sentence1 stringlengths 52 3.87M | sentence2 stringlengths 1 47.2k | label stringclasses 1
value |
|---|---|---|
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]... | Generate data from an npz file. | entailment |
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) | Current hypergeometric implementation in scipy is broken, so here's the correct version | entailment |
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... | 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. | entailment |
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 = ... | Calculate enrichment based on hypergeometric distribution | entailment |
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 = {}
if os.path.isfile(str(cutoff)):
for i,line in enumerate(open(cutoff)):
if line !... | 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 | entailment |
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... | 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
File name.
Returns
-------
filetyp... | entailment |
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... | automagically determine input type
the following types are detected:
- Fasta object
- FASTA file
- list of regions
- region file
- BED file | entailment |
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:
... | Return md5 checksum of file.
Note: only works for files < 4GB.
Parameters
----------
filename : str
File used to calculate checksum.
Returns
-------
checkum : str | entailment |
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 = ... | 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. | entailment |
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) | Check if dir exists, if not: give warning and die | entailment |
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... | Index a single, one-sequence fasta-file | entailment |
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
if not... | Index all fasta-files in fasta_dir (one sequence per file!) and
store the results in index_dir | entailment |
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... | read the param_file, index_dir should already be set | entailment |
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) | retrieve a number of lines from a fasta file-object, starting at offset | entailment |
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... | Retrieve multiple sequences from same chr (RC not possible yet) | entailment |
def get_sequence(self, chrom, start, end, strand=None):
""" Retrieve a sequence """
# 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 sequence
fasta_file =... | Retrieve a sequence | entailment |
def get_size(self, chrom=None):
""" Return the sizes of all sequences in the index, or the size of chrom if specified
as an optional argument """
if len(self.size) == 0:
raise LookupError("no chromosomes in index, is the index correct?")
if chrom:
if chrom in sel... | Return the sizes of all sequences in the index, or the size of chrom if specified
as an optional argument | entailment |
def get_tool(name):
"""
Returns an instance of a specific tool.
Parameters
----------
name : str
Name of the tool (case-insensitive).
Returns
-------
tool : MotifProgram instance
"""
tool = name.lower()
if tool not in __tools__:
raise ValueError("Tool {0} n... | Returns an instance of a specific tool.
Parameters
----------
name : str
Name of the tool (case-insensitive).
Returns
-------
tool : MotifProgram instance | entailment |
def locate_tool(name, verbose=True):
"""
Returns the binary of a tool.
Parameters
----------
name : str
Name of the tool (case-insensitive).
Returns
-------
tool_bin : str
Binary of tool.
"""
m = get_tool(name)
tool_bin = which(m.cmd)
if tool_bin:
... | Returns the binary of a tool.
Parameters
----------
name : str
Name of the tool (case-insensitive).
Returns
-------
tool_bin : str
Binary of tool. | entailment |
def bin(self):
"""
Get the command used to run the tool.
Returns
-------
command : str
The tool system command.
"""
if self.local_bin:
return self.local_bin
else:
return self.config.bin(self.name) | Get the command used to run the tool.
Returns
-------
command : str
The tool system command. | entailment |
def is_installed(self):
"""
Check if the tool is installed.
Returns
-------
is_installed : bool
True if the tool is installed.
"""
return self.is_configured() and os.access(self.bin(), os.X_OK) | Check if the tool is installed.
Returns
-------
is_installed : bool
True if the tool is installed. | entailment |
def run(self, fastafile, params=None, tmp=None):
"""
Run the tool and predict motifs from a FASTA file.
Parameters
----------
fastafile : str
Name of the FASTA input file.
params : dict, optional
Optional parameters. For some of the tools require... | Run the tool and predict motifs from a FASTA file.
Parameters
----------
fastafile : str
Name of the FASTA input file.
params : dict, optional
Optional parameters. For some of the tools required parameters
are passed using this dictionary.
t... | entailment |
def _parse_params(self, params=None):
"""
Parse parameters.
Combine default and user-defined parameters.
"""
prm = self.default_params.copy()
if params is not None:
prm.update(params)
if prm["background"]:
# Absolute path, just to be su... | Parse parameters.
Combine default and user-defined parameters. | entailment |
def _run_program(self, bin, fastafile, params=None):
"""
Run XXmotif 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,... | Run XXmotif 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, optional
Optional parameters. For some of the tools required... | entailment |
def _parse_params(self, params=None):
"""
Parse parameters.
Combine default and user-defined parameters.
"""
prm = self.default_params.copy()
if params is not None:
prm.update(params)
# Background file is essential!
if not prm["background"]... | Parse parameters.
Combine default and user-defined parameters. | entailment |
def _run_program(self, bin, fastafile, params=None):
"""
Run Homer 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... | Run Homer 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, optional
Optional parameters. For some of the tools required p... | entailment |
def parse(self, fo):
"""
Convert BioProspector output to motifs
Parameters
----------
fo : file-like
File object containing BioProspector output.
Returns
-------
motifs : list
List of Motif instances.
"""
m... | Convert BioProspector output to motifs
Parameters
----------
fo : file-like
File object containing BioProspector output.
Returns
-------
motifs : list
List of Motif instances. | entailment |
def _run_program(self, bin, fastafile, params=None):
"""
Run HMS 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, opt... | Run HMS 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, optional
Optional parameters. For some of the tools required par... | entailment |
def parse(self, fo):
"""
Convert HMS output to motifs
Parameters
----------
fo : file-like
File object containing HMS output.
Returns
-------
motifs : list
List of Motif instances.
"""
motifs = []
m... | Convert HMS output to motifs
Parameters
----------
fo : file-like
File object containing HMS output.
Returns
-------
motifs : list
List of Motif instances. | entailment |
def _run_program(self, bin, fastafile, params=None):
"""
Run AMD 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, opt... | Run AMD 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, optional
Optional parameters. For some of the tools required par... | entailment |
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 = []
... | Convert AMD output to motifs
Parameters
----------
fo : file-like
File object containing AMD output.
Returns
-------
motifs : list
List of Motif instances. | entailment |
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 ... | Convert Improbizer output to motifs
Parameters
----------
fo : file-like
File object containing Improbizer output.
Returns
-------
motifs : list
List of Motif instances. | entailment |
def _run_program(self, bin, fastafile, params=None):
"""
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,... | 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, optional
Optional parameters. For some of the tools required... | entailment |
def _run_program(self, bin,fastafile, params=None):
"""
Run Weeder 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... | Run Weeder 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, optional
Optional parameters. For some of the tools required ... | entailment |
def _parse_params(self, params=None):
"""
Parse parameters.
Combine default and user-defined parameters.
"""
prm = self.default_params.copy()
if params is not None:
prm.update(params)
if prm["background_model"]:
# Absolute path, just to... | Parse parameters.
Combine default and user-defined parameters. | entailment |
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 : ... | 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 : dict, optional
Optional parameters. For some of the tools req... | entailment |
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.
"""
mot... | Convert MotifSampler output to motifs
Parameters
----------
fo : file-like
File object containing MotifSampler output.
Returns
-------
motifs : list
List of Motif instances. | entailment |
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.
"""
... | Convert MotifSampler output to motifs
Parameters
----------
fo : file-like
File object containing MotifSampler output.
Returns
-------
motifs : list
List of Motif instances. | entailment |
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... | 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, optional
Optional parameters. For some of the tools require... | entailment |
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.
"""
motifs = []... | Convert MDmodule output to motifs
Parameters
----------
fo : file-like
File object containing MDmodule output.
Returns
-------
motifs : list
List of Motif instances. | entailment |
def _parse_params(self, params=None):
"""
Parse parameters.
Combine default and user-defined parameters.
"""
prm = self.default_params.copy()
if params is not None:
prm.update(params)
return prm | Parse parameters.
Combine default and user-defined parameters. | entailment |
def _run_program(self, bin, fastafile, params=None):
"""
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... | 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, optional
Optional parameters. For some of the tools require... | entailment |
def parse(self, fo):
"""
Convert ChIPMunk output to motifs
Parameters
----------
fo : file-like
File object containing ChIPMunk output.
Returns
-------
motifs : list
List of Motif instances.
"""
#KDIC|6.124... | Convert ChIPMunk output to motifs
Parameters
----------
fo : file-like
File object containing ChIPMunk output.
Returns
-------
motifs : list
List of Motif instances. | entailment |
def _run_program(self, bin, fastafile, params=None):
"""
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... | 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, optional
Optional parameters. For some of the tools required p... | entailment |
def parse(self, fo, width, seed=None):
"""
Convert Posmo output to motifs
Parameters
----------
fo : file-like
File object containing Posmo output.
Returns
-------
motifs : list
List of Motif instances.
"""
... | Convert Posmo output to motifs
Parameters
----------
fo : file-like
File object containing Posmo output.
Returns
-------
motifs : list
List of Motif instances. | entailment |
def parse(self, fo):
"""
Convert GADEM output to motifs
Parameters
----------
fo : file-like
File object containing GADEM output.
Returns
-------
motifs : list
List of Motif instances.
"""
motifs = []
... | Convert GADEM output to motifs
Parameters
----------
fo : file-like
File object containing GADEM output.
Returns
-------
motifs : list
List of Motif instances. | entailment |
def _run_program(self, bin, fastafile, params=None):
"""
Get enriched JASPAR motifs in a FASTA file.
Parameters
----------
bin : str
Command used to run the tool.
fastafile : str
Name of the FASTA input file.
params : dict, optio... | Get enriched JASPAR motifs in a FASTA file.
Parameters
----------
bin : str
Command used to run the tool.
fastafile : str
Name of the FASTA input file.
params : dict, optional
Optional parameters. For some of the tools required param... | entailment |
def _run_program(self, bin, fastafile, params=None):
"""
Run MEME 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, op... | Run MEME 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, optional
Optional parameters. For some of the tools required pa... | entailment |
def parse(self, fo):
"""
Convert MEME output to motifs
Parameters
----------
fo : file-like
File object containing MEME output.
Returns
-------
motifs : list
List of Motif instances.
"""
motifs = []
... | Convert MEME output to motifs
Parameters
----------
fo : file-like
File object containing MEME output.
Returns
-------
motifs : list
List of Motif instances. | entailment |
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
feather file.
genome : str
Genome name. C... | 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
feather file.
genome : str
Genome name. Can be either the name of a FASTA-formatted file or a
genomepy genome name... | entailment |
def run_maelstrom(infile, genome, outdir, pwmfile=None, plot=True, cluster=False,
score_table=None, count_table=None, methods=None, ncpus=None):
"""Run maelstrom on an input table.
Parameters
----------
infile : str
Filename of input table. Can be either a text-separated tab file o... | Run maelstrom on an input table.
Parameters
----------
infile : str
Filename of input table. Can be either a text-separated tab file or a
feather file.
genome : str
Genome name. Can be either the name of a FASTA-formatted file or a
genomepy genome name.
... | entailment |
def plot_heatmap(self, kind="final", min_freq=0.01, threshold=2, name=True, max_len=50, aspect=1, **kwargs):
"""Plot clustered heatmap of predicted motif activity.
Parameters
----------
kind : str, optional
Which data type to use for plotting. Default is 'final', whi... | Plot clustered heatmap of predicted motif activity.
Parameters
----------
kind : str, optional
Which data type to use for plotting. Default is 'final', which will plot the
result of the rang aggregation. Other options are 'freq' for the motif frequencies,
... | entailment |
def plot_scores(self, motifs, name=True, max_len=50):
"""Create motif scores boxplot of different clusters.
Motifs can be specified as either motif or factor names.
The motif scores will be scaled and plotted as z-scores.
Parameters
----------
motifs : iterable o... | Create motif scores boxplot of different clusters.
Motifs can be specified as either motif or factor names.
The motif scores will be scaled and plotted as z-scores.
Parameters
----------
motifs : iterable or str
List of motif or factor names.
... | entailment |
def get_version(package, url_pattern=URL_PATTERN):
"""Return version of package on pypi.python.org using json. Adapted from https://stackoverflow.com/a/34366589"""
req = requests.get(url_pattern.format(package=package))
version = parse('0')
if req.status_code == requests.codes.ok:
# j = json.loa... | Return version of package on pypi.python.org using json. Adapted from https://stackoverflow.com/a/34366589 | entailment |
def get_args(parser):
"""
Converts arguments extracted from a parser to a dict,
and will dismiss arguments which default to NOT_SET.
:param parser: an ``argparse.ArgumentParser`` instance.
:type parser: argparse.ArgumentParser
:return: Dictionary with the configs found in the parsed CLI argumen... | Converts arguments extracted from a parser to a dict,
and will dismiss arguments which default to NOT_SET.
:param parser: an ``argparse.ArgumentParser`` instance.
:type parser: argparse.ArgumentParser
:return: Dictionary with the configs found in the parsed CLI arguments.
:rtype: dict | entailment |
def parse_value(val, parsebool=False):
"""Parse input string and return int, float or str depending on format.
@param val: Input string.
@param parsebool: If True parse yes / no, on / off as boolean.
@return: Value of type int, float or str.
"""
try:
return i... | Parse input string and return int, float or str depending on format.
@param val: Input string.
@param parsebool: If True parse yes / no, on / off as boolean.
@return: Value of type int, float or str. | entailment |
def socket_read(fp):
"""Buffered read from socket. Reads all data available from socket.
@fp: File pointer for socket.
@return: String of characters read from buffer.
"""
response = ''
oldlen = 0
newlen = 0
while True:
response += fp.read(buffSize)
newlen = ... | Buffered read from socket. Reads all data available from socket.
@fp: File pointer for socket.
@return: String of characters read from buffer. | entailment |
def exec_command(args, env=None):
"""Convenience function that executes command and returns result.
@param args: Tuple of command and arguments.
@param env: Dictionary of environment variables.
(Environment is not modified if None.)
@return: Command output.
"""
t... | Convenience function that executes command and returns result.
@param args: Tuple of command and arguments.
@param env: Dictionary of environment variables.
(Environment is not modified if None.)
@return: Command output. | entailment |
def set_nested(self, klist, value):
"""D.set_nested((k1, k2,k3, ...), v) -> D[k1][k2][k3] ... = v"""
keys = list(klist)
if len(keys) > 0:
curr_dict = self
last_key = keys.pop()
for key in keys:
if not curr_dict.has_key(key) or not isinstance(cu... | D.set_nested((k1, k2,k3, ...), v) -> D[k1][k2][k3] ... = v | entailment |
def registerFilter(self, column, patterns, is_regex=False,
ignore_case=False):
"""Register filter on a column of table.
@param column: The column name.
@param patterns: A single pattern or a list of patterns used for
matching ... | Register filter on a column of table.
@param column: The column name.
@param patterns: A single pattern or a list of patterns used for
matching column values.
@param is_regex: The patterns will be treated as regex if True, the
... | entailment |
def unregisterFilter(self, column):
"""Unregister filter on a column of the table.
@param column: The column header.
"""
if self._filters.has_key(column):
del self._filters[column] | Unregister filter on a column of the table.
@param column: The column header. | entailment |
def registerFilters(self, **kwargs):
"""Register multiple filters at once.
@param **kwargs: Multiple filters are registered using keyword
variables. Each keyword must correspond to a field name
with an optional suffix:
... | Register multiple filters at once.
@param **kwargs: Multiple filters are registered using keyword
variables. Each keyword must correspond to a field name
with an optional suffix:
field: Field equal to value or in list... | entailment |
def applyFilters(self, headers, table):
"""Apply filter on ps command result.
@param headers: List of column headers.
@param table: Nested list of rows and columns.
@return: Nested list of rows and columns filtered using
registered filters.
... | Apply filter on ps command result.
@param headers: List of column headers.
@param table: Nested list of rows and columns.
@return: Nested list of rows and columns filtered using
registered filters. | entailment |
def open(self, host=None, port=0, socket_file=None,
timeout=socket.getdefaulttimeout()):
"""Connect to a host.
With a host argument, it connects the instance using TCP; port number
and timeout are optional, socket_file must be None. The port number
defaults to the standar... | Connect to a host.
With a host argument, it connects the instance using TCP; port number
and timeout are optional, socket_file must be None. The port number
defaults to the standard telnet port (23).
With a socket_file argument, it connects the instance using
named soc... | entailment |
def analyze(egg, subjgroup=None, listgroup=None, subjname='Subject',
listname='List', analysis=None, position=0, permute=False,
n_perms=1000, parallel=False, match='exact',
distance='euclidean', features=None, ts=None):
"""
General analysis function that groups data by subjec... | General analysis function that groups data by subject/list number and performs analysis.
Parameters
----------
egg : Egg data object
The data to be analyzed
subjgroup : list of strings or ints
String/int variables indicating how to group over subjects. Must be
the length of th... | entailment |
def _analyze_chunk(data, subjgroup=None, subjname='Subject', listgroup=None,
listname='List', analysis=None, analysis_type=None,
pass_features=False, features=None, parallel=False,
**kwargs):
"""
Private function that groups data by subject/list number an... | Private function that groups data by subject/list number and performs
analysis for a chunk of data.
Parameters
----------
data : Egg data object
The data to be analyzed
subjgroup : list of strings or ints
String/int variables indicating how to group over subjects. Must be
... | entailment |
def retrieveVals(self):
"""Retrieve values for graphs."""
if self.hasGraph('tomcat_memory'):
stats = self._tomcatInfo.getMemoryStats()
self.setGraphVal('tomcat_memory', 'used',
stats['total'] - stats['free'])
self.setGraphVal('tomcat_memo... | Retrieve values for graphs. | entailment |
def function(data, maxt=None):
"""
Calculate the autocorrelation function for a 1D time series.
Parameters
----------
data : numpy.ndarray (N,)
The time series.
Returns
-------
rho : numpy.ndarray (N,)
An autocorrelation function.
"""
data = np.atleast_1d(data)... | Calculate the autocorrelation function for a 1D time series.
Parameters
----------
data : numpy.ndarray (N,)
The time series.
Returns
-------
rho : numpy.ndarray (N,)
An autocorrelation function. | entailment |
def retrieveVals(self):
"""Retrieve values for graphs."""
nginxInfo = NginxInfo(self._host, self._port,
self._user, self._password,
self._statuspath, self._ssl)
stats = nginxInfo.getServerStats()
if stats:
if... | Retrieve values for graphs. | entailment |
def autoconf(self):
"""Implements Munin Plugin Auto-Configuration Option.
@return: True if plugin can be auto-configured, False otherwise.
"""
nginxInfo = NginxInfo(self._host, self._port,
self._user, self._password,
... | Implements Munin Plugin Auto-Configuration Option.
@return: True if plugin can be auto-configured, False otherwise. | entailment |
def getStats(self):
"""Query and parse Web Server Status Page.
"""
url = "%s://%s:%d/%s" % (self._proto, self._host, self._port,
self._monpath)
response = util.get_url(url, self._user, self._password)
stats = {}
for line in respo... | Query and parse Web Server Status Page. | entailment |
def retrieveVals(self):
"""Retrieve values for graphs."""
apcinfo = APCinfo(self._host, self._port, self._user, self._password,
self._monpath, self._ssl, self._extras)
stats = apcinfo.getAllStats()
if self.hasGraph('php_apc_memory') and stats:
... | Retrieve values for graphs. | entailment |
def autoconf(self):
"""Implements Munin Plugin Auto-Configuration Option.
@return: True if plugin can be auto-configured, False otherwise.
"""
apcinfo = APCinfo(self._host, self._port, self._user, self._password,
self._monpath, self.... | Implements Munin Plugin Auto-Configuration Option.
@return: True if plugin can be auto-configured, False otherwise. | entailment |
def getStats(self):
"""Runs varnishstats command to get stats from Varnish Cache.
@return: Dictionary of stats.
"""
info_dict = {}
args = [varnishstatCmd, '-1']
if self._instance is not None:
args.extend(['-n', self._instance])
output = util.... | Runs varnishstats command to get stats from Varnish Cache.
@return: Dictionary of stats. | entailment |
def getDesc(self, entry):
"""Returns description for stat entry.
@param entry: Entry name.
@return: Description for entry.
"""
if len(self._descDict) == 0:
self.getStats()
return self._descDict.get(entry) | Returns description for stat entry.
@param entry: Entry name.
@return: Description for entry. | entailment |
def retrieveVals(self):
"""Retrieve values for graphs."""
opcinfo = OPCinfo(self._host, self._port, self._user, self._password,
self._monpath, self._ssl)
stats = opcinfo.getAllStats()
if self.hasGraph('php_opc_memory') and stats:
mem = stat... | Retrieve values for graphs. | entailment |
def autoconf(self):
"""Implements Munin Plugin Auto-Configuration Option.
@return: True if plugin can be auto-configured, False otherwise.
"""
opcinfo = OPCinfo(self._host, self._port, self._user, self._password,
self._monpath, self.... | Implements Munin Plugin Auto-Configuration Option.
@return: True if plugin can be auto-configured, False otherwise. | entailment |
def fingerprint_helper(egg, permute=False, n_perms=1000,
match='exact', distance='euclidean', features=None):
"""
Computes clustering along a set of feature dimensions
Parameters
----------
egg : quail.Egg
Data to analyze
dist_funcs : dict
Dictionary of d... | Computes clustering along a set of feature dimensions
Parameters
----------
egg : quail.Egg
Data to analyze
dist_funcs : dict
Dictionary of distance functions for feature clustering analyses
Returns
----------
probabilities : Numpy array
Each number represents cluste... | entailment |
def compute_feature_weights(pres_list, rec_list, feature_list, distances):
"""
Compute clustering scores along a set of feature dimensions
Parameters
----------
pres_list : list
list of presented words
rec_list : list
list of recalled words
feature_list : list
list... | Compute clustering scores along a set of feature dimensions
Parameters
----------
pres_list : list
list of presented words
rec_list : list
list of recalled words
feature_list : list
list of feature dicts for presented words
distances : dict
dict of distance ma... | entailment |
def lagcrp_helper(egg, match='exact', distance='euclidean',
ts=None, features=None):
"""
Computes probabilities for each transition distance (probability that a word
recalled will be a given distance--in presentation order--from the previous
recalled word).
Parameters
--------... | Computes probabilities for each transition distance (probability that a word
recalled will be a given distance--in presentation order--from the previous
recalled word).
Parameters
----------
egg : quail.Egg
Data to analyze
match : str (exact, best or smooth)
Matching approach t... | entailment |
def retrieveVals(self):
"""Retrieve values for graphs."""
if self._diskList:
self._fetchDevAll('disk', self._diskList,
self._info.getDiskStats)
if self._mdList:
self._fetchDevAll('md', self._mdList,
self._info.... | Retrieve values for graphs. | entailment |
def _configDevRequests(self, namestr, titlestr, devlist):
"""Generate configuration for I/O Request stats.
@param namestr: Field name component indicating device type.
@param titlestr: Title component indicating device type.
@param devlist: List of devices.
""... | Generate configuration for I/O Request stats.
@param namestr: Field name component indicating device type.
@param titlestr: Title component indicating device type.
@param devlist: List of devices. | entailment |
def _configDevActive(self, namestr, titlestr, devlist):
"""Generate configuration for I/O Queue Length.
@param namestr: Field name component indicating device type.
@param titlestr: Title component indicating device type.
@param devlist: List of devices.
"""
... | Generate configuration for I/O Queue Length.
@param namestr: Field name component indicating device type.
@param titlestr: Title component indicating device type.
@param devlist: List of devices. | entailment |
def _fetchDevAll(self, namestr, devlist, statsfunc):
"""Initialize I/O stats for devices.
@param namestr: Field name component indicating device type.
@param devlist: List of devices.
@param statsfunc: Function for retrieving stats for device.
"""
fo... | Initialize I/O stats for devices.
@param namestr: Field name component indicating device type.
@param devlist: List of devices.
@param statsfunc: Function for retrieving stats for device. | entailment |
def retrieveVals(self):
"""Retrieve values for graphs."""
for graph_name in self.getGraphList():
for field_name in self.getGraphFieldList(graph_name):
self.setGraphVal(graph_name, field_name, self._stats.get(field_name)) | Retrieve values for graphs. | entailment |
def retrieveVals(self):
"""Retrieve values for graphs."""
if self.hasGraph('sys_loadavg'):
self._loadstats = self._sysinfo.getLoadAvg()
if self._loadstats:
self.setGraphVal('sys_loadavg', 'load15min', self._loadstats[2])
self.setGraphVal('sys_loada... | Retrieve values for graphs. | entailment |
def get(key, default=None):
"""
Searches os.environ. If a key is found try evaluating its type else;
return the string.
returns: k->value (type as defined by ast.literal_eval)
"""
try:
# Attempt to evaluate into python literal
return ast.literal_eval(os.environ.get(k... | Searches os.environ. If a key is found try evaluating its type else;
return the string.
returns: k->value (type as defined by ast.literal_eval) | entailment |
def save(filepath=None, **kwargs):
"""
Saves a list of keyword arguments as environment variables to a file.
If no filepath given will default to the default `.env` file.
"""
if filepath is None:
filepath = os.path.join('.env')
with open(filepath, 'wb') as file_handle:
f... | Saves a list of keyword arguments as environment variables to a file.
If no filepath given will default to the default `.env` file. | entailment |
def load(filepath=None):
"""
Reads a .env file into os.environ.
For a set filepath, open the file and read contents into os.environ.
If filepath is not set then look in current dir for a .env file.
"""
if filepath and os.path.exists(filepath):
pass
else:
if not o... | Reads a .env file into os.environ.
For a set filepath, open the file and read contents into os.environ.
If filepath is not set then look in current dir for a .env file. | entailment |
def _get_line_(filepath):
"""
Gets each line from the file and parse the data.
Attempt to translate the value into a python type is possible
(falls back to string).
"""
for line in open(filepath):
line = line.strip()
# allows for comments in the file
if line.startswith('#... | Gets each line from the file and parse the data.
Attempt to translate the value into a python type is possible
(falls back to string). | entailment |
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... | Query and parse Apache Web Server Status Page. | entailment |
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: {... | Returns a df of features for presented items | entailment |
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... | Returns a df of features for recalled items | entailment |
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... | Print info about the data egg | entailment |
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
... | 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
A name for the file. If the file extension (.egg) is n... | entailment |
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... | 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
----------
fname : str
A name for the file. If the file extension ... | entailment |
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... | 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 analyze
position : int
Position of item to be analyzed
match : str (exact, best or smooth)
... | entailment |
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... | Retrieve values for graphs. | entailment |
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,
... | Implements Munin Plugin Auto-Configuration Option.
@return: True if plugin can be auto-configured, False otherwise. | entailment |
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)
... | Retrieve values for graphs. | entailment |
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