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smdabdoub/phylotoast | phylotoast/util.py | split_phylogeny | def split_phylogeny(p, level="s"):
"""
Return either the full or truncated version of a QIIME-formatted taxonomy string.
:type p: str
:param p: A QIIME-formatted taxonomy string: k__Foo; p__Bar; ...
:type level: str
:param level: The different level of identification are kingdom (k), phylum (p... | python | def split_phylogeny(p, level="s"):
"""
Return either the full or truncated version of a QIIME-formatted taxonomy string.
:type p: str
:param p: A QIIME-formatted taxonomy string: k__Foo; p__Bar; ...
:type level: str
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smdabdoub/phylotoast | phylotoast/util.py | ensure_dir | def ensure_dir(d):
"""
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method catches OSError exceptions and returns a descriptive message instead of
re-raising the error.
:type d: str
:param d: It is the full path to a directory.
:return: Does not retu... | python | def ensure_dir(d):
"""
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:type d: str
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smdabdoub/phylotoast | phylotoast/util.py | file_handle | def file_handle(fnh, mode="rU"):
"""
Takes either a file path or an open file handle, checks validity and returns an open
file handle or raises an appropriate Exception.
:type fnh: str
:param fnh: It is the full path to a file, or open file handle
:type mode: str
:param mode: The way in wh... | python | def file_handle(fnh, mode="rU"):
"""
Takes either a file path or an open file handle, checks validity and returns an open
file handle or raises an appropriate Exception.
:type fnh: str
:param fnh: It is the full path to a file, or open file handle
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smdabdoub/phylotoast | phylotoast/util.py | gather_categories | def gather_categories(imap, header, categories=None):
"""
Find the user specified categories in the map and create a dictionary to contain the
relevant data for each type within the categories. Multiple categories will have their
types combined such that each possible combination will have its own entry... | python | def gather_categories(imap, header, categories=None):
"""
Find the user specified categories in the map and create a dictionary to contain the
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smdabdoub/phylotoast | phylotoast/util.py | parse_unifrac | def parse_unifrac(unifracFN):
"""
Parses the unifrac results file into a dictionary
:type unifracFN: str
:param unifracFN: The path to the unifrac results file
:rtype: dict
:return: A dictionary with keys: 'pcd' (principle coordinates data) which is a
dictionary of the data keyed ... | python | def parse_unifrac(unifracFN):
"""
Parses the unifrac results file into a dictionary
:type unifracFN: str
:param unifracFN: The path to the unifrac results file
:rtype: dict
:return: A dictionary with keys: 'pcd' (principle coordinates data) which is a
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smdabdoub/phylotoast | phylotoast/util.py | parse_unifrac_v1_8 | def parse_unifrac_v1_8(unifrac, file_data):
"""
Function to parse data from older version of unifrac file obtained from Qiime version
1.8 and earlier.
:type unifrac: dict
:param unifracFN: The path to the unifrac results file
:type file_data: list
:param file_data: Unifrac data lines after... | python | def parse_unifrac_v1_8(unifrac, file_data):
"""
Function to parse data from older version of unifrac file obtained from Qiime version
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:type unifrac: dict
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smdabdoub/phylotoast | phylotoast/util.py | parse_unifrac_v1_9 | def parse_unifrac_v1_9(unifrac, file_data):
"""
Function to parse data from newer version of unifrac file obtained from Qiime version
1.9 and later.
:type unifracFN: str
:param unifracFN: The path to the unifrac results file
:type file_data: list
:param file_data: Unifrac data lines after ... | python | def parse_unifrac_v1_9(unifrac, file_data):
"""
Function to parse data from newer version of unifrac file obtained from Qiime version
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:type unifracFN: str
:param unifracFN: The path to the unifrac results file
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smdabdoub/phylotoast | phylotoast/util.py | color_mapping | def color_mapping(sample_map, header, group_column, color_column=None):
"""
Determine color-category mapping. If color_column was specified, then map the category
names to color values. Otherwise, use the palettable colors to automatically generate
a set of colors for the group values.
:type sample... | python | def color_mapping(sample_map, header, group_column, color_column=None):
"""
Determine color-category mapping. If color_column was specified, then map the category
names to color values. Otherwise, use the palettable colors to automatically generate
a set of colors for the group values.
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christophertbrown/bioscripts | ctbBio/shuffle_genome.py | rev_c | def rev_c(read):
"""
return reverse completment of read
"""
rc = []
rc_nucs = {'A':'T', 'T':'A', 'G':'C', 'C':'G', 'N':'N'}
for base in read:
rc.extend(rc_nucs[base.upper()])
return rc[::-1] | python | def rev_c(read):
"""
return reverse completment of read
"""
rc = []
rc_nucs = {'A':'T', 'T':'A', 'G':'C', 'C':'G', 'N':'N'}
for base in read:
rc.extend(rc_nucs[base.upper()])
return rc[::-1] | [
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christophertbrown/bioscripts | ctbBio/shuffle_genome.py | shuffle_genome | def shuffle_genome(genome, cat, fraction = float(100), plot = True, \
alpha = 0.1, beta = 100000, \
min_length = 1000, max_length = 200000):
"""
randomly shuffle genome
"""
header = '>randomized_%s' % (genome.name)
sequence = list(''.join([i[1] for i in parse_fasta(genome)]))
len... | python | def shuffle_genome(genome, cat, fraction = float(100), plot = True, \
alpha = 0.1, beta = 100000, \
min_length = 1000, max_length = 200000):
"""
randomly shuffle genome
"""
header = '>randomized_%s' % (genome.name)
sequence = list(''.join([i[1] for i in parse_fasta(genome)]))
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opengridcc/opengrid | opengrid/library/regression.py | MultiVarLinReg._prune | def _prune(self, fit, p_max):
"""
If the fit contains statistically insignificant parameters, remove them.
Returns a pruned fit where all parameters have p-values of the t-statistic below p_max
Parameters
----------
fit: fm.ols fit object
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"""
If the fit contains statistically insignificant parameters, remove them.
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opengridcc/opengrid | opengrid/library/regression.py | MultiVarLinReg.find_best_rsquared | def find_best_rsquared(list_of_fits):
"""Return the best fit, based on rsquared"""
res = sorted(list_of_fits, key=lambda x: x.rsquared)
return res[-1] | python | def find_best_rsquared(list_of_fits):
"""Return the best fit, based on rsquared"""
res = sorted(list_of_fits, key=lambda x: x.rsquared)
return res[-1] | [
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opengridcc/opengrid | opengrid/library/regression.py | MultiVarLinReg._predict | def _predict(self, fit, df):
"""
Return a df with predictions and confidence interval
Notes
-----
The df will contain the following columns:
- 'predicted': the model output
- 'interval_u', 'interval_l': upper and lower confidence bounds.
The result will ... | python | def _predict(self, fit, df):
"""
Return a df with predictions and confidence interval
Notes
-----
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- 'predicted': the model output
- 'interval_u', 'interval_l': upper and lower confidence bounds.
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smdabdoub/phylotoast | phylotoast/biom_calc.py | relative_abundance | def relative_abundance(biomf, sampleIDs=None):
"""
Calculate the relative abundance of each OTUID in a Sample.
:type biomf: A BIOM file.
:param biomf: OTU table format.
:type sampleIDs: list
:param sampleIDs: A list of sample id's from BIOM format OTU table.
:rtype: dict
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"""
Calculate the relative abundance of each OTUID in a Sample.
:type biomf: A BIOM file.
:param biomf: OTU table format.
:type sampleIDs: list
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smdabdoub/phylotoast | phylotoast/biom_calc.py | mean_otu_pct_abundance | def mean_otu_pct_abundance(ra, otuIDs):
"""
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:type ra: Dict
:param ra: 'ra' refers to a dictionary keyed on SampleIDs, and the values are
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Calculate the mean OTU abundance percentage.
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smdabdoub/phylotoast | phylotoast/biom_calc.py | MRA | def MRA(biomf, sampleIDs=None, transform=None):
"""
Calculate the mean relative abundance percentage.
:type biomf: A BIOM file.
:param biomf: OTU table format.
:type sampleIDs: list
:param sampleIDs: A list of sample id's from BIOM format OTU table.
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"""
Calculate the mean relative abundance percentage.
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smdabdoub/phylotoast | phylotoast/biom_calc.py | raw_abundance | def raw_abundance(biomf, sampleIDs=None, sample_abd=True):
"""
Calculate the total number of sequences in each OTU or SampleID.
:type biomf: A BIOM file.
:param biomf: OTU table format.
:type sampleIDs: List
:param sampleIDs: A list of column id's from BIOM format OTU table. By default, the
... | python | def raw_abundance(biomf, sampleIDs=None, sample_abd=True):
"""
Calculate the total number of sequences in each OTU or SampleID.
:type biomf: A BIOM file.
:param biomf: OTU table format.
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smdabdoub/phylotoast | phylotoast/biom_calc.py | transform_raw_abundance | def transform_raw_abundance(biomf, fn=math.log10, sampleIDs=None, sample_abd=True):
"""
Function to transform the total abundance calculation for each sample ID to another
format based on user given transformation function.
:type biomf: A BIOM file.
:param biomf: OTU table format.
:param fn: M... | python | def transform_raw_abundance(biomf, fn=math.log10, sampleIDs=None, sample_abd=True):
"""
Function to transform the total abundance calculation for each sample ID to another
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smdabdoub/phylotoast | bin/diversity.py | print_MannWhitneyU | def print_MannWhitneyU(div_calc):
"""
Compute the Mann-Whitney U test for unequal group sample sizes.
"""
try:
x = div_calc.values()[0].values()
y = div_calc.values()[1].values()
except:
return "Error setting up input arrays for Mann-Whitney U Test. Skipping "\
... | python | def print_MannWhitneyU(div_calc):
"""
Compute the Mann-Whitney U test for unequal group sample sizes.
"""
try:
x = div_calc.values()[0].values()
y = div_calc.values()[1].values()
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return "Error setting up input arrays for Mann-Whitney U Test. Skipping "\
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smdabdoub/phylotoast | bin/diversity.py | print_KruskalWallisH | def print_KruskalWallisH(div_calc):
"""
Compute the Kruskal-Wallis H-test for independent samples. A typical rule is that
each group must have at least 5 measurements.
"""
calc = defaultdict(list)
try:
for k1, v1 in div_calc.iteritems():
for k2, v2 in v1.iteritems():
... | python | def print_KruskalWallisH(div_calc):
"""
Compute the Kruskal-Wallis H-test for independent samples. A typical rule is that
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"""
calc = defaultdict(list)
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smdabdoub/phylotoast | bin/diversity.py | handle_program_options | def handle_program_options():
"""Parses the given options passed in at the command line."""
parser = argparse.ArgumentParser(description="Calculate the alpha diversity\
of a set of samples using one or more \
metrics and output a kernal d... | python | def handle_program_options():
"""Parses the given options passed in at the command line."""
parser = argparse.ArgumentParser(description="Calculate the alpha diversity\
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christophertbrown/bioscripts | ctbBio/search.py | blastdb | def blastdb(fasta, maxfile = 10000000):
"""
make blast db
"""
db = fasta.rsplit('.', 1)[0]
type = check_type(fasta)
if type == 'nucl':
type = ['nhr', type]
else:
type = ['phr', type]
if os.path.exists('%s.%s' % (db, type[0])) is False \
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"""
make blast db
"""
db = fasta.rsplit('.', 1)[0]
type = check_type(fasta)
if type == 'nucl':
type = ['nhr', type]
else:
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christophertbrown/bioscripts | ctbBio/search.py | usearchdb | def usearchdb(fasta, alignment = 'local', usearch_loc = 'usearch'):
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mkouhei/bootstrap-py | bootstrap_py/control.py | _pp | def _pp(dict_data):
"""Pretty print."""
for key, val in dict_data.items():
# pylint: disable=superfluous-parens
print('{0:<11}: {1}'.format(key, val)) | python | def _pp(dict_data):
"""Pretty print."""
for key, val in dict_data.items():
# pylint: disable=superfluous-parens
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mkouhei/bootstrap-py | bootstrap_py/control.py | print_licences | def print_licences(params, metadata):
"""Print licenses.
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"""
if hasattr(params, 'licenses'):
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sys.exit(0) | python | def print_licences(params, metadata):
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mkouhei/bootstrap-py | bootstrap_py/control.py | check_repository_existence | def check_repository_existence(params):
"""Check repository existence.
:param argparse.Namespace params: parameters
"""
repodir = os.path.join(params.outdir, params.name)
if os.path.isdir(repodir):
raise Conflict(
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"""Check repository existence.
:param argparse.Namespace params: parameters
"""
repodir = os.path.join(params.outdir, params.name)
if os.path.isdir(repodir):
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mkouhei/bootstrap-py | bootstrap_py/control.py | generate_package | def generate_package(params):
"""Generate package repository.
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"""
pkg_data = package.PackageData(params)
pkg_tree = package.PackageTree(pkg_data)
pkg_tree.generate()
pkg_tree.move()
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"""Generate package repository.
:param argparse.Namespace params: parameters
"""
pkg_data = package.PackageData(params)
pkg_tree = package.PackageTree(pkg_data)
pkg_tree.generate()
pkg_tree.move()
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christophertbrown/bioscripts | ctbBio/sam2fastq.py | print_single | def print_single(line, rev):
"""
print single reads to stderr
"""
if rev is True:
seq = rc(['', line[9]])[1]
qual = line[10][::-1]
else:
seq = line[9]
qual = line[10]
fq = ['@%s' % line[0], seq, '+%s' % line[0], qual]
print('\n'.join(fq), file = sys.stderr) | python | def print_single(line, rev):
"""
print single reads to stderr
"""
if rev is True:
seq = rc(['', line[9]])[1]
qual = line[10][::-1]
else:
seq = line[9]
qual = line[10]
fq = ['@%s' % line[0], seq, '+%s' % line[0], qual]
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christophertbrown/bioscripts | ctbBio/sam2fastq.py | sam2fastq | def sam2fastq(sam, singles = False, force = False):
"""
convert sam to fastq
"""
L, R = None, None
for line in sam:
if line.startswith('@') is True:
continue
line = line.strip().split()
bit = [True if i == '1' else False \
for i in bin(int(line[1])... | python | def sam2fastq(sam, singles = False, force = False):
"""
convert sam to fastq
"""
L, R = None, None
for line in sam:
if line.startswith('@') is True:
continue
line = line.strip().split()
bit = [True if i == '1' else False \
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christophertbrown/bioscripts | ctbBio/subset_sam.py | sort_sam | def sort_sam(sam, sort):
"""
sort sam file
"""
tempdir = '%s/' % (os.path.abspath(sam).rsplit('/', 1)[0])
if sort is True:
mapping = '%s.sorted.sam' % (sam.rsplit('.', 1)[0])
if sam != '-':
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"""
sort sam file
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tempdir = '%s/' % (os.path.abspath(sam).rsplit('/', 1)[0])
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christophertbrown/bioscripts | ctbBio/subset_sam.py | sub_sam | def sub_sam(sam, percent, sort = True, sbuffer = False):
"""
randomly subset sam file
"""
mapping = sort_sam(sam, sort)
pool = [1 for i in range(0, percent)] + [0 for i in range(0, 100 - percent)]
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for line in mapping:
line = line.strip().split()
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"""
randomly subset sam file
"""
mapping = sort_sam(sam, sort)
pool = [1 for i in range(0, percent)] + [0 for i in range(0, 100 - percent)]
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christophertbrown/bioscripts | ctbBio/fastq2fasta.py | fq2fa | def fq2fa(fq):
"""
convert fq to fa
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c = cycle([1, 2, 3, 4])
for line in fq:
n = next(c)
if n == 1:
seq = ['>%s' % (line.strip().split('@', 1)[1])]
if n == 2:
seq.append(line.strip())
yield seq | python | def fq2fa(fq):
"""
convert fq to fa
"""
c = cycle([1, 2, 3, 4])
for line in fq:
n = next(c)
if n == 1:
seq = ['>%s' % (line.strip().split('@', 1)[1])]
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elbow-jason/Uno-deprecated | uno/decorators.py | change_return_type | def change_return_type(f):
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"""
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elbow-jason/Uno-deprecated | uno/decorators.py | convert_args_to_sets | def convert_args_to_sets(f):
"""
Converts all args to 'set' type via self.setify function.
"""
@wraps(f)
def wrapper(*args, **kwargs):
args = (setify(x) for x in args)
return f(*args, **kwargs)
return wrapper | python | def convert_args_to_sets(f):
"""
Converts all args to 'set' type via self.setify function.
"""
@wraps(f)
def wrapper(*args, **kwargs):
args = (setify(x) for x in args)
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laymonage/kbbi-python | kbbi/kbbi.py | KBBI._init_entri | def _init_entri(self, laman):
"""Membuat objek-objek entri dari laman yang diambil.
:param laman: Laman respons yang dikembalikan oleh KBBI daring.
:type laman: Response
"""
sup = BeautifulSoup(laman.text, 'html.parser')
estr = ''
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"""Membuat objek-objek entri dari laman yang diambil.
:param laman: Laman respons yang dikembalikan oleh KBBI daring.
:type laman: Response
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laymonage/kbbi-python | kbbi/kbbi.py | Entri._init_kata_dasar | def _init_kata_dasar(self, dasar):
"""Memproses kata dasar yang ada dalam nama entri.
:param dasar: ResultSet untuk label HTML dengan class="rootword"
:type dasar: ResultSet
"""
for tiap in dasar:
kata = tiap.find('a')
dasar_no = kata.find('sup')
... | python | def _init_kata_dasar(self, dasar):
"""Memproses kata dasar yang ada dalam nama entri.
:param dasar: ResultSet untuk label HTML dengan class="rootword"
:type dasar: ResultSet
"""
for tiap in dasar:
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laymonage/kbbi-python | kbbi/kbbi.py | Entri.serialisasi | def serialisasi(self):
"""Mengembalikan hasil serialisasi objek Entri ini.
:returns: Dictionary hasil serialisasi
:rtype: dict
"""
return {
"nama": self.nama,
"nomor": self.nomor,
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"pelafalan": self.p... | python | def serialisasi(self):
"""Mengembalikan hasil serialisasi objek Entri ini.
:returns: Dictionary hasil serialisasi
:rtype: dict
"""
return {
"nama": self.nama,
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:rtype: str
"""
if len(self.makna) > 1:
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for i, makna in enumera... | python | def _makna(self):
"""Mengembalikan representasi string untuk semua makna entri ini.
:returns: String representasi makna-makna
:rtype: str
"""
if len(self.makna) > 1:
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laymonage/kbbi-python | kbbi/kbbi.py | Entri._nama | def _nama(self):
"""Mengembalikan representasi string untuk nama entri ini.
:returns: String representasi nama entri
:rtype: str
"""
hasil = self.nama
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"""Mengembalikan representasi string untuk nama entri ini.
:returns: String representasi nama entri
:rtype: str
"""
hasil = self.nama
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laymonage/kbbi-python | kbbi/kbbi.py | Entri._varian | def _varian(self, varian):
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:param varian: List bentuk tidak baku atau varian
:type varian: list
:returns: String representasi varian atau bentuk tidak baku
... | python | def _varian(self, varian):
"""Mengembalikan representasi string untuk varian entri ini.
Dapat digunakan untuk "Varian" maupun "Bentuk tidak baku".
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laymonage/kbbi-python | kbbi/kbbi.py | Makna._init_kelas | def _init_kelas(self, makna_label):
"""Memproses kelas kata yang ada dalam makna.
:param makna_label: BeautifulSoup untuk makna yang ingin diproses.
:type makna_label: BeautifulSoup
"""
kelas = makna_label.find(color='red')
lain = makna_label.find(color='darkgreen')
... | python | def _init_kelas(self, makna_label):
"""Memproses kelas kata yang ada dalam makna.
:param makna_label: BeautifulSoup untuk makna yang ingin diproses.
:type makna_label: BeautifulSoup
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kelas = makna_label.find(color='red')
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laymonage/kbbi-python | kbbi/kbbi.py | Makna._init_contoh | def _init_contoh(self, makna_label):
"""Memproses contoh yang ada dalam makna.
:param makna_label: BeautifulSoup untuk makna yang ingin diproses.
:type makna_label: BeautifulSoup
"""
indeks = makna_label.text.find(': ')
if indeks != -1:
contoh = makna_label.... | python | def _init_contoh(self, makna_label):
"""Memproses contoh yang ada dalam makna.
:param makna_label: BeautifulSoup untuk makna yang ingin diproses.
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indeks = makna_label.text.find(': ')
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laymonage/kbbi-python | kbbi/kbbi.py | Makna.serialisasi | def serialisasi(self):
"""Mengembalikan hasil serialisasi objek Makna ini.
:returns: Dictionary hasil serialisasi
:rtype: dict
"""
return {
"kelas": self.kelas,
"submakna": self.submakna,
"info": self.info,
"contoh": self.contoh
... | python | def serialisasi(self):
"""Mengembalikan hasil serialisasi objek Makna ini.
:returns: Dictionary hasil serialisasi
:rtype: dict
"""
return {
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mkouhei/bootstrap-py | bootstrap_py/docs.py | build_sphinx | def build_sphinx(pkg_data, projectdir):
"""Build sphinx documentation.
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:return: subprocess.call return code
:param `bootstrap_py.control.PackageData` pkg_data: package meta data
:param str projectdir: project root directory
"""
try:
version, _minor_version = pkg_data.ve... | python | def build_sphinx(pkg_data, projectdir):
"""Build sphinx documentation.
:rtype: int
:return: subprocess.call return code
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christophertbrown/bioscripts | ctbBio/crossmap.py | bowtiedb | def bowtiedb(fa, keepDB):
"""
make bowtie db
"""
btdir = '%s/bt2' % (os.getcwd())
# make directory for
if not os.path.exists(btdir):
os.mkdir(btdir)
btdb = '%s/%s' % (btdir, fa.rsplit('/', 1)[-1])
if keepDB is True:
if os.path.exists('%s.1.bt2' % (btdb)):
retu... | python | def bowtiedb(fa, keepDB):
"""
make bowtie db
"""
btdir = '%s/bt2' % (os.getcwd())
# make directory for
if not os.path.exists(btdir):
os.mkdir(btdir)
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christophertbrown/bioscripts | ctbBio/crossmap.py | bowtie | def bowtie(sam, btd, f, r, u, opt, no_shrink, threads):
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generate bowtie2 command
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"""
generate bowtie2 command
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christophertbrown/bioscripts | ctbBio/crossmap.py | crossmap | def crossmap(fas, reads, options, no_shrink, keepDB, threads, cluster, nodes):
"""
map all read sets against all fasta files
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if cluster is True:
threads = '48'
btc = []
for fa in fas:
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"""
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disqus/nydus | nydus/db/base.py | BaseCluster.get_conn | def get_conn(self, *args, **kwargs):
"""
Returns a connection object from the router given ``args``.
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Redis pipelines.
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scottrice/pysteam | pysteam/_crc_algorithms.py | Crc.__get_nondirect_init | def __get_nondirect_init(self, init):
"""
return the non-direct init if the direct algorithm has been selected.
"""
crc = init
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crc >>= 1
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"""
return the non-direct init if the direct algorithm has been selected.
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crc = init
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bit = crc & 0x01
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scottrice/pysteam | pysteam/_crc_algorithms.py | Crc.reflect | def reflect(self, data, width):
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"""
x = data & 0x01
for i in range(width - 1):
data >>= 1
x = (x << 1) | (data & 0x01)
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"""
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"""
x = data & 0x01
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data >>= 1
x = (x << 1) | (data & 0x01)
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scottrice/pysteam | pysteam/_crc_algorithms.py | Crc.bit_by_bit | def bit_by_bit(self, in_data):
"""
Classic simple and slow CRC implementation. This function iterates bit
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value at the end.
"""
# If the input data is a string, convert to bytes.
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"""
Classic simple and slow CRC implementation. This function iterates bit
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scottrice/pysteam | pysteam/_crc_algorithms.py | Crc.gen_table | def gen_table(self):
"""
This function generates the CRC table used for the table_driven CRC
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instead.
"""
table_length = 1... | python | def gen_table(self):
"""
This function generates the CRC table used for the table_driven CRC
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scottrice/pysteam | pysteam/_crc_algorithms.py | Crc.table_driven | def table_driven(self, in_data):
"""
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# If the input data is a string, convert to bytes.
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in_data = [ord(c) for c in in_data]
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christophertbrown/bioscripts | ctbBio/strip_masked.py | parse_masked | def parse_masked(seq, min_len):
"""
parse masked sequence into non-masked and masked regions
"""
nm, masked = [], [[]]
prev = None
for base in seq[1]:
if base.isupper():
nm.append(base)
if masked != [[]] and len(masked[-1]) < min_len:
nm.extend(mas... | python | def parse_masked(seq, min_len):
"""
parse masked sequence into non-masked and masked regions
"""
nm, masked = [], [[]]
prev = None
for base in seq[1]:
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nm.append(base)
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christophertbrown/bioscripts | ctbBio/strip_masked.py | strip_masked | def strip_masked(fasta, min_len, print_masked):
"""
remove masked regions from fasta file as long as
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"""
for seq in parse_fasta(fasta):
nm, masked = parse_masked(seq, min_len)
nm = ['%s removed_masked >=%s' % (seq[0], min_len), ''.join(nm)]
yield ... | python | def strip_masked(fasta, min_len, print_masked):
"""
remove masked regions from fasta file as long as
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"""
for seq in parse_fasta(fasta):
nm, masked = parse_masked(seq, min_len)
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smdabdoub/phylotoast | bin/network_plots_gephi.py | get_relative_abundance | def get_relative_abundance(biomfile):
"""
Return arcsine transformed relative abundance from a BIOM format file.
:type biomfile: BIOM format file
:param biomfile: BIOM format file used to obtain relative abundances for each OTU in
a SampleID, which are used as node sizes in network... | python | def get_relative_abundance(biomfile):
"""
Return arcsine transformed relative abundance from a BIOM format file.
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smdabdoub/phylotoast | bin/iTol.py | find_otu | def find_otu(otuid, tree):
"""
Find an OTU ID in a Newick-format tree.
Return the starting position of the ID or None if not found.
"""
for m in re.finditer(otuid, tree):
before, after = tree[m.start()-1], tree[m.start()+len(otuid)]
if before in ["(", ",", ")"] and after in [":", ";"... | python | def find_otu(otuid, tree):
"""
Find an OTU ID in a Newick-format tree.
Return the starting position of the ID or None if not found.
"""
for m in re.finditer(otuid, tree):
before, after = tree[m.start()-1], tree[m.start()+len(otuid)]
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smdabdoub/phylotoast | bin/iTol.py | newick_replace_otuids | def newick_replace_otuids(tree, biomf):
"""
Replace the OTU ids in the Newick phylogenetic tree format with truncated
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"""
for val, id_, md in biomf.iter(axis="observation"):
otu_loc = find_otu(id_, tree)
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tree = tree[:otu_loc] + \
... | python | def newick_replace_otuids(tree, biomf):
"""
Replace the OTU ids in the Newick phylogenetic tree format with truncated
OTU names
"""
for val, id_, md in biomf.iter(axis="observation"):
otu_loc = find_otu(id_, tree)
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christophertbrown/bioscripts | ctbBio/cluster_ani.py | genome_info | def genome_info(genome, info):
"""
return genome info for choosing representative
if ggKbase table provided - choose rep based on SCGs and genome length
- priority for most SCGs - extra SCGs, then largest genome
otherwise, based on largest genome
"""
try:
scg = info['#SCG... | python | def genome_info(genome, info):
"""
return genome info for choosing representative
if ggKbase table provided - choose rep based on SCGs and genome length
- priority for most SCGs - extra SCGs, then largest genome
otherwise, based on largest genome
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christophertbrown/bioscripts | ctbBio/cluster_ani.py | print_clusters | def print_clusters(fastas, info, ANI):
"""
choose represenative genome and
print cluster information
*if ggKbase table is provided, use SCG info to choose best genome
"""
header = ['#cluster', 'num. genomes', 'rep.', 'genome', '#SCGs', '#SCG duplicates', \
'genome size (bp)', 'fragm... | python | def print_clusters(fastas, info, ANI):
"""
choose represenative genome and
print cluster information
*if ggKbase table is provided, use SCG info to choose best genome
"""
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christophertbrown/bioscripts | ctbBio/cluster_ani.py | parse_ggKbase_tables | def parse_ggKbase_tables(tables, id_type):
"""
convert ggKbase genome info tables to dictionary
"""
g2info = {}
for table in tables:
for line in open(table):
line = line.strip().split('\t')
if line[0].startswith('name'):
header = line
h... | python | def parse_ggKbase_tables(tables, id_type):
"""
convert ggKbase genome info tables to dictionary
"""
g2info = {}
for table in tables:
for line in open(table):
line = line.strip().split('\t')
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christophertbrown/bioscripts | ctbBio/cluster_ani.py | parse_checkM_tables | def parse_checkM_tables(tables):
"""
convert checkM genome info tables to dictionary
"""
g2info = {}
for table in tables:
for line in open(table):
line = line.strip().split('\t')
if line[0].startswith('Bin Id'):
header = line
header[8] ... | python | def parse_checkM_tables(tables):
"""
convert checkM genome info tables to dictionary
"""
g2info = {}
for table in tables:
for line in open(table):
line = line.strip().split('\t')
if line[0].startswith('Bin Id'):
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christophertbrown/bioscripts | ctbBio/cluster_ani.py | genome_lengths | def genome_lengths(fastas, info):
"""
get genome lengths
"""
if info is False:
info = {}
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name = genome.rsplit('.', 1)[0].rsplit('/', 1)[-1].rsplit('.contigs')[0]
if name in info:
continue
length = 0
fragments = 0
for s... | python | def genome_lengths(fastas, info):
"""
get genome lengths
"""
if info is False:
info = {}
for genome in fastas:
name = genome.rsplit('.', 1)[0].rsplit('/', 1)[-1].rsplit('.contigs')[0]
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disqus/nydus | nydus/db/routers/base.py | BaseRouter.get_dbs | def get_dbs(self, attr, args, kwargs, **fkwargs):
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disqus/nydus | nydus/db/routers/base.py | BaseRouter.setup_router | def setup_router(self, args, kwargs, **fkwargs):
"""
Call method to perform any setup
"""
self._ready = self._setup_router(args=args, kwargs=kwargs, **fkwargs)
return self._ready | python | def setup_router(self, args, kwargs, **fkwargs):
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Call method to perform any setup
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disqus/nydus | nydus/db/routers/base.py | BaseRouter._route | def _route(self, attr, args, kwargs, **fkwargs):
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disqus/nydus | nydus/db/routers/base.py | RoundRobinRouter.check_down_connections | def check_down_connections(self):
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now = time.time()
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self.mark_connection_up(db_num) | python | def flush_down_connections(self):
"""
Marks all connections which were previously listed as unavailable as being up.
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opengridcc/opengrid | opengrid/library/analysis.py | standby | def standby(df, resolution='24h', time_window=None):
"""
Compute standby power
Parameters
----------
df : pandas.DataFrame or pandas.Series
Electricity Power
resolution : str, default='d'
Resolution of the computation. Data will be resampled to this resolution (as mean) before ... | python | def standby(df, resolution='24h', time_window=None):
"""
Compute standby power
Parameters
----------
df : pandas.DataFrame or pandas.Series
Electricity Power
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opengridcc/opengrid | opengrid/library/analysis.py | share_of_standby | def share_of_standby(df, resolution='24h', time_window=None):
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----------
df : pandas.DataFrame or pandas.Series
Power (typically electricity, can be anything)
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df : pandas.DataFrame or pandas.Series
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opengridcc/opengrid | opengrid/library/analysis.py | count_peaks | def count_peaks(ts):
"""
Toggle counter for gas boilers
Counts the number of times the gas consumption increases with more than 3kW
Parameters
----------
ts: Pandas Series
Gas consumption in minute resolution
Returns
-------
int
"""
on_toggles = ts.diff() > 3000
... | python | def count_peaks(ts):
"""
Toggle counter for gas boilers
Counts the number of times the gas consumption increases with more than 3kW
Parameters
----------
ts: Pandas Series
Gas consumption in minute resolution
Returns
-------
int
"""
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opengridcc/opengrid | opengrid/library/analysis.py | load_factor | def load_factor(ts, resolution=None, norm=None):
"""
Calculate the ratio of input vs. norm over a given interval.
Parameters
----------
ts : pandas.Series
timeseries
resolution : str, optional
interval over which to calculate the ratio
default: resolution of the input ti... | python | def load_factor(ts, resolution=None, norm=None):
"""
Calculate the ratio of input vs. norm over a given interval.
Parameters
----------
ts : pandas.Series
timeseries
resolution : str, optional
interval over which to calculate the ratio
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christophertbrown/bioscripts | ctbBio/besthits.py | top_hits | def top_hits(hits, num, column, reverse):
"""
get top hits after sorting by column number
"""
hits.sort(key = itemgetter(column), reverse = reverse)
for hit in hits[0:num]:
yield hit | python | def top_hits(hits, num, column, reverse):
"""
get top hits after sorting by column number
"""
hits.sort(key = itemgetter(column), reverse = reverse)
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christophertbrown/bioscripts | ctbBio/besthits.py | numBlast_sort | def numBlast_sort(blast, numHits, evalueT, bitT):
"""
parse b6 output with sorting
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header = ['#query', 'target', 'pident', 'alen', 'mismatch', 'gapopen',
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yield header
hmm = {h:[] for h in header}
for line in blast:
... | python | def numBlast_sort(blast, numHits, evalueT, bitT):
"""
parse b6 output with sorting
"""
header = ['#query', 'target', 'pident', 'alen', 'mismatch', 'gapopen',
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"""
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christophertbrown/bioscripts | ctbBio/besthits.py | numDomtblout | def numDomtblout(domtblout, numHits, evalueT, bitT, sort):
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parse hmm domain table output
this version is faster but does not work unless the table is sorted
"""
if sort is True:
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head... | python | def numDomtblout(domtblout, numHits, evalueT, bitT, sort):
"""
parse hmm domain table output
this version is faster but does not work unless the table is sorted
"""
if sort is True:
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christophertbrown/bioscripts | ctbBio/stockholm2fa.py | stock2fa | def stock2fa(stock):
"""
convert stockholm to fasta
"""
seqs = {}
for line in stock:
if line.startswith('#') is False and line.startswith(' ') is False and len(line) > 3:
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id = id.rsplit('/', 1)[0]
id = re.split('[0-9]\|', id,... | python | def stock2fa(stock):
"""
convert stockholm to fasta
"""
seqs = {}
for line in stock:
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opengridcc/opengrid | opengrid/library/utils.py | week_schedule | def week_schedule(index, on_time=None, off_time=None, off_days=None):
""" Return boolean time series following given week schedule.
Parameters
----------
index : pandas.DatetimeIndex
Datetime index
on_time : str or datetime.time
Daily opening time. Default: '09:00'
off_time : st... | python | def week_schedule(index, on_time=None, off_time=None, off_days=None):
""" Return boolean time series following given week schedule.
Parameters
----------
index : pandas.DatetimeIndex
Datetime index
on_time : str or datetime.time
Daily opening time. Default: '09:00'
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opengridcc/opengrid | opengrid/library/plotting.py | carpet | def carpet(timeseries, **kwargs):
"""
Draw a carpet plot of a pandas timeseries.
The carpet plot reads like a letter. Every day one line is added to the
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(evening).
The color denotes the level of consumption and is scale... | python | def carpet(timeseries, **kwargs):
"""
Draw a carpet plot of a pandas timeseries.
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christophertbrown/bioscripts | ctbBio/compare_aligned.py | calc_pident_ignore_gaps | def calc_pident_ignore_gaps(a, b):
"""
calculate percent identity
"""
m = 0 # matches
mm = 0 # mismatches
for A, B in zip(list(a), list(b)):
if A == '-' or A == '.' or B == '-' or B == '.':
continue
if A == B:
m += 1
else:
mm += 1
t... | python | def calc_pident_ignore_gaps(a, b):
"""
calculate percent identity
"""
m = 0 # matches
mm = 0 # mismatches
for A, B in zip(list(a), list(b)):
if A == '-' or A == '.' or B == '-' or B == '.':
continue
if A == B:
m += 1
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christophertbrown/bioscripts | ctbBio/compare_aligned.py | remove_gaps | def remove_gaps(A, B):
"""
skip column if either is a gap
"""
a_seq, b_seq = [], []
for a, b in zip(list(A), list(B)):
if a == '-' or a == '.' or b == '-' or b == '.':
continue
a_seq.append(a)
b_seq.append(b)
return ''.join(a_seq), ''.join(b_seq) | python | def remove_gaps(A, B):
"""
skip column if either is a gap
"""
a_seq, b_seq = [], []
for a, b in zip(list(A), list(B)):
if a == '-' or a == '.' or b == '-' or b == '.':
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christophertbrown/bioscripts | ctbBio/compare_aligned.py | compare_seqs | def compare_seqs(seqs):
"""
compare pairs of sequences
"""
A, B, ignore_gaps = seqs
a, b = A[1], B[1] # actual sequences
if len(a) != len(b):
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exit()
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pident = calc_pident_ignore_gaps(a, b... | python | def compare_seqs(seqs):
"""
compare pairs of sequences
"""
A, B, ignore_gaps = seqs
a, b = A[1], B[1] # actual sequences
if len(a) != len(b):
print('# reads are not the same length', file=sys.stderr)
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christophertbrown/bioscripts | ctbBio/compare_aligned.py | compare_seqs_leven | def compare_seqs_leven(seqs):
"""
calculate Levenshtein ratio of sequences
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a, b = remove_gaps(A[1], B[1]) # actual sequences
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exit()
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return A... | python | def compare_seqs_leven(seqs):
"""
calculate Levenshtein ratio of sequences
"""
A, B, ignore_gaps = seqs
a, b = remove_gaps(A[1], B[1]) # actual sequences
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christophertbrown/bioscripts | ctbBio/compare_aligned.py | pairwise_compare | def pairwise_compare(afa, leven, threads, print_list, ignore_gaps):
"""
make pairwise sequence comparisons between aligned sequences
"""
# load sequences into dictionary
seqs = {seq[0]: seq for seq in nr_fasta([afa], append_index = True)}
num_seqs = len(seqs)
# define all pairs
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"""
make pairwise sequence comparisons between aligned sequences
"""
# load sequences into dictionary
seqs = {seq[0]: seq for seq in nr_fasta([afa], append_index = True)}
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christophertbrown/bioscripts | ctbBio/compare_aligned.py | print_pairwise | def print_pairwise(pw, median = False):
"""
print matrix of pidents to stdout
"""
names = sorted(set([i for i in pw]))
if len(names) != 0:
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else:
yield ['#'] + names
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"""
print matrix of pidents to stdout
"""
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christophertbrown/bioscripts | ctbBio/compare_aligned.py | print_comps | def print_comps(comps):
"""
print stats for comparisons
"""
if comps == []:
print('n/a')
else:
print('# min: %s, max: %s, mean: %s' % \
(min(comps), max(comps), np.mean(comps))) | python | def print_comps(comps):
"""
print stats for comparisons
"""
if comps == []:
print('n/a')
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christophertbrown/bioscripts | ctbBio/compare_aligned.py | compare_clades | def compare_clades(pw):
"""
print min. pident within each clade and then matrix of between-clade max.
"""
names = sorted(set([i for i in pw]))
for i in range(0, 4):
wi, bt = {}, {}
for a in names:
for b in pw[a]:
if ';' not in a or ';' not in b:
... | python | def compare_clades(pw):
"""
print min. pident within each clade and then matrix of between-clade max.
"""
names = sorted(set([i for i in pw]))
for i in range(0, 4):
wi, bt = {}, {}
for a in names:
for b in pw[a]:
if ';' not in a or ';' not in b:
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christophertbrown/bioscripts | ctbBio/compare_aligned.py | matrix2dictionary | def matrix2dictionary(matrix):
"""
convert matrix to dictionary of comparisons
"""
pw = {}
for line in matrix:
line = line.strip().split('\t')
if line[0].startswith('#'):
names = line[1:]
continue
a = line[0]
for i, pident in enumerate(line[1:]... | python | def matrix2dictionary(matrix):
"""
convert matrix to dictionary of comparisons
"""
pw = {}
for line in matrix:
line = line.strip().split('\t')
if line[0].startswith('#'):
names = line[1:]
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mkouhei/bootstrap-py | bootstrap_py/commands.py | setoption | def setoption(parser, metadata=None):
"""Set argument parser option."""
parser.add_argument('-v', action='version',
version=__version__)
subparsers = parser.add_subparsers(help='sub commands help')
create_cmd = subparsers.add_parser('create')
create_cmd.add_argument('name',
... | python | def setoption(parser, metadata=None):
"""Set argument parser option."""
parser.add_argument('-v', action='version',
version=__version__)
subparsers = parser.add_subparsers(help='sub commands help')
create_cmd = subparsers.add_parser('create')
create_cmd.add_argument('name',
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mkouhei/bootstrap-py | bootstrap_py/commands.py | parse_options | def parse_options(metadata):
"""Parse argument options."""
parser = argparse.ArgumentParser(description='%(prog)s usage:',
prog=__prog__)
setoption(parser, metadata=metadata)
return parser | python | def parse_options(metadata):
"""Parse argument options."""
parser = argparse.ArgumentParser(description='%(prog)s usage:',
prog=__prog__)
setoption(parser, metadata=metadata)
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mkouhei/bootstrap-py | bootstrap_py/commands.py | main | def main():
"""Execute main processes."""
try:
pkg_version = Update()
if pkg_version.updatable():
pkg_version.show_message()
metadata = control.retreive_metadata()
parser = parse_options(metadata)
argvs = sys.argv
if len(argvs) <= 1:
parser... | python | def main():
"""Execute main processes."""
try:
pkg_version = Update()
if pkg_version.updatable():
pkg_version.show_message()
metadata = control.retreive_metadata()
parser = parse_options(metadata)
argvs = sys.argv
if len(argvs) <= 1:
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mkouhei/bootstrap-py | bootstrap_py/package.py | PackageData._check_or_set_default_params | def _check_or_set_default_params(self):
"""Check key and set default vaule when it does not exists."""
if not hasattr(self, 'date'):
self._set_param('date', datetime.utcnow().strftime('%Y-%m-%d'))
if not hasattr(self, 'version'):
self._set_param('version', self.default_ve... | python | def _check_or_set_default_params(self):
"""Check key and set default vaule when it does not exists."""
if not hasattr(self, 'date'):
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mkouhei/bootstrap-py | bootstrap_py/package.py | PackageTree.move | def move(self):
"""Move directory from working directory to output directory."""
if not os.path.isdir(self.outdir):
os.makedirs(self.outdir)
shutil.move(self.tmpdir, os.path.join(self.outdir, self.name)) | python | def move(self):
"""Move directory from working directory to output directory."""
if not os.path.isdir(self.outdir):
os.makedirs(self.outdir)
shutil.move(self.tmpdir, os.path.join(self.outdir, self.name)) | [
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mkouhei/bootstrap-py | bootstrap_py/package.py | PackageTree.vcs_init | def vcs_init(self):
"""Initialize VCS repository."""
VCS(os.path.join(self.outdir, self.name), self.pkg_data) | python | def vcs_init(self):
"""Initialize VCS repository."""
VCS(os.path.join(self.outdir, self.name), self.pkg_data) | [
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scottrice/pysteam | pysteam/winutils.py | find_steam_location | def find_steam_location():
"""
Finds the location of the current Steam installation on Windows machines.
Returns None for any non-Windows machines, or for Windows machines where
Steam is not installed.
"""
if registry is None:
return None
key = registry.CreateKey(registry.HKEY_CURRENT_USER,"Software\... | python | def find_steam_location():
"""
Finds the location of the current Steam installation on Windows machines.
Returns None for any non-Windows machines, or for Windows machines where
Steam is not installed.
"""
if registry is None:
return None
key = registry.CreateKey(registry.HKEY_CURRENT_USER,"Software\... | [
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smdabdoub/phylotoast | bin/PCoA_bubble.py | plot_PCoA | def plot_PCoA(cat_data, otu_name, unifrac, names, colors, xr, yr, outDir,
save_as, plot_style):
"""
Plot PCoA principal coordinates scaled by the relative abundances of
otu_name.
"""
fig = plt.figure(figsize=(14, 8))
ax = fig.add_subplot(111)
for i, cat in enumerate(cat_data):... | python | def plot_PCoA(cat_data, otu_name, unifrac, names, colors, xr, yr, outDir,
save_as, plot_style):
"""
Plot PCoA principal coordinates scaled by the relative abundances of
otu_name.
"""
fig = plt.figure(figsize=(14, 8))
ax = fig.add_subplot(111)
for i, cat in enumerate(cat_data):... | [
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smdabdoub/phylotoast | bin/transpose_biom.py | split_by_category | def split_by_category(biom_cols, mapping, category_id):
"""
Split up the column data in a biom table by mapping category value.
"""
columns = defaultdict(list)
for i, col in enumerate(biom_cols):
columns[mapping[col['id']][category_id]].append((i, col))
return columns | python | def split_by_category(biom_cols, mapping, category_id):
"""
Split up the column data in a biom table by mapping category value.
"""
columns = defaultdict(list)
for i, col in enumerate(biom_cols):
columns[mapping[col['id']][category_id]].append((i, col))
return columns | [
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christophertbrown/bioscripts | ctbBio/stockholm2oneline.py | print_line | def print_line(l):
"""
print line if starts with ...
"""
print_lines = ['# STOCKHOLM', '#=GF', '#=GS', ' ']
if len(l.split()) == 0:
return True
for start in print_lines:
if l.startswith(start):
return True
return False | python | def print_line(l):
"""
print line if starts with ...
"""
print_lines = ['# STOCKHOLM', '#=GF', '#=GS', ' ']
if len(l.split()) == 0:
return True
for start in print_lines:
if l.startswith(start):
return True
return False | [
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christophertbrown/bioscripts | ctbBio/stockholm2oneline.py | stock2one | def stock2one(stock):
"""
convert stockholm to single line format
"""
lines = {}
for line in stock:
line = line.strip()
if print_line(line) is True:
yield line
continue
if line.startswith('//'):
continue
ID, seq = line.rsplit(' ', 1... | python | def stock2one(stock):
"""
convert stockholm to single line format
"""
lines = {}
for line in stock:
line = line.strip()
if print_line(line) is True:
yield line
continue
if line.startswith('//'):
continue
ID, seq = line.rsplit(' ', 1... | [
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elbow-jason/Uno-deprecated | uno/helpers.py | math_func | def math_func(f):
"""
Statics the methods. wut.
"""
@wraps(f)
def wrapper(*args, **kwargs):
if len(args) > 0:
return_type = type(args[0])
if kwargs.has_key('return_type'):
return_type = kwargs['return_type']
kwargs.pop('return_type')
re... | python | def math_func(f):
"""
Statics the methods. wut.
"""
@wraps(f)
def wrapper(*args, **kwargs):
if len(args) > 0:
return_type = type(args[0])
if kwargs.has_key('return_type'):
return_type = kwargs['return_type']
kwargs.pop('return_type')
re... | [
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