पाइथन

Question

पर सी ++ डबल पॉइंटर पास करने से मैं नीचे की तरह पायथन के लिए एक-आयाम सरणी पारित कर सकता हूं। और मुझे आश्चर्य है कि क्या मैं cty+, numpy का उपयोग कर पाइथन में C++ डबल पॉइंटर सरणी पास कर सकता हूं।

test.cpp:

#include <stdio.h> 
extern "C" void cfun(const void * indatav, int rowcount, int colcount, void * outdatav); 

void cfun(const void * indatav, int rowcount, int colcount, void * outdatav) { 
    //void cfun(const double * indata, int rowcount, int colcount, double * outdata) { 
    const double * indata = (double *) indatav; 
    double * outdata = (double *) outdatav; 
    int i; 
    puts("Here we go!"); 
    for (i = 0; i < rowcount * colcount; ++i) { 
     outdata[i] = indata[i] * 4; 
    } 
    puts("Done!"); 
} 

test.py:

import numpy 
import ctypes 

indata = numpy.ones((5,6), dtype=numpy.double) 
outdata = numpy.zeros((5,6), dtype=numpy.double) 
lib = ctypes.cdll.LoadLibrary('./ctest.so') 
fun = lib.cfun 
# Here comes the fool part. 
#fun(ctypes.c_void_p(indata.ctypes.data), ctypes.c_void_p(outdata.ctypes.data)) 

fun(ctypes.c_void_p(indata.ctypes.data), ctypes.c_int(5), ctypes.c_int(6), 
    ctypes.c_void_p(outdata.ctypes.data)) 


print 'indata: %s' % indata 
print 'outdata: %s' % outdata 

Answer 1

यहाँ एक तरीका है। मुझे डबल ** के साथ numpy का उपयोग करने का एक अच्छा तरीका नहीं देखा।

test.cpp (विंडोज़)

#include <stdio.h> 

extern "C" __declspec(dllexport) void cfun(const double ** indata, int rowcount, int colcount, double ** outdata) { 
    for (int i = 0; i < rowcount; ++i) { 
     for (int j = 0; j < colcount; ++j) { 
      outdata[i][j] = indata[i][j] * 4; 
     } 
    } 
} 

test.py

import numpy 
import ctypes 

# Allocate array of double* 
indata = (ctypes.POINTER(ctypes.c_double) * 5)() 
for i in range(5): 
    # Allocate arrays of double 
    indata[i] = (ctypes.c_double * 6)() 
    for j in range(6): 
     indata[i][j] = 1.0 

outdata = (ctypes.POINTER(ctypes.c_double) * 5)() 
for i in range(5): 
    outdata[i] = (ctypes.c_double * 6)() 
    for j in range(6): 
     outdata[i][j] = 1.0 

lib = ctypes.cdll.LoadLibrary('test') 
fun = lib.cfun 

def dump(a,rows,cols): 
    for i in range(rows): 
     for j in range(cols): 
      print a[i][j], 
     print 

dump(indata,5,6) 
fun(ctypes.byref(indata),5,6,ctypes.byref(outdata)) 
dump(outdata,5,6) 

आउटपुट

1.0 1.0 1.0 1.0 1.0 1.0 
1.0 1.0 1.0 1.0 1.0 1.0 
1.0 1.0 1.0 1.0 1.0 1.0 
1.0 1.0 1.0 1.0 1.0 1.0 
1.0 1.0 1.0 1.0 1.0 1.0 
4.0 4.0 4.0 4.0 4.0 4.0 
4.0 4.0 4.0 4.0 4.0 4.0 
4.0 4.0 4.0 4.0 4.0 4.0 
4.0 4.0 4.0 4.0 4.0 4.0 
4.0 4.0 4.0 4.0 4.0 4.0