不同的結果加載二進制文件的matlab和python

我想從一個讀出板讀取二進制文件，將被轉換爲圖像。在Matlab中，所有字節都被正確讀取並且圖像完整地填充。但在Python（ver2.7使用anaconda）中，每127列有一行零。的Matlab代碼是：不同的結果加載二進制文件的matlab和python

fid = fopen(filename); 
Rawdata = fread(fid,'uint8'); 
Data1d = Rawdata(2:2:end).* 256+ Rawdata(1:2:end) ; 
% converts Data1 to a 2D vector, adding a row of zeros to make the reshape 
% possible to 3D 
Data2d = [reshape(Data1d,4127,1792); zeros(1,1792)]; 
% reshapes again, but adding a new dimension 
Data3d = reshape(Data2d(:),129,32,1792); 
% selects the first 128 values in the first dimension 
Data3d = Data3d(1:128,:,:); 
Data2d = reshape(Data3d(:),4096,1792); 
Data2d = Data2d'; 
CMVimage = Data2d; 
fclose(fid); %VGM 2017-01-14 the file should be closed.

在蟒我嘗試使用f.read（）具有相同的結果從蟒np.fromfile（）和直接讀取。

import numpy as np 
import matplotlib.pyplot as plt 
""" 
reads the input .dat file and converts it to an image 
Problem: line of zeros every 127 columns in columns: 127,257,368... 
curiosly, the columns are in the position of the new byte. 
In matlab it works very well. 
""" 


def readDatFile(filename): 
""" reads the binary file in python not in numpy 
the data is byte type and it is converted to integer. 

    """ 
    import binascii 
    f = open(filename, 'rb') 
    data = f.read() 
    #dataByte = bytearray(data) 

    f.close() 
    data_out = [] 
    for num in data: 
     aux = int(binascii.hexlify(num), 16) 
     data_out.append(aux) 
     #print aux 

    myarray = np.asarray(data_out) 
    return myarray 




def rawConversionNew(filename): 
    # reads data from a binary file with tupe uint 
# f = open(filename, 'rb') 
# Rawdata = np.fromfile(f, dtype=np.uint8) 
# f.close() 

    Rawdata = readDatFile(filename) 

    ## gets the image 
    Data1d = 256*Rawdata[1::2] + Rawdata[0::2]    
    Data2d = Data1d.reshape(1792,4127) 
    Data2d = Data2d.T 
    Data2d = np.vstack([Data2d,np.zeros((1,1792),dtype=np.uint16)]) 
    Data3d = Data2d.reshape(129,32,1792) 
    Data3d = Data3d[0:128,:,:] 
    #plt.figure() 
    #plt.plot(np.arange(Data3d.shape[0]),Data3d[:,1,1]) 
    #print (Data3d[:,0,0]) 
    CMVimage = Data3d.reshape(4096,1792).T 

    return CMVimage

來源

2017-07-11 vicgarmu

你確定你的索引是正確的？我在過去將matlab轉換爲python時遇到了麻煩，而這一切都歸功於數組索引... – DavidG

謝謝@DavidG。事實上有兩個錯誤，沒有將文件標記爲二進制文件（「rb」）和重塑，這在Matlab和numpy中以不同的方式完成。我嘗試着上傳並接受你的回覆，但我沒有管理。 – vicgarmu

可能最好自己寫答案，然後將其標記爲已接受，因爲我沒有做太多的工作！ – DavidG

實際上有兩個錯誤，不標記該文件作爲二進制（「RB」）和重塑，這是在Matlab和numpy的不同的方式完成。如果使用重塑完成整形（dim1，dim2，order ='F'），結果是相同的。檢查：Matlab vs Python: Reshape

來源

2017-07-13 12:02:09 vicgarmu

不同的結果加載二進制文件的matlab和python

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