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 range

path: root/tests/rotate_test.py

blob: 92eff84761907e2a429a4823da2c3abe0e69869f (plain)