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resultsAnalysis_dataLoading.py
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100 lines (79 loc) · 2.34 KB
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# coding: utf-8
# # Results analysis: data loading
#
# Load hard data that are never edited
# In[ ]:
import pandas as pd
import neuralNetwork_utils as ut
# In[ ]:
trainUB = '2012-12'
validationLB = '2013-1'
validationUB = '2013-12'
testLB = '2014'
# In[ ]:
returnsPath = '../donnees/clean/RET_PX_LAST.csv'
returns = ut.getInputs(scalingFactor=1,
stocksFile=returnsPath)
train, validation, test = ut.splitData(returns,
trainUB=trainUB,
validationLB=validationLB,
validationUB=validationUB,
testLB=testLB)
# In[ ]:
parametersSetML = ['scalingFactor',
'encoding_dim',
'denoising',
'dropoutProba',
'optimizer',
'loss_func',
'nb_epoch',
'batch_size',
'activFirstLayer',
'activSecondLayer']
numericML = ['scalingFactor',
'encoding_dim',
'dropoutProba',
'nb_epoch',
'batch_size',
'loss',
'smoothness']
parametersSetStrat = ['amount',
'strategyLength',
'isLong',
'isShort',
'legSize',
'legSizeLong',
'legSizeShort',
'involvedProportion',
'longShortMinLegSize',
'weight_type']
numericStrat = ['amount',
'strategyLength',
'legSizeLong',
'legSizeShort',
'involvedProportion',
'longShortMinLegSize']
# In[ ]:
print '----------'
print 'Date partition :'
print ''
print ' - train upper bound : %s'%trainUB
print ' - validation : %s - %s'%(validationLB, validationUB)
print ' - test lower bound : %s'%testLB
print ''
print 'Available variables :'
print ''
print ' - returns'
print ' - train'
print ' - validation'
print ' - test'
print ''
print ' - parametersSetML :'
print ' %s'%parametersSetML
print ' - numericML :'
print ' %s'%numericML
print ' - parametersSetStrat :'
print ' %s'%parametersSetStrat
print ' - numericStrat :'
print ' %s'%numericStrat
print '----------'