656 lines
19 KiB
Python
656 lines
19 KiB
Python
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# Test interfaces to fortran blas.
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#
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# The tests are more of interface than they are of the underlying blas.
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# Only very small matrices checked -- N=3 or so.
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#
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# !! Complex calculations really aren't checked that carefully.
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# !! Only real valued complex numbers are used in tests.
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from __future__ import division, print_function, absolute_import
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from numpy import float32, float64, complex64, complex128, arange, array, \
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zeros, shape, transpose, newaxis, common_type, conjugate
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from scipy.linalg import _fblas as fblas
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from scipy._lib.six import xrange
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from numpy.testing import assert_array_equal, \
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assert_allclose, assert_array_almost_equal, assert_
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# decimal accuracy to require between Python and LAPACK/BLAS calculations
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accuracy = 5
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# Since numpy.dot likely uses the same blas, use this routine
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# to check.
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def matrixmultiply(a, b):
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if len(b.shape) == 1:
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b_is_vector = True
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b = b[:, newaxis]
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else:
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b_is_vector = False
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assert_(a.shape[1] == b.shape[0])
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c = zeros((a.shape[0], b.shape[1]), common_type(a, b))
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for i in xrange(a.shape[0]):
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for j in xrange(b.shape[1]):
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s = 0
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for k in xrange(a.shape[1]):
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s += a[i, k] * b[k, j]
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c[i, j] = s
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if b_is_vector:
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c = c.reshape((a.shape[0],))
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return c
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##################################################
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# Test blas ?axpy
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class BaseAxpy(object):
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''' Mixin class for axpy tests '''
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def test_default_a(self):
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x = arange(3., dtype=self.dtype)
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y = arange(3., dtype=x.dtype)
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real_y = x*1.+y
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y = self.blas_func(x, y)
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assert_array_equal(real_y, y)
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def test_simple(self):
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x = arange(3., dtype=self.dtype)
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y = arange(3., dtype=x.dtype)
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real_y = x*3.+y
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y = self.blas_func(x, y, a=3.)
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assert_array_equal(real_y, y)
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def test_x_stride(self):
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x = arange(6., dtype=self.dtype)
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y = zeros(3, x.dtype)
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y = arange(3., dtype=x.dtype)
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real_y = x[::2]*3.+y
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y = self.blas_func(x, y, a=3., n=3, incx=2)
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assert_array_equal(real_y, y)
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def test_y_stride(self):
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x = arange(3., dtype=self.dtype)
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y = zeros(6, x.dtype)
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real_y = x*3.+y[::2]
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y = self.blas_func(x, y, a=3., n=3, incy=2)
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assert_array_equal(real_y, y[::2])
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def test_x_and_y_stride(self):
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x = arange(12., dtype=self.dtype)
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y = zeros(6, x.dtype)
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real_y = x[::4]*3.+y[::2]
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y = self.blas_func(x, y, a=3., n=3, incx=4, incy=2)
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assert_array_equal(real_y, y[::2])
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def test_x_bad_size(self):
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x = arange(12., dtype=self.dtype)
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y = zeros(6, x.dtype)
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try:
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self.blas_func(x, y, n=4, incx=5)
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except: # what kind of error should be caught?
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return
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# should catch error and never get here
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assert_(0)
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def test_y_bad_size(self):
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x = arange(12., dtype=self.dtype)
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y = zeros(6, x.dtype)
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try:
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self.blas_func(x, y, n=3, incy=5)
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except: # what kind of error should be caught?
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return
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# should catch error and never get here
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assert_(0)
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try:
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class TestSaxpy(BaseAxpy):
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blas_func = fblas.saxpy
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dtype = float32
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except AttributeError:
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class TestSaxpy:
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pass
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class TestDaxpy(BaseAxpy):
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blas_func = fblas.daxpy
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dtype = float64
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try:
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class TestCaxpy(BaseAxpy):
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blas_func = fblas.caxpy
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dtype = complex64
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except AttributeError:
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class TestCaxpy:
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pass
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class TestZaxpy(BaseAxpy):
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blas_func = fblas.zaxpy
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dtype = complex128
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##################################################
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# Test blas ?scal
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class BaseScal(object):
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''' Mixin class for scal testing '''
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def test_simple(self):
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x = arange(3., dtype=self.dtype)
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real_x = x*3.
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x = self.blas_func(3., x)
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assert_array_equal(real_x, x)
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def test_x_stride(self):
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x = arange(6., dtype=self.dtype)
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real_x = x.copy()
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real_x[::2] = x[::2]*array(3., self.dtype)
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x = self.blas_func(3., x, n=3, incx=2)
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assert_array_equal(real_x, x)
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def test_x_bad_size(self):
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x = arange(12., dtype=self.dtype)
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try:
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self.blas_func(2., x, n=4, incx=5)
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except: # what kind of error should be caught?
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return
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# should catch error and never get here
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assert_(0)
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try:
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class TestSscal(BaseScal):
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blas_func = fblas.sscal
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dtype = float32
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except AttributeError:
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class TestSscal:
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pass
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class TestDscal(BaseScal):
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blas_func = fblas.dscal
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dtype = float64
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try:
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class TestCscal(BaseScal):
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blas_func = fblas.cscal
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dtype = complex64
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except AttributeError:
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class TestCscal:
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pass
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class TestZscal(BaseScal):
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blas_func = fblas.zscal
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dtype = complex128
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##################################################
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# Test blas ?copy
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class BaseCopy(object):
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''' Mixin class for copy testing '''
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def test_simple(self):
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x = arange(3., dtype=self.dtype)
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y = zeros(shape(x), x.dtype)
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y = self.blas_func(x, y)
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assert_array_equal(x, y)
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def test_x_stride(self):
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x = arange(6., dtype=self.dtype)
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y = zeros(3, x.dtype)
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y = self.blas_func(x, y, n=3, incx=2)
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assert_array_equal(x[::2], y)
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def test_y_stride(self):
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x = arange(3., dtype=self.dtype)
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y = zeros(6, x.dtype)
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y = self.blas_func(x, y, n=3, incy=2)
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assert_array_equal(x, y[::2])
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def test_x_and_y_stride(self):
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x = arange(12., dtype=self.dtype)
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y = zeros(6, x.dtype)
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y = self.blas_func(x, y, n=3, incx=4, incy=2)
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assert_array_equal(x[::4], y[::2])
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def test_x_bad_size(self):
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x = arange(12., dtype=self.dtype)
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y = zeros(6, x.dtype)
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try:
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self.blas_func(x, y, n=4, incx=5)
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except: # what kind of error should be caught?
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return
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# should catch error and never get here
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assert_(0)
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def test_y_bad_size(self):
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x = arange(12., dtype=self.dtype)
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y = zeros(6, x.dtype)
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try:
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self.blas_func(x, y, n=3, incy=5)
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except: # what kind of error should be caught?
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return
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# should catch error and never get here
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assert_(0)
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# def test_y_bad_type(self):
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## Hmmm. Should this work? What should be the output.
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# x = arange(3.,dtype=self.dtype)
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# y = zeros(shape(x))
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# self.blas_func(x,y)
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# assert_array_equal(x,y)
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try:
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class TestScopy(BaseCopy):
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blas_func = fblas.scopy
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dtype = float32
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except AttributeError:
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class TestScopy:
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pass
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class TestDcopy(BaseCopy):
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blas_func = fblas.dcopy
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dtype = float64
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try:
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class TestCcopy(BaseCopy):
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blas_func = fblas.ccopy
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dtype = complex64
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except AttributeError:
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class TestCcopy:
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pass
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class TestZcopy(BaseCopy):
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blas_func = fblas.zcopy
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dtype = complex128
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##################################################
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# Test blas ?swap
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class BaseSwap(object):
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''' Mixin class for swap tests '''
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def test_simple(self):
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x = arange(3., dtype=self.dtype)
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y = zeros(shape(x), x.dtype)
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desired_x = y.copy()
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desired_y = x.copy()
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x, y = self.blas_func(x, y)
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assert_array_equal(desired_x, x)
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assert_array_equal(desired_y, y)
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def test_x_stride(self):
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x = arange(6., dtype=self.dtype)
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y = zeros(3, x.dtype)
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desired_x = y.copy()
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desired_y = x.copy()[::2]
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x, y = self.blas_func(x, y, n=3, incx=2)
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assert_array_equal(desired_x, x[::2])
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assert_array_equal(desired_y, y)
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def test_y_stride(self):
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x = arange(3., dtype=self.dtype)
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y = zeros(6, x.dtype)
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desired_x = y.copy()[::2]
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desired_y = x.copy()
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x, y = self.blas_func(x, y, n=3, incy=2)
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assert_array_equal(desired_x, x)
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assert_array_equal(desired_y, y[::2])
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def test_x_and_y_stride(self):
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x = arange(12., dtype=self.dtype)
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y = zeros(6, x.dtype)
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desired_x = y.copy()[::2]
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desired_y = x.copy()[::4]
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x, y = self.blas_func(x, y, n=3, incx=4, incy=2)
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assert_array_equal(desired_x, x[::4])
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assert_array_equal(desired_y, y[::2])
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def test_x_bad_size(self):
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x = arange(12., dtype=self.dtype)
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y = zeros(6, x.dtype)
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try:
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self.blas_func(x, y, n=4, incx=5)
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except: # what kind of error should be caught?
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return
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# should catch error and never get here
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assert_(0)
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def test_y_bad_size(self):
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x = arange(12., dtype=self.dtype)
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y = zeros(6, x.dtype)
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try:
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self.blas_func(x, y, n=3, incy=5)
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except: # what kind of error should be caught?
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return
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# should catch error and never get here
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assert_(0)
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try:
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class TestSswap(BaseSwap):
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blas_func = fblas.sswap
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dtype = float32
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except AttributeError:
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class TestSswap:
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pass
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class TestDswap(BaseSwap):
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blas_func = fblas.dswap
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dtype = float64
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try:
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class TestCswap(BaseSwap):
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blas_func = fblas.cswap
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dtype = complex64
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except AttributeError:
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class TestCswap:
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pass
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class TestZswap(BaseSwap):
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blas_func = fblas.zswap
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dtype = complex128
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##################################################
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# Test blas ?gemv
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# This will be a mess to test all cases.
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class BaseGemv(object):
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''' Mixin class for gemv tests '''
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def get_data(self, x_stride=1, y_stride=1):
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mult = array(1, dtype=self.dtype)
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if self.dtype in [complex64, complex128]:
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mult = array(1+1j, dtype=self.dtype)
|
||
|
|
from numpy.random import normal, seed
|
||
|
|
seed(1234)
|
||
|
|
alpha = array(1., dtype=self.dtype) * mult
|
||
|
|
beta = array(1., dtype=self.dtype) * mult
|
||
|
|
a = normal(0., 1., (3, 3)).astype(self.dtype) * mult
|
||
|
|
x = arange(shape(a)[0]*x_stride, dtype=self.dtype) * mult
|
||
|
|
y = arange(shape(a)[1]*y_stride, dtype=self.dtype) * mult
|
||
|
|
return alpha, beta, a, x, y
|
||
|
|
|
||
|
|
def test_simple(self):
|
||
|
|
alpha, beta, a, x, y = self.get_data()
|
||
|
|
desired_y = alpha*matrixmultiply(a, x)+beta*y
|
||
|
|
y = self.blas_func(alpha, a, x, beta, y)
|
||
|
|
assert_array_almost_equal(desired_y, y)
|
||
|
|
|
||
|
|
def test_default_beta_y(self):
|
||
|
|
alpha, beta, a, x, y = self.get_data()
|
||
|
|
desired_y = matrixmultiply(a, x)
|
||
|
|
y = self.blas_func(1, a, x)
|
||
|
|
assert_array_almost_equal(desired_y, y)
|
||
|
|
|
||
|
|
def test_simple_transpose(self):
|
||
|
|
alpha, beta, a, x, y = self.get_data()
|
||
|
|
desired_y = alpha*matrixmultiply(transpose(a), x)+beta*y
|
||
|
|
y = self.blas_func(alpha, a, x, beta, y, trans=1)
|
||
|
|
assert_array_almost_equal(desired_y, y)
|
||
|
|
|
||
|
|
def test_simple_transpose_conj(self):
|
||
|
|
alpha, beta, a, x, y = self.get_data()
|
||
|
|
desired_y = alpha*matrixmultiply(transpose(conjugate(a)), x)+beta*y
|
||
|
|
y = self.blas_func(alpha, a, x, beta, y, trans=2)
|
||
|
|
assert_array_almost_equal(desired_y, y)
|
||
|
|
|
||
|
|
def test_x_stride(self):
|
||
|
|
alpha, beta, a, x, y = self.get_data(x_stride=2)
|
||
|
|
desired_y = alpha*matrixmultiply(a, x[::2])+beta*y
|
||
|
|
y = self.blas_func(alpha, a, x, beta, y, incx=2)
|
||
|
|
assert_array_almost_equal(desired_y, y)
|
||
|
|
|
||
|
|
def test_x_stride_transpose(self):
|
||
|
|
alpha, beta, a, x, y = self.get_data(x_stride=2)
|
||
|
|
desired_y = alpha*matrixmultiply(transpose(a), x[::2])+beta*y
|
||
|
|
y = self.blas_func(alpha, a, x, beta, y, trans=1, incx=2)
|
||
|
|
assert_array_almost_equal(desired_y, y)
|
||
|
|
|
||
|
|
def test_x_stride_assert(self):
|
||
|
|
# What is the use of this test?
|
||
|
|
alpha, beta, a, x, y = self.get_data(x_stride=2)
|
||
|
|
try:
|
||
|
|
y = self.blas_func(1, a, x, 1, y, trans=0, incx=3)
|
||
|
|
assert_(0)
|
||
|
|
except:
|
||
|
|
pass
|
||
|
|
try:
|
||
|
|
y = self.blas_func(1, a, x, 1, y, trans=1, incx=3)
|
||
|
|
assert_(0)
|
||
|
|
except:
|
||
|
|
pass
|
||
|
|
|
||
|
|
def test_y_stride(self):
|
||
|
|
alpha, beta, a, x, y = self.get_data(y_stride=2)
|
||
|
|
desired_y = y.copy()
|
||
|
|
desired_y[::2] = alpha*matrixmultiply(a, x)+beta*y[::2]
|
||
|
|
y = self.blas_func(alpha, a, x, beta, y, incy=2)
|
||
|
|
assert_array_almost_equal(desired_y, y)
|
||
|
|
|
||
|
|
def test_y_stride_transpose(self):
|
||
|
|
alpha, beta, a, x, y = self.get_data(y_stride=2)
|
||
|
|
desired_y = y.copy()
|
||
|
|
desired_y[::2] = alpha*matrixmultiply(transpose(a), x)+beta*y[::2]
|
||
|
|
y = self.blas_func(alpha, a, x, beta, y, trans=1, incy=2)
|
||
|
|
assert_array_almost_equal(desired_y, y)
|
||
|
|
|
||
|
|
def test_y_stride_assert(self):
|
||
|
|
# What is the use of this test?
|
||
|
|
alpha, beta, a, x, y = self.get_data(y_stride=2)
|
||
|
|
try:
|
||
|
|
y = self.blas_func(1, a, x, 1, y, trans=0, incy=3)
|
||
|
|
assert_(0)
|
||
|
|
except:
|
||
|
|
pass
|
||
|
|
try:
|
||
|
|
y = self.blas_func(1, a, x, 1, y, trans=1, incy=3)
|
||
|
|
assert_(0)
|
||
|
|
except:
|
||
|
|
pass
|
||
|
|
|
||
|
|
|
||
|
|
try:
|
||
|
|
class TestSgemv(BaseGemv):
|
||
|
|
blas_func = fblas.sgemv
|
||
|
|
dtype = float32
|
||
|
|
|
||
|
|
def test_sgemv_on_osx(self):
|
||
|
|
from itertools import product
|
||
|
|
import sys
|
||
|
|
import numpy as np
|
||
|
|
|
||
|
|
if sys.platform != 'darwin':
|
||
|
|
return
|
||
|
|
|
||
|
|
def aligned_array(shape, align, dtype, order='C'):
|
||
|
|
# Make array shape `shape` with aligned at `align` bytes
|
||
|
|
d = dtype()
|
||
|
|
# Make array of correct size with `align` extra bytes
|
||
|
|
N = np.prod(shape)
|
||
|
|
tmp = np.zeros(N * d.nbytes + align, dtype=np.uint8)
|
||
|
|
address = tmp.__array_interface__["data"][0]
|
||
|
|
# Find offset into array giving desired alignment
|
||
|
|
for offset in range(align):
|
||
|
|
if (address + offset) % align == 0:
|
||
|
|
break
|
||
|
|
tmp = tmp[offset:offset+N*d.nbytes].view(dtype=dtype)
|
||
|
|
return tmp.reshape(shape, order=order)
|
||
|
|
|
||
|
|
def as_aligned(arr, align, dtype, order='C'):
|
||
|
|
# Copy `arr` into an aligned array with same shape
|
||
|
|
aligned = aligned_array(arr.shape, align, dtype, order)
|
||
|
|
aligned[:] = arr[:]
|
||
|
|
return aligned
|
||
|
|
|
||
|
|
def assert_dot_close(A, X, desired):
|
||
|
|
assert_allclose(self.blas_func(1.0, A, X), desired,
|
||
|
|
rtol=1e-5, atol=1e-7)
|
||
|
|
|
||
|
|
testdata = product((15, 32), (10000,), (200, 89), ('C', 'F'))
|
||
|
|
for align, m, n, a_order in testdata:
|
||
|
|
A_d = np.random.rand(m, n)
|
||
|
|
X_d = np.random.rand(n)
|
||
|
|
desired = np.dot(A_d, X_d)
|
||
|
|
# Calculation with aligned single precision
|
||
|
|
A_f = as_aligned(A_d, align, np.float32, order=a_order)
|
||
|
|
X_f = as_aligned(X_d, align, np.float32, order=a_order)
|
||
|
|
assert_dot_close(A_f, X_f, desired)
|
||
|
|
|
||
|
|
except AttributeError:
|
||
|
|
class TestSgemv:
|
||
|
|
pass
|
||
|
|
|
||
|
|
|
||
|
|
class TestDgemv(BaseGemv):
|
||
|
|
blas_func = fblas.dgemv
|
||
|
|
dtype = float64
|
||
|
|
|
||
|
|
|
||
|
|
try:
|
||
|
|
class TestCgemv(BaseGemv):
|
||
|
|
blas_func = fblas.cgemv
|
||
|
|
dtype = complex64
|
||
|
|
except AttributeError:
|
||
|
|
class TestCgemv:
|
||
|
|
pass
|
||
|
|
|
||
|
|
|
||
|
|
class TestZgemv(BaseGemv):
|
||
|
|
blas_func = fblas.zgemv
|
||
|
|
dtype = complex128
|
||
|
|
|
||
|
|
|
||
|
|
"""
|
||
|
|
##################################################
|
||
|
|
### Test blas ?ger
|
||
|
|
### This will be a mess to test all cases.
|
||
|
|
|
||
|
|
class BaseGer(object):
|
||
|
|
def get_data(self,x_stride=1,y_stride=1):
|
||
|
|
from numpy.random import normal, seed
|
||
|
|
seed(1234)
|
||
|
|
alpha = array(1., dtype = self.dtype)
|
||
|
|
a = normal(0.,1.,(3,3)).astype(self.dtype)
|
||
|
|
x = arange(shape(a)[0]*x_stride,dtype=self.dtype)
|
||
|
|
y = arange(shape(a)[1]*y_stride,dtype=self.dtype)
|
||
|
|
return alpha,a,x,y
|
||
|
|
def test_simple(self):
|
||
|
|
alpha,a,x,y = self.get_data()
|
||
|
|
# tranpose takes care of Fortran vs. C(and Python) memory layout
|
||
|
|
desired_a = alpha*transpose(x[:,newaxis]*y) + a
|
||
|
|
self.blas_func(x,y,a)
|
||
|
|
assert_array_almost_equal(desired_a,a)
|
||
|
|
def test_x_stride(self):
|
||
|
|
alpha,a,x,y = self.get_data(x_stride=2)
|
||
|
|
desired_a = alpha*transpose(x[::2,newaxis]*y) + a
|
||
|
|
self.blas_func(x,y,a,incx=2)
|
||
|
|
assert_array_almost_equal(desired_a,a)
|
||
|
|
def test_x_stride_assert(self):
|
||
|
|
alpha,a,x,y = self.get_data(x_stride=2)
|
||
|
|
try:
|
||
|
|
self.blas_func(x,y,a,incx=3)
|
||
|
|
assert(0)
|
||
|
|
except:
|
||
|
|
pass
|
||
|
|
def test_y_stride(self):
|
||
|
|
alpha,a,x,y = self.get_data(y_stride=2)
|
||
|
|
desired_a = alpha*transpose(x[:,newaxis]*y[::2]) + a
|
||
|
|
self.blas_func(x,y,a,incy=2)
|
||
|
|
assert_array_almost_equal(desired_a,a)
|
||
|
|
|
||
|
|
def test_y_stride_assert(self):
|
||
|
|
alpha,a,x,y = self.get_data(y_stride=2)
|
||
|
|
try:
|
||
|
|
self.blas_func(a,x,y,incy=3)
|
||
|
|
assert(0)
|
||
|
|
except:
|
||
|
|
pass
|
||
|
|
|
||
|
|
class TestSger(BaseGer):
|
||
|
|
blas_func = fblas.sger
|
||
|
|
dtype = float32
|
||
|
|
class TestDger(BaseGer):
|
||
|
|
blas_func = fblas.dger
|
||
|
|
dtype = float64
|
||
|
|
"""
|
||
|
|
##################################################
|
||
|
|
# Test blas ?gerc
|
||
|
|
# This will be a mess to test all cases.
|
||
|
|
|
||
|
|
"""
|
||
|
|
class BaseGerComplex(BaseGer):
|
||
|
|
def get_data(self,x_stride=1,y_stride=1):
|
||
|
|
from numpy.random import normal, seed
|
||
|
|
seed(1234)
|
||
|
|
alpha = array(1+1j, dtype = self.dtype)
|
||
|
|
a = normal(0.,1.,(3,3)).astype(self.dtype)
|
||
|
|
a = a + normal(0.,1.,(3,3)) * array(1j, dtype = self.dtype)
|
||
|
|
x = normal(0.,1.,shape(a)[0]*x_stride).astype(self.dtype)
|
||
|
|
x = x + x * array(1j, dtype = self.dtype)
|
||
|
|
y = normal(0.,1.,shape(a)[1]*y_stride).astype(self.dtype)
|
||
|
|
y = y + y * array(1j, dtype = self.dtype)
|
||
|
|
return alpha,a,x,y
|
||
|
|
def test_simple(self):
|
||
|
|
alpha,a,x,y = self.get_data()
|
||
|
|
# tranpose takes care of Fortran vs. C(and Python) memory layout
|
||
|
|
a = a * array(0.,dtype = self.dtype)
|
||
|
|
#desired_a = alpha*transpose(x[:,newaxis]*self.transform(y)) + a
|
||
|
|
desired_a = alpha*transpose(x[:,newaxis]*y) + a
|
||
|
|
#self.blas_func(x,y,a,alpha = alpha)
|
||
|
|
fblas.cgeru(x,y,a,alpha = alpha)
|
||
|
|
assert_array_almost_equal(desired_a,a)
|
||
|
|
|
||
|
|
#def test_x_stride(self):
|
||
|
|
# alpha,a,x,y = self.get_data(x_stride=2)
|
||
|
|
# desired_a = alpha*transpose(x[::2,newaxis]*self.transform(y)) + a
|
||
|
|
# self.blas_func(x,y,a,incx=2)
|
||
|
|
# assert_array_almost_equal(desired_a,a)
|
||
|
|
#def test_y_stride(self):
|
||
|
|
# alpha,a,x,y = self.get_data(y_stride=2)
|
||
|
|
# desired_a = alpha*transpose(x[:,newaxis]*self.transform(y[::2])) + a
|
||
|
|
# self.blas_func(x,y,a,incy=2)
|
||
|
|
# assert_array_almost_equal(desired_a,a)
|
||
|
|
|
||
|
|
class TestCgeru(BaseGerComplex):
|
||
|
|
blas_func = fblas.cgeru
|
||
|
|
dtype = complex64
|
||
|
|
def transform(self,x):
|
||
|
|
return x
|
||
|
|
class TestZgeru(BaseGerComplex):
|
||
|
|
blas_func = fblas.zgeru
|
||
|
|
dtype = complex128
|
||
|
|
def transform(self,x):
|
||
|
|
return x
|
||
|
|
|
||
|
|
class TestCgerc(BaseGerComplex):
|
||
|
|
blas_func = fblas.cgerc
|
||
|
|
dtype = complex64
|
||
|
|
def transform(self,x):
|
||
|
|
return conjugate(x)
|
||
|
|
|
||
|
|
class TestZgerc(BaseGerComplex):
|
||
|
|
blas_func = fblas.zgerc
|
||
|
|
dtype = complex128
|
||
|
|
def transform(self,x):
|
||
|
|
return conjugate(x)
|
||
|
|
"""
|