def create_nd_histogram(self, var, mean_id):
"""
Create nd histograms for given variable and mean id
Only 0 (factor=1.00), 9 (factor=1.03), 18 (factor=0.97),
27 (factor=1.06) and 36 (factor=0.94) working.
:param str var: variable name
:param int mean_id: index of mean map.
"""
self.config.logger.info(
"DataValidator::create_nd_histogram, var = %s, mean_id = %d", var,
mean_id)
self.__check_mean_id(mean_id)
mean_factor = self.__get_mean_factor(mean_id)
column_names = ['phi', 'r', 'z', 'deltaSC']
diff_index = var.find("Diff")
if diff_index == -1:
column_names.append(var)
else:
column_names = column_names + [
var[:diff_index], var[:diff_index] + "Pred"
]
df_val = tree_to_pandas(
"%s/%s/validation_mean%.2f_nEv%d_fapply%d.root" %
(self.config.dirtree, self.config.suffix, mean_factor,
self.config.train_events, self.config.num_fourier_coeffs_apply),
'validation',
columns=column_names)
if diff_index != -1:
df_val[var] = \
df_val[var[:diff_index] + "Pred"] - df_val[var[:diff_index]]
# Definition string for nd histogram required by makeHistogram function in RootInteractive
# 1) variables from data frame
# 2) cut selection
# 3) histogram name and binning in each dimension
# E.g. "var1:var2:var3:#cut_selection>>histo_name(n1,min1,max1,n2,min2,max2,n3,min3,max3)"
histo_string = "%s:phi:r:z:deltaSC" % (var) + \
":#r>0" + \
">>%s" % (var) + \
"(%d,%.4f,%.4f," % (200, df_val[var].min(), df_val[var].max()) + \
"180,0.0,6.283," + \
"33,83.5,254.5," + \
"40,0,250," + \
"%d,%.4f,%.4f)" % (10, df_val['deltaSC'].min(), df_val['deltaSC'].max())
output_file_name = "%s/%s/ndHistogram_%s_mean%.2f_nEv%d.gzip" \
% (self.config.dirhist, self.config.suffix, var, mean_factor,
self.config.train_events)
with gzip.open(output_file_name, 'wb') as output_file:
pickle.dump(makeHistogram(df_val, histo_string), output_file)
output_file.close()
self.config.logger.info("Nd histogram %s written to %s.", histo_string,
output_file_name)
def create_nd_histogram(self, var, mean_id):
"""
Create nd histograms for given variable and mean id
var: string of the variable name
mean_id: index of mean map. Only 0 (factor=1.0), 9 (factor=1.1) and 18 (factor=0.9) working.
"""
self.logger.info(
"DataValidator::create_nd_histogram, var = %s, mean_id = %d", var,
mean_id)
if mean_id not in (0, 9, 18):
self.logger.info(
"Code implementation only designed for mean ids 0, 9, 18. Exiting..."
)
sys.exit()
mean_factor = 1 + 0.1 * (mean_id != 0) * (1 - 2 * (mean_id == 18))
column_names = ['phi', 'r', 'z', 'deltaSC']
diff_index = var.find("Diff")
if diff_index == -1:
column_names.append(var)
else:
column_names = column_names + [
var[:diff_index], var[:diff_index] + "Pred"
]
df_val = read_root(
"%s/%s/treeValidation_mean%.1f_nEv%d.root" %
(self.diroutflattree, self.suffix, mean_factor, self.train_events),
key='validation',
columns=column_names)
if diff_index != -1:
df_val[var] = \
df_val[var[:diff_index] + "Pred"] - df_val[var[:diff_index]]
# Definition string for nd histogram required by makeHistogram function in RootInteractive
# 1) variables from data frame
# 2) cut selection
# 3) histogram name and binning in each dimension
# E.g. "var1:var2:var3:#cut_selection>>histo_name(n1,min1,max1,n2,min2,max2,n3,min3,max3)"
histo_string = "%s:phi:r:z:deltaSC" % (var) + \
":#r>0" + \
">>%s" % (var) + \
"(%d,%.4f,%.4f," % (200, df_val[var].min(), df_val[var].max()) + \
"180,0.0,6.283," + \
"33,83.5,254.5," + \
"40,0,250," + \
"%d,%.4f,%.4f)" % (10, df_val['deltaSC'].min(), df_val['deltaSC'].max())
output_file_name = "%s/%s/ndHistogram_%s_mean%.1f_nEv%d.gzip" \
% (self.dirouthistograms, self.suffix, var, mean_factor, self.train_events)
with gzip.open(output_file_name, 'wb') as output_file:
pickle.dump(makeHistogram(df_val, histo_string), output_file)
output_file.close()
self.logger.info("Nd histogram %s written to %s.", histo_string,
output_file_name)