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acutesoftware/AIKIF | aikif/toolbox/image_tools.py | add_text_to_image | def add_text_to_image(fname, txt, opFilename):
""" convert an image by adding text """
ft = ImageFont.load("T://user//dev//src//python//_AS_LIB//timR24.pil")
#wh = ft.getsize(txt)
print("Adding text ", txt, " to ", fname, " pixels wide to file " , opFilename)
im = Image.open(fname)
draw = ImageD... | python | def add_text_to_image(fname, txt, opFilename):
""" convert an image by adding text """
ft = ImageFont.load("T://user//dev//src//python//_AS_LIB//timR24.pil")
#wh = ft.getsize(txt)
print("Adding text ", txt, " to ", fname, " pixels wide to file " , opFilename)
im = Image.open(fname)
draw = ImageD... | [
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acutesoftware/AIKIF | aikif/toolbox/image_tools.py | add_crosshair_to_image | def add_crosshair_to_image(fname, opFilename):
""" convert an image by adding a cross hair """
im = Image.open(fname)
draw = ImageDraw.Draw(im)
draw.line((0, 0) + im.size, fill=(255, 255, 255))
draw.line((0, im.size[1], im.size[0], 0), fill=(255, 255, 255))
del draw
im.save(opFilename) | python | def add_crosshair_to_image(fname, opFilename):
""" convert an image by adding a cross hair """
im = Image.open(fname)
draw = ImageDraw.Draw(im)
draw.line((0, 0) + im.size, fill=(255, 255, 255))
draw.line((0, im.size[1], im.size[0], 0), fill=(255, 255, 255))
del draw
im.save(opFilename) | [
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acutesoftware/AIKIF | aikif/toolbox/image_tools.py | filter_contour | def filter_contour(imageFile, opFile):
""" convert an image by applying a contour """
im = Image.open(imageFile)
im1 = im.filter(ImageFilter.CONTOUR)
im1.save(opFile) | python | def filter_contour(imageFile, opFile):
""" convert an image by applying a contour """
im = Image.open(imageFile)
im1 = im.filter(ImageFilter.CONTOUR)
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acutesoftware/AIKIF | aikif/toolbox/image_tools.py | get_img_hash | def get_img_hash(image, hash_size = 8):
""" Grayscale and shrink the image in one step """
image = image.resize((hash_size + 1, hash_size), Image.ANTIALIAS, )
pixels = list(image.getdata())
#print('get_img_hash: pixels=', pixels)
# Compare adjacent pixels.
difference = []
for row in range... | python | def get_img_hash(image, hash_size = 8):
""" Grayscale and shrink the image in one step """
image = image.resize((hash_size + 1, hash_size), Image.ANTIALIAS, )
pixels = list(image.getdata())
#print('get_img_hash: pixels=', pixels)
# Compare adjacent pixels.
difference = []
for row in range... | [
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acutesoftware/AIKIF | aikif/toolbox/image_tools.py | load_image | def load_image(fname):
""" read an image from file - PIL doesnt close nicely """
with open(fname, "rb") as f:
i = Image.open(fname)
#i.load()
return i | python | def load_image(fname):
""" read an image from file - PIL doesnt close nicely """
with open(fname, "rb") as f:
i = Image.open(fname)
#i.load()
return i | [
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acutesoftware/AIKIF | aikif/toolbox/image_tools.py | dump_img | def dump_img(fname):
""" output the image as text """
img = Image.open(fname)
width, _ = img.size
txt = ''
pixels = list(img.getdata())
for col in range(width):
txt += str(pixels[col:col+width])
return txt | python | def dump_img(fname):
""" output the image as text """
img = Image.open(fname)
width, _ = img.size
txt = ''
pixels = list(img.getdata())
for col in range(width):
txt += str(pixels[col:col+width])
return txt | [
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mpg-age-bioinformatics/AGEpy | AGEpy/plots.py | NormInt | def NormInt(df,sampleA,sampleB):
"""
Normalizes intensities of a gene in two samples
:param df: dataframe output of GetData()
:param sampleA: column header of sample A
:param sampleB: column header of sample B
:returns: normalized intensities
"""
c1=df[sampleA]
c2=df[sampleB]
... | python | def NormInt(df,sampleA,sampleB):
"""
Normalizes intensities of a gene in two samples
:param df: dataframe output of GetData()
:param sampleA: column header of sample A
:param sampleB: column header of sample B
:returns: normalized intensities
"""
c1=df[sampleA]
c2=df[sampleB]
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Nachtfeuer/pipeline | examples/python/primes/demo/primes.py | is_prime | def is_prime(number):
"""
Testing given number to be a prime.
>>> [n for n in range(100+1) if is_prime(n)]
[2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97]
"""
if number < 2:
return False
if number % 2 == 0:
return number == 2
... | python | def is_prime(number):
"""
Testing given number to be a prime.
>>> [n for n in range(100+1) if is_prime(n)]
[2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97]
"""
if number < 2:
return False
if number % 2 == 0:
return number == 2
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OpenHydrology/floodestimation | floodestimation/analysis.py | QmedAnalysis.qmed_all_methods | def qmed_all_methods(self):
"""
Returns a dict of QMED methods using all available methods.
Available methods are defined in :attr:`qmed_methods`. The returned dict keys contain the method name, e.g.
`amax_record` with value representing the corresponding QMED estimate in m³/s.
... | python | def qmed_all_methods(self):
"""
Returns a dict of QMED methods using all available methods.
Available methods are defined in :attr:`qmed_methods`. The returned dict keys contain the method name, e.g.
`amax_record` with value representing the corresponding QMED estimate in m³/s.
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OpenHydrology/floodestimation | floodestimation/analysis.py | QmedAnalysis._qmed_from_amax_records | def _qmed_from_amax_records(self):
"""
Return QMED estimate based on annual maximum flow records.
:return: QMED in m³/s
:rtype: float
"""
valid_flows = valid_flows_array(self.catchment)
n = len(valid_flows)
if n < 2:
raise InsufficientDataErro... | python | def _qmed_from_amax_records(self):
"""
Return QMED estimate based on annual maximum flow records.
:return: QMED in m³/s
:rtype: float
"""
valid_flows = valid_flows_array(self.catchment)
n = len(valid_flows)
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OpenHydrology/floodestimation | floodestimation/analysis.py | QmedAnalysis._pot_month_counts | def _pot_month_counts(self, pot_dataset):
"""
Return a list of 12 sets. Each sets contains the years included in the POT record period.
:param pot_dataset: POT dataset (records and meta data)
:type pot_dataset: :class:`floodestimation.entities.PotDataset`
"""
periods = p... | python | def _pot_month_counts(self, pot_dataset):
"""
Return a list of 12 sets. Each sets contains the years included in the POT record period.
:param pot_dataset: POT dataset (records and meta data)
:type pot_dataset: :class:`floodestimation.entities.PotDataset`
"""
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OpenHydrology/floodestimation | floodestimation/analysis.py | QmedAnalysis._qmed_from_area | def _qmed_from_area(self):
"""
Return QMED estimate based on catchment area.
TODO: add source of method
:return: QMED in m³/s
:rtype: float
"""
try:
return 1.172 * self.catchment.descriptors.dtm_area ** self._area_exponent() # Area in km²
ex... | python | def _qmed_from_area(self):
"""
Return QMED estimate based on catchment area.
TODO: add source of method
:return: QMED in m³/s
:rtype: float
"""
try:
return 1.172 * self.catchment.descriptors.dtm_area ** self._area_exponent() # Area in km²
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OpenHydrology/floodestimation | floodestimation/analysis.py | QmedAnalysis._qmed_from_descriptors_1999 | def _qmed_from_descriptors_1999(self, as_rural=False):
"""
Return QMED estimation based on FEH catchment descriptors, 1999 methodology.
Methodology source: FEH, Vol. 3, p. 14
:param as_rural: assume catchment is fully rural. Default: false.
:type as_rural: bool
:return:... | python | def _qmed_from_descriptors_1999(self, as_rural=False):
"""
Return QMED estimation based on FEH catchment descriptors, 1999 methodology.
Methodology source: FEH, Vol. 3, p. 14
:param as_rural: assume catchment is fully rural. Default: false.
:type as_rural: bool
:return:... | [
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OpenHydrology/floodestimation | floodestimation/analysis.py | QmedAnalysis._qmed_from_descriptors_2008 | def _qmed_from_descriptors_2008(self, as_rural=False, donor_catchments=None):
"""
Return QMED estimation based on FEH catchment descriptors, 2008 methodology.
Methodology source: Science Report SC050050, p. 36
:param as_rural: assume catchment is fully rural. Default: false.
:t... | python | def _qmed_from_descriptors_2008(self, as_rural=False, donor_catchments=None):
"""
Return QMED estimation based on FEH catchment descriptors, 2008 methodology.
Methodology source: Science Report SC050050, p. 36
:param as_rural: assume catchment is fully rural. Default: false.
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OpenHydrology/floodestimation | floodestimation/analysis.py | QmedAnalysis._pruaf | def _pruaf(self):
"""
Return percentage runoff urban adjustment factor.
Methodology source: eqn. 6, Kjeldsen 2010
"""
return 1 + 0.47 * self.catchment.descriptors.urbext(self.year) \
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:type dist: float
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Generic distance-decaying correlation function
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Methodology source: Kjeldsen, Jones and Morris, 2009, eqs 3 and 10
:param donor_catchments: Catchments to use as donors
:type donor_catchments: list of :class:`Catchment`
... | python | def _vec_b(self, donor_catchments):
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:type catchment: :class:`Catchment`
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Methodology source: Kjelsen, Jones & Morris 2014, eqs 2 and 3
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:type donor_catchments: list of :class:`Catchment`
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:type donor_catchments: list of :class:`Catchment`
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:type donor_catchments: list of :class:`Catchment`
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Return a suitable donor catchment to improve a QMED estimate based on catchment descriptors alone.
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OpenHydrology/floodestimation | floodestimation/analysis.py | GrowthCurveAnalysis._var_and_skew | def _var_and_skew(self, catchments, as_rural=False):
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Calculate L-CV and L-SKEW from a single catchment or a pooled group of catchments.
Methodology source: Science Report SC050050, para. 6.4.1-6.4.2
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OpenHydrology/floodestimation | floodestimation/analysis.py | GrowthCurveAnalysis._l_cv_and_skew | def _l_cv_and_skew(self, catchment):
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Methodology source: Science Report SC050050, para. 6.7.5
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retur... | python | def _l_cv_and_skew(self, catchment):
"""
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OpenHydrology/floodestimation | floodestimation/analysis.py | GrowthCurveAnalysis._l_cv_weight | def _l_cv_weight(self, donor_catchment):
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Methodology source: Science Report SC050050, eqn. 6.18 and 6.22a
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OpenHydrology/floodestimation | floodestimation/analysis.py | GrowthCurveAnalysis._l_skew_weight | def _l_skew_weight(self, donor_catchment):
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OpenHydrology/floodestimation | floodestimation/analysis.py | GrowthCurveAnalysis._growth_curve_single_site | def _growth_curve_single_site(self, distr='glo'):
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"""
Return flood growth curve function based on `amax_records` from a pooling group.
:return: Inverse cumulative distribution function with one parameter `aep` (annual exceedance probability)
:type: :class:`.GrowthCurve... | python | def _growth_curve_pooling_group(self, distr='glo', as_rural=False):
"""
Return flood growth curve function based on `amax_records` from a pooling group.
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Nachtfeuer/pipeline | spline/tools/version.py | VersionsCheck.process | def process(self, document):
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"""Logging versions of required tools."""
content = json.dumps(document)
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"""
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"""Logging version sorted ascending by tool name."""
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"""Registers new events after instance creation
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name (str): The name of the :class:`Event` or
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acutesoftware/AIKIF | aikif/toolbox/image_detection_tools.py | TEST | def TEST(fname):
"""
Test function to step through all functions in
order to try and identify all features on a map
This test function should be placed in a main
section later
"""
#fname = os.path.join(os.getcwd(), '..','..', # os.path.join(os.path.getcwd(), '
m = MapObject(fname, os.p... | python | def TEST(fname):
"""
Test function to step through all functions in
order to try and identify all features on a map
This test function should be placed in a main
section later
"""
#fname = os.path.join(os.getcwd(), '..','..', # os.path.join(os.path.getcwd(), '
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acutesoftware/AIKIF | aikif/dataTools/cls_datatable.py | DataTable.describe_contents | def describe_contents(self):
""" describes various contents of data table """
print('======================================================================')
print(self)
print('Table = ', str(len(self.header)) + ' cols x ' + str(len(self.arr)) + ' rows')
print('HEADER = ', self... | python | def describe_contents(self):
""" describes various contents of data table """
print('======================================================================')
print(self)
print('Table = ', str(len(self.header)) + ' cols x ' + str(len(self.arr)) + ' rows')
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acutesoftware/AIKIF | aikif/dataTools/cls_datatable.py | DataTable.select_where | def select_where(self, where_col_list, where_value_list, col_name=''):
"""
selects rows from the array where col_list == val_list
"""
res = [] # list of rows to be returned
col_ids = [] # ids of the columns to check
#print('select_where : arr = ', len(self.ar... | python | def select_where(self, where_col_list, where_value_list, col_name=''):
"""
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acutesoftware/AIKIF | aikif/dataTools/cls_datatable.py | DataTable.percentile | def percentile(self, lst_data, percent , key=lambda x:x):
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new_list = sorted(lst_data)
#print('new list = ' , new_list)
#n = float(len(lst_data))
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f = math.floor(k)
c = ... | python | def percentile(self, lst_data, percent , key=lambda x:x):
""" calculates the 'num' percentile of the items in the list """
new_list = sorted(lst_data)
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acutesoftware/AIKIF | aikif/dataTools/cls_datatable.py | DataTable.save | def save(self, filename, content):
"""
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with open(filename, "w") as f:
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"""
default is to save a file from list of lines
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acutesoftware/AIKIF | aikif/dataTools/cls_datatable.py | DataTable.save_csv | def save_csv(self, filename, write_header_separately=True):
"""
save the default array as a CSV file
"""
txt = ''
#print("SAVING arr = ", self.arr)
with open(filename, "w") as f:
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"""
save the default array as a CSV file
"""
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#print("SAVING arr = ", self.arr)
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acutesoftware/AIKIF | aikif/dataTools/cls_datatable.py | DataTable.drop | def drop(self, fname):
"""
drop the table, view or delete the file
"""
if self.dataset_type == 'file':
import os
try:
os.remove(fname)
except Exception as ex:
print('cant drop file "' + fname + '" : ' + str(ex)) | python | def drop(self, fname):
"""
drop the table, view or delete the file
"""
if self.dataset_type == 'file':
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try:
os.remove(fname)
except Exception as ex:
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acutesoftware/AIKIF | aikif/dataTools/cls_datatable.py | DataTable.get_col_data_by_name | def get_col_data_by_name(self, col_name, WHERE_Clause=''):
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#print('get_col_data_by_name: col_name = ', col_name, ' WHERE = ', WHERE_Clause)
col_key = self.get_col_by_name(col_name)
if col_key is None:
print('get_col_da... | python | def get_col_data_by_name(self, col_name, WHERE_Clause=''):
""" returns the values of col_name according to where """
#print('get_col_data_by_name: col_name = ', col_name, ' WHERE = ', WHERE_Clause)
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"""
return table in RST format
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num_cols = len(self.header)
col_width = 25
for _ in range(num_cols):
res += ''.join(['=' for _ in range(col_width - 1)]) + ' '
res += '\n'
for c in self.header:
... | python | def format_rst(self):
"""
return table in RST format
"""
res = ''
num_cols = len(self.header)
col_width = 25
for _ in range(num_cols):
res += ''.join(['=' for _ in range(col_width - 1)]) + ' '
res += '\n'
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mpg-age-bioinformatics/AGEpy | AGEpy/homology.py | getHomoloGene | def getHomoloGene(taxfile="build_inputs/taxid_taxname",\
genefile="homologene.data",\
proteinsfile="build_inputs/all_proteins.data",\
proteinsclusterfile="build_inputs/proteins_for_clustering.data",\
baseURL="http://ftp.ncbi.nih.gov/pub/HomoloGene/... | python | def getHomoloGene(taxfile="build_inputs/taxid_taxname",\
genefile="homologene.data",\
proteinsfile="build_inputs/all_proteins.data",\
proteinsclusterfile="build_inputs/proteins_for_clustering.data",\
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mpg-age-bioinformatics/AGEpy | AGEpy/fasta.py | getFasta | def getFasta(opened_file, sequence_name):
"""
Retrieves a sequence from an opened multifasta file
:param opened_file: an opened multifasta file eg. opened_file=open("/path/to/file.fa",'r+')
:param sequence_name: the name of the sequence to be retrieved eg. for '>2 dna:chromosome chromosome:GRCm38:2:1:1... | python | def getFasta(opened_file, sequence_name):
"""
Retrieves a sequence from an opened multifasta file
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mpg-age-bioinformatics/AGEpy | AGEpy/fasta.py | writeFasta | def writeFasta(sequence, sequence_name, output_file):
"""
Writes a fasta sequence into a file.
:param sequence: a string with the sequence to be written
:param sequence_name: name of the the fasta sequence
:param output_file: /path/to/file.fa to be written
:returns: nothing
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"""
Writes a fasta sequence into a file.
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:param sequence_name: name of the the fasta sequence
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"""
Rewrites a specific sequence in a multifasta file while keeping the sequence header.
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acutesoftware/AIKIF | aikif/toolbox/Toolbox.py | Toolbox._get_tool_str | def _get_tool_str(self, tool):
"""
get a string representation of the tool
"""
res = tool['file']
try:
res += '.' + tool['function']
except Exception as ex:
print('Warning - no function defined for tool ' + str(tool))
res += '\n'
r... | python | def _get_tool_str(self, tool):
"""
get a string representation of the tool
"""
res = tool['file']
try:
res += '.' + tool['function']
except Exception as ex:
print('Warning - no function defined for tool ' + str(tool))
res += '\n'
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acutesoftware/AIKIF | aikif/toolbox/Toolbox.py | Toolbox.get_tool_by_name | def get_tool_by_name(self, nme):
"""
get the tool object by name or file
"""
for t in self.lstTools:
if 'name' in t:
if t['name'] == nme:
return t
if 'file' in t:
if t['file'] == nme:
return t... | python | def get_tool_by_name(self, nme):
"""
get the tool object by name or file
"""
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if 'name' in t:
if t['name'] == nme:
return t
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acutesoftware/AIKIF | aikif/toolbox/Toolbox.py | Toolbox.save | def save(self, fname=''):
"""
Save the list of tools to AIKIF core and optionally to local file fname
"""
if fname != '':
with open(fname, 'w') as f:
for t in self.lstTools:
self.verify(t)
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"""
Save the list of tools to AIKIF core and optionally to local file fname
"""
if fname != '':
with open(fname, 'w') as f:
for t in self.lstTools:
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acutesoftware/AIKIF | aikif/toolbox/Toolbox.py | Toolbox.verify | def verify(self, tool):
"""
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"""
if os.path.isfile(tool['file']):
print('Toolbox: program exists = TOK :: ' + tool['file'])
return True
else:
print('Toolbox: program exists = FAIL :: ' + tool['file'])
retu... | python | def verify(self, tool):
"""
check that the tool exists
"""
if os.path.isfile(tool['file']):
print('Toolbox: program exists = TOK :: ' + tool['file'])
return True
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acutesoftware/AIKIF | aikif/toolbox/Toolbox.py | Toolbox.run | def run(self, tool, args, new_import_path=''):
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import the tool and call the function, passing the args.
"""
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#print('APPENDING PATH = ', new_import_path)
sys.path.append(new_import_path)
#if silent == 'N':
prin... | python | def run(self, tool, args, new_import_path=''):
"""
import the tool and call the function, passing the args.
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if new_import_path != '':
#print('APPENDING PATH = ', new_import_path)
sys.path.append(new_import_path)
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Nachtfeuer/pipeline | spline/application.py | main | def main(**kwargs):
"""The Pipeline tool."""
options = ApplicationOptions(**kwargs)
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application = Application(options)
application.run(options.definition) | python | def main(**kwargs):
"""The Pipeline tool."""
options = ApplicationOptions(**kwargs)
Event.configure(is_logging_enabled=options.event_logging)
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Nachtfeuer/pipeline | spline/application.py | Application.setup_logging | def setup_logging(self):
"""Setup of application logging."""
is_custom_logging = len(self.options.logging_config) > 0
is_custom_logging = is_custom_logging and os.path.isfile(self.options.logging_config)
is_custom_logging = is_custom_logging and not self.options.dry_run
if is_cu... | python | def setup_logging(self):
"""Setup of application logging."""
is_custom_logging = len(self.options.logging_config) > 0
is_custom_logging = is_custom_logging and os.path.isfile(self.options.logging_config)
is_custom_logging = is_custom_logging and not self.options.dry_run
if is_cu... | [
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Nachtfeuer/pipeline | spline/application.py | Application.validate_document | def validate_document(self, definition):
"""
Validate given pipeline document.
The method is trying to load, parse and validate the spline document.
The validator verifies the Python structure B{not} the file format.
Args:
definition (str): path and filename of a ya... | python | def validate_document(self, definition):
"""
Validate given pipeline document.
The method is trying to load, parse and validate the spline document.
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definition (str): path and filename of a ya... | [
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Nachtfeuer/pipeline | spline/application.py | Application.run_matrix | def run_matrix(self, matrix_definition, document):
"""
Running pipeline via a matrix.
Args:
matrix_definition (dict): one concrete matrix item.
document (dict): spline document (complete) as loaded from yaml file.
"""
matrix = Matrix(matrix_definition, 'm... | python | def run_matrix(self, matrix_definition, document):
"""
Running pipeline via a matrix.
Args:
matrix_definition (dict): one concrete matrix item.
document (dict): spline document (complete) as loaded from yaml file.
"""
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Nachtfeuer/pipeline | spline/application.py | Application.shutdown | def shutdown(self, collector, success):
"""Shutdown of the application."""
self.event.delegate(success)
if collector is not None:
collector.queue.put(None)
collector.join()
if not success:
sys.exit(1) | python | def shutdown(self, collector, success):
"""Shutdown of the application."""
self.event.delegate(success)
if collector is not None:
collector.queue.put(None)
collector.join()
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Nachtfeuer/pipeline | spline/application.py | Application.provide_temporary_scripts_path | def provide_temporary_scripts_path(self):
"""When configured trying to ensure that path does exist."""
if len(self.options.temporary_scripts_path) > 0:
if os.path.isfile(self.options.temporary_scripts_path):
self.logger.error("Error: configured script path seems to be a file!... | python | def provide_temporary_scripts_path(self):
"""When configured trying to ensure that path does exist."""
if len(self.options.temporary_scripts_path) > 0:
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Nachtfeuer/pipeline | spline/application.py | Application.create_and_run_collector | def create_and_run_collector(document, options):
"""Create and run collector process for report data."""
collector = None
if not options.report == 'off':
collector = Collector()
collector.store.configure(document)
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"""Create and run collector process for report data."""
collector = None
if not options.report == 'off':
collector = Collector()
collector.store.configure(document)
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Nachtfeuer/pipeline | spline/tools/filters.py | docker_environment | def docker_environment(env):
"""
Transform dictionary of environment variables into Docker -e parameters.
>>> result = docker_environment({'param1': 'val1', 'param2': 'val2'})
>>> result in ['-e "param1=val1" -e "param2=val2"', '-e "param2=val2" -e "param1=val1"']
True
"""
return ' '.join(
... | python | def docker_environment(env):
"""
Transform dictionary of environment variables into Docker -e parameters.
>>> result = docker_environment({'param1': 'val1', 'param2': 'val2'})
>>> result in ['-e "param1=val1" -e "param2=val2"', '-e "param2=val2" -e "param1=val1"']
True
"""
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OpenHydrology/floodestimation | floodestimation/fehdata.py | _retrieve_download_url | def _retrieve_download_url():
"""
Retrieves download location for FEH data zip file from hosted json configuration file.
:return: URL for FEH data file
:rtype: str
"""
try:
# Try to obtain the url from the Open Hydrology json config file.
with urlopen(config['nrfa']['oh_json_url... | python | def _retrieve_download_url():
"""
Retrieves download location for FEH data zip file from hosted json configuration file.
:return: URL for FEH data file
:rtype: str
"""
try:
# Try to obtain the url from the Open Hydrology json config file.
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OpenHydrology/floodestimation | floodestimation/fehdata.py | update_available | def update_available(after_days=1):
"""
Check whether updated NRFA data is available.
:param after_days: Only check if not checked previously since a certain number of days ago
:type after_days: float
:return: `True` if update available, `False` if not, `None` if remote location cannot be reached.
... | python | def update_available(after_days=1):
"""
Check whether updated NRFA data is available.
:param after_days: Only check if not checked previously since a certain number of days ago
:type after_days: float
:return: `True` if update available, `False` if not, `None` if remote location cannot be reached.
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OpenHydrology/floodestimation | floodestimation/fehdata.py | download_data | def download_data():
"""
Downloads complete station dataset including catchment descriptors and amax records. And saves it into a cache
folder.
"""
with urlopen(_retrieve_download_url()) as f:
with open(os.path.join(CACHE_FOLDER, CACHE_ZIP), "wb") as local_file:
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"""
Downloads complete station dataset including catchment descriptors and amax records. And saves it into a cache
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"""
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OpenHydrology/floodestimation | floodestimation/fehdata.py | _update_nrfa_metadata | def _update_nrfa_metadata(remote_config):
"""
Save NRFA metadata to local config file using retrieved config data
:param remote_config: Downloaded JSON data, not a ConfigParser object!
"""
config['nrfa']['oh_json_url'] = remote_config['nrfa_oh_json_url']
config['nrfa']['version'] = remote_confi... | python | def _update_nrfa_metadata(remote_config):
"""
Save NRFA metadata to local config file using retrieved config data
:param remote_config: Downloaded JSON data, not a ConfigParser object!
"""
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OpenHydrology/floodestimation | floodestimation/fehdata.py | nrfa_metadata | def nrfa_metadata():
"""
Return metadata on the NRFA data.
Returned metadata is a dict with the following elements:
- `url`: string with NRFA data download URL
- `version`: string with NRFA version number, e.g. '3.3.4'
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"""
Return metadata on the NRFA data.
Returned metadata is a dict with the following elements:
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OpenHydrology/floodestimation | floodestimation/fehdata.py | unzip_data | def unzip_data():
"""
Extract all files from downloaded FEH data zip file.
"""
with ZipFile(os.path.join(CACHE_FOLDER, CACHE_ZIP), 'r') as zf:
zf.extractall(path=CACHE_FOLDER) | python | def unzip_data():
"""
Extract all files from downloaded FEH data zip file.
"""
with ZipFile(os.path.join(CACHE_FOLDER, CACHE_ZIP), 'r') as zf:
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acutesoftware/AIKIF | aikif/toolbox/xml_tools.py | get_xml_stats | def get_xml_stats(fname):
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res['filesize'] = str(f.size) + ... | python | def get_xml_stats(fname):
"""
return a dictionary of statistics about an
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number of elements, count by elements
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f = mod_file.TextFile(fname)
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acutesoftware/AIKIF | aikif/toolbox/xml_tools.py | make_random_xml_file | def make_random_xml_file(fname, num_elements=200, depth=3):
"""
makes a random xml file mainly for testing the xml_split
"""
with open(fname, 'w') as f:
f.write('<?xml version="1.0" ?>\n<random>\n')
for dep_num, _ in enumerate(range(1,depth)):
f.write(' <depth>\n <content>\n... | python | def make_random_xml_file(fname, num_elements=200, depth=3):
"""
makes a random xml file mainly for testing the xml_split
"""
with open(fname, 'w') as f:
f.write('<?xml version="1.0" ?>\n<random>\n')
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mpg-age-bioinformatics/AGEpy | AGEpy/kegg.py | organismsKEGG | def organismsKEGG():
"""
Lists all organisms present in the KEGG database.
:returns: a dataframe containing one organism per row.
"""
organisms=urlopen("http://rest.kegg.jp/list/organism").read()
organisms=organisms.split("\n")
#for o in organisms:
# print o
# sys.stdout.flus... | python | def organismsKEGG():
"""
Lists all organisms present in the KEGG database.
:returns: a dataframe containing one organism per row.
"""
organisms=urlopen("http://rest.kegg.jp/list/organism").read()
organisms=organisms.split("\n")
#for o in organisms:
# print o
# sys.stdout.flus... | [
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mpg-age-bioinformatics/AGEpy | AGEpy/kegg.py | databasesKEGG | def databasesKEGG(organism,ens_ids):
"""
Finds KEGG database identifiers for a respective organism given example ensembl ids.
:param organism: an organism as listed in organismsKEGG()
:param ens_ids: a list of ensenbl ids of the respective organism
:returns: nothing if no database was found, or a... | python | def databasesKEGG(organism,ens_ids):
"""
Finds KEGG database identifiers for a respective organism given example ensembl ids.
:param organism: an organism as listed in organismsKEGG()
:param ens_ids: a list of ensenbl ids of the respective organism
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mpg-age-bioinformatics/AGEpy | AGEpy/kegg.py | ensembl_to_kegg | def ensembl_to_kegg(organism,kegg_db):
"""
Looks up KEGG mappings of KEGG ids to ensembl ids
:param organism: an organisms as listed in organismsKEGG()
:param kegg_db: a matching KEGG db as reported in databasesKEGG
:returns: a Pandas dataframe of with 'KEGGid' and 'ENSid'.
"""
print("KEG... | python | def ensembl_to_kegg(organism,kegg_db):
"""
Looks up KEGG mappings of KEGG ids to ensembl ids
:param organism: an organisms as listed in organismsKEGG()
:param kegg_db: a matching KEGG db as reported in databasesKEGG
:returns: a Pandas dataframe of with 'KEGGid' and 'ENSid'.
"""
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mpg-age-bioinformatics/AGEpy | AGEpy/kegg.py | ecs_idsKEGG | def ecs_idsKEGG(organism):
"""
Uses KEGG to retrieve all ids and respective ecs for a given KEGG organism
:param organism: an organisms as listed in organismsKEGG()
:returns: a Pandas dataframe of with 'ec' and 'KEGGid'.
"""
kegg_ec=urlopen("http://rest.kegg.jp/link/"+organism+"/enzyme").read... | python | def ecs_idsKEGG(organism):
"""
Uses KEGG to retrieve all ids and respective ecs for a given KEGG organism
:param organism: an organisms as listed in organismsKEGG()
:returns: a Pandas dataframe of with 'ec' and 'KEGGid'.
"""
kegg_ec=urlopen("http://rest.kegg.jp/link/"+organism+"/enzyme").read... | [
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mpg-age-bioinformatics/AGEpy | AGEpy/kegg.py | idsKEGG | def idsKEGG(organism):
"""
Uses KEGG to retrieve all ids for a given KEGG organism
:param organism: an organism as listed in organismsKEGG()
:returns: a Pandas dataframe of with 'gene_name' and 'KEGGid'.
"""
ORG=urlopen("http://rest.kegg.jp/list/"+organism).read()
ORG=ORG.split("\n")
... | python | def idsKEGG(organism):
"""
Uses KEGG to retrieve all ids for a given KEGG organism
:param organism: an organism as listed in organismsKEGG()
:returns: a Pandas dataframe of with 'gene_name' and 'KEGGid'.
"""
ORG=urlopen("http://rest.kegg.jp/list/"+organism).read()
ORG=ORG.split("\n")
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mpg-age-bioinformatics/AGEpy | AGEpy/kegg.py | biomaRtTOkegg | def biomaRtTOkegg(df):
"""
Transforms a pandas dataframe with the columns 'ensembl_gene_id','kegg_enzyme'
to dataframe ready for use in ...
:param df: a pandas dataframe with the following columns: 'ensembl_gene_id','kegg_enzyme'
:returns: a pandas dataframe with the following columns: 'ensembl_ge... | python | def biomaRtTOkegg(df):
"""
Transforms a pandas dataframe with the columns 'ensembl_gene_id','kegg_enzyme'
to dataframe ready for use in ...
:param df: a pandas dataframe with the following columns: 'ensembl_gene_id','kegg_enzyme'
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mpg-age-bioinformatics/AGEpy | AGEpy/kegg.py | expKEGG | def expKEGG(organism,names_KEGGids):
"""
Gets all KEGG pathways for an organism
:param organism: an organism as listed in organismsKEGG()
:param names_KEGGids: a Pandas dataframe with the columns 'gene_name': and 'KEGGid' as reported from idsKEGG(organism) (or a subset of it).
:returns df: a Pand... | python | def expKEGG(organism,names_KEGGids):
"""
Gets all KEGG pathways for an organism
:param organism: an organism as listed in organismsKEGG()
:param names_KEGGids: a Pandas dataframe with the columns 'gene_name': and 'KEGGid' as reported from idsKEGG(organism) (or a subset of it).
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mpg-age-bioinformatics/AGEpy | AGEpy/rbiom.py | RdatabasesBM | def RdatabasesBM(host=rbiomart_host):
"""
Lists BioMart databases through a RPY2 connection.
:param host: address of the host server, default='www.ensembl.org'
:returns: nothing
"""
biomaRt = importr("biomaRt")
print(biomaRt.listMarts(host=host)) | python | def RdatabasesBM(host=rbiomart_host):
"""
Lists BioMart databases through a RPY2 connection.
:param host: address of the host server, default='www.ensembl.org'
:returns: nothing
"""
biomaRt = importr("biomaRt")
print(biomaRt.listMarts(host=host)) | [
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mpg-age-bioinformatics/AGEpy | AGEpy/rbiom.py | RdatasetsBM | def RdatasetsBM(database,host=rbiomart_host):
"""
Lists BioMart datasets through a RPY2 connection.
:param database: a database listed in RdatabasesBM()
:param host: address of the host server, default='www.ensembl.org'
:returns: nothing
"""
biomaRt = importr("biomaRt")
ensemblMart=bi... | python | def RdatasetsBM(database,host=rbiomart_host):
"""
Lists BioMart datasets through a RPY2 connection.
:param database: a database listed in RdatabasesBM()
:param host: address of the host server, default='www.ensembl.org'
:returns: nothing
"""
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mpg-age-bioinformatics/AGEpy | AGEpy/rbiom.py | RfiltersBM | def RfiltersBM(dataset,database,host=rbiomart_host):
"""
Lists BioMart filters through a RPY2 connection.
:param dataset: a dataset listed in RdatasetsBM()
:param database: a database listed in RdatabasesBM()
:param host: address of the host server, default='www.ensembl.org'
:returns: nothing
... | python | def RfiltersBM(dataset,database,host=rbiomart_host):
"""
Lists BioMart filters through a RPY2 connection.
:param dataset: a dataset listed in RdatasetsBM()
:param database: a database listed in RdatabasesBM()
:param host: address of the host server, default='www.ensembl.org'
:returns: nothing
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mpg-age-bioinformatics/AGEpy | AGEpy/rbiom.py | RattributesBM | def RattributesBM(dataset,database,host=rbiomart_host):
"""
Lists BioMart attributes through a RPY2 connection.
:param dataset: a dataset listed in RdatasetsBM()
:param database: a database listed in RdatabasesBM()
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"""
Lists BioMart attributes through a RPY2 connection.
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acutesoftware/AIKIF | scripts/examples/document_AIKIF.py | get_list_of_applications | def get_list_of_applications():
"""
Get list of applications
"""
apps = mod_prg.Programs('Applications', 'C:\\apps')
fl = mod_fl.FileList(['C:\\apps'], ['*.exe'], ["\\bk\\"])
for f in fl.get_list():
apps.add(f, 'autogenerated list')
apps.list()
apps.save() | python | def get_list_of_applications():
"""
Get list of applications
"""
apps = mod_prg.Programs('Applications', 'C:\\apps')
fl = mod_fl.FileList(['C:\\apps'], ['*.exe'], ["\\bk\\"])
for f in fl.get_list():
apps.add(f, 'autogenerated list')
apps.list()
apps.save() | [
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Timusan/wtforms-dynamic-fields | wtforms_dynamic_fields/wtforms_dynamic_fields.py | WTFormsDynamicFields.add_field | def add_field(self, name, label, field_type, *args, **kwargs):
""" Add the field to the internal configuration dictionary. """
if name in self._dyn_fields:
raise AttributeError('Field already added to the form.')
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""" Add the field to the internal configuration dictionary. """
if name in self._dyn_fields:
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else:
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Timusan/wtforms-dynamic-fields | wtforms_dynamic_fields/wtforms_dynamic_fields.py | WTFormsDynamicFields.add_validator | def add_validator(self, name, validator, *args, **kwargs):
""" Add the validator to the internal configuration dictionary.
:param name:
The field machine name to apply the validator on
:param validator:
The WTForms validator object
The rest are optional arguments... | python | def add_validator(self, name, validator, *args, **kwargs):
""" Add the validator to the internal configuration dictionary.
:param name:
The field machine name to apply the validator on
:param validator:
The WTForms validator object
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Timusan/wtforms-dynamic-fields | wtforms_dynamic_fields/wtforms_dynamic_fields.py | WTFormsDynamicFields.process | def process(self, form, post):
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Itterate over the POST values and check each field
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For each field that is valid, check all the validator
parameters for possible %field% replacement, then bind
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mpg-age-bioinformatics/AGEpy | AGEpy/bed.py | GetBEDnarrowPeakgz | def GetBEDnarrowPeakgz(URL_or_PATH_TO_file):
"""
Reads a gz compressed BED narrow peak file from a web address or local file
:param URL_or_PATH_TO_file: web address of path to local file
:returns: a Pandas dataframe
"""
if os.path.isfile(URL_or_PATH_TO_file):
response=open(URL_or_PATH... | python | def GetBEDnarrowPeakgz(URL_or_PATH_TO_file):
"""
Reads a gz compressed BED narrow peak file from a web address or local file
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mpg-age-bioinformatics/AGEpy | AGEpy/bed.py | dfTObedtool | def dfTObedtool(df):
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Transforms a pandas dataframe into a bedtool
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:returns: a bedtool
"""
df=df.astype(str)
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df=df.values.tolist()
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df="\n".join(df)
df=BedTool(df, from_string=True)
re... | python | def dfTObedtool(df):
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:returns: a bedtool
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Nachtfeuer/pipeline | spline/tools/event.py | Event.failed | def failed(self, **kwargs):
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self.information.update(kwargs)
self.logger.info("Failed - took %f seconds.", self.duration())
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"""Finish event as failed with optional additional information."""
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self.logger.info("Failed - took %f seconds.", self.duration())
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Nachtfeuer/pipeline | spline/tools/event.py | Event.update_report_collector | def update_report_collector(self, timestamp):
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acutesoftware/AIKIF | aikif/toolbox/sql_tools.py | count_lines_in_file | def count_lines_in_file(src_file ):
"""
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except:
res = 'ERROR -couldnt open file'
return res | python | def count_lines_in_file(src_file ):
"""
test function.
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try:
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tot += 1
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acutesoftware/AIKIF | aikif/toolbox/sql_tools.py | load_txt_to_sql | def load_txt_to_sql(tbl_name, src_file_and_path, src_file, op_folder):
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asyncdef/aitertools | aitertools/__init__.py | anext | async def anext(*args):
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iterable: An async iterable.
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asyncdef/aitertools | aitertools/__init__.py | repeat | def repeat(obj, times=None):
"""Make an iterator that returns object over and over again."""
if times is None:
return AsyncIterWrapper(sync_itertools.repeat(obj))
return AsyncIterWrapper(sync_itertools.repeat(obj, times)) | python | def repeat(obj, times=None):
"""Make an iterator that returns object over and over again."""
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return AsyncIterWrapper(sync_itertools.repeat(obj, times)) | [
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asyncdef/aitertools | aitertools/__init__.py | _async_callable | def _async_callable(func):
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async def _async_def_wrapper(*args, **kwargs):
"""Wrap a a sync callable in an async def."""
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retu... | python | def _async_callable(func):
"""Ensure the callable is an async def."""
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async def _async_def_wrapper(*args, **kwargs):
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asyncdef/aitertools | aitertools/__init__.py | tee | def tee(iterable, n=2):
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nocarryr/python-dispatch | pydispatch/properties.py | Property._on_change | def _on_change(self, obj, old, value, **kwargs):
"""Called internally to emit changes from the instance object
The keyword arguments here will be passed to callbacks through the
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Keyword Args:
property: T... | python | def _on_change(self, obj, old, value, **kwargs):
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OpenHydrology/floodestimation | floodestimation/parsers.py | FehFileParser.parse_str | def parse_str(self, s):
"""
Parse string and return relevant object
:param s: string to parse
:type s: str
:return: Parsed object
"""
self.object = self.parsed_class()
in_section = None # Holds name of FEH file section while traversing through file.
... | python | def parse_str(self, s):
"""
Parse string and return relevant object
:param s: string to parse
:type s: str
:return: Parsed object
"""
self.object = self.parsed_class()
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