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    <p>You could do it with the <code>struct</code> module. Here's a simple example based on the file formatting information you mentioned in a comment:</p> <pre><code>import struct def read_complex_array(filename, M, N): row_fmt = '={}h'.format(N) # "=" prefix means integers in native byte-order row_len = struct.calcsize(row_fmt) result = [] with open(filename, "rb" ) as input: for col in xrange(M): reals = struct.unpack(row_fmt, input.read(row_len)) imags = struct.unpack(row_fmt, input.read(row_len)) cmplx = [complex(r,i) for r,i in zip(reals, imags)] result.append(cmplx) return result </code></pre> <p>This will return a list of complex-number lists, as can be seen in this output from a trivial test I ran:</p> <pre><code>[ [ 0.0+ 1.0j 1.0+ 2.0j 2.0+ 3.0j 3.0+ 4.0j], [256.0+257.0j 257.0+258.0j 258.0+259.0j 259.0+260.0j], [512.0+513.0j 513.0+514.0j 514.0+515.0j 515.0+516.0j] ] </code></pre> <p>Both the real and imaginary parts of complex numbers in Python are usually represented as a pair of machine-level double precision floating point numbers.</p> <p>You could also use the <code>array</code> module. Here's the same thing using it:</p> <pre><code>import array def read_complex_array2(filename, M, N): result = [] with open(filename, "rb" ) as input: for col in xrange(M): reals = array.array('h') reals.fromfile(input, N) # reals.byteswap() # if necessary imags = array.array('h') imags.fromfile(input, N) # imags.byteswap() # if necessary cmplx = [complex(r,i) for r,i in zip(reals, imags)] result.append(cmplx) return result </code></pre> <p>As you can see, they're very similar, so it's not clear there's a big advantage to using one over the other. I suspect the <code>array</code> based version might be faster, but that would have to be determined by actually timing it with some real data to be able to say with any certainty.</p>
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    1. COthank you. It worked. I didn't check speed. I will test later again and post which one is faster.
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    2. COYou're welcome -- and thanks for accepting my answer. There are other, trickier and likely faster ways of doing it than what I wrote, but I tried to keep things simple and understandable. Please let us know what you're timing measurements are after you've made them.
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