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PMBio/limix-backup | limix/mtSet/core/preprocessCore.py | computePCsPlink | def computePCsPlink(plink_path,k,out_dir,bfile,ffile):
"""
computing the covariance matrix via plink
"""
print("Using plink to compute principal components")
cmd = '%s --bfile %s --pca %d '%(plink_path,bfile,k)
cmd+= '--out %s'%(os.path.join(out_dir,'plink'))
subprocess.call(cmd,shell=True)
... | python | def computePCsPlink(plink_path,k,out_dir,bfile,ffile):
"""
computing the covariance matrix via plink
"""
print("Using plink to compute principal components")
cmd = '%s --bfile %s --pca %d '%(plink_path,bfile,k)
cmd+= '--out %s'%(os.path.join(out_dir,'plink'))
subprocess.call(cmd,shell=True)
... | [
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PMBio/limix-backup | limix/mtSet/core/preprocessCore.py | computePCsPython | def computePCsPython(out_dir,k,bfile,ffile):
""" reading in """
RV = plink_reader.readBED(bfile,useMAFencoding=True)
X = np.ascontiguousarray(RV['snps'])
""" normalizing markers """
print('Normalizing SNPs...')
p_ref = X.mean(axis=0)/2.
X -= 2*p_ref
with warnings.catch_warnings():
... | python | def computePCsPython(out_dir,k,bfile,ffile):
""" reading in """
RV = plink_reader.readBED(bfile,useMAFencoding=True)
X = np.ascontiguousarray(RV['snps'])
""" normalizing markers """
print('Normalizing SNPs...')
p_ref = X.mean(axis=0)/2.
X -= 2*p_ref
with warnings.catch_warnings():
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PMBio/limix-backup | limix/mtSet/core/preprocessCore.py | computeCovarianceMatrixPython | def computeCovarianceMatrixPython(out_dir,bfile,cfile,sim_type='RRM'):
print("Using python to create covariance matrix. This might be slow. We recommend using plink instead.")
if sim_type is not 'RRM':
raise Exception('sim_type %s is not known'%sim_type)
""" loading data """
data = plink_reade... | python | def computeCovarianceMatrixPython(out_dir,bfile,cfile,sim_type='RRM'):
print("Using python to create covariance matrix. This might be slow. We recommend using plink instead.")
if sim_type is not 'RRM':
raise Exception('sim_type %s is not known'%sim_type)
""" loading data """
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PMBio/limix-backup | limix/mtSet/core/preprocessCore.py | computePCs | def computePCs(plink_path,k,bfile,ffile):
"""
compute the first k principal components
Input:
k : number of principal components
plink_path : plink path
bfile : binary bed file (bfile.bed, bfile.bim and bfile.fam are required)
ffile : name of output file
... | python | def computePCs(plink_path,k,bfile,ffile):
"""
compute the first k principal components
Input:
k : number of principal components
plink_path : plink path
bfile : binary bed file (bfile.bed, bfile.bim and bfile.fam are required)
ffile : name of output file
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PMBio/limix-backup | limix/mtSet/core/preprocessCore.py | computeCovarianceMatrix | def computeCovarianceMatrix(plink_path,bfile,cfile,sim_type='RRM'):
"""
compute similarity matrix using plink
Input:
plink_path : plink path
bfile : binary bed file (bfile.bed, bfile.bim and bfile.fam are required)
cfile : the covariance matrix will be written to cfile.cov... | python | def computeCovarianceMatrix(plink_path,bfile,cfile,sim_type='RRM'):
"""
compute similarity matrix using plink
Input:
plink_path : plink path
bfile : binary bed file (bfile.bed, bfile.bim and bfile.fam are required)
cfile : the covariance matrix will be written to cfile.cov... | [
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bfile : binary bed file (bfile.bed, bfile.bim and bfile.fam are required)
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PMBio/limix-backup | limix/mtSet/core/preprocessCore.py | eighCovarianceMatrix | def eighCovarianceMatrix(cfile):
"""
compute similarity matrix using plink
Input:
cfile : the covariance matrix will be read from cfile.cov while the eigenvalues and the eigenverctors will
be written to cfile.cov.eval and cfile.cov.evec respectively
"""
# precom... | python | def eighCovarianceMatrix(cfile):
"""
compute similarity matrix using plink
Input:
cfile : the covariance matrix will be read from cfile.cov while the eigenvalues and the eigenverctors will
be written to cfile.cov.eval and cfile.cov.evec respectively
"""
# precom... | [
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PMBio/limix-backup | limix/mtSet/core/preprocessCore.py | fit_null | def fit_null(Y,S_XX,U_XX,nfile,F):
"""
fit null model
Y NxP phenotype matrix
S_XX eigenvalues of the relatedness matrix
U_XX eigen vectors of the relatedness matrix
"""
mtSet = limix.MTSet(Y, S_R=S_XX, U_R=U_XX, F=F)
RV = mtSet.fitNull(cache=False)
params = np.array([RV... | python | def fit_null(Y,S_XX,U_XX,nfile,F):
"""
fit null model
Y NxP phenotype matrix
S_XX eigenvalues of the relatedness matrix
U_XX eigen vectors of the relatedness matrix
"""
mtSet = limix.MTSet(Y, S_R=S_XX, U_R=U_XX, F=F)
RV = mtSet.fitNull(cache=False)
params = np.array([RV... | [
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PMBio/limix-backup | limix/mtSet/core/preprocessCore.py | preprocess | def preprocess(options):
assert options.bfile!=None, 'Please specify a bfile.'
""" computing the covariance matrix """
if options.compute_cov:
assert options.bfile!=None, 'Please specify a bfile.'
assert options.cfile is not None, 'Specify covariance matrix basename'
print('Computing ... | python | def preprocess(options):
assert options.bfile!=None, 'Please specify a bfile.'
""" computing the covariance matrix """
if options.compute_cov:
assert options.bfile!=None, 'Please specify a bfile.'
assert options.cfile is not None, 'Specify covariance matrix basename'
print('Computing ... | [
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bretth/woven | bin/woven-admin.py | copy_helper | def copy_helper(app_or_project, name, directory, dist, template_dir, noadmin):
"""
Replacement for django copy_helper
Copies a Django project layout template into the specified distribution directory
"""
import shutil
if not re.search(r'^[_a-zA-Z]\w*$', name): # If it's not a valid direct... | python | def copy_helper(app_or_project, name, directory, dist, template_dir, noadmin):
"""
Replacement for django copy_helper
Copies a Django project layout template into the specified distribution directory
"""
import shutil
if not re.search(r'^[_a-zA-Z]\w*$', name): # If it's not a valid direct... | [
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bretth/woven | bin/woven-admin.py | start_distribution | def start_distribution(project_name, template_dir, dist, noadmin):
"""
Custom startproject command to override django default
"""
directory = os.getcwd()
# Check that the project_name cannot be imported.
try:
import_module(project_name)
except ImportError:
pass
else:
... | python | def start_distribution(project_name, template_dir, dist, noadmin):
"""
Custom startproject command to override django default
"""
directory = os.getcwd()
# Check that the project_name cannot be imported.
try:
import_module(project_name)
except ImportError:
pass
else:
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PMBio/limix-backup | limix/deprecated/utils/preprocess.py | variance_K | def variance_K(K, verbose=False):
"""estimate the variance explained by K"""
c = SP.sum((SP.eye(len(K)) - (1.0 / len(K)) * SP.ones(K.shape)) * SP.array(K))
scalar = (len(K) - 1) / c
return 1.0/scalar | python | def variance_K(K, verbose=False):
"""estimate the variance explained by K"""
c = SP.sum((SP.eye(len(K)) - (1.0 / len(K)) * SP.ones(K.shape)) * SP.array(K))
scalar = (len(K) - 1) / c
return 1.0/scalar | [
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PMBio/limix-backup | limix/deprecated/utils/preprocess.py | scale_K | def scale_K(K, verbose=False,trace_method=True):
"""scale covariance K such that it explains unit variance
trace_method: standardize to unit trace (deafault: True)
"""
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scalar=1.0/(K.diagonal().mean())
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"""scale covariance K such that it explains unit variance
trace_method: standardize to unit trace (deafault: True)
"""
if trace_method:
scalar=1.0/(K.diagonal().mean())
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PMBio/limix-backup | limix/deprecated/utils/preprocess.py | rankStandardizeNormal | def rankStandardizeNormal(X):
"""
Gaussianize X: [samples x phenotypes]
- each phentoype is converted to ranks and transformed back to normal using the inverse CDF
"""
Is = X.argsort(axis=0)
RV = SP.zeros_like(X)
rank = SP.zeros_like(X)
for i in range(X.shape[1]):
x = X[:,i]
i_nan = SP.isnan(x)
if 0:
... | python | def rankStandardizeNormal(X):
"""
Gaussianize X: [samples x phenotypes]
- each phentoype is converted to ranks and transformed back to normal using the inverse CDF
"""
Is = X.argsort(axis=0)
RV = SP.zeros_like(X)
rank = SP.zeros_like(X)
for i in range(X.shape[1]):
x = X[:,i]
i_nan = SP.isnan(x)
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heuer/cablemap | helpers/fix_subjects.py | _aftenposten_cable_ids | def _aftenposten_cable_ids():
"""\
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See: <http://aebr.home.xs4all.nl/wl/aftenposten/>
"""
s = urllib2.urlopen(_AP_IRI).read()
return set(_WL_CABLE_ID_PATTERN.findall(s)) | python | def _aftenposten_cable_ids():
"""\
Returns a set of cable identifiers of cables published by Aftenposten.
See: <http://aebr.home.xs4all.nl/wl/aftenposten/>
"""
s = urllib2.urlopen(_AP_IRI).read()
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heuer/cablemap | helpers/fix_subjects.py | _russianreporter_cable_ids | def _russianreporter_cable_ids():
"""\
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See <http://aebr.home.xs4all.nl/wl/rusrep/>
"""
s = urllib2.urlopen(_RR_IRI).read()
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"""\
Returns a set of cable identifiers of cables published by Russian Reporter.
See <http://aebr.home.xs4all.nl/wl/rusrep/>
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s = urllib2.urlopen(_RR_IRI).read()
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rjw57/starman | starman/util.py | as_square_array | def as_square_array(arr):
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"""
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if len(arr.shape) != 2 or arr.shape[0] != arr.shape[1]:
raise ValueError("Expected square array")
return arr | python | def as_square_array(arr):
"""Return arr massaged into a square array. Raises ValueError if arr cannot be
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"""
arr = np.atleast_2d(arr)
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""" perform parametric fit of the test statistics and provide permutation and test pvalues """
resdir = options.resdir
out_file = options.outfile
tol = options.tol
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inveniosoftware-contrib/invenio-classifier | invenio_classifier/api.py | output_keywords_for_sources | def output_keywords_for_sources(
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match_mode="full", no_cache=False, with_author_keywords=False,
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**kwargs):
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input_sources, taxonomy_name, output_mode="text",
output_limit=None, spires=False,
match_mode="full", no_cache=False, with_author_keywords=False,
rebuild_cache=False, only_core_tags=False, extract_acronyms=False,
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inveniosoftware-contrib/invenio-classifier | invenio_classifier/api.py | get_keywords_from_local_file | def get_keywords_from_local_file(
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output_limit=None, spires=False,
match_mode="full", no_cache=False, with_author_keywords=False,
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inveniosoftware-contrib/invenio-classifier | invenio_classifier/api.py | get_keywords_from_text | def get_keywords_from_text(text_lines, taxonomy_name, output_mode="text",
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StyXman/ayrton | ayrton/parser/astcompiler/misc.py | dict_to_switch | def dict_to_switch(d):
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jhshi/wltrace | wltrace/dot11.py | mcs_to_rate | def mcs_to_rate(mcs, bw=20, long_gi=True):
"""Convert MCS index to rate in Mbps.
See http://mcsindex.com/
Args:
mcs (int): MCS index
bw (int): bandwidth, 20, 40, 80, ...
long_gi(bool): True if long GI is used.
Returns:
rate (float): bitrate in Mbps
>>> mcs_to_rat... | python | def mcs_to_rate(mcs, bw=20, long_gi=True):
"""Convert MCS index to rate in Mbps.
See http://mcsindex.com/
Args:
mcs (int): MCS index
bw (int): bandwidth, 20, 40, 80, ...
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rate (float): bit rate in Mbps
bw (int): bandwidth, 20, 40, 80, ...
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mcs (int): MCS index
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... | python | def rate_to_mcs(rate, bw=20, long_gi=True):
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rate (float): bit rate in Mbps
bw (int): bandwidth, 20, 40, 80, ...
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inveniosoftware-contrib/invenio-classifier | invenio_classifier/engine.py | extract_abbreviations | def extract_abbreviations(fulltext):
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:param fulltext: utf-8 string
:return: dictionary of matches in a formt {
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inveniosoftware-contrib/invenio-classifier | invenio_classifier/engine.py | extract_author_keywords | def extract_author_keywords(skw_db, ckw_db, fulltext):
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inveniosoftware-contrib/invenio-classifier | invenio_classifier/engine.py | build_marc | def build_marc(recid, single_keywords, composite_keywords,
spires=False, author_keywords=None, acronyms=None):
"""Create xml record.
:var recid: integer
:var single_keywords: dictionary of kws
:var composite_keywords: dictionary of kws
:keyword spires: please don't use, left for hist... | python | def build_marc(recid, single_keywords, composite_keywords,
spires=False, author_keywords=None, acronyms=None):
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:var recid: integer
:var single_keywords: dictionary of kws
:var composite_keywords: dictionary of kws
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inveniosoftware-contrib/invenio-classifier | invenio_classifier/engine.py | _output_marc | def _output_marc(output_complete, categories,
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acro_field=None,
provenience='Classifier'):
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:var skw_matches: list of single keywords
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kw_field=None,
auth_field=None,
acro_field=None,
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inveniosoftware-contrib/invenio-classifier | invenio_classifier/engine.py | _output_text | def _output_text(complete_output, categories):
"""Output the results obtained in text format.
:return: str, html formatted output
"""
output = ""
for result in complete_output:
list_result = complete_output[result]
if list_result:
list_result_sorted = sorted(list_result... | python | def _output_text(complete_output, categories):
"""Output the results obtained in text format.
:return: str, html formatted output
"""
output = ""
for result in complete_output:
list_result = complete_output[result]
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inveniosoftware-contrib/invenio-classifier | invenio_classifier/engine.py | _get_singlekws | def _get_singlekws(skw_matches, spires=False):
"""Get single keywords.
:var skw_matches: dict of {keyword: [info,...]}
:keyword spires: bool, to get the spires output
:return: list of formatted keywords
"""
output = {}
for single_keyword, info in skw_matches:
output[single_keyword.o... | python | def _get_singlekws(skw_matches, spires=False):
"""Get single keywords.
:var skw_matches: dict of {keyword: [info,...]}
:keyword spires: bool, to get the spires output
:return: list of formatted keywords
"""
output = {}
for single_keyword, info in skw_matches:
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inveniosoftware-contrib/invenio-classifier | invenio_classifier/engine.py | _get_compositekws | def _get_compositekws(ckw_matches, spires=False):
"""Get composite keywords.
:var ckw_matches: dict of {keyword: [info,...]}
:keyword spires: bool, to get the spires output
:return: list of formatted keywords
"""
output = {}
for composite_keyword, info in ckw_matches:
output[composi... | python | def _get_compositekws(ckw_matches, spires=False):
"""Get composite keywords.
:var ckw_matches: dict of {keyword: [info,...]}
:keyword spires: bool, to get the spires output
:return: list of formatted keywords
"""
output = {}
for composite_keyword, info in ckw_matches:
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inveniosoftware-contrib/invenio-classifier | invenio_classifier/engine.py | _get_acronyms | def _get_acronyms(acronyms):
"""Return a formatted list of acronyms."""
acronyms_str = {}
if acronyms:
for acronym, expansions in iteritems(acronyms):
expansions_str = ", ".join(["%s (%d)" % expansion
for expansion in expansions])
acron... | python | def _get_acronyms(acronyms):
"""Return a formatted list of acronyms."""
acronyms_str = {}
if acronyms:
for acronym, expansions in iteritems(acronyms):
expansions_str = ", ".join(["%s (%d)" % expansion
for expansion in expansions])
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inveniosoftware-contrib/invenio-classifier | invenio_classifier/engine.py | _get_fieldcodes | def _get_fieldcodes(skw_matches, ckw_matches, spires=False):
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:var skw_matches: dict of {keyword: [info,...]}
:var ckw_matches: dict of {keyword: [info,...]}
:keyword spires: bool, to get the spires output
:return: list of tuples with (fieldcodes, keywords)
... | python | def _get_fieldcodes(skw_matches, ckw_matches, spires=False):
"""Return the output for the field codes.
:var skw_matches: dict of {keyword: [info,...]}
:var ckw_matches: dict of {keyword: [info,...]}
:keyword spires: bool, to get the spires output
:return: list of tuples with (fieldcodes, keywords)
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inveniosoftware-contrib/invenio-classifier | invenio_classifier/engine.py | _get_core_keywords | def _get_core_keywords(skw_matches, ckw_matches, spires=False):
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:var skw_matches: dict of {keyword: [info,...]}
:var ckw_matches: dict of {keyword: [info,...]}
:keyword spires: bool, to get the spires output
:return: list of formatted core keywords
"""
... | python | def _get_core_keywords(skw_matches, ckw_matches, spires=False):
"""Return the output for the field codes.
:var skw_matches: dict of {keyword: [info,...]}
:var ckw_matches: dict of {keyword: [info,...]}
:keyword spires: bool, to get the spires output
:return: list of formatted core keywords
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inveniosoftware-contrib/invenio-classifier | invenio_classifier/engine.py | filter_core_keywords | def filter_core_keywords(keywords):
"""Only return keywords that are CORE."""
matches = {}
for kw, info in keywords.items():
if kw.core:
matches[kw] = info
return matches | python | def filter_core_keywords(keywords):
"""Only return keywords that are CORE."""
matches = {}
for kw, info in keywords.items():
if kw.core:
matches[kw] = info
return matches | [
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inveniosoftware-contrib/invenio-classifier | invenio_classifier/engine.py | clean_before_output | def clean_before_output(kw_matches):
"""Return a clean copy of the keywords data structure.
Stripped off the standalone and other unwanted elements.
"""
filtered_kw_matches = {}
for kw_match, info in iteritems(kw_matches):
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"""Return a clean copy of the keywords data structure.
Stripped off the standalone and other unwanted elements.
"""
filtered_kw_matches = {}
for kw_match, info in iteritems(kw_matches):
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inveniosoftware-contrib/invenio-classifier | invenio_classifier/engine.py | _skw_matches_comparator | def _skw_matches_comparator(kw0, kw1):
"""Compare 2 single keywords objects.
First by the number of their spans (ie. how many times they were found),
if it is equal it compares them by lenghts of their labels.
"""
def compare(a, b):
return (a > b) - (a < b)
list_comparison = compare(le... | python | def _skw_matches_comparator(kw0, kw1):
"""Compare 2 single keywords objects.
First by the number of their spans (ie. how many times they were found),
if it is equal it compares them by lenghts of their labels.
"""
def compare(a, b):
return (a > b) - (a < b)
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inveniosoftware-contrib/invenio-classifier | invenio_classifier/engine.py | _kw | def _kw(keywords):
"""Turn list of keywords into dictionary."""
r = {}
for k, v in keywords:
r[k] = v
return r | python | def _kw(keywords):
"""Turn list of keywords into dictionary."""
r = {}
for k, v in keywords:
r[k] = v
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inveniosoftware-contrib/invenio-classifier | invenio_classifier/engine.py | _sort_kw_matches | def _sort_kw_matches(skw_matches, limit=0):
"""Return a resized version of keywords to the given length."""
sorted_keywords = list(skw_matches.items())
sorted(sorted_keywords, key=cmp_to_key(_skw_matches_comparator))
return limit and sorted_keywords[:limit] or sorted_keywords | python | def _sort_kw_matches(skw_matches, limit=0):
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inveniosoftware-contrib/invenio-classifier | invenio_classifier/engine.py | get_partial_text | def get_partial_text(fulltext):
"""Return a short version of the fulltext used with partial matching mode.
The version is composed of 20% in the beginning and 20% in the middle of
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"""
def _get_index(x):
return int(float(x) / 100 * len(fulltext))
partial_text = [
fullt... | python | def get_partial_text(fulltext):
"""Return a short version of the fulltext used with partial matching mode.
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"""
def _get_index(x):
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inveniosoftware-contrib/invenio-classifier | invenio_classifier/engine.py | save_keywords | def save_keywords(filename, xml):
"""Save keyword XML to filename."""
tmp_dir = os.path.dirname(filename)
if not os.path.isdir(tmp_dir):
os.mkdir(tmp_dir)
file_desc = open(filename, "w")
file_desc.write(xml)
file_desc.close() | python | def save_keywords(filename, xml):
"""Save keyword XML to filename."""
tmp_dir = os.path.dirname(filename)
if not os.path.isdir(tmp_dir):
os.mkdir(tmp_dir)
file_desc = open(filename, "w")
file_desc.write(xml)
file_desc.close() | [
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inveniosoftware-contrib/invenio-classifier | invenio_classifier/engine.py | _parse_marc_code | def _parse_marc_code(field):
"""Parse marc field and return default indicators if not filled in."""
field = str(field)
if len(field) < 4:
raise Exception('Wrong field code: %s' % field)
else:
field += '__'
tag = field[0:3]
ind1 = field[3].replace('_', '')
ind2 = field[4].repl... | python | def _parse_marc_code(field):
"""Parse marc field and return default indicators if not filled in."""
field = str(field)
if len(field) < 4:
raise Exception('Wrong field code: %s' % field)
else:
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StyXman/ayrton | ayrton/__init__.py | run_tree | def run_tree (tree, g, l):
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runner= Ayrton (g=g, l=l)
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StyXman/ayrton | ayrton/__init__.py | run_file_or_script | def run_file_or_script (script=None, file_name='script_from_command_line',
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rjw57/starman | starman/kalman.py | KalmanFilter.clone | def clone(self):
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rjw57/starman | starman/kalman.py | KalmanFilter.truncate | def truncate(self, new_count):
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alexandrovteam/cpyMSpec | cpyMSpec/spectrum.py | isotopePattern | def isotopePattern(sum_formula, threshold=1e-4, rel_threshold=True, desired_prob=None):
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alexandrovteam/cpyMSpec | cpyMSpec/spectrum.py | SpectrumBase.masses | def masses(self):
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return list(buf) | python | def masses(self):
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alexandrovteam/cpyMSpec | cpyMSpec/spectrum.py | SpectrumBase.trim | def trim(self, n_peaks):
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alexandrovteam/cpyMSpec | cpyMSpec/spectrum.py | ProfileSpectrum.centroids | def centroids(self, window_size=5):
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alexandrovteam/cpyMSpec | cpyMSpec/spectrum.py | TheoreticalSpectrum.centroids | def centroids(self, instrument, min_abundance=1e-4, points_per_fwhm=25):
"""
Estimates centroided peaks for a given instrument model.
:param instrument: instrument model
:param min_abundance: minimum abundance for including a peak
:param points_per_fwhm: grid density used for en... | python | def centroids(self, instrument, min_abundance=1e-4, points_per_fwhm=25):
"""
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alexandrovteam/cpyMSpec | cpyMSpec/spectrum.py | TheoreticalSpectrum.envelope | def envelope(self, instrument):
"""
Computes isotopic envelope for a given instrument model
:param instrument: instrument model to use
:returns: isotopic envelope as a function of mass
:rtype: function float(mz: float)
"""
def envelopeFunc(mz):
if is... | python | def envelope(self, instrument):
"""
Computes isotopic envelope for a given instrument model
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:rtype: function float(mz: float)
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alexandrovteam/cpyMSpec | cpyMSpec/spectrum.py | CentroidedSpectrum.charged | def charged(self, charge):
"""
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:param charge: number of electrons to add
:type charge: integer
:returns: a spectrum with appropriately shifted masses
:rtype: CentroidedSpectrum
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result = self.copy()
... | python | def charged(self, charge):
"""
Adds/subtracts electrons and returns a new object.
:param charge: number of electrons to add
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:returns: a spectrum with appropriately shifted masses
:rtype: CentroidedSpectrum
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alexandrovteam/cpyMSpec | cpyMSpec/spectrum.py | CentroidedSpectrum.trimmed | def trimmed(self, n_peaks):
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:rtype: CentroidedSpectrum
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fitnr/twitter_bot_utils | twitter_bot_utils/archive.py | read_csv | def read_csv(directory):
'''
Scrape a twitter archive csv, yielding tweet text.
Args:
directory (str): CSV file or (directory containing tweets.csv).
field (str): Field with the tweet's text (default: text).
fieldnames (list): The column names for a csv with no header. Must contain ... | python | def read_csv(directory):
'''
Scrape a twitter archive csv, yielding tweet text.
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directory (str): CSV file or (directory containing tweets.csv).
field (str): Field with the tweet's text (default: text).
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fitnr/twitter_bot_utils | twitter_bot_utils/archive.py | read_json | def read_json(directory, data_files='data/js/tweets/*.js'):
'''
Scrape a twitter archive file.
Inspiration from https://github.com/mshea/Parse-Twitter-Archive
'''
files = path.join(directory, data_files)
for fname in iglob(files):
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# Twitter's JSON... | python | def read_json(directory, data_files='data/js/tweets/*.js'):
'''
Scrape a twitter archive file.
Inspiration from https://github.com/mshea/Parse-Twitter-Archive
'''
files = path.join(directory, data_files)
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KelSolaar/Foundations | foundations/namespace.py | set_namespace | def set_namespace(namespace, attribute, namespace_splitter=NAMESPACE_SPLITTER):
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Sets given namespace to given attribute.
Usage::
>>> set_namespace("parent", "child")
u'parent|child'
:param namespace: Namespace.
:type namespace: unicode
:param attribute: Attribute.
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"""
Sets given namespace to given attribute.
Usage::
>>> set_namespace("parent", "child")
u'parent|child'
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KelSolaar/Foundations | foundations/namespace.py | get_namespace | def get_namespace(attribute, namespace_splitter=NAMESPACE_SPLITTER, root_only=False):
"""
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Usage::
>>> get_namespace("grandParent|parent|child")
u'grandParent|parent'
>>> get_namespace("grandParent|parent|child", root_only=True)
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"""
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Usage::
>>> get_namespace("grandParent|parent|child")
u'grandParent|parent'
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KelSolaar/Foundations | foundations/namespace.py | remove_namespace | def remove_namespace(attribute, namespace_splitter=NAMESPACE_SPLITTER, root_only=False):
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>>> remove_namespace("grandParent|parent|child")
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TAPPGuild/sqlalchemy-models | sqlalchemy_models/wallet.py | Balance.load_commodities | def load_commodities(self):
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Load the commodities for Amounts in this object.
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self.available = Amount("{0:.8f} {1}".format(self.available.to_double(), self.currency))
else:
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"""
Load the commodities for Amounts in this object.
"""
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else:
self.fee = Amount("{0:.8f} {1}".format(self.fee, self.c... | python | def load_commodities(self):
"""
Load the commodities for Amounts in this object.
"""
if isinstance(self.fee, Amount):
self.fee = Amount("{0:.8f} {1}".format(self.fee.to_double(), self.currency))
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KelSolaar/Foundations | foundations/ui/common.py | center_widget_on_screen | def center_widget_on_screen(widget, screen=None):
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:type widget: QWidget
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:type screen: int
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:rtype: bool
"""
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Centers given Widget on the screen.
:param widget: Current Widget.
:type widget: QWidget
:param screen: Screen used for centering.
:type screen: int
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KelSolaar/Foundations | foundations/ui/common.py | QWidget_factory | def QWidget_factory(ui_file=None, *args, **kwargs):
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:type ui_file: unicode
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:type \*args: \*
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nirum-lang/nirum-python | nirum/deserialize.py | is_support_abstract_type | def is_support_abstract_type(t):
"""FIXME: 3.5 only"""
if hasattr(t, '__origin__') and t.__origin__:
data_type = t.__origin__
else:
data_type = t
abstract_types = {
typing.Sequence,
typing.List,
typing.Set,
typing.AbstractSet,
typing.Mapping,
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"""FIXME: 3.5 only"""
if hasattr(t, '__origin__') and t.__origin__:
data_type = t.__origin__
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data_type = t
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theonion/djes | djes/utils/query.py | batched_queryset | def batched_queryset(queryset, chunksize=1000):
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Iterate over a Django Queryset ordered by the primary key
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Iterate over a Django Queryset ordered by the primary key
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deeplook/vbbvg | vbbvg/vbbvg.py | load_data | def load_data(verbose=False):
"Load all VBB stop names and IDs into a Pandas dataframe."
df = pd.read_csv(STOPS_PATH, usecols=['stop_id', 'stop_name'])
if verbose:
print('- Loaded %d entries from "%s".' % (len(df), STOPS_PATH))
return df | python | def load_data(verbose=False):
"Load all VBB stop names and IDs into a Pandas dataframe."
df = pd.read_csv(STOPS_PATH, usecols=['stop_id', 'stop_name'])
if verbose:
print('- Loaded %d entries from "%s".' % (len(df), STOPS_PATH))
return df | [
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deeplook/vbbvg | vbbvg/vbbvg.py | filter_data | def filter_data(df, filter_name, verbose=False):
"Filter certain entries with given name."
# pick only entries ending with 'Berlin' in column stop_name, incl. '(Berlin)'
# df = df[df.stop_name.apply(lambda cell: 'Berlin' in cell)]
df = df[df.stop_name.apply(
lambda cell: filter_name.encode('ut... | python | def filter_data(df, filter_name, verbose=False):
"Filter certain entries with given name."
# pick only entries ending with 'Berlin' in column stop_name, incl. '(Berlin)'
# df = df[df.stop_name.apply(lambda cell: 'Berlin' in cell)]
df = df[df.stop_name.apply(
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deeplook/vbbvg | vbbvg/vbbvg.py | get_name_id_interactive | def get_name_id_interactive(stop, df):
"""
Return VBB/BVG ID for given stop name in given table.
Enter interactive dialog when result is not unique.
"""
# this is very fast, but searching in a list of ca. 2900 tuples might be also
# fast enough, and that would mean removing some repeated prepr... | python | def get_name_id_interactive(stop, df):
"""
Return VBB/BVG ID for given stop name in given table.
Enter interactive dialog when result is not unique.
"""
# this is very fast, but searching in a list of ca. 2900 tuples might be also
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deeplook/vbbvg | vbbvg/vbbvg.py | wait_time | def wait_time(departure, now=None):
"""
Calculate waiting time until the next departure time in 'HH:MM' format.
Return time-delta (as 'MM:SS') from now until next departure time in the
future ('HH:MM') given as (year, month, day, hour, minute, seconds).
Time-deltas shorter than 60 seconds are red... | python | def wait_time(departure, now=None):
"""
Calculate waiting time until the next departure time in 'HH:MM' format.
Return time-delta (as 'MM:SS') from now until next departure time in the
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deeplook/vbbvg | vbbvg/vbbvg.py | get_next_departures | def get_next_departures(stop, filter_line=None, num_line_groups=1, verbose=False):
"""
Get all real-time departure times for given stop and return as filtered table.
Terminate if we can assume there is no connection to the internet.
"""
# Get departures table from online service
# (great: we ... | python | def get_next_departures(stop, filter_line=None, num_line_groups=1, verbose=False):
"""
Get all real-time departure times for given stop and return as filtered table.
Terminate if we can assume there is no connection to the internet.
"""
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deeplook/vbbvg | vbbvg/vbbvg.py | show_header | def show_header(**header):
"Display a HTTP-style header on the command-line."
print('%s: %s' % ('Now', header['now']))
print('%s: %s' % ('Stop-Name', header['name']))
print('%s: %s' % ('Stop-ID', header.get('id', None)))
print('') | python | def show_header(**header):
"Display a HTTP-style header on the command-line."
print('%s: %s' % ('Now', header['now']))
print('%s: %s' % ('Stop-Name', header['name']))
print('%s: %s' % ('Stop-ID', header.get('id', None)))
print('') | [
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deeplook/vbbvg | vbbvg/vbbvg.py | show_table | def show_table(args):
"Output table on standard out."
df = load_data(verbose=args.verbose)
df = filter_data(df, filter_name=args.filter_name, verbose=args.verbose)
stop = re.sub(' +', ' ', args.stop)
if re.match('^\d+$', stop.decode('utf-8')):
_id = stop
name = df[df.stop_id==int(_... | python | def show_table(args):
"Output table on standard out."
df = load_data(verbose=args.verbose)
df = filter_data(df, filter_name=args.filter_name, verbose=args.verbose)
stop = re.sub(' +', ' ', args.stop)
if re.match('^\d+$', stop.decode('utf-8')):
_id = stop
name = df[df.stop_id==int(_... | [
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idlesign/envbox | envbox/cli.py | show | def show():
"""Show (print out) current environment variables."""
env = get_environment()
for key, val in sorted(env.env.items(), key=lambda item: item[0]):
click.secho('%s = %s' % (key, val)) | python | def show():
"""Show (print out) current environment variables."""
env = get_environment()
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heuer/cablemap | examples/convertgermancablestocsv.py | generate_csv | def generate_csv(src, out):
"""\
Walks through `src` and generates the CSV file `out`
"""
writer = UnicodeWriter(open(out, 'wb'), delimiter=';')
writer.writerow(('Reference ID', 'Created', 'Origin', 'Subject'))
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"""\
Walks through `src` and generates the CSV file `out`
"""
writer = UnicodeWriter(open(out, 'wb'), delimiter=';')
writer.writerow(('Reference ID', 'Created', 'Origin', 'Subject'))
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heuer/cablemap | cablemap.core/cablemap/core/handler.py | handle_cable | def handle_cable(cable, handler, standalone=True):
"""\
Emits event from the provided `cable` to the handler.
`cable`
A cable object.
`handler`
A ICableHandler instance.
`standalone`
Indicates if a `start` and `end` event should be
issued (default: ``True``).
... | python | def handle_cable(cable, handler, standalone=True):
"""\
Emits event from the provided `cable` to the handler.
`cable`
A cable object.
`handler`
A ICableHandler instance.
`standalone`
Indicates if a `start` and `end` event should be
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heuer/cablemap | cablemap.core/cablemap/core/handler.py | handle_cables | def handle_cables(cables, handler):
"""\
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issues a ``handler.end()`` event.
`cables`
An iterable of Cable objects.
`handler`
The `ICableHandler` instance which should receive the events.
"""
handler.start()
... | python | def handle_cables(cables, handler):
"""\
Issues one ``handler.start()`` event, processes all `cables` and
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`cables`
An iterable of Cable objects.
`handler`
The `ICableHandler` instance which should receive the events.
"""
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peterldowns/djoauth2 | djoauth2/authorization.py | make_authorization_endpoint | def make_authorization_endpoint(missing_redirect_uri,
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""" Returns a endpoint that handles OAuth authorization requests.
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peterldowns/djoauth2 | djoauth2/authorization.py | AuthorizationCodeGenerator.validate | def validate(self, request):
""" Check that a Client's authorization request is valid.
If the request is invalid or malformed in any way, raises the appropriate
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each ... | python | def validate(self, request):
""" Check that a Client's authorization request is valid.
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peterldowns/djoauth2 | djoauth2/authorization.py | AuthorizationCodeGenerator.get_request_uri_parameters | def get_request_uri_parameters(self, as_dict=False):
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The query parameters returned by this method **MUST** be included in the
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peterldowns/djoauth2 | djoauth2/authorization.py | AuthorizationCodeGenerator.make_error_redirect | def make_error_redirect(self, authorization_error=None):
""" Return a Django ``HttpResponseRedirect`` describing the request failure.
If the :py:meth:`validate` method raises an error, the authorization
endpoint should return the result of calling this method like so:
>>> auth_code_generator = (
... | python | def make_error_redirect(self, authorization_error=None):
""" Return a Django ``HttpResponseRedirect`` describing the request failure.
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... | [
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peterldowns/djoauth2 | djoauth2/authorization.py | AuthorizationCodeGenerator.make_success_redirect | def make_success_redirect(self):
""" Return a Django ``HttpResponseRedirect`` describing the request success.
The custom authorization endpoint should return the result of this method
when the user grants the Client's authorization request. The request is
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""" Return a Django ``HttpResponseRedirect`` describing the request success.
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StyXman/ayrton | ayrton/parser/error.py | strerror | def strerror(errno):
"""Translate an error code to a message string."""
from pypy.module._codecs.locale import str_decode_locale_surrogateescape
return str_decode_locale_surrogateescape(os.strerror(errno)) | python | def strerror(errno):
"""Translate an error code to a message string."""
from pypy.module._codecs.locale import str_decode_locale_surrogateescape
return str_decode_locale_surrogateescape(os.strerror(errno)) | [
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StyXman/ayrton | ayrton/parser/error.py | oefmt | def oefmt(w_type, valuefmt, *args):
"""Equivalent to OperationError(w_type, space.wrap(valuefmt % args)).
More efficient in the (common) case where the value is not actually
needed. Note that in the py3k branch the exception message will
always be unicode.
Supports the standard %s and %d formats, p... | python | def oefmt(w_type, valuefmt, *args):
"""Equivalent to OperationError(w_type, space.wrap(valuefmt % args)).
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StyXman/ayrton | ayrton/parser/error.py | OperationError.async | def async(self, space):
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return (self.match(space, space.w_SystemExit) or
self.match(space, space.w_KeyboardInterrupt)) | python | def async(self, space):
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StyXman/ayrton | ayrton/parser/error.py | OperationError.errorstr | def errorstr(self, space, use_repr=False):
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# this part NOT_RPYTHON
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w = space.wr... | python | def errorstr(self, space, use_repr=False):
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StyXman/ayrton | ayrton/parser/error.py | OperationError.print_application_traceback | def print_application_traceback(self, space, file=None):
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self.print_app_tb_only(file)
print >> file, self.errorstr(space) | python | def print_application_traceback(self, space, file=None):
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