(num='14',name='P14',func=Pin.BIDIR,do_erc=True),
Pin(num='24',name='P24',func=Pin.BIDIR,do_erc=True),
Pin(num='34',name='P34',func=Pin.BIDIR,do_erc=True),
Pin(num='44',name='P44',func=Pin.BIDIR,do_erc=True),
Pin(num='54',name='P54',func=Pin.BIDIR,do_erc=True),
Pin(num='64',name='VCCIO',func=Pin.PWRIN,do_erc=True),
Pin(num='74',name='I/O/GSR',func=Pin.BIDIR,do_erc=True),
Pin(num='84',name='P84',func=Pin.BIDIR,do_erc=True),
Pin(num='15',name='P15',func=Pin.BIDIR,do_erc=True),
Pin(num='25',name='P25',func=Pin.BIDIR,do_erc=True),
Pin(num='35',name='P35',func=Pin.BIDIR,do_erc=True),
Pin(num='45',name='P45',func=Pin.BIDIR,do_erc=True),
Pin(num='55',name='P55',func=Pin.BIDIR,do_erc=True),
Pin(num='65',name='P65',func=Pin.BIDIR,do_erc=True),
Pin(num='75',name='P75',func=Pin.BIDIR,do_erc=True),
Pin(num='16',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='26',name='P26',func=Pin.BIDIR,do_erc=True),
Pin(num='36',name='P36',func=Pin.BIDIR,do_erc=True),
Pin(num='46',name='P46',func=Pin.BIDIR,do_erc=True),
Pin(num='56',name='P56',func=Pin.BIDIR,do_erc=True),
Pin(num='66',name='P66',func=Pin.BIDIR,do_erc=True),
Pin(num='76',name='I/O/GTS1',func=Pin.BIDIR,do_erc=True),
Pin(num='17',name='P17',func=Pin.BIDIR,do_erc=True),
Pin(num='27',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='37',name='P37',func=Pin.BIDIR,do_erc=True),
Pin(num='47',name='P47',func=Pin.BIDIR,do_erc=True),
Pin(num='57',name='P57',func=Pin.BIDIR,do_erc=True),
Pin(num='67',name='P67',func=Pin.BIDIR,do_erc=True),
Pin(num='77',name='I/O/GTS2',func=Pin.BIDIR,do_erc=True),
Pin(num='18',name='P18',func=Pin.BIDIR,do_erc=True),
Pin(num='28',name='TDI',do_erc=True),
Pin(num='38',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='48',name='P48',func=Pin.BIDIR,do_erc=True),
Pin(num='58',name='P58',func=Pin.BIDIR,do_erc=True),
Pin(num='68',name='P68',func=Pin.BIDIR,do_erc=True),
Pin(num='78',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='19',name='P19',func=Pin.BIDIR,do_erc=True),
Pin(num='29',name='TMS',do_erc=True),
Pin(num='39',name='P39',func=Pin.BIDIR,do_erc=True),
Pin(num='49',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='59',name='TDO',func=Pin.OUTPUT,do_erc=True),
Pin(num='69',name='P69',func=Pin.BIDIR,do_erc=True),
Pin(num='79',name='P79',func=Pin.BIDIR,do_erc=True)]),
Part(name='XC95108PQ100',dest=TEMPLATE,tool=SKIDL,ref_prefix='U',num_units=1,do_erc=True,pins=[
Pin(num='1',name='I/O/GSR',func=Pin.BIDIR,do_erc=True),
Pin(num='2',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='3',name='P3',func=Pin.BIDIR,do_erc=True),
Pin(num='4',name='P4',func=Pin.BIDIR,do_erc=True),
Pin(num='5',name='I/O/GTS1',func=Pin.BIDIR,do_erc=True),
Pin(num='6',name='I/O/GTS2',func=Pin.BIDIR,do_erc=True),
Pin(num='7',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='8',name='P8',func=Pin.BIDIR,do_erc=True),
Pin(num='9',name='P9',func=Pin.BIDIR,do_erc=True),
Pin(num='10',name='P10',func=Pin.BIDIR,do_erc=True),
Pin(num='20',name='P20',func=Pin.BIDIR,do_erc=True),
Pin(num='30',name='P30',func=Pin.BIDIR,do_erc=True),
Pin(num='40',name='VCCIO',func=Pin.PWRIN,do_erc=True),
Pin(num='50',name='TCK',do_erc=True),
Pin(num='60',name='P60',func=Pin.BIDIR,do_erc=True),
Pin(num='70',name='P70',func=Pin.BIDIR,do_erc=True),
Pin(num='80',name='P80',func=Pin.BIDIR,do_erc=True),
Pin(num='90',name='VCCIO',func=Pin.PWRIN,do_erc=True),
Pin(num='11',name='P11',func=Pin.BIDIR,do_erc=True),
Pin(num='21',name='P21',func=Pin.BIDIR,do_erc=True),
Pin(num='31',name='P31',func=Pin.BIDIR,do_erc=True),
Pin(num='41',name='P41',func=Pin.BIDIR,do_erc=True),
Pin(num='51',name='P51',func=Pin.BIDIR,do_erc=True),
Pin(num='61',name='P61',func=Pin.BIDIR,do_erc=True),
Pin(num='71',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='81',name='P81',func=Pin.BIDIR,do_erc=True),
Pin(num='91',name='P91',func=Pin.BIDIR,do_erc=True),
Pin(num='12',name='P12',func=Pin.BIDIR,do_erc=True),
Pin(num='22',name='P22',func=Pin.BIDIR,do_erc=True),
Pin(num='32',name='P32',func=Pin.BIDIR,do_erc=True),
Pin(num='42',name='P42',func=Pin.BIDIR,do_erc=True),
Pin(num='52',name='P52',func=Pin.BIDIR,do_erc=True),
Pin(num='62',name='P62',func=Pin.BIDIR,do_erc=True),
Pin(num='72',name='P72',func=Pin.BIDIR,do_erc=True),
Pin(num='82',name='P82',func=Pin.BIDIR,do_erc=True),
Pin(num='92',name='P92',func=Pin.BIDIR,do_erc=True),
Pin(num='13',name='P13',func=Pin.BIDIR,do_erc=True),
Pin(num='23',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='33',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='43',name='P43',func=Pin.BIDIR,do_erc=True),
Pin(num='53',name='VCCIO',func=Pin.PWRIN,do_erc=True),
Pin(num='63',name='P63',func=Pin.BIDIR,do_erc=True),
Pin(num='73',name='P73',func=Pin.BIDIR,do_erc=True),
Pin(num='83',name='P83',func=Pin.BIDIR,do_erc=True),
Pin(num='93',name='P93',func=Pin.BIDIR,do_erc=True),
Pin(num='14',name='P14',func=Pin.BIDIR,do_erc=True),
Pin(num='24',name='I/O/GCK1',func=Pin.BIDIR,do_erc=True),
Pin(num='34',name='P34',func=Pin.BIDIR,do_erc=True),
Pin(num='44',name='P44',func=Pin.BIDIR,do_erc=True),
Pin(num='54',name='P54',func=Pin.BIDIR,do_erc=True),
Pin(num='64',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='74',name='P74',func=Pin.BIDIR,do_erc=True),
Pin(num='84',name='P84',func=Pin.BIDIR,do_erc=True),
Pin(num='94',name='P94',func=Pin.BIDIR,do_erc=True),
Pin(num='15',name='P15',func=Pin.BIDIR,do_erc=True),
Pin(num='25',name='I/O/GCK2',func=Pin.BIDIR,do_erc=True),
Pin(num='35',name='P35',func=Pin.BIDIR,do_erc=True),
Pin(num='45',name='P45',func=Pin.BIDIR,do_erc=True),
Pin(num='55',name='P55',func=Pin.BIDIR,do_erc=True),
Pin(num='65',name='P65',func=Pin.BIDIR,do_erc=True),
Pin(num='75',name='P75',func=Pin.BIDIR,do_erc=True),
Pin(num='85',name='TDO',func=Pin.OUTPUT,do_erc=True),
Pin(num='95',name='P95',func=Pin.BIDIR,do_erc=True),
Pin(num='16',name='P16',func=Pin.BIDIR,do_erc=True),
Pin(num='26',name='P26',func=Pin.BIDIR,do_erc=True),
Pin(num='36',name='P36',func=Pin.BIDIR,do_erc=True),
Pin(num='46',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='56',name='P56',func=Pin.BIDIR,do_erc=True),
Pin(num='66',name='P66',func=Pin.BIDIR,do_erc=True),
Pin(num='76',name='P76',func=Pin.BIDIR,do_erc=True),
Pin(num='86',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='96',name='P96',func=Pin.BIDIR,do_erc=True),
Pin(num='17',name='P17',func=Pin.BIDIR,do_erc=True),
Pin(num='27',name='P27',func=Pin.BIDIR,do_erc=True),
Pin(num='37',name='P37',func=Pin.BIDIR,do_erc=True),
Pin(num='47',name='TDI',do_erc=True),
Pin(num='57',name='P57',func=Pin.BIDIR,do_erc=True),
Pin(num='67',name='P67',func=Pin.BIDIR,do_erc=True),
Pin(num='77',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='87',name='P87',func=Pin.BIDIR,do_erc=True),
Pin(num='97',name='P97',func=Pin.BIDIR,do_erc=True),
Pin(num='18',name='P18',func=Pin.BIDIR,do_erc=True),
Pin(num='28',name='VCCIO',func=Pin.PWRIN,do_erc=True),
Pin(num='38',name='P38',func=Pin.BIDIR,do_erc=True),
Pin(num='48',name='P48',func=Pin.BIDIR,do_erc=True),
Pin(num='58',name='P58',func=Pin.BIDIR,do_erc=True),
Pin(num='68',name='P68',func=Pin.BIDIR,do_erc=True),
Pin(num='78',name='P78',func=Pin.BIDIR,do_erc=True),
Pin(num='88',name='P88',func=Pin.BIDIR,do_erc=True),
Pin(num='98',name='P98',func=Pin.BIDIR,do_erc=True),
Pin(num='19',name='P19',func=Pin.BIDIR,do_erc=True),
Pin(num='29',name='I/O/GCK3',func=Pin.BIDIR,do_erc=True),
Pin(num='39',name='P39',func=Pin.BIDIR,do_erc=True),
Pin(num='49',name='TMS',do_erc=True),
Pin(num='59',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='69',name='P69',func=Pin.BIDIR,do_erc=True),
Pin(num='79',name='P79',func=Pin.BIDIR,do_erc=True),
Pin(num='89',name='P89',func=Pin.BIDIR,do_erc=True),
Pin(num='99',name='P99',func=Pin.BIDIR,do_erc=True),
Pin(num='100',name='VCC',func=Pin.PWRIN,do_erc=True)]),
Part(name='XC95144PQ100',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='XC95144XL-TQ100',dest=TEMPLATE,tool=SKIDL,keywords='CPLD',description='CPLD, 144 macrocells, 3200 usable gates',ref_prefix='U',num_units=1,fplist=['TQFP*14x14mm*Pitch0.5mm*'],do_erc=True,pins=[
Pin(num='1',name='I/O/GTS3',func=Pin.BIDIR,do_erc=True),
Pin(num='2',name='I/O/GTS4',func=Pin.BIDIR,do_erc=True),
Pin(num='3',name='I/O/GTS1',func=Pin.BIDIR,do_erc=True),
Pin(num='4',name='I/O/GTS2',func=Pin.BIDIR,do_erc=True),
Pin(num='5',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='6',name='P6',func=Pin.BIDIR,do_erc=True),
Pin(num='7',name='P7',func=Pin.BIDIR,do_erc=True),
Pin(num='8',name='P8',func=Pin.BIDIR,do_erc=True),
Pin(num='9',name='P9',func=Pin.BIDIR,do_erc=True),
Pin(num='10',name='P10',func=Pin.BIDIR,do_erc=True),
Pin(num='20',name='P20',func=Pin.BIDIR,do_erc=True),
Pin(num='30',name='P30',func=Pin.BIDIR,do_erc=True),
Pin(num='40',name='P40',func=Pin.BIDIR,do_erc=True),
Pin(num='50',name='P50',func=Pin.BIDIR,do_erc=True),
Pin(num='60',name='P60',func=Pin.BIDIR,do_erc=True),
Pin(num='70',name='P70',func=Pin.BIDIR,do_erc=True),
Pin(num='80',name='P80',func=Pin.BIDIR,do_erc=True),
Pin(num='90',name='P90',func=Pin.BIDIR,do_erc=True),
Pin(num='11',name='P11',func=Pin.BIDIR,do_erc=True),
Pin(num='21',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='31',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='41',name='P41',func=Pin.BIDIR,do_erc=True),
Pin(num='51',name='VCCIO',func=Pin.PWRIN,do_erc=True),
Pin(num='61',name='P61',func=Pin.BIDIR,do_erc=True),
Pin(num='71',name='P71',func=Pin.BIDIR,do_erc=True),
Pin(num='81',name='P81',func=Pin.BIDIR,do_erc=True),
Pin(num='91',name='P91',func=Pin.BIDIR,do_erc=True),
Pin(num='12',name='P12',func=Pin.BIDIR,do_erc=True),
Pin(num='22',name='I/O/GCK1',func=Pin.BIDIR,do_erc=True),
Pin(num='32',name='P32',func=Pin.BIDIR,do_erc=True),
Pin(num='42',name='P42',func=Pin.BIDIR,do_erc=True),
Pin(num='52',name='P52',func=Pin.BIDIR,do_erc=True),
Pin(num='62',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='72',name='P72',func=Pin.BIDIR,do_erc=True),
Pin(num='82',name='P82',func=Pin.BIDIR,do_erc=True),
Pin(num='92',name='P92',func=Pin.BIDIR,do_erc=True),
Pin(num='13',name='P13',func=Pin.BIDIR,do_erc=True),
Pin(num='23',name='I/O/GCK2',func=Pin.BIDIR,do_erc=True),
Pin(num='33',name='P33',func=Pin.BIDIR,do_erc=True),
Pin(num='43',name='P43',func=Pin.BIDIR,do_erc=True),
Pin(num='53',name='P53',func=Pin.BIDIR,do_erc=True),
Pin(num='63',name='P63',func=Pin.BIDIR,do_erc=True),
Pin(num='73',name='P73',func=Pin.BIDIR,do_erc=True),
Pin(num='83',name='TDO',func=Pin.OUTPUT,do_erc=True),
Pin(num='93',name='P93',func=Pin.BIDIR,do_erc=True),
Pin(num='14',name='P14',func=Pin.BIDIR,do_erc=True),
Pin(num='24',name='P24',func=Pin.BIDIR,do_erc=True),
Pin(num='34',name='P34',func=Pin.BIDIR,do_erc=True),
Pin(num='44',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='54',name='P54',func=Pin.BIDIR,do_erc=True),
Pin(num='64',name='P64',func=Pin.BIDIR,do_erc=True),
Pin(num='74',name='P74',func=Pin.BIDIR,do_erc=True),
Pin(num='84',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='94',name='P94',func=Pin.BIDIR,do_erc=True),
Pin(num='15',name='P15',func=Pin.BIDIR,do_erc=True),
Pin(num='25',name='P25',func=Pin.BIDIR,do_erc=True),
Pin(num='35',name='P35',func=Pin.BIDIR,do_erc=True),
Pin(num='45',name='TDI',do_erc=True),
Pin(num='55',name='P55',func=Pin.BIDIR,do_erc=True),
Pin(num='65',name='P65',func=Pin.BIDIR,do_erc=True),
Pin(num='75',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='85',name='P85',func=Pin.BIDIR,do_erc=True),
Pin(num='95',name='P95',func=Pin.BIDIR,do_erc=True),
Pin(num='16',name='P16',func=Pin.BIDIR,do_erc=True),
Pin(num='26',name='VCCIO',func=Pin.PWRIN,do_erc=True),
Pin(num='36',name='P36',func=Pin.BIDIR,do_erc=True),
Pin(num='46',name='P46',func=Pin.BIDIR,do_erc=True),
Pin(num='56',name='P56',func=Pin.BIDIR,do_erc=True),
Pin(num='66',name='P66',func=Pin.BIDIR,do_erc=True),
Pin(num='76',name='P76',func=Pin.BIDIR,do_erc=True),
Pin(num='86',name='P86',func=Pin.BIDIR,do_erc=True),
Pin(num='96',name='P96',func=Pin.BIDIR,do_erc=True),
Pin(num='17',name='P17',func=Pin.BIDIR,do_erc=True),
Pin(num='27',name='I/O/GCK3',func=Pin.BIDIR,do_erc=True),
Pin(num='37',name='P37',func=Pin.BIDIR,do_erc=True),
Pin(num='47',name='TMS',do_erc=True),
Pin(num='57',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='67',name='P67',func=Pin.BIDIR,do_erc=True),
Pin(num='77',name='P77',func=Pin.BIDIR,do_erc=True),
Pin(num='87',name='P87',func=Pin.BIDIR,do_erc=True),
Pin(num='97',name='P97',func=Pin.BIDIR,do_erc=True),
Pin(num='18',name='P18',func=Pin.BIDIR,do_erc=True),
Pin(num='28',name='P28',func=Pin.BIDIR,do_erc=True),
Pin(num='38',name='VCCIO',func=Pin.PWRIN,do_erc=True),
Pin(num='48',name='TCK',do_erc=True),
Pin(num='58',name='P58',func=Pin.BIDIR,do_erc=True),
Pin(num='68',name='P68',func=Pin.BIDIR,do_erc=True),
Pin(num='78',name='P78',func=Pin.BIDIR,do_erc=True),
Pin(num='88',name='VCCIO',func=Pin.PWRIN,do_erc=True),
Pin(num='98',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='19',name='P19',func=Pin.BIDIR,do_erc=True),
Pin(num='29',name='P29',func=Pin.BIDIR,do_erc=True),
Pin(num='39',name='P39',func=Pin.BIDIR,do_erc=True),
Pin(num='49',name='P49',func=Pin.BIDIR,do_erc=True),
Pin(num='59',name='P59',func=Pin.BIDIR,do_erc=True),
Pin(num='69',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='79',name='P79',func=Pin.BIDIR,do_erc=True),
Pin(num='89',name='P89',func=Pin.BIDIR,do_erc=True),
Pin(num='99',name='I/O/GSR',func=Pin.BIDIR,do_erc=True),
Pin(num='100',name='GND',func=Pin.PWRIN,do_erc=True)]),
Part(name='XC95144XL-TQ144',dest=TEMPLATE,tool=SKIDL,keywords='CPLD',description='CPLD, 144 macrocells, 3200 usable gates',ref_prefix='U',num_units=1,fplist=['TQFP*20x20mm*Pitch0.5mm*'],do_erc=True,pins=[
Pin(num='1',name='VCCIO',func=Pin.PWRIN,do_erc=True),
Pin(num='2',name='I/O/GTS3',func=Pin.BIDIR,do_erc=True),
Pin(num='3',name='I/O/GTS4',func=Pin.BIDIR,do_erc=True),
Pin(num='4',name='P4',func=Pin.BIDIR,do_erc=True),
Pin(num='5',name='I/O/GTS1',func=Pin.BIDIR,do_erc=True),
Pin(num='6',name='I/O/GTS2',func=Pin.BIDIR,do_erc=True),
Pin(num='7',name='P7',func=Pin.BIDIR,do_erc=True),
Pin(num='8',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='9',name='P9',func=Pin.BIDIR,do_erc=True),
Pin(num='10',name='P10',func=Pin.BIDIR,do_erc=True),
Pin(num='20',name='P20',func=Pin.BIDIR,do_erc=True),
Pin(num='30',name='I/O/GCK1',func=Pin.BIDIR,do_erc=True),
Pin(num='40',name='P40',func=Pin.BIDIR,do_erc=True),
Pin(num='50',name='P50',func=Pin.BIDIR,do_erc=True),
Pin(num='60',name='P60',func=Pin.BIDIR,do_erc=True),
Pin(num='70',name='P70',func=Pin.BIDIR,do_erc=True),
Pin(num='80',name='P80',func=Pin.BIDIR,do_erc=True),
Pin(num='90',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='11',name='P11',func=Pin.BIDIR,do_erc=True),
Pin(num='21',name='P21',func=Pin.BIDIR,do_erc=True),
Pin(num='31',name='P31',func=Pin.BIDIR,do_erc=True),
Pin(num='41',name='P41',func=Pin.BIDIR,do_erc=True),
Pin(num='51',name='P51',func=Pin.BIDIR,do_erc=True),
Pin(num='61',name='P61',func=Pin.BIDIR,do_erc=True),
Pin(num='71',name='P71',func=Pin.BIDIR,do_erc=True),
Pin(num='81',name='P81',func=Pin.BIDIR,do_erc=True),
Pin(num='91',name='P91',func=Pin.BIDIR,do_erc=True),
Pin(num='12',name='P12',func=Pin.BIDIR,do_erc=True),
Pin(num='22',name='P22',func=Pin.BIDIR,do_erc=True),
Pin(num='32',name='I/O/GCK2',func=Pin.BIDIR,do_erc=True),
Pin(num='42',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='52',name='P52',func=Pin.BIDIR,do_erc=True),
Pin(num='62',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='72',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='82',name='P82',func=Pin.BIDIR,do_erc=True),
Pin(num='92',name='P92',func=Pin.BIDIR,do_erc=True),
Pin(num='13',name='P13',func=Pin.BIDIR,do_erc=True),
Pin(num='23',name='P23',func=Pin.BIDIR,do_erc=True),
Pin(num='33',name='P33',func=Pin.BIDIR,do_erc=True),
Pin(num='43',name='P43',func=Pin.BIDIR,do_erc=True),
Pin(num='53',name='P53',func=Pin.BIDIR,do_erc=True),
Pin(num='63',name='TDI',func=Pin.BIDIR,do_erc=True),
Pin(num='73',name='VCCIO',func=Pin.PWRIN,do_erc=True),
Pin(num='83',name='P83',func=Pin.BIDIR,do_erc=True),
Pin(num='93',name='P93',func=Pin.BIDIR,do_erc=True),
Pin(num='14',name='P14',func=Pin.BIDIR,do_erc=True),
Pin(num='24',name='P24',func=Pin.BIDIR,do_erc=True),
Pin(num='34',name='P34',func=Pin.BIDIR,do_erc=True),
Pin(num='44',name='P44',func=Pin.BIDIR,do_erc=True),
Pin(num='54',name='P54',func=Pin.BIDIR,do_erc=True),
Pin(num='64',name='P64',func=Pin.BIDIR,do_erc=True),
Pin(num='74',name='P74',func=Pin.BIDIR,do_erc=True),
Pin(num='84',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='94',name='P94',func=Pin.BIDIR,do_erc=True),
Pin(num='15',name='P15',func=Pin.BIDIR,do_erc=True),
Pin(num='25',name='P25',func=Pin.BIDIR,do_erc=True),
Pin(num='35',name='P35',func=Pin.BIDIR,do_erc=True),
Pin(num='45',name='P45',func=Pin.BIDIR,do_erc=True),
Pin(num='55',name='VCCIO',func=Pin.PWRIN,do_erc=True),
Pin(num='65',name='TMS',func=Pin.BIDIR,do_erc=True),
Pin(num='75',name='P75',func=Pin.BIDIR,do_erc=True),
Pin(num='85',name='P85',func=Pin.BIDIR,do_erc=True),
Pin(num='95',name='P95',func=Pin.BIDIR,do_erc=True),
Pin(num='16',name='P16',func=Pin.BIDIR,do_erc=True),
Pin(num='26',name='P26',func=Pin.BIDIR,do_erc=True),
Pin(num='36',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='46',name='P46',func=Pin.BIDIR,do_erc=True),
Pin(num='56',name='P56',func=Pin.BIDIR,do_erc=True),
Pin(num='66',name='P66',func=Pin.BIDIR,do_erc=True),
Pin(num='76',name='P76',func=Pin.BIDIR,do_erc=True),
Pin(num='86',name='P86',func=Pin.BIDIR,do_erc=True),
Pin(num='96',name='P96',func=Pin.BIDIR,do_erc=True),
Pin(num='17',name='P17',func=Pin.BIDIR,do_erc=True),
Pin(num='27',name='P27',func=Pin.BIDIR,do_erc=True),
Pin(num='37',name='VCCIO',func=Pin.PWRIN,do_erc=True),
Pin(num='47',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='57',name='P57',func=Pin.BIDIR,do_erc=True),
Pin(num='67',name='TCK',func=Pin.BIDIR,do_erc=True),
Pin(num='77',name='P77',func=Pin.BIDIR,do_erc=True),
Pin(num='87',name='P87',func=Pin.BIDIR,do_erc=True),
Pin(num='97',name='P97',func=Pin.BIDIR,do_erc=True),
Pin(num='18',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='28',name='P28',func=Pin.BIDIR,do_erc=True),
Pin(num='38',name='I/O/GCK3',func=Pin.BIDIR,do_erc=True),
Pin(num='48',name='P48',func=Pin.BIDIR,do_erc=True),
Pin(num='58',name='P58',func=Pin.BIDIR,do_erc=True),
Pin(num='68',name='P68',func=Pin.BIDIR,do_erc=True),
Pin(num='78',name='P78',func=Pin.BIDIR,do_erc=True),
Pin(num='88',name='P88',func=Pin.BIDIR,do_erc=True),
Pin(num='98',name='P98',func=Pin.BIDIR,do_erc=True),
Pin(num='19',name='P19',func=Pin.BIDIR,do_erc=True),
Pin(num='29',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='39',name='P39',func=Pin.BIDIR,do_erc=True),
Pin(num='49',name='P49',func=Pin.BIDIR,do_erc=True),
Pin(num='59',name='P59',func=Pin.BIDIR,do_erc=True),
Pin(num='69',name='P69',func=Pin.BIDIR,do_erc=True),
Pin(num='79',name='P79',func=Pin.BIDIR,do_erc=True),
Pin(num='89',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='99',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='100',name='P100',func=Pin.BIDIR,do_erc=True),
Pin(num='110',name='P110',func=Pin.BIDIR,do_erc=True),
Pin(num='120',name='P120',func=Pin.BIDIR,do_erc=True),
Pin(num='130',name='P130',func=Pin.BIDIR,do_erc=True),
Pin(num='140',name='P140',func=Pin.BIDIR,do_erc=True),
Pin(num='101',name='P101',func=Pin.BIDIR,do_erc=True),
Pin(num='111',name='P111',func=Pin.BIDIR,do_erc=True),
Pin(num='121',name='P121',func=Pin.BIDIR,do_erc=True),
Pin(num='131',name='P131',func=Pin.BIDIR,do_erc=True),
Pin(num='141',name='VCCINT',func=Pin.PWRIN,do_erc=True),
Pin(num='102',name='P102',func=Pin.BIDIR,do_erc=True),
Pin(num='112',name='P112',func=Pin.BIDIR,do_erc=True),
Pin(num='122',name='TDO',func=Pin.BIDIR,do_erc=True),
Pin(num='132',name='P132',func=Pin.BIDIR,do_erc=True),
Pin(num='142',name='P142',func=Pin.BIDIR,do_erc=True),
Pin(num='103',name='P103',func=Pin.BIDIR,do_erc=True),
Pin(num='113',name='P113',func=Pin.BIDIR,do_erc=True),
Pin(num='123',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='133',name='P133',func=Pin.BIDIR,do_erc=True),
Pin(num='143',name='I/O/GSR',func=Pin.BIDIR,do_erc=True),
Pin(num='104',name='P104',func=Pin.BIDIR,do_erc=True),
Pin(num='114',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='124',name='P124',func=Pin.BIDIR,do_erc=True),
Pin(num='134',name='P134',func=Pin.BIDIR,do_erc=True),
Pin(num='144',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='105',name='P105',func=Pin.BIDIR,do_erc=True),
Pin(num='115',name='P115',func=Pin.BIDIR,do_erc=True),
Pin(num='125',name='P125',func=Pin.BIDIR,do_erc=True),
Pin(num='135',name='P135',func=Pin.BIDIR,do_erc=True),
Pin(num='106',name='P106',func=Pin.BIDIR,do_erc=True),
Pin(num='116',name='P116',func=Pin.BIDIR,do_erc=True),
Pin(num='126',name='P126',func=Pin.BIDIR,do_erc=True),
Pin(num='136',name='P136',func=Pin.BIDIR,do_erc=True),
Pin(num='107',name='P107',func=Pin.BIDIR,do_erc=True),
Pin(num='117',name='P117',func=Pin.BIDIR,do_erc=True),
Pin(num='127',name='VCCIO',func=Pin.PWRIN,do_erc=True),
Pin(num='137',name='P137',func=Pin.BIDIR,do_erc=True),
Pin(num='108',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='118',name='P118',func=Pin.BIDIR,do_erc=True),
Pin(num='128',name='P128',func=Pin.BIDIR,do_erc=True),
Pin(num='138',name='P138',func=Pin.BIDIR,do_erc=True),
Pin(num='109',name='VCCIO',func=Pin.PWRIN,do_erc=True),
Pin(num='119',name='P119',func=Pin.BIDIR,do_erc=True),
Pin(num='129',name='P129',func=Pin.BIDIR,do_erc=True),
Pin(num='139',name='P139',func=Pin.BIDIR,do_erc=True)]),
Part(name='XC9536PC44',dest=TEMPLATE,tool=SKIDL,ref_prefix='U',num_units=1,do_erc=True,pins=[
Pin(num='1',name='M1',func=Pin.BIDIR,do_erc=True),
Pin(num='2',name='M1',func=Pin.BIDIR,do_erc=True),
Pin(num='3',name='M2',func=Pin.BIDIR,do_erc=True),
Pin(num='4',name='M4',func=Pin.BIDIR,do_erc=True),
Pin(num='5',name='I/O/GCK1',func=Pin.BIDIR,do_erc=True),
Pin(num='6',name='I/O/GCK2',func=Pin.BIDIR,do_erc=True),
Pin(num='7',name='I/O/GCK3',func=Pin.BIDIR,do_erc=True),
Pin(num='8',name='M6',func=Pin.BIDIR,do_erc=True),
Pin(num='9',name='M8',func=Pin.BIDIR,do_erc=True),
Pin(num='10',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='20',name='M15',func=Pin.BIDIR,do_erc=True),
Pin(num='30',name='TDO',func=Pin.OUTPUT,do_erc=True),
Pin(num='40',name='I/O/GTS2',func=Pin.BIDIR,do_erc=True),
Pin(num='11',name='M9',func=Pin.BIDIR,do_erc=True),
Pin(num='21',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='31',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='41',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='12',name='M10',func=Pin.BIDIR,do_erc=True),
Pin(num='22',name='M16',func=Pin.BIDIR,do_erc=True),
Pin(num='32',name='VCCIO',func=Pin.PWRIN,do_erc=True),
Pin(num='42',name='I/O/GTS1',func=Pin.BIDIR,do_erc=True),
Pin(num='13',name='M11',func=Pin.BIDIR,do_erc=True),
Pin(num='23',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='33',name='M12',func=Pin.BIDIR,do_erc=True),
Pin(num='43',name='M4',func=Pin.BIDIR,do_erc=True),
Pin(num='14',name='M12',func=Pin.BIDIR,do_erc=True),
Pin(num='24',name='M17',func=Pin.BIDIR,do_erc=True),
Pin(num='34',name='M11',func=Pin.BIDIR,do_erc=True),
Pin(num='44',name='M2',func=Pin.BIDIR,do_erc=True),
Pin(num='15',name='TDI',do_erc=True),
Pin(num='25',name='M17',func=Pin.BIDIR,do_erc=True),
Pin(num='35',name='M10',func=Pin.BIDIR,do_erc=True),
Pin(num='16',name='TMS',do_erc=True),
Pin(num='26',name='M16',func=Pin.BIDIR,do_erc=True),
Pin(num='36',name='M9',func=Pin.BIDIR,do_erc=True),
Pin(num='17',name='TCK',do_erc=True),
Pin(num='27',name='M15',func=Pin.BIDIR,do_erc=True),
Pin(num='37',name='M8',func=Pin.BIDIR,do_erc=True),
Pin(num='18',name='M13',func=Pin.BIDIR,do_erc=True),
Pin(num='28',name='M14',func=Pin.BIDIR,do_erc=True),
Pin(num='38',name='M7',func=Pin.BIDIR,do_erc=True),
Pin(num='19',name='M14',func=Pin.BIDIR,do_erc=True),
Pin(num='29',name='M13',func=Pin.BIDIR,do_erc=True),
Pin(num='39',name='I/O/GSR',func=Pin.BIDIR,do_erc=True)]),
Part(name='XC9572XL-TQ100',dest=TEMPLATE,tool=SKIDL,keywords='CPLD',description='CPLD, 72 macrocells, 1600 usable gates',ref_prefix='U',num_units=1,fplist=['TQFP*14x14mm*Pitch0.5mm*'],do_erc=True,pins=[
Pin(num='1',name='I/O/GTS3',func=Pin.BIDIR,do_erc=True),
Pin(num='2',name='NC',func=Pin.NOCONNECT,do_erc=True),
Pin(num='3',name='I/O/GTS1',func=Pin.BIDIR,do_erc=True),
Pin(num='4',name='I/O/GTS2',func=Pin.BIDIR,do_erc=True),
Pin(num='5',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='6',name='P6',func=Pin.BIDIR,do_erc=True),
Pin(num='7',name='NC',func=Pin.NOCONNECT,do_erc=True),
Pin(num='8',name='P8',func=Pin.BIDIR,do_erc=True),
Pin(num='9',name='P9',func=Pin.BIDIR,do_erc=True),
Pin(num='10',name='P10',func=Pin.BIDIR,do_erc=True),
Pin(num='20',name='P20',func=Pin.BIDIR,do_erc=True),
Pin(num='30',name='P30',func=Pin.BIDIR,do_erc=True),
Pin(num='40',name='P40',func=Pin.BIDIR,do_erc=True),
Pin(num='50',name='P50',func=Pin.BIDIR,do_erc=True),
Pin(num='60',name='P60',func=Pin.BIDIR,do_erc=True),
Pin(num='70',name='P70',func=Pin.BIDIR,do_erc=True),
Pin(num='80',name='NC',func=Pin.NOCONNECT,do_erc=True),
Pin(num='90',name='P90',func=Pin.BIDIR,do_erc=True),
Pin(num='11',name='P11',func=Pin.BIDIR,do_erc=True),
Pin(num='21',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='31',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='41',name='P41',func=Pin.BIDIR,do_erc=True),
Pin(num='51',name='VCCIO',func=Pin.PWRIN,do_erc=True),
Pin(num='61',name='P61',func=Pin.BIDIR,do_erc=True),
Pin(num='71',name='P71',func=Pin.BIDIR,do_erc=True),
Pin(num='81',name='P81',func=Pin.BIDIR,do_erc=True),
Pin(num='91',name='P91',func=Pin.BIDIR,do_erc=True),
Pin(num='12',name='P12',func=Pin.BIDIR,do_erc=True),
Pin(num='22',name='I/O/GCK1',func=Pin.BIDIR,do_erc=True),
Pin(num='32',name='P32',func=Pin.BIDIR,do_erc=True),
Pin(num='42',name='P42',func=Pin.BIDIR,do_erc=True),
Pin(num='52',name='P52',func=Pin.BIDIR,do_erc=True),
Pin(num='62',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='72',name='P72',func=Pin.BIDIR,do_erc=True),
Pin(num='82',name='P82',func=Pin.BIDIR,do_erc=True),
Pin(num='92',name='P92',func=Pin.BIDIR,do_erc=True),
Pin(num='13',name='P13',func=Pin.BIDIR,do_erc=True),
Pin(num='23',name='I/O/GCK2',func=Pin.BIDIR,do_erc=True),
Pin(num='33',name='P33',func=Pin.BIDIR,do_erc=True),
Pin(num='43',name='NC',func=Pin.NOCONNECT,do_erc=True),
Pin(num='53',name='P53',func=Pin.BIDIR,do_erc=True),
Pin(num='63',name='P63',func=Pin.BIDIR,do_erc=True),
Pin(num='73',name='NC',func=Pin.NOCONNECT,do_erc=True),
Pin(num='83',name='TDO',func=Pin.OUTPUT,do_erc=True),
Pin(num='93',name='P93',func=Pin.BIDIR,do_erc=True),
Pin(num='14',name='P14',func=Pin.BIDIR,do_erc=True),
Pin(num='24',name='NC',func=Pin.NOCONNECT,do_erc=True),
Pin(num='34',name='NC',func=Pin.NOCONNECT,do_erc=True),
Pin(num='44',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='54',name='P54',func=Pin.BIDIR,do_erc=True),
Pin(num='64',name='P64',func=Pin.BIDIR,do_erc=True),
Pin(num='74',name='P74',func=Pin.BIDIR,do_erc=True),
Pin(num='84',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='94',name='P94',func=Pin.BIDIR,do_erc=True),
Pin(num='15',name='P15',func=Pin.BIDIR,do_erc=True),
Pin(num='25',name='P25',func=Pin.BIDIR,do_erc=True),
Pin(num='35',name='P35',func=Pin.BIDIR,do_erc=True),
Pin(num='45',name='TDI',do_erc=True),
Pin(num='55',name='P55',func=Pin.BIDIR,do_erc=True),
Pin(num='65',name='P65',func=Pin.BIDIR,do_erc=True),
Pin(num='75',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='85',name='P85',func=Pin.BIDIR,do_erc=True),
Pin(num='95',name='P95',func=Pin.BIDIR,do_erc=True),
Pin(num='16',name='P16',func=Pin.BIDIR,do_erc=True),
Pin(num='26',name='VCCIO',func=Pin.PWRIN,do_erc=True),
Pin(num='36',name='P36',func=Pin.BIDIR,do_erc=True),
Pin(num='46',name='NC',func=Pin.NOCONNECT,do_erc=True),
Pin(num='56',name='P56',func=Pin.BIDIR,do_erc=True),
Pin(num='66',name='P66',func=Pin.BIDIR,do_erc=True),
Pin(num='76',name='P76',func=Pin.BIDIR,do_erc=True),
Pin(num='86',name='P86',func=Pin.BIDIR,do_erc=True),
Pin(num='96',name='P96',func=Pin.BIDIR,do_erc=True),
Pin(num='17',name='P17',func=Pin.BIDIR,do_erc=True),
Pin(num='27',name='I/O/GCK3',func=Pin.BIDIR,do_erc=True),
Pin(num='37',name='P37',func=Pin.BIDIR,do_erc=True),
Pin(num='47',name='TMS',do_erc=True),
Pin(num='57',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='67',name='P67',func=Pin.BIDIR,do_erc=True),
Pin(num='77',name='P77',func=Pin.BIDIR,do_erc=True),
Pin(num='87',name='P87',func=Pin.BIDIR,do_erc=True),
Pin(num='97',name='P97',func=Pin.BIDIR,do_erc=True),
Pin(num='18',name='P18',func=Pin.BIDIR,do_erc=True),
Pin(num='28',name='P28',func=Pin.BIDIR,do_erc=True),
Pin(num='38',name='VCCIO',func=Pin.PWRIN,do_erc=True),
Pin(num='48',name='TCK',do_erc=True),
Pin(num='58',name='P58',func=Pin.BIDIR,do_erc=True),
Pin(num='68',name='P68',func=Pin.BIDIR,do_erc=True),
Pin(num='78',name='P78',func=Pin.BIDIR,do_erc=True),
Pin(num='88',name='VCCIO',func=Pin.PWRIN,do_erc=True),
Pin(num='98',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='19',name='NC',func=Pin.NOCONNECT,do_erc=True),
Pin(num='29',name='P29',func=Pin.BIDIR,do_erc=True),
Pin(num='39',name='P39',func=Pin.BIDIR,do_erc=True),
Pin(num='49',name='P49',func=Pin.BIDIR,do_erc=True),
Pin(num='59',name='P59',func=Pin.BIDIR,do_erc=True),
Pin(num='69',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='79',name='P79',func=Pin.BIDIR,do_erc=True),
Pin(num='89',name='P89',func=Pin.BIDIR,do_erc=True),
Pin(num='99',name='I/O/GSR',func=Pin.BIDIR,do_erc=True),
Pin(num='100',name='GND',func=Pin.PWRIN,do_erc=True)]),
Part(name='XCF08P',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='XCR3064-VQ100',dest=TEMPLATE,tool=SKIDL,description='Xilinx CoolRunner',ref_prefix='U',num_units=1,do_erc=True,pins=[
Pin(num='3',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='4',name='B8/TDI',func=Pin.PASSIVE,do_erc=True),
Pin(num='6',name='B9',func=Pin.PASSIVE,do_erc=True),
Pin(num='8',name='B10',func=Pin.PASSIVE,do_erc=True),
Pin(num='9',name='B11',func=Pin.PASSIVE,do_erc=True),
Pin(num='10',name='B12',func=Pin.PASSIVE,do_erc=True),
Pin(num='20',name='D4',func=Pin.PASSIVE,do_erc=True),
Pin(num='30',name='D9',func=Pin.PASSIVE,do_erc=True),
Pin(num='40',name='C15',func=Pin.PASSIVE,do_erc=True),
Pin(num='60',name='C2',func=Pin.PASSIVE,do_erc=True),
Pin(num='80',name='A4',func=Pin.PASSIVE,do_erc=True),
Pin(num='90',name='CLK0/IN0',do_erc=True),
Pin(num='11',name='PORT_EN',func=Pin.PASSIVE,do_erc=True),
Pin(num='21',name='D5',func=Pin.PASSIVE,do_erc=True),
Pin(num='31',name='D10',func=Pin.PASSIVE,do_erc=True),
Pin(num='41',name='C14',func=Pin.PASSIVE,do_erc=True),
Pin(num='51',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='61',name='C1',func=Pin.PASSIVE,do_erc=True),
Pin(num='71',name='A9',func=Pin.PASSIVE,do_erc=True),
Pin(num='81',name='A3',func=Pin.PASSIVE,do_erc=True),
Pin(num='91',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='12',name='B13',func=Pin.PASSIVE,do_erc=True),
Pin(num='32',name='D11',func=Pin.PASSIVE,do_erc=True),
Pin(num='42',name='C13',func=Pin.PASSIVE,do_erc=True),
Pin(num='52',name='C7',func=Pin.PASSIVE,do_erc=True),
Pin(num='62',name='C0/TCK',func=Pin.PASSIVE,do_erc=True),
Pin(num='82',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='92',name='B0',func=Pin.PASSIVE,do_erc=True),
Pin(num='13',name='B14',func=Pin.PASSIVE,do_erc=True),
Pin(num='23',name='D6',func=Pin.PASSIVE,do_erc=True),
Pin(num='33',name='D12',func=Pin.PASSIVE,do_erc=True),
Pin(num='43',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='63',name='A15',func=Pin.PASSIVE,do_erc=True),
Pin(num='73',name='A8/TDO',func=Pin.PASSIVE,do_erc=True),
Pin(num='83',name='A2',func=Pin.PASSIVE,do_erc=True),
Pin(num='93',name='B1',func=Pin.PASSIVE,do_erc=True),
Pin(num='14',name='B15',func=Pin.PASSIVE,do_erc=True),
Pin(num='34',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='44',name='C12',func=Pin.PASSIVE,do_erc=True),
Pin(num='54',name='C6',func=Pin.PASSIVE,do_erc=True),
Pin(num='64',name='A14',func=Pin.PASSIVE,do_erc=True),
Pin(num='74',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='84',name='A1',func=Pin.PASSIVE,do_erc=True),
Pin(num='94',name='B2',func=Pin.PASSIVE,do_erc=True),
Pin(num='15',name='D0/TMS',func=Pin.PASSIVE,do_erc=True),
Pin(num='25',name='D7',func=Pin.PASSIVE,do_erc=True),
Pin(num='35',name='D13',func=Pin.PASSIVE,do_erc=True),
Pin(num='45',name='C11',func=Pin.PASSIVE,do_erc=True),
Pin(num='65',name='A13',func=Pin.PASSIVE,do_erc=True),
Pin(num='75',name='A7',func=Pin.PASSIVE,do_erc=True),
Pin(num='85',name='A0',func=Pin.PASSIVE,do_erc=True),
Pin(num='95',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='16',name='D1',func=Pin.PASSIVE,do_erc=True),
Pin(num='26',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='36',name='D14',func=Pin.PASSIVE,do_erc=True),
Pin(num='46',name='C10',func=Pin.PASSIVE,do_erc=True),
Pin(num='56',name='C5',func=Pin.PASSIVE,do_erc=True),
Pin(num='66',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='76',name='A6',func=Pin.PASSIVE,do_erc=True),
Pin(num='86',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='96',name='B3',func=Pin.PASSIVE,do_erc=True),
Pin(num='17',name='D2',func=Pin.PASSIVE,do_erc=True),
Pin(num='37',name='D15',func=Pin.PASSIVE,do_erc=True),
Pin(num='47',name='C9',func=Pin.PASSIVE,do_erc=True),
Pin(num='57',name='C4',func=Pin.PASSIVE,do_erc=True),
Pin(num='67',name='A12',func=Pin.PASSIVE,do_erc=True),
Pin(num='87',name='CLK3/IN3',do_erc=True),
Pin(num='97',name='B4',func=Pin.PASSIVE,do_erc=True),
Pin(num='18',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='38',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='48',name='C8',func=Pin.PASSIVE,do_erc=True),
Pin(num='58',name='C3',func=Pin.PASSIVE,do_erc=True),
Pin(num='68',name='A11',func=Pin.PASSIVE,do_erc=True),
Pin(num='88',name='CLK2/IN2',do_erc=True),
Pin(num='98',name='B5',func=Pin.PASSIVE,do_erc=True),
Pin(num='19',name='D3',func=Pin.PASSIVE,do_erc=True),
Pin(num='29',name='D8',func=Pin.PASSIVE,do_erc=True),
Pin(num='39',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='59',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='69',name='A10',func=Pin.PASSIVE,do_erc=True),
Pin(num='79',name='A5',func=Pin.PASSIVE,do_erc=True),
Pin(num='89',name='CLK1/IN1',do_erc=True),
Pin(num='99',name='B6',func=Pin.PASSIVE,do_erc=True),
Pin(num='100',name='B7',func=Pin.PASSIVE,do_erc=True)]),
Part(name='XCR3064-VQ44',dest=TEMPLATE,tool=SKIDL,description='Xilinx CoolRunner',ref_prefix='U',num_units=1,do_erc=True,pins=[
Pin(num='1',name='TDI',func=Pin.PASSIVE,do_erc=True),
Pin(num='2',name='B9',func=Pin.PASSIVE,do_erc=True),
Pin(num='3',name='B10',func=Pin.PASSIVE,do_erc=True),
Pin(num='4',name='PORT_EN',func=Pin.PASSIVE,do_erc=True),
Pin(num='5',name='B13',func=Pin.PASSIVE,do_erc=True),
Pin(num='6',name='B14',func=Pin.PASSIVE,do_erc=True),
Pin(num='7',name='TMS',func=Pin.PASSIVE,do_erc=True),
Pin(num='8',name='D1',func=Pin.PASSIVE,do_erc=True),
Pin(num='9',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='10',name='D3',func=Pin.PASSIVE,do_erc=True),
Pin(num='20',name='C10',func=Pin.PASSIVE,do_erc=True),
Pin(num='30',name='A10',func=Pin.PASSIVE,do_erc=True),
Pin(num='40',name='CLC0/IN0',do_erc=True),
Pin(num='11',name='D4',func=Pin.PASSIVE,do_erc=True),
Pin(num='21',name='C9',func=Pin.PASSIVE,do_erc=True),
Pin(num='31',name='A9',func=Pin.PASSIVE,do_erc=True),
Pin(num='41',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='12',name='D8',func=Pin.PASSIVE,do_erc=True),
Pin(num='22',name='C8',func=Pin.PASSIVE,do_erc=True),
Pin(num='32',name='TDO',func=Pin.PASSIVE,do_erc=True),
Pin(num='42',name='B0',func=Pin.PASSIVE,do_erc=True),
Pin(num='13',name='D9',func=Pin.PASSIVE,do_erc=True),
Pin(num='23',name='C3',func=Pin.PASSIVE,do_erc=True),
Pin(num='33',name='A7',func=Pin.PASSIVE,do_erc=True),
Pin(num='43',name='B1',func=Pin.PASSIVE,do_erc=True),
Pin(num='14',name='D10',func=Pin.PASSIVE,do_erc=True),
Pin(num='24',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='34',name='A1',func=Pin.PASSIVE,do_erc=True),
Pin(num='44',name='B2',func=Pin.PASSIVE,do_erc=True),
Pin(num='15',name='D11',func=Pin.PASSIVE,do_erc=True),
Pin(num='25',name='C1',func=Pin.PASSIVE,do_erc=True),
Pin(num='35',name='A0',func=Pin.PASSIVE,do_erc=True),
Pin(num='16',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='26',name='TCK',func=Pin.PASSIVE,do_erc=True),
Pin(num='36',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='17',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='27',name='A14',func=Pin.PASSIVE,do_erc=True),
Pin(num='37',name='CLK3/IN3',do_erc=True),
Pin(num='18',name='C12',func=Pin.PASSIVE,do_erc=True),
Pin(num='28',name='A13',func=Pin.PASSIVE,do_erc=True),
Pin(num='38',name='CLK2/IN2',do_erc=True),
Pin(num='19',name='C11',func=Pin.PASSIVE,do_erc=True),
Pin(num='29',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='39',name='CLK1/IN1',do_erc=True)]),
Part(name='XCR3128-VQ100',dest=TEMPLATE,tool=SKIDL,description='Xilinx CoolRunner',ref_prefix='U',num_units=1,do_erc=True,pins=[
Pin(num='1',name='E1',func=Pin.PASSIVE,do_erc=True),
Pin(num='2',name='E0',func=Pin.PASSIVE,do_erc=True),
Pin(num='3',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='4',name='F1/TDI',func=Pin.PASSIVE,do_erc=True),
Pin(num='5',name='F2',func=Pin.PASSIVE,do_erc=True),
Pin(num='6',name='F3',func=Pin.PASSIVE,do_erc=True),
Pin(num='7',name='F4',func=Pin.PASSIVE,do_erc=True),
Pin(num='8',name='F5',func=Pin.PASSIVE,do_erc=True),
Pin(num='9',name='F6',func=Pin.PASSIVE,do_erc=True),
Pin(num='10',name='F10',func=Pin.PASSIVE,do_erc=True),
Pin(num='20',name='H6',func=Pin.PASSIVE,do_erc=True),
Pin(num='30',name='G10',func=Pin.PASSIVE,do_erc=True),
Pin(num='40',name='D1',func=Pin.PASSIVE,do_erc=True),
Pin(num='50',name='D13',func=Pin.PASSIVE,do_erc=True),
Pin(num='60',name='C3',func=Pin.PASSIVE,do_erc=True),
Pin(num='70',name='A4',func=Pin.PASSIVE,do_erc=True),
Pin(num='80',name='B5',func=Pin.PASSIVE,do_erc=True),
Pin(num='90',name='CLK0/IN0',do_erc=True),
Pin(num='11',name='PORT_EN',func=Pin.PASSIVE,do_erc=True),
Pin(num='21',name='H10',func=Pin.PASSIVE,do_erc=True),
Pin(num='31',name='G6',func=Pin.PASSIVE,do_erc=True),
Pin(num='41',name='D2',func=Pin.PASSIVE,do_erc=True),
Pin(num='51',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='61',name='C2',func=Pin.PASSIVE,do_erc=True),
Pin(num='71',name='A3',func=Pin.PASSIVE,do_erc=True),
Pin(num='81',name='B6',func=Pin.PASSIVE,do_erc=True),
Pin(num='91',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='12',name='F13',func=Pin.PASSIVE,do_erc=True),
Pin(num='22',name='H11',func=Pin.PASSIVE,do_erc=True),
Pin(num='32',name='G5',func=Pin.PASSIVE,do_erc=True),
Pin(num='42',name='D3',func=Pin.PASSIVE,do_erc=True),
Pin(num='52',name='C14',func=Pin.PASSIVE,do_erc=True),
Pin(num='62',name='C1/TCK',func=Pin.PASSIVE,do_erc=True),
Pin(num='72',name='A2',func=Pin.PASSIVE,do_erc=True),
Pin(num='82',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='92',name='E14',func=Pin.PASSIVE,do_erc=True),
Pin(num='13',name='F14',func=Pin.PASSIVE,do_erc=True),
Pin(num='23',name='H12',func=Pin.PASSIVE,do_erc=True),
Pin(num='33',name='G4',func=Pin.PASSIVE,do_erc=True),
Pin(num='43',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='53',name='C13',func=Pin.PASSIVE,do_erc=True),
Pin(num='63',name='A14',func=Pin.PASSIVE,do_erc=True),
Pin(num='73',name='A1/TDO',func=Pin.PASSIVE,do_erc=True),
Pin(num='83',name='B10',func=Pin.PASSIVE,do_erc=True),
Pin(num='93',name='E13',func=Pin.PASSIVE,do_erc=True),
Pin(num='14',name='F15',func=Pin.PASSIVE,do_erc=True),
Pin(num='24',name='H13',func=Pin.PASSIVE,do_erc=True),
Pin(num='34',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='44',name='D4',func=Pin.PASSIVE,do_erc=True),
Pin(num='54',name='C12',func=Pin.PASSIVE,do_erc=True),
Pin(num='64',name='A13',func=Pin.PASSIVE,do_erc=True),
Pin(num='74',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='84',name='B11',func=Pin.PASSIVE,do_erc=True),
Pin(num='94',name='E12',func=Pin.PASSIVE,do_erc=True),
Pin(num='15',name='H1/TMS',func=Pin.PASSIVE,do_erc=True),
Pin(num='25',name='H14',func=Pin.PASSIVE,do_erc=True),
Pin(num='35',name='G3',func=Pin.PASSIVE,do_erc=True),
Pin(num='45',name='D5',func=Pin.PASSIVE,do_erc=True),
Pin(num='55',name='C11',func=Pin.PASSIVE,do_erc=True),
Pin(num='65',name='A12',func=Pin.PASSIVE,do_erc=True),
Pin(num='75',name='B0',func=Pin.PASSIVE,do_erc=True),
Pin(num='85',name='B12',func=Pin.PASSIVE,do_erc=True),
Pin(num='95',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='16',name='H2',func=Pin.PASSIVE,do_erc=True),
Pin(num='26',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='36',name='G2',func=Pin.PASSIVE,do_erc=True),
Pin(num='46',name='D6',func=Pin.PASSIVE,do_erc=True),
Pin(num='56',name='C10',func=Pin.PASSIVE,do_erc=True),
Pin(num='66',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='76',name='B1',func=Pin.PASSIVE,do_erc=True),
Pin(num='86',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='96',name='E6',func=Pin.PASSIVE,do_erc=True),
Pin(num='17',name='H3',func=Pin.PASSIVE,do_erc=True),
Pin(num='27',name='G13',func=Pin.PASSIVE,do_erc=True),
Pin(num='37',name='G1',func=Pin.PASSIVE,do_erc=True),
Pin(num='47',name='D10',func=Pin.PASSIVE,do_erc=True),
Pin(num='57',name='C6',func=Pin.PASSIVE,do_erc=True),
Pin(num='67',name='A10',func=Pin.PASSIVE,do_erc=True),
Pin(num='77',name='B2',func=Pin.PASSIVE,do_erc=True),
Pin(num='87',name='CLK3/IN3',do_erc=True),
Pin(num='97',name='E5',func=Pin.PASSIVE,do_erc=True),
Pin(num='18',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='28',name='G12',func=Pin.PASSIVE,do_erc=True),
Pin(num='38',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='48',name='D11',func=Pin.PASSIVE,do_erc=True),
Pin(num='58',name='C5',func=Pin.PASSIVE,do_erc=True),
Pin(num='68',name='A6',func=Pin.PASSIVE,do_erc=True),
Pin(num='78',name='B3',func=Pin.PASSIVE,do_erc=True),
Pin(num='88',name='CLK2/IN2',do_erc=True),
Pin(num='98',name='E4',func=Pin.PASSIVE,do_erc=True),
Pin(num='19',name='H5',func=Pin.PASSIVE,do_erc=True),
Pin(num='29',name='G11',func=Pin.PASSIVE,do_erc=True),
Pin(num='39',name='VCC',func=Pin.PWRIN,do_erc=True),
Pin(num='49',name='D12',func=Pin.PASSIVE,do_erc=True),
Pin(num='59',name='GND',func=Pin.PWRIN,do_erc=True),
Pin(num='69',name='A5',func=Pin.PASSIVE,do_erc=True),
Pin(num='79',name='B4',func=Pin.PASSIVE,do_erc=True),
Pin(num='89',name='CLK1/IN1',do_erc=True),
Pin(num='99',name='E3',func=Pin.PASSIVE,do_erc=True),
Pin(num='100',name='E2',func=Pin.PASSIVE,do_erc=True)]),
Part(name='XCR3256-TQ144',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='XCV150_BG352',dest=TEMPLATE,tool=SKIDL,do_erc=True)])
|
mpi4jax/_src/collective_ops/alltoall.py | Thenerdstation/mpi4jax | 122 | 11122943 | <filename>mpi4jax/_src/collective_ops/alltoall.py
import numpy as _np
from mpi4py import MPI as _MPI
from jax import abstract_arrays, core
from jax.core import Primitive
from jax.interpreters import xla
from jax.lax import create_token
from jax.lib import xla_client
from ..utils import (
HashableMPIType,
default_primitive_impl,
to_dtype_handle,
to_mpi_handle,
unpack_hashable,
wrap_as_hashable,
xla_constant_intc,
xla_constant_uintptr,
)
from ..decorators import translation_rule_cpu, translation_rule_gpu
from ..validation import enforce_types
from ..comm import get_default_comm
from ..jax_compat import Tracer, Token
# The Jax primitive
mpi_alltoall_p = Primitive("alltoall_mpi") # Create the primitive
mpi_alltoall_impl = default_primitive_impl(mpi_alltoall_p)
# This function applies the primitive to an AST
@enforce_types(
comm=(type(None), _MPI.Intracomm, HashableMPIType),
token=(type(None), Token, Tracer),
)
def alltoall(
x,
*,
comm=None,
token=None,
):
"""Perform an alltoall operation.
Arguments:
x: Array input to send. First axis must have size ``nproc``.
comm (mpi4py.MPI.Comm): The MPI communicator to use (defaults to
a clone of :obj:`COMM_WORLD`).
token (Token): XLA token to use to ensure correct execution order.
If not given, a new token is generated.
Returns:
Tuple[DeviceArray, Token]:
- Received data.
- A new, modified token, that depends on this operation.
"""
if token is None:
token = create_token(x)
if comm is None:
comm = get_default_comm()
size = comm.Get_size()
if x.shape[0] != size:
raise ValueError("Alltoall input must have shape (nproc, ...)")
comm = wrap_as_hashable(comm)
return tuple(
mpi_alltoall_p.bind(
x,
token,
comm=comm,
)
)
# This function compiles the operation
@translation_rule_cpu
def mpi_alltoall_xla_encode_cpu(c, x, token, comm):
comm = unpack_hashable(comm)
shape = c.GetShape(x)
dtype = shape.element_type()
dims = shape.dimensions()
# compute total number of elements in array
size = comm.Get_size()
assert dims[0] == size
nitems_per_proc = _np.prod(dims[1:], dtype=int)
dtype_handle = to_dtype_handle(dtype)
sh = xla_client.Shape.tuple_shape(
[
xla_client.Shape.array_shape(dtype, dims),
xla_client.Shape.token_shape(),
]
)
operands = (
xla_constant_intc(c, nitems_per_proc),
x,
xla_constant_uintptr(c, dtype_handle),
# we only support matching input and output arrays
xla_constant_intc(c, nitems_per_proc),
xla_constant_uintptr(c, dtype_handle),
#
xla_constant_uintptr(c, to_mpi_handle(comm)),
token,
)
return xla_client.ops.CustomCall(
c,
b"mpi_alltoall",
operands=operands,
shape=sh,
has_side_effect=True,
)
@translation_rule_gpu
def mpi_alltoall_xla_encode_gpu(c, x, token, comm):
from ..xla_bridge.mpi_xla_bridge_gpu import build_alltoall_descriptor
comm = unpack_hashable(comm)
shape = c.GetShape(x)
dtype = shape.element_type()
dims = shape.dimensions()
# compute total number of elements in send array
size = comm.Get_size()
assert dims[0] == size
nitems_per_proc = _np.prod(dims[1:], dtype=int)
dtype_handle = to_dtype_handle(dtype)
sh = xla_client.Shape.tuple_shape(
[
xla_client.Shape.array_shape(dtype, dims),
xla_client.Shape.token_shape(),
]
)
descriptor = build_alltoall_descriptor(
nitems_per_proc,
dtype_handle,
# we only support matching input and output arrays
nitems_per_proc,
dtype_handle,
#
to_mpi_handle(comm),
)
return xla_client.ops.CustomCall(
c,
b"mpi_alltoall",
operands=(
x,
token,
),
shape=sh,
opaque=descriptor,
has_side_effect=True,
)
# This function evaluates only the shapes during AST construction
def mpi_alltoall_abstract_eval(xs, token, comm):
return (
abstract_arrays.ShapedArray(xs.shape, xs.dtype),
core.abstract_token,
)
mpi_alltoall_p.multiple_results = True
mpi_alltoall_p.def_impl(mpi_alltoall_impl)
mpi_alltoall_p.def_abstract_eval(mpi_alltoall_abstract_eval)
# assign to the primitive the correct encoder
xla.backend_specific_translations["cpu"][mpi_alltoall_p] = mpi_alltoall_xla_encode_cpu
xla.backend_specific_translations["gpu"][mpi_alltoall_p] = mpi_alltoall_xla_encode_gpu
|
test/e101_example.py | shardros/autopep8 | 3,459 | 11122971 | <gh_stars>1000+
# -*- coding: utf-8 -*-
# From https://github.com/coto/gae-boilerplate/blob/233a88c59e46bb10de7a901ef4e6a5b60d0006a5/web/handlers.py
"""
This example will take a long time if we don't filter innocuous E101
errors from pep8.
"""
import models.models as models
from webapp2_extras.auth import InvalidAuthIdError
from webapp2_extras.auth import InvalidPasswordError
from webapp2_extras import security
from lib import utils
from lib import captcha
from lib.basehandler import BaseHandler
from lib.basehandler import user_required
from google.appengine.api import taskqueue
import logging
import config
import webapp2
import web.forms as forms
from webapp2_extras.i18n import gettext as _
from webapp2_extras.appengine.auth.models import Unique
from lib import twitter
class LoginBaseHandler(BaseHandler):
"""
Base class for handlers with login form.
"""
@webapp2.cached_property
def form(self):
return forms.LoginForm(self)
class RegisterBaseHandler(BaseHandler):
"""
Base class for handlers with registration and login forms.
"""
@webapp2.cached_property
def form(self):
if self.is_mobile:
return forms.RegisterMobileForm(self)
else:
return forms.RegisterForm(self)
@webapp2.cached_property
def form_login(self):
return forms.LoginForm(self)
@webapp2.cached_property
def forms(self):
return {'form_login' : self.form_login,
'form' : self.form}
class SendEmailHandler(BaseHandler):
"""
Handler for sending Emails
Use with TaskQueue
"""
def post(self):
to = self.request.get("to")
subject = self.request.get("subject")
body = self.request.get("body")
sender = self.request.get("sender")
utils.send_email(to, subject, body, sender)
class LoginHandler(LoginBaseHandler):
"""
Handler for authentication
"""
def get(self):
""" Returns a simple HTML form for login """
if self.user:
self.redirect_to('home', id=self.user_id)
params = {}
return self.render_template('boilerplate_login.html', **params)
def post(self):
"""
username: Get the username from POST dict
password: Get the password from POST dict
"""
if not self.form.validate():
return self.get()
username = self.form.username.data.lower()
try:
if utils.is_email_valid(username):
user = models.User.get_by_email(username)
if user:
auth_id = user.auth_ids[0]
else:
raise InvalidAuthIdError
else:
auth_id = "own:%s" % username
user = models.User.get_by_auth_id(auth_id)
password = self.form.password.data.strip()
remember_me = True if str(self.request.POST.get('remember_me')) == 'on' else False
# Password to <PASSWORD>
password = utils.encrypt(password, config.salt)
# Try to login user with password
# Raises InvalidAuthIdError if user is not found
# Raises InvalidPasswordError if provided password
# doesn't match with specified user
self.auth.get_user_by_password(
auth_id, password, remember=remember_me)
# if user account is not activated, logout and redirect to home
if (user.activated == False):
# logout
self.auth.unset_session()
# redirect to home with error message
resend_email_uri = self.uri_for('resend-account-activation', encoded_email=utils.encode(user.email))
message = _('Sorry, your account') + ' <strong>{0:>s}</strong>'.format(username) + " " +\
_('has not been activated. Please check your email to activate your account') + ". " +\
_('Or click') + " <a href='"+resend_email_uri+"'>" + _('this') + "</a> " + _('to resend the email')
self.add_message(message, 'error')
return self.redirect_to('home')
# check twitter association in session
twitter_helper = twitter.TwitterAuth(self)
twitter_association_data = twitter_helper.get_association_data()
if twitter_association_data is not None:
if models.SocialUser.check_unique(user.key, 'twitter', str(twitter_association_data['id'])):
social_user = models.SocialUser(
user = user.key,
provider = 'twitter',
uid = str(twitter_association_data['id']),
extra_data = twitter_association_data
)
social_user.put()
logVisit = models.LogVisit(
user=user.key,
uastring=self.request.user_agent,
ip=self.request.remote_addr,
timestamp=utils.get_date_time()
)
logVisit.put()
self.redirect_to('home')
except (InvalidAuthIdError, InvalidPasswordError), e:
# Returns error message to self.response.write in
# the BaseHandler.dispatcher
message = _("Login invalid, Try again.") + "<br/>" + _("Don't have an account?") + \
' <a href="' + self.uri_for('register') + '">' + _("Sign Up") + '</a>'
self.add_message(message, 'error')
return self.redirect_to('login')
class SocialLoginHandler(BaseHandler):
"""
Handler for Social authentication
"""
def get(self, provider_name):
provider_display_name = models.SocialUser.PROVIDERS_INFO[provider_name]['label']
if not config.enable_federated_login:
message = _('Federated login is disabled.')
self.add_message(message,'warning')
return self.redirect_to('login')
callback_url = "%s/social_login/%s/complete" % (self.request.host_url, provider_name)
if provider_name == "twitter":
twitter_helper = twitter.TwitterAuth(self, redirect_uri=callback_url)
self.redirect(twitter_helper.auth_url())
else:
message = _('%s authentication is not implemented yet.') % provider_display_name
self.add_message(message,'warning')
self.redirect_to('edit-profile')
class CallbackSocialLoginHandler(BaseHandler):
"""
Callback (Save Information) for Social Authentication
"""
def get(self, provider_name):
if not config.enable_federated_login:
message = _('Federated login is disabled.')
self.add_message(message,'warning')
return self.redirect_to('login')
if provider_name == "twitter":
oauth_token = self.request.get('oauth_token')
oauth_verifier = self.request.get('oauth_verifier')
twitter_helper = twitter.TwitterAuth(self)
user_data = twitter_helper.auth_complete(oauth_token,
oauth_verifier)
if self.user:
# new association with twitter
user_info = models.User.get_by_id(long(self.user_id))
if models.SocialUser.check_unique(user_info.key, 'twitter', str(user_data['id'])):
social_user = models.SocialUser(
user = user_info.key,
provider = 'twitter',
uid = str(user_data['id']),
extra_data = user_data
)
social_user.put()
message = _('Twitter association added!')
self.add_message(message,'success')
else:
message = _('This Twitter account is already in use!')
self.add_message(message,'error')
self.redirect_to('edit-profile')
else:
# login with twitter
social_user = models.SocialUser.get_by_provider_and_uid('twitter',
str(user_data['id']))
if social_user:
# Social user exists. Need authenticate related site account
user = social_user.user.get()
self.auth.set_session(self.auth.store.user_to_dict(user), remember=True)
logVisit = models.LogVisit(
user = user.key,
uastring = self.request.user_agent,
ip = self.request.remote_addr,
timestamp = utils.get_date_time()
)
logVisit.put()
self.redirect_to('home')
else:
# Social user does not exists. Need show login and registration forms
twitter_helper.save_association_data(user_data)
message = _('Account with association to your Twitter does not exist. You can associate it right now, if you login with existing site account or create new on Sign up page.')
self.add_message(message,'info')
self.redirect_to('login')
# Debug Callback information provided
# for k,v in user_data.items():
# print(k +":"+ v )
# google, myopenid, yahoo OpenID Providers
elif provider_name in models.SocialUser.open_id_providers():
provider_display_name = models.SocialUser.PROVIDERS_INFO[provider_name]['label']
# get info passed from OpenId Provider
from google.appengine.api import users
current_user = users.get_current_user()
if current_user:
if current_user.federated_identity():
uid = current_user.federated_identity()
else:
uid = current_user.user_id()
email = current_user.email()
else:
message = _('No user authentication information received from %s. Please ensure you are logging in from an authorized OpenID Provider (OP).' % provider_display_name)
self.add_message(message,'error')
return self.redirect_to('login')
if self.user:
# add social account to user
user_info = models.User.get_by_id(long(self.user_id))
if models.SocialUser.check_unique(user_info.key, provider_name, uid):
social_user = models.SocialUser(
user = user_info.key,
provider = provider_name,
uid = uid
)
social_user.put()
message = provider_display_name + _(' association added!')
self.add_message(message,'success')
else:
message = _('This %s account is already in use!' % provider_display_name)
self.add_message(message,'error')
self.redirect_to('edit-profile')
else:
# login with OpenId Provider
social_user = models.SocialUser.get_by_provider_and_uid(provider_name, uid)
if social_user:
# Social user found. Authenticate the user
user = social_user.user.get()
self.auth.set_session(self.auth.store.user_to_dict(user), remember=True)
logVisit = models.LogVisit(
user = user.key,
uastring = self.request.user_agent,
ip = self.request.remote_addr,
timestamp = utils.get_date_time()
)
logVisit.put()
self.redirect_to('home')
else:
# Social user does not exist yet so create it with the federated identity provided (uid)
# and create prerequisite user and log the user account in
if models.SocialUser.check_unique_uid(provider_name, uid):
# create user
# Returns a tuple, where first value is BOOL.
# If True ok, If False no new user is created
# Assume provider has already verified email address
# if email is provided so set activated to True
auth_id = "%s:%s" % (provider_name, uid)
if email:
unique_properties = ['email']
user_info = self.auth.store.user_model.create_user(
auth_id, unique_properties, email=email,
activated=True
)
else:
user_info = self.auth.store.user_model.create_user(
auth_id, activated=True
)
if not user_info[0]: #user is a tuple
message = _('This %s account is already in use!' % provider_display_name)
self.add_message(message, 'error')
return self.redirect_to('register')
user = user_info[1]
# create social user and associate with user
social_user = models.SocialUser(
user = user.key,
provider = provider_name,
uid = uid
)
social_user.put()
# authenticate user
self.auth.set_session(self.auth.store.user_to_dict(user), remember=True)
logVisit = models.LogVisit(
user = user.key,
uastring = self.request.user_agent,
ip = self.request.remote_addr,
timestamp = utils.get_date_time()
)
logVisit.put()
self.redirect_to('home')
message = provider_display_name + _(' association added!')
self.add_message(message,'success')
self.redirect_to('home')
else:
message = _('This %s account is already in use!' % provider_display_name)
self.add_message(message,'error')
self.redirect_to('login')
else:
message = _('%s authentication is not implemented yet.') % provider_display_name
self.add_message(message,'warning')
self.redirect_to('login')
class DeleteSocialProviderHandler(BaseHandler):
"""
Delete Social association with an account
"""
@user_required
def get(self, provider_name):
if self.user:
user_info = models.User.get_by_id(long(self.user_id))
social_user = models.SocialUser.get_by_user_and_provider(user_info.key, provider_name)
if social_user:
social_user.key.delete()
message = provider_name + _(' disassociated!')
self.add_message(message,'success')
else:
message = _('Social account on ') + provider_name + _(' not found for this user!')
self.add_message(message,'error')
self.redirect_to('edit-profile')
class LogoutHandler(BaseHandler):
"""
Destroy user session and redirect to login
"""
def get(self):
if self.user:
message = _("You've signed out successfully. Warning: Please clear all cookies and logout \
of OpenId providers too if you logged in on a public computer.") # Info message
self.add_message(message, 'info')
self.auth.unset_session()
# User is logged out, let's try redirecting to login page
try:
self.redirect(self.auth_config['login_url'])
except (AttributeError, KeyError), e:
return _("User is logged out, but there was an error "\
"on the redirection.")
class RegisterHandler(RegisterBaseHandler):
"""
Handler for Sign Up Users
"""
def get(self):
""" Returns a simple HTML form for create a new user """
if self.user:
self.redirect_to('home', id=self.user_id)
params = {}
return self.render_template('boilerplate_register.html', **params)
def post(self):
""" Get fields from POST dict """
if not self.form.validate():
return self.get()
username = self.form.username.data.lower()
name = self.form.name.data.strip()
last_name = self.form.last_name.data.strip()
email = self.form.email.data.lower()
password = self.form.password.data.strip()
country = self.form.country.data
# Password to SHA512
password = utils.encrypt(password, config.salt)
# Passing password_raw=password so password will be hashed
# Returns a tuple, where first value is BOOL.
# If True ok, If False no new user is created
unique_properties = ['username', 'email']
auth_id = "own:%s" % username
user = self.auth.store.user_model.create_user(
auth_id, unique_properties, password_raw=password,
username=username, name=name, last_name=last_name, email=email,
country=country, activated=False
)
if not user[0]: #user is a tuple
message = _('Sorry, This user') + ' <strong>{0:>s}</strong>'.format(username) + " " +\
_('is already registered.')
self.add_message(message, 'error')
return self.redirect_to('register')
else:
# User registered successfully
# But if the user registered using the form, the user has to check their email to activate the account ???
try:
user_info = models.User.get_by_email(email)
if (user_info.activated == False):
# send email
subject = config.app_name + " Account Verification Email"
encoded_email = utils.encode(email)
confirmation_url = self.uri_for("account-activation",
encoded_email = encoded_email,
_full = True)
# load email's template
template_val = {
"app_name": config.app_name,
"username": username,
"confirmation_url": confirmation_url,
"support_url": self.uri_for("contact", _full=True)
}
body_path = "emails/account_activation.txt"
body = self.jinja2.render_template(body_path, **template_val)
email_url = self.uri_for('taskqueue-send-email')
taskqueue.add(url = email_url, params={
'to': str(email),
'subject' : subject,
'body' : body,
})
message = _('Congratulations') + ", " + str(username) + "! " + _('You are now registered') +\
". " + _('Please check your email to activate your account')
self.add_message(message, 'success')
return self.redirect_to('home')
# If the user didn't register using registration form ???
db_user = self.auth.get_user_by_password(user[1].auth_ids[0], password)
# Check twitter association in session
twitter_helper = twitter.TwitterAuth(self)
twitter_association_data = twitter_helper.get_association_data()
if twitter_association_data is not None:
if models.SocialUser.check_unique(user[1].key, 'twitter', str(twitter_association_data['id'])):
social_user = models.SocialUser(
user = user[1].key,
provider = 'twitter',
uid = str(twitter_association_data['id']),
extra_data = twitter_association_data
)
social_user.put()
message = _('Welcome') + " " + str(username) + ", " + _('you are now logged in.')
self.add_message(message, 'success')
return self.redirect_to('home')
except (AttributeError, KeyError), e:
message = _('Unexpected error creating '\
'user') + " " + '{0:>s}.'.format(username)
self.add_message(message, 'error')
self.abort(403)
class AccountActivationHandler(BaseHandler):
"""
Handler for account activation
"""
def get(self, encoded_email):
try:
email = utils.decode(encoded_email)
user = models.User.get_by_email(email)
# activate the user's account
user.activated = True
user.put()
message = _('Congratulations') + "! " + _('Your account') + " (@" + user.username + ") " +\
_('has just been activated') + ". " + _('Please login to your account')
self.add_message(message, "success")
self.redirect_to('login')
except (AttributeError, KeyError, InvalidAuthIdError), e:
message = _('Unexpected error activating '\
'account') + " " + '{0:>s}.'.format(user.username)
self.add_message(message, 'error')
self.abort(403)
class ResendActivationEmailHandler(BaseHandler):
"""
Handler to resend activation email
"""
def get(self, encoded_email):
try:
email = utils.decode(encoded_email)
user = models.User.get_by_email(email)
if (user.activated == False):
# send email
subject = config.app_name + " Account Verification Email"
encoded_email = utils.encode(email)
confirmation_url = self.uri_for("account-activation",
encoded_email = encoded_email,
_full = True)
# load email's template
template_val = {
"app_name": config.app_name,
"username": user.username,
"confirmation_url": confirmation_url,
"support_url": self.uri_for("contact", _full=True)
}
body_path = "emails/account_activation.txt"
body = self.jinja2.render_template(body_path, **template_val)
email_url = self.uri_for('taskqueue-send-email')
taskqueue.add(url = email_url, params={
'to': str(email),
'subject' : subject,
'body' : body,
})
message = _('The verification email has been resent to') + " " + str(email) + ". " +\
_('Please check your email to activate your account')
self.add_message(message, "success")
return self.redirect_to('home')
else:
message = _('Your account has been activated') + ". " +\
_('Please login to your account')
self.add_message(message, "warning")
return self.redirect_to('home')
except (KeyError, AttributeError), e:
message = _('Sorry') + ". " + _('Some error occurred') + "."
self.add_message(message, "error")
return self.redirect_to('home')
class ContactHandler(BaseHandler):
"""
Handler for Contact Form
"""
def get(self):
""" Returns a simple HTML for contact form """
if self.user:
user_info = models.User.get_by_id(long(self.user_id))
if user_info.name or user_info.last_name:
self.form.name.data = user_info.name + " " + user_info.last_name
if user_info.email:
self.form.email.data = user_info.email
params = {
"exception" : self.request.get('exception')
}
return self.render_template('boilerplate_contact.html', **params)
def post(self):
""" validate contact form """
if not self.form.validate():
return self.get()
remoteip = self.request.remote_addr
user_agent = self.request.user_agent
exception = self.request.POST.get('exception')
name = self.form.name.data.strip()
email = self.form.email.data.lower()
message = self.form.message.data.strip()
try:
subject = _("Contact")
body = ""
# exceptions for error pages that redirect to contact
if exception != "":
body = "* Exception error: %s" % exception
body = body + """
* IP Address: %s
* Web Browser: %s
* Sender name: %s
* Sender email: %s
* Message: %s
""" % (remoteip, user_agent, name, email, message)
email_url = self.uri_for('taskqueue-send-email')
taskqueue.add(url = email_url, params={
'to': config.contact_recipient,
'subject' : subject,
'body' : body,
'sender' : config.contact_sender,
})
message = _('Message sent successfully.')
self.add_message(message, 'success')
return self.redirect_to('contact')
except (AttributeError, KeyError), e:
message = _('Error sending the message. Please try again later.')
self.add_message(message, 'error')
return self.redirect_to('contact')
@webapp2.cached_property
def form(self):
return forms.ContactForm(self)
class EditProfileHandler(BaseHandler):
"""
Handler for Edit User Profile
"""
@user_required
def get(self):
""" Returns a simple HTML form for edit profile """
params = {}
if self.user:
user_info = models.User.get_by_id(long(self.user_id))
self.form.username.data = user_info.username
self.form.name.data = user_info.name
self.form.last_name.data = user_info.last_name
self.form.country.data = user_info.country
providers_info = user_info.get_social_providers_info()
params['used_providers'] = providers_info['used']
params['unused_providers'] = providers_info['unused']
params['country'] = user_info.country
return self.render_template('boilerplate_edit_profile.html', **params)
def post(self):
""" Get fields from POST dict """
if not self.form.validate():
return self.get()
username = self.form.username.data.lower()
name = self.form.name.data.strip()
last_name = self.form.last_name.data.strip()
country = self.form.country.data
try:
user_info = models.User.get_by_id(long(self.user_id))
try:
message=''
# update username if it has changed and it isn't already taken
if username != user_info.username:
user_info.unique_properties = ['username','email']
uniques = [
'User.username:%s' % username,
'User.auth_id:own:%s' % username,
]
# Create the unique username and auth_id.
success, existing = Unique.create_multi(uniques)
if success:
# free old uniques
Unique.delete_multi(['User.username:%s' % user_info.username, 'User.auth_id:own:%s' % user_info.username])
# The unique values were created, so we can save the user.
user_info.username=username
user_info.auth_ids[0]='own:%s' % username
message+= _('Your new username is ') + '<strong>' + username + '</strong>.'
else:
message+= _('Username') + " <strong>" + username + "</strong> " + _('is already taken. It is not changed.')
# At least one of the values is not unique.
self.add_message(message,'error')
return self.get()
user_info.name=name
user_info.last_name=last_name
user_info.country=country
user_info.put()
message+= " " + _('Your profile has been updated!')
self.add_message(message,'success')
return self.get()
except (AttributeError, KeyError, ValueError), e:
message = _('Unable to update profile!')
logging.error('Unable to update profile: ' + e)
self.add_message(message,'error')
return self.get()
except (AttributeError, TypeError), e:
login_error_message = _('Sorry you are not logged in!')
self.add_message(login_error_message,'error')
self.redirect_to('login')
@webapp2.cached_property
def form(self):
return forms.EditProfileForm(self)
class EditPasswordHandler(BaseHandler):
"""
Handler for Edit User Password
"""
@user_required
def get(self):
""" Returns a simple HTML form for editing password """
params = {}
return self.render_template('boilerplate_edit_password.html', **params)
def post(self):
""" Get fields from POST dict """
if not self.form.validate():
return self.get()
current_password = self.form.current_password.data.strip()
password = self.form.password.data.strip()
try:
user_info = models.User.get_by_id(long(self.user_id))
auth_id = "own:%s" % user_info.username
# Password to SHA512
current_password = utils.encrypt(current_password, config.salt)
try:
user = models.User.get_by_auth_password(auth_id, current_password)
# Password to SHA512
password = utils.encrypt(password, config.salt)
user.password = security.generate_password_hash(password, length=12)
user.put()
# send email
subject = config.app_name + " Account Password Changed"
# load email's template
template_val = {
"app_name": config.app_name,
"first_name": user.name,
"username": user.username,
"email": user.email,
"reset_password_url": self.uri_for("password-reset", _full=True)
}
email_body_path = "emails/password_changed.txt"
email_body = self.jinja2.render_template(email_body_path, **template_val)
email_url = self.uri_for('taskqueue-send-email')
taskqueue.add(url = email_url, params={
'to': user.email,
'subject' : subject,
'body' : email_body,
'sender' : config.contact_sender,
})
# Login User
self.auth.get_user_by_password(user.auth_ids[0], password)
self.add_message(_('Password changed successfully'), 'success')
return self.redirect_to('edit-profile')
except (InvalidAuthIdError, InvalidPasswordError), e:
# Returns error message to self.response.write in
# the BaseHandler.dispatcher
message = _("Your Current Password is wrong, please try again")
self.add_message(message, 'error')
return self.redirect_to('edit-password')
except (AttributeError,TypeError), e:
login_error_message = _('Sorry you are not logged in!')
self.add_message(login_error_message,'error')
self.redirect_to('login')
@webapp2.cached_property
def form(self):
if self.is_mobile:
return forms.EditPasswordMobileForm(self)
else:
return forms.EditPasswordForm(self)
class EditEmailHandler(BaseHandler):
"""
Handler for Edit User's Email
"""
@user_required
def get(self):
""" Returns a simple HTML form for edit email """
params = {}
if self.user:
user_info = models.User.get_by_id(long(self.user_id))
self.form.new_email.data = user_info.email
return self.render_template('boilerplate_edit_email.html', **params)
def post(self):
""" Get fields from POST dict """
if not self.form.validate():
return self.get()
new_email = self.form.new_email.data.strip()
password = self.form.<PASSWORD>.strip()
try:
user_info = models.User.get_by_id(long(self.user_id))
auth_id = "own:%s" % user_info.username
# Password to <PASSWORD>
password = utils.encrypt(password, config.salt)
try:
# authenticate user by its password
user = models.User.get_by_auth_password(auth_id, password)
# if the user change his/her email address
if new_email != user.email:
# check whether the new email has been used by another user
aUser = models.User.get_by_email(new_email)
if aUser is not None:
message = _("The email %s is already registered." % new_email)
self.add_message(message, "error")
return self.redirect_to("edit-email")
# send email
subject = config.app_name + " Email Changed Notification"
user_token = models.User.create_auth_token(self.user_id)
confirmation_url = self.uri_for("email-changed-check",
user_id = user_info.get_id(),
encoded_email = utils.encode(new_email),
token = user_token,
_full = True)
# load email's template
template_val = {
"app_name": config.app_name,
"first_name": user.name,
"username": user.username,
"new_email": new_email,
"confirmation_url": confirmation_url,
"support_url": self.uri_for("contact", _full=True)
}
old_body_path = "emails/email_changed_notification_old.txt"
old_body = self.jinja2.render_template(old_body_path, **template_val)
new_body_path = "emails/email_changed_notification_new.txt"
new_body = self.jinja2.render_template(new_body_path, **template_val)
email_url = self.uri_for('taskqueue-send-email')
taskqueue.add(url = email_url, params={
'to': user.email,
'subject' : subject,
'body' : old_body,
})
email_url = self.uri_for('taskqueue-send-email')
taskqueue.add(url = email_url, params={
'to': new_email,
'subject' : subject,
'body' : new_body,
})
logging.error(user)
# display successful message
msg = _("Please check your new email for confirmation. Your email will be updated after confirmation.")
self.add_message(msg, 'success')
return self.redirect_to('edit-profile')
else:
self.add_message(_("You didn't change your email"), "warning")
return self.redirect_to("edit-email")
except (InvalidAuthIdError, InvalidPasswordError), e:
# Returns error message to self.response.write in
# the BaseHandler.dispatcher
message = _("Your password is wrong, please try again")
self.add_message(message, 'error')
return self.redirect_to('edit-email')
except (AttributeError,TypeError), e:
login_error_message = _('Sorry you are not logged in!')
self.add_message(login_error_message,'error')
self.redirect_to('login')
@webapp2.cached_property
def form(self):
return forms.EditEmailForm(self)
class PasswordResetHandler(LoginBaseHandler):
"""
Password Reset Handler with Captcha
"""
reCaptcha_public_key = config.captcha_public_key
reCaptcha_private_key = config.captcha_private_key
def get(self):
chtml = captcha.displayhtml(
public_key = self.reCaptcha_public_key,
use_ssl = False,
error = None)
params = {
'captchahtml': chtml,
}
return self.render_template('boilerplate_password_reset.html', **params)
def post(self):
# check captcha
challenge = self.request.POST.get('recaptcha_challenge_field')
response = self.request.POST.get('recaptcha_response_field')
remoteip = self.request.remote_addr
cResponse = captcha.submit(
challenge,
response,
self.reCaptcha_private_key,
remoteip)
if cResponse.is_valid:
# captcha was valid... carry on..nothing to see here
pass
else:
logging.warning(cResponse.error_code)
_message = _('Wrong image verification code. Please try again.')
self.add_message(_message, 'error')
return self.redirect_to('password-reset')
# check if we got an email or username
email_or_username = str(self.request.POST.get('email_or_username')).lower().strip()
if utils.is_email_valid(email_or_username):
user = models.User.get_by_email(email_or_username)
_message = _("If the e-mail address you entered") + " (<strong>%s</strong>) " % email_or_username
else:
auth_id = "own:%s" % email_or_username
user = models.User.get_by_auth_id(auth_id)
_message = _("If the username you entered") + " (<strong>%s</strong>) " % email_or_username
if user is not None:
user_id = user.get_id()
token = models.User.create_auth_token(user_id)
email_url = self.uri_for('taskqueue-send-email')
reset_url = self.uri_for('password-reset-check', user_id=user_id, token=token, _full=True)
subject = _("Password reminder")
body = _('Please click below to create a new password:') +\
"""
%s
""" % reset_url
taskqueue.add(url = email_url, params={
'to': user.email,
'subject' : subject,
'body' : body,
'sender' : config.contact_sender,
})
_message = _message + _("is associated with an account in our records, you will receive "\
"an e-mail from us with instructions for resetting your password. "\
"<br>If you don't receive this e-mail, please check your junk mail folder or ") +\
'<a href="' + self.uri_for('contact') + '">' + _('contact us') + '</a> ' + _("for further assistance.")
self.add_message(_message, 'success')
return self.redirect_to('login')
_message = _('Your email / username was not found. Please try another or ') + '<a href="' + self.uri_for('register') + '">' + _('create an account') + '</a>'
self.add_message(_message, 'error')
return self.redirect_to('password-reset')
class PasswordResetCompleteHandler(LoginBaseHandler):
"""
Handler to process the link of reset password that received the user
"""
def get(self, user_id, token):
verify = models.User.get_by_auth_token(int(user_id), token)
params = {}
if verify[0] is None:
message = _('There was an error or the link is outdated. Please copy and paste the link from your email or enter your details again below to get a new one.')
self.add_message(message, 'warning')
return self.redirect_to('password-reset')
else:
return self.render_template('boilerplate_password_reset_complete.html', **params)
def post(self, user_id, token):
verify = models.User.get_by_auth_token(int(user_id), token)
user = verify[0]
password = self.form.password.data.strip()
if user and self.form.validate():
# Password to SHA512
password = utils.encrypt(password, config.salt)
user.password = security.generate_password_hash(password, length=12)
user.put()
# Delete token
models.User.delete_auth_token(int(user_id), token)
# Login User
self.auth.get_user_by_password(user.auth_ids[0], password)
self.add_message(_('Password changed successfully'), 'success')
return self.redirect_to('home')
else:
self.add_message(_('Please correct the form errors.'), 'error')
return self.redirect_to('password-reset-check', user_id=user_id, token=token)
@webapp2.cached_property
def form(self):
if self.is_mobile:
return forms.PasswordResetCompleteMobileForm(self)
else:
return forms.PasswordResetCompleteForm(self)
class EmailChangedCompleteHandler(BaseHandler):
"""
Handler for completed email change
Will be called when the user click confirmation link from email
"""
def get(self, user_id, encoded_email, token):
verify = models.User.get_by_auth_token(int(user_id), token)
email = utils.decode(encoded_email)
if verify[0] is None:
self.add_message('There was an error or the link is outdated. Please copy and paste the link from your email.', 'warning')
self.redirect_to('home')
else:
# save new email
user = verify[0]
user.email = email
user.put()
# delete token
models.User.delete_auth_token(int(user_id), token)
# add successful message and redirect
self.add_message("Your email has been successfully updated!", "success")
self.redirect_to('edit-profile')
class SecureRequestHandler(BaseHandler):
"""
Only accessible to users that are logged in
"""
@user_required
def get(self, **kwargs):
user_session = self.user
user_session_object = self.auth.store.get_session(self.request)
user_info = models.User.get_by_id(long( self.user_id ))
user_info_object = self.auth.store.user_model.get_by_auth_token(
user_session['user_id'], user_session['token'])
try:
params = {
"user_session" : user_session,
"user_session_object" : user_session_object,
"user_info" : user_info,
"user_info_object" : user_info_object,
"userinfo_logout-url" : self.auth_config['logout_url'],
}
return self.render_template('boilerplate_secure_zone.html', **params)
except (AttributeError, KeyError), e:
return _("Secure zone error:") + " %s." % e
class HomeRequestHandler(RegisterBaseHandler):
"""
Handler to show the home page
"""
def get(self):
""" Returns a simple HTML form for home """
params = {}
return self.render_template('boilerplate_home.html', **params)
|
examples/wordle-cairo.py | josh95117/freetype-py | 242 | 11122973 | <reponame>josh95117/freetype-py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# -----------------------------------------------------------------------------
#
# pycairo/cairocffi-based wordle example - Copyright 2017 <NAME>
# Distributed under the terms of the new BSD license.
#
# rewrite of the numply,matplotlib-based example from <NAME>
# - Cairo can paint partly off-screen, so this example does!
#
# This example behaves differently under pycairo 1.11+ (released in 2017-04-09).
# Auto-checked. On older pycairo, it does not draw partial patterns at the edges.
# Also, Suface.get_data() is not in the "python 3, pycairo < 1.11" combination.
#
# -----------------------------------------------------------------------------
from math import cos, sin
from numpy import random, sort, sqrt, ndarray, ubyte
from freetype import *
try:
# pycairo 1.11+:
from cairo import Region, RectangleInt, REGION_OVERLAP_OUT
except ImportError:
# stubs for pycairo < 1.11:
class Region:
def __init__(self):
return
def union(self, rec):
return
def contains_rectangle(self, rec):
# inhibit drawing
return True
class RectangleInt:
def __init__(self, x, y, w, h):
return
REGION_OVERLAP_OUT = False
from cairo import Context, ImageSurface, FORMAT_A8, FORMAT_ARGB32, Matrix
from bitmap_to_surface import make_image_surface
def make_label(text, filename, size=12, angle=0):
'''
Parameters:
-----------
text : string
Text to be displayed
filename : string
Path to a font
size : int
Font size in 1/64th points
angle : float
Text angle in degrees
'''
face = Face(filename)
face.set_char_size( size*64 )
# FT_Angle is a 16.16 fixed-point value expressed in degrees.
angle = FT_Angle(angle * 65536)
matrix = FT_Matrix( FT_Cos( angle ),
- FT_Sin( angle ),
FT_Sin( angle ) ,
FT_Cos( angle ) )
flags = FT_LOAD_RENDER
pen = FT_Vector(0,0)
FT_Set_Transform( face._FT_Face, byref(matrix), byref(pen) )
previous = 0
xmin, xmax = 0, 0
ymin, ymax = 0, 0
for c in text:
face.load_char(c, flags)
kerning = face.get_kerning(previous, c)
previous = c
bitmap = face.glyph.bitmap
pitch = face.glyph.bitmap.pitch
width = face.glyph.bitmap.width
rows = face.glyph.bitmap.rows
top = face.glyph.bitmap_top
left = face.glyph.bitmap_left
pen.x += kerning.x
x0 = (pen.x >> 6) + left
x1 = x0 + width
y0 = (pen.y >> 6) - (rows - top)
y1 = y0 + rows
xmin, xmax = min(xmin, x0), max(xmax, x1)
ymin, ymax = min(ymin, y0), max(ymax, y1)
pen.x += face.glyph.advance.x
pen.y += face.glyph.advance.y
L = ImageSurface(FORMAT_A8, xmax-xmin, ymax-ymin)
previous = 0
pen.x, pen.y = 0, 0
ctx = Context(L)
for c in text:
face.load_char(c, flags)
kerning = face.get_kerning(previous, c)
previous = c
bitmap = face.glyph.bitmap
pitch = face.glyph.bitmap.pitch
width = face.glyph.bitmap.width
rows = face.glyph.bitmap.rows
top = face.glyph.bitmap_top
left = face.glyph.bitmap_left
pen.x += kerning.x
x = (pen.x >> 6) - xmin + left
y = - (pen.y >> 6) + ymax - top
if (width > 0):
glyph_surface = make_image_surface(face.glyph.bitmap)
ctx.set_source_surface(glyph_surface, x, y)
ctx.paint()
pen.x += face.glyph.advance.x
pen.y += face.glyph.advance.y
L.flush()
return L
if __name__ == '__main__':
from PIL import Image
n_words = 200
H, W, dpi = 600, 800, 72.0
I = ImageSurface(FORMAT_A8, W, H)
ctxI = Context(I)
ctxI.rectangle(0,0,800,600)
ctxI.set_source_rgba (0.9, 0.9, 0.9, 0)
ctxI.fill()
S = random.normal(0,1,n_words)
S = (S-S.min())/(S.max()-S.min())
S = sort(1-sqrt(S))[::-1]
sizes = (12 + S*48).astype(int).tolist()
def spiral():
eccentricity = 1.5
radius = 8
step = 0.1
t = 0
while True:
t += step
yield eccentricity*radius*t*cos(t), radius*t*sin(t)
drawn_regions = Region()
for size in sizes:
angle = random.randint(-25,25)
try:
L = make_label('Hello', './Vera.ttf', size, angle=angle)
except NotImplementedError:
raise SystemExit("For python 3.x, you need pycairo >= 1.11+ (from https://github.com/pygobject/pycairo)")
h = L.get_height()
w = L.get_width()
if h < H and w < W:
x0 = W//2 + (random.uniform()-.1)*50
y0 = H//2 + (random.uniform()-.1)*50
for dx,dy in spiral():
c = .25+.75*random.random()
x = int(x0+dx)
y = int(y0+dy)
checked = False
I.flush()
if not (x <= w//2 or y <= h//2 or x >= (W-w//2) or y >= (H-h//2)):
ndI = ndarray(shape=(h,w), buffer=I.get_data(), dtype=ubyte, order='C',
offset=(x-w//2) + I.get_stride() * (y-h//2),
strides=[I.get_stride(), 1])
ndL = ndarray(shape=(h,w), buffer=L.get_data(), dtype=ubyte, order='C',
strides=[L.get_stride(), 1])
if ((ndI * ndL).sum() == 0):
checked = True
new_region = RectangleInt(x-w//2, y-h//2, w, h)
if (checked or ( drawn_regions.contains_rectangle(new_region) == REGION_OVERLAP_OUT )):
ctxI.set_source_surface(L, 0, 0)
pattern = ctxI.get_source()
scalematrix = Matrix()
scalematrix.scale(1.0,1.0)
scalematrix.translate(w//2 - x, h//2 - y)
pattern.set_matrix(scalematrix)
ctxI.set_source_rgba(c,c,c,c)
ctxI.mask(pattern)
drawn_regions.union(new_region)
break
I.flush()
I.write_to_png("wordle-cairo.png")
Image.open("wordle-cairo.png").show()
|
lib/chips/chip_generator.py | pigtamer/SNIPER | 2,722 | 11122998 | # --------------------------------------------------------------
# SNIPER: Efficient Multi-Scale Training
# Licensed under The Apache-2.0 License [see LICENSE for details]
# by <NAME> and <NAME>
# --------------------------------------------------------------
import chips
from bbox.bbox_transform import clip_boxes, ignore_overlaps
import numpy as np
class chip_generator(object):
def __init__(self, chip_stride=32, use_cpp=True):
self.use_cpp = use_cpp
self.chip_stride = chip_stride
def generate(self, boxes, width, height, chipsize):
if self.use_cpp:
return self._cgenerate(boxes, width, height, chipsize, self.chip_stride)
else:
return self._pygenerate(boxes, width, height, chipsize, self.chip_stride)
@staticmethod
def _cgenerate(boxes, width, height, chipsize, stride):
boxes = clip_boxes(boxes, np.array([height - 1, width - 1]))
return chips.generate(np.ascontiguousarray(boxes, dtype=np.float32),
width, height, chipsize, stride)
@staticmethod
def _pygenerate(boxes, width, height, chipsize, stride):
chips = []
boxes = clip_boxes(boxes, np.array([height-1, width-1]))
# ensure coverage of image for worst case
# corners
chips.append([max(width - chipsize, 0), 0, width - 1, min(chipsize, height-1)])
chips.append([0, max(height - chipsize, 0), min(chipsize, width-1), height-1])
chips.append([max(width - chipsize, 0), max(height - chipsize, 0), width-1, height-1])
for i in range(0, width - int(chipsize), stride):
for j in range(0, height - int(chipsize), stride):
x1 = i
y1 = j
x2 = i + chipsize - 1
y2 = j + chipsize - 1
chips.append([x1, y1, x2, y2])
for j in range(0, height - int(chipsize), stride):
x1 = max(width - chipsize - 1,0)
y1 = j
x2 = width - 1
y2 = j + chipsize - 1
chips.append([x1, y1, x2, y2])
for i in range(0, width - int(chipsize), stride):
x1 = i
y1 = max(height - chipsize - 1,0)
x2 = i + chipsize - 1
y2 = height - 1
chips.append([x1, y1, x2, y2])
chips = np.array(chips).astype(np.float)
p = np.random.permutation(chips.shape[0])
chips = chips[p]
overlaps = ignore_overlaps(chips, boxes.astype(np.float))
chip_matches = []
num_matches = []
for j in range(len(chips)):
nvids = np.where(overlaps[j, :] == 1)[0]
chip_matches.append(set(nvids.tolist()))
num_matches.append(len(nvids))
fchips = []
totalmatches = 0
while True:
max_matches = 0
max_match = max(num_matches)
mid = np.argmax(np.array(num_matches))
if max_match == 0:
break
if max_match > max_matches:
max_matches = max_match
maxid = mid
bestchip = chip_matches[maxid]
fchips.append(chips[maxid])
totalmatches = totalmatches + max_matches
# now remove all rois in bestchip
for j in range(len(num_matches)):
chip_matches[j] = chip_matches[j] - bestchip
num_matches[j] = len(chip_matches[j])
return fchips
|
Competitions/Skillenza/Focuthon/String Replacement.py | cnm06/Competitive-Programming | 994 | 11123102 | <gh_stars>100-1000
n = int(raw_input())
for i in xrange(0, n):
s = raw_input()
s = s.replace('a', 'v#nt&r#s!ty').replace('e', 'v#nt&r#s!ty').replace('i', 'v#nt&r#s!ty').replace('o', 'v#nt&r#s!ty').replace('u', 'v#nt&r#s!ty').replace('A', 'v#nt&r#s!ty').replace('E', 'v#nt&r#s!ty').replace('I', 'v#nt&r#s!ty').replace('O', 'v#nt&r#s!ty').replace('U', 'v#nt&r#s!ty')
s = s.replace('#', 'e').replace('&', 'u').replace('!', 'i')
print s
|
pipeline/trainers/segmentation.py | PavelOstyakov/pipeline | 214 | 11123117 | from .base import TrainerBase
class TrainerSegmentation(TrainerBase):
pass
|
eda/implementacoes/estruturas_de_dados/SingleLinkedList.py | gabrielmbs/Tamburetei | 209 | 11123144 | # # Esta implementação foi feita em Python 3.
# Esteja ciente disso ao executar :)
# Nesse arquivo, focaremos na implementação da Single
# Linked List, uma estrutura similar a um array, mas
# de tamanho dinâmico, e que funciona por meio de nós,
# onde a lista mantém uma referência ao primeiro nó,
# e cada nó mantém o seu valor e a referência ao nó
# seguinte. As funções implementadas se baseiam nas
# necessárias em LEDA.
from LinkedListNodes import SingleLinkedListNode
class SingleLinkedList(object):
def __init__(self):
"""
Construtor da classe.
Inicia uma Single Linked List vazia, apenas
com referência ao primeiro elemento.
"""
self.head = SingleLinkedListNode()
def is_empty(self):
"""
Retorna se a lista está vazia.
A lista está vazia se o primeiro elemento
for um nó NIL.
"""
return self.head.is_nil()
def insert(self, element):
"""
Insere um novo elemento na LinkedList.
O elemento passado como parâmetro deve ser
um elemento válido e, caso seja None, deve ser
ignorado.
"""
if (element != None):
if (self.head.is_nil()):
self.head.set_value(element)
else:
current_node = self.head
while (not current_node.get_next() == None):
current_node = current_node.get_next()
current_node.set_next_node(SingleLinkedListNode(element))
def remove(self, element):
"""
Remove um elemento existente na LinkedList.
O elemento passado como parâmetro deve ser
um elemento válido, isto é, não pode ser None.
Caso o elemento passado não exista na lista,
esta deve se manter inalterada.
"""
to_return = None
if (element != None and not self.head.is_nil()):
if (self.head.get_value() == element):
if (self.head.get_next() != None):
self.head = self.head.get_next()
else:
self.head.set_value(None)
to_return = element
else:
current_node = self.head
while (current_node.get_next() != None):
if (current_node.get_next().get_value() == element):
current_node.set_next_node(current_node.get_next().get_next())
to_return = element
break
else:
current_node = current_node.get_next()
return to_return
def size(self):
"""
Calcula o tamanho da lista encadeada.
"""
linked_size = 0
current_node = self.head
while (current_node != None and not current_node.is_nil()):
linked_size += 1
current_node = current_node.get_next()
return linked_size
def search_index(self, searched_value):
"""
Busca um elemento na lista encadeada e retorna
sua posição. Caso o elemento não seja encontrado,
deve-se retornar -1.
"""
index = -1
if (searched_value != None):
current_node = self.head
while (current_node != None and not current_node.is_nil()):
index += 1
if (current_node.get_value() == searched_value):
break
current_node = current_node.get_next()
return index
def search(self, searched_value):
"""
Busca um elemento na lista encadeada e retorna
seu valor. Caso o elemento não seja encontrado,
deve-se retornar None.
"""
node_value = None
if (searched_value != None):
current_node = self.head
while (current_node != None and not current_node.is_nil()):
if (current_node.get_value() == searched_value):
node_value = searched_value
break
current_node = current_node.get_next()
return node_value
def to_array(self):
"""
Transforma a lista encadeada em uma lista,
respeitando a ordem dos elementos da lista
encadeada
"""
array = []
current_node = self.head
while (current_node != None and not current_node.is_nil()):
array.append(current_node.get_value())
current_node = current_node.get_next()
return array
# Agora, criaremos algumas asserções, verificando a corretude
# da implementação da nossa Single linked List :)
# Teste 1: inserção e remoção na lista
sll = SingleLinkedList()
assert sll.is_empty() == True
assert sll.to_array() == []
assert sll.size() == 0
sll.insert(3)
assert sll.is_empty() == False
assert sll.search(3) == 3
assert sll.search_index(3) == 0
assert sll.to_array() == [3]
assert sll.size() == 1
assert sll.remove(3) == 3
assert sll.size() == 0
# Teste 2: mais inserção e remoção na lista :D
sll = SingleLinkedList()
assert sll.is_empty() == True
assert sll.to_array() == []
sll.insert(1)
assert sll.is_empty() == False
assert sll.search(1) == 1
assert sll.search_index(1) == 0
assert sll.to_array() == [1]
assert sll.size() == 1
sll.insert(5)
assert sll.is_empty() == False
assert sll.to_array() == [1, 5]
assert sll.search(5) == 5
assert sll.search_index(5) == 1
assert sll.size() == 2
sll.insert(10)
assert sll.is_empty() == False
assert sll.search(10) == 10
assert sll.search_index(10) == 2
assert sll.to_array() == [1, 5, 10]
assert sll.size() == 3
assert sll.remove(5)
assert sll.to_array() == [1, 10]
assert sll.size() == 2
assert sll.remove(1)
assert sll.to_array() == [10]
assert sll.size() == 1
assert sll.remove(10)
assert sll.to_array() == []
assert sll.size() == 0
# Teste 3: Erros
sll = SingleLinkedList()
assert sll.is_empty() == True
assert sll.to_array() == []
assert sll.size() == 0
sll.insert(15)
assert sll.is_empty() == False
assert sll.search(15) == 15
assert sll.search_index(15) == 0
assert sll.to_array() == [15]
assert sll.size() == 1
assert sll.remove(3) == None
assert sll.size() == 1
assert sll.to_array() == [15]
sll.insert(None)
assert sll.size() == 1
assert sll.to_array() == [15]
assert sll.remove(None) == None |
djrill/__init__.py | timgates42/Djrill | 172 | 11123152 | from ._version import __version__, VERSION
from .exceptions import (MandrillAPIError, MandrillRecipientsRefused,
NotSerializableForMandrillError, NotSupportedByMandrillError)
|
prod/stock_gj/run_es_restful_server.py | UtorYeung/vnpy | 323 | 11123162 | # flake8: noqa
import os
import sys
# 将repostory的目录i，作为根目录，添加到系统环境中。
ROOT_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..'))
sys.path.append(ROOT_PATH)
print(f'append {ROOT_PATH} into sys.path')
from vnpy.api.easytrader import server
server.run(port=1430)
|
DQMOffline/CalibTracker/test/CRAFTCalib/SiStripDQMBadStrips_cfg.py | ckamtsikis/cmssw | 852 | 11123198 | <reponame>ckamtsikis/cmssw
import FWCore.ParameterSet.Config as cms
process = cms.Process( "SiStripDQMBadStrips" )
### Miscellanous ###
## Logging ##
process.options = cms.untracked.PSet(
wantSummary = cms.untracked.bool( True )
)
process.MessageLogger = cms.Service( "MessageLogger",
destinations = cms.untracked.vstring(
'cout'
),
cout = cms.untracked.PSet(
threshold = cms.untracked.string( 'INFO' )
)
)
## Profiling ##
# Memory #
process.SimpleMemoryCheck = cms.Service( "SimpleMemoryCheck",
ignoreTotal = cms.untracked.int32( 0 )
)
### Import ###
## Magnetic fiels ##
process.load( "Configuration.StandardSequences.MagneticField_38T_cff" )
## Geometry ##
process.load( "Configuration.StandardSequences.GeometryRecoDB_cff" )
## Calibration ##
# Global tag #
process.load( "Configuration.StandardSequences.FrontierConditions_GlobalTag_cff" )
process.GlobalTag.connect = 'frontier://FrontierProd/CMS_COND_21X_GLOBALTAG'
process.GlobalTag.globaltag = 'CRAFT_ALL_V4P::All'
process.es_prefer_GlobalTag = cms.ESPrefer(
'PoolDBESSource',
'GlobalTag'
)
# exclude masking
process.siStripQualityESProducer.ListOfRecordToMerge = cms.VPSet(
cms.PSet(
record = cms.string( 'SiStripDetCablingRcd' ),
tag = cms.string( '' )
),
cms.PSet(
record = cms.string( 'SiStripBadChannelRcd' ),
tag = cms.string( '' )
)
)
### SiStrip DQM ###
## Reconstruction ##
process.load( "DQM.SiStripMonitorClient.RecoForDQM_Cosmic_cff" )
## DQM modules ##
# SiStripMonitorCluster #
import DQM.SiStripMonitorCluster.SiStripMonitorCluster_cfi
process.siStripMonitorCluster = DQM.SiStripMonitorCluster.SiStripMonitorCluster_cfi.SiStripMonitorCluster.clone()
process.siStripMonitorCluster.OutputMEsInRootFile = False
process.siStripMonitorCluster.SelectAllDetectors = True
process.siStripMonitorCluster.StripQualityLabel = ''
process.siStripMonitorCluster.TH1ClusterPos.moduleswitchon = True
process.siStripMonitorCluster.TH1nClusters.layerswitchon = True
process.siStripMonitorCluster.TH1nClusters.moduleswitchon = False
process.siStripMonitorCluster.TH1ClusterStoN.moduleswitchon = False
process.siStripMonitorCluster.TH1ClusterStoNVsPos.moduleswitchon = True
process.siStripMonitorCluster.TH1ClusterNoise.moduleswitchon = False
process.siStripMonitorCluster.TH1NrOfClusterizedStrips.moduleswitchon = False
process.siStripMonitorCluster.TH1ModuleLocalOccupancy.moduleswitchon = False
process.siStripMonitorCluster.TH1ClusterCharge.moduleswitchon = False
process.siStripMonitorCluster.TH1ClusterWidth.moduleswitchon = False
### Input ###
## PoolSource ##
process.source = cms.Source( "PoolSource",
fileNames = cms.untracked.vstring(
'/store/data/Commissioning08/RandomTriggers/RAW/v1/000/068/665/422164BB-FEA8-DD11-85E7-001D09F24E39.root',
'/store/data/Commissioning08/RandomTriggers/RAW/v1/000/068/665/486C391B-00A9-DD11-807C-001D09F24498.root',
'/store/data/Commissioning08/RandomTriggers/RAW/v1/000/068/665/5AD8595F-04A9-DD11-8627-0030487A1FEC.root',
'/store/data/Commissioning08/RandomTriggers/RAW/v1/000/068/665/90E5BCC7-1DA9-DD11-813C-001617C3B70E.root',
'/store/data/Commissioning08/RandomTriggers/RAW/v1/000/068/665/BC010482-01A9-DD11-AC2D-001D09F28EA3.root',
'/store/data/Commissioning08/RandomTriggers/RAW/v1/000/068/665/F8554B2C-07A9-DD11-A5AC-001D09F244BB.root'
),
skipEvents = cms.untracked.uint32( 0 )
)
## Input steering ##
process.maxEvents = cms.untracked.PSet(
input = cms.untracked.int32( 100000 )
)
### Output ###
## DQM ##
process.load( "DQMServices.Core.DQM_cfg" )
process.DQM.collectorHost = ''
process.load( "DQMServices.Components.DQMEnvironment_cfi" )
process.dqmSaver.convention = 'Online'
process.dqmSaver.dirName = '/afs/cern.ch/cms/CAF/CMSCOMM/COMM_TRACKER/DQM/SiStrip/jobs/output'
process.dqmSaver.producer = 'DQM'
process.dqmSaver.saveByRun = 1
process.dqmSaver.saveAtJobEnd = True
process.dqmSaver.referenceHandling = 'qtests'
process.dqmEnv.subSystemFolder = 'SiStrip'
### Scheduling ###
## Paths ##
# DQM path #
process.p = cms.Path(
process.siStripDigis *
process.siStripZeroSuppression *
process.siStripClusters *
process.siStripMonitorCluster *
process.dqmSaver
)
|
modules/nltk_contrib/tiger/query/constraints.py | h4ck3rm1k3/NLP-project | 123 | 11123225 | <filename>modules/nltk_contrib/tiger/query/constraints.py
# -*- coding: utf-8 -*-
# Copyright © 2007-2008 Stockholm TreeAligner Project
# Author: <NAME> <<EMAIL>>
# Licensed under the GNU GPLv2
"""Contains the classes for constraint checking.
The code and the interfaces of this module are still subject to change. Please refer to the
inline comments for more information.
"""
from __future__ import with_statement
from nltk_contrib.tiger.query.exceptions import UndefinedNameError
from nltk_contrib.tiger.graph import NodeType
from nltk_contrib.tiger.index import ID, EDGE_LABEL, CONTINUITY, LEFT_CORNER, RIGHT_CORNER, TOKEN_ORDER, GORN_ADDRESS
from nltk_contrib.tiger.query import ast
from nltk_contrib.tiger.utils.enum import Enum, enum_member
from nltk_contrib.tiger.utils.factory import FactoryBase
DEFAULT_TYPES = (NodeType.UNKNOWN, NodeType.UNKNOWN)
# WARNING: This module is still subject to heavy change!
# FIXME: while the code is correct (well, the tests run through), it's
# also quite convoluted. There should be an easier way to do this,
# ideally one that allows to combine constraints over the same
# pair of nodes.
# This is also the reason why this code is not properly documented.
# the short story:
# A constraint must implement the class method setup_context, which will
# be called exactly once for each corpus, and may only be used for setting
# data in the evaluator context, which will also be handed into the
# from_op method.
# The plan is to rewrite this that each constraint takes a node and a list of nodes
# and returns those nodes that fulfill the constraint. This way, constraints
# can take advantage of natural ordering in some cases
# For evaluation, the check method will be called. For speed reasons,
# the check methods should not contain any branches.
class Direction(Enum):
LEFT_TO_RIGHT = enum_member()
RIGHT_TO_LEFT = enum_member()
NONE = enum_member()
BOTH = enum_member()
class Constraint(object):
__converters__ = {}
@classmethod
def setup_context(cls, context):
pass
@classmethod
def from_op(cls, op_node, var_types, ctx):
kwargs = {}
for modifier_name in cls.__attributes__:
conv = cls.__converters__.get(modifier_name, lambda *x: x[0])
kwargs[modifier_name] = conv(op_node.modifiers[modifier_name], cls, ctx)
kwargs["types"] = var_types
return cls(**kwargs)
def __init__(self, types, *args):
self._types = types
self._modifiers = args
def __ne__(self, other):
return not self.__eq__(other)
def __eq__(self, other):
return self.__class__ is other.__class__ and \
self._modifiers == other._modifiers
def get_complement(self):
assert self.__attributes__[-1] == "negated"
args = list(self._modifiers)
args[-1] = not args[-1]
return self.__class__(self._types, *args)
def __repr__(self):
return "%s(%s)" % (self.__class__.__name__, ", ".join(str(x) for x in self._modifiers))
def get_predicates(self, left, right):
return [], []
def get_node_variable_types(self):
return NodeType.UNKNOWN, NodeType.UNKNOWN
def get_singlematch_direction(self):
return Direction.NONE
class PrecedenceConstraint(Constraint):
__attributes__ = ("range", "negated")
def __init__(self, types = DEFAULT_TYPES, range = (1, 1), negated = False):
super(PrecedenceConstraint, self).__init__(types, range, negated)
self._negated = not negated
self._direction = Direction.NONE
if range == (1, 1):
if types == (NodeType.TERMINAL, NodeType.TERMINAL):
self.check = self.check_immedidate_tt
if self._negated:
self._direction = Direction.BOTH
else:
self.check = self.check_immediate
elif range == (1, ):
self.check = self.check_general
else:
self._min, self._max = range
self.check = self.ranged_check
def ranged_check(self, left_op, right_op, qc):
l = left_op if left_op[CONTINUITY] == 0 else qc.get_node(left_op[LEFT_CORNER])
r = right_op if right_op[CONTINUITY] == 0 else qc.get_node(right_op[LEFT_CORNER])
return (self._min <= r[TOKEN_ORDER] - l[TOKEN_ORDER] <= self._max) is self._negated
def check_general(self, left_op, right_op, qc):
l = left_op if left_op[CONTINUITY] == 0 else qc.get_node(left_op[LEFT_CORNER])
r = right_op if right_op[CONTINUITY] == 0 else qc.get_node(right_op[LEFT_CORNER])
return (l[TOKEN_ORDER] < r[TOKEN_ORDER]) is self._negated
def check_immediate(self, left_op, right_op, qc):
l = left_op if left_op[CONTINUITY] == 0 else qc.get_node(left_op[LEFT_CORNER])
r = right_op if right_op[CONTINUITY] == 0 else qc.get_node(right_op[LEFT_CORNER])
return (l[TOKEN_ORDER] == r[TOKEN_ORDER] - 1) is self._negated
def check_immedidate_tt(self, left_op, right_op, qc):
return (left_op[TOKEN_ORDER] == right_op[TOKEN_ORDER] - 1) is self._negated
def get_singlematch_direction(self):
return self._direction
class SiblingConstraint(Constraint):
__attributes__ = ("ordered", "negated")
def __init__(self, types = DEFAULT_TYPES, ordered = False, negated = False):
assert not (negated and ordered)
super(SiblingConstraint, self).__init__(types, ordered, negated)
if ordered:
self.check = self.check_ordered
elif negated:
self.check = self.check_negated
else:
self.check = self.check_normal
def check_negated(self, left_op, right_op, qc):
return len(left_op[GORN_ADDRESS]) != len(right_op[GORN_ADDRESS]) \
or left_op[GORN_ADDRESS][:-1] != right_op[GORN_ADDRESS][:-1]
def check_normal(self, left_op, right_op, qc):
return len(left_op[GORN_ADDRESS]) == len(right_op[GORN_ADDRESS]) \
and left_op[GORN_ADDRESS][:-1] == right_op[GORN_ADDRESS][:-1]
def check_ordered(self, left_op, right_op, qc):
if len(left_op[GORN_ADDRESS]) == len(right_op[GORN_ADDRESS]) \
and left_op[GORN_ADDRESS][:-1] == right_op[GORN_ADDRESS][:-1]:
l = left_op if left_op[CONTINUITY] == 0 else qc.get_node(left_op[LEFT_CORNER])
r = right_op if right_op[CONTINUITY] == 0 else qc.get_node(right_op[LEFT_CORNER])
return l[TOKEN_ORDER] < r[TOKEN_ORDER]
else:
return False
def guarded(func, exc_type, new_exc_factory, *args, **kwargs):
try:
return func(*args, **kwargs)
except exc_type, e:
raise new_exc_factory(e)
from contextlib import contextmanager
@contextmanager
def convert_exception(exc_type, new_exc_type, args = lambda exc: exc.args):
try:
yield
except exc_type, e:
raise new_exc_type, args(e)
def _get_label_id(label, dct, domain):
with convert_exception(KeyError, UndefinedNameError, lambda exc: (domain, exc.args[0])):
return dct[label]
class DominanceConstraint(Constraint):
class ChildrenTypePredicate(object):
def get_query_fragment(self):
return "node_data.token_order > 1"
def __eq__(self, other):
return self.__class__ is other.__class__
def __ne__(self, other):
return not self.__eq__(other)
FOR_NODE = True
class EdgeLabelPredicate(object):
def __init__(self, label_id):
self._label_id = label_id
def get_query_fragment(self):
return "edge_label = %i" % (self._label_id)
def __eq__(self, other):
return self.__class__ == other.__class__ and self._label_id == other._label_id
def __ne__(self, other):
return not self.__eq__(other)
FOR_NODE = True
__attributes__ = ("label", "range", "negated")
__converters__ = {
"label": lambda l, cls, ctx: _get_label_id(l, ctx.edge_label_map,
UndefinedNameError.EDGELABEL)
}
@classmethod
def setup_context(cls, context):
context.edge_label_map = dict(context.db.execute("SELECT label, id FROM edge_labels"))
context.edge_label_map[None] = None
def __init__(self, types = DEFAULT_TYPES, label = None, range = (1, 1), negated = False):
super(DominanceConstraint, self).__init__(types, label, range, negated)
self._lbl = label
self._negated = not negated
self._direction = Direction.NONE
if range == (1, 1):
if self._negated:
self._direction = Direction.RIGHT_TO_LEFT
if self._lbl is None:
self.check = self.check_immediate
else:
self.check = self.check_immediate_lbl
elif range == (1, ):
assert label is None
if negated:
self.check = self.check_general_ngt
else:
self.check = self.check_general
else:
assert label is None
self._min, self._max = range
self.check = self.ranged_check
def ranged_check(self, left_op, right_op, qc):
l = len(left_op[GORN_ADDRESS])
r = len(right_op[GORN_ADDRESS])
return (self._min <= r - l <= self._max and
buffer(right_op[GORN_ADDRESS][:l]) == left_op[GORN_ADDRESS]) is self._negated
def check_general_ngt(self, left_op, right_op, qc):
l = len(left_op[GORN_ADDRESS])
r = len(right_op[GORN_ADDRESS])
return not (r - l > 0 and buffer(right_op[GORN_ADDRESS][:l]) == left_op[GORN_ADDRESS])
def check_general(self, left_op, right_op, qc):
l = len(left_op[GORN_ADDRESS])
r = len(right_op[GORN_ADDRESS])
return (r - l > 0 and buffer(right_op[GORN_ADDRESS][:l]) == left_op[GORN_ADDRESS])
def check_immediate(self, left_op, right_op, qc):
l = len(left_op[GORN_ADDRESS])
r = len(right_op[GORN_ADDRESS])
return (r - l == 1 and buffer(right_op[GORN_ADDRESS][:l]) == left_op[GORN_ADDRESS]) \
is self._negated
def check_immediate_lbl(self, left_op, right_op, qc):
l = len(left_op[GORN_ADDRESS])
r = len(right_op[GORN_ADDRESS])
return (r - l == 1 and buffer(right_op[GORN_ADDRESS][:l]) == left_op[GORN_ADDRESS] \
and right_op[EDGE_LABEL] == self._lbl) is self._negated
def get_predicates(self, left, right):
l = []
if right.var_type is NodeType.NONTERMINAL:
l.append(self.ChildrenTypePredicate())
return l, [self.EdgeLabelPredicate(self._lbl)] if self._lbl is not None else []
def get_node_variable_types(self):
return NodeType.NONTERMINAL, NodeType.UNKNOWN
def get_singlematch_direction(self):
return self._direction
class SecEdgeConstraint(Constraint):
class SecEdgePredicate(object):
# secedges.label_id is not indexed, therefore it is cheaper to load
# all secedges and then check for the correct labels later
ORIGIN = 0
TARGET = 1
_ID_NAMES = ["origin_id", "target_id"]
def __init__(self, node):
self._node = node
def get_query_fragment(self):
return "(SELECT COUNT(*) FROM secedges WHERE secedges.%s = node_data.id) > 0" % (
self._ID_NAMES[self._node], )
def __eq__(self, other):
return self.__class__ == other.__class__ and self._node == other._node
def __ne__(self, other):
return not self.__eq__(other)
FOR_NODE = True
__attributes__ = ("label", "negated")
__converters__ = {
"label": lambda l, cls, ctx: _get_label_id(l, ctx.secedge_label_map,
UndefinedNameError.SECEDGELABEL)
}
@classmethod
def setup_context(cls, ev_context):
ev_context.secedge_label_map = \
dict(ev_context.db.execute("SELECT label, id FROM secedge_labels"))
ev_context.secedge_label_map[None] = None
def __init__(self, types = DEFAULT_TYPES, label = None, negated = False):
super(SecEdgeConstraint, self).__init__(types, label, negated)
self._lbl = label
self._neg = negated
def check(self, left_op, right_op, query_context):
if self._lbl is not None:
query_context.cursor.execute(
"""SELECT origin_id FROM secedges
WHERE origin_id = ? AND target_id = ? AND label_id = ?""",
(left_op[ID], right_op[ID], self._lbl))
else:
query_context.cursor.execute("""SELECT origin_id FROM secedges
WHERE origin_id = ? AND target_id = ?""", (left_op[ID], right_op[ID]))
return (query_context.cursor.fetchone() is None) is self._neg
def get_predicates(self, left, right):
return ([self.SecEdgePredicate(self.SecEdgePredicate.ORIGIN)],
[self.SecEdgePredicate(self.SecEdgePredicate.TARGET)])
class CornerConstraint(Constraint):
_IDX = {"l": LEFT_CORNER,
"r": RIGHT_CORNER}
__attributes__ = ("corner", "negated")
__converters__ = {
"corner": lambda c, cls, ctx: cls._IDX[c]
}
def __init__(self, types, corner, negated = False):
super(CornerConstraint, self).__init__(types, corner, negated)
if negated:
self.check = lambda l, r, qc: l[corner] != r[ID] and not (r[ID] == l[ID] and \
l[CONTINUITY] == 0)
else:
self.check = lambda l, r, qc: l[corner] == r[ID] or r[ID] == l[ID] and\
l[CONTINUITY] == 0
def get_node_variable_types(self):
return NodeType.UNKNOWN, NodeType.TERMINAL
class ConstraintFactory(FactoryBase):
__classes__ = {
ast.SiblingOperator: SiblingConstraint,
ast.PrecedenceOperator: PrecedenceConstraint,
ast.CornerOperator: CornerConstraint,
ast.SecEdgeOperator: SecEdgeConstraint,
ast.DominanceOperator: DominanceConstraint
}
def _create_instance(self, cls, op_node, var_types, context):
return cls.from_op(op_node, var_types, context)
def _get_switch(self, op_node, var_types, context):
return op_node.TYPE
|
examples/origin_str.py | huihui7987/blind_watermark | 1,699 | 11123299 | <filename>examples/origin_str.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# embed string
import numpy as np
from blind_watermark import WaterMark
bwm1 = WaterMark(password_img=1, password_wm=1)
bwm1.read_img('pic/ori_img.jpg')
wm = '@guofei9987 开源万岁！'
bwm1.read_wm(wm, mode='str')
bwm1.embed('output/embedded.png')
len_wm = len(bwm1.wm_bit)
print('Put down the length of wm_bit {len_wm}'.format(len_wm=len_wm))
# %% 解水印
bwm1 = WaterMark(password_img=1, password_wm=1)
wm_extract = bwm1.extract('output/embedded.png', wm_shape=len_wm, mode='str')
print(wm_extract)
assert wm == wm_extract, '提取水印和原水印不一致'
|
tests/test_fragment_select.py | zverok/wikipedia_ql | 334 | 11123301 | <gh_stars>100-1000
import re
import pytest
from bs4 import BeautifulSoup
from wikipedia_ql.fragment import Fragment
from wikipedia_ql.selectors import text, text_group, sentence, section, css, alt, page
def make_fragment(html):
# Because fragment is Wikipedia-oriented and always looks for this div :shrug:
return Fragment.parse(f'<div class="mw-parser-output">{html.strip()}</div>')
def h(html):
return re.sub(r'\s+<', '<', re.sub(r'>\s+', '>', html))
def apply(fragment, selector, simplify=False):
if simplify:
return [h(str(f.soup)) for f in fragment._select(selector)]
else:
return [str(f.soup) for f in fragment._select(selector)]
def test_select_text():
def select(html, selector):
return apply(make_fragment(html), text(pattern=selector))
assert select("""
<h2>Header</h2>
<p>Paragraph with a <a href="foo">link</a>. And <b>bold</b> text.</p>
""",
'with a link') == ['<span>with a <a href="foo">link</a></span>']
def test_select_section():
def select(fragment, **args):
return apply(fragment, section(**args), simplify=True)
fragment = make_fragment("""
<section>
<h2>Section1</h2>
<p>Text1</p>
<section>
<h3>Section1.1</h3>
<p>Text2</p>
</section>
<section>
<h3>Section1.2</h3>
<p>Text4</p>
</section>
</section>
<section>
<h2>Section2</h2>
<p>Text5</p>
</section>
""")
assert select(fragment, heading='Section1') == [
h("""
<div>
<h2>Section1</h2>
<p>Text1</p>
<section>
<h3>Section1.1</h3>
<p>Text2</p>
</section>
<section>
<h3>Section1.2</h3>
<p>Text4</p>
</section>
</div>
"""),
h("""
<div>
<h3>Section1.1</h3>
<p>Text2</p>
</div>
"""),
h("""
<div>
<h3>Section1.2</h3>
<p>Text4</p>
</div>
""")
]
assert select(fragment, heading='Section1.1') == [
h("""
<div>
<h3>Section1.1</h3>
<p>Text2</p>
</div>
""")
]
assert select(fragment, heading='Section2') == [
h("""
<div>
<h2>Section2</h2>
<p>Text5</p>
</div>
""")
]
# TODO:
# all
# by level
# intersecting sections?..
# text pattern (include, start/stop with, regexp)
def test_select_css():
def select(fragment, css_selector):
return apply(fragment, css(css_selector=css_selector), simplify=True)
fragment = make_fragment("""
<h2>Section1</h2>
<p>Text1</p>
<ul>
<li><a class="first">Link1</a></li>
<li class="item"><a class="second">Link2</a>text</li>
</ul>
""")
assert select(fragment, '.item') == [
h("""
<li class="item"><a class="second">Link2</a>text</li>
""")
]
def test_select_sentence():
def select(fragment, pattern):
return apply(fragment, sentence(pattern=pattern))
fragment = make_fragment(
"""
<p>This is <b>sentence</b> one. This is phrase <a href="foo">two.</a> This is NOT</p>
<p>sentence three, probably!</p>
"""
)
assert select(fragment, 'one') == ['<span>This is <b>sentence</b> one.</span>']
assert select(fragment, 'This.+two') == ['<span>This is phrase <a href="foo">two.</a></span>']
assert select(fragment, 'This.+three') == []
assert select(fragment, None) == [
'<span>This is <b>sentence</b> one.</span>',
'<span>This is phrase <a href="foo">two.</a></span>',
'This is NOT', # the whole text after </a>
'sentence three, probably!' # takes the whole paragraph, that's why no span
]
def test_select_nested():
def select(fragment, selector):
return [str(f.soup) for f in fragment.select(selector)]
fragment = make_fragment("""
<section>
<h2>Section1</h2>
<p>Text1</p>
<ul>
<li><a class="first">Link1</a></li>
<li class="item"><a class="second">Link2</a>text</li>
</ul>
</section>
""")
selector = section(heading='Section1', nested=css(css_selector='ul', nested=text(pattern='Li...')))
assert select(fragment, selector) \
== ['<a class="first">Link1</a>', '<a class="second">Link2</a>']
# edge case: css selector of top-level node:
selector = text(pattern='Link1', nested=css(css_selector='a'))
assert select(fragment, selector) == ['<a class="first">Link1</a>']
def test_select_alt():
def select(fragment, *selectors):
return apply(fragment, alt(*selectors), simplify=True)
fragment = make_fragment("""
<h2>Section1</h2>
<p>Text1</p>
<ul>
<li><a class="first">Link1</a></li>
<li class="item"><a class="second">Link2</a>text</li>
</ul>
""")
assert select(fragment, text(pattern='Link1'), css(css_selector='a.second')) == \
['<a class="first">Link1</a>', '<a class="second">Link2</a>']
def test_select_text_group():
def select(fragment, id):
return apply(fragment, text_group(group_id=id))
fragment = make_fragment(
'<p>Some paragraph with <b>empasis</b> and <a href="#foo">link</a></p>'
)
assert select(fragment.select(text(pattern=r'with (\S+ and) li(.*)')), 1) == [
'<span><b>empasis</b> and</span>'
]
# When not after text
with pytest.raises(ValueError, match='text-group is only allowed after text'):
select(fragment, 1)
# When slice index is out of range
assert select(fragment.select(text(pattern=r'with (\S+ and) li(.*)')), 10) == []
# Named groups
assert select(fragment.select(text(pattern=r'with (?P<group1>\S+ and) li(.*)')), 'group1') == [
'<span><b>empasis</b> and</span>'
]
# Non-existent group:
assert select(fragment.select(text(pattern=r'with (?P<group1>\S+ and) li(.*)')), 'group2') == []
def test_select_page():
fragment = make_fragment("""
<h2>Section1</h2>
<p>Text1</p>
<ul>
<li><a class="first">Link1</a></li>
<li class="item"><a class="second">Link2</a>text</li>
</ul>
""")
assert str(fragment.select(page()).items[0].soup) == str(fragment.soup)
assert str(fragment.select(css(css_selector='li', nested=page())).items[0].soup) == str(fragment.soup)
# TODO: (laterz!) wikitable, infobox, ...
|
packages/vaex-astro/vaex/astro/tap.py | sethvargo/vaex | 337 | 11123308 | import numpy as np
from vaex.dataset import DatasetArrays
class DatasetTap(DatasetArrays):
class TapColumn(object):
def __init__(self, tap_dataset, column_name, column_type, ucd):
self.tap_dataset = tap_dataset
self.column_name = column_name
self.column_type = column_type
self.ucd = ucd
self.alpha_min = 0
length = len(tap_dataset)
steps = length/1e6 # try to do it in chunks
self.alpha_step = 360/steps
self.alpha_max = self.alpha_min + self.alpha_step
logger.debug("stepping in alpha %f" % self.alpha_step)
self.data = []
self.offset = 0
self.shape = (length,)
self.dtype = DatasetTap.type_map[self.column_type]().dtype
self.left_over_chunk = None
self.rows_left = length
import tempfile
self.download_file = tempfile.mktemp(".vot")
def __getitem__(self, slice):
start, stop, step = slice.start, slice.stop, slice.step
required_length = stop - start
assert start >= self.offset
chunk_data = self.left_over_chunk
enough = False if chunk_data is None else len(chunk_data) >= required_length
if chunk_data is not None:
logger.debug("start %s offset %s chunk length %s", start, self.offset, len(chunk_data))
#assert len(chunk_data) == start - self.offset
if enough:
logger.debug("we can skip the query, already have results from previous query")
while not enough:
adql_query = "SELECT {column_name} FROM {table_name} WHERE alpha >= {alpha_min} AND alpha < {alpha_max} ORDER BY alpha ASC"\
.format(column_name=self.column_name, table_name=self.tap_dataset.table_name, alpha_min=self.alpha_min, alpha_max=self.alpha_max)
logger.debug("executing: %s" % adql_query)
logger.debug("executing: %s" % adql_query.replace(" ", "+"))
url = self.tap_dataset.tap_url + "/sync?REQUEST=doQuery&LANG=ADQL&MAXREC=10000000&FORMAT=votable&QUERY=" +adql_query.replace(" ", "+")
import urllib2
response = urllib2.urlopen(url)
with open(self.download_file, "w") as f:
f.write(response.read())
votable = astropy.io.votable.parse(self.download_file)
data = votable.get_first_table().array[self.column_name].data
# TODO: respect masked array
#table = astropy.table.Table.read(url, format="votable") #, show_progress=False)
#data = table[self.column_name].data.data.data
logger.debug("new chunk is of lenght %d", len(data))
self.rows_left -= len(data)
logger.debug("rows left %d", self.rows_left)
if chunk_data is None:
chunk_data = data
else:
chunk_data = np.concatenate([chunk_data, data])
if len(chunk_data) >= required_length:
enough = True
logger.debug("total chunk is of lenght %d, enough: %s", len(chunk_data), enough)
self.alpha_min += self.alpha_step
self.alpha_max += self.alpha_step
result, self.left_over_chunk = chunk_data[:required_length], chunk_data[required_length:]
#print(result)
logger.debug("left over is of length %d", len(self.left_over_chunk))
return result #np.zeros(N, dtype=self.dtype)
type_map = {
'REAL':np.float32,
'SMALLINT':np.int32,
'DOUBLE':np.float64,
'BIGINT':np.int64,
'INTEGER':np.int32,
'BOOLEAN':np.bool8
}
#not supported types yet 'VARCHAR',', u'BOOLEAN', u'INTEGER', u'CHAR
def __init__(self, tap_url="http://gaia.esac.esa.int/tap-server/tap/g10_smc", table_name=None):
logger.debug("tap url: %r", tap_url)
self.tap_url = tap_url
self.table_name = table_name
if table_name is None: # let us try to infer the table name
if tap_url.endswith("tap") or tap_url.endswith("tap/"):
pass # this mean we really didn't provide one
else:
index = tap_url.rfind("tap/")
if index != -1:
self.tap_url, self.table_name = tap_url[:index+4], self.tap_url[index+4:]
logger.debug("inferred url is %s, and table name is %s", self.tap_url, self.table_name)
if self.tap_url.startswith("tap+"): # remove tap+ part from tap+http(s), only keep http(s) part
self.tap_url = self.tap_url[len("tap+"):]
import requests
super(DatasetTap, self).__init__(self.table_name)
self.req = requests.request("get", self.tap_url+"/tables/")
self.path = "tap+" +self.tap_url + "/" + table_name
#print dir(self.req)
from bs4 import BeautifulSoup
#self.soup = BeautifulSoup(req.response)
tables = BeautifulSoup(self.req.content, 'xml')
self.tap_tables = collections.OrderedDict()
for table in tables.find_all("table"):
#print table.find("name").string, table.description.string, table["gaiatap:size"]
table_name = unicode(table.find("name").string)
table_size = int(table["esatapplus:size"])
#print table_name, table_size
logger.debug("tap table %r ", table_name)
columns = []
for column in table.find_all("column"):
column_name = unicode(column.find("name").string)
column_type = unicode(column.dataType.string)
ucd = column.ucd.string if column.ucd else None
unit = column.unit.string if column.unit else None
description = column.description.string if column.description else None
#print "\t", column_name, column_type, ucd
#types.add()
columns.append((column_name, column_type, ucd, unit, description))
self.tap_tables[table_name] = (table_size, columns)
if not self.tap_tables:
raise ValueError("no tables or wrong url")
for name, (table_size, columns) in self.tap_tables.items():
logger.debug("table %s has length %d", name, table_size)
self._full_length, self._tap_columns = self.tap_tables[self.table_name]
self._length = self._full_length
logger.debug("selected table table %s has length %d", self.table_name, self._full_length)
#self.column_names = []
#self.columns = collections.OrderedDict()
for column_name, column_type, ucd, unit, description in self._tap_columns:
logger.debug(" column %s has type %s and ucd %s, unit %s and description %s", column_name, column_type, ucd, unit, description)
if column_type in self.type_map.keys():
self.column_names.append(column_name)
if ucd:
self.ucds[column_name] = ucd
if unit:
self.units[column_name] = unit
if description:
self.descriptions[column_name] = description
self.columns[column_name] = self.TapColumn(self, column_name, column_type, ucd)
else:
logger.warning(" type of column %s is not supported, it will be skipped", column_name)
@classmethod
def open(cls, path, *args, **kwargs):
return cls(path, *args, **kwargs)
@classmethod
def quick_test(cls, path, *args, **kwargs):
return False
@classmethod
def can_open(cls, path, *args, **kwargs):
can_open = False
url = None
try:
url = urlparse(path)
except:
return False
if url.scheme:
if url.scheme.startswith("tap+http"): # will also catch https
can_open = True
logger.debug("%r can open: %r" %(cls.__name__, can_open))
return can_open
|
Face Reconstruction/Fast Few-shot Face alignment by Reconstruction/constants.py | swapnilgarg7/Face-X | 175 | 11123310 | TRAIN = 'train'
VAL = 'val'
TEST = 'test'
|
tests/regressiontests/id_package.py | kylehodgson/SimpleIDML | 136 | 11123348 | <reponame>kylehodgson/SimpleIDML
# -*- coding: utf-8 -*-
import os
import unittest
from simple_idml.id_package import ZipInDesignPackage
from simple_idml.id_package import merge_font_lst
CURRENT_DIR = os.path.dirname(__file__)
IDMLFILES_DIR = os.path.join(CURRENT_DIR, "IDML")
class ZipInDesignPackageTestCase(unittest.TestCase):
def test_get_font_list(self):
archive_name = os.path.join(IDMLFILES_DIR, "article-1photo-package.zip")
zip_indesign_package = ZipInDesignPackage(archive_name, "r")
self.assertEqual(
set(zip_indesign_package.get_font_list()),
set([('AdobeFnt13.lst', 'article-1photo-package/Document fonts/AdobeFnt13.lst'),
('._AdobeFnt13.lst', '__MACOSX/article-1photo-package/Document fonts/._AdobeFnt13.lst'),
('MinionPro-Bold.otf', 'article-1photo-package/Document fonts/MinionPro-Bold.otf'),
('MinionPro-It.otf', 'article-1photo-package/Document fonts/MinionPro-It.otf'),
('MinionPro-Regular.otf', 'article-1photo-package/Document fonts/MinionPro-Regular.otf')])
)
class IDPackageTestCase(unittest.TestCase):
def test_merge_font_lst(self):
font_suitecases = [
("output/Document fonts/AdobeFnt13.lst", ""),
("output/Document fonts/AdobeFnt13.lst", ""),
("output/Document fonts/AdobeFnt13.lst", ""),
]
filename, content = merge_font_lst(font_suitecases)
self.assertEqual(content, "")
# The first file may not reference any font.
font_suitecases = [
("output/Document fonts/AdobeFnt13.lst", ""),
("output/Document fonts/AdobeFnt13.lst",
"""%!Adobe-FontList 1.13
%Locale:0x409
%BeginFont
Handler:DirectoryHandler
FontType:Suitcase
FontName:Times-Roman
OutlineFileName:\Times-Roman
ResourceID:20
MacStyle:0
FileLength:12882
FileModTime:1342371272
%EndFont
%BeginFont
Handler:DirectoryHandler
FontType:Type1
FontName:Times-Roman
FamilyName:Times
StyleName:Roman
MenuName:Times
StyleBits:0
WeightClass:400
WidthClass:5
AngleClass:0
FullName:Times Roman
WritingScript:Roman
OutlineFileName:\TimesRom
DataFormat:POSTResource
UsesStandardEncoding:yes
isCFF:no
FileLength:34006
FileModTime:1342371272
DesignSize:-1
%EndFont
"""),
("output/Document fonts/AdobeFnt13.lst",
"""%!Adobe-FontList 1.13
%Locale:0x409
%BeginFont
Handler:DirectoryHandler
FontType:Suitcase
FontName:AGaramond-BoldItalic
OutlineFileName:\AGaramond-BoldItalic.ECR
ResourceID:14570
MacStyle:0
FileLength:10327
FileModTime:1341477738
%EndFont
%BeginFont
Handler:DirectoryHandler
FontType:Suitcase
FontName:AGaramond-Regular
OutlineFileName:\AGaramond-Regular.ECR
ResourceID:14562
MacStyle:0
FileLength:18702
FileModTime:1341477705
%EndFont
%BeginFont
Handler:DirectoryHandler
FontType:Type1
FontName:AGaramond-BoldItalic
FamilyName:Adobe Garamond
StyleName:Bold Italic
MenuName:AGaramond Bold
StyleBits:3
WeightClass:700
WidthClass:5
AngleClass:1
FullName:Adobe Garamond Bold Italic
WritingScript:Roman
OutlineFileName:\AGarBolIta
DataFormat:POSTResource
UsesStandardEncoding:yes
isCFF:no
FileLength:45072
FileModTime:1341477738
DesignSize:-1
%EndFont
%BeginFont
Handler:DirectoryHandler
FontType:Type1
FontName:AGaramond-Regular
FamilyName:Adobe Garamond
StyleName:Regular
MenuName:AGaramond
StyleBits:0
WeightClass:400
WidthClass:5
AngleClass:0
FullName:Adobe Garamond Regular
WritingScript:Roman
OutlineFileName:\AGarReg
DataFormat:POSTResource
UsesStandardEncoding:yes
isCFF:no
FileLength:45376
FileModTime:1341477705
DesignSize:-1
%EndFont
""")]
filename, content = merge_font_lst(font_suitecases)
self.assertEqual(content,
"""%!Adobe-FontList 1.13
%Locale:0x409
%BeginFont
Handler:DirectoryHandler
FontType:Suitcase
FontName:Times-Roman
OutlineFileName:\Times-Roman
ResourceID:20
MacStyle:0
FileLength:12882
FileModTime:1342371272
%EndFont
%BeginFont
Handler:DirectoryHandler
FontType:Type1
FontName:Times-Roman
FamilyName:Times
StyleName:Roman
MenuName:Times
StyleBits:0
WeightClass:400
WidthClass:5
AngleClass:0
FullName:Times Roman
WritingScript:Roman
OutlineFileName:\TimesRom
DataFormat:POSTResource
UsesStandardEncoding:yes
isCFF:no
FileLength:34006
FileModTime:1342371272
DesignSize:-1
%EndFont
%BeginFont
Handler:DirectoryHandler
FontType:Suitcase
FontName:AGaramond-BoldItalic
OutlineFileName:\AGaramond-BoldItalic.ECR
ResourceID:14570
MacStyle:0
FileLength:10327
FileModTime:1341477738
%EndFont
%BeginFont
Handler:DirectoryHandler
FontType:Suitcase
FontName:AGaramond-Regular
OutlineFileName:\AGaramond-Regular.ECR
ResourceID:14562
MacStyle:0
FileLength:18702
FileModTime:1341477705
%EndFont
%BeginFont
Handler:DirectoryHandler
FontType:Type1
FontName:AGaramond-BoldItalic
FamilyName:Adobe Garamond
StyleName:Bold Italic
MenuName:AGaramond Bold
StyleBits:3
WeightClass:700
WidthClass:5
AngleClass:1
FullName:Adobe Garamond Bold Italic
WritingScript:Roman
OutlineFileName:\AGarBolIta
DataFormat:POSTResource
UsesStandardEncoding:yes
isCFF:no
FileLength:45072
FileModTime:1341477738
DesignSize:-1
%EndFont
%BeginFont
Handler:DirectoryHandler
FontType:Type1
FontName:AGaramond-Regular
FamilyName:Adobe Garamond
StyleName:Regular
MenuName:AGaramond
StyleBits:0
WeightClass:400
WidthClass:5
AngleClass:0
FullName:Adobe Garamond Regular
WritingScript:Roman
OutlineFileName:\AGarReg
DataFormat:POSTResource
UsesStandardEncoding:yes
isCFF:no
FileLength:45376
FileModTime:1341477705
DesignSize:-1
%EndFont
""")
def test_merge_font_lst_1file(self):
font_suitecases = [
('21283009/Document fonts/AdobeFnt13.lst',
"""%!Adobe-FontList 1.13
%Locale:0x409
%BeginFont
Handler:DirectoryHandler
FontType:Suitcase
FontName:AGaramond-Bold
OutlineFileName:\\AGaramond-Bold.ECR
ResourceID:14571
MacStyle:0
FileLength:12909
FileModTime:1341477750
%EndFont
%BeginFont
Handler:DirectoryHandler
FontType:Type1
FontName:AGaramond-Bold
FamilyName:Adobe Garamond
StyleName:Bold
MenuName:AGaramond Bold
StyleBits:2
WeightClass:700
WidthClass:5
AngleClass:0
FullName:Adobe Garamond Bold
WritingScript:Roman
OutlineFileName:\\AGarBol
DataFormat:POSTResource
UsesStandardEncoding:yes
isCFF:no
FileLength:46237
FileModTime:1341477750
DesignSize:-1
%EndFont
""")
]
filename, content = merge_font_lst(font_suitecases)
self.assertEqual(content, '%!Adobe-FontList 1.13\n%Locale:0x409\n\n%BeginFont\nHandler:DirectoryHandler\nFontType:Suitcase\nFontName:AGaramond-Bold\nOutlineFileName:\\AGaramond-Bold.ECR\nResourceID:14571\nMacStyle:0\nFileLength:12909\nFileModTime:1341477750\n%EndFont\n\n%BeginFont\nHandler:DirectoryHandler\nFontType:Type1\nFontName:AGaramond-Bold\nFamilyName:Adobe Garamond\nStyleName:Bold\nMenuName:AGaramond Bold\nStyleBits:2\nWeightClass:700\nWidthClass:5\nAngleClass:0\nFullName:Adobe Garamond Bold\nWritingScript:Roman\nOutlineFileName:\\AGarBol\nDataFormat:POSTResource\nUsesStandardEncoding:yes\nisCFF:no\nFileLength:46237\nFileModTime:1341477750\nDesignSize:-1\n%EndFont\n\n')
def suite():
suite = unittest.TestLoader().loadTestsFromTestCase(ZipInDesignPackageTestCase)
suite.addTests(unittest.TestLoader().loadTestsFromTestCase(IDPackageTestCase))
return suite
|
commandment/pki/ca.py | pythonModule/commandment | 138 | 11123352 | <gh_stars>100-1000
from flask import g, current_app
import sqlalchemy.orm.exc
from .models import CertificateAuthority
from commandment.models import db, Device
from commandment.pki.models import CertificateType, Certificate
def get_ca() -> CertificateAuthority:
if 'ca' not in g:
try:
ca = db.session.query(CertificateAuthority).filter_by(common_name='COMMANDMENT-CA').one()
except sqlalchemy.orm.exc.NoResultFound:
ca = CertificateAuthority.create()
g.ca = ca
return g.ca
#
# @current_app.teardown_appcontext
# def teardown_ca():
# ca = g.pop('ca', None)
|
generators/datagenerator/segment.py | honey-sangtani-c5i/retail-demo-store | 404 | 11123389 | # Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: MIT-0
import datagenerator
import json
import requests
# Segment event support
# This follows the Segment HTTP API spec, here:
# https://segment.com/docs/connections/sources/catalog/libraries/server/http-api/
#
# These classes accept a user, platform, and general event properties and map them
# a Segment API compatible representation. This does not support implicit identify
# traits
class SegmentEvent:
def __init__(self, timestamp, user, platform):
self.timestamp = timestamp.isoformat()
self.sentAt = timestamp.isoformat()
self.userId = user.id
context = {
'library': {
'version': datagenerator.aws_datagenerator_version,
'name': 'AWSEventGen'
}
}
platform_data = user.get_platform_data(platform)
self.anonymousId = platform_data['anonymous_id']
if platform == 'ios':
context['device'] = {
'advertisingId': platform_data['advertising_id'],
'manufacturer': 'tim_apple',
'model': platform_data['model'],
'version': platform_data['version']
}
elif platform == 'android':
context['device'] = {
'advertisingId': platform_data['advertising_id'],
'manufacturer': 'google',
'model': platform_data['model'],
'version': platform_data['version']
}
else:
context['userAgent'] = platform_data['user_agent']
self.context = context
self.integrations = {
'All': True
}
def toJson(self):
return self.__repr__()
def __repr__(self):
return json.dumps(self.__dict__)
class SegmentIdentifyEvent(SegmentEvent):
def __init__(self, timestamp, user, platform):
super().__init__(timestamp, user, platform)
self.type = 'identify'
self.traits = user.traits
self.traits['name'] = user.name
self.traits['email'] = user.email
self.traits['age'] = user.age
self.traits['gender'] = user.gender
self.traits['persona'] = user.persona
self.traits['username'] = user.username
class SegmentTrackEvent(SegmentEvent):
def __init__(self, name, timestamp, user, platform, properties):
super().__init__(timestamp, user, platform)
self.event = name
self.type = 'track'
self.properties = properties
class SegmentSender:
def __init__(self, config):
self.config_keys = config # MUST BE: { 'ios': <write key | none>, 'android': <write key | none>, 'web': <write key | none> }
self.endpoint = 'https://api.segment.io/v1/batch'
def send_batch(self, platform, events, debug=False):
batch_events = {
"batch": events
}
key = self.config_keys[platform]
if key != None:
events_str = json.dumps(batch_events, default=lambda x: x.__dict__)
#print(f'Batch length bytes: {len(events_str)}')
if debug:
parsed = json.loads(events_str)
print(f'{json.dumps(parsed, indent=4)}')
response = None
else:
response = requests.post(self.endpoint,
data=events_str,
auth=(self.config_keys[platform], ''))
#print(self.config_keys[platform])
#print(json.dumps(batch_events, default=lambda x: x.__dict__))
#print(f'Sent {len(batch_events["batch"])} events and got {response}')
return response
else:
return None
|
paz/datasets/fat.py | niqbal996/paz | 300 | 11123395 | import os
from glob import glob
import json
import numpy as np
from tensorflow.keras.utils import Progbar
from ..abstract import Loader
from .utils import get_class_names
class FAT(Loader):
""" Dataset loader for the falling things dataset (FAT).
# Arguments
path: String indicating full path to dataset
e.g. /home/user/fat/
split: String determining the data split to load.
e.g. `train`, `val` or `test`
class_names: `all` or list. If list it should contain as elements
strings indicating each class name.
# References
- [Deep Object Pose
Estimation (DOPE)](https://github.com/NVlabs/Deep_Object_Pose)
"""
# TODO: Allow selection of class_names.
def __init__(self, path, split='train', class_names='all'):
if class_names == 'all':
class_names = get_class_names('FAT')
self.class_to_arg = dict(
zip(class_names, list(range(len(class_names)))))
super(FAT, self).__init__(path, split, class_names, 'FAT')
def load_data(self):
scene_names = glob(self.path + 'mixed/*')
image_paths, label_paths = [], []
for scene_name in scene_names:
scene_image_paths, scene_label_paths = [], []
for image_side in ['left', 'right']:
image_names = glob(scene_name + '/*%s.jpg' % image_side)
side_image_paths = sorted(image_names, key=self._base_number)
label_names = glob(scene_name + '/0*%s.json' % image_side)
side_label_paths = sorted(label_names, key=self._base_number)
scene_image_paths = scene_image_paths + side_image_paths
scene_label_paths = scene_label_paths + side_label_paths
image_paths = image_paths + scene_image_paths
label_paths = label_paths + scene_label_paths
self.data = []
progress_bar = Progbar(len(image_paths))
for sample_arg, sample in enumerate(zip(image_paths, label_paths)):
image_path, label_path = sample
if not self._valid_name_match(image_path, label_path):
raise ValueError('Invalid name match:', image_path, label_path)
boxes = self._extract_boxes(label_path)
if boxes is None:
continue
self.data.append({'image': image_path, 'boxes': boxes})
progress_bar.update(sample_arg + 1)
return self.data
def _extract_boxes(self, json_filename):
json_data = json.load(open(json_filename, 'r'))
num_objects = len(json_data['objects'])
if num_objects == 0:
return None
box_data = np.zeros((num_objects, 5))
for object_arg, object_data in enumerate(json_data['objects']):
bounding_box = object_data['bounding_box']
y_min, x_min = bounding_box['top_left']
y_max, x_max = bounding_box['bottom_right']
x_min, y_min = x_min / 960., y_min / 540.
x_max, y_max = x_max / 960., y_max / 540.
box_data[object_arg, :4] = x_min, y_min, x_max, y_max
class_name = object_data['class'][:-4]
box_data[object_arg, -1] = self.class_to_arg[class_name]
return box_data
def _base_number(self, filename):
order = os.path.basename(filename)
order = order.split('.')[0]
order = float(order)
return order
def _valid_name_match(self, image_path, label_path):
image_name = os.path.basename(image_path)
label_name = os.path.basename(label_path)
return image_name[:-3] == label_name[:-4]
|
Python/demos/d13_HelicalGeometry.py | tsadakane/TIGRE | 326 | 11123439 | <reponame>tsadakane/TIGRE
#%% Demo 13: Helical Geometry tests
#
#
# This demo shows an example of TIGRE working on Helical scan geometries
#
# --------------------------------------------------------------------------
# --------------------------------------------------------------------------
# This file is part of the TIGRE Toolbox
#
# Copyright (c) 2015, University of Bath and
# CERN-European Organization for Nuclear Research
# All rights reserved.
#
# License: Open Source under BSD.
# See the full license at
# https://github.com/CERN/TIGRE/blob/master/LICENSE
#
# Contact: <EMAIL>
# Codes: https://github.com/CERN/TIGRE/
# Coded by: <NAME>
# --------------------------------------------------------------------------
##
#%%Initialize
import tigre
import numpy as np
from tigre.utilities import sample_loader
import tigre.algorithms as algs
import time
#%% Geometry
geo = tigre.geometry_default(high_resolution=False)
angles = np.linspace(0, 2 * np.pi, 100)
angles = np.hstack([angles, angles, angles]) # loop 3 times
# Load thorax phatom data
head = sample_loader.load_head_phantom(geo.nVoxel)
# This makes it helical
geo.offOrigin = np.zeros((angles.shape[0], 3))
geo.offOrigin[:, 2] = np.linspace(
-1024 / 2 + 128, 1024 / 2 - 128, angles.shape[0]
) # about 256^3 images fit int he detector with this size.
# project data
data = tigre.Ax(head, geo, angles)
# Uncomment if you want to see the data
# plotProj(data,angles);
## Reconstruct Helical
SIRTimg = algs.sirt(data, geo, angles, 30)
# SARTimg=SART(data,geo,angles,30); # takes time
CGLSimg = algs.cgls(data, geo, angles, 20)
## Plot results
# CGLS and SIRT
tigre.plotImg(np.concatenate([head, SIRTimg, CGLSimg], axis=1), dim="z", step=3, clims=[0, 1])
|
BlogPosts/Hyperparameter_tuning_comparison/hyperparameter_tuning_comparison_code.py | markgraves/roamresearch | 190 | 11123442 | """
Companion code for the Roam blog post on hyperparameter optimization.
"""
import itertools as it
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
from operator import itemgetter
import pandas as pd
import random
from scipy import stats
from time import time
from hyperopt import fmin, tpe, hp, STATUS_OK, Trials
from skopt import gp_minimize, forest_minimize, gbrt_minimize
from skopt.space import Categorical
from sklearn.datasets import make_classification
from sklearn.cross_validation import cross_val_score, StratifiedKFold
from sklearn.metrics import accuracy_score
from sklearn.linear_model import LogisticRegression
from xgboost import XGBClassifier
# Ignore these warnings, which are related to the bleeding
# edge sklearn we're using.
import warnings
import sklearn.metrics.base
warnings.filterwarnings("ignore", category=DeprecationWarning)
__author__ = '<NAME> and <NAME>'
__version__ = '1.0'
__license__ = 'Apache License Version 2.0, January 2004 http://www.apache.org/licenses/'
plt.style.use('../../src/roam.mplstyle')
LOG_LOSS = 'log_loss' # Newer versions will use 'neg_log_loss'
def artificial_dataset(
n_samples=1000,
n_features=100,
n_classes=3,
random_state=None):
"""
sklearn random classification dataset generation using
`sklearn.datasets.make_classification`.
Parameters
----------
n_samples : int
n_features : int
n_classes : int
random_state : int or None
Returns
-------
(X, y)
The design matrix `X` and target `y`.
"""
n_informative = int(0.8 * n_features)
n_redundant = int(0.05 * n_features)
X, y = make_classification(
n_samples=n_samples,
n_features=n_features,
n_informative=n_informative,
n_redundant=n_redundant,
n_classes=n_classes,
random_state=random_state)
return (X, y)
def assess(
X, y,
search_func,
model_class,
param_grid,
xval_indices,
loss=LOG_LOSS,
test_metric=accuracy_score,
dataset_name=None,
search_func_args={}):
"""
The core of the experimental framework. This runs cross-validation
and, for the inner loop, does cross-validation to find the optimal
hyperparameters according to `search_func`. These optimal
parameters are then used for an assessment in the outer
cross-validation run.
Parameters
----------
X : np.array
The design matrix, dimension `(n_samples, n_features)`.
y : list or np.array
The target, of dimension `n_samples`.
search_func : function
The search function to use. Can be `grid_search`,
`randomized_search`, `hyperopt_search`, `skopt_gp_minimize`,
`skopt_forest_minimize`, or `skopt_forest_gbrt`, all
defined in this module. This choice has to be compatible with
`param_grid`, in the sense that `grid_search` and
`randomized_search` require a dict from strings to lists of
values, `hyperopt_search` requires a dict from strings to
hyperopt sampling functions, and the `skopt` functions
require dicts from strings to (upper, lower) pairs of
special `skopt` functions.
model_class : classifier
A classifier model in the mode of `sklearn`, with at least
`fit` and `predict` methods operating on things like
`X` and `y`.
param_grid : dict
Map from parameter names to appropriate specifications of
appropriate values for that parameter. This is not the
expanded grid, but rather the simple map that can be expanded
by `expand_grid` below (though not all methods call for that).
This has to be compatible with `search_func`, and all the
values must be suitable arguments to `model_class` instances.
loss : function or string
An appropriate loss function or string recognizable by
`sklearn.cross_validation.cross_val_score`. In `sklearn`, scores
are positive and losses are negative because they maximize,
but here we are minimizing so we always want smaller to mean
better.
test_metric : function
An `sklearn.metrics` function.
xval_indices : list
List of train and test indices into `X` and `y`. This defines
the cross-validation. This is done outside of this method to
allow for identical splits across different experiments.
dataset_name : str or None
Name for the dataset being analyzed. For book-keeping and
display only.
search_func_args : dict
Keyword arguments to feed to `search_func`.
Returns
-------
dict
Accumulated information about the experiment:
{'Test accuracy': list of float,
'Cross-validation time (in secs.)':list of float,
'Parameters sampled': list of int,
'Method': search_func.__name__,
'Model': model_class.__name__,
'Dataset': dataset_name,
'Best parameters': list of dict,
'Mean test accuracy': float,
'Mean cross-validation time (in secs.)': float,
'Mean parameters sampled': float}
"""
data = {'Test accuracy': [],
'Cross-validation time (in secs.)': [],
'Parameters sampled': [],
'Best parameters': [],
'Method': search_func.__name__,
'Model': model_class.__name__,
'Dataset': dataset_name,
'Best parameters':[]}
for cv_index, (train_index, test_index) in enumerate(xval_indices, start=1):
print("\t{}".format(cv_index))
X_train, X_test = X[train_index], X[test_index]
y_train, y_test = y[train_index], y[test_index]
start = time()
results = search_func(
X_train,
y_train,
model_class,
param_grid,
loss,
**search_func_args)
data['Cross-validation time (in secs.)'].append(time() - start)
data['Parameters sampled'].append(len(results))
best_params = sorted(results, key=itemgetter('loss'), reverse=False)
best_params = best_params[0]['params']
data['Best parameters'].append(best_params)
bestmod = model_class(**best_params)
bestmod.fit(X_train, y_train)
predictions = bestmod.predict(X_test)
data['Test accuracy'].append(test_metric(y_test, predictions))
data['Mean test accuracy'] = np.mean(
data['Test accuracy'])
data['Mean cross-validation time (in secs.)'] = np.mean(
data['Cross-validation time (in secs.)'])
data['Mean parameters sampled'] = np.mean(
data['Parameters sampled'])
return data
def get_cross_validation_indices(X, y, n_folds=5, random_state=None):
"""
Use `StratifiedKFold` to create an `n_folds` cross-validator for
the dataset defined by `X` and y`. Only `y` is used, but both are
given for an intuitive interface; `X` could just as easily be used.
"""
return StratifiedKFold(y, n_folds=n_folds, random_state=random_state)
def random_search(
X_train, y_train, model_class, param_grid, loss, sampsize=None):
"""
Random search over the grid defined by `param_grid`.
Parameters
----------
X_train : np.array
The design matrix, dimension `(n_samples, n_features)`.
y_train : list or np.array
The target, of dimension `n_samples`.
model_class : classifier
A classifier model in the mode of `sklearn`, with at least
`fit` and `predict` methods operating on things like
`X` and `y`.
param_grid : dict
Map from parameter names to lists of appropriate values
for that parameter. This is not the expanded grid, but
rather the simple map that can be expanded by `expand_grid`
below. This method performs the expansion.
loss : function or string
An appropriate loss function or string recognizable by
sklearn.cross_validation.cross_val_score. In sklearn, scores
are positive and losses are negative because they maximize,
but here we are minimizing so we always want smaller to mean
better.
sampsize : int or None
Number of samples to take from the grid. If `None`, then
`sampsize` is half the size of the full grid.
Returns
-------
list of dict
Each has keys 'loss' and 'params', where 'params' stores the
values from `param_grid` for that run. The primary organizing
value is 'loss'.
Example
-------
>>> param_grid = {
'max_depth' : [4, 8],
'learning_rate' : [0.01, 0.3],
'n_estimators' : [20, 50],
'objective' : ['multi:softprob'],
'gamma' : [0, 0.25],
'min_child_weight' : [1],
'subsample' : [1],
'colsample_bytree' : [1]}
>>> res = random_search(X, y, XGBClassifier, param_grid, LOG_LOSS)
To be followed by (see below):
>>> best_params, best_loss = best_results(res)
"""
exapnded_param_grid = expand_grid(param_grid)
if sampsize == None:
sampsize = int(len(exapnded_param_grid) / 2.0)
samp = random.sample(exapnded_param_grid, sampsize)
results = []
for params in samp:
err = cross_validated_scorer(
X_train, y_train, model_class, params, loss)
results.append({'loss': err, 'params': params})
return results
def grid_search(X_train, y_train, model_class, param_grid, loss):
"""
Full grid search over the grid defined by `param_grid`.
Parameters
----------
X_train : np.array
The design matrix, dimension `(n_samples, n_features)`.
y_train : list or np.array
The target, of dimension `n_samples`.
model_class : classifier
A classifier model in the mode of `sklearn`, with at least
`fit` and `predict` methods operating on things like
`X` and `y`.
param_grid : dict
Map from parameter names to lists of appropriate values
for that parameter. This is not the expanded grid, but
rather the simple map that can be expanded by `expand_grid`
below. This method performs the expansion.
loss : function or string
An appropriate loss function or string recognizable by
sklearn.cross_validation.cross_val_score. In sklearn, scores
are positive and losses are negative because they maximize,
but here we are minimizing so we always want smaller to mean
better.
Returns
-------
list of dict
Each has keys 'loss' and 'params', where 'params' stores the
values from `param_grid` for that run. The primary organizing
value is 'loss'.
Example
-------
>>> param_grid = {
'max_depth' : [4, 8],
'learning_rate' : [0.01, 0.3],
'n_estimators' : [20, 50],
'objective' : ['multi:softprob'],
'gamma' : [0, 0.25],
'min_child_weight' : [1],
'subsample' : [1],
'colsample_bytree' : [1]}
>>> res = grid_search(X, y, XGBClassifier, param_grid, LOG_LOSS)
To be followed by (see below):
>>> best_params, best_loss = best_results(res)
"""
results = []
expanded_param_grid = expand_grid(param_grid)
for params in expanded_param_grid:
err = cross_validated_scorer(
X_train, y_train, model_class, params, loss)
results.append({'loss': err, 'params': params})
return results
def expand_grid(param_grid):
"""
Expand `param_grid` to the full grid, as a list of dicts.
Parameters
----------
param_grid : dict
Map from parameter names to lists of appropriate values
for that parameter. This is not the expanded grid, but
rather the simple map that can be expanded by `expand_grid`
below. This method performs the expansion.
Returns
-------
list of dict
If `param_grid` was
{'foo': [1,2], 'bar': [3,4]}
Then the return value would be
[{'foo': 1, 'bar': 3}, {'foo': 1, 'bar': 4},
{'foo': 2, 'bar': 3}, {'foo': 2, 'bar': 4}]
"""
varNames = sorted(param_grid)
return [dict(zip(varNames, prod))
for prod in it.product(*(param_grid[varName]
for varName in varNames))]
def cross_validated_scorer(
X_train, y_train, model_class, params, loss, kfolds=5):
"""
The scoring function used through this module, by all search
functions.
Parameters
----------
X_train : np.array
The design matrix, dimension `(n_samples, n_features)`.
y_train : list or np.array
The target, of dimension `n_samples`.
model_class : classifier
A classifier model in the mode of `sklearn`, with at least
`fit` and `predict` methods operating on things like
`X` and `y`.
params : dict
Map from parameter names to single appropriate values
for that parameter. This will be used to build a model
from `model_class`.
loss : function or string
An appropriate loss function or string recognizable by
sklearn.cross_validation.cross_val_score. In sklearn, scores
are positive and losses are negative because they maximize,
but here we are minimizing so we always want smaller to mean
better.
kfolds : int
Number of cross-validation runs to do.
Returns
-------
float
Average loss over the `kfolds` runs.
"""
mod = model_class(**params)
cv_score = -1 * cross_val_score(
mod,
X_train,
y=y_train,
scoring=loss,
cv=kfolds,
n_jobs=1).mean()
return cv_score
def hyperopt_search(
X_train, y_train, model_class, param_grid, loss, max_evals=100):
"""
Search according to hyperopt's Tree of Parzen Estimator.
Parameters
----------
X_train : np.array
The design matrix, dimension `(n_samples, n_features)`.
y_train : list or np.array
The target, of dimension `n_samples`.
model_class : classifier
A classifier model in the mode of `sklearn`, with at least
`fit` and `predict` methods operating on things like
`X` and `y`.
param_grid : dict
Map from parameter names to `hyperopt` sampling functions.
The parameter names need to work with `model_class`, and the
values specifying how to sample values.
loss : function or string
An appropriate loss function or string recognizable by
sklearn.cross_validation.cross_val_score. In sklearn, scores
are positive and losses are negative because they maximize,
but here we are minimizing so we always want smaller to mean
better.
max_evals : int
Number of evaluations to do.
Returns
-------
list of dict
Each has keys 'loss' and 'params', where 'params' stores the
values from `param_grid` for that run. The primary organizing
value is 'loss'. These values are accumulated and stored by
the `Trials` instance used in the call to `fmin`. A 'status'
record is also retained but not used elsewhere in the module.
Example
-------
>>> hyperopt_grid = {
'max_depth' : hp.choice('max_depth', range(4, 13, 1)),
'learning_rate' : hp.quniform('learning_rate', 0.01, 0.5, 0.01),
'n_estimators' : hp.choice('n_estimators', range(20, 205, 5)),
'objective' : 'multi:softprob',
'gamma' : hp.quniform('gamma', 0, 0.50, 0.01),
'min_child_weight' : hp.quniform('min_child_weight', 1, 5, 1),
'subsample' : hp.quniform('subsample', 0.1, 1, 0.01),
'colsample_bytree' : hp.quniform('colsample_bytree', 0.1, 1.0, 0.01)}
>>> res = hyperopt_search(X, y, XGBClassifier, hyperopt_grid, LOG_LOSS, max_evals=10)
To be followed by (see below):
>>> best_params, best_loss = best_results(res)
"""
def objective(params):
err = cross_validated_scorer(
X_train, y_train, model_class, params, loss)
return {'loss': err, 'params': params, 'status': STATUS_OK}
trials = Trials()
results = fmin(
objective, param_grid, algo=tpe.suggest,
trials=trials, max_evals=max_evals)
return trials.results
def skopt_search(
X_train, y_train, model_class, param_grid, loss, skopt_method, n_calls=100):
"""
General method for applying `skopt_method` to the data.
Parameters
----------
X_train : np.array
The design matrix, dimension `(n_samples, n_features)`.
y_train : list or np.array
The target, of dimension `n_samples`.
model_class : classifier
A classifier model in the mode of `sklearn`, with at least
`fit` and `predict` methods operating on things like
`X` and `y`.
param_grid : dict
Map from parameter names to pairs of values specifying the
upper and lower ends of the space from which to sample.
The values can also be directly specified as `skopt`
objects like `Categorical`.
loss : function or string
An appropriate loss function or string recognizable by
sklearn.cross_validation.cross_val_score. In sklearn, scores
are positive and losses are negative because they maximize,
but here we are minimizing so we always want smaller to mean
better.
skopt_method : skopt function
Can be `gp_minimize`, `forest_minimize`, or `gbrt_minimize`.
n_calls : int
Number of evaluations to do.
Returns
-------
list of dict
Each has keys 'loss' and 'params', where 'params' stores the
values from `param_grid` for that run. The primary organizing
value is 'loss'.
"""
param_keys, param_vecs = zip(*param_grid.items())
param_keys = list(param_keys)
param_vecs = list(param_vecs)
def skopt_scorer(param_vec):
params = dict(zip(param_keys, param_vec))
err = cross_validated_scorer(
X_train, y_train, model_class, params, loss)
return err
outcome = skopt_method(skopt_scorer, list(param_vecs), n_calls=n_calls)
results = []
for err, param_vec in zip(outcome.func_vals, outcome.x_iters):
params = dict(zip(param_keys, param_vec))
results.append({'loss': err, 'params': params})
return results
def skopt_gp_search(
X_train, y_train, model_class, param_grid, loss, n_calls=100):
"""`skopt` according to the Gaussian Process search method. For
details on the parameters, see `skopt_search`.
Example
-------
>>> skopt_grid = {
'max_depth': (4, 12),
'learning_rate': (0.01, 0.5),
'n_estimators': (20, 200),
'objective' : Categorical(('multi:softprob',)),
'gamma': (0, 0.5),
'min_child_weight': (1, 5),
'subsample': (0.1, 1),
'colsample_bytree': (0.1, 1)}
>>> res = skopt_gp_search(X, y, XGBClassifier, skopt_grid, LOG_LOSS, n_calls=10)
To be followed by (see below):
>>> best_params, best_loss = best_results(res)
"""
return skopt_search(
X_train, y_train, model_class, param_grid, loss, gp_minimize, n_calls=n_calls)
def skopt_forest_search(
X_train, y_train, model_class, param_grid, loss, n_calls=100):
"""`skopt` according to the decision tree search method. For
details on the parameters, see `skopt_search`.
Example
-------
>>> skopt_grid = {
'max_depth': (4, 12),
'learning_rate': (0.01, 0.5),
'n_estimators': (20, 200),
'objective' : Categorical(('multi:softprob',)),
'gamma': (0, 0.5),
'min_child_weight': (1, 5),
'subsample': (0.1, 1),
'colsample_bytree': (0.1, 1)}
>>> res = skopt_forest_search(X, y, XGBClassifier, skopt_grid, LOG_LOSS, n_calls=10)
To be followed by (see below):
>>> best_params, best_loss = best_results(res)
"""
return skopt_search(
X_train, y_train, model_class, param_grid, loss, forest_minimize, n_calls=n_calls)
def skopt_gbrt_search(
X_train, y_train, model_class, param_grid, loss, n_calls=100):
"""`skopt` according to the gradient-boosting-tree search method.
For details on the parameters, see `skopt_search`.
Example
-------
>>> skopt_grid = {
'max_depth': (4, 12),
'learning_rate': (0.01, 0.5),
'n_estimators': (20, 200),
'objective' : Categorical(('multi:softprob',)),
'gamma': (0, 0.5),
'min_child_weight': (1, 5),
'subsample': (0.1, 1),
'colsample_bytree': (0.1, 1)}
>>> res = skopt_gbrt_search(X, y, XGBClassifier, skopt_grid, LOG_LOSS, n_calls=10)
To be followed by (see below):
>>> best_params, best_loss = best_results(res)
"""
return skopt_search(
X_train, y_train, model_class, param_grid, loss, gbrt_minimize, n_calls=n_calls)
def prepare_summary(results):
"""Format the `results` dictionary into a `pandas` `DataFrame`,
with columns 'Method', 'Mean parameters sampled', 'Mean test accuracy',
'Mean cross-validation time (in secs.)'."""
results = {k:v for k,v in results.items()
if k not in {'Test accuracy',
'Cross-validation time (in secs.)',
'Parameters sampled'}}
df = pd.DataFrame([results])
df = df[['Method',
'Mean parameters sampled',
'Mean test accuracy',
'Mean cross-validation time (in secs.)']]
return df
def prepare_summaries(results_list):
"""Format all the results dictionaries in `results_list` into a
single pandas `DataFrame`.
"""
dfs = []
for results in results_list:
dfs.append(prepare_summary(results))
combo = pd.concat(dfs, axis=0)
combo.index = range(1,len(combo)+1)
return combo
def run_experiments(
experimental_run,
dataset,
model_class=XGBClassifier,
loss=LOG_LOSS,
test_metric=accuracy_score,
random_state=None,
dataset_name=None):
"""
Basic experimental framework.
Parameters
----------
experimental_run : list of tuples
These tuples should have exactly three members: the first one
of `grid_search`, `randomized_search`, `hyperopt_search`,
`skopt_gp_minimize`, `skopt_forest_minimize`, or
`skopt_forest_gbrt`, the second an appropriate `param_grid`
dict for that function, and the third a dict specifying
keyword arguments to the search function.
dataset : (np.array, iterable)
A dataset (X, y) where `X` has dimension
`(n_samples, n_features)` and `y` has
dimension `n_samples`.
model_class : classifier
A classifier model in the mode of `sklearn`, with at least
`fit` and `predict` methods operating on things like
`X` and `y`.
loss : function or string
An appropriate loss function or string recognizable by
`sklearn.cross_validation.cross_val_score`. In `sklearn`, scores
are positive and losses are negative because they maximize,
but here we are minimizing so we always want smaller to mean
better.
test_metric : function
An `sklearn.metrics` function.
random_state : int
dataset_name : str or None
Informal name to give the dataset. Purely for
book-keeping.
Returns
-------
list of dict
Each dict is a results dictionary of the sort returned
by `assess`.
"""
X, y = dataset
skf = get_cross_validation_indices(
X, y, random_state=random_state)
all_results = []
# This loop can easily be parallelized, but doing so can
# be tricky on some systems, since `cross_val_score`
# calls `joblib` even if `n_jobs=1`, resulting in
# nested parallel jobs even if there is no actual
# parallelization elsewhere in the experimental run.
for search_func, param_grid, kwargs in experimental_run:
print(search_func.__name__)
all_results.append(
assess(
X, y,
search_func=search_func,
model_class=XGBClassifier,
param_grid=param_grid,
xval_indices=skf,
loss=loss,
test_metric=test_metric,
dataset_name=dataset_name,
search_func_args=kwargs))
return all_results
def representation_size_experiments(
experimental_run,
n_samples=100,
min_features=50,
max_features=100,
increment=50,
loss=LOG_LOSS,
test_metric=accuracy_score,
random_state=None):
"""Run a series of experiments with `experimental_run`
exploring `n_feature` sizes from `min_features` to
`max_features` (inclusive) in increments of `increment`.
Parameters
----------
experimental_run : list of tuples
These tuples should have exactly three members: the first one
of `grid_search`, `randomized_search`, `hyperopt_search`,
`skopt_gp_minimize`, `skopt_forest_minimize`, or
`skopt_forest_gbrt`, the second an appropriate `param_grid`
dict for that function, and the third a dict specifying
keyword arguments to the search function.
n_samples : int
Number of examples.
min_features : int
Smallest feature representation size.
max_features : int
Largest feature representation size.
increment : int
Increments between `min_features` and `max_features`.
loss : function or string
An appropriate loss function or string recognizable by
`sklearn.cross_validation.cross_val_score`. In `sklearn`, scores
are positive and losses are negative because they maximize,
but here we are minimizing so we always want smaller to mean
better.
test_metric : function
An `sklearn.metrics` function.
random_state : int
Returns
-------
list of values returned by `run_experiments`.
"""
all_results = []
for n_features in range(min_features, max_features+1, increment):
dataset = artificial_dataset(
n_samples=100,
n_features=n_features,
n_classes=3,
random_state=random_state)
results = run_experiments(
experimental_run,
dataset,
loss=loss,
test_metric=accuracy_score,
random_state=random_state,
dataset_name=n_features)
all_results.append(results)
return all_results
def plot_representation_size_accuracy(
representation_size_results, include_cis=True):
"""Plot the test accuracy values from the output of
`representation_size_experiments`"""
kwargs = {
'metric_name': 'Test accuracy',
'metric_mean_name': 'Mean test accuracy',
'ylabel': 'Test accuracy',
'value_transform': (lambda x : x),
'include_cis': include_cis,
'ylabel_overlap_threshold': 0.02}
plot_representation_size(representation_size_results, **kwargs)
def plot_representation_size_time(
representation_size_results, include_cis=True):
"""Plot the cross-validation time values from the output of
`representation_size_experiments`"""
kwargs = {
'metric_name': 'Cross-validation time (in secs.)',
'metric_mean_name': 'Mean cross-validation time (in secs.)',
'ylabel': 'Cross-validation time (log-scale)',
'value_transform': (lambda x : np.log(x)),
'include_cis': include_cis,
'ylabel_overlap_threshold': 0.2}
plot_representation_size(representation_size_results, **kwargs)
def plot_representation_size(
representation_size_results,
metric_name='',
metric_mean_name='',
ylabel='',
value_transform=(lambda x : x),
include_cis=True,
ylabel_overlap_threshold=0.2):
"""Generic interface for plotting the output of
`representation_size_experiments`"""
fig, ax = plt.subplots(1)
fig.set_figwidth(10)
fig.set_figheight(8)
methods = set([d['Method'] for results in representation_size_results
for d in results])
colors = {
'grid_search': '#212121',
'random_search': '#876DB5',
'hyperopt_search': '#4D8951',
'skopt_forest_minimize': '#0499CC',
'skopt_gp_minimize': '#03A9F4',
'skopt_forest_gbrt': '#32A8B4'}
text_positions = []
for method in methods:
color = colors[method]
method_results = [d for results in representation_size_results
for d in results if d['Method']==method]
method_results = sorted(method_results, key=itemgetter('Dataset'))
xpos = [d['Dataset'] for d in method_results]
mus = [value_transform(d[metric_mean_name]) for d in method_results]
if include_cis:
cis = [value_transform(get_ci(d[metric_name]))
for d in method_results]
for x, ci in zip(xpos, cis):
ax.plot([x,x], ci, color=color)
ax.plot(
xpos, mus, marker='.', linestyle='-', markersize=12, color=color)
text_positions.append(mus[-1])
method_text_positions = [[p,m] for p, m in zip(text_positions, methods)]
method_text_positions = sorted(method_text_positions)
for i in range(len(method_text_positions)-1):
here = method_text_positions[i][0]
there = method_text_positions[i+1][0]
if there - here < ylabel_overlap_threshold:
method_text_positions[i+1][0] = here + ylabel_overlap_threshold
xpad = min(xpos)*0.2
for text_pos, method in method_text_positions:
ax.text(max(xpos)+(xpad*2), text_pos, method,
fontsize=16, color=colors[method],
va='center', weight='bold')
ax.set_xlim([min(xpos)-xpad, max(xpos)+xpad])
ax.set_xlabel("Number of features")
ax.set_ylabel(ylabel)
def get_ci(vals, percent=0.95):
"""Confidence interval for `vals` from the Students' t
distribution. Uses `stats.t.interval`.
Parameters
----------
percent : float
Size of the confidence interval. The default is 0.95. The only
requirement is that this be above 0 and at or below 1.
Returns
-------
tuple
The first member is the upper end of the interval, the second
the lower end of the interval.
"""
if len(set(vals)) == 1:
return (vals[0], vals[0])
mu = np.mean(vals)
df = len(vals)-1
sigma = np.std(vals) / np.sqrt(len(vals))
return stats.t.interval(percent, df, loc=mu, scale=sigma)
|
爬虫小demo/31 下载bilibili视频.py | lb2281075105/Python-Spider | 713 | 11123455 | import requests
from lxml import html
import re
import urllib3
urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
def star(url):
url2 = "https://api.bilibili.com/x/player/playurl?avid={avid}&cid={cid}&qn=32&type=&otype=json"
headers2 = {
"host": "",
"Referer": "https://www.bilibili.com",
"User-Agent": "Mozilla/5.0(Windows NT 10.0;WOW64) AppleWebKit/537.36(KHTML,likeGecko)Chrome/63.0.3239.132Safari/537.36"
}
avid = re.findall("video/av(.+)\?", url)
print(avid)
cid ,name = get_cid(avid[0])
print(cid,name)
flv_url , size = get_flvurl(url2.format(avid=avid[0],cid=cid))
shuju = size / 1024 / 1024
print("本视频大小为：%.2fM" % shuju)
h = re.findall("https://(.+)com",flv_url)
host = h[0]+"com"
headers2["host"] = host
res = requests.get(flv_url,headers=headers2,stream=True, verify=False)
print(res.status_code)
save_movie(res,name)
def get_cid(aid):#获得cid
header = {
'host': 'api.bilibili.com',
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64; rv:6.0) Gecko/20100101 Firefox/6.0'
}
url = "https://api.bilibili.com/x/player/pagelist?aid={aid}&jsonp=jsonp".format(aid=aid)
response = requests.get(url,headers=header).json()
# print(response["data"])
# 这个地方设置index是因为下载集合里面的视频,顺序,0代表下载第一个视频,1代表下载集合里面第二个视频,2,3,4...依次类推
index = 0
return response["data"][index]["cid"] ,response["data"][index]["part"]
def get_flvurl(url):#获得视频真实flv地址
header = {'host': 'api.bilibili.com',
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64; rv:6.0) Gecko/20100101 Firefox/6.0'}
response = requests.get(url,headers=header).json()
return response["data"]["durl"][0]["url"],response["data"]["durl"][0]["size"]
def save_movie(res,name):#保存视频
chunk_size = 1024
with open("{name}.flv".format(name = name),"wb") as f:
for data in res.iter_content(1024):
f.write(data)
if __name__ == "__main__":
# 把下面的av后面的'583959574'在要下载的视频集合里面找到就可以下载视频了
url = "https://www.bilibili.com/video/av583959574?spm_id_from=333.334.b_62696c695f646f756761.5"
star(url)
|
benchexec/tools/skink.py | MartinSpiessl/benchexec | 137 | 11123506 | # This file is part of BenchExec, a framework for reliable benchmarking:
# https://github.com/sosy-lab/benchexec
#
# SPDX-FileCopyrightText: 2007-2020 <NAME> <https://www.sosy-lab.org>
# SPDX-FileCopyrightText: 2015 <NAME>
#
# SPDX-License-Identifier: Apache-2.0
import benchexec.util as util
import benchexec.tools.template
import benchexec.result as result
class Tool(benchexec.tools.template.BaseTool):
REQUIRED_PATHS = [
"bin",
"lib",
"include",
"logback-test.xml",
"skink.sh",
"skink.jar",
"skink-fpbv.jar",
"application.conf",
]
def executable(self):
return util.find_executable("skink.sh")
def name(self):
return "skink"
def version(self, executable):
return self._version_from_tool(executable)
def determine_result(self, returncode, returnsignal, output, isTimeout):
output = "\n".join(output)
if "TRUE" in output:
status = result.RESULT_TRUE_PROP
elif "FALSE" in output:
status = result.RESULT_FALSE_REACH
else:
status = result.RESULT_UNKNOWN
return status
|
dask/tests/test_ml.py | marcelned/dask | 9,684 | 11123523 | def test_basic():
try:
import dask_ml # noqa: F401
except ImportError:
try:
from dask.ml.model_selection import GridSearchCV # noqa: F401
except ImportError as e:
assert "conda install dask-ml" in str(e)
else:
assert False
else:
from dask.ml.model_selection import GridSearchCV # noqa: F401
|
njunmt/encoders/rnn_encoder.py | whr94621/NJUNMT-tf | 111 | 11123534 | <reponame>whr94621/NJUNMT-tf
# Copyright 2017 Natural Language Processing Group, Nanjing University, <EMAIL>.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
""" Define RNN-based encoders. """
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import copy
import tensorflow as tf
from njunmt.encoders.encoder import Encoder
from njunmt.utils.rnn_cell_utils import get_multilayer_rnn_cells
class StackBidirectionalRNNEncoder(Encoder):
""" Define stacked bidirectional RNN encoder. """
def __init__(self, params, mode, name=None, verbose=True):
""" Initializes the parameters of the encoder.
Args:
params: A dictionary of parameters to construct the
encoder architecture.
mode: A mode.
name: The name of this encoder.
verbose: Print encoder parameters if set True.
"""
super(StackBidirectionalRNNEncoder, self).__init__(params, mode, name, verbose)
self._cells_fw = get_multilayer_rnn_cells(**self.params['rnn_cell'])
self._cells_bw = get_multilayer_rnn_cells(**self.params['rnn_cell'])
@staticmethod
def default_params():
""" Returns a dictionary of default parameters of this encoder. """
return {
"rnn_cell": {
"cell_class": "LSTMCell",
"cell_params": {},
"dropout_input_keep_prob": 1.0,
"dropout_state_keep_prob": 1.0,
"num_layers": 1
}
}
def encode(self, features, feature_length, **kwargs):
""" Encodes the inputs via a stacked bi-directional RNN.
Args:
features: A Tensor, [batch_size, max_features_length, dim].
feature_length: A Tensor, [batch_size, ].
**kwargs:
Returns: An instance of `collections.namedtuple`.
"""
scope = self.name
if "scope" in kwargs:
scope = kwargs.pop("scope")
# outputs: [batch_size, max_time, layers_output]
# layers_output = size_of_fw + size_of_bw
# the returned states:
# `tuple` type which has only one item, because we use MultiRNN cell for multiple cells
outputs, states_fw, states_bw = tf.contrib.rnn.stack_bidirectional_dynamic_rnn(
cells_fw=[self._cells_fw],
cells_bw=[self._cells_bw],
inputs=features,
sequence_length=feature_length,
dtype=tf.float32,
scope=scope,
**kwargs)
# because we use MultiRNNCell, unpack the top tuple structure
states_fw = states_fw[0]
states_bw = states_bw[0]
return self._encoder_output_tuple_type(
outputs=outputs,
final_states={
"forward": states_fw[-1],
"backward": states_bw[-1]},
attention_values=outputs,
attention_length=feature_length)
class UnidirectionalRNNEncoder(Encoder):
""" Define a unidirectional RNN encoder. """
def __init__(self, params, mode, name=None, verbose=True):
""" Initializes the parameters of the encoder.
Args:
params: A dictionary of parameters to construct the
encoder architecture.
mode: A mode.
name: The name of this encoder.
verbose: Print encoder parameters if set True.
"""
super(UnidirectionalRNNEncoder, self).__init__(params, mode, name, verbose)
self._cells_fw = get_multilayer_rnn_cells(**self.params['rnn_cell'])
@staticmethod
def default_params():
""" Returns a dictionary of default parameters of this encoder. """
return {
"rnn_cell": {
"cell_class": "LSTMCell",
"cell_params": {},
"dropout_input_keep_prob": 1.0,
"dropout_state_keep_prob": 1.0,
"num_layers": 1
}
}
def encode(self, features, feature_length, **kwargs):
""" Encodes the inputs.
Args:
features: A Tensor, [batch_size, max_features_length, dim].
feature_length: A Tensor, [batch_size, ].
**kwargs:
Returns: An instance of `collections.namedtuple`.
"""
scope = self.name
if "scope" in kwargs:
scope = kwargs.pop("scope")
# outputs: [batch_size, max_time, num_units_of_hidden]
outputs, states = tf.nn.dynamic_rnn(
cell=self._cells_fw,
inputs=features,
sequence_length=feature_length,
dtype=tf.float32,
scope=scope,
**kwargs)
return self._encoder_output_tuple_type(
outputs=outputs,
final_statest=states[-1],
attention_values=outputs,
attention_length=feature_length)
class BiUnidirectionalRNNEncoder(Encoder):
""" Define a unidirectional RNN encoder. """
def __init__(self, params, mode, name=None, verbose=True):
""" Initializes the parameters of the encoder.
Args:
params: A dictionary of parameters to construct the
encoder architecture.
mode: A mode.
name: The name of this encoder.
verbose: Print encoder parameters if set True.
"""
super(BiUnidirectionalRNNEncoder, self).__init__(params, mode, name, verbose)
rnn_cell_params = copy.deepcopy(self.params["rnn_cell"])
rnn_cell_params["num_layers"] = 1
self._cells_fw = get_multilayer_rnn_cells(**rnn_cell_params)
self._cells_bw = get_multilayer_rnn_cells(**rnn_cell_params)
if self.params["rnn_cell"]["num_layers"] > 1:
rnn_cell_params["num_layers"] = self.params["rnn_cell"]["num_layers"]-1
self._cells = get_multilayer_rnn_cells(**rnn_cell_params)
@staticmethod
def default_params():
""" Returns a dictionary of default parameters of this encoder. """
return {
"rnn_cell": {
"cell_class": "LSTMCell",
"cell_params": {},
"dropout_input_keep_prob": 1.0,
"dropout_state_keep_prob": 1.0,
"num_layers": 2
}
}
def encode(self, features, feature_length, **kwargs):
""" Encodes the inputs.
Args:
features: A Tensor, [batch_size, max_features_length, dim].
feature_length: A Tensor, [batch_size, ].
**kwargs:
Returns: An instance of `collections.namedtuple`.
"""
scope = self.name
if "scope" in kwargs:
scope = kwargs.pop("scope")
# outputs: [batch_size, max_features_length, hidden_size * 2]
outputs, states_fw, states_bw = tf.contrib.rnn.stack_bidirectional_dynamic_rnn(
cells_fw=[self._cells_fw],
cells_bw=[self._cells_bw],
inputs=features,
sequence_length=feature_length,
dtype=tf.float32,
scope=scope,
**kwargs)
final_states = {"forward": states_fw[-1],
"backward": states_bw[-1]}
if self.params["rnn_cell"]["num_layers"] > 1:
# outputs: [batch_size, max_time, num_units_of_hidden]
outputs, states = tf.nn.dynamic_rnn(
cell=self._cells,
inputs=outputs,
sequence_length=feature_length,
dtype=tf.float32,
scope=scope,
**kwargs)
final_states = states[-1]
return self._encoder_output_tuple_type(
outputs=outputs,
final_states=final_states,
attention_values=outputs,
attention_length=feature_length)
|
pypower/int2ext.py | Bengt/PYPOWER | 221 | 11123572 | <gh_stars>100-1000
# Copyright (c) 1996-2015 PSERC. All rights reserved.
# Use of this source code is governed by a BSD-style
# license that can be found in the LICENSE file.
"""Converts internal to external bus numbering.
"""
import sys
from warnings import warn
from copy import deepcopy
from pypower.idx_bus import BUS_I
from pypower.idx_gen import GEN_BUS
from pypower.idx_brch import F_BUS, T_BUS
from pypower.idx_area import PRICE_REF_BUS
from pypower.run_userfcn import run_userfcn
from pypower.i2e_field import i2e_field
from pypower.i2e_data import i2e_data
def int2ext(ppc, val_or_field=None, oldval=None, ordering=None, dim=0):
"""Converts internal to external bus numbering.
C{ppc = int2ext(ppc)}
If the input is a single PYPOWER case dict, then it restores all
buses, generators and branches that were removed because of being
isolated or off-line, and reverts to the original generator ordering
and original bus numbering. This requires that the 'order' key
created by L{ext2int} be in place.
Example::
ppc = int2ext(ppc)
@see: L{ext2int}, L{i2e_field}, L{i2e_data}
@author: <NAME> (PSERC Cornell)
"""
ppc = deepcopy(ppc)
if val_or_field is None: # nargin == 1
if 'order' not in ppc:
sys.stderr.write('int2ext: ppc does not have the "order" field '
'required for conversion back to external numbering.\n')
o = ppc["order"]
if o["state"] == 'i':
## execute userfcn callbacks for 'int2ext' stage
if 'userfcn' in ppc:
ppc = run_userfcn(ppc["userfcn"], 'int2ext', ppc)
## save data matrices with internal ordering & restore originals
o["int"] = {}
o["int"]["bus"] = ppc["bus"].copy()
o["int"]["branch"] = ppc["branch"].copy()
o["int"]["gen"] = ppc["gen"].copy()
ppc["bus"] = o["ext"]["bus"].copy()
ppc["branch"] = o["ext"]["branch"].copy()
ppc["gen"] = o["ext"]["gen"].copy()
if 'gencost' in ppc:
o["int"]["gencost"] = ppc["gencost"].copy()
ppc["gencost"] = o["ext"]["gencost"].copy()
if 'areas' in ppc:
o["int"]["areas"] = ppc["areas"].copy()
ppc["areas"] = o["ext"]["areas"].copy()
if 'A' in ppc:
o["int"]["A"] = ppc["A"].copy()
ppc["A"] = o["ext"]["A"].copy()
if 'N' in ppc:
o["int"]["N"] = ppc["N"].copy()
ppc["N"] = o["ext"]["N"].copy()
## update data (in bus, branch and gen only)
ppc["bus"][o["bus"]["status"]["on"], :] = \
o["int"]["bus"]
ppc["branch"][o["branch"]["status"]["on"], :] = \
o["int"]["branch"]
ppc["gen"][o["gen"]["status"]["on"], :] = \
o["int"]["gen"][o["gen"]["i2e"], :]
if 'areas' in ppc:
ppc["areas"][o["areas"]["status"]["on"], :] = \
o["int"]["areas"]
## revert to original bus numbers
ppc["bus"][o["bus"]["status"]["on"], BUS_I] = \
o["bus"]["i2e"] \
[ ppc["bus"][o["bus"]["status"]["on"], BUS_I].astype(int) ]
ppc["branch"][o["branch"]["status"]["on"], F_BUS] = \
o["bus"]["i2e"][ ppc["branch"] \
[o["branch"]["status"]["on"], F_BUS].astype(int) ]
ppc["branch"][o["branch"]["status"]["on"], T_BUS] = \
o["bus"]["i2e"][ ppc["branch"] \
[o["branch"]["status"]["on"], T_BUS].astype(int) ]
ppc["gen"][o["gen"]["status"]["on"], GEN_BUS] = \
o["bus"]["i2e"][ ppc["gen"] \
[o["gen"]["status"]["on"], GEN_BUS].astype(int) ]
if 'areas' in ppc:
ppc["areas"][o["areas"]["status"]["on"], PRICE_REF_BUS] = \
o["bus"]["i2e"][ ppc["areas"] \
[o["areas"]["status"]["on"], PRICE_REF_BUS].astype(int) ]
if 'ext' in o: del o['ext']
o["state"] = 'e'
ppc["order"] = o
else:
sys.stderr.write('int2ext: ppc claims it is already using '
'external numbering.\n')
else: ## convert extra data
if isinstance(val_or_field, str) or isinstance(val_or_field, list):
## field (key)
warn('Calls of the form MPC = INT2EXT(MPC, ''FIELD_NAME'', ...) have been deprecated. Please replace INT2EXT with I2E_FIELD.')
bus, gen = val_or_field, oldval
if ordering is not None:
dim = ordering
ppc = i2e_field(ppc, bus, gen, dim)
else:
## value
warn('Calls of the form VAL = INT2EXT(MPC, VAL, ...) have been deprecated. Please replace INT2EXT with I2E_DATA.')
bus, gen, branch = val_or_field, oldval, ordering
ppc = i2e_data(ppc, bus, gen, branch, dim)
return ppc
def int2ext1(i2e, bus, gen, branch, areas):
"""Converts from the consecutive internal bus numbers back to the originals
using the mapping provided by the I2E vector returned from C{ext2int}.
@see: L{ext2int}
@see: U{http://www.pserc.cornell.edu/matpower/}
"""
bus[:, BUS_I] = i2e[ bus[:, BUS_I].astype(int) ]
gen[:, GEN_BUS] = i2e[ gen[:, GEN_BUS].astype(int) ]
branch[:, F_BUS] = i2e[ branch[:, F_BUS].astype(int) ]
branch[:, T_BUS] = i2e[ branch[:, T_BUS].astype(int) ]
if areas != None and len(areas) > 0:
areas[:, PRICE_REF_BUS] = i2e[ areas[:, PRICE_REF_BUS].astype(int) ]
return bus, gen, branch, areas
return bus, gen, branch
|
mongodb/mongodb_consistent_backup/official/mongodb_consistent_backup/Common/__init__.py | smthkissinger/docker-images | 282 | 11123586 | from Config import Config, parse_config_bool # NOQA
from DB import DB, parse_read_pref_tags # NOQA
from LocalCommand import LocalCommand # NOQA
from Lock import Lock # NOQA
from MongoUri import MongoUri # NOQA
from Timer import Timer # NOQA
from Util import config_to_string, is_datetime, parse_method, validate_hostname, wait_popen # NOQA
|
search/show_search_results.py | dongan-beta/PyRetri | 1,063 | 11123622 | # -*- coding: utf-8 -*-
import os
import argparse
import json
import codecs
from utils.misc import save_to_csv, filter_by_keywords
def parse_args():
parser = argparse.ArgumentParser(description='A tool box for deep learning-based image retrieval')
parser.add_argument('opts', default=None, nargs=argparse.REMAINDER)
parser.add_argument('--results_json_path', '-r', default=None, type=str, help="path of the result json")
args = parser.parse_args()
return args
def show_results(results):
for i in range(len(results)):
print(results[i])
def main():
# init args
args = parse_args()
assert os.path.exists(args.results_json_path), 'the config file must be existed!'
with open(args.results_json_path, "r") as f:
results = json.load(f)
# save the search results in a csv format file.
csv_path = '/home/songrenjie/projects/RetrievalToolBox/test.csv'
save_to_csv(results, csv_path)
# define the keywords to be selected
keywords = {
'data_name': ['market'],
'pre_process_name': list(),
'model_name': list(),
'feature_map_name': list(),
'aggregator_name': list(),
'post_process_name': ['no_fea_process', 'l2_normalize', 'pca_whiten', 'pca_wo_whiten'],
}
# show search results according to the given keywords
results = filter_by_keywords(results, keywords)
show_results(results)
if __name__ == '__main__':
main()
|
alibi_detect/cd/tests/test_mmd_online.py | sugatoray/alibi-detect | 1,227 | 11123630 | import numpy as np
import pytest
from alibi_detect.cd import MMDDriftOnline
from alibi_detect.cd.pytorch.mmd_online import MMDDriftOnlineTorch
from alibi_detect.cd.tensorflow.mmd_online import MMDDriftOnlineTF
n, n_features = 100, 5
tests_mmddriftonline = ['tensorflow', 'pytorch', 'PyToRcH', 'mxnet']
n_tests = len(tests_mmddriftonline)
@pytest.fixture
def mmddriftonline_params(request):
return tests_mmddriftonline[request.param]
@pytest.mark.parametrize('mmddriftonline_params', list(range(n_tests)), indirect=True)
def test_mmddriftonline(mmddriftonline_params):
backend = mmddriftonline_params
x_ref = np.random.randn(*(n, n_features))
# Instantiate and check detector class
try:
cd = MMDDriftOnline(x_ref=x_ref, ert=25, window_size=5, backend=backend, n_bootstraps=100)
except NotImplementedError:
cd = None
if backend.lower() == 'pytorch':
assert isinstance(cd._detector, MMDDriftOnlineTorch)
elif backend.lower() == 'tensorflow':
assert isinstance(cd._detector, MMDDriftOnlineTF)
else:
assert cd is None
return
# Test predict
x_t = np.random.randn(n_features)
t0 = cd.t
cd.predict(x_t)
assert cd.t - t0 == 1 # This checks state updated (self.t at least)
# Test score
t0 = cd.t
cd.score(x_t)
assert cd.t - t0 == 1
|
test/test_oneview_ethernet_network_facts.py | nabhajit-ray/oneview-ansible | 108 | 11123673 | #!/usr/bin/python
# -*- coding: utf-8 -*-
###
# Copyright (2016-2019) Hewlett Packard Enterprise Development LP
#
# Licensed under the Apache License, Version 2.0 (the "License");
# You may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###
import pytest
from mock import mock
from hpe_test_utils import OneViewBaseFactsTest
from oneview_module_loader import EthernetNetworkFactsModule
ERROR_MSG = 'Fake message error'
PARAMS_GET_ALL = dict(
config='config.json',
name=None
)
PARAMS_GET_BY_NAME = dict(
config='config.json',
name="Test Ethernet Network",
options=[]
)
PARAMS_GET_BY_NAME_WITH_OPTIONS = dict(
config='config.json',
name="Test Ethernet Network",
options=['associatedProfiles', 'associatedUplinkGroups']
)
PRESENT_ENETS = [{
"name": "Test Ethernet Network",
"uri": "/rest/ethernet-networks/d34dcf5e-0d8e-441c-b00d-e1dd6a067188"
}]
ENET_ASSOCIATED_UPLINK_GROUP_URIS = [
"/rest/uplink-sets/c6bf9af9-48e7-4236-b08a-77684dc258a5",
"/rest/uplink-sets/e2f0031b-52bd-4223-9ac1-d91cb519d548"
]
ENET_ASSOCIATED_PROFILE_URIS = [
"/rest/server-profiles/83e2e117-59dc-4e33-9f24-462af951cbbe",
"/rest/server-profiles/57d3af2a-b6d2-4446-8645-f38dd808ea4d"
]
ENET_ASSOCIATED_UPLINK_GROUPS = [dict(uri=ENET_ASSOCIATED_UPLINK_GROUP_URIS[0], name='Uplink Set 1'),
dict(uri=ENET_ASSOCIATED_UPLINK_GROUP_URIS[1], name='Uplink Set 2')]
ENET_ASSOCIATED_PROFILES = [dict(uri=ENET_ASSOCIATED_PROFILE_URIS[0], name='Server Profile 1'),
dict(uri=ENET_ASSOCIATED_PROFILE_URIS[1], name='Server Profile 2')]
@pytest.mark.resource(TestEthernetNetworkFactsModule='ethernet_networks')
class TestEthernetNetworkFactsModule(OneViewBaseFactsTest):
def test_should_get_all_enets(self):
self.resource.get_all.return_value = PRESENT_ENETS
self.mock_ansible_module.params = PARAMS_GET_ALL
EthernetNetworkFactsModule().run()
self.mock_ansible_module.exit_json.assert_called_once_with(
changed=False,
ansible_facts=dict(ethernet_networks=(PRESENT_ENETS))
)
def test_should_get_enet_by_name(self):
self.resource.data = PRESENT_ENETS
self.mock_ansible_module.params = PARAMS_GET_BY_NAME
EthernetNetworkFactsModule().run()
self.mock_ansible_module.exit_json.assert_called_once_with(
changed=False,
ansible_facts=dict(ethernet_networks=(PRESENT_ENETS))
)
def test_should_get_enet_by_name_with_options(self):
self.resource.data = PRESENT_ENETS
self.resource.get_associated_profiles.return_value = ENET_ASSOCIATED_PROFILE_URIS
self.resource.get_associated_uplink_groups.return_value = ENET_ASSOCIATED_UPLINK_GROUP_URIS
profiles = []
for data in ENET_ASSOCIATED_PROFILES:
obj = mock.Mock()
obj.data = data
profiles.append(obj)
uplinks = []
for data in ENET_ASSOCIATED_UPLINK_GROUPS:
obj = mock.Mock()
obj.data = data
uplinks.append(obj)
self.mock_ov_client.server_profiles.get_by_uri.side_effect = profiles
self.mock_ov_client.uplink_sets.get_by_uri.side_effect = uplinks
self.mock_ansible_module.params = PARAMS_GET_BY_NAME_WITH_OPTIONS
EthernetNetworkFactsModule().run()
self.mock_ansible_module.exit_json.assert_called_once_with(
changed=False,
ansible_facts=dict(ethernet_networks=PRESENT_ENETS,
enet_associated_profiles=ENET_ASSOCIATED_PROFILES,
enet_associated_uplink_groups=ENET_ASSOCIATED_UPLINK_GROUPS)
)
if __name__ == '__main__':
pytest.main([__file__])
|
solutions/problem_114.py | ksvr444/daily-coding-problem | 1,921 | 11123720 | <reponame>ksvr444/daily-coding-problem<gh_stars>1000+
def reverse_words(string, delimiters):
words = list()
delims = list()
delim_positions = list() # stores positions of the delimiters seen
start = 0
i = 0
while i < len(string):
char = string[i]
if char in delimiters:
word = string[start:i]
if i - start > 1:
words.append(word)
delims.append(char)
delim_positions.append(len(words) + len(delims) - 1)
start = i + 1
i += 1
# get last word if present
if i - start > 1:
words.append(string[start:i])
words.reverse() # reverse just the words
reversed_order = list()
word_index = 0
delim_index = 0
# merging the reversed words and the delimiters
for i in range(len(words) + len(delims)):
if delim_index < len(delim_positions) and delim_positions[delim_index] == i:
# insert next delimiter if the position is saved for a delimiter
reversed_order.append(delims[delim_index])
delim_index += 1
else:
reversed_order.append(words[word_index])
word_index += 1
reversed_string = "".join(reversed_order)
return reversed_string
assert reverse_words("hello/world:here/",
set([':', '/'])) == "here/world:hello/"
assert reverse_words(":hello//world:here/",
set([':', '/'])) == ":here//world:hello/"
assert reverse_words("hello//world:here",
set([':', '/'])) == "here//world:hello"
assert reverse_words("hello/world:here",
set([':', '/'])) == "here/world:hello"
|
tools/benchmark.py | Genevievekim/semantic-segmentation-1 | 196 | 11123766 | <reponame>Genevievekim/semantic-segmentation-1
import torch
import argparse
import time
from fvcore.nn import flop_count_table, FlopCountAnalysis
import sys
sys.path.insert(0, '.')
from semseg.models import *
def main(
model_name: str,
backbone_name: str,
image_size: list,
num_classes: int,
device: str,
):
device = torch.device('cuda' if torch.cuda.is_available() and device == 'cuda' else 'cpu')
inputs = torch.randn(1, 3, *image_size).to(device)
model = eval(model_name)(backbone_name, num_classes)
model = model.to(device)
model.eval()
print(flop_count_table(FlopCountAnalysis(model, inputs)))
total_time = 0.0
for _ in range(10):
tic = time.perf_counter()
model(inputs)
toc = time.perf_counter()
total_time += toc - tic
total_time /= 10
print(f"Inference time: {total_time*1000:.2f}ms")
print(f"FPS: {1/total_time}")
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--model-name', type=str, default='SegFormer')
parser.add_argument('--backbone-name', type=str, default='MiT-B0')
parser.add_argument('--image-size', type=list, default=[512, 512])
parser.add_argument('--num-classes', type=int, default=11)
parser.add_argument('--device', type=str, default='cuda')
args = parser.parse_args()
main(args.model_name, args.backbone_name, args.image_size, args.num_classes, args.device) |
uecli/CMakeCustomFlags.py | MonsterClosetGames/ue4cli | 179 | 11123775 | <reponame>MonsterClosetGames/ue4cli
import os
# The list of include directory substrings that trigger custom CMake flags
CUSTOM_FLAGS_FOR_INCLUDE_DIRS = {
'libPNG-': 'PNG_PNG_INCLUDE_DIR'
}
# The list of library files that trigger custom CMake flags
CUSTOM_FLAGS_FOR_LIBS = {
'png': 'PNG_LIBRARY',
'z': 'ZLIB_LIBRARY',
'z_fPIC': 'ZLIB_LIBRARY',
'zlibstatic': 'ZLIB_LIBRARY'
}
class CMakeCustomFlags(object):
@staticmethod
def processLibraryDetails(details):
"""
Processes the supplied ThirdPartyLibraryDetails instance and sets any custom CMake flags
"""
# If the header include directories list contains any directories we have flags for, add them
for includeDir in details.includeDirs:
# If the directory path matches any of the substrings in our list, generate the relevant flags
for pattern in CUSTOM_FLAGS_FOR_INCLUDE_DIRS:
if pattern in includeDir:
flag = '-D' + CUSTOM_FLAGS_FOR_INCLUDE_DIRS[pattern] + '=' + includeDir
details.cmakeFlags.append(flag)
# If the libraries list contains any libs we have flags for, add them
for lib in details.libs:
# Extract the name of the library from the filename
# (We remove any "lib" prefix or numerical suffix)
filename = os.path.basename(lib)
(name, ext) = os.path.splitext(filename)
libName = name.replace('lib', '') if name.startswith('lib') else name
libName = libName.rstrip('_-1234567890')
# If the library name matches one in our list, generate its flag
if libName in CUSTOM_FLAGS_FOR_LIBS:
flag = '-D' + CUSTOM_FLAGS_FOR_LIBS[libName] + '=' + lib
details.cmakeFlags.append(flag)
|
houdini/handlers/play/card.py | Oblivion-Max/houdini | 444 | 11123793 | import random
from houdini import handlers
from houdini.data.ninja import CardCollection, CardStarterDeck, PenguinCardCollection
from houdini.handlers import Priority, XMLPacket, XTPacket
@handlers.boot
async def cards_load(server):
server.cards = await CardCollection.get_collection()
server.logger.info(f'Loaded {len(server.cards)} ninja cards')
starter_deck_cards = await CardStarterDeck.query.gino.all()
server.cards.set_starter_decks(starter_deck_cards)
server.logger.info(f'Loaded {len(server.cards.starter_decks)} starter decks')
@handlers.handler(XMLPacket('login'), priority=Priority.Low)
@handlers.allow_once
async def load_card_inventory(p):
p.cards = await PenguinCardCollection.get_collection(p.id)
@handlers.handler(XTPacket('i', 'ai'))
async def handle_buy_starter_deck(p, deck_id: int):
if deck_id in p.server.cards.starter_decks:
starter_deck = p.server.cards.starter_decks[deck_id]
power_cards = [card for card, qty in starter_deck if card.power_id > 0]
for card, qty in starter_deck:
if card.power_id == 0:
await p.add_card(card, quantity=qty)
power_card = random.choice(power_cards)
await p.add_card(power_card, quantity=1)
@handlers.handler(XTPacket('cd', 'gcd'))
async def handle_get_card_data(p):
await p.send_xt('gcd', '|'.join(f'{card.card_id},{card.quantity},{card.member_quantity}'
for card in p.cards.values()))
@handlers.handler(XTPacket('cd', 'bpc'))
async def handle_buy_power_cards(p):
if p.coins >= 1500:
power_cards = random.sample(p.server.cards.power_cards, 3)
for card in power_cards:
await p.add_card(card, member_quantity=1)
await p.update(coins=p.coins - 1500).apply()
await p.send_xt('bpc', ','.join([str(card.id) for card in power_cards]), p.coins)
else:
await p.send_xt('bpc', 401)
|
autoPyTorch/pipeline/nodes/one_hot_encoding.py | mens-artis/Auto-PyTorch | 1,657 | 11123799 | <filename>autoPyTorch/pipeline/nodes/one_hot_encoding.py
__author__ = "<NAME>, <NAME> and <NAME>"
__version__ = "0.0.1"
__license__ = "BSD"
from autoPyTorch.pipeline.base.pipeline_node import PipelineNode
from autoPyTorch.utils.config.config_option import ConfigOption, to_bool
from sklearn.preprocessing import OneHotEncoder
from sklearn.compose import ColumnTransformer
import numpy as np
import scipy.sparse
class OneHotEncoding(PipelineNode):
def __init__(self):
super(OneHotEncoding, self).__init__()
self.encode_Y = False
def fit(self, pipeline_config, X, Y, dataset_info):
categorical_features = dataset_info.categorical_features
ohe = OneHotEncoder(categories="auto", sparse=False, handle_unknown="ignore")
encoder = ColumnTransformer(transformers=[("ohe", ohe, [i for i, f in enumerate(categorical_features) if f])], remainder="passthrough")
encoder.categories_ = np.array([])
encoder.categorical_features = categorical_features
if any(categorical_features) and not dataset_info.is_sparse:
# encode X
X = encoder.fit_transform(X)
encoder.categories_ = encoder.transformers_[0][1].categories_
# Y to matrix
Y, y_encoder = self.complete_y_tranformation(Y)
dataset_info.categorical_features = None
return {'X': X, 'one_hot_encoder': encoder, 'Y': Y, 'y_one_hot_encoder': y_encoder, 'dataset_info': dataset_info}
def predict(self, pipeline_config, X, one_hot_encoder):
categorical_features = pipeline_config["categorical_features"]
if categorical_features and any(categorical_features) and not scipy.sparse.issparse(X):
X = one_hot_encoder.transform(X)
return {'X': X, 'one_hot_encoder': one_hot_encoder}
def reverse_transform_y(self, Y, y_one_hot_encoder):
if y_one_hot_encoder is None:
return Y
return y_one_hot_encoder.categories_[0][np.argmax(Y, axis=1)].reshape(-1, 1)
def transform_y(self, Y, y_one_hot_encoder):
if y_one_hot_encoder is None:
return Y
return y_one_hot_encoder.transform(Y.reshape(-1, 1))
def complete_y_tranformation(self, Y):
# Y to matrix
y_encoder = None
Y = Y.astype(np.float32)
if len(Y.shape) == 1:
Y = Y.reshape(-1, 1)
# encode Y
if self.encode_Y:
y_encoder = OneHotEncoder(sparse=False, categories="auto", handle_unknown='ignore')
y_encoder.categories_ = np.array([])
Y = y_encoder.fit_transform(Y)
return Y, y_encoder |
src/maestral/utils/caches.py | gliptak/maestral | 436 | 11123803 | """Module containing cache implementations."""
from collections import OrderedDict
from threading import RLock
from typing import Any
class LRUCache:
"""A simple LRU cache implementation
:param capacity: Maximum number of entries to keep.
"""
_cache: OrderedDict
def __init__(self, capacity: int) -> None:
self._lock = RLock()
self._cache = OrderedDict()
self.capacity = capacity
def get(self, key: Any) -> Any:
"""
Get the cached value for a key. Mark as most recently used.
:param key: Key to query.
:returns: Cached value or None.
"""
with self._lock:
try:
self._cache.move_to_end(key)
return self._cache[key]
except KeyError:
return None
def put(self, key: Any, value: Any) -> None:
"""
Set the cached value for a key. Mark as most recently used.
:param key: Key to use. Must be hashable.
:param value: Value to cache.
"""
with self._lock:
self._cache[key] = value
self._cache.move_to_end(key)
if len(self._cache) > self.capacity:
self._cache.popitem(last=False)
def clear(self) -> None:
"""
Clears the cache.
"""
with self._lock:
self._cache.clear()
|
examples/tutorials/05_async_python/02_cube_blinker.py | rootless4real/cozmo-python-sdk | 794 | 11123830 | <filename>examples/tutorials/05_async_python/02_cube_blinker.py
#!/usr/bin/env python3
# Copyright (c) 2016 Anki, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License in the file LICENSE.txt or at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
'''Cube Blinker asynchronous example
Cozmo first looks around for a cube. Once a cube is found,
the cube's lights blink green in a circular fashion. The
script then waits for the cube to be tapped.
'''
import asyncio
import sys
import cozmo
class BlinkyCube(cozmo.objects.LightCube):
'''Subclass LightCube and add a light-chaser effect.'''
def __init__(self, *a, **kw):
super().__init__(*a, **kw)
self._chaser = None
def start_light_chaser(self):
'''Cycles the lights around the cube with 1 corner lit up green,
changing to the next corner every 0.1 seconds.
'''
if self._chaser:
raise ValueError("Light chaser already running")
async def _chaser():
while True:
for i in range(4):
cols = [cozmo.lights.off_light] * 4
cols[i] = cozmo.lights.green_light
self.set_light_corners(*cols)
await asyncio.sleep(0.1, loop=self._loop)
self._chaser = asyncio.ensure_future(_chaser(), loop=self._loop)
def stop_light_chaser(self):
if self._chaser:
self._chaser.cancel()
self._chaser = None
# Make sure World knows how to instantiate the subclass
cozmo.world.World.light_cube_factory = BlinkyCube
async def cozmo_program(robot: cozmo.robot.Robot):
'''The async equivalent of 01_cube_blinker_sync.
The usage of ``async def`` makes the cozmo_program method a coroutine.
Within a coroutine, ``await`` can be used. With ``await``, the statement
blocks until the request being waited for has completed. Meanwhile
the event loop continues in the background.
For instance, the statement
``await robot.world.wait_for_observed_light_cube(timeout=60)``
blocks until Cozmo discovers a light cube or the 60 second timeout
elapses, whichever occurs first.
Likewise, the statement ``await cube.wait_for_tap(timeout=10)``
blocks until the tap event is received or the 10 second timeout occurs,
whichever occurs first.
For more information, see
https://docs.python.org/3/library/asyncio-task.html
'''
cube = None
look_around = robot.start_behavior(cozmo.behavior.BehaviorTypes.LookAroundInPlace)
try:
cube = await robot.world.wait_for_observed_light_cube(timeout=60)
except asyncio.TimeoutError:
print("Didn't find a cube :-(")
return
finally:
look_around.stop()
cube.start_light_chaser()
try:
print("Waiting for cube to be tapped")
await cube.wait_for_tap(timeout=10)
print("Cube tapped")
except asyncio.TimeoutError:
print("No-one tapped our cube :-(")
finally:
cube.stop_light_chaser()
cube.set_lights_off()
cozmo.run_program(cozmo_program)
|
openff/toolkit/utils/ambertools_wrapper.py | andrew-abimansour/openff-toolkit | 120 | 11123868 | """
Wrapper class providing a minimal consistent interface to `AmberTools <http://ambermd.org/AmberTools.php>`_.
"""
__all__ = ("AmberToolsToolkitWrapper",)
# =============================================================================================
# IMPORTS
# =============================================================================================
import subprocess
import tempfile
from collections import defaultdict
from distutils.spawn import find_executable
import numpy as np
try:
from openmm import unit
except ImportError:
from simtk import unit
from openff.toolkit.utils import base_wrapper, rdkit_wrapper
from openff.toolkit.utils.exceptions import (
AntechamberNotFoundError,
ChargeCalculationError,
ChargeMethodUnavailableError,
ToolkitUnavailableException,
)
from openff.toolkit.utils.utils import temporary_cd
# =============================================================================================
# IMPLEMENTATION
# =============================================================================================
class AmberToolsToolkitWrapper(base_wrapper.ToolkitWrapper):
"""
AmberTools toolkit wrapper
.. warning :: This API is experimental and subject to change.
"""
_toolkit_name = "AmberTools"
_toolkit_installation_instructions = (
"The AmberTools toolkit (free and open source) can be found at "
"https://anaconda.org/conda-forge/ambertools"
)
def __init__(self):
super().__init__()
self._toolkit_file_read_formats = []
self._toolkit_file_write_formats = []
if not self.is_available():
raise ToolkitUnavailableException(
f"The required toolkit {self._toolkit_name} is not "
f"available. {self._toolkit_installation_instructions}"
)
# TODO: More reliable way to extract AmberTools version
out = subprocess.check_output(["antechamber", "-L"])
ambertools_version = out.decode("utf-8").split("\n")[1].split()[3].strip(":")
self._toolkit_version = ambertools_version
# TODO: Find AMBERHOME or executable home, checking miniconda if needed
# Store an instance of an RDKitToolkitWrapper for file I/O
self._rdkit_toolkit_wrapper = rdkit_wrapper.RDKitToolkitWrapper()
@staticmethod
def is_available():
"""
Check whether the AmberTools toolkit is installed
Returns
-------
is_installed : bool
True if AmberTools is installed, False otherwise.
"""
# TODO: Check all tools needed
# TODO: How should we implement find_executable?
ANTECHAMBER_PATH = find_executable("antechamber")
if ANTECHAMBER_PATH is None:
return False
# AmberToolsToolkitWrapper needs RDKit to do basically anything, since its interface requires SDF I/O
if not (rdkit_wrapper.RDKitToolkitWrapper.is_available()):
return False
return True
def assign_partial_charges(
self,
molecule,
partial_charge_method=None,
use_conformers=None,
strict_n_conformers=False,
normalize_partial_charges=True,
_cls=None,
):
"""
Compute partial charges with AmberTools using antechamber/sqm, and assign
the new values to the partial_charges attribute.
.. warning :: This API experimental and subject to change.
.. todo ::
* Do we want to also allow ESP/RESP charges?
Parameters
----------
molecule : openff.toolkit.topology.Molecule
Molecule for which partial charges are to be computed
partial_charge_method : str, optional, default=None
The charge model to use. One of ['gasteiger', 'am1bcc', 'am1-mulliken'].
If None, 'am1-mulliken' will be used.
use_conformers : iterable of openmm.unit.Quantity-wrapped numpy arrays, each
with shape (n_atoms, 3) and dimension of distance. Optional, default = None
List of (n_atoms x 3) openmm.unit.Quantities to use for partial charge calculation.
If None, an appropriate number of conformers will be generated.
strict_n_conformers : bool, default=False
Whether to raise an exception if an invalid number of conformers is provided for
the given charge method.
If this is False and an invalid number of conformers is found, a warning will be raised.
normalize_partial_charges : bool, default=True
Whether to offset partial charges so that they sum to the total formal charge of the molecule.
This is used to prevent accumulation of rounding errors when the partial charge generation method has
low precision.
_cls : class
Molecule constructor
Raises
------
ChargeMethodUnavailableError if the requested charge method can not be handled by this toolkit
ChargeCalculationError if the charge method is supported by this toolkit, but fails
"""
import os
import subprocess
from openff.toolkit.topology import Molecule
if partial_charge_method is None:
partial_charge_method = "am1-mulliken"
else:
# Standardize method name for string comparisons
partial_charge_method = partial_charge_method.lower()
SUPPORTED_CHARGE_METHODS = {
"am1bcc": {
"antechamber_keyword": "bcc",
"min_confs": 1,
"max_confs": 1,
"rec_confs": 1,
},
"am1-mulliken": {
"antechamber_keyword": "mul",
"min_confs": 1,
"max_confs": 1,
"rec_confs": 1,
},
"gasteiger": {
"antechamber_keyword": "gas",
"min_confs": 0,
"max_confs": 0,
"rec_confs": 0,
},
}
if partial_charge_method not in SUPPORTED_CHARGE_METHODS:
raise ChargeMethodUnavailableError(
f"partial_charge_method '{partial_charge_method}' is not available from AmberToolsToolkitWrapper. "
f"Available charge methods are {list(SUPPORTED_CHARGE_METHODS.keys())} "
)
charge_method = SUPPORTED_CHARGE_METHODS[partial_charge_method]
if _cls is None:
_cls = Molecule
# Make a temporary copy of the molecule, since we'll be messing with its conformers
mol_copy = _cls(molecule)
if use_conformers is None:
if charge_method["rec_confs"] == 0:
mol_copy._conformers = None
else:
mol_copy.generate_conformers(
n_conformers=charge_method["rec_confs"],
rms_cutoff=0.25 * unit.angstrom,
toolkit_registry=rdkit_wrapper.RDKitToolkitWrapper(),
)
# TODO: What's a "best practice" RMS cutoff to use here?
else:
mol_copy._conformers = None
for conformer in use_conformers:
mol_copy._add_conformer(conformer)
self._check_n_conformers(
mol_copy,
partial_charge_method=partial_charge_method,
min_confs=charge_method["min_confs"],
max_confs=charge_method["max_confs"],
strict_n_conformers=strict_n_conformers,
)
# Find the path to antechamber
# TODO: How should we implement find_executable?
ANTECHAMBER_PATH = find_executable("antechamber")
if ANTECHAMBER_PATH is None:
raise AntechamberNotFoundError(
"Antechamber not found, cannot run charge_mol()"
)
# Compute charges
with tempfile.TemporaryDirectory() as tmpdir:
with temporary_cd(tmpdir):
net_charge = mol_copy.total_charge.value_in_unit(unit.elementary_charge)
# Write out molecule in SDF format
# TODO: How should we handle multiple conformers?
self._rdkit_toolkit_wrapper.to_file(
mol_copy, "molecule.sdf", file_format="sdf"
)
# Compute desired charges
# TODO: Add error handling if antechamber chokes
short_charge_method = charge_method["antechamber_keyword"]
subprocess.check_output(
[
"antechamber",
"-i",
"molecule.sdf",
"-fi",
"sdf",
"-o",
"charged.mol2",
"-fo",
"mol2",
"-pf",
"yes",
"-dr",
"n",
"-c",
short_charge_method,
"-nc",
str(net_charge),
]
)
# Write out just charges
subprocess.check_output(
[
"antechamber",
"-dr",
"n",
"-i",
"charged.mol2",
"-fi",
"mol2",
"-o",
"charges2.mol2",
"-fo",
"mol2",
"-c",
"wc",
"-cf",
"charges.txt",
"-pf",
"yes",
]
)
# Check to ensure charges were actually produced
if not os.path.exists("charges.txt"):
# TODO: copy files into local directory to aid debugging?
raise ChargeCalculationError(
"Antechamber/sqm partial charge calculation failed on "
"molecule {} (SMILES {})".format(
molecule.name, molecule.to_smiles()
)
)
# Read the charges
with open("charges.txt", "r") as infile:
contents = infile.read()
text_charges = contents.split()
charges = np.zeros([molecule.n_atoms], np.float64)
for index, token in enumerate(text_charges):
charges[index] = float(token)
# TODO: Ensure that the atoms in charged.mol2 are in the same order as in molecule.sdf
charges = unit.Quantity(charges, unit.elementary_charge)
molecule.partial_charges = charges
if normalize_partial_charges:
molecule._normalize_partial_charges()
def compute_partial_charges_am1bcc(
self, molecule, use_conformers=None, strict_n_conformers=False
):
"""
Compute partial charges with AmberTools using antechamber/sqm. This will calculate AM1-BCC charges on the first
conformer only.
.. warning :: This API is experimental and subject to change.
Parameters
----------
molecule : Molecule
Molecule for which partial charges are to be computed
use_conformers : iterable of openmm.unit.Quantity-wrapped numpy arrays,
each with shape (n_atoms, 3) and dimension of distance. Optional, default = None
Coordinates to use for partial charge calculation. If None, an appropriate number
of conformers will be generated.
strict_n_conformers : bool, default=False
Whether to raise an exception if an invalid number of conformers is provided.
If this is False and an invalid number of conformers is found, a warning will
be raised instead of an Exception.
Returns
-------
charges : numpy.array of shape (natoms) of type float
The partial charges
"""
import warnings
warnings.warn(
"compute_partial_charges_am1bcc will be deprecated in an upcoming release. "
"Use assign_partial_charges(partial_charge_method='am1bcc') instead.",
DeprecationWarning,
)
self.assign_partial_charges(
molecule,
partial_charge_method="AM1BCC",
use_conformers=use_conformers,
strict_n_conformers=strict_n_conformers,
)
return molecule.partial_charges
def _modify_sqm_in_to_request_bond_orders(self, file_path):
"""
Modify a sqm.in file produced by antechamber to include the "printbondorders=1" directive
in the header. This method will overwrite the original file.
Parameters
----------
file_path : str
The path to sqm.in
"""
data = open(file_path).read()
# Original sqm.in file headerlooks like:
# Run semi-empirical minimization
# &qmmm
# qm_theory='AM1', grms_tol=0.0005,
# scfconv=1.d-10, ndiis_attempts=700, qmcharge=0,
# /
# ... (atom coordinates in something like XYZ format) ...
# To get WBOs, we need to add "printbondorders=1" to the list of keywords
# First, split the sqm.in text at the "/" mark at the end of the header
datasp = data.split("/")
# Insert the "printbondorders" directive in a new line and re-add the "/"
datasp.insert(1, "printbondorders=1, \n /")
# Reassemble the file text
new_data = "".join(datasp)
# Write the new file contents, overwriting the original file.
with open(file_path, "w") as of:
of.write(new_data)
def _get_fractional_bond_orders_from_sqm_out(
self, file_path, validate_elements=None
):
"""
Process a SQM output file containing bond orders, and return a dict of the form
dict[atom_1_index, atom_2_index] = fractional_bond_order
Parameters
----------
file_path : str
File path for sqm output file
validate_elements : iterable of str
The element symbols expected in molecule index order. A ValueError will be raised
if the elements are not found in this order.
Returns
-------
bond_orders : dict[(int, int)]: float
A dictionary where the keys are tuples of two atom indices and the values are
floating-point bond orders. The keys are sorted in ascending order, such that
the lower atom index is key[0] and the higher is key[1].
"""
# Example sqm.out section with WBOs:
# Bond Orders
#
# QMMM: NUM1 ELEM1 NUM2 ELEM2 BOND_ORDER
# QMMM: 2 C 1 C 1.41107532
# QMMM: 3 C 1 C 1.41047804
# ...
# QMMM: 15 H 13 H 0.00000954
# QMMM: 15 H 14 H 0.00000813
#
# --------- Calculation Completed ----------
data = open(file_path).read()
begin_sep = """ Bond Orders
QMMM: NUM1 ELEM1 NUM2 ELEM2 BOND_ORDER
"""
end_sep = """
--------- Calculation Completed ----------
"""
# Extract the chunk of text between begin_sep and end_sep, and split it by newline
fbo_lines = data.split(begin_sep)[1].split(end_sep)[0].split("\n")
# Iterate over the lines and populate the dict to return
bond_orders = dict()
for line in fbo_lines:
linesp = line.split()
atom_index_1 = int(linesp[1])
atom_element_1 = linesp[2]
atom_index_2 = int(linesp[3])
atom_element_2 = linesp[4]
bond_order = float(linesp[5])
# If validate_elements was provided, ensure that the ordering of element symbols is what we expected
if validate_elements is not None:
if (atom_element_1 != validate_elements[atom_index_1 - 1]) or (
atom_element_2 != validate_elements[atom_index_2 - 1]
):
# raise ValueError('\n'.join(fbo_lines))
raise ValueError(
f"Elements or indexing in sqm output differ from expectation. "
f"Expected {validate_elements[atom_index_1]} with index {atom_index_1} and "
f"{validate_elements[atom_index_2]} with index {atom_index_2}, "
f"but SQM output has {atom_element_1} and {atom_element_2} for the same atoms."
)
# To make lookup easier, we identify bonds as integer tuples with the lowest atom index
# first and the highest second.
index_tuple = tuple(sorted([atom_index_1, atom_index_2]))
bond_orders[index_tuple] = bond_order
return bond_orders
def assign_fractional_bond_orders(
self, molecule, bond_order_model=None, use_conformers=None, _cls=None
):
"""
Update and store list of bond orders this molecule. Bond orders are stored on each
bond, in the `bond.fractional_bond_order` attribute.
.. warning :: This API is experimental and subject to change.
Parameters
----------
molecule : openff.toolkit.topology.molecule Molecule
The molecule to assign wiberg bond orders to
bond_order_model : str, optional, default=None
The charge model to use. Only allowed value is 'am1-wiberg'. If None, 'am1-wiberg' will be used.
use_conformers : iterable of openmm.unit.Quantity(np.array) with shape (n_atoms, 3)
and dimension of distance, optional, default=None
The conformers to use for fractional bond order calculation. If None, an appropriate
number of conformers will be generated by an available ToolkitWrapper.
_cls : class
Molecule constructor
"""
from openff.toolkit.topology import Molecule
# Find the path to antechamber
# TODO: How should we implement find_executable?
ANTECHAMBER_PATH = find_executable("antechamber")
if ANTECHAMBER_PATH is None:
raise AntechamberNotFoundError(
"Antechamber not found, cannot run "
"AmberToolsToolkitWrapper.assign_fractional_bond_orders()"
)
if _cls is None:
_cls = Molecule
# Make a copy since we'll be messing with this molecule's conformers
temp_mol = _cls(molecule)
if use_conformers is None:
temp_mol.generate_conformers(
n_conformers=1,
toolkit_registry=self._rdkit_toolkit_wrapper,
)
else:
temp_mol._conformers = None
for conformer in use_conformers:
temp_mol._add_conformer(conformer)
if len(temp_mol.conformers) == 0:
raise ValueError(
"No conformers present in molecule submitted for fractional bond order calculation. Consider "
"loading the molecule from a file with geometry already present or running "
"molecule.generate_conformers() before calling molecule.assign_fractional_bond_orders"
)
# Compute bond orders
bond_order_model_to_antechamber_keyword = {"am1-wiberg": "mul"}
supported_bond_order_models = list(
bond_order_model_to_antechamber_keyword.keys()
)
if bond_order_model is None:
bond_order_model = "am1-wiberg"
bond_order_model = bond_order_model.lower()
if bond_order_model not in supported_bond_order_models:
raise ValueError(
f"Bond order model '{bond_order_model}' is not supported by AmberToolsToolkitWrapper. "
f"Supported models are {supported_bond_order_models}"
)
ac_charge_keyword = bond_order_model_to_antechamber_keyword[bond_order_model]
bond_orders = defaultdict(list)
for conformer in [*temp_mol.conformers]:
with tempfile.TemporaryDirectory() as tmpdir:
with temporary_cd(tmpdir):
net_charge = temp_mol.total_charge
# Write out molecule in SDF format
temp_mol._conformers = [conformer]
self._rdkit_toolkit_wrapper.to_file(
temp_mol, "molecule.sdf", file_format="sdf"
)
# Prepare sqm.in file as if we were going to run charge calc
# TODO: Add error handling if antechamber chokes
subprocess.check_output(
[
"antechamber",
"-i",
"molecule.sdf",
"-fi",
"sdf",
"-o",
"sqm.in",
"-fo",
"sqmcrt",
"-pf",
"yes",
"-c",
ac_charge_keyword,
"-nc",
str(net_charge),
]
)
# Modify sqm.in to request bond order calculation
self._modify_sqm_in_to_request_bond_orders("sqm.in")
# Run sqm to get bond orders
subprocess.check_output(
["sqm", "-i", "sqm.in", "-o", "sqm.out", "-O"]
)
# Ensure that antechamber/sqm did not change the indexing by checking against
# an ordered list of element symbols for this molecule
expected_elements = [at.element.symbol for at in molecule.atoms]
conformer_bond_orders = (
self._get_fractional_bond_orders_from_sqm_out(
"sqm.out", validate_elements=expected_elements
)
)
for bond_indices, value in conformer_bond_orders.items():
bond_orders[bond_indices].append(value)
# Note that sqm calculate WBOs for ALL PAIRS of atoms, not just those that have
# bonds defined in the original molecule. So here we iterate over the bonds in
# the original molecule and only nab the WBOs for those.
for bond in molecule.bonds:
# The atom index tuples that act as bond indices are ordered from lowest to highest by
# _get_fractional_bond_orders_from_sqm_out, so here we make sure that we look them up in
# sorted order as well
sorted_atom_indices = sorted(
tuple([bond.atom1_index + 1, bond.atom2_index + 1])
)
bond.fractional_bond_order = np.mean(
bond_orders[tuple(sorted_atom_indices)]
)
|
xfdnn/rt/scripts/layerwise.py | yarenty/ml-suite | 334 | 11123876 | <filename>xfdnn/rt/scripts/layerwise.py<gh_stars>100-1000
#!/usr/bin/env python
#
# // SPDX-License-Identifier: BSD-3-CLAUSE
#
# (C) Copyright 2018, Xilinx, Inc.
#
import sys, os
sys.path.append(os.environ['MLSUITE_ROOT'] + '/xfdnn/rt')
import xdnn, xdnn_io
import numpy as np
import json, copy
def generateLayerwiseJson(layername):
#args = xdnn_io.processCommandLine()
parser = xdnn_io.default_parser_args()
parser.add_argument('--layerindex', type=int, default=0, help='Index value for layer in json', required=True)
argvt = parser.parse_args()
args = xdnn_io.make_dict_args(argvt)
with open (args['netcfg'], 'r') as fp:
data = json.load(fp)
#print json.dumps(data, indent=2)
# Get layers from json
nodes = data['network']
#print "Total layers (nodes): ", len(nodes)
reachedNode = False
for node in nodes:
if node['active'] == 0:
continue
#print "Active: ", node['active'], " ", node['name']
if reachedNode == False and node['name'] == layername:
reachedNode = True
elif reachedNode and node['name'] != layername:
node['active'] = 0
fname = str(layername) + str('.json')
fjson = fname.replace('/', '_')
with open(fjson, 'w') as wfp:
json.dump(data, wfp, indent=2, sort_keys=True)
return fjson
def networkForward(netcfg, layername):
#args = xdnn_io.processCommandLine()
parser = xdnn_io.default_parser_args()
parser.add_argument('--layerindex', type=int, default=0, help='Index value for layer in json', required=True)
argvt = parser.parse_args()
args = xdnn_io.make_dict_args(argvt)
args['netcfg'] = netcfg
# Hardcode these parameters, so we only have to look at performance of 1 PE
args["batch_sz"] = 1
args["PE"] = 0
#print "{:-^100}".format(' Before: createHandle ')
ret, handles = xdnn.createHandle(args['xclbin'], "kernelSxdnn_0")
#print "{:-^100}".format(' After: createHandle ')
if ret != 0:
sys.exit(1)
fpgaRT = xdnn.XDNNFPGAOp(handles, args)
#print "{:-^100}".format('1')
fpgaOutput = fpgaRT.getOutputs()
#print "{:-^100}".format('2')
fpgaInput = fpgaRT.getInputs()
#print "{:-^100}".format('3')
img_paths = xdnn_io.getFilePaths(args['images'])
inShape = (args['batch_sz'],) + tuple ( tuple (fpgaRT.getInputDescriptors().values() )[0][1:] )
firstInput = list(fpgaInput.values())[0]
firstOutput = list (fpgaOutput.values())[0]
for i in xrange(0, len(img_paths), args['batch_sz']):
pl = []
for j, p in enumerate(img_paths[i:i + args['batch_sz']]):
firstInput[0, ...], _ = xdnn_io.loadImageBlobFromFile(img_paths[0], args['img_raw_scale'], args['img_mean'], args['img_input_scale'], inShape[2], inShape[3])
pl.append(p)
with open(args['netcfg']) as fp:
data = json.load(fp)
#print json.dumps(data, indent=2)
# Strip nodes that don't run in hardware
nodes = data['network']
nodes = [x for x in nodes if x['xdnn_kv']]
nLayers = len(nodes)
# How many iterations to run, and average across
iterations = 1
# Initialize empty list to hold accumulated runtime
t1 = []
for k in range(iterations):
t1.append(0.0)
# Run N iterations of network permutations
for l in range(iterations):
fpgaRT.execute(fpgaInput, fpgaOutput)
t1[l] += (fpgaRT.get_exec_time())
#for node in nodes:
# print node['name']
# Average it
avetime = sum(t1)/iterations
#print "{:<25} = {:<25}".format(layername, avetime)
return avetime
xdnn.closeHandle()
del fpgaRT
del fpgaInput
del fpgaOutput
del ret
def getCurrentLayerByIndex(index = 0):
#args = xdnn_io.processCommandLine()
parser = xdnn_io.default_parser_args()
parser.add_argument('--layerindex', type=int, default=0, help='Index value for layer in json', required=True)
argvt = parser.parse_args()
args = xdnn_io.make_dict_args(argvt)
if 'layerindex' in args:
index = args['layerindex']
with open(args['netcfg']) as fp:
data = json.load(fp)
# Strip nodes that don't run in hardware
nodes = data['network']
nodes = [x for x in nodes if x['xdnn_kv'] and x['active'] == 1]
# Get layername
if index >= len(nodes):
return None, None
if nodes[index]['xdnn_kv']['slice'] == "0":
return nodes[index]['name'], "DBL"
return nodes[index]['name'], nodes[index]['xdnn_kv']['XNOp']
if __name__ == '__main__':
parser = xdnn_io.default_parser_args()
parser.add_argument('--layerindex', type=int, default=0, help='Index value for layer in json', required=True)
argvt = parser.parse_args()
args = xdnn_io.make_dict_args(argvt)
#print json.dumps(args, indent=2)
# Get layer name
layername, opname = getCurrentLayerByIndex()
if layername is None and opname is None:
print "All = Done"
sys.exit(0)
if opname is not None and layername is None:
print "DataMovementLayer = 0"
sys.exit(0)
if opname == "DBL":
layername = layername + "-DBL"
print layername,"= 0"
sys.exit(0)
# print "\n{:-^100}".format(layername)
# Generate compiler JSON till this layer
jsonname = generateLayerwiseJson(layername)
# print "\n{:-^100}".format(jsonname)
# Get the latency of the network till this layer
latency = networkForward(jsonname, layername)
print "{} = {}".format(layername, latency)
|
example/market/sub_pricedepth_bbo.py | bailzx5522/huobi_Python | 611 | 11123889 |
from huobi.client.market import MarketClient
def callback(price_depth_event: 'PriceDepthBboEvent'):
price_depth_event.print_object()
print()
def error(e: 'HuobiApiException'):
print(e.error_code + e.error_message)
market_client = MarketClient()
market_client.sub_pricedepth_bbo("btcusdt", callback, error)
|
RecoTracker/DebugTools/python/TrackAlgoCompareUtil_cff.py | ckamtsikis/cmssw | 852 | 11123892 | import FWCore.ParameterSet.Config as cms
from RecoTracker.DebugTools.TrackAlgoCompareUtil_cfi import *
|
cflearn/models/cv/encoder/backbone/settings/mobilenet.py | carefree0910/carefree-learn | 400 | 11123893 | from typing import List
from collections import OrderedDict
from ..api import Preset
remove_layers: List[str] = []
target_layers = OrderedDict(
slice0="stage0",
slice1="stage1",
slice2="stage2",
slice3="stage3",
slice4="stage4",
)
@Preset.register_settings()
class MobileNetPreset(Preset):
remove_layers = {
"mobilenet_v2": remove_layers,
}
target_layers = {
"mobilenet_v2": target_layers,
}
increment_configs = {
"mobilenet_v2": {"out_channels": [16, 24, 32, 96, 320]},
}
__all__ = ["MobileNetPreset"]
|
cisco-ios-xr/ydk/models/cisco_ios_xr/Cisco_IOS_XR_sysadmin_vm.py | CiscoDevNet/ydk-py | 177 | 11123901 | <reponame>CiscoDevNet/ydk-py
""" Cisco_IOS_XR_sysadmin_vm
This module contains definitions
for the Calvados model objects.
This module contains the YANG definitions
for the Cisco IOS\-XR SysAdmin
'vm profile\|cpu\|memory' commands.
Copyright(c) 2018 by Cisco Systems, Inc.
All rights reserved.
Copyright (c) 2012\-2018 by Cisco Systems, Inc.
All rights reserved.
"""
import sys
from collections import OrderedDict
from ydk.types import Entity as _Entity_
from ydk.types import EntityPath, Identity, Enum, YType, YLeaf, YLeafList, YList, LeafDataList, Bits, Empty, Decimal64
from ydk.types import Entity, EntityPath, Identity, Enum, YType, YLeaf, YLeafList, YList, LeafDataList, Bits, Empty, Decimal64
from ydk.filters import YFilter
from ydk.errors import YError, YModelError
from ydk.errors.error_handler import handle_type_error as _handle_type_error
class Vm(_Entity_):
"""
.. attribute:: config
**type**\: :py:class:`Config <ydk.models.cisco_ios_xr.Cisco_IOS_XR_sysadmin_vm.Vm.Config>`
"""
_prefix = 'vm'
_revision = '2018-11-20'
def __init__(self):
if sys.version_info > (3,):
super().__init__()
else:
super(Vm, self).__init__()
self._top_entity = None
self.yang_name = "vm"
self.yang_parent_name = "Cisco-IOS-XR-sysadmin-vm"
self.is_top_level_class = True
self.has_list_ancestor = False
self.ylist_key_names = []
self._child_classes = OrderedDict([("config", ("config", Vm.Config))])
self._leafs = OrderedDict()
self.config = Vm.Config()
self.config.parent = self
self._children_name_map["config"] = "config"
self._segment_path = lambda: "Cisco-IOS-XR-sysadmin-vm:vm"
self._is_frozen = True
def __setattr__(self, name, value):
self._perform_setattr(Vm, [], name, value)
class Config(_Entity_):
"""
.. attribute:: hw_profile
**type**\: :py:class:`HwProfile <ydk.models.cisco_ios_xr.Cisco_IOS_XR_sysadmin_vm.Vm.Config.HwProfile>`
.. attribute:: memory
**type**\: :py:class:`Memory <ydk.models.cisco_ios_xr.Cisco_IOS_XR_sysadmin_vm.Vm.Config.Memory>`
.. attribute:: cpu
**type**\: :py:class:`Cpu <ydk.models.cisco_ios_xr.Cisco_IOS_XR_sysadmin_vm.Vm.Config.Cpu>`
"""
_prefix = 'vm'
_revision = '2018-11-20'
def __init__(self):
if sys.version_info > (3,):
super().__init__()
else:
super(Vm.Config, self).__init__()
self.yang_name = "config"
self.yang_parent_name = "vm"
self.is_top_level_class = False
self.has_list_ancestor = False
self.ylist_key_names = []
self._child_classes = OrderedDict([("hw-profile", ("hw_profile", Vm.Config.HwProfile)), ("memory", ("memory", Vm.Config.Memory)), ("cpu", ("cpu", Vm.Config.Cpu))])
self._leafs = OrderedDict()
self.hw_profile = Vm.Config.HwProfile()
self.hw_profile.parent = self
self._children_name_map["hw_profile"] = "hw-profile"
self.memory = Vm.Config.Memory()
self.memory.parent = self
self._children_name_map["memory"] = "memory"
self.cpu = Vm.Config.Cpu()
self.cpu.parent = self
self._children_name_map["cpu"] = "cpu"
self._segment_path = lambda: "config"
self._absolute_path = lambda: "Cisco-IOS-XR-sysadmin-vm:vm/%s" % self._segment_path()
self._is_frozen = True
def __setattr__(self, name, value):
self._perform_setattr(Vm.Config, [], name, value)
class HwProfile(_Entity_):
"""
.. attribute:: profile
xrv9k profile vpe\|vrr
**type**\: :py:class:`Profile <ydk.models.cisco_ios_xr.Cisco_IOS_XR_sysadmin_vm.Vm.Config.HwProfile.Profile>`
"""
_prefix = 'vm'
_revision = '2018-11-20'
def __init__(self):
if sys.version_info > (3,):
super().__init__()
else:
super(Vm.Config.HwProfile, self).__init__()
self.yang_name = "hw-profile"
self.yang_parent_name = "config"
self.is_top_level_class = False
self.has_list_ancestor = False
self.ylist_key_names = []
self._child_classes = OrderedDict([])
self._leafs = OrderedDict([
('profile', (YLeaf(YType.enumeration, 'profile'), [('ydk.models.cisco_ios_xr.Cisco_IOS_XR_sysadmin_vm', 'Vm', 'Config.HwProfile.Profile')])),
])
self.profile = None
self._segment_path = lambda: "hw-profile"
self._absolute_path = lambda: "Cisco-IOS-XR-sysadmin-vm:vm/config/%s" % self._segment_path()
self._is_frozen = True
def __setattr__(self, name, value):
self._perform_setattr(Vm.Config.HwProfile, ['profile'], name, value)
class Profile(Enum):
"""
Profile (Enum Class)
xrv9k profile vpe\|vrr
.. data:: vrr = 0
"""
vrr = Enum.YLeaf(0, "vrr")
@staticmethod
def _meta_info():
from ydk.models.cisco_ios_xr._meta import _Cisco_IOS_XR_sysadmin_vm as meta
return meta._meta_table['Vm.Config.HwProfile.Profile']
@staticmethod
def _meta_info():
from ydk.models.cisco_ios_xr._meta import _Cisco_IOS_XR_sysadmin_vm as meta
return meta._meta_table['Vm.Config.HwProfile']['meta_info']
class Memory(_Entity_):
"""
.. attribute:: admin
admin container memory in GB
**type**\: int
**range:** 0..4294967295
.. attribute:: rp
rp container memory in GB
**type**\: int
**range:** 0..4294967295
.. attribute:: lc
lc container memory in GB
**type**\: int
**range:** 0..4294967295
"""
_prefix = 'vm'
_revision = '2018-11-20'
def __init__(self):
if sys.version_info > (3,):
super().__init__()
else:
super(Vm.Config.Memory, self).__init__()
self.yang_name = "memory"
self.yang_parent_name = "config"
self.is_top_level_class = False
self.has_list_ancestor = False
self.ylist_key_names = []
self._child_classes = OrderedDict([])
self._leafs = OrderedDict([
('admin', (YLeaf(YType.uint32, 'admin'), ['int'])),
('rp', (YLeaf(YType.uint32, 'rp'), ['int'])),
('lc', (YLeaf(YType.uint32, 'lc'), ['int'])),
])
self.admin = None
self.rp = None
self.lc = None
self._segment_path = lambda: "memory"
self._absolute_path = lambda: "Cisco-IOS-XR-sysadmin-vm:vm/config/%s" % self._segment_path()
self._is_frozen = True
def __setattr__(self, name, value):
self._perform_setattr(Vm.Config.Memory, ['admin', 'rp', 'lc'], name, value)
@staticmethod
def _meta_info():
from ydk.models.cisco_ios_xr._meta import _Cisco_IOS_XR_sysadmin_vm as meta
return meta._meta_table['Vm.Config.Memory']['meta_info']
class Cpu(_Entity_):
"""
.. attribute:: assign
assign cpu cores to control/data plane
**type**\: str
**pattern:** 0(\-[0\-9]+)?/[0\-9]+(\-[0\-9]+)?
"""
_prefix = 'vm'
_revision = '2018-11-20'
def __init__(self):
if sys.version_info > (3,):
super().__init__()
else:
super(Vm.Config.Cpu, self).__init__()
self.yang_name = "cpu"
self.yang_parent_name = "config"
self.is_top_level_class = False
self.has_list_ancestor = False
self.ylist_key_names = []
self._child_classes = OrderedDict([])
self._leafs = OrderedDict([
('assign', (YLeaf(YType.str, 'assign'), ['str'])),
])
self.assign = None
self._segment_path = lambda: "cpu"
self._absolute_path = lambda: "Cisco-IOS-XR-sysadmin-vm:vm/config/%s" % self._segment_path()
self._is_frozen = True
def __setattr__(self, name, value):
self._perform_setattr(Vm.Config.Cpu, ['assign'], name, value)
@staticmethod
def _meta_info():
from ydk.models.cisco_ios_xr._meta import _Cisco_IOS_XR_sysadmin_vm as meta
return meta._meta_table['Vm.Config.Cpu']['meta_info']
@staticmethod
def _meta_info():
from ydk.models.cisco_ios_xr._meta import _Cisco_IOS_XR_sysadmin_vm as meta
return meta._meta_table['Vm.Config']['meta_info']
def clone_ptr(self):
self._top_entity = Vm()
return self._top_entity
@staticmethod
def _meta_info():
from ydk.models.cisco_ios_xr._meta import _Cisco_IOS_XR_sysadmin_vm as meta
return meta._meta_table['Vm']['meta_info']
|
integration/continuous_test.py | drozzy/autonomous-learning-library | 584 | 11123948 | import unittest
from all.environments import GymEnvironment
from all.presets.continuous import ddpg, ppo, sac
from validate_agent import validate_agent
class TestContinuousPresets(unittest.TestCase):
def test_ddpg(self):
validate_agent(
ddpg.device('cpu').hyperparameters(replay_start_size=50),
GymEnvironment('LunarLanderContinuous-v2')
)
def test_ppo(self):
validate_agent(
ppo.device('cpu'),
GymEnvironment('LunarLanderContinuous-v2')
)
def test_sac(self):
validate_agent(
sac.device('cpu').hyperparameters(replay_start_size=50),
GymEnvironment('LunarLanderContinuous-v2')
)
if __name__ == '__main__':
unittest.main()
|
deep_privacy/inference/deep_privacy_anonymizer.py | chinitaberrio/DeepPrivacy | 1,128 | 11124003 | <gh_stars>1000+
import numpy as np
import torch
import deep_privacy.torch_utils as torch_utils
import cv2
import pathlib
import typing
from deep_privacy.detection.detection_api import ImageAnnotation
from .anonymizer import Anonymizer
from . import infer
def batched_iterator(batch, batch_size):
k = list(batch.keys())[0]
num_samples = len(batch[k])
num_batches = int(np.ceil(num_samples / batch_size))
for idx in range(num_batches):
start = batch_size * idx
end = start + batch_size
yield {
key: torch_utils.to_cuda(arr[start:end])
for key, arr in batch.items()
}
class DeepPrivacyAnonymizer(Anonymizer):
def __init__(self, generator, batch_size, save_debug,
fp16_inference: bool,
truncation_level=5, **kwargs):
super().__init__(**kwargs)
self.inference_imsize = self.cfg.models.max_imsize
self.batch_size = batch_size
self.pose_size = self.cfg.models.pose_size
self.generator = generator
self.truncation_level = truncation_level
self.save_debug = save_debug
self.fp16_inference = fp16_inference
self.debug_directory = pathlib.Path(".debug", "inference")
self.debug_directory.mkdir(exist_ok=True, parents=True)
@torch.no_grad()
def _get_face(self, batch):
keys = ["condition", "mask", "landmarks", "z"]
forward = [batch[k] for k in keys]
# print([x.shape for x in forward])
with torch.cuda.amp.autocast(enabled=self.fp16_inference):
return self.generator(*forward).cpu()
@torch.no_grad()
def anonymize_images(self,
images: np.ndarray,
image_annotations: typing.List[ImageAnnotation]
) -> typing.List[np.ndarray]:
anonymized_images = []
for im_idx, image_annotation in enumerate(image_annotations):
# pre-process
imsize = self.inference_imsize
condition = torch.zeros(
(len(image_annotation), 3, imsize, imsize),
dtype=torch.float32)
mask = torch.zeros((len(image_annotation), 1, imsize, imsize))
landmarks = torch.empty(
(len(image_annotation), self.pose_size), dtype=torch.float32)
for face_idx in range(len(image_annotation)):
face, mask_ = image_annotation.get_face(face_idx, imsize)
condition[face_idx] = torch_utils.image_to_torch(
face, cuda=False, normalize_img=True
)
mask[face_idx, 0] = torch.from_numpy(mask_).float()
kp = image_annotation.aligned_keypoint(face_idx)
landmarks[face_idx] = kp[:, :self.pose_size]
img = condition
condition = condition * mask
z = infer.truncated_z(
condition, self.cfg.models.generator.z_shape,
self.truncation_level)
batches = dict(
condition=condition,
mask=mask,
landmarks=landmarks,
z=z,
img=img
)
# Inference
anonymized_faces = np.zeros((
len(image_annotation), imsize, imsize, 3), dtype=np.float32)
for idx, batch in enumerate(
batched_iterator(batches, self.batch_size)):
face = self._get_face(batch)
face = torch_utils.image_to_numpy(
face, to_uint8=False, denormalize=True)
start = idx * self.batch_size
anonymized_faces[start:start + self.batch_size] = face
anonymized_image = image_annotation.stitch_faces(anonymized_faces)
anonymized_images.append(anonymized_image)
if self.save_debug:
num_faces = len(batches["condition"])
for face_idx in range(num_faces):
orig_face = torch_utils.image_to_numpy(
batches["img"][face_idx], denormalize=True, to_uint8=True)
condition = torch_utils.image_to_numpy(
batches["condition"][face_idx],
denormalize=True, to_uint8=True)
fake_face = anonymized_faces[face_idx]
fake_face = (fake_face * 255).astype(np.uint8)
to_save = np.concatenate(
(orig_face, condition, fake_face), axis=1)
filepath = self.debug_directory.joinpath(
f"im{im_idx}_face{face_idx}.png")
cv2.imwrite(str(filepath), to_save[:, :, ::-1])
return anonymized_images
def use_mask(self):
return self.generator.use_mask
|
moonshot/commission/fx.py | windblood/moonshot | 122 | 11124020 | <gh_stars>100-1000
# Copyright 2017-2021 QuantRocket LLC - All Rights Reserved
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from moonshot.commission import PercentageCommission
class SpotFXCommission(PercentageCommission):
"""
Commission class for spot FX. This class can be used as-is.
NOTE: min commissions are not modeled for spot FX. This is because min
commissions for spot FX are in USD ($2), regardless of the quote
currency. The Moonshot class passes NLVs in the quote currency (the
Currency field). To accurately model min commissions, these NLVs would need
to be converted to USD.
Examples
--------
Use this on your strategy:
>>> class MyFXStrategy(Moonshot):
>>> COMMISSION_CLASS = SpotFXCommission
"""
BROKER_COMMISSION_RATE = 0.00002 # 0.2 bps
EXCHANGE_FEE_RATE = 0
MIN_COMMISSION = 0 # see NOTE in docstring
|
scripts/search.py | phasorhand/PyTorchText | 1,136 | 11124034 | <gh_stars>1000+
#coding:utf8
import sys
sys.path.append('../')
from utils import get_score
import json
import pickle
file1='/mnt/zhihu/data/RCNN_deep_word_val_4115'
file2='/mnt/zhihu/data/rccndeep_char_val_4037.pth'
file3='/mnt/zhihu/data/multicnntextbndeep40705_val_word.pth'
label_path = '/mnt/zhihu/data/labels.json'
# test_data_path='/mnt/zhihu/data/test.npz'
def ensamble(file1,file2,file3,label_path=label_path,test_data_path=test_data_path,result_csv=None):
import torch as t
import numpy as np
if result_csv is None:
import time
result_csv = time.strftime('%y%m%d_%H%M%S.csv')
a = t.load(file1)
b = t.load(file2)
c = t.load(file3)
index2qid = np.load(test_data_path)['index2qid'].item()
with open(label_path) as f:
labels_info = json.load(f)
qid2label = labels_info['d']
# with open(label_path) as f: label2qid = json.load(f)['id2label']
true_labels = [qid2label[index2qid[2999967-200000+ii]] for ii in range(len(a))]
# for ii,item in enumerate(result):
# rows[ii] = [index2qid[ii]] + [label2qid[str(_)] for _ in item ]
previous_best_score = 0.42
def target(args):
w1,w2 = args
r = a + b*w1 +c*w2
result = r.topk(5,1)[1]
predict_label_and_marked_label_list = [[_1,_2] for _1,_2 in zip(result,true_labels)]
score,_,_,_ = get_score(predict_label_and_marked_label_list)
print (args,score,_)
if score>previous_best_score:
previous_best_score = score
with open(str(score) ,'wb') as f:
pickle.dump(args,f)
return -score
list_space = [hp.uniform('w1',0,2),hp.uniform('w2',0,2)]
best = fmin(new_target,list_space,algo=tpe.suggest,max_evals=50)
print best
# import csv
# with open(result_csv,'w') as f:
# writer = csv.writer(f)
# writer.writerows(rows)
if __name__ == '__main__':
import fire
fire.Fire()
|
test/integration/test_setup.py | wnojopra/dsub | 146 | 11124049 | # Copyright 2016 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Setup module for dsub tests."""
# test_setup.py
#
# Intended to be imported into a test.
# The code here will:
#
# * Ensure the DSUB_PROVIDER is set (default: local)
# * Set the TEST_NAME based on the name of the calling script.
# * Set the TEST_DIR to the directory the test file is in.
# * For task file tests, set TASKS_FILE and TASKS_FILE_TMPL.
# * Set the TEST_TMP variable for a temporary directory.
from __future__ import print_function
import datetime
import os
import random
import string
import sys
# If the DSUB_PROVIDER is not set, figure it out from the name of the script.
# If the script name is <test>.<provider>.sh, pull out the provider.
# If the script name is <test>.sh, use "local".
# If the DSUB_PROVIDER is set, make sure it is correct for a provider test.
SCRIPT_NAME = os.path.basename(sys.argv[0])
SCRIPT_DEFAULT_PROVIDER = SCRIPT_NAME.split('.')[1] if SCRIPT_NAME.count(
'.') == 2 else None
DSUB_PROVIDER = os.getenv('DSUB_PROVIDER')
if not DSUB_PROVIDER:
if SCRIPT_DEFAULT_PROVIDER:
DSUB_PROVIDER = SCRIPT_DEFAULT_PROVIDER
else:
DSUB_PROVIDER = 'local'
elif SCRIPT_DEFAULT_PROVIDER:
if DSUB_PROVIDER != SCRIPT_DEFAULT_PROVIDER:
print('DSUB_PROVIDER inconsistent with default provider', file=sys.stderr)
print('"%s" is not "%s"' % (DSUB_PROVIDER, SCRIPT_DEFAULT_PROVIDER),
file=sys.stderr)
sys.exit(1)
# Compute the name of the test from the calling script
# (trim the e2e_ or unit_ prefix, along with the .py extension)
TEST_NAME = os.path.splitext(SCRIPT_NAME.split('_', 1)[1])[0]
print('Setting up test: %s' % TEST_NAME)
TEST_DIR = os.path.dirname(sys.argv[0])
TEST_TMP = '%s/tmp' % os.getenv('TEST_TMP', '/tmp/dsub-test/py/%s/%s' %
(DSUB_PROVIDER, TEST_NAME))
if TEST_NAME.endswith('_tasks'):
TASKS_FILE_TMPL = '%s/%s.tsv.tmpl' % (TEST_DIR, TEST_NAME)
TASKS_FILE = '%s/%s.tsv' % (TEST_TMP, TEST_NAME)
else:
TASKS_FILE_TMPL = None
TASKS_FILE = None
def _generate_test_token():
# Generate an id for tests to use that is reasonably likely to be unique
# (timestamp + 8 random characters).
timestamp = datetime.datetime.now().strftime('%Y%m%d_%H%M%S')
suffix = ''.join(
random.choice(string.ascii_lowercase + string.digits) for _ in range(8))
return '{}_{}'.format(timestamp, suffix)
TEST_TOKEN = os.getenv('TEST_TOKEN', _generate_test_token())
|
examples/kitchensink/KitchenSink.py | takipsizad/pyjs | 739 | 11124068 | import pyjd # this is dummy in pyjs
from pyjamas import logging
from pyjamas.ui.Button import Button
from pyjamas.ui.RootPanel import RootPanel
from pyjamas.ui.HTML import HTML
from pyjamas.ui.DockPanel import DockPanel
from pyjamas.ui import HasAlignment
from pyjamas.ui.Hyperlink import Hyperlink
from pyjamas.ui.VerticalPanel import VerticalPanel
from pyjamas.ui.Sink import SinkList
from pyjamas import History
from pyjamas import Window
import sink.Info as Info
import sink.Buttons as Buttons
import sink.Layouts as Layouts
import sink.Images as Images
import sink.Menus as Menus
import sink.Lists as Lists
import sink.Popups as Popups
import sink.Tables as Tables
import sink.Text as Text
import sink.Trees as Trees
import sink.Frames as Frames
import sink.Tabs as Tabs
from sink.Logger import Logger
log = logging.getAppendLogger(__name__, logging.DEBUG, logging.PLAIN_FORMAT)
class KitchenSink:
def onHistoryChanged(self, token):
log.debug("onHistoryChanged: %s", token)
info = self.sink_list.find(token)
if info is not None:
self.show(info, False)
else:
self.showInfo()
def onModuleLoad(self):
self.curInfo=''
self.curSink=None
self.description=HTML()
self.sink_list=SinkList()
self.panel=DockPanel()
self.loadSinks()
self.sinkContainer = DockPanel()
self.sinkContainer.setStyleName("ks-Sink")
vp=VerticalPanel()
vp.setWidth("100%")
vp.add(self.description)
vp.add(self.sinkContainer)
self.description.setStyleName("ks-Info")
self.panel.add(self.sink_list, DockPanel.WEST)
self.panel.add(vp, DockPanel.CENTER)
self.panel.setCellVerticalAlignment(self.sink_list, HasAlignment.ALIGN_TOP)
self.panel.setCellWidth(vp, "100%")
History.addHistoryListener(self)
RootPanel().add(self.panel)
RootPanel().add(Logger())
#Show the initial screen.
initToken = History.getToken()
if len(initToken):
self.onHistoryChanged(initToken)
else:
self.showInfo()
def show(self, info, affectHistory):
if info == self.curInfo: return
self.curInfo = info
#log.debug("showing " + info.getName())
if self.curSink is not None:
#log.debug("removing " + str(self.curSink))
self.curSink.onHide()
self.sinkContainer.remove(self.curSink)
self.curSink = info.getInstance()
self.sink_list.setSinkSelection(info.getName())
self.description.setHTML(info.getDescription())
if (affectHistory):
History.newItem(info.getName())
self.sinkContainer.add(self.curSink, DockPanel.CENTER)
self.sinkContainer.setCellWidth(self.curSink, "100%")
self.sinkContainer.setCellHeight(self.curSink, "100%")
self.sinkContainer.setCellVerticalAlignment(self.curSink, HasAlignment.ALIGN_TOP)
self.curSink.onShow()
def loadSinks(self):
self.sink_list.add(Info.init())
self.sink_list.add(Buttons.init())
self.sink_list.add(Menus.init())
self.sink_list.add(Images.init())
self.sink_list.add(Layouts.init())
self.sink_list.add(Lists.init())
self.sink_list.add(Popups.init())
self.sink_list.add(Tables.init())
self.sink_list.add(Text.init())
self.sink_list.add(Trees.init())
self.sink_list.add(Frames.init())
self.sink_list.add(Tabs.init())
def showInfo(self):
self.show(self.sink_list.find("Info"), False)
if __name__ == '__main__':
pyjd.setup("public/KitchenSink.html")
app = KitchenSink()
app.onModuleLoad()
pyjd.run()
|
tests/data/translated_titles/conf.py | asmeurer/nikola | 1,901 | 11124076 | # -*- coding: utf-8 -*-
import time
BLOG_AUTHOR = "<NAME>" # (translatable)
BLOG_TITLE = "Demo Site" # (translatable)
SITE_URL = "https://example.com/"
BLOG_EMAIL = "<EMAIL>"
BLOG_DESCRIPTION = "This is a demo site for Nikola." # (translatable)
DEFAULT_LANG = "en"
TRANSLATIONS = {
"en": "",
"pl": "./pl",
}
TRANSLATIONS_PATTERN = "{path}.{lang}.{ext}"
NAVIGATION_LINKS = {
DEFAULT_LANG: (
('/archive.html', 'Archives'),
('/categories/index.html', 'Tags'),
('/rss.xml', 'RSS'),
),
}
POSTS = (
("posts/*.rst", "posts", "post.tmpl"),
("posts/*.txt", "posts", "post.tmpl"),
)
PAGES = (
("pages/*.rst", "pages", "page.tmpl"),
("pages/*.txt", "pages", "page.tmpl"),
)
COMPILERS = {
"rest": ('.rst', '.txt'),
"markdown": ('.md', '.mdown', '.markdown'),
"textile": ('.textile',),
"txt2tags": ('.t2t',),
"bbcode": ('.bb',),
"wiki": ('.wiki',),
"ipynb": ('.ipynb',),
"html": ('.html', '.htm'),
# PHP files are rendered the usual way (i.e. with the full templates).
# The resulting files have .php extensions, making it possible to run
# them without reconfiguring your server to recognize them.
"php": ('.php',),
# Pandoc detects the input from the source filename
# but is disabled by default as it would conflict
# with many of the others.
# "pandoc": ('.rst', '.md', '.txt'),
}
REDIRECTIONS = []
THEME = "bootblog4"
LICENSE = ""
CONTENT_FOOTER = 'Contents © {date} <a href="mailto:{email}">{author}</a> - Powered by <a href="https://getnikola.com/" rel="nofollow">Nikola</a> {license}'
CONTENT_FOOTER_FORMATS = {
DEFAULT_LANG: (
(),
{
"email": BLOG_EMAIL,
"author": BLOG_AUTHOR,
"date": time.gmtime().tm_year,
"license": LICENSE
}
)
}
COMMENT_SYSTEM = "disqus"
COMMENT_SYSTEM_ID = "nikolademo"
GLOBAL_CONTEXT = {}
|
CurvesGenerator/draw.py | CodesHub/PathPlanning | 3,693 | 11124078 | import matplotlib.pyplot as plt
import numpy as np
PI = np.pi
class Arrow:
def __init__(self, x, y, theta, L, c):
angle = np.deg2rad(30)
d = 0.5 * L
w = 2
x_start = x
y_start = y
x_end = x + L * np.cos(theta)
y_end = y + L * np.sin(theta)
theta_hat_L = theta + PI - angle
theta_hat_R = theta + PI + angle
x_hat_start = x_end
x_hat_end_L = x_hat_start + d * np.cos(theta_hat_L)
x_hat_end_R = x_hat_start + d * np.cos(theta_hat_R)
y_hat_start = y_end
y_hat_end_L = y_hat_start + d * np.sin(theta_hat_L)
y_hat_end_R = y_hat_start + d * np.sin(theta_hat_R)
plt.plot([x_start, x_end], [y_start, y_end], color=c, linewidth=w)
plt.plot([x_hat_start, x_hat_end_L],
[y_hat_start, y_hat_end_L], color=c, linewidth=w)
plt.plot([x_hat_start, x_hat_end_R],
[y_hat_start, y_hat_end_R], color=c, linewidth=w)
class Car:
def __init__(self, x, y, yaw, w, L):
theta_B = PI + yaw
xB = x + L / 4 * np.cos(theta_B)
yB = y + L / 4 * np.sin(theta_B)
theta_BL = theta_B + PI / 2
theta_BR = theta_B - PI / 2
x_BL = xB + w / 2 * np.cos(theta_BL) # Bottom-Left vertex
y_BL = yB + w / 2 * np.sin(theta_BL)
x_BR = xB + w / 2 * np.cos(theta_BR) # Bottom-Right vertex
y_BR = yB + w / 2 * np.sin(theta_BR)
x_FL = x_BL + L * np.cos(yaw) # Front-Left vertex
y_FL = y_BL + L * np.sin(yaw)
x_FR = x_BR + L * np.cos(yaw) # Front-Right vertex
y_FR = y_BR + L * np.sin(yaw)
plt.plot([x_BL, x_BR, x_FR, x_FL, x_BL],
[y_BL, y_BR, y_FR, y_FL, y_BL],
linewidth=1, color='black')
Arrow(x, y, yaw, L / 2, 'black')
# plt.axis("equal")
# plt.show()
if __name__ == '__main__':
# Arrow(-1, 2, 60)
Car(0, 0, 1, 2, 60)
|
tests/test_manage.py | klen/muffin | 704 | 11124183 | <filename>tests/test_manage.py<gh_stars>100-1000
import pytest
from unittest import mock
@pytest.fixture(params=['curio', 'trio', 'asyncio'])
def cmd_aiolib(request):
return request.param
def test_command(app):
@app.manage
def cmd1(name, lower=False):
"""Custom description.
:param name: help for name
"""
pass
assert cmd1.parser
assert cmd1.parser.description == 'Custom description.'
assert cmd1.parser._actions[1].help == 'help for name'
ns = cmd1.parser.parse_args(['test'])
assert dict(ns._get_kwargs()) == {'name': 'test', 'lower': False}
@app.manage
def cmd2(*names, lower=False):
pass
ns = cmd2.parser.parse_args(['test'])
assert dict(ns._get_kwargs()) == {'*': ['test'], 'lower': False}
def test_manage(app, capsys, monkeypatch):
@app.manage
def hello(user_name, lower=False):
if lower:
user_name = user_name.lower()
print("hello " + user_name)
with pytest.raises(SystemExit):
app.manage.run(*'hello')
out, err = capsys.readouterr()
assert not out
assert err
app.manage.run(*'hello Mike'.split())
out, err = capsys.readouterr()
assert "hello Mike\n" == out
app.manage.run(*'hello Sam --lower'.split())
out, err = capsys.readouterr()
assert "hello sam\n" == out
def test_manage_async(app, cmd_aiolib):
import typing as t
from muffin.utils import current_async_library
start = mock.MagicMock()
app.on_startup(start)
finish = mock.MagicMock()
app.on_shutdown(finish)
run = mock.MagicMock()
@app.manage(lifespan=True)
async def command(name: t.Union[str, int]):
run(name)
assert current_async_library() == cmd_aiolib
app.manage.run(*f"--aiolib={cmd_aiolib} command test".split())
assert run.called
args, _ = run.call_args
assert args == ('test',)
assert start.called
assert finish.called
def test_shell_context(app):
assert app.cfg.MANAGE_SHELL
@app.manage.shell
def custom_context():
return {"custom": True}
assert app.cfg.MANAGE_SHELL is custom_context
|
test/unit/__init__.py | daltonconley/amazon-redshift-python-driver | 125 | 11124233 | <gh_stars>100-1000
from .mocks import MockCredentialsProvider
|
plugins/discovery/shodan/__init__.py | otherbeast/hackers-tool-kit | 655 | 11124254 | <filename>plugins/discovery/shodan/__init__.py<gh_stars>100-1000
from api import WebAPI
__version__ = "0.5.0"
__all__ = ['WebAPI']
|
tests/config/test_file_browser.py | kubajir/msticpy | 820 | 11124269 | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
"""Module docstring."""
import pytest_check as check
from msticpy.config.file_browser import FileBrowser
__author__ = "<NAME>"
# pylint: disable=protected-access, global-statement, invalid-name
file_name = ""
def test_file_browser():
"""Function_docstring."""
f_brow = FileBrowser(".", select_cb=_callback)
starting_folder = f_brow.current_folder
check.greater(len(f_brow.select_file.options), 0)
check.greater(len(f_brow.select_folder.options), 0)
check.is_in("..", f_brow.select_folder.options)
curr_files = f_brow.select_file.options
check.equal(curr_files, f_brow.select_file.options)
f_brow._open_folder(tgt_folder="msticpy")
check.not_equal(curr_files, f_brow.select_file.options)
f_brow.txt_path.value = str(starting_folder)
f_brow._enter_folder(event=None)
check.greater(len(f_brow.select_file.options), 0)
f_brow.select_file.selected_index = 1
f_brow._return_file(btn=None)
check.equal(file_name, f_brow.file)
f_brow.txt_search.value = "*.py"
f_brow._search(f_brow.btn_search)
check.greater(len(f_brow.select_search.options), 0)
def _callback(file):
global file_name
file_name = file
|
tests/trac/test-trac-0204.py | eLBati/pyxb | 123 | 11124278 | # -*- coding: utf-8 -*-
import logging
if __name__ == '__main__':
logging.basicConfig()
_log = logging.getLogger(__name__)
import pyxb.binding.generate
import pyxb.utils.domutils
from xml.dom import Node
import os.path
xsd='''<?xml version="1.0" encoding="UTF-8"?>
<xs:schema xmlns:xs="http://www.w3.org/2001/XMLSchema">
<xs:complexType name="YesNoChoice">
<xs:annotation>
<xs:documentation>Yes No Choice</xs:documentation>
</xs:annotation>
<xs:choice>
<xs:element name="Yes" type="xs:boolean" fixed="true"/>
<xs:element name="No" type="xs:boolean" fixed="true"/>
</xs:choice>
</xs:complexType>
<xs:element name="yesNoChoice" type="YesNoChoice"/>
</xs:schema>'''
code = pyxb.binding.generate.GeneratePython(schema_text=xsd)
#open('code.py', 'w').write(code)
rv = compile(code, 'test', 'exec')
eval(rv)
from pyxb.exceptions_ import *
import unittest
import sys
class TestTrac0204 (unittest.TestCase):
if sys.version_info[:2] < (2, 7):
def assertIsNone (self, v):
self.assertEqual(None, v)
def assertIsNotNone (self, v):
self.assertNotEqual(None, v)
def testCtor (self):
instance = yesNoChoice()
self.assertIsNone(instance.Yes)
self.assertIsNone(instance.No)
instance = yesNoChoice(Yes=True)
self.assertIsNotNone(instance.Yes)
self.assertIsNone(instance.No)
instance = yesNoChoice(Yes=True, No=True)
self.assertRaises(pyxb.UnprocessedElementContentError, instance.validateBinding)
if __name__ == '__main__':
unittest.main()
|
resotocore/core/dependencies.py | someengineering/cloudkeeper | 316 | 11124302 | import argparse
import logging
import multiprocessing as mp
import os.path
from argparse import Namespace
from typing import Optional, List, Callable
from urllib.parse import urlparse
from arango.database import StandardDatabase
from resotolib.args import ArgumentParser
from resotolib.jwt import add_args as jwt_add_args
from core import async_extensions
from core.analytics import AnalyticsEventSender
from core.db.db_access import DbAccess
from core.model.adjust_node import DirectAdjuster
from core.task.task_handler import TaskHandler
log = logging.getLogger(__name__)
def parse_args(args: Optional[List[str]] = None, namespace: Optional[str] = None) -> Namespace:
def is_file(message: str) -> Callable[[str], str]:
def check_file(path: str) -> str:
if os.path.isfile(path):
return path
else:
raise AttributeError(f"{message}: path {path} is not a directory!")
return check_file
def is_dir(message: str) -> Callable[[str], str]:
def check_dir(path: str) -> str:
if os.path.isdir(path):
return path
else:
raise AttributeError(f"{message}: path {path} is not a directory!")
return check_dir
def is_url(message: str) -> Callable[[str], str]:
def check_url(url: str) -> str:
try:
urlparse(url)
return url
except ValueError as ex:
raise AttributeError(f"{message}: url {url} can not be parsed!") from ex
return check_url
parser = ArgumentParser(
env_args_prefix="RESOTOCORE_",
description="Maintains graphs of resources of any shape.",
epilog="Keeps all the things.",
)
jwt_add_args(parser)
parser.add_argument(
"--log-level",
default="info",
help="Log level (default: info)",
)
parser.add_argument(
"--graphdb-server",
default="http://localhost:8529",
dest="graphdb_server",
help="Graph database server (default: http://localhost:8529)",
)
parser.add_argument(
"--graphdb-database",
default="resoto",
dest="graphdb_database",
help="Graph database name (default: resoto)",
)
parser.add_argument(
"--graphdb-username",
default="resoto",
dest="graphdb_username",
help="Graph database login (default: resoto)",
)
parser.add_argument(
"--graphdb-password",
default="",
dest="graphdb_password",
help='Graph database password (default: "")',
)
parser.add_argument(
"--graphdb-type",
default="arangodb",
dest="graphdb_type",
help="Graph database type (default: arangodb)",
)
parser.add_argument(
"--graphdb-no-ssl-verify",
action="store_true",
dest="graphdb_no_ssl_verify",
help="If the connection should not be verified (default: False)",
)
parser.add_argument(
"--graphdb-request-timeout",
type=int,
default=900,
dest="graphdb_request_timeout",
help="Request timeout in seconds (default: 900)",
)
parser.add_argument(
"--plantuml-server",
default="http://plantuml.resoto.org:8080",
help="PlantUML server URI for UML image rendering.",
)
parser.add_argument(
"--host",
type=str,
default="localhost",
nargs="+",
help="TCP host(s) to bind on (default: localhost)",
)
parser.add_argument(
"--port",
type=int,
default=8900,
help="TCP port to bind on (default: 8900)",
)
parser.add_argument(
"--merge_max_wait_time_seconds",
type=int,
default=3600,
help="Max waiting time to complete a merge graph action.",
)
parser.add_argument("--debug", default=False, action="store_true", help=argparse.SUPPRESS)
parser.add_argument(
"--analytics-opt-out",
default=False,
action="store_true",
help="Stop collecting analytics data.",
)
parser.add_argument(
"--ui-path",
type=is_dir("can not parse --ui-dir"),
help="The directory where the UI is installed. This directory will be served under /ui/.",
)
parser.add_argument(
"--tsdb-proxy-url",
type=is_url("can not parse --tsdb-proxy-url"),
help="The url to the time series database. This path will be served under /tsdb/.",
)
parser.add_argument(
"--tls-cert",
type=is_file("can not parse --tls-cert"),
help="Path to a single file in PEM format containing the certificate as well as any number "
"of CA certificates needed to establish the certificate’s authenticity.",
)
parser.add_argument(
"--tls-key",
type=is_file("can not parse --tls-key"),
help="Path to a file containing the private key. "
"If not defined the private key will be taken from certfile as well.",
)
parser.add_argument(
"--tls-password",
type=str,
help="Optional password to decrypt the private key file.",
)
parser.add_argument(
"--cli-default-graph",
type=str,
default="resoto",
dest="cli_default_graph",
help="Use this graph for CLI actions, if no graph is specified explicitly.",
)
parser.add_argument(
"--cli-default-section",
type=str,
default="reported",
dest="cli_default_section",
help="Use this graph section by default, if no section is specified."
"Relative paths will be interpreted with respect to this section.",
)
TaskHandler.add_args(parser)
return parser.parse_args(args, namespace) # type: ignore
# Note: this method should be called from every started process as early as possible
def setup_process(args: Namespace, child_process: Optional[str] = None) -> None:
# Note: if another appender than the log appender is used, proper multiprocess logging needs to be enabled.
# See https://docs.python.org/3/howto/logging-cookbook.html#logging-to-a-single-file-from-multiple-processes
log_format = "%(asctime)s|resotocore|%(levelname)5s|%(process)d|%(threadName)10s %(message)s"
logging.basicConfig(
format=log_format,
datefmt="%y-%m-%d %H:%M:%S",
level=logging.getLevelName(args.log_level.upper()),
force=True,
)
# adjust log levels for specific loggers
if not args.debug:
# mute analytics transmission errors unless debug is enabled
logging.getLogger("posthog").setLevel(logging.FATAL)
logging.getLogger("backoff").setLevel(logging.FATAL)
# transitions (fsm) creates a lot of log noise. Only show warnings.
logging.getLogger("transitions.core").setLevel(logging.WARNING)
# set/reset process creation method
reset_process_start_method()
# reset global async thread pool (forked processes need to create a fresh pool)
async_extensions.GlobalAsyncPool = None
def reset_process_start_method() -> None:
preferred = "spawn"
current = mp.get_start_method(True)
if current != preferred:
if preferred in mp.get_all_start_methods():
log.debug(f"Set process start method to {preferred}")
mp.set_start_method(preferred, True)
return
log.warning(f"{preferred} method not available. Have {mp.get_all_start_methods()}. Use {current}")
def db_access(db: StandardDatabase, event_sender: AnalyticsEventSender) -> DbAccess:
adjuster = DirectAdjuster()
return DbAccess(db, event_sender, adjuster)
|
lib/pylayer/mask_layer.py | giladsharir/MNC-1 | 544 | 11124315 | <reponame>giladsharir/MNC-1
# --------------------------------------------------------
# Multitask Network Cascade
# Written by <NAME>
# Copyright (c) 2016, <NAME>
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
import caffe
import cv2
import numpy as np
from transform.mask_transform import mask_overlap
from mnc_config import cfg
class MaskLayer(caffe.Layer):
"""
This layer Take input from sigmoid predicted masks
Assign each label for segmentation classifier according
to region overlap
"""
def setup(self, bottom, top):
self._phase = str(self.phase)
self._top_name_map = {}
top[0].reshape(1, 1, cfg.MASK_SIZE, cfg.MASK_SIZE)
self._top_name_map['mask_proposal'] = 0
if self._phase == 'TRAIN':
top[1].reshape(1, 1)
self._top_name_map['mask_proposal_label'] = 1
def reshape(self, bottom, top):
"""
Reshaping happens during the call to forward
"""
pass
def forward(self, bottom, top):
if str(self.phase) == 'TRAIN':
blobs = self.forward_train(bottom, top)
elif str(self.phase) == 'TEST':
blobs = self.forward_test(bottom, top)
else:
print 'Unrecognized phase'
raise NotImplementedError
for blob_name, blob in blobs.iteritems():
top[self._top_name_map[blob_name]].reshape(*blob.shape)
top[self._top_name_map[blob_name]].data[...] = blob.astype(np.float32, copy=False)
def backward(self, top, propagate_down, bottom):
if propagate_down[0]:
bottom[0].diff.fill(0.)
top_grad = top[0].diff.reshape(top[0].diff.shape[0], cfg.MASK_SIZE * cfg.MASK_SIZE)
bottom[0].diff[self.pos_sample, :] = top_grad[self.pos_sample, :]
def forward_train(self, bottom, top):
# Take sigmoid prediction as input
mask_pred = bottom[0].data
# get ground truth mask and labels
gt_masks = bottom[1].data
gt_masks_info = bottom[2].data
num_mask_pred = mask_pred.shape[0]
top_label = np.zeros((gt_masks_info.shape[0], 1))
# 2. Calculate region overlap
# Since the target gt mask may have different size
# We need to resize predicted masks into different sizes
mask_size = cfg.MASK_SIZE
for i in xrange(num_mask_pred):
# if the bounding box is itself background
if gt_masks_info[i][0] == -1:
top_label[i][0] = 0
continue
else:
info = gt_masks_info[i]
gt_mask = gt_masks[info[0]][0:info[1], 0:info[2]]
ex_mask = mask_pred[i].reshape((mask_size, mask_size))
ex_box = np.round(info[4:8]).astype(int)
gt_box = np.round(info[8:12]).astype(int)
# resize to large gt_masks, note cv2.resize is column first
ex_mask = cv2.resize(ex_mask.astype(np.float32), (ex_box[2] - ex_box[0] + 1,
ex_box[3] - ex_box[1] + 1))
ex_mask = ex_mask >= cfg.BINARIZE_THRESH
top_label[i][0] = 0 if mask_overlap(ex_box, gt_box, ex_mask, gt_mask) < cfg.TRAIN.FG_SEG_THRESH else info[3]
# output continuous mask for MNC
resized_mask_pred = mask_pred.reshape((num_mask_pred, 1, cfg.MASK_SIZE, cfg.MASK_SIZE))
self.pos_sample = np.where(top_label > 0)[0]
blobs = {
'mask_proposal': resized_mask_pred,
'mask_proposal_label': top_label
}
return blobs
def forward_test(self, bottom, top):
mask_pred = bottom[0].data
num_mask_pred = mask_pred.shape[0]
resized_mask_pred = mask_pred.reshape((num_mask_pred, 1, cfg.MASK_SIZE, cfg.MASK_SIZE))
blobs = {
'mask_proposal': resized_mask_pred
}
return blobs
|
benchmark/okon_grep_benchmark.py | droidmonkey/okon | 194 | 11124322 | import subprocess
import sys
import os
import timeit
from okon_benchmark_utils import *
NUMBER_OF_HASHES_TO_BENCHMARK = int(sys.argv[1])
PATH_TO_ORIGINAL_FILE = sys.argv[2]
NUMBER_OF_HASHES_IN_ORIGINAL_FILE = int(sys.argv[3])
BENCHMARK_SEED = int(sys.argv[4]) if len(sys.argv) > 4 else 0
def run_benchmark(hash_to_benchmark):
os.system('sudo sh -c "sync; echo 3 > /proc/sys/vm/drop_caches"')
command = ['grep', '-m', '1', '^{}'.format(hash_to_benchmark), PATH_TO_ORIGINAL_FILE]
start = timeit.default_timer()
subprocess.run(command, stdout=subprocess.PIPE)
end = timeit.default_timer()
return int((end - start) * 1000)
hashes = collect_hashes_to_benchmark(BENCHMARK_SEED, NUMBER_OF_HASHES_TO_BENCHMARK, PATH_TO_ORIGINAL_FILE, NUMBER_OF_HASHES_IN_ORIGINAL_FILE)
results = run_benchmarks(hashes, run_benchmark)
print('Grep benchmark done, result: {}ms'.format(sum(results) / len(results)))
|
devtools/src/klio_devtools/cli.py | gaybro8777/klio | 705 | 11124335 | # Copyright 2020 Spotify AB
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import os
import click
from klio_cli import cli as main_cli
from klio_cli import options
from klio_cli.cli import main
from klio_cli.utils import cli_utils
from klio_core import config
from klio_core import options as core_options
from klio_core import utils as core_utils
from klio_devtools.commands import develop
@main.command(
"develop",
short_help="Develop on the klio ecosystem in a job's container.",
help=(
"Builds & runs a job's container, mounts the job's code in "
"`/usr/src/app`, installs klio packages as 'editable' packages "
"that will automatically pick up local changes, and attaches to "
"the container with an interactive terminal to enable manual "
"runs of `klioexec`.\n\nNOTE: It's probably a good idea to locally "
"bump the versions of the libraries to ensure proper installation."
),
)
@core_options.job_dir
@core_options.config_file
@core_options.image_tag(default=None, show_default="``git-sha[dirty?]``")
@options.runtime
@click.option(
"--klio-path",
type=click.Path(
exists=True,
dir_okay=True,
file_okay=False,
readable=True,
writable=True,
resolve_path=True,
),
help="Path to klio repo",
required=True,
)
@click.option(
"--exclude", help="exclude installing a particular package", multiple=True,
)
def develop_job(job_dir, config_file, **kwargs):
job_dir, config_path = core_utils.get_config_job_dir(job_dir, config_file)
config_data = core_utils.get_config_by_path(config_path)
conf = config.KlioConfig(config_data)
git_sha = cli_utils.get_git_sha(job_dir, kwargs.get("image_tag"))
image_tag = kwargs.get("image_tag") or git_sha
if config_file:
basename = os.path.basename(config_file)
image_tag = "{}-{}".format(image_tag, basename)
runtime_config = main_cli.DockerRuntimeConfig(
image_tag=image_tag,
force_build=kwargs.get("force_build"),
config_file_override=config_file,
)
klio_pipeline = develop.DevelopKlioContainer(
job_dir, conf, runtime_config, kwargs["klio_path"], kwargs["exclude"]
)
klio_pipeline.run()
|
examples/xtensa/wasm_fac/make_flash.py | rakati/ppci-mirror | 161 | 11124337 | #!/usr/bin/python
from ppci.api import construct
construct('build.xml')
with open('hello.bin', 'rb') as f:
hello_bin = f.read()
flash_size = 4 * 1024 * 1024
with open('lx60.flash', 'wb') as f:
f.write(hello_bin)
padding = flash_size - len(hello_bin)
f.write(bytes(padding))
|
python codes/Queue.py | mflilian/Hacktoberfest2020-1 | 266 | 11124430 | class Queue:
def __init__(self):
self.items = []
def add_item(self, item):
return self.items.insert(0, item)
def remove_item(self):
if self.is_empty():
return print("Queue is Empty")
return self.items.pop()
def is_empty(self):
return self.items == []
def length(self):
return len(self.items)
def peek(self):
if self.is_empty():
return print("Queue is Empty")
return self.items[-1]
def main():
queue = Queue()
print("Type Your Name : ")
name = input()
print("Welcome " + name)
print("Choose your option")
while True:
print(" 1. Add Item \n 2. Remove Item \n 3. Length of Queue \n 4. Next Remove Item \n 5. Show Queue")
print("________________________\n________________________")
choice = input()
if choice == "1":
print("Enter Element (Any Data Type)")
x = input()
queue.add_item(x)
print("*********************\n*********************")
elif choice == "2":
queue.remove_item()
elif choice == "3":
print('Length of the Queue is in Below')
print(queue.length())
print("*********************\n*********************")
elif choice == "4":
print("Next Remove Item is in below")
print(queue.peek())
print("*********************\n*********************")
elif choice == "5":
print(queue.items)
print("*********************\n*********************")
main()
|
h2o-docs/src/booklets/v2_2015/source/Python_Vignette_code_examples/python_display_day_of_month.py | ahmedengu/h2o-3 | 6,098 | 11124476 | <filename>h2o-docs/src/booklets/v2_2015/source/Python_Vignette_code_examples/python_display_day_of_month.py
df14['D'].day()
# D
# ---
# 18
# 19
# 20 |
Applications/ctkSimplePythonShell/Python/ctkSimplePythonShell.py | ntoussaint/CTK | 515 | 11124489 | <filename>Applications/ctkSimplePythonShell/Python/ctkSimplePythonShell.py
import qt, ctk
def app():
return _ctkSimplePythonShellInstance
def quit():
exit()
def exit():
app().quit()
|
__scraping__/newegg.ca - urllib, BS/main.py | furas/python-code | 140 | 11124506 | <reponame>furas/python-code
# author: Bartlomiej "furas" Burek (https://blog.furas.pl)
# date: 2021.10.07
#
# title: 'NoneType' object is not subscriptable when webscraping image title
# url: https://stackoverflow.com/questions/69475748/nonetype-object-is-not-subscriptable-when-webscraping-image-title/69477667#69477667
# ['NoneType' object is not subscriptable when webscraping image title](https://stackoverflow.com/questions/69475748/nonetype-object-is-not-subscriptable-when-webscraping-image-title/69477667#69477667)
from bs4 import BeautifulSoup as soup
from urllib.request import urlopen as ureq
url2 = 'https://www.newegg.ca/Desktop-Graphics-Cards/SubCategory/ID-48?Tid=7708'
# opening up connection, grabbing page
uclient = ureq(url2)
html = uclient.read()
uclient.close()
# html parsing
page_soup = soup(html, "html.parser")
#grabs each product
containers = page_soup.findAll("div", {"class": "item-container"})
#print(containers[15].div.div.a.img["title"])
for number, container in enumerate(containers):
print("---", number, "---")
#if container.div.div.a.img:
# brand = container.div.div.a.img["title"]
#else:
# brand = '???'
brand = container.div.find("img", {"title": True})["title"]
product_name = container.find("a", {"class": "item-title"}).text
shipping = container.find("li", {"class": "price-ship"}).text.strip()
print(brand)
print(product_name)
print(shipping)
|
concordia/migrations/0004_auto_20181010_1715.py | juliecentofanti172/juliecentofanti.github.io | 134 | 11124523 | # Generated by Django 2.0.9 on 2018-10-10 17:15
import django.db.models.deletion
from django.conf import settings
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
("concordia", "0003_auto_20181004_2103"),
]
operations = [
migrations.RemoveField(model_name="asset", name="status"),
migrations.RemoveField(model_name="campaign", name="status"),
migrations.RemoveField(model_name="item", name="status"),
migrations.RemoveField(model_name="project", name="status"),
migrations.RemoveField(model_name="transcription", name="status"),
migrations.AddField(
model_name="asset",
name="published",
field=models.BooleanField(default=False),
),
migrations.AddField(
model_name="asset",
name="transcription_status",
field=models.CharField(
choices=[
("edit", "Open for Edit"),
("submitted", "Submitted for Review"),
("completed", "Completed"),
],
default="edit",
editable=False,
max_length=10,
),
),
migrations.AddField(
model_name="transcription",
name="accepted",
field=models.DateTimeField(blank=True, null=True),
),
migrations.AddField(
model_name="transcription",
name="rejected",
field=models.DateTimeField(blank=True, null=True),
),
migrations.AddField(
model_name="transcription",
name="reviewed_by",
field=models.ForeignKey(
blank=True,
null=True,
on_delete=django.db.models.deletion.SET_NULL,
related_name="transcription_reviewers",
to=settings.AUTH_USER_MODEL,
),
),
migrations.AddField(
model_name="transcription",
name="submitted",
field=models.DateTimeField(
blank=True,
help_text="Timestamp when the creator submitted this for review",
null=True,
),
),
migrations.AddField(
model_name="transcription",
name="supersedes",
field=models.ForeignKey(
blank=True,
help_text="A previous transcription record which is replaced by this one", # NOQA
null=True,
on_delete=django.db.models.deletion.CASCADE,
to="concordia.Transcription",
),
),
]
|
benchmarks/_bench/robust_plot_synthetic.py | rth/scikit-learn-extra | 120 | 11124529 | """
==================================================================
Plot of accuracy and time as sample_size and num_features increase
==================================================================
We show that the increase in computation time is linear when
increasing the number of features or the sample size increases.
"""
import matplotlib.pyplot as plt
import numpy as np
from time import time
from sklearn_extra.robust import RobustWeightedEstimator
from sklearn.linear_model import SGDClassifier
from sklearn.datasets import make_classification
from sklearn.model_selection import cross_val_score
rng = np.random.RandomState(42)
x_label = "Number of features"
dimensions = np.linspace(50, 5000, num=8).astype(int)
sample_sizes = np.linspace(50, 5000, num=8).astype(int)
accuracies = []
times = []
# Get the accuracy and time of computations for a dataset with varying number
# of features
for d in dimensions:
# Make an example in dimension d. Use a scale factor for the problem to be
# easy even in high dimension.
X, y = make_classification(
n_samples=200, n_features=d, scale=1 / np.sqrt(2 * d), random_state=rng
)
stime = time()
clf = RobustWeightedEstimator(
SGDClassifier(loss="hinge", penalty="l1"),
loss="hinge",
random_state=rng,
)
accuracies.append(np.mean(cross_val_score(clf, X, y, cv=10)))
times.append(time() - stime)
fig, axs = plt.subplots(2, 2)
axs[0, 0].plot(dimensions, accuracies)
axs[0, 0].set_xlabel(x_label)
axs[0, 0].set_ylabel("accuracy")
axs[0, 1].plot(dimensions, times)
axs[0, 1].set_xlabel(x_label)
axs[0, 1].set_ylabel("Time to fit and predict (s)")
accuracies = []
times = []
# Get the accuracy and time of computations for a dataset with varying number
# of samples
for n in sample_sizes:
X, y = make_classification(n_samples=n, n_features=5, random_state=rng)
stime = time()
clf = RobustWeightedEstimator(
SGDClassifier(loss="hinge", penalty="l1"),
loss="hinge",
random_state=rng,
)
accuracies.append(np.mean(cross_val_score(clf, X, y, cv=10)))
times.append(time() - stime)
axs[1, 0].plot(dimensions, accuracies)
axs[1, 0].set_xlabel(x_label)
axs[1, 0].set_ylabel("accuracy")
axs[1, 1].plot(dimensions, times)
axs[1, 1].set_xlabel(x_label)
axs[1, 1].set_ylabel("Time to fit and predict (s)")
plt.show()
|
manga_py/providers/mangahi_net.py | sonvt1710/manga-py | 337 | 11124561 | <reponame>sonvt1710/manga-py
from .zmanga_net import ZMangaNet
class MangaHiNet(ZMangaNet):
_type = 'chapter'
main = MangaHiNet
|
samples/invoice/third_party_invoicing.py | Hey-Marvelous/PayPal-Python-SDK | 653 | 11124573 | from paypalrestsdk import Invoice
import logging
from paypalrestsdk.openid_connect import Tokeninfo
logging.basicConfig(level=logging.INFO)
# Using Log In with PayPal, third party merchants can authorize your application to create and submit invoices on their behalf.
# See https://developer.paypal.com/docs/integration/direct/identity/log-in-with-paypal/ for more details about Log In with PayPal.
# Step 1. Generate a Log In with PayPal authorization URL. The third party merchant will need to visit this URL and authorize your request. You should use the `openid`, `https://uri.paypal.com/services/invoicing`, and `email` scopes at the minimum.
# paypalrestsdk.configure({'openid_client_id': 'CLIENT_ID', 'openid_client_secret': 'CLIENT_SECRET', 'openid_redirect_uri': 'http://example.com'})
# login_url = Tokeninfo.authorize_url({'scope': 'openid profile'})
# For example, the URL to redirect the third party merchant may be like:
# https://www.sandbox.paypal.com/webapps/auth/protocol/openidconnect/v1/authorize?client_id=AYSq3RDGsmBLJE-otTkBtM-jBRd1TCQwFf9RGfwddNXWz0uFU9ztymylOhRS&scope=openid%20https%3A%2F%2Furi.paypal.com%2Fservices%2Finvoicing%20email&response_type=code&redirect_uri=http%3A%2F%2Flocalhost%2Fpaypal%2FPayPal-PHP-SDK%2Fsample%2Flipp%2FUserConsentRedirect.php%3Fsuccess%3Dtrue
# Step 2. After the third party merchant authorizes your request, Log In with PayPal will redirect the browser to your configured openid_redirect_uri with an authorization code query parameter value.
# For example, after the merchant successfully authorizes your request, they will be redirected to the merchant's website configured via `openid_redirect_uri` like:
# http://localhost/paypal/PayPal-Python-SDK/sample/UserConsentRedirect.php?success=true&scope=https%3A%2F%2Furi.paypal.com%2Fservices%2Finvoicing+openid+email&code=<KEY>
# Step 3. Your web app should parse the query parameters for the authorization `code` value. You should use the `code` value to get a refresh token and securely save it for later use.
#begin
# authorization_code = "<KEY>"
# tokeninfo = Tokeninfo.create(code)
# print(tokeninfo)
# # Response 200
# tokeninfo = {
# token_type: 'Bearer',
# expires_in: '28800',
# refresh_token: '<KEY>',
# id_token: '<some value>',
# access_token: '<some value>'
# }
#end
# Step 4. You can use the refresh token to get the third party merchant's email address to use in the invoice, and then you can create an invoice on behalf of the third party merchant.
refresh_token = "<KEY>"
token_info = Tokeninfo.create_with_refresh_token(refresh_token)
print(token_info)
user_info = token_info.userinfo()
print(user_info)
invoice = Invoice({
"merchant_info": {
# The email address used here would be of a third party.
"email": user_info.email,
"first_name": "Dennis",
"last_name": "Doctor",
"business_name": "Medical Professionals, LLC",
"phone": {
"country_code": "001",
"national_number": "5032141716"
},
"address": {
"line1": "1234 Main St.",
"city": "Portland",
"state": "OR",
"postal_code": "97217",
"country_code": "US"
}
},
"billing_info": [{"email": "<EMAIL>"}],
"items": [
{
"name": "Sutures",
"quantity": 50,
"unit_price": {
"currency": "USD",
"value": 5
}
}
],
"note": "Medical Invoice 16 Jul, 2013 PST",
"payment_term": {
"term_type": "NET_45"
},
"shipping_info": {
"first_name": "Sally",
"last_name": "Patient",
"business_name": "Not applicable",
"phone": {
"country_code": "001",
"national_number": "5039871234"
},
"address": {
"line1": "1234 Broad St.",
"city": "Portland",
"state": "OR",
"postal_code": "97216",
"country_code": "US"
}
}
})
if invoice.create(refresh_token):
print("Third Party Invoice[%s] created successfully" % (invoice.id))
# Fetch the resource similarly as shown below:
result = Invoice.find(invoice.id, refresh_token=refresh_token)
print("Invoice Detail: %s" % result)
else:
print(invoice.error)
|
convlab2/laug/Speech_Recognition/TTS.py | ljw23/ConvLab-2 | 339 | 11124610 | #coding: UTF-8
from gtts import gTTS
from pydub.audio_segment import AudioSegment
import os
def text2wav(text,language='en',filename='temp',tld='cn'):
gTTS(text=text, tld=tld,lang=language).save(filename+".mp3")
AudioSegment.from_mp3(filename+".mp3").set_frame_rate(16000).export(filename+".wav", format="wav")
|
packages/pyright-internal/src/tests/samples/descriptor2.py | Microsoft/pyright | 3,934 | 11124611 | <filename>packages/pyright-internal/src/tests/samples/descriptor2.py
# This sample validates that a member's descriptor protocol is
# accessed via a member access expression only when accessing it
# through a class variable, not through an instance variable.
from typing import Any
class Descriptor:
def __get__(self, obj: Any, objtype: Any = None) -> float:
return 1.0
class ClassA:
x: Descriptor
def __init__(self, x: Descriptor):
reveal_type(self.x, expected_type="float")
def func1(self):
reveal_type(self.x, expected_type="float")
class ClassB:
def __init__(self, x: Descriptor):
self.x = x
reveal_type(self.x, expected_type="Descriptor")
def func1(self):
reveal_type(self.x, expected_type="Descriptor")
|
src/commands/refactor/extract_variable.py | PranjalPansuriya/JavaScriptEnhancements | 690 | 11124644 | import sublime, sublime_plugin
import os
from ...libs import util
from ...libs import FlowCLI
class JavascriptEnhancementsRefactorExtractVariableCommand(sublime_plugin.TextCommand):
def run(self, edit, **args):
view = self.view
selection = view.sel()[0]
contents = view.substr(selection).strip()
contents = contents[:-1] if contents[-1] == ";" else contents
variable_name = "new_var"
flow_cli = FlowCLI(view)
result = flow_cli.ast(contents=contents)
if result[0] and not result[1]["errors"] and result[1]["body"] and "type" in result[1]["body"][0] and result[1]["body"][0]["type"] == "ExpressionStatement":
result = flow_cli.ast()
if result[0]:
if "body" in result[1]:
body = result[1]["body"]
items = util.nested_lookup("type", ["BlockStatement"], body)
last_block_statement = None
last_item = None
region = None
for item in items:
region = sublime.Region(int(item["range"][0]), int(item["range"][1]))
if region.contains(selection):
last_block_statement = region
last_item = item
if last_block_statement:
for item in last_item["body"]:
r = sublime.Region(int(item["range"][0]), int(item["range"][1]))
if r.contains(selection):
region = r
break
else:
for item in body:
r = sublime.Region(int(item["range"][0]), int(item["range"][1]))
if r.contains(selection):
region = r
break
if region:
prev_line_is_empty = util.prev_line_is_empty(view, region)
space = util.get_whitespace_from_line_begin(view, region)
str_assignement = ("\n" + space if not prev_line_is_empty else "") + "let " + variable_name + " = " + contents + "\n" + space
view.erase(edit, selection)
view.insert(edit, selection.begin(), variable_name)
view.insert(edit, region.begin(), str_assignement)
view.sel().clear()
view.sel().add_all([
sublime.Region(
selection.begin()+len(str_assignement),
selection.begin()+len(str_assignement)+len(variable_name)
),
sublime.Region(
region.begin() + len(("\n" + space if not prev_line_is_empty else "") + "let "), region.begin() + len(("\n" + space if not prev_line_is_empty else "") + "let ") + len(variable_name)
)
])
variable_kind = ["let", "const", "var"]
whitespace_length = len("\n" + space if not prev_line_is_empty else "")
view.window().show_quick_panel(variable_kind, None, 0, 0, lambda index: self.view.run_command("javascript_enhancements_replace_text_view", args={"start": region.begin() + whitespace_length, "end": region.begin() + whitespace_length + len(view.substr(view.word(region.begin() + whitespace_length))) , "text": variable_kind[index]}))
else:
sublime.error_message("Cannot introduce variable. Some problems occured.")
else:
sublime.error_message("Cannot introduce variable. Selection does not form an ExpressionStatement.")
def is_enabled(self, **args) :
view = self.view
if not util.selection_in_js_scope(view) :
return False
selection = view.sel()[0]
return selection.begin() != selection.end()
def is_visible(self, **args) :
view = self.view
if not util.selection_in_js_scope(view) :
return False
selection = view.sel()[0]
return selection.begin() != selection.end()
|
assembler.py | zshift/chungus-2-assembler | 183 | 11124652 | <reponame>zshift/chungus-2-assembler
from os import path
from typing import List, Tuple
import formats
from schem import generate_schematic
###############################################################################
# assembler
###############################################################################
class AssemblyError(Exception):
pass
def get_operands(line: str) -> Tuple[str, List[str]]:
"""Get the opcode and operands of an assembly line"""
opcode = line.split(" ")[0]
operands = line[len(opcode) + 1:].replace(",", "")
operands = operands.split() if operands else []
return (opcode, operands)
def to_decimal(number: str) -> int:
"""Convert other bases to decimal"""
if number[0:2] == "0b": # binary
return int(number[2:], 2)
if number[0:2] == "0x": # hex
return int(number[2:], 16)
if number[0:2] == "0o": # octal
return int(number[2:], 8)
if number[0:2] == "0d": # decimal
return int(number[2:], 10)
# default - decimal
return int(number)
def get_binary(number: int, length: int) -> str:
"""Convert a decimal number to signed binary number of given length"""
if number < 0: # use 2's complement
number = 2 ** length + number
result = str(bin(number))[2:]
# result over the maximum allowed size
if len(result) > length:
raise AssemblyError(f"Number too long for {length} bits: {number}")
return result.zfill(length)
def parse_immediate(immediate: str, length: int) -> str:
"""Get the binary representation of an immediate value"""
# ASCII character
if immediate[0] == '"':
return get_binary(ord(immediate[1].replace("@", " ")), length)
# remove prefix e.g. "M10" (for memory address 10) -> "10"
if not immediate[0] in "-0123456789":
immediate = immediate[1:]
# make sure immediate is an integer
try:
immediateindex = to_decimal(immediate)
except ValueError:
raise AssemblyError(f"Invalid immediate: {immediate}")
else:
# the immediate may be too long (for example in branch instructions)
# so take it mod 2 ^ length
return get_binary(immediateindex % (2 ** length), length)
def parse_register(register: str) -> str:
"""Get the binary representation of a register"""
# make sure it is actually a register
if not (len(register) == 2 and register[0] in ("$", "R")):
raise AssemblyError(f"Invalid register: {register}")
# make sure register is valid
try:
registerindex = to_decimal(register[1:])
except ValueError:
raise AssemblyError(f"Invalid register: {register}")
if registerindex > 7:
raise AssemblyError(f"Invalid register: {register}")
return get_binary(registerindex, 3)
def parse_line(line: str) -> str:
"""Translate an assembly instruction to machine code"""
opcode, operands = get_operands(line)
# get base instruction
base = formats.ALIAS.get(opcode, opcode)
if base not in formats.FORMATS:
raise AssemblyError(f"Invalid opcode: {opcode}")
result = ""
for operand in formats.FORMATS[base]:
if operand == "REG": # register - assume R0 if not given
result += parse_register(operands.pop(0)) if operands else "000"
elif operand[0:3] == "IMM": # fixed length immediate - default 0
length = int(operand.split("_")[1])
if not operands:
result += "0" * length
else:
result += parse_immediate(operands.pop(0), length)
elif operand == "BITS": # operand depends on the opcode
result += formats.BITS[opcode]
elif operand == "OPERAND": # control bits (required)
if not operands:
raise AssemblyError("Not enough operands")
if not operands[0] in formats.OPERANDS:
raise AssemblyError(f"Unknown operand: {operands[0]}")
result += formats.OPERANDS[operands.pop(0)]
else: # fixed operand for the instruction
result += operand
return result
###############################################################################
# cleanup code
###############################################################################
def remove_comments(lines: List[str]) -> List[str]:
"""Remove comments and empty lines"""
formatlines = []
for line in lines:
# comment
if "//" in line:
formatlines.append(line[:line.index("//")].strip())
# ignore blank lines
elif line:
formatlines.append(line)
return formatlines
def parse_pages(lines: List[str]) -> List[str]:
"""Add NOPs between pages to keep size 64"""
# (prevent 64 NOPs at the start of program)
if lines[0] == ".PAGE:0":
lines.pop(0)
instructioncount = 0
formatlines = []
for line in lines:
# if a new page is found and the last one is not full, fill with NOPs
# which assemble to 00000000
if line[0:6] == ".PAGE:":
formatlines.extend(["NOP" for i in range(64 - instructioncount)])
instructioncount = 0
# otherwise add to formatlines
else:
formatlines.append(line)
# ignore labels in instruction count
if line[0] != ".":
instructioncount += 1
return formatlines
def parse_labels(lines: List[str]) -> List[str]:
"""Turn labels into immediate values"""
def is_label(line): # check if a given line is a label
line = line.strip()
return line and line[0] == "."
labels = {}
linenum = 0
# find all labels and their line numbers
while linenum < len(lines):
if is_label(lines[linenum]):
# add to label dict and remove from lines
labels[lines[linenum].strip()] = str(linenum)
lines.pop(linenum)
else:
linenum += 1
# convert labels to immediates
formatlines = []
for line in lines:
if not line: # blank line (should be cleaned up?)
continue
# get operands - NOTE: you cannot just replace labels, because there
# could be a ".test" label but also a ".test2" label, and the first
# would overwrite the second.
opcode, operands = get_operands(line.strip())
operands = [labels.get(operand, operand) for operand in operands]
# turn back into a formatted assembly instruction
formatlines.append(opcode + " " + ", ".join(operands))
return formatlines
def cleanup(lines: List[str]) -> List[str]:
"""Clean up assembly code and parse labels"""
lines = remove_comments(lines)
lines = parse_pages(lines)
lines = parse_labels(lines)
return lines
###############################################################################
# file management
###############################################################################
def read_file(filepath: str) -> List[str]:
"""Read an assembly file and remove comments"""
with open(filepath, "r") as f:
lines = [line.strip() for line in f]
lines = remove_comments(lines)
return lines
def write_file(filepath: str, lines: List[str]) -> None:
"""Write a machine code file"""
with open(filepath, "w") as f:
for line in lines:
f.write(line + "\n")
###############################################################################
# io
###############################################################################
def assemble(lines: List[str]) -> List[str]:
"""Translate a list of assembly instructions to machine code"""
result = []
lines = cleanup(lines)
for linenumber, line in enumerate(lines):
try:
machinecode = parse_line(line)
except AssemblyError as error:
# format error message
errorcode = f"Error on line {linenumber}: {error}"
raise AssemblyError(errorcode) from None
else:
result.append(machinecode)
return format_assembly(result)
def assemble_file(filepath: str) -> None:
"""Assemble an assembly file to a machine code file"""
lines = read_file(filepath)
lines = assemble(lines)
# get resulting file name
filename = path.splitext(filepath)[0] + ".txt"
write_file(filename, lines)
# also create a schematic to run on the Minecraft hardware
generate_schematic(
[line[0:8] + line[9:17] for line in lines],
path.splitext(filepath)[0] + "_CHUNGUS2"
)
def format_assembly(lines: List[str]) -> List[str]:
"""Split assembly instructions into 2 bytes"""
return [line[0:8] + " " + line[8:16] for line in lines]
if __name__ == "__main__":
filepath = input("Enter file path: ")
assemble_file(filepath)
|
dagda/remote/agent.py | hoominkani/dagda | 947 | 11124673 | #
# Licensed to Dagda under one or more contributor
# license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright
# ownership. Dagda licenses this file to you under
# the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
#
import json
import requests
from analysis.analyzer import Analyzer
# Dagda remote agent class
class Agent:
# -- Public methods
# Agent Constructor
def __init__(self, dagda_server_url):
super(Agent, self).__init__()
self.dagda_server_url = dagda_server_url
self.analyzer = Analyzer(dagda_server_url=dagda_server_url)
def run_static_analysis(self, image_name=None, container_id=None):
evaluated_docker_image = self.analyzer.evaluate_image(image_name=image_name, container_id=container_id)
docker_image_name = evaluated_docker_image['image_name']
r = requests.post(self.dagda_server_url + '/history/' + docker_image_name,
data=json.dumps(evaluated_docker_image),
headers={'content-type': 'application/json'})
# -- Print cmd output
if r is not None and r.content:
print(json.dumps(json.loads(r.content.decode('utf-8')), sort_keys=True, indent=4))
|
text-generation/tests/test_text_generator.py | dumpmemory/serverless-transformers-on-aws-lambda | 103 | 11124694 | from src.text_generator import TextGenerator
pipeline = TextGenerator()
def test_response(requests, response):
assert response == pipeline(requests)
|
econml/dynamic/dml/__init__.py | imatiach-msft/EconML | 1,846 | 11124720 | <gh_stars>1000+
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
"""Double Machine Learning for Dynamic Treatment Effects.
A Double/Orthogonal machine learning approach to estimation of heterogeneous
treatment effect in the dynamic treatment regime. For the theoretical
foundations of these methods see: [dynamicdml]_.
References
----------
.. [dynamicdml] <NAME> and <NAME>.
Double/Debiased Machine Learning for Dynamic Treatment Effects.
`<https://arxiv.org/abs/2002.07285>`_, 2021.
"""
from ._dml import DynamicDML
__all__ = ["DynamicDML"]
|
pytorch-DRIT-PONO-MS/src/model_pono.py | Boyiliee/PONO | 133 | 11124730 | import networks_pono as networks
import torch
import torch.nn as nn
import torch.nn.functional as F
class DRIT(nn.Module):
def __init__(self, opts):
super(DRIT, self).__init__()
# parameters
lr = 0.0001
lr_dcontent = lr / 2.5
self.nz = 8
self.concat = opts.concat
self.arch = opts.arch
self.vgg_w = opts.vgg_w
if self.vgg_w > 0.:
self.vgg = networks.VGG19(init_weights='/home/fw245/share/public/vgg19.pth', feature_mode=True)
self.vgg.eval()
for param in self.vgg.parameters():
param.requires_grad = False
else:
self.vgg = None
# discriminators
if opts.dis_scale > 1:
self.disA = networks.MultiScaleDis(opts.input_dim_a, opts.dis_scale, norm=opts.dis_norm, sn=opts.dis_spectral_norm)
self.disB = networks.MultiScaleDis(opts.input_dim_b, opts.dis_scale, norm=opts.dis_norm, sn=opts.dis_spectral_norm)
self.disA2 = networks.MultiScaleDis(opts.input_dim_a, opts.dis_scale, norm=opts.dis_norm, sn=opts.dis_spectral_norm)
self.disB2 = networks.MultiScaleDis(opts.input_dim_b, opts.dis_scale, norm=opts.dis_norm, sn=opts.dis_spectral_norm)
else:
self.disA = networks.Dis(opts.input_dim_a, norm=opts.dis_norm, sn=opts.dis_spectral_norm)
self.disB = networks.Dis(opts.input_dim_b, norm=opts.dis_norm, sn=opts.dis_spectral_norm)
self.disA2 = networks.Dis(opts.input_dim_a, norm=opts.dis_norm, sn=opts.dis_spectral_norm)
self.disB2 = networks.Dis(opts.input_dim_b, norm=opts.dis_norm, sn=opts.dis_spectral_norm)
if self.arch in {'drit_pono_ms'}:
self.with_stats = True
self.disContent = networks.Dis_content_pono_ms(n_stats=3)
else:
self.with_stats = False
self.disContent = networks.Dis_content()
# encoders
if self.arch in {'drit_pono_ms'}:
self.enc_c = networks.E_content_pono_ms(opts.input_dim_a, opts.input_dim_b)
else:
self.enc_c = networks.E_content(opts.input_dim_a, opts.input_dim_b)
# enc_a
if self.concat:
self.enc_a = networks.E_attr_concat(opts.input_dim_a, opts.input_dim_b, self.nz, \
norm_layer=None, nl_layer=networks.get_non_linearity(layer_type='lrelu'))
else:
self.enc_a = networks.E_attr(opts.input_dim_a, opts.input_dim_b, self.nz)
# generator
if self.concat:
if self.arch in {'drit'}:
self.gen = networks.G_concat(opts.input_dim_a, opts.input_dim_b, nz=self.nz)
elif self.arch in {'drit_pono_ms'}:
self.gen = networks.G_concat_pono_ms(opts.input_dim_a, opts.input_dim_b, nz=self.nz)
else:
raise ValueError(self.arch)
else:
if self.arch in {'drit'}:
self.gen = networks.G(opts.input_dim_a, opts.input_dim_b, nz=self.nz)
elif self.arch in {'drit_pono_ms'}:
self.gen = networks.G_pono_ms(opts.input_dim_a, opts.input_dim_b, nz=self.nz)
else:
raise ValueError(self.arch)
# optimizers
self.disA_opt = torch.optim.Adam(self.disA.parameters(), lr=lr, betas=(0.5, 0.999), weight_decay=0.0001)
self.disB_opt = torch.optim.Adam(self.disB.parameters(), lr=lr, betas=(0.5, 0.999), weight_decay=0.0001)
self.disA2_opt = torch.optim.Adam(self.disA2.parameters(), lr=lr, betas=(0.5, 0.999), weight_decay=0.0001)
self.disB2_opt = torch.optim.Adam(self.disB2.parameters(), lr=lr, betas=(0.5, 0.999), weight_decay=0.0001)
self.disContent_opt = torch.optim.Adam(self.disContent.parameters(), lr=lr_dcontent, betas=(0.5, 0.999), weight_decay=0.0001)
self.enc_c_opt = torch.optim.Adam(self.enc_c.parameters(), lr=lr, betas=(0.5, 0.999), weight_decay=0.0001)
self.enc_a_opt = torch.optim.Adam(self.enc_a.parameters(), lr=lr, betas=(0.5, 0.999), weight_decay=0.0001)
self.gen_opt = torch.optim.Adam(self.gen.parameters(), lr=lr, betas=(0.5, 0.999), weight_decay=0.0001)
# Setup the loss function for training
self.criterionL1 = torch.nn.L1Loss()
def initialize(self):
self.disA.apply(networks.gaussian_weights_init)
self.disB.apply(networks.gaussian_weights_init)
self.disA2.apply(networks.gaussian_weights_init)
self.disB2.apply(networks.gaussian_weights_init)
self.disContent.apply(networks.gaussian_weights_init)
self.gen.apply(networks.gaussian_weights_init)
self.enc_c.apply(networks.gaussian_weights_init)
self.enc_a.apply(networks.gaussian_weights_init)
def set_scheduler(self, opts, last_ep=0):
self.disA_sch = networks.get_scheduler(self.disA_opt, opts, last_ep)
self.disB_sch = networks.get_scheduler(self.disB_opt, opts, last_ep)
self.disA2_sch = networks.get_scheduler(self.disA2_opt, opts, last_ep)
self.disB2_sch = networks.get_scheduler(self.disB2_opt, opts, last_ep)
self.disContent_sch = networks.get_scheduler(self.disContent_opt, opts, last_ep)
self.enc_c_sch = networks.get_scheduler(self.enc_c_opt, opts, last_ep)
self.enc_a_sch = networks.get_scheduler(self.enc_a_opt, opts, last_ep)
self.gen_sch = networks.get_scheduler(self.gen_opt, opts, last_ep)
def setgpu(self, gpu):
self.gpu = gpu
self.disA.cuda(self.gpu)
self.disB.cuda(self.gpu)
self.disA2.cuda(self.gpu)
self.disB2.cuda(self.gpu)
self.disContent.cuda(self.gpu)
self.enc_c.cuda(self.gpu)
self.enc_a.cuda(self.gpu)
self.gen.cuda(self.gpu)
if self.vgg is not None:
self.vgg.cuda(self.gpu)
def get_z_random(self, batchSize, nz, random_type='gauss'):
z = torch.randn(batchSize, nz).cuda(self.gpu)
return z
def test_forward(self, image, a2b=True):
self.z_random = self.get_z_random(image.size(0), self.nz, 'gauss')
if a2b:
self.z_content = self.enc_c.forward_a(image)
output = self.gen.forward_b(self.z_content, self.z_random)
else:
self.z_content = self.enc_c.forward_b(image)
output = self.gen.forward_a(self.z_content, self.z_random)
return output
def test_forward_transfer(self, image_a, image_b, a2b=True):
self.z_content_a, self.z_content_b = self.enc_c.forward(image_a, image_b)
if self.concat:
self.mu_a, self.logvar_a, self.mu_b, self.logvar_b = self.enc_a.forward(image_a, image_b)
std_a = self.logvar_a.mul(0.5).exp_()
eps = self.get_z_random(std_a.size(0), std_a.size(1), 'gauss')
self.z_attr_a = eps.mul(std_a).add_(self.mu_a)
std_b = self.logvar_b.mul(0.5).exp_()
eps = self.get_z_random(std_b.size(0), std_b.size(1), 'gauss')
self.z_attr_b = eps.mul(std_b).add_(self.mu_b)
else:
self.z_attr_a, self.z_attr_b = self.enc_a.forward(image_a, image_b)
if a2b:
output = self.gen.forward_b(self.z_content_a, self.z_attr_b)
else:
output = self.gen.forward_a(self.z_content_b, self.z_attr_a)
return output
def forward(self):
# input images
half_size = 1
real_A = self.input_A
real_B = self.input_B
self.real_A_encoded = real_A[0:half_size]
self.real_A_random = real_A[half_size:]
self.real_B_encoded = real_B[0:half_size]
self.real_B_random = real_B[half_size:]
# get encoded z_c
self.z_content_a, self.z_content_b = self.enc_c.forward(self.real_A_encoded, self.real_B_encoded)
# get encoded z_a
if self.concat:
self.mu_a, self.logvar_a, self.mu_b, self.logvar_b = self.enc_a.forward(self.real_A_encoded, self.real_B_encoded)
std_a = self.logvar_a.mul(0.5).exp_()
eps_a = self.get_z_random(std_a.size(0), std_a.size(1), 'gauss')
self.z_attr_a = eps_a.mul(std_a).add_(self.mu_a)
std_b = self.logvar_b.mul(0.5).exp_()
eps_b = self.get_z_random(std_b.size(0), std_b.size(1), 'gauss')
self.z_attr_b = eps_b.mul(std_b).add_(self.mu_b)
else:
self.z_attr_a, self.z_attr_b = self.enc_a.forward(self.real_A_encoded, self.real_B_encoded)
# get random z_a
self.z_random = self.get_z_random(self.real_A_encoded.size(0), self.nz, 'gauss')
# first cross translation
if self.with_stats:
input_content_forA = (
torch.cat((self.z_content_b[0], self.z_content_a[0], self.z_content_b[0]), 0),
[
(torch.cat((self.z_content_b[1][i][0], self.z_content_a[1][i][0], self.z_content_b[1][i][0]), 0),
torch.cat((self.z_content_b[1][i][1], self.z_content_a[1][i][1], self.z_content_b[1][i][1]), 0))
for i in range(len(self.z_content_b[1]))
],
)
input_content_forB = (
torch.cat((self.z_content_a[0], self.z_content_b[0], self.z_content_a[0]), 0),
[
(torch.cat((self.z_content_a[1][i][0], self.z_content_b[1][i][0], self.z_content_a[1][i][0]), 0),
torch.cat((self.z_content_a[1][i][1], self.z_content_b[1][i][1], self.z_content_a[1][i][1]), 0))
for i in range(len(self.z_content_b[1]))
],
)
else:
input_content_forA = torch.cat((self.z_content_b, self.z_content_a, self.z_content_b),0)
input_content_forB = torch.cat((self.z_content_a, self.z_content_b, self.z_content_a),0)
input_attr_forA = torch.cat((self.z_attr_a, self.z_attr_a, self.z_random),0)
input_attr_forB = torch.cat((self.z_attr_b, self.z_attr_b, self.z_random),0)
output_fakeA = self.gen.forward_a(input_content_forA, input_attr_forA)
output_fakeB = self.gen.forward_b(input_content_forB, input_attr_forB)
if self.with_stats:
self.fake_A_encoded, self.fake_AA_encoded, self.fake_A_random = torch.split(output_fakeA, self.z_content_a[0].size(0), dim=0)
self.fake_B_encoded, self.fake_BB_encoded, self.fake_B_random = torch.split(output_fakeB, self.z_content_a[0].size(0), dim=0)
else:
self.fake_A_encoded, self.fake_AA_encoded, self.fake_A_random = torch.split(output_fakeA, self.z_content_a.size(0), dim=0)
self.fake_B_encoded, self.fake_BB_encoded, self.fake_B_random = torch.split(output_fakeB, self.z_content_a.size(0), dim=0)
# get reconstructed encoded z_c
self.z_content_recon_b, self.z_content_recon_a = self.enc_c.forward(self.fake_A_encoded, self.fake_B_encoded)
# get reconstructed encoded z_a
if self.concat:
self.mu_recon_a, self.logvar_recon_a, self.mu_recon_b, self.logvar_recon_b = self.enc_a.forward(self.fake_A_encoded, self.fake_B_encoded)
std_a = self.logvar_recon_a.mul(0.5).exp_()
eps_a = self.get_z_random(std_a.size(0), std_a.size(1), 'gauss')
self.z_attr_recon_a = eps_a.mul(std_a).add_(self.mu_recon_a)
std_b = self.logvar_recon_b.mul(0.5).exp_()
eps_b = self.get_z_random(std_b.size(0), std_b.size(1), 'gauss')
self.z_attr_recon_b = eps_b.mul(std_b).add_(self.mu_recon_b)
else:
self.z_attr_recon_a, self.z_attr_recon_b = self.enc_a.forward(self.fake_A_encoded, self.fake_B_encoded)
# second cross translation
self.fake_A_recon = self.gen.forward_a(self.z_content_recon_a, self.z_attr_recon_a)
self.fake_B_recon = self.gen.forward_b(self.z_content_recon_b, self.z_attr_recon_b)
# for display
self.image_display = torch.cat((self.real_A_encoded[0:1].detach().cpu(), self.fake_B_encoded[0:1].detach().cpu(), \
self.fake_B_random[0:1].detach().cpu(), self.fake_AA_encoded[0:1].detach().cpu(), self.fake_A_recon[0:1].detach().cpu(), \
self.real_B_encoded[0:1].detach().cpu(), self.fake_A_encoded[0:1].detach().cpu(), \
self.fake_A_random[0:1].detach().cpu(), self.fake_BB_encoded[0:1].detach().cpu(), self.fake_B_recon[0:1].detach().cpu()), dim=0)
# for latent regression
if self.concat:
self.mu2_a, _, self.mu2_b, _ = self.enc_a.forward(self.fake_A_random, self.fake_B_random)
else:
self.z_attr_random_a, self.z_attr_random_b = self.enc_a.forward(self.fake_A_random, self.fake_B_random)
def forward_content(self):
half_size = 1
self.real_A_encoded = self.input_A[0:half_size]
self.real_B_encoded = self.input_B[0:half_size]
# get encoded z_c
self.z_content_a, self.z_content_b = self.enc_c.forward(self.real_A_encoded, self.real_B_encoded)
def update_D_content(self, image_a, image_b):
self.input_A = image_a
self.input_B = image_b
self.forward_content()
self.disContent_opt.zero_grad()
loss_D_Content = self.backward_contentD(self.z_content_a, self.z_content_b)
self.disContent_loss = loss_D_Content.item()
nn.utils.clip_grad_norm_(self.disContent.parameters(), 5)
self.disContent_opt.step()
def update_D(self, image_a, image_b):
self.input_A = image_a
self.input_B = image_b
self.forward()
# update disA
self.disA_opt.zero_grad()
loss_D1_A = self.backward_D(self.disA, self.real_A_encoded, self.fake_A_encoded)
self.disA_loss = loss_D1_A.item()
self.disA_opt.step()
# update disA2
self.disA2_opt.zero_grad()
loss_D2_A = self.backward_D(self.disA2, self.real_A_random, self.fake_A_random)
self.disA2_loss = loss_D2_A.item()
self.disA2_opt.step()
# update disB
self.disB_opt.zero_grad()
loss_D1_B = self.backward_D(self.disB, self.real_B_encoded, self.fake_B_encoded)
self.disB_loss = loss_D1_B.item()
self.disB_opt.step()
# update disB2
self.disB2_opt.zero_grad()
loss_D2_B = self.backward_D(self.disB2, self.real_B_random, self.fake_B_random)
self.disB2_loss = loss_D2_B.item()
self.disB2_opt.step()
# update disContent
self.disContent_opt.zero_grad()
loss_D_Content = self.backward_contentD(self.z_content_a, self.z_content_b)
self.disContent_loss = loss_D_Content.item()
nn.utils.clip_grad_norm_(self.disContent.parameters(), 5)
self.disContent_opt.step()
def backward_D(self, netD, real, fake):
pred_fake = netD.forward(fake.detach())
pred_real = netD.forward(real)
loss_D = 0
for it, (out_a, out_b) in enumerate(zip(pred_fake, pred_real)):
out_fake = torch.sigmoid(out_a)
out_real = torch.sigmoid(out_b)
all0 = torch.zeros_like(out_fake).cuda(self.gpu)
all1 = torch.ones_like(out_real).cuda(self.gpu)
ad_fake_loss = nn.functional.binary_cross_entropy(out_fake, all0)
ad_true_loss = nn.functional.binary_cross_entropy(out_real, all1)
loss_D += ad_true_loss + ad_fake_loss
loss_D.backward()
return loss_D
def backward_contentD(self, imageA, imageB):
if self.with_stats:
# import pdb; pdb.set_trace()
imageA = (imageA[0].detach(), [(imageA[1][i][0].detach(), imageA[1][i][1].detach()) for i in range(len(imageA[1]))])
imageB = (imageB[0].detach(), [(imageB[1][i][0].detach(), imageB[1][i][1].detach()) for i in range(len(imageB[1]))])
else:
imageA, imageB = imageA.detach(), imageB.detach()
pred_fake = self.disContent.forward(imageA)
pred_real = self.disContent.forward(imageB)
for it, (out_a, out_b) in enumerate(zip(pred_fake, pred_real)):
out_fake = torch.sigmoid(out_a)
out_real = torch.sigmoid(out_b)
all1 = torch.ones((out_real.size(0))).cuda(self.gpu)
all0 = torch.zeros((out_fake.size(0))).cuda(self.gpu)
ad_true_loss = nn.functional.binary_cross_entropy(out_real, all1)
ad_fake_loss = nn.functional.binary_cross_entropy(out_fake, all0)
loss_D = ad_true_loss + ad_fake_loss
loss_D.backward()
return loss_D
def update_EG(self):
# update G, Ec, Ea
self.enc_c_opt.zero_grad()
self.enc_a_opt.zero_grad()
self.gen_opt.zero_grad()
self.backward_EG()
self.enc_c_opt.step()
self.enc_a_opt.step()
self.gen_opt.step()
# update G, Ec
self.enc_c_opt.zero_grad()
self.gen_opt.zero_grad()
self.backward_G_alone()
self.enc_c_opt.step()
self.gen_opt.step()
def backward_EG(self):
# content Ladv for generator
loss_G_GAN_Acontent = self.backward_G_GAN_content(self.z_content_a)
loss_G_GAN_Bcontent = self.backward_G_GAN_content(self.z_content_b)
# Ladv for generator
loss_G_GAN_A = self.backward_G_GAN(self.fake_A_encoded, self.disA)
loss_G_GAN_B = self.backward_G_GAN(self.fake_B_encoded, self.disB)
# KL loss - z_a
if self.concat:
kl_element_a = self.mu_a.pow(2).add_(self.logvar_a.exp()).mul_(-1).add_(1).add_(self.logvar_a)
loss_kl_za_a = torch.sum(kl_element_a).mul_(-0.5) * 0.01
kl_element_b = self.mu_b.pow(2).add_(self.logvar_b.exp()).mul_(-1).add_(1).add_(self.logvar_b)
loss_kl_za_b = torch.sum(kl_element_b).mul_(-0.5) * 0.01
else:
loss_kl_za_a = self._l2_regularize(self.z_attr_a) * 0.01
loss_kl_za_b = self._l2_regularize(self.z_attr_b) * 0.01
# KL loss - z_c
if self.with_stats:
loss_kl_zc_a = self._l2_regularize(self.z_content_a[0]) * 0.01
# for mean, std in self.z_content_a[1]:
# loss_kl_zc_a += (self._l2_regularize(mean) + self._l2_regularize(std)) * 0.001
loss_kl_zc_b = self._l2_regularize(self.z_content_b[0]) * 0.01
# for mean, std in self.z_content_a[1]:
# loss_kl_zc_b += (self._l2_regularize(mean) + self._l2_regularize(std)) * 0.001
else:
loss_kl_zc_a = self._l2_regularize(self.z_content_a) * 0.01
loss_kl_zc_b = self._l2_regularize(self.z_content_b) * 0.01
# cross cycle consistency loss
loss_G_L1_A = self.criterionL1(self.fake_A_recon, self.real_A_encoded) * 10
loss_G_L1_B = self.criterionL1(self.fake_B_recon, self.real_B_encoded) * 10
loss_G_L1_AA = self.criterionL1(self.fake_AA_encoded, self.real_A_encoded) * 10
loss_G_L1_BB = self.criterionL1(self.fake_BB_encoded, self.real_B_encoded) * 10
if self.vgg_w > 0.:
loss_vgg_a = self.compute_vgg19_loss(self.vgg, self.fake_A_encoded, self.real_B_encoded) * self.vgg_w
loss_vgg_b = self.compute_vgg19_loss(self.vgg, self.fake_B_encoded, self.real_A_encoded) * self.vgg_w
loss_vgg_a_rand = self.compute_vgg19_loss(self.vgg, self.fake_A_random, self.real_B_encoded) * self.vgg_w
loss_vgg_b_rand = self.compute_vgg19_loss(self.vgg, self.fake_B_random, self.real_A_encoded) * self.vgg_w
else:
loss_vgg_a = loss_vgg_b = loss_vgg_a_rand = loss_vgg_b_rand = 0.
loss_G = loss_G_GAN_A + loss_G_GAN_B + \
loss_G_GAN_Acontent + loss_G_GAN_Bcontent + \
loss_G_L1_AA + loss_G_L1_BB + \
loss_G_L1_A + loss_G_L1_B + \
loss_kl_zc_a + loss_kl_zc_b + \
loss_kl_za_a + loss_kl_za_b + \
loss_vgg_a + loss_vgg_b + \
loss_vgg_a_rand + loss_vgg_b_rand
loss_G.backward(retain_graph=True)
self.gan_loss_a = loss_G_GAN_A.item()
self.gan_loss_b = loss_G_GAN_B.item()
self.gan_loss_acontent = loss_G_GAN_Acontent.item()
self.gan_loss_bcontent = loss_G_GAN_Bcontent.item()
self.kl_loss_za_a = loss_kl_za_a.item()
self.kl_loss_za_b = loss_kl_za_b.item()
self.kl_loss_zc_a = loss_kl_zc_a.item()
self.kl_loss_zc_b = loss_kl_zc_b.item()
self.l1_recon_A_loss = loss_G_L1_A.item()
self.l1_recon_B_loss = loss_G_L1_B.item()
self.l1_recon_AA_loss = loss_G_L1_AA.item()
self.l1_recon_BB_loss = loss_G_L1_BB.item()
self.G_loss = loss_G.item()
if self.vgg_w > 0.:
self.vgg_loss_a = loss_vgg_a.item()
self.vgg_loss_b = loss_vgg_b.item()
self.vgg_loss_a_rand = loss_vgg_a_rand.item()
self.vgg_loss_b_rand = loss_vgg_b_rand.item()
def backward_G_GAN_content(self, data):
outs = self.disContent.forward(data)
for out in outs:
outputs_fake = torch.sigmoid(out)
all_half = 0.5*torch.ones((outputs_fake.size(0))).cuda(self.gpu)
ad_loss = nn.functional.binary_cross_entropy(outputs_fake, all_half)
return ad_loss
def backward_G_GAN(self, fake, netD=None):
outs_fake = netD.forward(fake)
loss_G = 0
for out_a in outs_fake:
outputs_fake = torch.sigmoid(out_a)
all_ones = torch.ones_like(outputs_fake).cuda(self.gpu)
loss_G += nn.functional.binary_cross_entropy(outputs_fake, all_ones)
return loss_G
def backward_G_alone(self):
# Ladv for generator
loss_G_GAN2_A = self.backward_G_GAN(self.fake_A_random, self.disA2)
loss_G_GAN2_B = self.backward_G_GAN(self.fake_B_random, self.disB2)
# latent regression loss
if self.concat:
loss_z_L1_a = torch.mean(torch.abs(self.mu2_a - self.z_random)) * 10
loss_z_L1_b = torch.mean(torch.abs(self.mu2_b - self.z_random)) * 10
else:
loss_z_L1_a = torch.mean(torch.abs(self.z_attr_random_a - self.z_random)) * 10
loss_z_L1_b = torch.mean(torch.abs(self.z_attr_random_b - self.z_random)) * 10
loss_z_L1 = loss_z_L1_a + loss_z_L1_b + loss_G_GAN2_A + loss_G_GAN2_B
loss_z_L1.backward()
self.l1_recon_z_loss_a = loss_z_L1_a.item()
self.l1_recon_z_loss_b = loss_z_L1_b.item()
self.gan2_loss_a = loss_G_GAN2_A.item()
self.gan2_loss_b = loss_G_GAN2_B.item()
def update_lr(self):
self.disA_sch.step()
self.disB_sch.step()
self.disA2_sch.step()
self.disB2_sch.step()
self.disContent_sch.step()
self.enc_c_sch.step()
self.enc_a_sch.step()
self.gen_sch.step()
def _l2_regularize(self, mu):
mu_2 = torch.pow(mu, 2)
encoding_loss = torch.mean(mu_2)
return encoding_loss
def resume(self, model_dir, train=True):
checkpoint = torch.load(model_dir)
# weight
if train:
self.disA.load_state_dict(checkpoint['disA'])
self.disA2.load_state_dict(checkpoint['disA2'])
self.disB.load_state_dict(checkpoint['disB'])
self.disB2.load_state_dict(checkpoint['disB2'])
self.disContent.load_state_dict(checkpoint['disContent'])
self.enc_c.load_state_dict(checkpoint['enc_c'])
self.enc_a.load_state_dict(checkpoint['enc_a'])
self.gen.load_state_dict(checkpoint['gen'])
# optimizer
if train:
self.disA_opt.load_state_dict(checkpoint['disA_opt'])
self.disA2_opt.load_state_dict(checkpoint['disA2_opt'])
self.disB_opt.load_state_dict(checkpoint['disB_opt'])
self.disB2_opt.load_state_dict(checkpoint['disB2_opt'])
self.disContent_opt.load_state_dict(checkpoint['disContent_opt'])
self.enc_c_opt.load_state_dict(checkpoint['enc_c_opt'])
self.enc_a_opt.load_state_dict(checkpoint['enc_a_opt'])
self.gen_opt.load_state_dict(checkpoint['gen_opt'])
return checkpoint['ep'], checkpoint['total_it']
def save(self, filename, ep, total_it):
state = {
'disA': self.disA.state_dict(),
'disA2': self.disA2.state_dict(),
'disB': self.disB.state_dict(),
'disB2': self.disB2.state_dict(),
'disContent': self.disContent.state_dict(),
'enc_c': self.enc_c.state_dict(),
'enc_a': self.enc_a.state_dict(),
'gen': self.gen.state_dict(),
'disA_opt': self.disA_opt.state_dict(),
'disA2_opt': self.disA2_opt.state_dict(),
'disB_opt': self.disB_opt.state_dict(),
'disB2_opt': self.disB2_opt.state_dict(),
'disContent_opt': self.disContent_opt.state_dict(),
'enc_c_opt': self.enc_c_opt.state_dict(),
'enc_a_opt': self.enc_a_opt.state_dict(),
'gen_opt': self.gen_opt.state_dict(),
'ep': ep,
'total_it': total_it
}
torch.save(state, filename)
return
def assemble_outputs(self):
images_a = self.normalize_image(self.real_A_encoded).detach()
images_b = self.normalize_image(self.real_B_encoded).detach()
images_a1 = self.normalize_image(self.fake_A_encoded).detach()
images_a2 = self.normalize_image(self.fake_A_random).detach()
images_a3 = self.normalize_image(self.fake_A_recon).detach()
images_a4 = self.normalize_image(self.fake_AA_encoded).detach()
images_b1 = self.normalize_image(self.fake_B_encoded).detach()
images_b2 = self.normalize_image(self.fake_B_random).detach()
images_b3 = self.normalize_image(self.fake_B_recon).detach()
images_b4 = self.normalize_image(self.fake_BB_encoded).detach()
row1 = torch.cat((images_a[0:1, ::], images_b1[0:1, ::], images_b2[0:1, ::], images_a4[0:1, ::], images_a3[0:1, ::]),3)
row2 = torch.cat((images_b[0:1, ::], images_a1[0:1, ::], images_a2[0:1, ::], images_b4[0:1, ::], images_b3[0:1, ::]),3)
return torch.cat((row1,row2),2)
def normalize_image(self, x):
return x[:,0:3,:,:]
def compute_vgg19_loss(self, vgg, img, target, vgg_type='vgg19'):
img_feature = self.vgg((img + 1) / 2)
target_feature = self.vgg((target + 1) / 2).detach()
return F.l1_loss(img_feature, target_feature)
|
BRATS/compress_data.py | eanemo/KiU-Net-pytorch | 236 | 11124758 | <gh_stars>100-1000
import argparse
import os
import numpy as np
from multiprocessing import Pool
def float2uint(file_path):
filename = file_path[:file_path.find('.npy')]+'.npz'
data_float32 = np.load(file_path)
data_temp = 255 * data_float32
data_uint8 = data_temp.astype(np.uint8)
print(filename)
np.savez_compressed(filename, data=data_uint8)
os.remove(file_path)
parser = argparse.ArgumentParser()
parser.add_argument('-output', '--output', default='/home/pkao/brats2017-master/output', type=str)
#parser.add_argument('-output', '--output', default='/media/hdd1/pkao/brats2018/output', type=str)
parser.add_argument('-cfg', '--cfg', default='unet_ce_hard', type=str)
#parser.add_argument('-mode', '--mode', default='validation', type=str)
args = parser.parse_args()
#root_dir = os.path.join(args.output, args.mode, args.cfg)
root_dir = os.path.join(args.output, args.cfg)
#print(root_dir)
float32_paths = [os.path.join(root, name) for root, dirs, files in os.walk(root_dir) for name in files if name.endswith('.npy')]
assert(len(float32_paths) == 191)
pool = Pool(16)
pool.map(float2uint, float32_paths)
|
tests/test_aliases.py | orsinium/condition | 311 | 11124781 | from inspect import getdoc
from typing import get_type_hints
import pytest
import deal
def get_func():
@deal.pre(lambda x: x > 0)
@deal.post(lambda x: x > 0)
@deal.ensure(lambda *args, **kwargs: True)
@deal.raises(ValueError)
@deal.safe
@deal.safe()
@deal.pure
@deal.chain(deal.safe, deal.pure)
def func(x: int) -> int:
"""docs were before docker
"""
return x
return func
def test_preserve_type_annotations():
"""
IMPORTANT: this checks preserving type annotations in runtime.
mypy is a static analyser and can produce a different result.
"""
func = get_func()
annotations = get_type_hints(func)
assert set(annotations) == {'x', 'return'}
assert annotations['x'] in ('int', int)
assert annotations['return'] in ('int', int)
def test_preserve_docstring():
func = get_func()
docs = getdoc(func)
assert docs is not None
assert docs.strip() == 'docs were before docker'
def test_implies():
@deal.pre(lambda x, y: deal.implies(x, y))
def f(x, y):
pass
f(True, True)
f(False, True)
f(False, False)
with pytest.raises(deal.PreContractError):
f(True, False)
def test_catch():
def div(x, y):
return x / y
assert deal.catch(div, 1, 2) is None
assert deal.catch(div, 1, y=2) is None
assert deal.catch(div, x=1, y=2) is None
assert deal.catch(div, 1, 0) is ZeroDivisionError
|
vaas-app/src/vaas/external/oauth.py | allegro/vaas | 251 | 11124789 | <reponame>allegro/vaas
import importlib
from django.conf import settings
from tastypie.authentication import MultiAuthentication
# If Oauth for API is enabled & custom module (OAUTH_AUTH_MODULE) is not present,
# default TastyPie OAuthAuthentication backend will be used
API_OAUTH_ENABLED = getattr(settings, 'API_OAUTH_ENABLED', False)
OAUTH_AUTH_MODULE = getattr(settings, 'OAUTH_AUTH_MODULE', 'tastypie.authentication')
if API_OAUTH_ENABLED:
oauth_module = importlib.import_module(OAUTH_AUTH_MODULE)
OAuthAuthentication = getattr(oauth_module, 'OAuthAuthentication')
class VaasMultiAuthentication(MultiAuthentication):
def __init__(self, *backends, **kwargs):
super(MultiAuthentication, self).__init__(**kwargs)
if API_OAUTH_ENABLED:
backends = backends + (OAuthAuthentication(),)
self.backends = backends
|
applications/MultilevelMonteCarloApplication/external_libraries/PyCOMPSs/exaqute/common/exception.py | lkusch/Kratos | 778 | 11124802 | <reponame>lkusch/Kratos<filename>applications/MultilevelMonteCarloApplication/external_libraries/PyCOMPSs/exaqute/common/exception.py<gh_stars>100-1000
class ExaquteException(Exception):
pass
|
tests/test_repo.py | Bing1012/3 | 1,040 | 11124823 | <reponame>Bing1012/3
import os
import subprocess
import sys
from pathlib import Path
import pytest
from pyscaffold import actions, api, cli, repo, shell, structure, toml
from pyscaffold.file_system import chdir, move, rm_rf
def test_init_commit_repo(tmpfolder):
with tmpfolder.mkdir("my_porject").as_cwd():
struct = {
"my_file": "Some other content",
"my_dir": {"my_file": "Some more content"},
"dummy": None,
}
structure.create_structure(struct, {})
dummy_file = Path("dummy")
with dummy_file.open(mode="w"):
os.utime(str(dummy_file), None)
repo.init_commit_repo(".", struct)
assert Path(".git").exists()
def test_pretend_init_commit_repo(tmpfolder):
with tmpfolder.mkdir("my_porject").as_cwd():
struct = {
"my_file": "Some other content",
"my_dir": {"my_file": "Some more content"},
"dummy": None,
}
structure.create_structure(struct, {})
dummy_file = Path("dummy")
with dummy_file.open(mode="w"):
os.utime(str(dummy_file), None)
repo.init_commit_repo(".", struct, pretend=True)
assert not Path(".git").exists()
def test_init_commit_repo_with_wrong_structure(tmpfolder):
project = "my_project"
struct = {"my_file": type("StrangeType", (object,), {})()}
os.mkdir(project)
with pytest.raises(TypeError):
repo.init_commit_repo(project, struct)
def test_add_tag(tmpfolder):
project = "my_project"
struct = {
"my_file": "Some other content",
"my_dir": {"my_file": "Some more content"},
}
structure.create_structure(struct, dict(project_path=project))
repo.init_commit_repo(project, struct)
repo.add_tag(project, "v0.0")
repo.add_tag(project, "v0.1", "Message with whitespace")
@pytest.mark.slow
def test_version_of_subdir(tmpfolder):
projects = ["main_project", "inner_project"]
for project in projects:
opts = cli.parse_args([project])
opts = api.bootstrap_options(opts)
_, opts = actions.get_default_options({}, opts)
struct, _ = structure.define_structure({}, opts)
struct, _ = structure.create_structure(struct, opts)
repo.init_commit_repo(project, struct)
rm_rf(Path("inner_project", ".git"))
move("inner_project", target="main_project/inner_project")
# setuptools_scm required explicitly setting the git root when setup.py is
# not at the root of the repository
nested_setup_py = Path(tmpfolder, "main_project/inner_project/setup.py")
content = nested_setup_py.read_text()
content = content.replace(
"use_scm_version={", 'use_scm_version={"root": "..", "relative_to": __file__, '
)
nested_setup_py.write_text(content)
nested_pyproject_toml = Path(tmpfolder, "main_project/inner_project/pyproject.toml")
config = toml.loads(nested_pyproject_toml.read_text())
config["tool"]["setuptools_scm"]["root"] = ".."
nested_pyproject_toml.write_text(toml.dumps(config))
with chdir("main_project"):
main_version = (
subprocess.check_output([sys.executable, "setup.py", "--version"])
.strip()
.splitlines()[-1]
)
with chdir("inner_project"):
inner_version = (
subprocess.check_output([sys.executable, "setup.py", "--version"])
.strip()
.splitlines()[-1]
)
assert main_version.strip() == inner_version.strip()
def test_is_git_repo(tmpfolder):
assert not repo.is_git_repo("/a-folder/that-not/exist")
newdir = tmpfolder.join("new").ensure_dir()
assert not repo.is_git_repo(str(newdir))
newdir.chdir()
shell.git("init")
tmpfolder.chdir()
assert repo.is_git_repo(str(newdir))
def test_get_git_root(tmpfolder):
project = "my_project"
struct = {
"my_file": "Some other content",
"my_dir": {"my_file": "Some more content"},
}
structure.create_structure(struct, {"project_path": project})
repo.init_commit_repo(project, struct)
with chdir(project):
git_root = repo.get_git_root()
assert Path(git_root).name == project
def test_get_git_root_with_nogit(tmpfolder, nogit_mock):
project = "my_project"
struct = {
"my_file": "Some other content",
"my_dir": {"my_file": "Some more content"},
}
structure.create_structure(struct, {"project_path": project})
with chdir(project):
git_root = repo.get_git_root(default=".")
assert git_root == "."
def test_get_git_root_with_nonegit(tmpfolder, nonegit_mock):
project = "my_project"
struct = {
"my_file": "Some other content",
"my_dir": {"my_file": "Some more content"},
}
structure.create_structure(struct, {"project_path": project})
with chdir(project):
git_root = repo.get_git_root(default=".")
assert git_root == "."
|
site/search-index/pagerank.py | vishalbelsare/neupy | 801 | 11124890 | <gh_stars>100-1000
import scipy
import numpy as np
import scipy.sparse as sp
def pagerank(graph_matrix, n_iter=100, alpha=0.9, tol=1e-6):
n_nodes = graph_matrix.shape[0]
n_edges_per_node = graph_matrix.sum(axis=1)
n_edges_per_node = np.array(n_edges_per_node).flatten()
np.seterr(divide='ignore')
normilize_vector = np.where((n_edges_per_node != 0),
1. / n_edges_per_node, 0)
np.seterr(divide='warn')
normilize_matrix = sp.spdiags(normilize_vector, 0,
*graph_matrix.shape, format='csr')
graph_proba_matrix = normilize_matrix * graph_matrix
teleport_proba = np.repeat(1. / n_nodes, n_nodes)
is_dangling, = scipy.where(normilize_vector == 0)
x_current = teleport_proba
for _ in range(n_iter):
x_previous = x_current.copy()
dangling_total_proba = sum(x_current[is_dangling])
x_current = (
x_current * graph_proba_matrix +
dangling_total_proba * teleport_proba
)
x_current = alpha * x_current + (1 - alpha) * teleport_proba
error = np.abs(x_current - x_previous).mean()
if error < tol:
break
else:
print("PageRank didn't converge")
return x_current
|
algoexpert.io/python/Longest_Common_Subsequence.py | its-sushant/coding-interview-gym | 713 | 11124895 | <reponame>its-sushant/coding-interview-gym
# Solution: My solution using 2d dp
# O(nm) time | O(nm) space
def longestCommonSubsequence(string1, string2):
dp = [[[] for _ in range(len(string2) + 1)] for _ in range(len(string1) + 1)]
for i in range(1, len(string1) + 1):
x = string1[i - 1]
for j in range(1, len(string2) + 1):
rx = string2[j - 1]
if x == rx:
dp[i][j] = dp[i - 1][j - 1] + [x]
else:
dp[i][j] = max(dp[i][j - 1], dp[i - 1][j], key=len)
return dp[-1][-1]
|
one_step_app.py | Questions1/Rong360_2nd | 107 | 11124909 |
import numpy as np
import pandas as pd
def read_app(file_path):
reader = pd.read_table(file_path, header=None, chunksize=10000)
data = pd.concat(reader, axis=0, ignore_index=True)
data.columns = ['id', 'apps']
return data
def get_apps_dummy(data):
"""
把dat_app里用户装的app信息0-1化
1. 读取需要的104个app：app_104_list
2. 然后得到长度为‘len(app_104_list)’的0-1向量
"""
def is_in_all_apps(x):
xs = x.split(',')
xs = set(xs)
app_vec = list(map(lambda app: int(app in xs), app_66))
return app_vec
apps_dummy_0 = list(map(is_in_all_apps, data['apps']))
apps_dummy_1 = pd.DataFrame(apps_dummy_0, columns=app_66)
apps_dummy_2 = pd.concat([data[['id']], apps_dummy_1], axis=1)
return apps_dummy_2
if __name__ == '__main__':
input_path = './'
sample_train = pd.read_table('./open_data/sample_train.txt') # 训练集约1.9万
valid_id = pd.read_table('./open_data/valid_id.txt') # 验证集
test_id = pd.read_table('./open_data/test_id.txt') # 测试集
dat_app = pd.concat([read_app('./open_data/dat_app/dat_app_%s' % x) for x in range(1, 8)],
axis=0, ignore_index=True)
important_feature_app = pd.read_csv('./output/important_feature_app.csv')
app_66 = [str(x) for x in important_feature_app['feature']]
son = pd.read_csv('./output/son.csv')
father = pd.read_csv('./output/father.csv')
all_id = pd.concat([sample_train[['id']], valid_id[['id']], test_id[['id']]], axis=0)
whole_id = list(set(son['to_id']).union(set(father['from_id'])).union(all_id['id']))
one_step_id = pd.DataFrame({'id': whole_id})
one_step_app = pd.merge(one_step_id, dat_app, on='id')
one_step_apps_dummy = get_apps_dummy(one_step_app)
one_step_apps_dummy.to_csv('./output/one_step_apps_dummy.csv', index=False)
|
controllers/admin/admin_offseason_scraper_controller.py | tervay/the-blue-alliance | 266 | 11124925 | import datetime
import logging
import os
from google.appengine.ext import ndb
from google.appengine.ext.webapp import template
from controllers.base_controller import LoggedInHandler
from datafeeds.datafeed_usfirst_offseason import DatafeedUsfirstOffseason
from consts.event_type import EventType
from helpers.event_manipulator import EventManipulator
from models.event import Event
class AdminOffseasonScraperController(LoggedInHandler):
"""
View and add un-added offseasons from FIRST's site
"""
def get(self):
self._require_admin()
df = DatafeedUsfirstOffseason()
new_events = df.getEventList()
old_events = Event.query().filter(
Event.event_type_enum == EventType.OFFSEASON).filter(
Event.year == datetime.datetime.now().year).filter(
Event.first_eid != None).fetch(100)
old_first_eids = [event.first_eid for event in old_events]
truly_new_events = [event for event in new_events if event.first_eid not in old_first_eids]
self.template_values.update({
"events": truly_new_events,
"event_key": self.request.get("event_key"),
"success": self.request.get("success"),
})
path = os.path.join(os.path.dirname(__file__), '../../templates/admin/offseasons.html')
self.response.out.write(template.render(path, self.template_values))
def post(self):
self._require_admin()
if self.request.get("submit") == "duplicate":
old_event = Event.get_by_id(self.request.get("duplicate_event_key"))
old_event.first_eid = self.request.get("event_first_eid")
old_event.dirty = True # TODO: hacky
EventManipulator.createOrUpdate(old_event)
self.redirect("/admin/offseasons?success=duplicate&event_key=%s" % self.request.get("duplicate_event_key"))
return
if self.request.get("submit") == "create":
start_date = None
if self.request.get("event_start_date"):
start_date = datetime.datetime.strptime(self.request.get("event_start_date"), "%Y-%m-%d")
end_date = None
if self.request.get("event_end_date"):
end_date = datetime.datetime.strptime(self.request.get("event_end_date"), "%Y-%m-%d")
event_key = str(self.request.get("event_year")) + str.lower(str(self.request.get("event_short")))
event = Event(
id=event_key,
event_type_enum=int(self.request.get("event_type_enum")),
event_short=self.request.get("event_short"),
first_eid=self.request.get("event_first_eid"),
name=self.request.get("event_name"),
year=int(self.request.get("event_year")),
start_date=start_date,
end_date=end_date,
city=self.request.get("city"),
state_prov=self.request.get("state_prov"),
country=self.request.get("country"),
)
event = EventManipulator.createOrUpdate(event)
self.redirect("/admin/offseasons?success=create&event_key=%s" % event_key)
return
self.redirect("/admin/offseasons")
|
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