从 MatLab 数据在 Python 中创建 .PNG 图像 [英] Create .PNG images in Python from MatLab data

问题描述

实际上我正在尝试在 Python 中创建 .png 图像.数据来自 Matlab 文件.这是我的代码.当我运行时出现错误:

Actually i'm trying to create .png images in Python. The data is get from a Matlab file. Here my code. When i running i have the error:

回溯(最近一次调用最后一次):文件readFromMatLab.py"，第 20 行，在矩阵[x][y][z] = 数据[x][y][z]索引错误:列表索引超出范围

Traceback (most recent call last): File "readFromMatLab.py", line 20, in matriz[x][y][z] = data[x][y][z] IndexError: list index out of range

Matlab 文件的数据是 512x512x200 双数组.

The data of the Matlab file is 512x512x200 Double array.

> {'__version__': '1.0', 'St3D': array([[[ -4.98510788e-02, 
> -4.98139346e-02,  -4.97636073e-02, ...,
>           -5.19862428e-02,  -5.20095813e-02,  -5.20122990e-02],
>         [ -4.98249255e-02,  -4.97792210e-02,  -4.97507640e-02, ...,
>           -5.19832396e-02,  -5.19884452e-02,  -5.20089354e-02],
>         [ -4.98121755e-02,  -4.97751679e-02,  -4.97488529e-02, ...,
>           -5.19605824e-02,  -5.19734534e-02,  -5.20023879e-02],
>         ...,
>        [[  9.10799464e-05,   1.75287655e-04,   2.26928715e-04, ...,
>            1.10619951e-04,   1.04038395e-04,   7.44506576e-05],
>         [  6.29097917e-05,   1.20765020e-04,   1.91577341e-04, ...,
>            8.24078623e-05,   8.96774520e-05,   7.44268856e-05],
>         [  4.14273859e-05,   7.96562916e-05,   1.20801256e-04, ...,
>            9.05750282e-05,   8.13201896e-05,   6.77554603e-05],
>         ..., 
>         [  1.72297366e-04,   1.68849830e-04,   2.21771692e-04, ...,
>            2.30046391e-04,   2.51247428e-04,   2.58021432e-04],
>         [  2.06350049e-04,   1.92126121e-04,   2.58923928e-04, ...,
>            2.48977658e-04,   2.78131275e-04,   2.76242136e-04],
>         [  2.42915268e-04,   2.47607632e-04,   2.89283796e-04, ...,
>            2.58819021e-04,   2.76203977e-04,   2.82977241e-04]]]), '__header__': 'MATLAB 5.0 MAT-file, Platform: PCWIN64, Created on: Fri
> Sep 19 17:03:17 2014', '__globals__': []}


#!/usr/bin/python
# -*- coding: utf-8 -*-
import pprint
import scipy.io
import numpy
from scipy import misc
from PIL import Image

# import file into a dictionary
fMatLab = scipy.io.loadmat('St3D', mat_dtype = True, squeeze_me = True, struct_as_record=False)

# read in the structure
data = fMatLab['St3D']

matriz = [[[0 for col in range(data.shape[0])] for row in range(data.shape[1])] for x in range(data.shape[2])]

for x in range(0,data.shape[0]):
    for y in range(0,data.shape[1]):
        for z in range(0,data.shape[2]):
            matriz[x][y][z] = data[x][y][z]

for i in range(len(matriz)):
    #im = numpy.random.random_integers(0, 255, 512*512).reshape((512, 512))
    misc.imsave('transect_%s.png' % i, matriz[i])

from glob import glob
filelist = glob('transect*.png')
filelist.sort()

推荐答案

在我看来，您正在尝试将 misc.imsave 应用到数据的特定维度上的每个切片.但是代码效率很低，尤其是从matriz =到matriz[x][y][z] =.您已经将矩阵作为 numpy 数组存储在变量 data 中，因此不需要列表理解或循环.如果你想在一维上循环 numpy 数组的切片，例如，第三维，以应用一个函数，只需执行以下操作:

It looks to me like you are trying to apply misc.imsave to each slice along a certain dimension of your data. However, the code is very inefficient, especially from matriz = to matriz[x][y][z] =. You already have the matrix stored as a numpy array in the variable data, so there is no need for the list comprehension or the loops. If you want to loop over slices of a numpy array across one dimension, say, for example, the third dimension, to apply a function, just do something like this:

for i in xrange(data.shape[2]):
    some_function(data[:, :, i])

编辑在你的情况下，这将转化为

EDIT In your case, this would translate to

data = fMatLab['St3D']
for i in xrange(data.shape[2]):
    misc.imsave('transect_%s.png' % i, data[:, :, i])

此外，最后三行不应缩进.

And, as a quick final note, the last three lines shouldn't be indented.

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