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POBuilding an interleaved buffer for pyopengl and numpy
 

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    <p>I'm trying to batch up a bunch of vertices and texture coords in an interleaved array before sending it to pyOpengl's glInterleavedArrays/glDrawArrays. The only problem is that I'm unable to find a suitably fast enough way to append data into a numpy array. </p> <p>Is there a better way to do this? I would have thought it would be quicker to preallocate the array and then fill it with data but instead, generating a python list and converting it to a numpy array is "faster". Although 15ms for 4096 quads seems slow.</p> <p>I have included some example code and their timings.</p> <pre><code>#!/usr/bin/python import timeit import numpy import ctypes import random USE_RANDOM=True USE_STATIC_BUFFER=True STATIC_BUFFER = numpy.empty(4096*20, dtype=numpy.float32) def render(i): # pretend these are different each time if USE_RANDOM: tex_left, tex_right, tex_top, tex_bottom = random.random(), random.random(), random.random(), random.random() left, right, top, bottom = random.random(), random.random(), random.random(), random.random() else: tex_left, tex_right, tex_top, tex_bottom = 0.0, 1.0, 1.0, 0.0 left, right, top, bottom = -1.0, 1.0, 1.0, -1.0 ibuffer = ( tex_left, tex_bottom, left, bottom, 0.0, # Lower left corner tex_right, tex_bottom, right, bottom, 0.0, # Lower right corner tex_right, tex_top, right, top, 0.0, # Upper right corner tex_left, tex_top, left, top, 0.0, # upper left ) return ibuffer # create python list.. convert to numpy array at end def create_array_1(): ibuffer = [] for x in xrange(4096): data = render(x) ibuffer += data ibuffer = numpy.array(ibuffer, dtype=numpy.float32) return ibuffer # numpy.array, placing individually by index def create_array_2(): if USE_STATIC_BUFFER: ibuffer = STATIC_BUFFER else: ibuffer = numpy.empty(4096*20, dtype=numpy.float32) index = 0 for x in xrange(4096): data = render(x) for v in data: ibuffer[index] = v index += 1 return ibuffer # using slicing def create_array_3(): if USE_STATIC_BUFFER: ibuffer = STATIC_BUFFER else: ibuffer = numpy.empty(4096*20, dtype=numpy.float32) index = 0 for x in xrange(4096): data = render(x) ibuffer[index:index+20] = data index += 20 return ibuffer # using numpy.concat on a list of ibuffers def create_array_4(): ibuffer_concat = [] for x in xrange(4096): data = render(x) # converting makes a diff! data = numpy.array(data, dtype=numpy.float32) ibuffer_concat.append(data) return numpy.concatenate(ibuffer_concat) # using numpy array.put def create_array_5(): if USE_STATIC_BUFFER: ibuffer = STATIC_BUFFER else: ibuffer = numpy.empty(4096*20, dtype=numpy.float32) index = 0 for x in xrange(4096): data = render(x) ibuffer.put( xrange(index, index+20), data) index += 20 return ibuffer # using ctype array CTYPES_ARRAY = ctypes.c_float*(4096*20) def create_array_6(): ibuffer = [] for x in xrange(4096): data = render(x) ibuffer += data ibuffer = CTYPES_ARRAY(*ibuffer) return ibuffer def equals(a, b): for i,v in enumerate(a): if b[i] != v: return False return True if __name__ == "__main__": number = 100 # if random, don't try and compare arrays if not USE_RANDOM and not USE_STATIC_BUFFER: a = create_array_1() assert equals( a, create_array_2() ) assert equals( a, create_array_3() ) assert equals( a, create_array_4() ) assert equals( a, create_array_5() ) assert equals( a, create_array_6() ) t = timeit.Timer( "testing2.create_array_1()", "import testing2" ) print 'from list:', t.timeit(number)/number*1000.0, 'ms' t = timeit.Timer( "testing2.create_array_2()", "import testing2" ) print 'array: indexed:', t.timeit(number)/number*1000.0, 'ms' t = timeit.Timer( "testing2.create_array_3()", "import testing2" ) print 'array: slicing:', t.timeit(number)/number*1000.0, 'ms' t = timeit.Timer( "testing2.create_array_4()", "import testing2" ) print 'array: concat:', t.timeit(number)/number*1000.0, 'ms' t = timeit.Timer( "testing2.create_array_5()", "import testing2" ) print 'array: put:', t.timeit(number)/number*1000.0, 'ms' t = timeit.Timer( "testing2.create_array_6()", "import testing2" ) print 'ctypes float array:', t.timeit(number)/number*1000.0, 'ms' </code></pre> <p>Timings using random numbers:</p> <pre><code>$ python testing2.py from list: 15.0486779213 ms array: indexed: 24.8184704781 ms array: slicing: 50.2214789391 ms array: concat: 44.1691994667 ms array: put: 73.5879898071 ms ctypes float array: 20.6674289703 ms </code></pre> <p><strong>edit note: changed code to produce random numbers for each render to reduce object reuse and to simulate different vertices each time.</strong></p> <p><strong>edit note2: added static buffer and force all numpy.empty() to use dtype=float32</strong></p> <p><strong>note 1/Apr/2010: still no progress and I don't really feel that any of the answers have solved the problem yet.</strong></p>
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