def __init__(self,
gdsc,
results=None,
sep="\t",
drug_decode=None,
verbose=True):
""".. rubric:: Constructor
:param gdsc: the instance with which you created the results to report
:param results: the results returned by :meth:`ANOVA.anova_all`. If
not provided, the ANOVA is run on the fly.
"""
self.verbose = verbose
self.figtools = Savefig(verbose=False)
self.gdsc = gdsc
if results is None:
results = gdsc.anova_all()
self.df = ANOVAResults(results).df # this does a copy and sanity check
# Make sure the DRUG are integers
self.df.DRUG_ID = self.df.DRUG_ID.astype(int)
self.settings = ANOVASettings()
for k, v in gdsc.settings.items():
self.settings[k] = v
self._colname_drug_id = 'DRUG_ID'
self.varname_pval = 'ANOVA_FEATURE_pval'
self.varname_qval = 'ANOVA_FEATURE_FDR'
# maybe there was not drug_decode in the gdsc parameter,
# so a user may have provide a file, in which case, we need
# to update the content of the dur_decoder.
if len(gdsc.drug_decode) == 0 and drug_decode is None:
warnings.warn("No drug name or target will be populated."
"You may want to provide a DRUG_DECODE file.")
self.drug_decode = DrugDecode()
elif drug_decode is not None:
# Read a file
self.drug_decode = DrugDecode(drug_decode)
else:
# Copy from gdsc instance
self.drug_decode = DrugDecode(gdsc.drug_decode)
self.df = self.drug_decode.drug_annotations(self.df)
#if sum(self.df == np.inf).sum()>0:
# print("WARNING: infinite values were found in your results... Set to zero")
try:
self.df = self.df.replace({np.inf: 0, -np.inf: 0})
except:
pass
# create some data
self._set_sensible_df()
self.company = None
def __init__(self, data, sep="\t", settings=None):
""".. rubric:: Constructor
:param data: an :class:`~gdsctools.anova.ANOVAResults` instance
or a dataframe with the proper columns names (see below)
:param settings: an instance of
:class:`~gdsctools.settings.ANOVASettings`
Expected column names to be found if a filename is provided::
ANOVA_FEATURE_pval
ANOVA_FEATURE_FDR
FEATURE_delta_MEAN_IC50
FEATURE_IC50_effect_size
N_FEATURE_pos
N_FEATURE_pos
FEATURE
DRUG_ID
If the plotting is too slow, you can use the :meth:`selector` to prune
the results (most of the data are noise and overlap on the middle
bottom area of the plot with little information.
"""
# a copy since we do may change the data
try:
# an ANOVAResults contains a df attribute
self.df = data.df.copy()
except:
# probably a dataframe
self.df = data.copy()
# this is redundant could reuse the input ??
if settings is None:
from gdsctools.settings import ANOVASettings
self.settings = ANOVASettings()
else:
self.settings = AttrDict(**settings)
self.figtools = Savefig()
self.figtools.directory = self.settings.directory
self.drugs = set(self.df[self._colname_drugid])
self.features = set(self.df[self._colname_feature])
# intensive calls made once for all
self.groups_by_drugs = self.df.groupby(self._colname_drugid).groups
self.groups_by_features = self.df.groupby(self._colname_feature).groups
def __init__(self, gdsc, results, sep="\t", drug_decode=None):
""".. rubric:: Constructor
:param gdsc: the instance with which you created the results to report
:param results: the results returned by :meth:`ANOVA.anova_all`
"""
self.figtools = Savefig()
self.gdsc = gdsc
self.df = ANOVAResults(results).df # this does a copy and sanity check
self.settings = ANOVASettings()
for k, v in gdsc.settings.items():
self.settings[k] = v
self._colname_drug_id = 'DRUG_ID'
self.varname_pval = 'ANOVA_FEATURE_pval'
self.varname_qval = 'ANOVA_FEATURE_FDR'
# maybe there was not drug_decode in the gdsc parameter,
# so a user may have provide a file, in which case, we need
# to update the content of the dur_decoder.
if len(gdsc.drug_decode) == 0 and drug_decode is None:
warnings.warn("No drug name or target will be populated."
"You may want to provide a DRUG_DECODE file.")
self.drug_decode = DrugDecode()
elif drug_decode is not None:
# Read a file
self.drug_decode = DrugDecode(drug_decode)
else:
# Copy from gdsc instance
self.drug_decode = DrugDecode(gdsc.drug_decode)
self.df = self.drug_decode.drug_annotations(self.df)
# create some data
self._set_sensible_df()
# just to create the directory
ReportMAIN(directory=self.settings.directory)
