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<p>我正在尝试在一个交错数组中批处理一堆顶点和纹理坐标,然后将其发送到pyOpengl的glinterleavedarray/gldrawarray。唯一的问题是,我无法找到一个足够快的适当方式将数据追加到numpy数组中。在</p>
<p>有更好的方法吗?我本以为预先分配数组,然后用数据填充它会更快,但是生成python列表并将其转换为numpy数组会“更快”。虽然4096个四头肌15毫秒看起来很慢。在</p>
<p>我已经包括了一些示例代码和它们的计时。在</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.<a href="https://www.cnpython.com/list/append" class="inner-link">append</a>(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>使用随机数计时:</p>
^{pr2}$
<p><strong>编辑说明:更改代码为每个渲染生成随机数,以减少对象重用,并每次模拟不同的顶点。</strong></p>
<p><strong>编辑注释2:添加了静态缓冲区和强制全部numpy.空的()使用dtype=float32</strong></p>
<p><strong>注1/2010年4月:仍然没有进展,我真的觉得没有任何答案能够解决问题。</strong></p>