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import os
import numpy as np
from pycuda import autoinit
from pycuda.compiler import SourceModule
import pycuda.driver as cuda
from pycuda import gpuarray
float3 = gpuarray.vec.float3
def rotate(x, phi, n):
x = np.asarray(x)
n = np.asarray(n)
r = np.cos(phi)*np.identity(3) + (1-np.cos(phi))*np.outer(n,n) + \
np.sin(phi)*np.array([[0,n[2],-n[1]],[-n[2],0,n[0]],[n[1],-n[0],0]])
return np.inner(x,r)
print 'device %s' % autoinit.device.name()
current_directory = os.path.split(os.path.realpath(__file__))[0]
source_directory = current_directory + '/../src'
source = open(current_directory + '/rotate_test.cu').read()
mod = SourceModule(source, options=['-I' + source_directory], no_extern_c=True, cache_dir=False)
rotate_gpu = mod.get_function('rotate')
size = {'block': (100,1,1), 'grid': (1,1)}
a = np.empty(size['block'][0], dtype=float3)
n = np.empty(size['block'][0], dtype=float3)
phi = np.random.random_sample(size=a.size).astype(np.float32)
a['x'] = np.random.random_sample(size=a.size)
a['y'] = np.random.random_sample(size=a.size)
a['z'] = np.random.random_sample(size=a.size)
n['x'] = np.random.random_sample(size=n.size)
n['y'] = np.random.random_sample(size=n.size)
n['z'] = np.random.random_sample(size=n.size)
a['x'] = np.ones(a.size)
a['y'] = np.zeros(a.size)
a['z'] = np.zeros(a.size)
n['x'] = np.zeros(n.size)
n['y'] = np.zeros(n.size)
n['z'] = np.ones(n.size)
phi = np.array([np.pi/2]*a.size).astype(np.float32)
def testrotate():
dest = np.empty(a.size, dtype=float3)
rotate_gpu(cuda.In(a), cuda.In(phi), cuda.In(n), cuda.Out(dest), **size)
for v, theta, w, rdest in zip(a,phi,n,dest):
r = rotate((v['x'], v['y'], v['z']), theta, (w['x'], w['y'], w['z']))
if not np.allclose(rdest['x'], r[0]) or \
not np.allclose(rdest['y'], r[1]) or \
not np.allclose(rdest['z'], r[2]):
print v
print theta
print w
print r
print rdest
assert False
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