参考链接： Python中的numpy.greater_equal
本文整理汇总了Python中numpy.fmod方法的典型用法代码示例。如果您正苦于以下问题：Python numpy.fmod方法的具体用法？Python numpy.fmod怎么用？Python numpy.fmod使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在模块numpy的用法示例。
在下文中一共展示了numpy.fmod方法的15个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于我们的系统推荐出更棒的Python代码示例。
示例1: test_NotImplemented_not_returned
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# 需要导入模块: import numpy [as 别名]
# 或者: from numpy import fmod [as 别名]
def test_NotImplemented_not_returned(self):
# See gh-5964 and gh-2091. Some of these functions are not operator
# related and were fixed for other reasons in the past.
binary_funcs = [
np.power, np.add, np.subtract, np.multiply, np.divide,
np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or,
np.bitwise_xor, np.left_shift, np.right_shift, np.fmax,
np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2,
np.logical_and, np.logical_or, np.logical_xor, np.maximum,
np.minimum, np.mod,
np.greater, np.greater_equal, np.less, np.less_equal,
np.equal, np.not_equal]
a = np.array('1')
b = 1
c = np.array([1., 2.])
for f in binary_funcs:
assert_raises(TypeError, f, a, b)
assert_raises(TypeError, f, c, a)
开发者ID:Frank-qlu，项目名称:recruit，代码行数:21，
示例2: test_NotImplemented_not_returned
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# 需要导入模块: import numpy [as 别名]
# 或者: from numpy import fmod [as 别名]
def test_NotImplemented_not_returned(self):
# See gh-5964 and gh-2091. Some of these functions are not operator
# related and were fixed for other reasons in the past.
binary_funcs = [
np.power, np.add, np.subtract, np.multiply, np.divide,
np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or,
np.bitwise_xor, np.left_shift, np.right_shift, np.fmax,
np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2,
np.logical_and, np.logical_or, np.logical_xor, np.maximum,
np.minimum, np.mod
]
# These functions still return NotImplemented. Will be fixed in
# future.
# bad = [np.greater, np.greater_equal, np.less, np.less_equal, np.not_equal]
a = np.array('1')
b = 1
for f in binary_funcs:
assert_raises(TypeError, f, a, b)
开发者ID:abhisuri97，项目名称:auto-alt-text-lambda-api，代码行数:22，
示例3: test_vectorized_intrin2
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# 需要导入模块: import numpy [as 别名]
# 或者: from numpy import fmod [as 别名]
def test_vectorized_intrin2(dtype="float32"):
c2 = tvm.tir.const(2, dtype=dtype)
test_funcs = [
(tvm.tir.power, lambda x : np.power(x, 2.0)),
(tvm.tir.fmod, lambda x : np.fmod(x, 2.0))
]
def run_test(tvm_intrin, np_func):
if not tvm.gpu(0).exist or not tvm.runtime.enabled("cuda"):
print("skip because cuda is not enabled..")
return
n = 128
A = te.placeholder((n,), dtype=dtype, name='A')
B = te.compute((n,), lambda i: tvm_intrin(A[i], c2), name='B')
s = sched(B)
f = tvm.build(s, [A, B], "cuda")
ctx = tvm.gpu(0)
a = tvm.nd.array(np.random.uniform(0, 1, size=n).astype(A.dtype), ctx)
b = tvm.nd.array(np.zeros(shape=(n,)).astype(A.dtype), ctx)
f(a, b)
tvm.testing.assert_allclose(b.asnumpy(), np_func(a.asnumpy()), atol=1e-3, rtol=1e-3)
for func in test_funcs:
run_test(*func)
开发者ID:apache，项目名称:incubator-tvm，代码行数:26，
示例4: test_mod
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# 需要导入模块: import numpy [as 别名]
# 或者: from numpy import fmod [as 别名]
def test_mod(self):
if legacy_opset_pre_ver(10):
raise unittest.SkipTest("ONNX version {} doesn't support Mod.".format(
defs.onnx_opset_version()))
x = self._get_rnd_float32(shape=[5, 5])
y = self._get_rnd_float32(shape=[5, 5])
node_def = helper.make_node("Mod", ["X", "Y"], ["Z"], fmod=0)
output = run_node(node_def, [x, y])
np.testing.assert_almost_equal(output["Z"], np.mod(x, y))
node_def = helper.make_node("Mod", ["X", "Y"], ["Z"], fmod=1)
output = run_node(node_def, [x, y])
np.testing.assert_almost_equal(output["Z"], np.fmod(x, y))
开发者ID:onnx，项目名称:onnx-tensorflow，代码行数:14，
示例5: __setattr__
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# 需要导入模块: import numpy [as 别名]
# 或者: from numpy import fmod [as 别名]
def __setattr__(self, key, value):
"""Set attributes with conversion to ndarray where needed."""
is_set = hasattr(self, key) # == False in constructor
# parameter canonicalization and some validation via reshaping
if value is None:
# TODO: maybe forbid for some fields
pass
elif key == 'translation':
value = np.array(value, dtype=np.float32).reshape(3, 1)
elif key == 'rotation':
value = np.array(value, dtype=np.float32).reshape(4)
value[0] = np.fmod(value[0], 2.0 * np.pi)
if value[0] < 0.0:
value[0] = 2.0 * np.pi
value[0] = np.cos(value[0] / 2)
norm = np.linalg.norm(value[1:4])
needed_norm = np.sqrt(1 - value[0] * value[0])
if abs(norm - needed_norm) > _epsilon:
if norm < _epsilon:
raise ValueError('Norm of (x, y, z) part of quaternion too close to zero')
value[1:4] = value[1:4] / norm * needed_norm
# assert abs(np.linalg.norm(value) - 1.0) < _epsilon
elif key == 'scaling':
value = np.array(value, dtype=np.float32).reshape(3)
elif key in ['parent_matrix', 'custom_matrix', 'model_matrix']:
value = np.array(value, dtype=np.float32).reshape((4, 4))
super(Transform, self).__setattr__(key, value)
if is_set and key != 'model_matrix':
self._recompute_matrix()
self._notify_dependants()
开发者ID:K3D-tools，项目名称:K3D-jupyter，代码行数:38，
示例6: __init__
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# 需要导入模块: import numpy [as 别名]
# 或者: from numpy import fmod [as 别名]
def __init__(self, input_grid, pitch, apodization, orientation=0, even_grid=False):
'''An even asphere micro-lens array.
Parameters
----------
input_grid : Grid
The grid on which the periodic optical element is evaluated.
pitch : scalar
The pitch of the periodic optical element.
apodization : Apodizer
The apodizer that will be evaluated on the periodic grid.
orientation : scalar
The orientation of the periodic optical element.
even_grid : bool
This determines whether zero is in between two elements or if it is the center of an element.
'''
self.input_grid = input_grid.copy()
self.input_grid = self.input_grid.rotated(orientation)
if even_grid:
xf = (np.fmod(abs(self.input_grid.x), pitch) - pitch / 2) * np.sign(self.input_grid.x)
yf = (np.fmod(abs(self.input_grid.y), pitch) - pitch / 2) * np.sign(self.input_grid.y)
else:
xf = (np.fmod(abs(self.input_grid.x) pitch / 2, pitch) - pitch / 2) * np.sign(self.input_grid.x)
yf = (np.fmod(abs(self.input_grid.y) pitch / 2, pitch) - pitch / 2) * np.sign(self.input_grid.y)
periodic_grid = CartesianGrid(UnstructuredCoords((xf, yf)))
self.apodization = apodization(periodic_grid)
开发者ID:ehpor，项目名称:hcipy，代码行数:30，
示例7: forward
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# 需要导入模块: import numpy [as 别名]
# 或者: from numpy import fmod [as 别名]
def forward(self, inputs, device):
x, divisor = inputs
y = functions.fmod(x, divisor)
return y,
开发者ID:chainer，项目名称:chainer，代码行数:6，
示例8: forward_expected
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# 需要导入模块: import numpy [as 别名]
# 或者: from numpy import fmod [as 别名]
def forward_expected(self, inputs):
x, divisor = inputs
expected = numpy.fmod(x, divisor)
expected = numpy.asarray(expected)
return expected,
开发者ID:chainer，项目名称:chainer，代码行数:7，
示例9: testFloat
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# 需要导入模块: import numpy [as 别名]
# 或者: from numpy import fmod [as 别名]
def testFloat(self):
x = [0.5, 0.7, 0.3]
for dtype in [np.float32, np.double]:
# Test scalar and vector versions.
for denom in [x[0], [x[0]] * 3]:
x_np = np.array(x, dtype=dtype)
with self.test_session(use_gpu=True):
x_tf = constant_op.constant(x_np, shape=x_np.shape)
y_tf = math_ops.mod(x_tf, denom)
y_tf_np = y_tf.eval()
y_np = np.fmod(x_np, denom)
self.assertAllClose(y_tf_np, y_np, atol=1e-2)
开发者ID:tobegit3hub，项目名称:deep_image_model，代码行数:14，
示例10: testTruncateModInt
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# 需要导入模块: import numpy [as 别名]
# 或者: from numpy import fmod [as 别名]
def testTruncateModInt(self):
nums, divs = self.intTestData()
with self.test_session():
tf_result = math_ops.truncatemod(nums, divs).eval()
np_result = np.fmod(nums, divs)
self.assertAllEqual(tf_result, np_result)
开发者ID:tobegit3hub，项目名称:deep_image_model，代码行数:8，
示例11: testTruncateModFloat
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# 需要导入模块: import numpy [as 别名]
# 或者: from numpy import fmod [as 别名]
def testTruncateModFloat(self):
nums, divs = self.floatTestData()
with self.test_session():
tf_result = math_ops.truncatemod(nums, divs).eval()
np_result = np.fmod(nums, divs)
self.assertAllEqual(tf_result, np_result)
开发者ID:tobegit3hub，项目名称:deep_image_model，代码行数:8，
示例12: wrap_180
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# 需要导入模块: import numpy [as 别名]
# 或者: from numpy import fmod [as 别名]
def wrap_180(self, angle):
if (angle > 3*np.pi or angle < -3*np.pi):
angle = np.fmod(angle,2*np.pi)
if (angle > np.pi):
angle = angle - 2*np.pi
if (angle < - np.pi):
angle = angle 2*np.pi
return angle;
开发者ID:purdue-biorobotics，项目名称:flappy，代码行数:10，
示例13: _periodic_boundary
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# 需要导入模块: import numpy [as 别名]
# 或者: from numpy import fmod [as 别名]
def _periodic_boundary(self,x,bound):
return np.fmod(x,bound)-np.trunc(x/bound)*bound
开发者ID:qkitgroup，项目名称:qkit，代码行数:4，
示例14: myProj
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# 需要导入模块: import numpy [as 别名]
# 或者: from numpy import fmod [as 别名]
def myProj(x):
angle = torch.norm(x, 2, 1, True)
axis = F.normalize(x)
angle = torch.fmod(angle, 2*np.pi)
return angle*axis
# my model for pose estimation: feature model 1layer pose model x 12
开发者ID:JHUVisionLab，项目名称:multi-modal-regression，代码行数:10，
示例15: test_fmod
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# 需要导入模块: import numpy [as 别名]
# 或者: from numpy import fmod [as 别名]
def test_fmod(self):
A, A_rdd = self.make_dense_rdd((8, 3))
B, B_rdd = self.make_dense_rdd((1, 3))
np_res = np.fmod(A, B)
assert_array_equal(
A_rdd.fmod(B).toarray(), np_res
)
开发者ID:lensacom，项目名称:sparkit-learn，代码行数:9，
注：本文中的numpy.fmod方法示例整理自Github/MSDocs等源码及文档管理平台，相关代码片段筛选自各路编程大神贡献的开源项目，源码版权归原作者所有，传播和使用请参考对应项目的License；未经允许，请勿转载。
