alpha-factory 0.1.0

generate alpha factors

sample:
from alpha_fatcory_v2 import generator_class
from RNWS import read
import numpy as np
import pandas as pd
df=pd.read_csv('.frames.csv')
factor_path='./alpha_fatcory_v2_test'
frame_path='./packages'
exr=read.read_df('./exr',file_pattern='exr',start=20160101,end=20160201)
cap=read.read_df('./cap',file_pattern='cap',header=0,dat_col='cap',start=20160101,end=20160201)
open_price,close,vwap,high,low,volume=read.read_df('./mkt_data',file_pattern='mkt',start=20160101,end=20160201,header=0,dat_col=['open','close','vwap','high','low','volume'])
ind1,ind2,ind3=read.read_df('./ind',file_pattern='ind',start=20160101,end=20160201,header=0,dat_col=['level1','level2','level3'])
parms={'exr':exr
,'cap':cap
,'open_price':open_price
,'close':close
,'vwap':vwap
,'high':high
,'low':low
,'volume':volume
,'ind1':ind1
,'ind2':ind2
,'ind3':ind3}

# generate starting:
gc=generator_class(df,factor_path,**parms)
gc.generator(batch_size=3)
gc.generator(batch_size=3)
gc.output_df(path=frame_path+'/frames_new.csv')

# generate continue:
with generator_class(df,factor_path,**parms) as gc:
gc.reload_df(path=frame_path+'/frames_new.csv')
gc.reload_factors()
gc.generator(batch_size=3)
gc.output_df(path=frame_path+'/frames_new2.csv')