What is the equivalent of 'fread' from Matlab in Python?

Question

I have practically no knowledge of Matlab, and need to translate some parsing routines into Python. They are for large files, that are themselves divided into \'blocks\', an

Answer 1

Python Code for Reading a 1-Dimensional Array

When replacing Matlab with Python, I wanted to read binary data into a numpy.array, so I used numpy.fromfile to read the data into a 1-dimensional array:

import numpy as np

with open(inputfilename, 'rb') as fid:
    data_array = np.fromfile(fid, np.int16)

Some advantages of using numpy.fromfile versus other Python solutions include:

• Not having to manually determine the number of items to be read. You can specify them using the count= argument, but it defaults to -1 which indicates reading the entire file.

• Being able to specify either an open file object (as I did above with fid) or you can specify a filename. I prefer using an open file object, but if you wanted to use a filename, you could replace the two lines above with:

  data_array = numpy.fromfile(inputfilename, numpy.int16)
  

Matlab Code for a 2-Dimensional Array

Matlab's fread has the ability to read the data into a matrix of form [m, n] instead of just reading it into a column vector. For instance, to read data into a matrix with 2 rows use:

fid = fopen(inputfilename, 'r');
data_array = fread(fid, [2, inf], 'int16');
fclose(fid);

Equivalent Python Code for a 2-Dimensional Array

You can handle this scenario in Python using Numpy's shape and transpose.

import numpy as np

with open(inputfilename, 'rb') as fid:
    data_array = np.fromfile(fid, np.int16).reshape((-1, 2)).T

• The -1 tells numpy.reshape to infer the length of the array for that dimension based on the other dimension—the equivalent of Matlab's inf infinity representation.
• The .T transposes the array so that it is a 2-dimensional array with the first dimension—the axis—having a length of 2.

Answer 2

Really though, I want to know how to replicate [A, count] = fread(fid, 3, 'uint32');

In Matlab, one of fread()'s signatures is fread(fileID, sizeA, precision). This reads in the first sizeA elements (not bytes) of a file, each of a size sufficient for precision. In this case, since you're reading in uint32, each element is of size 32 bits, or 4 bytes.

So, instead, try io.readline(12) to get the first 3 4-byte elements from the file.

Answer 3

From the documentation of fread, it is a function to read binary data. The second argument specifies the size of the output vector, the third one the size/type of the items read.

In order to recreate this in Python, you can use the array module:

f = open(...)
import array
a = array.array("L")  # L is the typecode for uint32
a.fromfile(f, 3)

This will read read three uint32 values from the file f, which are available in a afterwards. From the documentation of fromfile:

Read n items (as machine values) from the file object f and append them to the end of the array. If less than n items are available, EOFError is raised, but the items that were available are still inserted into the array. f must be a real built-in file object; something else with a read() method won’t do.

Arrays implement the sequence protocol and therefore support the same operations as lists, but you can also use the .tolist() method to create a normal list from the array.

Answer 4

The first part is covered by Torsten's answer... you're going to need array or numarray to do anything with this data anyway.

As for the %08X and the hex2dec stuff, %08X is just the print format for those unit32 numbers (8 digit hex, exactly the same as Python), and hex2dec('4D445254') is matlab for 0x4D445254.

Finally, ~= in matlab is a bitwise compare; use == in Python.