DEVOCEAN

%%cython
#cython에서 numpy를 사용하기 위해서 아래 3개를 import 해야됨
import numpy as np
cimport numpy as np
np.import_array()
def np_foo(object f):
    print(f)
    
temp = np.array([i for i in range(100)])
np_foo(temp)

%%cython
import numpy as np
cimport numpy as np
np.import_array()
def cython_np_add(np.ndarray f):
    for _ in range(10000):
        f += 5    
    return f

def python_np_add(f):
    for _ in range(10000):
        f += 5
    return f

import time
temp = np.array([i for i in range(4000000)])

st = time.time()
cython_np_add(temp)
print(f"cython time : {time.time()-st}")
st = time.time()
python_np_add(temp)
print(f"python time : {time.time()-st}")
'''
cython time : 16.287737607955933
python time : 16.263918161392212
'''

%%cython
import numpy as np
cimport numpy as np
np.import_array()
def cython_reduce_sum_with_numpy(np.ndarray f):
    cdef long long i = 0;
    cdef long long ret = 0;
    cdef long long data_len = f.shape[0];
    for i in range(data_len):
        ret += f[i]   
    return ret

def python_reduce_sum_with_numpy(f):
    ret = 0
    for i in range(len(f)):
        ret += f[i]
    return ret

import time
temp = np.array([i for i in range(100000000)])

st = time.time()
cython_reduce_sum_with_numpy(temp)
print(f"cython time : {time.time()-st}")
st = time.time()
python_reduce_sum_with_numpy(temp)
print(f"python time : {time.time()-st}")
"""
cython time : 8.304328441619873
python time : 4.437905550003052
"""

%%cython
import numpy as np
cimport numpy as np
np.import_array()
#cython의 매개변수에서 활용하기 위한 ctypedef
ctypedef np.int_t DTYPE_t

#매개변수로 받은 np.ndarray의 Data Type과 ndim을 명기해줌
def cython_reduce_sum_with_numpy(np.ndarray[DTYPE_t, ndim = 1] f):
    cdef long long i = 0;
    cdef long long ret = 0;
    cdef long long data_len = f.shape[0];
    for i in range(data_len):
        ret += f[i]   
    return ret

def python_reduce_sum_with_numpy(f):
    ret = 0
    for i in range(len(f)):
        ret += f[i]
    return ret

import time
temp = np.array([2 for i in range(100000000)])

st = time.time()
cython_reduce_sum_with_numpy(temp)
print(f"cython time : {time.time()-st}")
st = time.time()
python_reduce_sum_with_numpy(temp)
print(f"python time : {time.time()-st}")
'''
cython time : 0.07773971557617188
python time : 3.8791370391845703
'''

%%cython --annotate
import numpy as np
cimport numpy as np
np.import_array()
DTYPE = np.int_
ctypedef np.int_t DTYPE_t

cimport cython
@cython.boundscheck(False) # turn off bounds-checking for entire function
@cython.wraparound(False)  # turn off negative index wrapping for entire function
def cython_reduce_sum_with_opt_numpy(np.ndarray[DTYPE_t, ndim = 1] f):
    cdef long long i = 0;
    cdef long long ret = 0;
    cdef long long data_len = f.shape[0];
    for i in range(data_len):
        ret += f[i]   
    return ret

def cython_reduce_sum_with_numpy(np.ndarray[DTYPE_t, ndim = 1] f):
    cdef long long i = 0;
    cdef long long ret = 0;
    cdef long long data_len = f.shape[0];
    for i in range(data_len):
        ret += f[i]   
    return ret

import time
temp = np.array([2 for i in range(100000000)])

st = time.time()
cython_reduce_sum_with_numpy(temp)
print(f"cython time : {time.time()-st}")
st = time.time()
cython_reduce_sum_with_opt_numpy(temp)
print(f"cython opt time : {time.time()-st}")
'''
cython time : 0.0887763500213623
cython opt time : 0.03389263153076172
'''