python_code stringlengths 0 4.04M | repo_name stringlengths 7 58 | file_path stringlengths 5 147 |
|---|---|---|
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import tempfile
import crypten
import crypten.communicator as comm
import torch
import torch.nn as nn
import torch.nn... | CrypTen-main | examples/mpc_autograd_cnn/mpc_autograd_cnn.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
To run mpc_autograd_cnn example:
$ python examples/mpc_autograd_cnn/launcher.py
To run mpc_linear_svm example on ... | CrypTen-main | examples/mpc_autograd_cnn/launcher.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Generate function and model benchmarks
To Run:
$ python benchmark.py
# Only function benchmarks
$ python benchmar... | CrypTen-main | benchmarks/benchmark.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Contains models used for benchmarking
"""
from dataclasses import dataclass
from typing import Any
import crypte... | CrypTen-main | benchmarks/models.py |
CrypTen-main | benchmarks/__init__.py | |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
A script to run historical benchmarks.
- writes monthly data to 'dash_app/data/`
- example: 'dash_app/data/201... | CrypTen-main | benchmarks/run_historical_benchmarks.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Profiler with snakeviz for probing inference / training call stack
Run via Jupyter
"""
from benchmark import Mod... | CrypTen-main | benchmarks/profiler.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Contains data used for training / testing model benchmarks
"""
import os
from pathlib import Path
import crypten
... | CrypTen-main | benchmarks/data.py |
CrypTen-main | benchmarks/dash_app/__init__.py | |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import pathlib
import dash
import dash_core_components as dcc
import dash_html_components as html
import numpy as np
... | CrypTen-main | benchmarks/dash_app/app.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import os
import pandas as pd
def get_aggregated_data(base_dir, subdirs):
"""Aggregate dataframe for model and... | CrypTen-main | benchmarks/dash_app/load_data.py |
CrypTen-main | configs/__init__.py | |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import os
import subprocess
import uuid
from argparse import ArgumentParser, REMAINDER
"""
Wrapper to launch MPC scr... | CrypTen-main | scripts/distributed_launcher.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
This file is a tool to run MPC distributed training over AWS.
To run distributed training, first multiple AWS inst... | CrypTen-main | scripts/aws_launcher.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import os
import torch
from torchvision import datasets, transforms
def _get_norm_mnist(dir, reduce... | CrypTen-main | tutorials/mnist_utils.py |
#! /usr/bin/env python
import sys
if len(sys.argv) != 4:
print 'Wrong number of arguments'
print 'USAGE: ./compute_stats_helper.py $label_tsvfile $prediction_tsvfile $confidence'
exit(1)
label_filename = sys.argv[1]
pred_filename = sys.argv[2]
confidence = float(sys.argv[3])
# read label filename
label... | dd-genomics-master | results_log/compute_stats_helper.py |
import ddext
from ddext import SD
def init():
ddext.input('doc_id', 'text')
ddext.input('sent_id', 'int')
ddext.input('words', 'text[]')
ddext.input('lemmas', 'text[]')
ddext.input('poses', 'text[]')
ddext.input('ners', 'text[]')
ddext.returns('doc_id', 'text')
ddext.returns('sent_id', 'int')
ddext... | dd-genomics-master | xapp/code/gene_mentions.py |
import ddext
from ddext import SD
def init():
ddext.input('doc_id', 'text')
ddext.input('sent_id', 'int')
ddext.input('words', 'text[]')
ddext.input('lemmas', 'text[]')
ddext.input('poses', 'text[]')
ddext.input('ners', 'text[]')
ddext.returns('doc_id', 'text')
ddext.returns('sent_id', 'int')
ddext... | dd-genomics-master | xapp/code/pheno_mentions.py |
import ddext
def init():
ddext.input('doc_id', 'text')
ddext.input('sent_id', 'int')
ddext.input('words', 'text[]')
ddext.input('lemmas', 'text[]')
ddext.input('poses', 'text[]')
ddext.input('ners', 'text[]')
ddext.input('dep_paths', 'text[]')
ddext.input('dep_parents', 'int[]')
ddext.input('wordidxs... | dd-genomics-master | xapp/code/pair_features.py |
import ddext
from ddext import SD
def init():
ddext.input('doc_id', 'text')
ddext.input('sent_id_1', 'int')
ddext.input('mention_id_1', 'text')
ddext.input('wordidxs_1', 'int[]')
ddext.input('words_1', 'text[]')
ddext.input('entity_1', 'text')
ddext.input('type_1', 'text')
ddext.input('correct_1', 'bo... | dd-genomics-master | xapp/code/gene_pheno_pairs.py |
import ddext
def init():
ddext.input('doc_id', 'text')
ddext.input('sent_id', 'int')
ddext.input('words', 'text[]')
ddext.input('lemmas', 'text[]')
ddext.input('poses', 'text[]')
ddext.input('ners', 'text[]')
ddext.input('dep_paths', 'text[]')
ddext.input('dep_parents', 'int[]')
ddext.input('mention... | dd-genomics-master | xapp/code/mention_features.py |
#!/usr/bin/env python
import sys
if len(sys.argv) != 2:
print 'Wrong number of arguments'
print 'USAGE: ./compute_stats_helper.py $label_tsvfile $prediction_tsvfile $confidence'
exit(1)
old_labels_fn = sys.argv[1]
with open(old_labels_fn) as f:
for i, line in enumerate(f):
line = line.split(... | dd-genomics-master | labeling/convert_old_gp_labels.py |
#!/usr/bin/env python
import json
import sys
import os.path
# get the labeling version number
version = 0 # in case the file doesn't exist
if os.path.exists('version_labeling'):
with open('version_labeling') as f:
for i, line in enumerate(f):
if i == 0:
version = line[0].strip()
else:
print 've... | dd-genomics-master | labeling/extract_gene_labels_from_json.py |
#! /usr/bin/env python
import json
import sys
import os.path
# get the labeling version number
version = 0 # in case the file doesn't exist
if os.path.exists('version_labeling'):
with open('version_labeling') as f:
for i, line in enumerate(f):
if i == 0:
version = line[0].strip()
else:
print '... | dd-genomics-master | labeling/extract_genepheno_causation_labels_from_json.py |
#!/usr/bin/env python
import json
import sys
import os.path
# get the labeling version number
version = 0 # in case the file doesn't exist
if os.path.exists('version_labeling'):
with open('version_labeling') as f:
for i, line in enumerate(f):
if i == 0:
version = line[0].strip()
else:
print 've... | dd-genomics-master | labeling/extract_pheno_labels_from_json.py |
#!/usr/bin/env python
import sys
if len(sys.argv) != 2:
print 'Wrong number of arguments'
print 'USAGE: ./compute_stats_helper.py $label_tsvfile $prediction_tsvfile $confidence'
exit(1)
old_labels_fn = sys.argv[1]
with open(old_labels_fn) as f:
for i, line in enumerate(f):
line = line.split(... | dd-genomics-master | labeling/convert_old_g_labels.py |
#! /usr/bin/env python
import json
import sys
import os.path
# get the labeling version number
version = 0 # in case the file doesn't exist
if os.path.exists('version_labeling'):
with open('version_labeling') as f:
for i, line in enumerate(f):
if i == 0:
version = line[0].strip()
else:
print '... | dd-genomics-master | labeling/extract_genepheno_association_labels_from_json.py |
#!/usr/bin/env python
import extractor_util as util
from collections import namedtuple
import os
import ddlib
import config
import sys
import re
parser = util.RowParser([
('relation_id', 'text'),
('doc_id', 'text'),
('section_id', 'text'),
('sent_id', 'int'),
('gene_me... | dd-genomics-master | code/genepheno_extract_features.py |
#!/usr/bin/env python
import extractor_util as util
from collections import namedtuple
import os
import sys
import ddlib
import config
# This defines the Row object that we read in to the extractor
parser = util.RowParser([
('doc_id', 'text'),
('section_id', 'text'),
('sent_id', 'int'),
... | dd-genomics-master | code/variant_extract_features.py |
import collections
import extractor_util as util
import data_util as dutil
import dep_util as deps
import random
import re
import sys
# This defines the Row object that we read in to the extractor
parser = util.RowParser([
('relation_id', 'text'),
('doc_id', 'text'),
('section_id',... | dd-genomics-master | code/genepheno_supervision_util.py |
# -*- coding: utf-8 -*-
# CONFIG
# The master configuration file for candidate extraction, distant supervision and feature
# extraction hyperparameters / configurations
import sys
import copy
if sys.version_info < (2, 7):
assert False, "Need Python version 2.7 at least"
BOOL_VALS = [('neg', False), ('pos', True)]
... | dd-genomics-master | code/config.py |
#!/usr/bin/env python
import extractor_util as util
from collections import namedtuple
import os
import sys
import ddlib
parser = util.RowParser([
('relation_id', 'text'),
('doc_id', 'text'),
('section_id', 'text'),
('sent_id', 'int'),
('genevar_mention_id', 'text'),
... | dd-genomics-master | code/variantpheno_extract_features.py |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import collections
import extractor_util as util
import data_util as dutil
import random
import re
import os
import sys
import string
import config
import dep_util as deps
# This defines the Row object that we read in to the extractor
parser = util.RowParser([
(... | dd-genomics-master | code/variant_extract_candidates.py |
#!/usr/bin/env python
import collections
import extractor_util as util
import re
import sys
CACHE = dict() # Cache results of disk I/O
# This defines the Row object that we read in to the extractor
parser = util.RowParser([
('doc_id', 'text'),
('section_id', 'text'),
('sent_id', 'int')... | dd-genomics-master | code/sentences_input_ner_extraction.py |
"""Miscellaneous shared tools for maniuplating data used in the UDFs"""
from collections import defaultdict, namedtuple
import extractor_util as util
import os
import re
import sys
APP_HOME = os.environ['GDD_HOME']
onto_path = lambda p : '%s/onto/%s' % (os.environ['GDD_HOME'], p)
class Dag:
"""Class representing a... | dd-genomics-master | code/data_util.py |
#!/usr/bin/env python
from collections import namedtuple
import extractor_util as util
import os
import sys
import ddlib
import re
import config
# This defines the Row object that we read in to the extractor
parser = util.RowParser([
('doc_id', 'text'),
('section_id', 'text'),
('sent_id',... | dd-genomics-master | code/non_gene_acronyms_extract_features.py |
#!/usr/bin/env python
'''Link abbreviations to their full names
Based on
A Simple Algorithm for Identifying Abbreviations Definitions in Biomedical Text
A. Schwartz and M. Hearst
Biocomputing, 2003, pp 451-462.
# License: GNU General Public License, see http://www.clips.ua.ac.be/~vincent/scripts/LICENSE.txt
'''
__a... | dd-genomics-master | code/abbreviations.py |
#! /usr/bin/env python
import collections
import extractor_util as util
import data_util as dutil
import dep_util as deps
import random
import re
import sys
import config
# This defines the Row object that we read in to the extractor
parser = util.RowParser([
('relation_id', 'text'),
('doc_id'... | dd-genomics-master | code/genepheno_extract_features2.py |
#!/usr/bin/env python
from collections import defaultdict, namedtuple
import sys
import re
import os
import random
from itertools import chain
import extractor_util as util
import data_util as dutil
import config
# This defines the Row object that we read in to the extractor
parser = util.RowParser([
('doc... | dd-genomics-master | code/pheno_acronyms_to_mentions.py |
#!/usr/bin/env python
import collections
import extractor_util as util
import data_util as dutil
import dep_util as deps
import os
import random
import re
import sys
import config
# This defines the Row object that we read in to the extractor
parser = util.RowParser([
('doc_id', 'text'),
('section... | dd-genomics-master | code/genepheno_extract_candidates.py |
#!/usr/bin/env python
import collections
import os
import sys
import abbreviations
import config
import extractor_util as util
import levenshtein
CACHE = dict() # Cache results of disk I/O
# This defines the Row object that we read in to the extractor
parser = util.RowParser([
('doc_id', 'text'),
... | dd-genomics-master | code/non_gene_acronyms_extract_candidates.py |
#! /usr/bin/env python
import collections
import extractor_util as eutil
import sys
from dep_alignment.alignment_util import row_to_canonical_match_tree, DepParentsCycleException, OverlappingCandidatesException, RootException
from dep_alignment.multi_dep_alignment import MultiDepAlignment
import os
import random
impor... | dd-genomics-master | code/genepheno_sv_new.py |
#! /usr/bin/env python
import sys
import config
import genepheno_supervision_util as sv
if __name__ == '__main__':
sr = config.GENE_PHENO_CAUSATION['SR']
hf = config.GENE_PHENO_CAUSATION['HF']
sv.supervise(sr, hf, charite_allowed=True)
| dd-genomics-master | code/genepheno_causation_supervision.py |
#! /usr/bin/env python
import sys
import config
import genepheno_supervision_util as sv
if __name__ == '__main__':
sr = config.GENE_PHENO_CAUSATION['SR']
hf = config.GENE_PHENO_CAUSATION['HF']
sv.supervise(sr, hf, charite_allowed=False)
| dd-genomics-master | code/genepheno_causation_supervision_no_charite.py |
#!/usr/bin/env python
from collections import defaultdict, namedtuple
import sys
import re
import os
import random
from itertools import chain
import extractor_util as util
import data_util as dutil
import config
onto_path = lambda p : '%s/onto/%s' % (os.environ['GDD_HOME'], p)
# This defines the Row object that we r... | dd-genomics-master | code/pheno_extract_candidates.py |
#!/usr/bin/env python
import collections
import extractor_util as util
import data_util as dutil
import random
import re
import os
import sys
import string
import config
import dep_util as deps
CACHE = dict() # Cache results of disk I/O
# This defines the Row object that we read in to the extractor
parser = util.Ro... | dd-genomics-master | code/gene_extract_candidates.py |
#!/usr/bin/env python
import extractor_util as util
import os
import ddlib
import config
# This defines the Row object that we read in to the extractor
parser = util.RowParser([
('doc_id', 'text'),
('section_id', 'text'),
('sent_id', 'int'),
('words', 'text[]'),
('lemm... | dd-genomics-master | code/pheno_extract_features.py |
#!/usr/bin/env python
import collections
import extractor_util as util
import data_util as dutil
import dep_util as deps
import os
import random
import re
import sys
import config
# This defines the Row object that we read in to the extractor
parser = util.RowParser([
('doc_id', 'text'),
('gene_se... | dd-genomics-master | code/genevariant_extract_candidates.py |
#!/usr/bin/env python
import collections
import os
import sys
import abbreviations
import config
import extractor_util as util
import levenshtein
import data_util as dutil
CACHE = dict() # Cache results of disk I/O
# This defines the Row object that we read in to the extractor
parser = util.RowParser([
(... | dd-genomics-master | code/pheno_mentions_remove_super_dag_phenos.py |
#! /usr/bin/env python
import config
import sys
if __name__ == "__main__":
disallowed_phrases = config.PHENO['HF']['disallowed-phrases']
for line in sys.stdin:
take = True
for dp in disallowed_phrases:
if dp in line.lower():
take = False
break
if take:
sys.stdout.write(line... | dd-genomics-master | code/create_allowed_diseases_list.py |
"""Miscellaneous shared tools for extractors."""
import os
import re
import sys
import ddlib
import traceback
FIX_DEP_PARENTS = True
def rgx_comp(strings=[], rgxs=[]):
r = r'|'.join(re.escape(w) for w in strings)
if len(rgxs) > 0:
if len(strings) > 0:
r += r'|'
r += r'(' + r')|('.join(rgxs) + r')'
... | dd-genomics-master | code/extractor_util.py |
'''
Created on Aug 5, 2015
@author: jbirgmei
'''
# from wikipedia. let's hope it works
def levenshtein(s1, s2):
if len(s1) < len(s2):
return levenshtein(s2, s1)
# len(s1) >= len(s2)
if len(s2) == 0:
return len(s1)
previous_row = range(len(s2) + 1)
for i, c1 in enumerate(s1):
current_row = [i +... | dd-genomics-master | code/levenshtein.py |
#! /usr/bin/env python
from data_util import get_hpo_phenos, get_parents, read_hpo_dag, read_hpo_synonyms
if __name__ == "__main__":
hpo_dag = read_hpo_dag()
names = read_hpo_synonyms(1)
synonyms = read_hpo_synonyms()
allowed_phenos = set(get_hpo_phenos(hpo_dag))
for hpo_id in allowed_phenos.copy():
par... | dd-genomics-master | code/create_allowed_phenos_list.py |
from collections import defaultdict
# TODO: handle negations (neg, advmod + neg word) specially!
# See: http://nlp.stanford.edu/software/dependencies_manual.pdf
MAX_PATH_LEN = 100
class DepPathDAG:
def __init__(self, dep_parents, dep_paths, words, max_path_len=None, no_count_tags=('conj',), no_count_words=('_','*... | dd-genomics-master | code/dep_util.py |
#! /usr/bin/env python
import dep_util
import extractor_util as util
import sys
# This defines the Row object that we read in to the extractor
parser = util.RowParser([
('doc_id', 'text'),
('section_id', 'text'),
('sent_id', 'text'),
('dep_parents', 'int[]'),
('dep_pa... | dd-genomics-master | code/test_nlp.py |
#!/usr/bin/env python
import collections
import os
import sys
import abbreviations
import config
import extractor_util as util
import levenshtein
CACHE = dict() # Cache results of disk I/O
# This defines the Row object that we read in to the extractor
parser = util.RowParser([
('doc_id', 'text'),
... | dd-genomics-master | code/pheno_acronyms_extract_candidates.py |
#!/usr/bin/env python
from collections import namedtuple
import extractor_util as util
import os
import sys
import ddlib
import re
import config
# This defines the Row object that we read in to the extractor
parser = util.RowParser([
('doc_id', 'text'),
('section_id', 'text'),
('sent_id',... | dd-genomics-master | code/pheno_acronyms_extract_features.py |
#!/usr/bin/env python
from collections import namedtuple
import extractor_util as util
import ddlib
import re
# This defines the Row object that we read in to the extractor
parser = util.RowParser([
('doc_id', 'text'),
('section_id', 'text'),
('sent_id', 'int'),
('words', 'text[... | dd-genomics-master | code/gene_extract_features.py |
#!/usr/bin/env python
import collections
import extractor_util as util
import data_util as dutil
import dep_util as deps
import os
import random
import re
import sys
import config
# This defines the Row object that we read in to the extractor
parser = util.RowParser([
('doc_id', 'text'),
('section... | dd-genomics-master | code/variantpheno_extract_candidates.py |
#! /usr/bin/env python
#
# This file contains the generic features library that is included with ddlib.
#
# The three functions that a user should want to use are load_dictionary,
# get_generic_features_mention, and get_generic_features_relation.
# All the rest should be considered more or less private, except perhaps ... | dd-genomics-master | code/ddlib/gen_feats.py |
from collections import namedtuple,OrderedDict
import re
import sys
from inspect import isgeneratorfunction,getargspec
import csv
from StringIO import StringIO
def print_error(err_string):
"""Function to write to stderr"""
sys.stderr.write("ERROR[UDF]: " + str(err_string) + "\n")
BOOL_PARSER = {
't' : True,
... | dd-genomics-master | code/ddlib/util.py |
from dd import *
from gen_feats import *
from util import *
| dd-genomics-master | code/ddlib/__init__.py |
import sys
import collections
Word = collections.namedtuple('Word', ['begin_char_offset', 'end_char_offset', 'word', 'lemma', 'pos', 'ner', 'dep_par', 'dep_label'])
Span = collections.namedtuple('Span', ['begin_word_id', 'length'])
Sequence = collections.namedtuple('Sequence', ['is_inversed', 'elements'])
DepEdge = co... | dd-genomics-master | code/ddlib/dd.py |
import dependencies
import sys
def index_of_sublist(subl, l):
for i in range(len(l) - len(subl) + 1):
if subl == l[i:i + len(subl)]:
return i
def intersects(a1, a2):
for i in a1:
if i in a2:
return True
return False
def acyclic(a):
return len(a) == len(set(a))
... | dd-genomics-master | code/util/clf_util.py |
######################################################################################
# LATTICE - MEMEX plugins for latticelib
#
# latticelib is an extraction framework to allow quickly building extractors by
# specifying minimal target-specific code (candidate generation patterns and
# supervision rules). It has ... | dd-genomics-master | code/util/memex.py |
dd-genomics-master | code/util/__init__.py | |
#! /usr/bin/python -m trace --trace --file /dev/stderr
######################################################################################
# LATTICE - Util functions for working with dependencies
#
# Usage:
# Start by preparing a list of dep_patterns, eg. "he <-nsubj- buy"
#
# sentence is an object that con... | dd-genomics-master | code/util/dependencies.py |
dd-genomics-master | code/dep_alignment/__init__.py | |
#! /usr/bin/env python
def rc_to_match_tree(mixin, sent, cands, node, children, rv=None):
if rv is None:
rv = []
assert False, "TODO this method unfolds DAGS into trees, don't use it or fix it first"
mc = MatchCell(1)
rv.append(mc)
index = len(rv)
for i, cand in enumerate(cands):
if node == cand:
... | dd-genomics-master | code/dep_alignment/alignment_util.py |
#! /usr/bin/env python
import numpy as np
from alignment_util import AlignmentMixin, MatchCell
import sys
import copy
class MultiDepAlignment(AlignmentMixin):
word_match_score = 5
dict_match_score = 5
lemma_match_score = 5
pos_tag_match_score = -4
skip_score = -3
mismatch_score = -5
cand_match_score = ... | dd-genomics-master | code/dep_alignment/multi_dep_alignment.py |
#! /usr/bin/env python
import sys
import glob
import os
if __name__ == "__main__":
num = 0
if len(sys.argv) != 2:
print >>sys.stderr, 'Expecting list of folder names (without preceding numbers) in file as argument'
sys.exit(1)
with open(sys.argv[1]) as f:
for line in f:
assert num <= 99, 'Cann... | dd-genomics-master | snapshot-template/gill-reduced/number_folders.py |
#! /usr/bin/env python
import sys
import re
for line in sys.stdin:
print re.sub(r'\W+', ' ', line.strip())
| dd-genomics-master | onto/replace_non_alpha.py |
#! /usr/bin/env python
from xml.etree.ElementTree import ElementTree
import sys
import re
def attach_diseases(diseases, excludes):
excludes = [set(d.strip().split()) for d in excludes]
for line in diseases.split('\n'):
names = line.strip().split(';')
for name in names:
# if 'GLOMERULOSCLEROSIS' in n... | dd-genomics-master | onto/parse_diseases.py |
#! /usr/bin/env python
import sys
def main():
fname = sys.argv[1]
transcript = None
with open(fname) as f:
for line in f:
if line.startswith('>'):
if transcript:
print '%s\t{%s}' % (transcript, ','.join(sequence))
transcript = line.strip()[1:].split()[0].split('_')[2]
... | dd-genomics-master | onto/geneIsoformsToTable.py |
#! /usr/bin/env python
import sys
def main():
fname = sys.argv[1]
transcript = None
with open(fname) as f:
for line in f:
if line.startswith('>'):
if transcript:
print '%s\t{%s}' % (transcript, ','.join(sequence))
transcript = line.strip()[1:]
sequence = ''
c... | dd-genomics-master | onto/proteinIsoformsToTable.py |
import sys
import re
disease_to_hpos = {}
with open('data/hpo_disease_phenotypes.tsv', 'rb') as f:
for line in f.readlines():
source, source_id, name, name2, hpos = line.strip().split('\t')
if source == "OMIM":
disease_to_hpos[source_id] = hpos.split("|")
with open('raw/clinvar.tsv', 'rb') as f:
for... | dd-genomics-master | onto/join_clinvar_omim_hpo.py |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
A constant-space parser for the GeneOntology OBO v1.2 format
Version 1.0
"""
from collections import defaultdict
__author__ = "Uli Koehler"
__copyright__ = "Copyright 2013 Uli Koehler"
__license__ = "Apache v2.0"
def processGOTerm(goTerm):
"""
In an obje... | dd-genomics-master | onto/obo_parser.py |
#! /usr/bin/env python
import os
APP_HOME = os.environ['GDD_HOME']
import sys
sys.path.append('%s/code' % APP_HOME)
import data_util as dutil
### ATTENTION!!!! PLEASE PIPE THE OUTPUT OF THIS SCRIPT THROUGH sort | uniq !!! ###
### Doing it within python is a waste of resources. Linux does it much faster. ###
def ge... | dd-genomics-master | onto/load_hpo_abnormalities.py |
#! /usr/bin/env python
import sys
if len(sys.argv) != 4:
print >> sys.stderr, "usage: ./blah diseases_file ps_file ps_to_omim_file"
sys.exit(1)
diseases_filename = sys.argv[1]
ps_filename = sys.argv[2]
ps_to_omim_filename = sys.argv[3]
omim_to_ps = {}
ps_alt_names = {}
with open(ps_to_omim_filename) as f:
f... | dd-genomics-master | onto/omim_alt_names_to_series.py |
#! /usr/bin/env python
import os
APP_HOME = os.environ['GDD_HOME']
import sys
sys.path.append('%s/code' % APP_HOME)
import data_util as dutil
import argparse
### ATTENTION!!!! PLEASE PIPE THE OUTPUT OF THIS SCRIPT THROUGH sort | uniq !!! ###
### Doing it within python is a waste of resources. Linux does it much faste... | dd-genomics-master | onto/canonicalize_gene_phenotype.py |
"""
Output fields:
id, name, synonyms, related terms, alt IDs, parent, MeSh terms
"""
import argparse
from obo_parser import parseGOOBO
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('infile', help='Input HPO file in OBO v1.2 format.')
parser.add_argument('outfile', hel... | dd-genomics-master | onto/parse_hpo.py |
#!/usr/bin/env python
import sys
import re
import os
#from nltk.stem.snowball import SnowballStemmer
#from nltk.stem import PorterStemmer
from nltk.stem import WordNetLemmatizer
GDD_HOME = os.environ['GDD_HOME']
# [Alex 4/12/15]:
# This script is for preprocessing a dictionary of phenotype phrase - HPO code pairs to b... | dd-genomics-master | onto/prep_pheno_terms.py |
#! /usr/bin/env python
import fileinput
import sys
def getDigits(text):
c = ''
for i in text:
if i.isdigit():
c += i
if len(c) > 0:
return int(c)
return -1
if __name__ == "__main__":
for line in fileinput.input():
comps = line.strip().split('\t')
if len(comps) == 0:
continue
... | dd-genomics-master | parser/md_cleanup.py |
import json
import os
import re
import lxml.etree as et
class XMLTree:
"""
A generic tree representation which takes XML as input
Includes subroutines for conversion to JSON & for visualization based on js form
"""
def __init__(self, xml_root):
"""Calls subroutines to generate JSON form of XML input"""
... | dd-genomics-master | dsr/tree_structs.py |
from collections import namedtuple
import re
def read_ptsv_element(x):
"""
Parse an element in psql-compatible tsv format, i.e. {-format arrays
Takes a string as input, handles float, int, str vals, and arrays of these types
"""
if len(x) == 0:
return None
if x[0] == '{':
return map(read_ptsv_eleme... | dd-genomics-master | dsr/treedlib_util.py |
from IPython.core.display import display_html, HTML, display_javascript, Javascript
import json
import os
import re
import lxml.etree as et
class XMLTree:
"""
A generic tree representation which takes XML as input
Includes subroutines for conversion to JSON & for visualization based on js form
"""
def __init... | dd-genomics-master | dsr/tree_structs_ipynb.py |
#! /usr/bin/python
# -*- coding: utf-8 -*-
import json
import sys
from nltk.stem import WordNetLemmatizer
import re
from nltk.corpus import stopwords
def load_gene_name_to_genes(ensembl_genes_path):
ret = {}
with open(ensembl_genes_path) as f:
for line in f:
eid = line.strip().split(':')[0]
canoni... | dd-genomics-master | document_classifier/classification/lemmatize_gpv_stdin.py |
#! /usr/bin/python
# -*- coding: utf-8 -*-
import json
import sys
from nltk.stem import WordNetLemmatizer
import re
from nltk.corpus import stopwords
def load_gene_name_to_genes(ensembl_genes_path):
ret = {}
with open(ensembl_genes_path) as f:
for line in f:
eid = line.strip().split(':')[0]
canoni... | dd-genomics-master | document_classifier/classification/lemmatize_gpv.py |
#! /usr/bin/python
# -*- coding: utf-8 -*-
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
import sys
from bunch import *
import numpy as np
import random
from sklearn.linear_model import LogisticRegression
from nltk.stem import WordNetLemmatizer... | dd-genomics-master | document_classifier/classification/classify.py |
#! /usr/bin/env python
import sys
if __name__ == "__main__":
cur_pmid = -1
cur_str = ''
for line in sys.stdin:
comps = line.strip().split('\t')
pmid = int(comps[0])
if pmid == cur_pmid:
cur_str += ' '
cur_str += comps[1]
else:
if cur_pmid != -1:
print "%s\t%s" % (cur_pm... | dd-genomics-master | document_classifier/classification/merge_lines.py |
#!/usr/bin/env python
from collections import defaultdict, namedtuple
import sys
import re
import os
import random
from itertools import chain
import extractor_util as util
import data_util as dutil
import config
# This defines the Row object that we read in to the extractor
parser = util.RowParser([
('doc_... | dd-genomics-master | document_classifier/classification/pheno_extract_candidates.py |
#! /usr/bin/python
# -*- coding: utf-8 -*-
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
import sys
from bunch import *
import numpy as np
import random
from sklearn.linear_model import LogisticRegression
from nltk.stem import WordNetLemmatizer... | dd-genomics-master | document_classifier/classification/create_classifier.py |
#! /usr/bin/python
# -*- coding: utf-8 -*-
import json
import sys
import re
if __name__ == "__main__":
if len(sys.argv) != 2:
print >>sys.stderr, "need 2 args: symbol for file (NOT used for stdin), output path"
sys.exit(1)
pubmed = sys.argv[1]
out_path = sys.argv[2]
gene_rgx = comp_gene_rgxs(ensembl_g... | dd-genomics-master | document_classifier/classification/json_to_tsv.py |
#! /usr/bin/python
# -*- coding: utf-8 -*-
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
import sys
from bunch import *
import numpy as np
import random
from sklearn.naive_bayes import MultinomialNB
from sklearn.linear_model import LogisticRegr... | dd-genomics-master | document_classifier/classification/word_counter.py |
#! /usr/bin/python
# -*- coding: utf-8 -*-
import word_counter
import sys
import re
from bunch import *
import numpy as np
import random
from nltk.stem import WordNetLemmatizer
from nltk.corpus import stopwords
from functools32 import lru_cache
from nltk.stem import PorterStemmer
def toBunch(mmap):
rv = Bunch()
r... | dd-genomics-master | document_classifier/classification/preprocess_test_data.py |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import json
import sys
import re
def load_unlabeled_docs(data_path):
rv = {}
print >>sys.stderr, "Loading JSON data"
ctr = -1
with open(data_path) as f:
for line in f:
ctr += 1
if ctr % 100000 == 0:
print >>sys.stderr, "counting %d lines" ... | dd-genomics-master | document_classifier/classification/joined_data/json_to_tsv.py |
#! /usr/bin/env python
import sys
import re
if __name__ == "__main__":
no_alnum = re.compile(r'[\W_]+')
with open(sys.argv[2], 'w') as out_file:
with open(sys.argv[1]) as f:
for line in f:
comps = line.strip().split('\t')
pmid = comps[0]
journal = comps[1]
mesh_terms_stri... | dd-genomics-master | document_classifier/classification/processed/genomics_dump_to_processed.py |
"""Assess phenotype recall relative to known HPO-PMID map."""
import collections
import random
import sys
sys.path.append('../code')
import extractor_util as util
import data_util as dutil
NUM_ERRORS_TO_SAMPLE = 50
def main(id_file, candidate_file):
# Load list of all pubmed IDs in the dataset
print >> sys.stder... | dd-genomics-master | eval/pheno_recall.py |
import collections
import random
import sys
sys.path.append('../code')
import extractor_util as util
import data_util as dutil
HPO_DAG = dutil.read_hpo_dag()
def read_supervision():
"""Reads genepheno supervision data (from charite)."""
supervision_pairs = set()
with open('%s/onto/data/hpo_phenotype_genes.tsv'... | dd-genomics-master | eval/omim_coverage.py |
#! /usr/bin/env python
'''
Created on Aug 3, 2015
@author: jbirgmei
'''
import abbreviations
if __name__ == '__main__':
sentence = 'Scaffold proteins are abundant and essential components of the postsynaptic density -LRB- PSD -RRB- as well as I Hate JavaScript Proteins -LRB- IHJSP -RRB- , and a completely unrelat... | dd-genomics-master | archived/test-abbreviations.py |
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