Python numpy.bitwise_not() Examples
The following are 30
code examples of numpy.bitwise_not().
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Example #1
| Source File: lax_numpy_test.py From trax with Apache License 2.0 | 6 votes |
|
def testBitwiseOp(self, onp_op, lnp_op, rng_factory, shapes, dtypes):
rng = rng_factory()
args_maker = self._GetArgsMaker(rng, shapes, dtypes)
has_python_scalar = jtu.PYTHON_SCALAR_SHAPE in shapes
self._CheckAgainstNumpy(onp_op, lnp_op, args_maker, check_dtypes=True)
if onp_op == onp.bitwise_not and has_python_scalar:
# For bitwise_not with a Python `int`, npe.jit may choose a different
# dtype for the `int` from onp's choice, which may result in a different
# result value, so we skip _CompileAndCheck.
return
# Numpy does value-dependent dtype promotion on Python/numpy/array scalars
# which `jit` can't do (when np.result_type is called inside `jit`, tensor
# values are not available), so we skip dtype check in this case.
check_dtypes = not(set(shapes) & set([jtu.NUMPY_SCALAR_SHAPE,
jtu.PYTHON_SCALAR_SHAPE, ()]))
self._CompileAndCheck(lnp_op, args_maker, check_dtypes=check_dtypes)
Example #2
| Source File: test_umath.py From pySINDy with MIT License | 6 votes |
|
def test_values(self):
for dt in self.bitwise_types:
zeros = np.array([0], dtype=dt)
ones = np.array([-1], dtype=dt)
msg = "dt = '%s'" % dt.char
assert_equal(np.bitwise_not(zeros), ones, err_msg=msg)
assert_equal(np.bitwise_not(ones), zeros, err_msg=msg)
assert_equal(np.bitwise_or(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_or(zeros, ones), ones, err_msg=msg)
assert_equal(np.bitwise_or(ones, zeros), ones, err_msg=msg)
assert_equal(np.bitwise_or(ones, ones), ones, err_msg=msg)
assert_equal(np.bitwise_xor(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_xor(zeros, ones), ones, err_msg=msg)
assert_equal(np.bitwise_xor(ones, zeros), ones, err_msg=msg)
assert_equal(np.bitwise_xor(ones, ones), zeros, err_msg=msg)
assert_equal(np.bitwise_and(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_and(zeros, ones), zeros, err_msg=msg)
assert_equal(np.bitwise_and(ones, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_and(ones, ones), ones, err_msg=msg)
Example #3
| Source File: minmax.py From histogrammar-python with Apache License 2.0 | 6 votes |
|
def _numpy(self, data, weights, shape):
q = self.quantity(data)
self._checkNPQuantity(q, shape)
self._checkNPWeights(weights, shape)
weights = self._makeNPWeights(weights, shape)
# no possibility of exception from here on out (for rollback)
import numpy
selection = numpy.isnan(q)
numpy.bitwise_not(selection, selection)
numpy.bitwise_and(selection, weights > 0.0, selection)
q = q[selection]
self.entries += float(weights.sum())
if math.isnan(self.min):
if q.shape[0] > 0:
self.min = float(q.min())
else:
if q.shape[0] > 0:
self.min = min(self.min, float(q.min()))
Example #4
| Source File: test_umath.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
def test_values(self):
for dt in self.bitwise_types:
zeros = np.array([0], dtype=dt)
ones = np.array([-1], dtype=dt)
msg = "dt = '%s'" % dt.char
assert_equal(np.bitwise_not(zeros), ones, err_msg=msg)
assert_equal(np.bitwise_not(ones), zeros, err_msg=msg)
assert_equal(np.bitwise_or(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_or(zeros, ones), ones, err_msg=msg)
assert_equal(np.bitwise_or(ones, zeros), ones, err_msg=msg)
assert_equal(np.bitwise_or(ones, ones), ones, err_msg=msg)
assert_equal(np.bitwise_xor(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_xor(zeros, ones), ones, err_msg=msg)
assert_equal(np.bitwise_xor(ones, zeros), ones, err_msg=msg)
assert_equal(np.bitwise_xor(ones, ones), zeros, err_msg=msg)
assert_equal(np.bitwise_and(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_and(zeros, ones), zeros, err_msg=msg)
assert_equal(np.bitwise_and(ones, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_and(ones, ones), ones, err_msg=msg)
Example #5
| Source File: test_umath.py From mxnet-lambda with Apache License 2.0 | 6 votes |
|
def test_values(self):
for dt in self.bitwise_types:
zeros = np.array([0], dtype=dt)
ones = np.array([-1], dtype=dt)
msg = "dt = '%s'" % dt.char
assert_equal(np.bitwise_not(zeros), ones, err_msg=msg)
assert_equal(np.bitwise_not(ones), zeros, err_msg=msg)
assert_equal(np.bitwise_or(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_or(zeros, ones), ones, err_msg=msg)
assert_equal(np.bitwise_or(ones, zeros), ones, err_msg=msg)
assert_equal(np.bitwise_or(ones, ones), ones, err_msg=msg)
assert_equal(np.bitwise_xor(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_xor(zeros, ones), ones, err_msg=msg)
assert_equal(np.bitwise_xor(ones, zeros), ones, err_msg=msg)
assert_equal(np.bitwise_xor(ones, ones), zeros, err_msg=msg)
assert_equal(np.bitwise_and(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_and(zeros, ones), zeros, err_msg=msg)
assert_equal(np.bitwise_and(ones, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_and(ones, ones), ones, err_msg=msg)
Example #6
| Source File: test_umath.py From GraphicDesignPatternByPython with MIT License | 6 votes |
|
def test_values(self):
for dt in self.bitwise_types:
zeros = np.array([0], dtype=dt)
ones = np.array([-1], dtype=dt)
msg = "dt = '%s'" % dt.char
assert_equal(np.bitwise_not(zeros), ones, err_msg=msg)
assert_equal(np.bitwise_not(ones), zeros, err_msg=msg)
assert_equal(np.bitwise_or(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_or(zeros, ones), ones, err_msg=msg)
assert_equal(np.bitwise_or(ones, zeros), ones, err_msg=msg)
assert_equal(np.bitwise_or(ones, ones), ones, err_msg=msg)
assert_equal(np.bitwise_xor(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_xor(zeros, ones), ones, err_msg=msg)
assert_equal(np.bitwise_xor(ones, zeros), ones, err_msg=msg)
assert_equal(np.bitwise_xor(ones, ones), zeros, err_msg=msg)
assert_equal(np.bitwise_and(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_and(zeros, ones), zeros, err_msg=msg)
assert_equal(np.bitwise_and(ones, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_and(ones, ones), ones, err_msg=msg)
Example #7
| Source File: test_umath.py From elasticintel with GNU General Public License v3.0 | 6 votes |
|
def test_values(self):
for dt in self.bitwise_types:
zeros = np.array([0], dtype=dt)
ones = np.array([-1], dtype=dt)
msg = "dt = '%s'" % dt.char
assert_equal(np.bitwise_not(zeros), ones, err_msg=msg)
assert_equal(np.bitwise_not(ones), zeros, err_msg=msg)
assert_equal(np.bitwise_or(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_or(zeros, ones), ones, err_msg=msg)
assert_equal(np.bitwise_or(ones, zeros), ones, err_msg=msg)
assert_equal(np.bitwise_or(ones, ones), ones, err_msg=msg)
assert_equal(np.bitwise_xor(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_xor(zeros, ones), ones, err_msg=msg)
assert_equal(np.bitwise_xor(ones, zeros), ones, err_msg=msg)
assert_equal(np.bitwise_xor(ones, ones), zeros, err_msg=msg)
assert_equal(np.bitwise_and(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_and(zeros, ones), zeros, err_msg=msg)
assert_equal(np.bitwise_and(ones, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_and(ones, ones), ones, err_msg=msg)
Example #8
| Source File: sum.py From histogrammar-python with Apache License 2.0 | 6 votes |
|
def _numpy(self, data, weights, shape):
q = self.quantity(data)
self._checkNPQuantity(q, shape)
self._checkNPWeights(weights, shape)
weights = self._makeNPWeights(weights, shape)
# no possibility of exception from here on out (for rollback)
self.entries += float(weights.sum())
import numpy
selection = numpy.isnan(q)
numpy.bitwise_not(selection, selection)
numpy.bitwise_and(selection, weights > 0.0, selection)
q = q[selection]
weights = weights[selection]
q *= weights
self.sum += float(q.sum())
Example #9
| Source File: test_umath.py From coffeegrindsize with MIT License | 6 votes |
|
def test_values(self):
for dt in self.bitwise_types:
zeros = np.array([0], dtype=dt)
ones = np.array([-1], dtype=dt)
msg = "dt = '%s'" % dt.char
assert_equal(np.bitwise_not(zeros), ones, err_msg=msg)
assert_equal(np.bitwise_not(ones), zeros, err_msg=msg)
assert_equal(np.bitwise_or(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_or(zeros, ones), ones, err_msg=msg)
assert_equal(np.bitwise_or(ones, zeros), ones, err_msg=msg)
assert_equal(np.bitwise_or(ones, ones), ones, err_msg=msg)
assert_equal(np.bitwise_xor(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_xor(zeros, ones), ones, err_msg=msg)
assert_equal(np.bitwise_xor(ones, zeros), ones, err_msg=msg)
assert_equal(np.bitwise_xor(ones, ones), zeros, err_msg=msg)
assert_equal(np.bitwise_and(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_and(zeros, ones), zeros, err_msg=msg)
assert_equal(np.bitwise_and(ones, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_and(ones, ones), ones, err_msg=msg)
Example #10
| Source File: ArmaJump.py From Conditional_Density_Estimation with MIT License | 6 votes |
|
def simulate_conditional(self, X):
""" Draws random samples from the conditional distribution
Args:
X: x to be conditioned on when drawing a sample from y ~ p(y|x) - numpy array of shape (n_samples, ndim_x)
Returns:
Conditional random samples y drawn from p(y|x) - numpy array of shape (n_samples, ndim_y)
"""
mean = self.arma_c * (1 - self.arma_a1) + self.arma_a1 * X
y_ar = self.random_state.normal(loc=mean, scale=self.std, size=X.shape[0])
mean_jump = mean + self.jump_mean
y_jump = self.random_state.normal(loc=mean_jump, scale=self.jump_std, size=X.shape[0])
jump_bernoulli = self.random_state.uniform(size=X.shape[0]) < self.jump_prob
return X, np.select([jump_bernoulli, np.bitwise_not(jump_bernoulli)], [y_jump, y_ar])
Example #11
| Source File: test_umath.py From Mastering-Elasticsearch-7.0 with MIT License | 6 votes |
|
def test_values(self):
for dt in self.bitwise_types:
zeros = np.array([0], dtype=dt)
ones = np.array([-1], dtype=dt)
msg = "dt = '%s'" % dt.char
assert_equal(np.bitwise_not(zeros), ones, err_msg=msg)
assert_equal(np.bitwise_not(ones), zeros, err_msg=msg)
assert_equal(np.bitwise_or(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_or(zeros, ones), ones, err_msg=msg)
assert_equal(np.bitwise_or(ones, zeros), ones, err_msg=msg)
assert_equal(np.bitwise_or(ones, ones), ones, err_msg=msg)
assert_equal(np.bitwise_xor(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_xor(zeros, ones), ones, err_msg=msg)
assert_equal(np.bitwise_xor(ones, zeros), ones, err_msg=msg)
assert_equal(np.bitwise_xor(ones, ones), zeros, err_msg=msg)
assert_equal(np.bitwise_and(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_and(zeros, ones), zeros, err_msg=msg)
assert_equal(np.bitwise_and(ones, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_and(ones, ones), ones, err_msg=msg)
Example #12
| Source File: test_umath.py From vnpy_crypto with MIT License | 6 votes |
|
def test_values(self):
for dt in self.bitwise_types:
zeros = np.array([0], dtype=dt)
ones = np.array([-1], dtype=dt)
msg = "dt = '%s'" % dt.char
assert_equal(np.bitwise_not(zeros), ones, err_msg=msg)
assert_equal(np.bitwise_not(ones), zeros, err_msg=msg)
assert_equal(np.bitwise_or(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_or(zeros, ones), ones, err_msg=msg)
assert_equal(np.bitwise_or(ones, zeros), ones, err_msg=msg)
assert_equal(np.bitwise_or(ones, ones), ones, err_msg=msg)
assert_equal(np.bitwise_xor(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_xor(zeros, ones), ones, err_msg=msg)
assert_equal(np.bitwise_xor(ones, zeros), ones, err_msg=msg)
assert_equal(np.bitwise_xor(ones, ones), zeros, err_msg=msg)
assert_equal(np.bitwise_and(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_and(zeros, ones), zeros, err_msg=msg)
assert_equal(np.bitwise_and(ones, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_and(ones, ones), ones, err_msg=msg)
Example #13
| Source File: test_umath.py From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License | 6 votes |
|
def test_values(self):
for dt in self.bitwise_types:
zeros = np.array([0], dtype=dt)
ones = np.array([-1], dtype=dt)
msg = "dt = '%s'" % dt.char
assert_equal(np.bitwise_not(zeros), ones, err_msg=msg)
assert_equal(np.bitwise_not(ones), zeros, err_msg=msg)
assert_equal(np.bitwise_or(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_or(zeros, ones), ones, err_msg=msg)
assert_equal(np.bitwise_or(ones, zeros), ones, err_msg=msg)
assert_equal(np.bitwise_or(ones, ones), ones, err_msg=msg)
assert_equal(np.bitwise_xor(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_xor(zeros, ones), ones, err_msg=msg)
assert_equal(np.bitwise_xor(ones, zeros), ones, err_msg=msg)
assert_equal(np.bitwise_xor(ones, ones), zeros, err_msg=msg)
assert_equal(np.bitwise_and(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_and(zeros, ones), zeros, err_msg=msg)
assert_equal(np.bitwise_and(ones, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_and(ones, ones), ones, err_msg=msg)
Example #14
| Source File: test_umath.py From recruit with Apache License 2.0 | 6 votes |
|
def test_values(self):
for dt in self.bitwise_types:
zeros = np.array([0], dtype=dt)
ones = np.array([-1], dtype=dt)
msg = "dt = '%s'" % dt.char
assert_equal(np.bitwise_not(zeros), ones, err_msg=msg)
assert_equal(np.bitwise_not(ones), zeros, err_msg=msg)
assert_equal(np.bitwise_or(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_or(zeros, ones), ones, err_msg=msg)
assert_equal(np.bitwise_or(ones, zeros), ones, err_msg=msg)
assert_equal(np.bitwise_or(ones, ones), ones, err_msg=msg)
assert_equal(np.bitwise_xor(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_xor(zeros, ones), ones, err_msg=msg)
assert_equal(np.bitwise_xor(ones, zeros), ones, err_msg=msg)
assert_equal(np.bitwise_xor(ones, ones), zeros, err_msg=msg)
assert_equal(np.bitwise_and(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_and(zeros, ones), zeros, err_msg=msg)
assert_equal(np.bitwise_and(ones, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_and(ones, ones), ones, err_msg=msg)
Example #15
| Source File: test_umath.py From twitter-stock-recommendation with MIT License | 6 votes |
|
def test_values(self):
for dt in self.bitwise_types:
zeros = np.array([0], dtype=dt)
ones = np.array([-1], dtype=dt)
msg = "dt = '%s'" % dt.char
assert_equal(np.bitwise_not(zeros), ones, err_msg=msg)
assert_equal(np.bitwise_not(ones), zeros, err_msg=msg)
assert_equal(np.bitwise_or(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_or(zeros, ones), ones, err_msg=msg)
assert_equal(np.bitwise_or(ones, zeros), ones, err_msg=msg)
assert_equal(np.bitwise_or(ones, ones), ones, err_msg=msg)
assert_equal(np.bitwise_xor(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_xor(zeros, ones), ones, err_msg=msg)
assert_equal(np.bitwise_xor(ones, zeros), ones, err_msg=msg)
assert_equal(np.bitwise_xor(ones, ones), zeros, err_msg=msg)
assert_equal(np.bitwise_and(zeros, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_and(zeros, ones), zeros, err_msg=msg)
assert_equal(np.bitwise_and(ones, zeros), zeros, err_msg=msg)
assert_equal(np.bitwise_and(ones, ones), ones, err_msg=msg)
Example #16
| Source File: test_simple.py From starfish with MIT License | 5 votes |
|
def test_success():
mask_collection_0 = binary_mask_collection_2d()
binary_arrays, physical_ticks = binary_arrays_2d()
binary_arrays_negated = [
np.bitwise_not(binary_array)
for binary_array in binary_arrays
]
mask_collection_1 = BinaryMaskCollection.from_binary_arrays_and_ticks(
binary_arrays_negated, None, physical_ticks, None)
merged = SimpleMerge().run([mask_collection_0, mask_collection_1])
assert _ticks_equal(merged._pixel_ticks, mask_collection_0._pixel_ticks)
assert _ticks_equal(merged._physical_ticks, mask_collection_0._physical_ticks)
assert len(mask_collection_0) + len(mask_collection_1) == len(merged)
# go through all the original uncroppped masks, and verify that they are somewhere in the merged
# set.
for mask_collection in (mask_collection_0, mask_collection_1):
for ix in range(len(mask_collection)):
uncropped_original_mask = mask_collection.uncropped_mask(ix)
for jx in range(len(merged)):
uncropped_copy_mask = merged.uncropped_mask(jx)
if uncropped_original_mask.equals(uncropped_copy_mask):
# found the copy, break
break
else:
pytest.fail("could not find mask in merged set.")
Example #17
| Source File: test_simple.py From starfish with MIT License | 5 votes |
|
def test_physical_tick_mismatch():
mask_collection_0 = binary_mask_collection_2d()
mask_collection_0._physical_ticks[Coordinates.X] = np.asarray(
mask_collection_0._physical_ticks[Coordinates.X]) + 1
binary_arrays, physical_ticks = binary_arrays_2d()
binary_arrays_negated = [
np.bitwise_not(binary_array)
for binary_array in binary_arrays
]
mask_collection_1 = BinaryMaskCollection.from_binary_arrays_and_ticks(
binary_arrays_negated, None, physical_ticks, None)
with pytest.raises(ValueError):
SimpleMerge().run([mask_collection_0, mask_collection_1])
Example #18
| Source File: test_simple.py From starfish with MIT License | 5 votes |
|
def test_pixel_tick_mismatch():
mask_collection_0 = binary_mask_collection_2d()
mask_collection_0._pixel_ticks[Axes.X.value] = np.asarray(
mask_collection_0._pixel_ticks[Axes.X.value]) + 1
binary_arrays, physical_ticks = binary_arrays_2d()
binary_arrays_negated = [
np.bitwise_not(binary_array)
for binary_array in binary_arrays
]
mask_collection_1 = BinaryMaskCollection.from_binary_arrays_and_ticks(
binary_arrays_negated, None, physical_ticks, None)
with pytest.raises(ValueError):
SimpleMerge().run([mask_collection_0, mask_collection_1])
Example #19
| Source File: stack.py From histogrammar-python with Apache License 2.0 | 5 votes |
|
def _numpy(self, data, weights, shape):
q = self.quantity(data)
self._checkNPQuantity(q, shape)
self._checkNPWeights(weights, shape)
weights = self._makeNPWeights(weights, shape)
newentries = weights.sum()
import numpy
selection = numpy.isnan(q)
numpy.bitwise_not(selection, selection)
subweights = weights.copy()
subweights[selection] = 0.0
self.nanflow._numpy(data, subweights, shape)
# avoid nan warning in calculations by flinging the nans elsewhere
numpy.bitwise_not(selection, selection)
q = numpy.array(q, dtype=numpy.float64)
q[selection] = float("-inf")
weights = weights.copy()
weights[selection] = 0.0
selection = numpy.empty(q.shape, dtype=numpy.bool)
for threshold, sub in self.bins:
numpy.less(q, threshold, selection)
subweights[:] = weights
subweights[selection] = 0.0
sub._numpy(data, subweights, shape)
# no possibility of exception from here on out (for rollback)
self.entries += float(newentries)
Example #20
| Source File: transform.py From RLTrader with GNU General Public License v3.0 | 5 votes |
|
def transform(iterable: Iterable, inplace: bool = True, columns: List[str] = None, transform_fn: Callable[[Iterable], Iterable] = None):
if inplace is True:
transformed_iterable = iterable
else:
transformed_iterable = iterable.copy()
if isinstance(transformed_iterable, pd.DataFrame):
is_list = False
else:
is_list = True
transformed_iterable = pd.DataFrame(transformed_iterable, columns=columns)
transformed_iterable.fillna(0, inplace=True)
if transform_fn is None:
raise NotImplementedError()
if columns is None:
columns = transformed_iterable.columns
for column in columns:
transformed_iterable[column] = transform_fn(transformed_iterable[column])
transformed_iterable.fillna(method="bfill", inplace=True)
transformed_iterable[np.bitwise_not(np.isfinite(transformed_iterable))] = 0
if is_list:
transformed_iterable = transformed_iterable.values
return transformed_iterable
Example #21
| Source File: irregularlybin.py From histogrammar-python with Apache License 2.0 | 5 votes |
|
def _numpy(self, data, weights, shape):
q = self.quantity(data)
self._checkNPQuantity(q, shape)
self._checkNPWeights(weights, shape)
weights = self._makeNPWeights(weights, shape)
newentries = weights.sum()
import numpy
selection = numpy.isnan(q)
numpy.bitwise_not(selection, selection)
subweights = weights.copy()
subweights[selection] = 0.0
self.nanflow._numpy(data, subweights, shape)
# avoid nan warning in calculations by flinging the nans elsewhere
numpy.bitwise_not(selection, selection)
q = numpy.array(q, dtype=numpy.float64)
q[selection] = float("-inf")
weights = weights.copy()
weights[selection] = 0.0
# FIXME: the case of all Counts could be optimized with numpy.histogram (see CentrallyBin for an example)
selection = numpy.empty(q.shape, dtype=numpy.bool)
selection2 = numpy.empty(q.shape, dtype=numpy.bool)
subweights = weights.copy()
for (low, sub), (high, _) in zip(self.bins, self.bins[1:] + ((float("nan"), None),)):
numpy.greater_equal(q, low, selection)
numpy.greater_equal(q, high, selection2)
numpy.bitwise_not(selection2, selection2)
numpy.bitwise_and(selection, selection2, selection)
numpy.bitwise_not(selection, selection)
subweights[:] = weights
subweights[selection] = 0.0
sub._numpy(data, subweights, shape)
# no possibility of exception from here on out (for rollback)
self.entries += float(newentries)
Example #22
| Source File: _numpy_bitstrings.py From xcs with BSD 3-Clause "New" or "Revised" License | 5 votes |
|
def __invert__(self):
"""Overloads unary ~"""
bits = numpy.bitwise_not(self._bits)
# Make sure the bit array isn't writable so it can be used by the
# constructor
bits.flags.writeable = False
return type(self)(bits)
Example #23
| Source File: test_umath.py From elasticintel with GNU General Public License v3.0 | 5 votes |
|
def test_types(self):
for dt in self.bitwise_types:
zeros = np.array([0], dtype=dt)
ones = np.array([-1], dtype=dt)
msg = "dt = '%s'" % dt.char
assert_(np.bitwise_not(zeros).dtype == dt, msg)
assert_(np.bitwise_or(zeros, zeros).dtype == dt, msg)
assert_(np.bitwise_xor(zeros, zeros).dtype == dt, msg)
assert_(np.bitwise_and(zeros, zeros).dtype == dt, msg)
Example #24
| Source File: test_umath.py From coffeegrindsize with MIT License | 5 votes |
|
def test_types(self):
for dt in self.bitwise_types:
zeros = np.array([0], dtype=dt)
ones = np.array([-1], dtype=dt)
msg = "dt = '%s'" % dt.char
assert_(np.bitwise_not(zeros).dtype == dt, msg)
assert_(np.bitwise_or(zeros, zeros).dtype == dt, msg)
assert_(np.bitwise_xor(zeros, zeros).dtype == dt, msg)
assert_(np.bitwise_and(zeros, zeros).dtype == dt, msg)
Example #25
| Source File: test_topi_broadcast.py From incubator-tvm with Apache License 2.0 | 5 votes |
|
def test_bitwise_not():
def test_apply(
func,
name,
f_numpy,
shape,
dtype="int32",
):
# Build the logic and compile the function
A = te.placeholder(shape=shape, name="A", dtype=dtype)
B = func(A)
if isinstance(A, tvm.tir.PrimExpr):
assert (isinstance(B, tvm.tir.PrimExpr))
return
def check_device(device):
ctx = tvm.context(device, 0)
if not ctx.exist:
print("Skip because %s is not enabled" % device)
return
print("Running on target: %s" % device)
with tvm.target.create(device):
s = topi.testing.get_broadcast_schedule(device)(B)
foo = tvm.build(s, [A, B], device, name=name)
data_npy = np.random.uniform(size=shape).astype(A.dtype)
data_nd = tvm.nd.array(data_npy, ctx)
out_npy = f_numpy(data_npy)
out_nd = tvm.nd.array(np.empty(data_npy.shape).astype(B.dtype), ctx)
foo(data_nd, out_nd)
tvm.testing.assert_allclose(out_nd.asnumpy(), out_npy)
for device in get_all_backend():
check_device(device)
test_apply(topi.bitwise_not, "bitwise_not", np.bitwise_not, ())
test_apply(topi.bitwise_not, "bitwise_not", np.bitwise_not, (2, 1, 2))
Example #26
| Source File: test_umath.py From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License | 5 votes |
|
def test_types(self):
for dt in self.bitwise_types:
zeros = np.array([0], dtype=dt)
ones = np.array([-1], dtype=dt)
msg = "dt = '%s'" % dt.char
assert_(np.bitwise_not(zeros).dtype == dt, msg)
assert_(np.bitwise_or(zeros, zeros).dtype == dt, msg)
assert_(np.bitwise_xor(zeros, zeros).dtype == dt, msg)
assert_(np.bitwise_and(zeros, zeros).dtype == dt, msg)
Example #27
| Source File: test_umath.py From twitter-stock-recommendation with MIT License | 5 votes |
|
def test_types(self):
for dt in self.bitwise_types:
zeros = np.array([0], dtype=dt)
ones = np.array([-1], dtype=dt)
msg = "dt = '%s'" % dt.char
assert_(np.bitwise_not(zeros).dtype == dt, msg)
assert_(np.bitwise_or(zeros, zeros).dtype == dt, msg)
assert_(np.bitwise_xor(zeros, zeros).dtype == dt, msg)
assert_(np.bitwise_and(zeros, zeros).dtype == dt, msg)
Example #28
| Source File: MIMAS.py From Aegean with Academic Free License v3.0 | 5 votes |
|
def mask_table(region, table, negate=False, racol='ra', deccol='dec'):
"""
Apply a given mask (region) to the table, removing all the rows with ra/dec inside the region
If negate=False then remove the rows with ra/dec outside the region.
Parameters
----------
region : :class:`AegeanTools.regions.Region`
Region to mask.
table : Astropy.table.Table
Table to be masked.
negate : bool
If True then pixels *outside* the region are masked.
Default = False.
racol, deccol : str
The name of the columns in `table` that should be interpreted as ra and dec.
Default = 'ra', 'dec'
Returns
-------
masked : Astropy.table.Table
A view of the given table which has been masked.
"""
inside = region.sky_within(table[racol], table[deccol], degin=True)
if not negate:
mask = np.bitwise_not(inside)
else:
mask = inside
return table[mask]
Example #29
| Source File: TradingEnv.py From RLTrader with GNU General Public License v3.0 | 5 votes |
|
def _next_observation(self):
self.current_ohlcv = self.data_provider.next_ohlcv()
self.timestamps.append(pd.to_datetime(self.current_ohlcv.Date.item(), unit='s'))
self.observations = self.observations.append(self.current_ohlcv, ignore_index=True)
if self.stationarize_obs:
observations = log_and_difference(self.observations, inplace=False)
else:
observations = self.observations
if self.normalize_obs:
observations = max_min_normalize(observations)
obs = observations.values[-1]
if self.stationarize_obs:
scaled_history = log_and_difference(self.account_history, inplace=False)
else:
scaled_history = self.account_history
if self.normalize_obs:
scaled_history = max_min_normalize(scaled_history, inplace=False)
obs = np.insert(obs, len(obs), scaled_history.values[-1], axis=0)
obs = np.reshape(obs.astype('float16'), self.obs_shape)
obs[np.bitwise_not(np.isfinite(obs))] = 0
return obs
Example #30
| Source File: test_umath.py From recruit with Apache License 2.0 | 5 votes |
|
def test_types(self):
for dt in self.bitwise_types:
zeros = np.array([0], dtype=dt)
ones = np.array([-1], dtype=dt)
msg = "dt = '%s'" % dt.char
assert_(np.bitwise_not(zeros).dtype == dt, msg)
assert_(np.bitwise_or(zeros, zeros).dtype == dt, msg)
assert_(np.bitwise_xor(zeros, zeros).dtype == dt, msg)
assert_(np.bitwise_and(zeros, zeros).dtype == dt, msg)
