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@ -82,6 +82,9 @@ class Components :
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df = df.iloc[i]
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#
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# Certain columns need to be removed too large of a matrix
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#
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# if df.shape[0] == 0 :
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# print ("CAN NOT TRAIN EMPTY DATASET ")
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# return
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@ -130,7 +133,7 @@ class Components :
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self.generate(args)
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pass
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# @staticmethod
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def generate(self,args):
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"""
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@ -171,7 +174,7 @@ class Components :
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i = np.random.choice(df.shape[0],max_rows,replace=False)
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df = df.iloc[i]
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# bounds = Components.split(df,MAX_ROWS,PART_SIZE)
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# if partition != '' :
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# columns = args['columns']
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@ -194,13 +197,15 @@ class Components :
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if df[name].isnull().sum() > 0 :
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df[name].fillna(0,inplace=True)
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else:
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df[name] = df[name].astype(np.int64)
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df[name] = df[name].astype(int)
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_dc = pd.DataFrame()
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# for mdf in df :
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_args['data'] = df
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_args['data'] = df
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_dc = _dc.append(data.maker.generate(**_args))
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#
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# We need to post the generate the data in order to :
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# 1. compare immediately
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@ -356,14 +361,7 @@ if __name__ == '__main__' :
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else:
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generator.generate(args)
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# Components.generate(args)
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elif 'finalize' in args :
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#
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# This will finalize a given set of synthetic operations into a table
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#
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idataset = args['input'] if 'input' in args else 'io' #-- input dataset
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odataset = args['output'] #-- output dataset
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labels = [name.strip() for name in args['labels'].split(',') ]
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else:
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# DATA = np.array_split(DATA,PART_SIZE)
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