Module cellex.metrics.es_mu
Expand source code
import numpy as np
import pandas as pd
import time
import datetime
def es_mu(esws: list, verbose: bool=False) -> pd.DataFrame:
"""Compute ESmu
Computes mean of ESWs, i.e. ES_mu, for each gene / cell-type.
Parameters
----------
esws : list
List of ESw dataframes to compute mean from.
verbose : bool, optional (default: False)
Print progress report.
Returns
-------
esmu : DataFrame
ESw mean.
"""
start = 0
if verbose:
start = time.time()
print("Computing ESmu ...")
if len(esws) < 4:
print("WARNING: Computing esw_mu using {} metrics ...".format(len(esws)))
esmu = pd.DataFrame(data=np.mean(([df.values for df in esws]), axis=0),
columns=esws[0].columns.values,
index=esws[0].index.values)
esmu.index.name = "gene"
if verbose:
td = datetime.timedelta(seconds=(time.time() - start))
print(" finished in %d min %d sec" % (divmod(td.seconds, 60)))
return esmuFunctions
def es_mu(esws: list, verbose: bool = False) -> pandas.core.frame.DataFrame-
Compute ESmu
Computes mean of ESWs, i.e. ES_mu, for each gene / cell-type.
Parameters
esws:list- List of ESw dataframes to compute mean from.
verbose:bool, optional(default: False)- Print progress report.
Returns
esmu:DataFrame- ESw mean.
Expand source code
def es_mu(esws: list, verbose: bool=False) -> pd.DataFrame: """Compute ESmu Computes mean of ESWs, i.e. ES_mu, for each gene / cell-type. Parameters ---------- esws : list List of ESw dataframes to compute mean from. verbose : bool, optional (default: False) Print progress report. Returns ------- esmu : DataFrame ESw mean. """ start = 0 if verbose: start = time.time() print("Computing ESmu ...") if len(esws) < 4: print("WARNING: Computing esw_mu using {} metrics ...".format(len(esws))) esmu = pd.DataFrame(data=np.mean(([df.values for df in esws]), axis=0), columns=esws[0].columns.values, index=esws[0].index.values) esmu.index.name = "gene" if verbose: td = datetime.timedelta(seconds=(time.time() - start)) print(" finished in %d min %d sec" % (divmod(td.seconds, 60))) return esmu