Aug-31-2021, 05:51 PM
Hi Everyone,
Working on rebuilding my code into Cython but during the rebuild i got stuck on a part of the code
and cannot seem to get it at Cython speed.
Already vectorized but that does not help.
Also tried creating a separate functions:
what is going on and how can is solve it??
Full code file is saved as .pyx and compiled:
Working on rebuilding my code into Cython but during the rebuild i got stuck on a part of the code
and cannot seem to get it at Cython speed.
for prc_buy in range(1,90):
for prc_sell in range(1,90):
newarr[:,1] = newarr[:,5] * (prc_buy / prc)
newarr[:,2] = np.where(newarr[:,0] < newarr[:,1], 1,0)
newarr[:,3] = newarr[:,6] / (prc_sell / prc)
newarr[:,4] = np.where(newarr[:,0] > newarr[:,3], 1,0)once the code hits the section with np.where it gets really slow. i'm talking (without) 0.05 to (with)1.2 seconds slow. Already vectorized but that does not help.
Also tried creating a separate functions:
@cython.boundscheck(False) # turn off bounds-checking for entire function
@cython.wraparound(False) # turn off negative index wrapping for entire function
def position_smaller(np.ndarray[object, ndim=2] arr, sct1, sct2, upd):
cdef int row
cdef Py_ssize_t hmax = arr.shape[0]
for row in range(hmax):
if arr[row][sct1] < arr[row][sct2]:
arr[row][upd] = 1
return arrwhich does the same but is way slower then np.where.what is going on and how can is solve it??
Full code file is saved as .pyx and compiled:
#!python
#cython: language_level=3
import time
import csv
import sys, os
import numpy as np
cimport numpy as np
import cython
@cython.boundscheck(False) # turn off bounds-checking for entire function
@cython.wraparound(False) # turn off negative index wrapping for entire function
@cython.cdivision(True)
def processing(np.ndarray[object, ndim=1] dff_arr, min_plus_k, min_plus_v ,name, span_1, span_2, span_3):
cdef Py_ssize_t arr_shape = dff_arr.shape[0]
cdef np.ndarray newarr = np.zeros(shape=(arr_shape,7))
newarr[:,0] = dff_arr.astype(np.float64)
cdef float amount = 1000.0
cdef int buy_cnt_close
cdef long arr
cdef float prc_buy = 0.0
cdef float prc_sell = 0.0
cdef float prc = 100.0
cdef float sell_close, sell_coins
cdef float buy_close_price = 0.0
cdef float buy_coins = 0.0
cdef float sum = 0.0
cdef int range_2 = 100
cdef int range_1 = 100
cdef list fields = []
save_path = '/media/usbstick/SPAN/'
file_name = "%s.csv"%(name)
completeName = os.path.join(save_path, file_name)
newarr[:,5] = np.maximum.accumulate(newarr[:,0])
newarr[:,6] = np.minimum.accumulate(newarr[:,0])
cdef list list_of_lists = []
for prc_buy in range(range_2):
for prc_sell in range(range_1):
buy_cnt_close = 0
newarr[:,1] = newarr[:,5] * prc_buy / prc
newarr[:,2] = np.where(newarr[:,0] < newarr[:,1], 1.0,0.0)
newarr[:,3] = newarr[:,6] / prc_sell / prc
newarr[:,4] = np.where(newarr[:,0] > newarr[:,3], 1.0,0.0)
for arr in range(arr_shape):
if (buy_cnt_close == 0 and newarr[arr][4] == 1):
buy_close_price = newarr[arr][0]
buy_coins = amount / buy_close_price
buy_cnt_close = 1
continue
elif (buy_cnt_close == 1 and newarr[arr][2] == 1):
sell_close = newarr[arr][0]
sell_coins = (buy_coins * sell_close) - amount
fields=['%s ,%s, %s, %s, %s, %s, %s, %s, %s, %s ,%s\n'%(str(min_plus_k), str(min_plus_v) ,str(span_1), str(span_2), str(span_3), str(prc_buy) ,str(prc_sell) ,str(buy_close_price) ,str(buy_coins), str(sell_close), str(sell_coins))]
list_of_lists.append(fields)
buy_cnt_close = 0
sum += sell_coins
if (sum > 0):
with open(completeName, "a+", newline="") as f:
writer = csv.writer(f)
writer.writerows(list_of_lists)
list_of_lists = []
else:
list_of_lists = []
newarr = None