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-rw-r--r--tests/matrix_test.py327
1 files changed, 0 insertions, 327 deletions
diff --git a/tests/matrix_test.py b/tests/matrix_test.py
deleted file mode 100644
index c843025..0000000
--- a/tests/matrix_test.py
+++ /dev/null
@@ -1,327 +0,0 @@
-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
-
-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 + '/matrix_test.cu').read()
-
-mod = SourceModule(source, options=['-I' + source_directory], no_extern_c=True, cache_dir=False)
-
-det = mod.get_function('det')
-inv = mod.get_function('inv')
-matrixadd = mod.get_function('matrixadd')
-matrixsub = mod.get_function('matrixsub')
-matrixmul = mod.get_function('matrixmul')
-multiply = mod.get_function('multiply')
-matrixaddfloat = mod.get_function('matrixaddfloat')
-matrixsubfloat = mod.get_function('matrixsubfloat')
-matrixmulfloat = mod.get_function('matrixmulfloat')
-matrixdivfloat = mod.get_function('matrixdivfloat')
-floataddmatrix = mod.get_function('floataddmatrix')
-floatsubmatrix = mod.get_function('floatsubmatrix')
-floatmulmatrix = mod.get_function('floatmulmatrix')
-floatdivmatrix = mod.get_function('floatdivmatrix')
-matrixaddequals = mod.get_function('matrixaddequals')
-matrixsubequals = mod.get_function('matrixsubequals')
-matrixaddequalsfloat = mod.get_function('matrixaddequalsfloat')
-matrixsubequalsfloat = mod.get_function('matrixsubequalsfloat')
-matrixmulequalsfloat = mod.get_function('matrixmulequalsfloat')
-matrixdivequalsfloat = mod.get_function('matrixdivequalsfloat')
-outer = mod.get_function('outer')
-minusmatrix = mod.get_function('minusmatrix')
-
-size = {'block': (1,1,1), 'grid': (1,1)}
-
-for i in range(1):
- a = np.random.random_sample(size=9).astype(np.float32)
- b = np.random.random_sample(size=9).astype(np.float32)
- dest = np.empty(1, dtype=np.float32)
- c = np.int32(np.random.random_sample())
-
- print 'testing det...',
-
- det(cuda.In(a), cuda.Out(dest), **size)
-
- if not np.allclose(np.float32(np.linalg.det(a.reshape(3,3))), dest[0]):
- print 'fail'
- print np.float32(np.linalg.det(a.reshape(3,3)))
- print dest[0]
- else:
- print 'success'
-
- print 'testing inv...',
-
- dest = np.empty(9, dtype=np.float32)
-
- inv(cuda.In(a), cuda.Out(dest), **size)
-
- if not np.allclose(np.linalg.inv(a.reshape(3,3)).flatten().astype(np.float32), dest):
- print 'fail'
- print np.linalg.inv(a.reshape(3,3)).flatten().astype(np.float32)
- print dest
- else:
- print 'success'
-
- print 'testing matrixadd...',
-
- matrixadd(cuda.In(a), cuda.In(b), cuda.Out(dest), **size)
-
- if not np.allclose(a+b, dest):
- print 'fail'
- print a+b
- print dest
- else:
- print 'success'
-
- print 'testing matrixsub...',
-
- matrixsub(cuda.In(a), cuda.In(b), cuda.Out(dest), **size)
-
- if not np.allclose(a-b, dest):
- print 'fail'
- print a-b
- print dest
- else:
- print 'sucess'
-
- print 'testing matrixmul...',
-
- matrixmul(cuda.In(a), cuda.In(b), cuda.Out(dest), **size)
-
- if not np.allclose(np.dot(a.reshape(3,3),b.reshape(3,3)).flatten(), dest):
- print 'fail'
- print np.dot(a.reshape(3,3),b.reshape(3,3)).flatten()
- print dest
- else:
- print 'success'
-
- print 'testing multiply...',
-
- x_cpu = np.random.random_sample(size=3).astype(np.float32)
- x_gpu = np.array((x_cpu[0], x_cpu[1], x_cpu[2]), dtype=float3)
-
- dest = np.empty(1, dtype=float3)
-
- multiply(cuda.In(a), cuda.In(x_gpu), cuda.Out(dest), **size)
-
- m = a.reshape(3,3)
-
- if not np.allclose(np.dot(x_cpu,m[0]), dest[0]['x']) or \
- not np.allclose(np.dot(x_cpu,m[1]), dest[0]['y']) or \
- not np.allclose(np.dot(x_cpu,m[2]), dest[0]['z']):
- print 'fail'
- print np.dot(x_cpu,m[0])
- print np.dot(x_cpu,m[1])
- print np.dot(x_cpu,m[2])
- print dest[0]['x']
- print dest[0]['y']
- print dest[0]['z']
- else:
- print 'success'
-
- print 'testing matrixaddfloat...',
-
- dest = np.empty(9, dtype=np.float32)
-
- matrixaddfloat(cuda.In(a), c, cuda.Out(dest), **size)
-
- if not np.allclose(a+c, dest):
- print 'fail'
- print a+c
- print dest
- else:
- print 'success'
-
- print 'testing matrixsubfloat...',
-
- matrixsubfloat(cuda.In(a), c, cuda.Out(dest), **size)
-
- if not np.allclose(a-c, dest):
- print 'fail'
- print a-c
- print dest
- else:
- print 'success'
-
- print 'testing matrixmulfloat...',
-
- matrixmulfloat(cuda.In(a), c, cuda.Out(dest), **size)
-
- if not np.allclose(a*c, dest):
- print 'fail'
- print a-c
- print dest
- else:
- print 'success'
-
- print 'testing matrixdivfloat...',
-
- matrixdivfloat(cuda.In(a), c, cuda.Out(dest), **size)
-
- if not np.allclose(a/c, dest):
- print 'fail'
- print a/c
- print dest
- else:
- print 'success'
-
- print 'testing floataddmatrix...',
-
- floataddmatrix(cuda.In(a), c, cuda.Out(dest), **size)
-
- if not np.allclose(c+a, dest):
- print 'fail'
- print c+a
- print dest
- else:
- print 'success'
-
- print 'testing floatsubmatrix...',
-
- floatsubmatrix(cuda.In(a), c, cuda.Out(dest), **size)
-
- if not np.allclose(c-a, dest):
- print 'fail'
- print c-a
- print dest
- else:
- print 'success'
-
- print 'testing floatmulmatrix...',
-
- floatmulmatrix(cuda.In(a), c, cuda.Out(dest), **size)
-
- if not np.allclose(c*a, dest):
- print 'fail'
- print c*a
- print dest
- else:
- print 'success'
-
- print 'testing floatdivmatrix...',
-
- floatdivmatrix(cuda.In(a), c, cuda.Out(dest), **size)
-
- if not np.allclose(c/a, dest):
- print 'fail'
- print c/a
- print dest
- else:
- print 'success'
-
- print 'testing matrixaddequals...',
-
- dest = np.copy(a)
-
- matrixaddequals(cuda.InOut(dest), cuda.In(b), **size)
-
- if not np.allclose(a+b, dest):
- print 'fail'
- print a+b
- print dest
- else:
- print 'success'
-
- print 'testing matrixsubequals...',
-
- dest = np.copy(a)
-
- matrixsubequals(cuda.InOut(dest), cuda.In(b), **size)
-
- if not np.allclose(a-b, dest):
- print 'fail'
- print a-b
- print dest
- else:
- print 'success'
-
- print 'testing matrixaddequalsfloat...',
-
- dest = np.copy(a)
-
- matrixaddequalsfloat(cuda.InOut(dest), c, **size)
-
- if not np.allclose(a+c, dest):
- print 'fail'
- print a+c
- print dest
- else:
- print 'success'
-
- print 'testing matrixsubequalsfloat...',
-
- dest = np.copy(a)
-
- matrixsubequalsfloat(cuda.InOut(dest), c, **size)
-
- if not np.allclose(a-c, dest):
- print 'fail'
- print a-c
- print dest
- else:
- print 'success'
-
- print 'testing matrixmulequalsfloat...',
-
- dest = np.copy(a)
-
- matrixmulequalsfloat(cuda.InOut(dest), c, **size)
-
- if not np.allclose(a*c, dest):
- print 'fail'
- print a*c
- print dest
- else:
- print 'success'
-
- print 'testing matrixdivequalsfloat...',
-
- dest = np.copy(a)
-
- matrixdivequalsfloat(cuda.InOut(dest), c, **size)
-
- if not np.allclose(a/c, dest):
- print 'fail'
- print a*c
- print dest
- else:
- print 'success'
-
- print 'testing outer...',
-
- x1_cpu = np.random.random_sample(size=3).astype(np.float32)
- x2_cpu = np.random.random_sample(size=3).astype(np.float32)
-
- x1_gpu = np.array((x1_cpu[0], x1_cpu[1], x1_cpu[2]), dtype=float3)
- x2_gpu = np.array((x2_cpu[0], x2_cpu[1], x2_cpu[2]), dtype=float3)
-
- outer(x1_gpu, x2_gpu, cuda.Out(dest), **size)
-
- if not np.allclose(np.outer(x1_cpu, x2_cpu).flatten(), dest):
- print 'fail'
- print np.outer(x1_cpu, x2_cpu).flatten()
- print dest
- else:
- print 'success'
-
- print 'testing minus matrix...',
-
- dest = np.copy(a)
-
- minusmatrix(cuda.In(a), cuda.Out(dest), **size)
-
- if not np.allclose(-a, dest):
- print 'fail'
- print -a
- print dest
- else:
- print 'success'
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