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pescadores/pescador | examples/mux/mux_files_example.py | npz_generator | def npz_generator(npz_path):
"""Generate data from an npz file."""
npz_data = np.load(npz_path)
X = npz_data['X']
# Y is a binary maxtrix with shape=(n, k), each y will have shape=(k,)
y = npz_data['Y']
n = X.shape[0]
while True:
i = np.random.randint(0, n)
yield {'X': X[i]... | python | def npz_generator(npz_path):
"""Generate data from an npz file."""
npz_data = np.load(npz_path)
X = npz_data['X']
# Y is a binary maxtrix with shape=(n, k), each y will have shape=(k,)
y = npz_data['Y']
n = X.shape[0]
while True:
i = np.random.randint(0, n)
yield {'X': X[i]... | [
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vanheeringen-lab/gimmemotifs | gimmemotifs/utils.py | phyper | def phyper(k, good, bad, N):
""" Current hypergeometric implementation in scipy is broken, so here's the correct version """
pvalues = [phyper_single(x, good, bad, N) for x in range(k + 1, N + 1)]
return np.sum(pvalues) | python | def phyper(k, good, bad, N):
""" Current hypergeometric implementation in scipy is broken, so here's the correct version """
pvalues = [phyper_single(x, good, bad, N) for x in range(k + 1, N + 1)]
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vanheeringen-lab/gimmemotifs | gimmemotifs/utils.py | write_equalwidth_bedfile | def write_equalwidth_bedfile(bedfile, width, outfile):
"""Read input from <bedfile>, set the width of all entries to <width> and
write the result to <outfile>.
Input file needs to be in BED or WIG format."""
BUFSIZE = 10000
f = open(bedfile)
out = open(outfile, "w")
lines = f.readlines(BUF... | python | def write_equalwidth_bedfile(bedfile, width, outfile):
"""Read input from <bedfile>, set the width of all entries to <width> and
write the result to <outfile>.
Input file needs to be in BED or WIG format."""
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vanheeringen-lab/gimmemotifs | gimmemotifs/utils.py | calc_motif_enrichment | def calc_motif_enrichment(sample, background, mtc=None, len_sample=None, len_back=None):
"""Calculate enrichment based on hypergeometric distribution"""
INF = "Inf"
if mtc not in [None, "Bonferroni", "Benjamini-Hochberg", "None"]:
raise RuntimeError("Unknown correction: %s" % mtc)
sig = ... | python | def calc_motif_enrichment(sample, background, mtc=None, len_sample=None, len_back=None):
"""Calculate enrichment based on hypergeometric distribution"""
INF = "Inf"
if mtc not in [None, "Bonferroni", "Benjamini-Hochberg", "None"]:
raise RuntimeError("Unknown correction: %s" % mtc)
sig = ... | [
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vanheeringen-lab/gimmemotifs | gimmemotifs/utils.py | parse_cutoff | def parse_cutoff(motifs, cutoff, default=0.9):
""" Provide either a file with one cutoff per motif or a single cutoff
returns a hash with motif id as key and cutoff as value
"""
cutoffs = {}
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if line !... | python | def parse_cutoff(motifs, cutoff, default=0.9):
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cutoffs = {}
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vanheeringen-lab/gimmemotifs | gimmemotifs/utils.py | determine_file_type | def determine_file_type(fname):
"""
Detect file type.
The following file types are supported:
BED, narrowPeak, FASTA, list of chr:start-end regions
If the extension is bed, fa, fasta or narrowPeak, we will believe this
without checking!
Parameters
----------
fname : str
Fil... | python | def determine_file_type(fname):
"""
Detect file type.
The following file types are supported:
BED, narrowPeak, FASTA, list of chr:start-end regions
If the extension is bed, fa, fasta or narrowPeak, we will believe this
without checking!
Parameters
----------
fname : str
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vanheeringen-lab/gimmemotifs | gimmemotifs/utils.py | get_seqs_type | def get_seqs_type(seqs):
"""
automagically determine input type
the following types are detected:
- Fasta object
- FASTA file
- list of regions
- region file
- BED file
"""
region_p = re.compile(r'^(.+):(\d+)-(\d+)$')
if isinstance(seqs, Fasta):
re... | python | def get_seqs_type(seqs):
"""
automagically determine input type
the following types are detected:
- Fasta object
- FASTA file
- list of regions
- region file
- BED file
"""
region_p = re.compile(r'^(.+):(\d+)-(\d+)$')
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vanheeringen-lab/gimmemotifs | gimmemotifs/utils.py | file_checksum | def file_checksum(fname):
"""Return md5 checksum of file.
Note: only works for files < 4GB.
Parameters
----------
filename : str
File used to calculate checksum.
Returns
-------
checkum : str
"""
size = os.path.getsize(fname)
with open(fname, "r+") as f:
... | python | def file_checksum(fname):
"""Return md5 checksum of file.
Note: only works for files < 4GB.
Parameters
----------
filename : str
File used to calculate checksum.
Returns
-------
checkum : str
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size = os.path.getsize(fname)
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vanheeringen-lab/gimmemotifs | gimmemotifs/genome_index.py | download_annotation | def download_annotation(genomebuild, gene_file):
"""
Download gene annotation from UCSC based on genomebuild.
Will check UCSC, Ensembl and RefSeq annotation.
Parameters
----------
genomebuild : str
UCSC genome name.
gene_file : str
Output file name.
"""
pred_bin = ... | python | def download_annotation(genomebuild, gene_file):
"""
Download gene annotation from UCSC based on genomebuild.
Will check UCSC, Ensembl and RefSeq annotation.
Parameters
----------
genomebuild : str
UCSC genome name.
gene_file : str
Output file name.
"""
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vanheeringen-lab/gimmemotifs | gimmemotifs/genome_index.py | GenomeIndex._check_dir | def _check_dir(self, dirname):
""" Check if dir exists, if not: give warning and die"""
if not os.path.exists(dirname):
print("Directory %s does not exist!" % dirname)
sys.exit(1) | python | def _check_dir(self, dirname):
""" Check if dir exists, if not: give warning and die"""
if not os.path.exists(dirname):
print("Directory %s does not exist!" % dirname)
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vanheeringen-lab/gimmemotifs | gimmemotifs/genome_index.py | GenomeIndex._make_index | def _make_index(self, fasta, index):
""" Index a single, one-sequence fasta-file"""
out = open(index, "wb")
f = open(fasta)
# Skip first line of fasta-file
line = f.readline()
offset = f.tell()
line = f.readline()
while line:
out.write(pack(sel... | python | def _make_index(self, fasta, index):
""" Index a single, one-sequence fasta-file"""
out = open(index, "wb")
f = open(fasta)
# Skip first line of fasta-file
line = f.readline()
offset = f.tell()
line = f.readline()
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vanheeringen-lab/gimmemotifs | gimmemotifs/genome_index.py | GenomeIndex.create_index | def create_index(self,fasta_dir=None, index_dir=None):
"""Index all fasta-files in fasta_dir (one sequence per file!) and
store the results in index_dir"""
# Use default directories if they are not supplied
if not fasta_dir:
fasta_dir = self.fasta_dir
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fasta_dir = self.fasta_dir
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vanheeringen-lab/gimmemotifs | gimmemotifs/genome_index.py | GenomeIndex._read_index_file | def _read_index_file(self):
"""read the param_file, index_dir should already be set """
param_file = os.path.join(self.index_dir, self.param_file)
with open(param_file) as f:
for line in f.readlines():
(name, fasta_file, index_file, line_size, total_size) = line.strip... | python | def _read_index_file(self):
"""read the param_file, index_dir should already be set """
param_file = os.path.join(self.index_dir, self.param_file)
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vanheeringen-lab/gimmemotifs | gimmemotifs/genome_index.py | GenomeIndex._read_seq_from_fasta | def _read_seq_from_fasta(self, fasta, offset, nr_lines):
""" retrieve a number of lines from a fasta file-object, starting at offset"""
fasta.seek(offset)
lines = [fasta.readline().strip() for _ in range(nr_lines)]
return "".join(lines) | python | def _read_seq_from_fasta(self, fasta, offset, nr_lines):
""" retrieve a number of lines from a fasta file-object, starting at offset"""
fasta.seek(offset)
lines = [fasta.readline().strip() for _ in range(nr_lines)]
return "".join(lines) | [
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vanheeringen-lab/gimmemotifs | gimmemotifs/genome_index.py | GenomeIndex.get_sequences | def get_sequences(self, chr, coords):
""" Retrieve multiple sequences from same chr (RC not possible yet)"""
# Check if we have an index_dir
if not self.index_dir:
print("Index dir is not defined!")
sys.exit()
# retrieve all information for this specific sequ... | python | def get_sequences(self, chr, coords):
""" Retrieve multiple sequences from same chr (RC not possible yet)"""
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vanheeringen-lab/gimmemotifs | gimmemotifs/genome_index.py | GenomeIndex.get_sequence | def get_sequence(self, chrom, start, end, strand=None):
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | get_tool | def get_tool(name):
"""
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name : str
Name of the tool (case-insensitive).
Returns
-------
tool : MotifProgram instance
"""
tool = name.lower()
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"""
Returns an instance of a specific tool.
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name : str
Name of the tool (case-insensitive).
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tool : MotifProgram instance
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | locate_tool | def locate_tool(name, verbose=True):
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Returns the binary of a tool.
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name : str
Name of the tool (case-insensitive).
Returns
-------
tool_bin : str
Binary of tool.
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"""
Returns the binary of a tool.
Parameters
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name : str
Name of the tool (case-insensitive).
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tool_bin : str
Binary of tool.
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | MotifProgram.bin | def bin(self):
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Returns
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command : str
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"""
Get the command used to run the tool.
Returns
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command : str
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | MotifProgram.is_installed | def is_installed(self):
"""
Check if the tool is installed.
Returns
-------
is_installed : bool
True if the tool is installed.
"""
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"""
Check if the tool is installed.
Returns
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is_installed : bool
True if the tool is installed.
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | MotifProgram.run | def run(self, fastafile, params=None, tmp=None):
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Run the tool and predict motifs from a FASTA file.
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----------
fastafile : str
Name of the FASTA input file.
params : dict, optional
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | XXmotif._parse_params | def _parse_params(self, params=None):
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | XXmotif._run_program | def _run_program(self, bin, fastafile, params=None):
"""
Run XXmotif and predict motifs from a FASTA file.
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----------
bin : str
Command used to run the tool.
fastafile : str
Name of the FASTA input file.
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | Homer._run_program | def _run_program(self, bin, fastafile, params=None):
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Command used to run the tool.
fastafile : str
Name of the FASTA input file.
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | BioProspector.parse | def parse(self, fo):
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Convert BioProspector output to motifs
Parameters
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fo : file-like
File object containing BioProspector output.
Returns
-------
motifs : list
List of Motif instances.
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fo : file-like
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | Hms._run_program | def _run_program(self, bin, fastafile, params=None):
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bin : str
Command used to run the tool.
fastafile : str
Name of the FASTA input file.
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | Hms.parse | def parse(self, fo):
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fo : file-like
File object containing HMS output.
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motifs : list
List of Motif instances.
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | Amd._run_program | def _run_program(self, bin, fastafile, params=None):
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Name of the FASTA input file.
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | Amd.parse | def parse(self, fo):
"""
Convert AMD output to motifs
Parameters
----------
fo : file-like
File object containing AMD output.
Returns
-------
motifs : list
List of Motif instances.
"""
motifs = []
... | python | def parse(self, fo):
"""
Convert AMD output to motifs
Parameters
----------
fo : file-like
File object containing AMD output.
Returns
-------
motifs : list
List of Motif instances.
"""
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | Improbizer.parse | def parse(self, fo):
"""
Convert Improbizer output to motifs
Parameters
----------
fo : file-like
File object containing Improbizer output.
Returns
-------
motifs : list
List of Motif instances.
"""
motifs ... | python | def parse(self, fo):
"""
Convert Improbizer output to motifs
Parameters
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fo : file-like
File object containing Improbizer output.
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List of Motif instances.
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | Trawler._run_program | def _run_program(self, bin, fastafile, params=None):
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Run Trawler and predict motifs from a FASTA file.
Parameters
----------
bin : str
Command used to run the tool.
fastafile : str
Name of the FASTA input file.
params : dict,... | python | def _run_program(self, bin, fastafile, params=None):
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Run Trawler and predict motifs from a FASTA file.
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Command used to run the tool.
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Name of the FASTA input file.
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | Weeder._run_program | def _run_program(self, bin,fastafile, params=None):
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Command used to run the tool.
fastafile : str
Name of the FASTA input file.
params : dict, o... | python | def _run_program(self, bin,fastafile, params=None):
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | MotifSampler._parse_params | def _parse_params(self, params=None):
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"""
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"""
Parse parameters.
Combine default and user-defined parameters.
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | MotifSampler._run_program | def _run_program(self, bin, fastafile, params=None):
"""
Run MotifSampler and predict motifs from a FASTA file.
Parameters
----------
bin : str
Command used to run the tool.
fastafile : str
Name of the FASTA input file.
params : ... | python | def _run_program(self, bin, fastafile, params=None):
"""
Run MotifSampler and predict motifs from a FASTA file.
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Command used to run the tool.
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Name of the FASTA input file.
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | MotifSampler.parse | def parse(self, fo):
"""
Convert MotifSampler output to motifs
Parameters
----------
fo : file-like
File object containing MotifSampler output.
Returns
-------
motifs : list
List of Motif instances.
"""
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"""
Convert MotifSampler output to motifs
Parameters
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File object containing MotifSampler output.
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | MotifSampler.parse_out | def parse_out(self, fo):
"""
Convert MotifSampler output to motifs
Parameters
----------
fo : file-like
File object containing MotifSampler output.
Returns
-------
motifs : list
List of Motif instances.
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"""
Convert MotifSampler output to motifs
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File object containing MotifSampler output.
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | MDmodule._run_program | def _run_program(self, bin, fastafile, params=None):
"""
Run MDmodule and predict motifs from a FASTA file.
Parameters
----------
bin : str
Command used to run the tool.
fastafile : str
Name of the FASTA input file.
params : dict... | python | def _run_program(self, bin, fastafile, params=None):
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | MDmodule.parse | def parse(self, fo):
"""
Convert MDmodule output to motifs
Parameters
----------
fo : file-like
File object containing MDmodule output.
Returns
-------
motifs : list
List of Motif instances.
"""
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Convert MDmodule output to motifs
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File object containing MDmodule output.
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | ChIPMunk._parse_params | def _parse_params(self, params=None):
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | ChIPMunk._run_program | def _run_program(self, bin, fastafile, params=None):
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Run ChIPMunk and predict motifs from a FASTA file.
Parameters
----------
bin : str
Command used to run the tool.
fastafile : str
Name of the FASTA input file.
params : dict... | python | def _run_program(self, bin, fastafile, params=None):
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | ChIPMunk.parse | def parse(self, fo):
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Convert ChIPMunk output to motifs
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----------
fo : file-like
File object containing ChIPMunk output.
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-------
motifs : list
List of Motif instances.
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Convert ChIPMunk output to motifs
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | Posmo._run_program | def _run_program(self, bin, fastafile, params=None):
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Run Posmo and predict motifs from a FASTA file.
Parameters
----------
bin : str
Command used to run the tool.
fastafile : str
Name of the FASTA input file.
params : dict, o... | python | def _run_program(self, bin, fastafile, params=None):
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | Posmo.parse | def parse(self, fo, width, seed=None):
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Convert Posmo output to motifs
Parameters
----------
fo : file-like
File object containing Posmo output.
Returns
-------
motifs : list
List of Motif instances.
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Convert Posmo output to motifs
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File object containing Posmo output.
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | Gadem.parse | def parse(self, fo):
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Command used to run the tool.
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Name of the FASTA input file.
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | Meme._run_program | def _run_program(self, bin, fastafile, params=None):
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Command used to run the tool.
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Name of the FASTA input file.
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vanheeringen-lab/gimmemotifs | gimmemotifs/tools.py | Meme.parse | def parse(self, fo):
"""
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List of Motif instances.
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vanheeringen-lab/gimmemotifs | gimmemotifs/maelstrom.py | scan_to_table | def scan_to_table(input_table, genome, scoring, pwmfile=None, ncpus=None):
"""Scan regions in input table with motifs.
Parameters
----------
input_table : str
Filename of input table. Can be either a text-separated tab file or a
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Filename of input table. Can be either a text-separated tab file or a
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vanheeringen-lab/gimmemotifs | gimmemotifs/maelstrom.py | run_maelstrom | def run_maelstrom(infile, genome, outdir, pwmfile=None, plot=True, cluster=False,
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vanheeringen-lab/gimmemotifs | gimmemotifs/maelstrom.py | MaelstromResult.plot_heatmap | def plot_heatmap(self, kind="final", min_freq=0.01, threshold=2, name=True, max_len=50, aspect=1, **kwargs):
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kind : str, optional
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vanheeringen-lab/gimmemotifs | gimmemotifs/maelstrom.py | MaelstromResult.plot_scores | def plot_scores(self, motifs, name=True, max_len=50):
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biosustain/swiglpk | scripts/find_swiglpk_version.py | get_version | def get_version(package, url_pattern=URL_PATTERN):
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aouyar/PyMunin | pysysinfo/util.py | parse_value | def parse_value(val, parsebool=False):
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aouyar/PyMunin | pysysinfo/util.py | exec_command | def exec_command(args, env=None):
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@param env: Dictionary of environment variables.
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aouyar/PyMunin | pysysinfo/util.py | NestedDict.set_nested | def set_nested(self, klist, value):
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aouyar/PyMunin | pysysinfo/util.py | TableFilter.unregisterFilter | def unregisterFilter(self, column):
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ContextLab/quail | quail/analysis/analysis.py | analyze | def analyze(egg, subjgroup=None, listgroup=None, subjname='Subject',
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aouyar/PyMunin | pymunin/plugins/tomcatstats.py | MuninTomcatPlugin.retrieveVals | def retrieveVals(self):
"""Retrieve values for graphs."""
if self.hasGraph('tomcat_memory'):
stats = self._tomcatInfo.getMemoryStats()
self.setGraphVal('tomcat_memory', 'used',
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self.setGraphVal('tomcat_memo... | python | def retrieveVals(self):
"""Retrieve values for graphs."""
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rho : numpy.ndarray (N,)
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aouyar/PyMunin | pymunin/plugins/nginxstats.py | MuninNginxPlugin.retrieveVals | def retrieveVals(self):
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aouyar/PyMunin | pymunin/plugins/nginxstats.py | MuninNginxPlugin.autoconf | def autoconf(self):
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aouyar/PyMunin | pysysinfo/phpfpm.py | PHPfpmInfo.getStats | def getStats(self):
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aouyar/PyMunin | pymunin/plugins/phpapcstats.py | MuninPHPapcPlugin.retrieveVals | def retrieveVals(self):
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aouyar/PyMunin | pysysinfo/varnish.py | VarnishInfo.getStats | def getStats(self):
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aouyar/PyMunin | pysysinfo/varnish.py | VarnishInfo.getDesc | def getDesc(self, entry):
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aouyar/PyMunin | pymunin/plugins/phpopcstats.py | MuninPHPOPCPlugin.retrieveVals | def retrieveVals(self):
"""Retrieve values for graphs."""
opcinfo = OPCinfo(self._host, self._port, self._user, self._password,
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stats = opcinfo.getAllStats()
if self.hasGraph('php_opc_memory') and stats:
mem = stat... | python | def retrieveVals(self):
"""Retrieve values for graphs."""
opcinfo = OPCinfo(self._host, self._port, self._user, self._password,
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stats = opcinfo.getAllStats()
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aouyar/PyMunin | pymunin/plugins/phpopcstats.py | MuninPHPOPCPlugin.autoconf | def autoconf(self):
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@return: True if plugin can be auto-configured, False otherwise.
"""
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ContextLab/quail | quail/analysis/clustering.py | fingerprint_helper | def fingerprint_helper(egg, permute=False, n_perms=1000,
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Computes clustering along a set of feature dimensions
Parameters
----------
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Data to analyze
dist_funcs : dict
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ContextLab/quail | quail/analysis/clustering.py | compute_feature_weights | def compute_feature_weights(pres_list, rec_list, feature_list, distances):
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pres_list : list
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list of recalled words
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ContextLab/quail | quail/analysis/lagcrp.py | lagcrp_helper | def lagcrp_helper(egg, match='exact', distance='euclidean',
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aouyar/PyMunin | pymunin/plugins/diskiostats.py | MuninDiskIOplugin.retrieveVals | def retrieveVals(self):
"""Retrieve values for graphs."""
if self._diskList:
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if self._mdList:
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aouyar/PyMunin | pymunin/plugins/diskiostats.py | MuninDiskIOplugin._configDevRequests | def _configDevRequests(self, namestr, titlestr, devlist):
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@param namestr: Field name component indicating device type.
@param titlestr: Title component indicating device type.
@param devlist: List of devices.
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aouyar/PyMunin | pymunin/plugins/diskiostats.py | MuninDiskIOplugin._fetchDevAll | def _fetchDevAll(self, namestr, devlist, statsfunc):
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aouyar/PyMunin | pymunin/plugins/redisstats.py | RedisPlugin.retrieveVals | def retrieveVals(self):
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aouyar/PyMunin | pymunin/plugins/sysstats.py | MuninSysStatsPlugin.retrieveVals | def retrieveVals(self):
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mattseymour/python-env | dotenv/__init__.py | get | def get(key, default=None):
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] | train | https://github.com/mattseymour/python-env/blob/5ac09b1685fbba75c174c79cb40287aa49d0f208/dotenv/__init__.py#L67-L94 |
aouyar/PyMunin | pysysinfo/apache.py | ApacheInfo.initStats | def initStats(self):
"""Query and parse Apache Web Server Status Page."""
url = "%s://%s:%d/%s?auto" % (self._proto, self._host, self._port,
self._statuspath)
response = util.get_url(url, self._user, self._password)
self._statusDict = {}
f... | python | def initStats(self):
"""Query and parse Apache Web Server Status Page."""
url = "%s://%s:%d/%s?auto" % (self._proto, self._host, self._port,
self._statuspath)
response = util.get_url(url, self._user, self._password)
self._statusDict = {}
f... | [
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ContextLab/quail | quail/egg.py | Egg.get_pres_features | def get_pres_features(self, features=None):
"""
Returns a df of features for presented items
"""
if features is None:
features = self.dist_funcs.keys()
elif not isinstance(features, list):
features = [features]
return self.pres.applymap(lambda x: {... | python | def get_pres_features(self, features=None):
"""
Returns a df of features for presented items
"""
if features is None:
features = self.dist_funcs.keys()
elif not isinstance(features, list):
features = [features]
return self.pres.applymap(lambda x: {... | [
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ContextLab/quail | quail/egg.py | Egg.get_rec_features | def get_rec_features(self, features=None):
"""
Returns a df of features for recalled items
"""
if features is None:
features = self.dist_funcs.keys()
elif not isinstance(features, list):
features = [features]
return self.rec.applymap(lambda x: {k:v... | python | def get_rec_features(self, features=None):
"""
Returns a df of features for recalled items
"""
if features is None:
features = self.dist_funcs.keys()
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features = [features]
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ContextLab/quail | quail/egg.py | Egg.info | def info(self):
"""
Print info about the data egg
"""
print('Number of subjects: ' + str(self.n_subjects))
print('Number of lists per subject: ' + str(self.n_lists))
print('Number of words per list: ' + str(self.list_length))
print('Date created: ' + str(self.date... | python | def info(self):
"""
Print info about the data egg
"""
print('Number of subjects: ' + str(self.n_subjects))
print('Number of lists per subject: ' + str(self.n_lists))
print('Number of words per list: ' + str(self.list_length))
print('Date created: ' + str(self.date... | [
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ContextLab/quail | quail/egg.py | Egg.save | def save(self, fname, compression='blosc'):
"""
Save method for the Egg object
The data will be saved as a 'egg' file, which is a dictionary containing
the elements of a Egg saved in the hd5 format using
`deepdish`.
Parameters
----------
fname : str
... | python | def save(self, fname, compression='blosc'):
"""
Save method for the Egg object
The data will be saved as a 'egg' file, which is a dictionary containing
the elements of a Egg saved in the hd5 format using
`deepdish`.
Parameters
----------
fname : str
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fname : str
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ContextLab/quail | quail/egg.py | FriedEgg.save | def save(self, fname, compression='blosc'):
"""
Save method for the FriedEgg object
The data will be saved as a 'fegg' file, which is a dictionary containing
the elements of a FriedEgg saved in the hd5 format using
`deepdish`.
Parameters
----------
fnam... | python | def save(self, fname, compression='blosc'):
"""
Save method for the FriedEgg object
The data will be saved as a 'fegg' file, which is a dictionary containing
the elements of a FriedEgg saved in the hd5 format using
`deepdish`.
Parameters
----------
fnam... | [
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fname : str
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ContextLab/quail | quail/analysis/pnr.py | pnr_helper | def pnr_helper(egg, position, match='exact',
distance='euclidean', features=None):
"""
Computes probability of a word being recalled nth (in the appropriate recall
list), given its presentation position. Note: zero indexed
Parameters
----------
egg : quail.Egg
Data to a... | python | def pnr_helper(egg, position, match='exact',
distance='euclidean', features=None):
"""
Computes probability of a word being recalled nth (in the appropriate recall
list), given its presentation position. Note: zero indexed
Parameters
----------
egg : quail.Egg
Data to a... | [
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Parameters
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egg : quail.Egg
Data to analyze
position : int
Position of item to be analyzed
match : str (exact, best or smooth)
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aouyar/PyMunin | pymunin/plugins/apachestats.py | MuninApachePlugin.retrieveVals | def retrieveVals(self):
"""Retrieve values for graphs."""
apacheInfo = ApacheInfo(self._host, self._port,
self._user, self._password,
self._statuspath, self._ssl)
stats = apacheInfo.getServerStats()
if self.hasGraph('apache... | python | def retrieveVals(self):
"""Retrieve values for graphs."""
apacheInfo = ApacheInfo(self._host, self._port,
self._user, self._password,
self._statuspath, self._ssl)
stats = apacheInfo.getServerStats()
if self.hasGraph('apache... | [
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aouyar/PyMunin | pymunin/plugins/apachestats.py | MuninApachePlugin.autoconf | def autoconf(self):
"""Implements Munin Plugin Auto-Configuration Option.
@return: True if plugin can be auto-configured, False otherwise.
"""
apacheInfo = ApacheInfo(self._host, self._port,
self._user, self._password,
... | python | def autoconf(self):
"""Implements Munin Plugin Auto-Configuration Option.
@return: True if plugin can be auto-configured, False otherwise.
"""
apacheInfo = ApacheInfo(self._host, self._port,
self._user, self._password,
... | [
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@return: True if plugin can be auto-configured, False otherwise. | [
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aouyar/PyMunin | pymunin/plugins/ntphostoffsets.py | MuninNTPhostOffsetsPlugin.retrieveVals | def retrieveVals(self):
"""Retrieve values for graphs."""
ntpinfo = NTPinfo()
ntpstats = ntpinfo.getHostOffsets(self._remoteHosts)
if ntpstats:
for host in self._remoteHosts:
hostkey = re.sub('\.', '_', host)
hoststats = ntpstats.get(host)
... | python | def retrieveVals(self):
"""Retrieve values for graphs."""
ntpinfo = NTPinfo()
ntpstats = ntpinfo.getHostOffsets(self._remoteHosts)
if ntpstats:
for host in self._remoteHosts:
hostkey = re.sub('\.', '_', host)
hoststats = ntpstats.get(host)
... | [
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