動作環境
GeForce GTX 1070 (8GB)
ASRock Z170M Pro4S [Intel Z170chipset]
Ubuntu 14.04 LTS desktop amd64
TensorFlow v0.11
cuDNN v5.1 for Linux
CUDA v8.0
Python 2.7.6
IPython 5.1.0 -- An enhanced Interactive Python.
gcc (Ubuntu 4.8.4-2ubuntu1~14.04.3) 4.8.4
C++のコードで生成する係数をJupyter/matplotlibで画像表示したい。
それにはCのfwrite()結果をPythonで読込むことになりそう。
実装してみた。
v0.1 (1つの値)
C (write)
writeTest.c
#include <stdio.h>
#include <stdlib.h>
int main(void){
FILE *wfp;
float pi = 3.141592;
wfp = fopen("sample.bin","wb");
fwrite(&pi, sizeof(float), 1, wfp);
fclose(wfp);
}
Python (read)
参考 http://stackoverflow.com/questions/2146031/what-is-the-equivalent-of-fread-from-matlab-in-python
readTest.py
import numpy as np
import array
with open("sample.bin") as rfp:
a = array.array("f") # f: typecode for float
a.fromfile(rfp, 1)
print (a)
上記のtypecodeは以下を参考にした。
https://docs.python.org/3.1/library/array.html
実行
sample.bin生成
$ gcc writeTest.c && ./a.out
sample.bin読込み
$ python readTest.py
array('f', [3.141592025756836])
読めた。
v0.2 (3つの値)
C (write)
writeTest.c
#include <stdio.h>
#include <stdlib.h>
int main(void){
FILE *wfp;
float pi = 3.141592;
float napier = 2.718;
float avogadro1 = 6.022;
wfp = fopen("sample.bin","wb");
fwrite(&pi, sizeof(float), 1, wfp);
fwrite(&napier, sizeof(float), 1, wfp);
fwrite(&avogadro1, sizeof(float), 1, wfp);
fclose(wfp);
}
Python (read)
readTest.py
import numpy as np
import array
with open("sample.bin","rb") as rfp:
a = array.array("f") # f: typecode for float
a.fromfile(rfp, 3)
print (a)
実行
sample.bin生成
$ gcc writeTest.c && ./a.out
sample.bin読込み
$ python readTest.py
array('f', [3.141592025756836, 2.7179999351501465, 6.021999835968018])
v0.3 (size_t)対応
(追記 2016/12/19)
size_t型の読込みで躓いていた。
v0.1 @ http://qiita.com/7of9/items/68673ac3239532064c28
size_t型
sizeofPrint.c
#include <stdio.h>
#include <stdlib.h>
int main(void) {
printf("%ld\n", sizeof(size_t));
printf("%ld\n", sizeof(int));
}
実行
$ gcc sizeofPrint.c && ./a.out
8
4
こちらの環境ではsize_tは8。
C (write)
writeTest.c
#include <stdio.h>
#include <stdlib.h>
int main(void){
FILE *wfp;
size_t pi = 314;
float napier = 2.718;
float avogadro1 = 6.022;
wfp = fopen("sample.bin","wb");
fwrite(&pi, sizeof(size_t), 1, wfp);
fwrite(&napier, sizeof(float), 1, wfp);
fwrite(&avogadro1, sizeof(float), 1, wfp);
fclose(wfp);
}
Python (read)
Python側でsize_t(sizeof()=8)の値を読むには[unsigned long]型だろう。
https://docs.python.org/3.1/library/array.html
によるとL
readTest.py
import numpy as np
import array
with open("sample.bin","rb") as rfp:
szv = array.array("L") # L: typecodef for [unsigned long]
szv.fromfile(rfp, 1)
print (szv)
flv = array.array("f") # f: typecode for float
flv.fromfile(rfp, 2)
print (flv)
実行
$ python readTest.py
array('L', [314L])
array('f', [2.7179999351501465, 6.021999835968018])
v0.4 (double complex読込み)
(追記 2016/12/20)
double complex型を読込むにはどうするか。
double型でとりあえず読んでみた。
C (write)
アボガドロ数の実際の値とは違うがとりあえず。
writeTest.c
#include <stdio.h>
#include <stdlib.h>
#include <complex.h>
int main(void){
FILE *wfp;
size_t pi = 314;
float napier = 2.718;
double complex avogadro = 6.022 + 10.23 * I;
wfp = fopen("sample.bin","wb");
fwrite(&pi, sizeof(size_t), 1, wfp);
fwrite(&napier, sizeof(float), 1, wfp);
fwrite(&avogadro, sizeof(double complex), 1, wfp);
fclose(wfp);
}
Python (read)
readTest.py
import numpy as np
import array
with open("sample.bin","rb") as rfp:
szv = array.array("L") # L: typecodef for [unsigned long]
szv.fromfile(rfp, 1)
print (szv)
napier = array.array("f") # f: typecode for float
napier.fromfile(rfp, 1)
print (napier)
avogadro = array.array("d") # d: typecode for double
avogadro.fromfile(rfp, 2) # real and imaginary part of the complex number
print (avogadro)
実行
$ gcc writeTest.c && ./a.out
$ python readTest.py
array('L', [314L])
array('f', [2.7179999351501465])
array('d', [6.022, 10.23])
とりあえずdouble complexの実部と虚部の読込みはできた。
あとは２つの値を元にcomplex型にキャストするというような方法だろうか。