本文整理匯總了Python中numpy.core.multiarray.dot方法的典型用法代碼示例。如果您正苦於以下問題:Python multiarray.dot方法的具體用法?Python multiarray.dot怎麽用?Python multiarray.dot使用的例子?那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類numpy.core.multiarray
的用法示例。
在下文中一共展示了multiarray.dot方法的15個代碼示例,這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚,您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: restoredot
# 需要導入模塊: from numpy.core import multiarray [as 別名]
# 或者: from numpy.core.multiarray import dot [as 別名]
def restoredot():
"""
Restore `dot`, `vdot`, and `innerproduct` to the default non-BLAS
implementations.
Typically, the user will only need to call this when troubleshooting
and installation problem, reproducing the conditions of a build without
an accelerated BLAS, or when being very careful about benchmarking
linear algebra operations.
.. note:: Deprecated in Numpy 1.10
The cblas functions have been integrated into the multarray
module and restoredot now longer does anything. It will be
removed in Numpy 1.11.0.
See Also
--------
alterdot : `restoredot` undoes the effects of `alterdot`.
"""
# 2014-08-13, 1.10
warnings.warn("restoredot no longer does anything.", DeprecationWarning)
示例2: test_dot
# 需要導入模塊: from numpy.core import multiarray [as 別名]
# 或者: from numpy.core.multiarray import dot [as 別名]
def test_dot(self):
a = np.array([[1, 0], [0, 1]])
b = np.array([[0, 1], [1, 0]])
c = np.array([[9, 1], [1, -9]])
assert_equal(np.dot(a, b), a.dot(b))
assert_equal(np.dot(np.dot(a, b), c), a.dot(b).dot(c))
# test passing in an output array
c = np.zeros_like(a)
a.dot(b, c)
assert_equal(c, np.dot(a, b))
# test keyword args
c = np.zeros_like(a)
a.dot(b=b, out=c)
assert_equal(c, np.dot(a, b))
示例3: test_dot_3args
# 需要導入模塊: from numpy.core import multiarray [as 別名]
# 或者: from numpy.core.multiarray import dot [as 別名]
def test_dot_3args(self):
from numpy.core.multiarray import dot
np.random.seed(22)
f = np.random.random_sample((1024, 16))
v = np.random.random_sample((16, 32))
r = np.empty((1024, 32))
for i in range(12):
dot(f, v, r)
assert_equal(sys.getrefcount(r), 2)
r2 = dot(f, v, out=None)
assert_array_equal(r2, r)
assert_(r is dot(f, v, out=r))
v = v[:, 0].copy() # v.shape == (16,)
r = r[:, 0].copy() # r.shape == (1024,)
r2 = dot(f, v)
assert_(r is dot(f, v, r))
assert_array_equal(r2, r)
示例4: test_dot_override
# 需要導入模塊: from numpy.core import multiarray [as 別名]
# 或者: from numpy.core.multiarray import dot [as 別名]
def test_dot_override(self):
class A(object):
def __numpy_ufunc__(self, ufunc, method, pos, inputs, **kwargs):
return "A"
class B(object):
def __numpy_ufunc__(self, ufunc, method, pos, inputs, **kwargs):
return NotImplemented
a = A()
b = B()
c = np.array([[1]])
assert_equal(np.dot(a, b), "A")
assert_equal(c.dot(a), "A")
assert_raises(TypeError, np.dot, b, c)
assert_raises(TypeError, c.dot, b)
示例5: alterdot
# 需要導入模塊: from numpy.core import multiarray [as 別名]
# 或者: from numpy.core.multiarray import dot [as 別名]
def alterdot():
"""
Change `dot`, `vdot`, and `inner` to use accelerated BLAS functions.
Typically, as a user of Numpy, you do not explicitly call this
function. If Numpy is built with an accelerated BLAS, this function is
automatically called when Numpy is imported.
When Numpy is built with an accelerated BLAS like ATLAS, these
functions are replaced to make use of the faster implementations. The
faster implementations only affect float32, float64, complex64, and
complex128 arrays. Furthermore, the BLAS API only includes
matrix-matrix, matrix-vector, and vector-vector products. Products of
arrays with larger dimensionalities use the built in functions and are
not accelerated.
.. note:: Deprecated in Numpy 1.10
The cblas functions have been integrated into the multarray
module and alterdot now longer does anything. It will be
removed in Numpy 1.11.0.
See Also
--------
restoredot : `restoredot` undoes the effects of `alterdot`.
"""
# 2014-08-13, 1.10
warnings.warn("alterdot no longer does anything.", DeprecationWarning)
示例6: test_dot_2args
# 需要導入模塊: from numpy.core import multiarray [as 別名]
# 或者: from numpy.core.multiarray import dot [as 別名]
def test_dot_2args(self):
from numpy.core.multiarray import dot
a = np.array([[1, 2], [3, 4]], dtype=float)
b = np.array([[1, 0], [1, 1]], dtype=float)
c = np.array([[3, 2], [7, 4]], dtype=float)
d = dot(a, b)
assert_allclose(c, d)
示例7: test_dot_3args_errors
# 需要導入模塊: from numpy.core import multiarray [as 別名]
# 或者: from numpy.core.multiarray import dot [as 別名]
def test_dot_3args_errors(self):
from numpy.core.multiarray import dot
np.random.seed(22)
f = np.random.random_sample((1024, 16))
v = np.random.random_sample((16, 32))
r = np.empty((1024, 31))
assert_raises(ValueError, dot, f, v, r)
r = np.empty((1024,))
assert_raises(ValueError, dot, f, v, r)
r = np.empty((32,))
assert_raises(ValueError, dot, f, v, r)
r = np.empty((32, 1024))
assert_raises(ValueError, dot, f, v, r)
assert_raises(ValueError, dot, f, v, r.T)
r = np.empty((1024, 64))
assert_raises(ValueError, dot, f, v, r[:, ::2])
assert_raises(ValueError, dot, f, v, r[:, :32])
r = np.empty((1024, 32), dtype=np.float32)
assert_raises(ValueError, dot, f, v, r)
r = np.empty((1024, 32), dtype=int)
assert_raises(ValueError, dot, f, v, r)
示例8: test_matmat
# 需要導入模塊: from numpy.core import multiarray [as 別名]
# 或者: from numpy.core.multiarray import dot [as 別名]
def test_matmat(self):
A = self.A
c1 = dot(A.transpose(), A)
c2 = dot_(A.transpose(), A)
assert_almost_equal(c1, c2, decimal=self.N)
示例9: test_matvec2
# 需要導入模塊: from numpy.core import multiarray [as 別名]
# 或者: from numpy.core.multiarray import dot [as 別名]
def test_matvec2(self):
A, b2 = self.A, self.b2
c1 = dot(A, b2)
c2 = dot_(A, b2)
assert_almost_equal(c1, c2, decimal=self.N)
示例10: test_vecmat
# 需要導入模塊: from numpy.core import multiarray [as 別名]
# 或者: from numpy.core.multiarray import dot [as 別名]
def test_vecmat(self):
A, b4 = self.A, self.b4
c1 = dot(b4, A)
c2 = dot_(b4, A)
assert_almost_equal(c1, c2, decimal=self.N)
示例11: test_vecmat2
# 需要導入模塊: from numpy.core import multiarray [as 別名]
# 或者: from numpy.core.multiarray import dot [as 別名]
def test_vecmat2(self):
b3, A = self.b3, self.A
c1 = dot(b3, A.transpose())
c2 = dot_(b3, A.transpose())
assert_almost_equal(c1, c2, decimal=self.N)
示例12: test_vecmat3
# 需要導入模塊: from numpy.core import multiarray [as 別名]
# 或者: from numpy.core.multiarray import dot [as 別名]
def test_vecmat3(self):
A, b4 = self.A, self.b4
c1 = dot(A.transpose(), b4)
c2 = dot_(A.transpose(), b4)
assert_almost_equal(c1, c2, decimal=self.N)
示例13: test_vecvecouter
# 需要導入模塊: from numpy.core import multiarray [as 別名]
# 或者: from numpy.core.multiarray import dot [as 別名]
def test_vecvecouter(self):
b1, b3 = self.b1, self.b3
c1 = dot(b1, b3)
c2 = dot_(b1, b3)
assert_almost_equal(c1, c2, decimal=self.N)
示例14: test_columnvect1
# 需要導入模塊: from numpy.core import multiarray [as 別名]
# 或者: from numpy.core.multiarray import dot [as 別名]
def test_columnvect1(self):
b1 = ones((3, 1))
b2 = [5.3]
c1 = dot(b1, b2)
c2 = dot_(b1, b2)
assert_almost_equal(c1, c2, decimal=self.N)
示例15: test_columnvect2
# 需要導入模塊: from numpy.core import multiarray [as 別名]
# 或者: from numpy.core.multiarray import dot [as 別名]
def test_columnvect2(self):
b1 = ones((3, 1)).transpose()
b2 = [6.2]
c1 = dot(b2, b1)
c2 = dot_(b2, b1)
assert_almost_equal(c1, c2, decimal=self.N)