alpha-factory 0.1.6

generate alpha factors

This programme is to automatically generate alpha factors

Dependencies

• python >= 3.5

• pandas >= 0.22.0

• numpy >= 1.14.0

• RNWS >= 0.1.1

• numba >= 0.38.0

Sample

from alpha_factory import generator_class,get_memory_use_pct,clean
from RNWS import read
import numpy as np
import pandas as pd

factor_path='.'
frame_path='.'

# frames contains df_name,equation,dependency,type
# type includes df,cap,group
# original frames.csv have df_name: exr,cap,open_price,close,vwap,high,low,volume,ind1,ind2,ind3
df=pd.read_csv(frame_path+'/frames.csv')

# read in data
exr=read.read_df('./exr',file_pattern='exr',start=20160101,end=20170201)
cap=read.read_df('./cap',file_pattern='cap',header=0,dat_col='cap',start=20160101,end=20170201)
open_price,close,vwap,high,low,volume=read.read_df('./mkt_data',file_pattern='mkt',start=20160101,end=20170201,header=0,dat_col=['open','close','vwap','high','low','volume'])
ind1,ind2,ind3=read.read_df('./ind',file_pattern='ind',start=20160101,end=20170201,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()
    clean()
    for i in range(5):
        gc.generator(batch_size=2)
        print('step %d memory usage:\t %.1f%% \n'%(i,get_memory_use_pct()))
        if get_memory_use_pct()>65:
            break
    gc.output_df(path=frame_path+'/frames_new2.csv')

multiprocessing is deprecated due to memory sharing issue