bug fix ...

dev
Steve L. Nyemba 5 years ago
parent e27624b697
commit 52e91ec063

@ -593,7 +593,7 @@ class Predict(GNet):
# #
# df = pd.DataFrame(np.round(f)).astype(np.int32) # df = pd.DataFrame(np.round(f)).astype(np.int32)
df = pd.DataFrame(np.round(f),dtype=np.uint8) df = pd.DataFrame(np.round(f),dtype=int)
p = 0 not in df.sum(axis=1).values p = 0 not in df.sum(axis=1).values
x = df.sum(axis=1).values x = df.sum(axis=1).values
@ -637,6 +637,8 @@ class Predict(GNet):
if self.logger : if self.logger :
info = {"found":len(found),"rows":df.shape[0],"cols":df.shape[1],"expected":len(self.values)} info = {"found":len(found),"rows":df.shape[0],"cols":df.shape[1],"expected":len(self.values)}
if df.shape[1] > len(self.values) :
df = df.iloc[:len(self.values)]
if INDEX > 0 : if INDEX > 0 :
info =dict(info ,**{"selected":INDEX, "ratio": ratio[INDEX] }) info =dict(info ,**{"selected":INDEX, "ratio": ratio[INDEX] })
else : else :

@ -82,6 +82,9 @@ class Components :
df = df.iloc[i] df = df.iloc[i]
#
# Certain columns need to be removed too large of a matrix
#
# if df.shape[0] == 0 : # if df.shape[0] == 0 :
# print ("CAN NOT TRAIN EMPTY DATASET ") # print ("CAN NOT TRAIN EMPTY DATASET ")
# return # return
@ -194,13 +197,15 @@ class Components :
if df[name].isnull().sum() > 0 : if df[name].isnull().sum() > 0 :
df[name].fillna(0,inplace=True) df[name].fillna(0,inplace=True)
else: else:
df[name] = df[name].astype(np.int64) df[name] = df[name].astype(int)
_dc = pd.DataFrame() _dc = pd.DataFrame()
# for mdf in df : # for mdf in df :
_args['data'] = df _args['data'] = df
_dc = _dc.append(data.maker.generate(**_args)) _dc = _dc.append(data.maker.generate(**_args))
# #
# We need to post the generate the data in order to : # We need to post the generate the data in order to :
# 1. compare immediately # 1. compare immediately
@ -356,13 +361,6 @@ if __name__ == '__main__' :
else: else:
generator.generate(args) generator.generate(args)
# Components.generate(args) # Components.generate(args)
elif 'finalize' in args :
#
# This will finalize a given set of synthetic operations into a table
#
idataset = args['input'] if 'input' in args else 'io' #-- input dataset
odataset = args['output'] #-- output dataset
labels = [name.strip() for name in args['labels'].split(',') ]
else: else:

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