Here are the examples of the python api numpy.array_equal taken from open source projects. By voting up you can indicate which examples are most useful and appropriate.
175 Examples
5
Example 1
Project: theanolm Source File: bigramoptimizer_test.py
def assert_optimizers_equal(self, numpy_optimizer, theano_optimizer):
self.assertTrue(numpy.array_equal(numpy_optimizer._word_counts, theano_optimizer._word_counts.get_value()))
self.assertEqual((numpy_optimizer._ww_counts - theano_optimizer._ww_counts.get_value()).nnz, 0)
self.assertTrue(numpy.array_equal(numpy_optimizer._class_counts, theano_optimizer._class_counts.get_value()))
self.assertTrue(numpy.array_equal(numpy_optimizer._cc_counts, theano_optimizer._cc_counts.get_value()))
self.assertTrue(numpy.array_equal(numpy_optimizer._cw_counts, theano_optimizer._cw_counts.get_value()))
self.assertTrue(numpy.array_equal(numpy_optimizer._wc_counts, theano_optimizer._wc_counts.get_value()))
5
Example 2
Project: selective_search_py Source File: test_color_space.py
def test_convert_color_value(self):
assert numpy.array_equal(convert_color(self.Irand, 'rgb'), self.Irand)
assert numpy.array_equal(convert_color(self.Irand, 'lab'), to_Lab(self.Irand))
assert numpy.array_equal(convert_color(self.Irand, 'rgi'), to_rgI(self.Irand))
assert numpy.array_equal(convert_color(self.Irand, 'hsv'), to_HSV(self.Irand))
assert numpy.array_equal(convert_color(self.Irand, 'nrgb'), to_nRGB(self.Irand))
assert numpy.array_equal(convert_color(self.Irand, 'hue'), to_Hue(self.Irand))
3
Example 3
def test_pickle(self, net_fitted, X_test, y_pred):
recursionlimit = sys.getrecursionlimit()
sys.setrecursionlimit(10000)
pickled = pickle.dumps(net_fitted, -1)
net_loaded = pickle.loads(pickled)
assert np.array_equal(net_loaded.predict(X_test), y_pred)
sys.setrecursionlimit(recursionlimit)
3
Example 4
Project: pyphi Source File: utils.py
def independent(repertoire):
"""Check whether the repertoire is independent."""
marginals = [marginal(repertoire, i) for i in range(repertoire.ndim)]
# TODO: is there a way to do without an explicit iteration?
joint = marginals[0]
for m in marginals[1:]:
joint = joint * m
# TODO: should we round here?
#repertoire = repertoire.round(config.PRECISION)
#joint = joint.round(config.PRECISION)
return np.array_equal(repertoire, joint)
3
Example 5
def __eq__(self, other):
'''
Check equivalence between MinHash
'''
return self.seed == other.seed and \
np.array_equal(self.hashvalues, other.hashvalues)
3
Example 6
def test(self):
op = numeric.Sqrt()
out = op.shade([1, 1, 1])
self.assertTrue(np.array_equal(out, [1, 1, 1]))
a = np.array([[4, 4, 4],
[9, 9, 9],
[25, 25, 25]])
expected = np.array([[2, 2, 2],
[3, 3, 3],
[5, 5, 5]], dtype=float)
out = op.shade(a)
self.assertTrue(np.array_equal(out, expected),
"Unequal:\n %s \n = \n %s" % (out, expected))
3
Example 7
def __eq__(self, other):
if self is other:
return True
if type(other) is not Matrix:
return False
if self._data is None and other._data is None:
return True
return numpy.array_equal(self._data, other._data)
3
Example 8
Project: diogenes Source File: test_modify.py
def test_col_fewer_than_n_nonzero(self):
M = cast_list_of_list_to_sa(
[[0,2,3], [0,3,4], [1,4,5]],
col_names=['height','weight', 'age'])
arguments = [{'func': col_fewer_than_n_nonzero, 'vals': 2}]
M = remove_cols_where(M, arguments)
correct = cast_list_of_list_to_sa(
[[2,3], [3,4], [4,5]],
col_names=['weight', 'age'])
self.assertTrue(np.array_equal(M, correct))
3
Example 9
def _K_computations(self, X, X2):
if not (np.array_equal(X, self._X) and np.array_equal(X2, self._X2) and np.array_equal(self._params , self._get_params())):
self._X = X.copy()
self._params = self._get_params().copy()
if X2 is None:
self._X2 = None
X = X * self.inv_lengthscale
Xsquare = np.sum(np.square(X), 1)
self._K_dist2 = -2.*tdot(X) + (Xsquare[:, None] + Xsquare[None, :])
else:
self._X2 = X2.copy()
X = X * self.inv_lengthscale
X2 = X2 * self.inv_lengthscale
self._K_dist2 = -2.*np.dot(X, X2.T) + (np.sum(np.square(X), 1)[:, None] + np.sum(np.square(X2), 1)[None, :])
self._K_dvar = np.exp(-0.5 * self._K_dist2)
3
Example 10
def check_hdf5_file(output_path, expected, dataset="buffer"):
import h5py
import numpy
with h5py.File(output_path, 'r') as fp:
if dataset not in fp:
return False
if not numpy.array_equal(expected, fp[dataset]):
return False
return True
3
Example 11
Project: TensorVision Source File: test_utils.py
def test_overlay_segmentation():
"""Test overlay_segmentation."""
from tensorvision.utils import overlay_segmentation
import scipy.ndimage
import numpy as np
seg_image = 'tensorvision/tests/Crocodylus-johnsoni-3-seg.png'
original_image = 'tensorvision/tests/Crocodylus-johnsoni-3.jpg'
target_path = 'tensorvision/tests/croco-overlay-new.png'
correct_path = 'tensorvision/tests/croco-overlay.png'
input_image = scipy.misc.imread(original_image)
segmentation = scipy.misc.imread(seg_image)
color_changes = {0: (0, 255, 0, 127),
'default': (0, 0, 0, 0)}
res = overlay_segmentation(input_image, segmentation, color_changes)
scipy.misc.imsave(target_path, res)
img1 = scipy.ndimage.imread(correct_path)
img2 = scipy.ndimage.imread(target_path)
assert np.array_equal(img1, img2)
3
Example 12
def test_data(self):
for dm, exp in zip(self.dms, self.dm_redundant_forms):
obs = dm.data
self.assertTrue(np.array_equal(obs, exp))
with self.assertRaises(AttributeError):
self.dm_3x3.data = 'foo'
3
Example 13
def test_h5(init_pyDive):
test_array = pyDive.h5.open(input_file, "particles/pos")
ref_array_x = h5.File(input_file, "r")["particles/pos/x"][:]
ref_array_y = h5.File(input_file, "r")["particles/pos/y"][:]
assert np.array_equal(ref_array_x, test_array["x"].load().gather())
assert np.array_equal(ref_array_y, test_array["y"].load().gather())
assert np.array_equal(ref_array_x, test_array.load()["x"].gather())
assert np.array_equal(ref_array_y, test_array.load()["y"].gather())
3
Example 14
Project: spark-tk Source File: inspect_dicom_test.py
def test_image_content_inspect_dcm_basic(self):
"""content test of image data for dicom"""
# load the files so we can compare with the dicom result
files = []
for filename in os.listdir(self.image_directory):
pixel_data = dicom.read_file(self.image_directory + filename).pixel_array
files.append(pixel_data)
# iterate through the data in the files and in the dicom frame
# and ensure that they match
image_inspect = self.dicom.pixeldata.inspect().rows
for dcm_image in image_inspect:
result = any(numpy.array_equal(dcm_image[1], file_image) for file_image in files)
self.assertTrue(result)
3
Example 15
def run_spread(self, spread, in_vals, expected, **kwargs):
op = npg.Spread(factor=spread, **kwargs)
out = op.shade(in_vals)
self.assertTrue(np.array_equal(out, expected),
'incorrect value spreading\n %s' % str(out))
3
Example 16
Project: theanolm Source File: vocabulary_test.py
def test_from_state(self):
self.classes_file.seek(0)
vocabulary1 = Vocabulary.from_file(self.classes_file, 'srilm-classes')
f = h5py.File('in-memory.h5', driver='core', backing_store=False)
vocabulary1.get_state(f)
vocabulary2 = Vocabulary.from_state(f)
self.assertTrue(numpy.array_equal(vocabulary1.id_to_word,
vocabulary2.id_to_word))
self.assertDictEqual(vocabulary1.word_to_id, vocabulary2.word_to_id)
self.assertTrue(numpy.array_equal(vocabulary1.word_id_to_class_id,
vocabulary2.word_id_to_class_id))
self.assertListEqual(list(vocabulary1._word_classes),
list(vocabulary2._word_classes))
3
Example 17
Project: diogenes Source File: test_modify.py
def test_col_val_eq(self):
M = cast_list_of_list_to_sa(
[[1,2,3], [1,3,4], [1,4,5]],
col_names=['height','weight', 'age'])
arguments = [{'func': col_val_eq, 'vals': 1}]
M = remove_cols_where(M, arguments)
correct = cast_list_of_list_to_sa(
[[2,3], [3,4], [4,5]],
col_names=['weight', 'age'])
self.assertTrue(np.array_equal(M, correct))
3
Example 18
Project: bhmm Source File: test_bhmm.py
def test_transition_matrix_samples(self):
Psamples = self.sampled_hmm_lag10.transition_matrix_samples
# shape
assert np.array_equal(Psamples.shape, (self.nsamples, self.nstates, self.nstates))
# consistency
import msmtools.analysis as msmana
for P in Psamples:
assert msmana.is_transition_matrix(P)
assert msmana.is_reversible(P)
3
Example 19
Project: butterflow Source File: test_source.py
def test_seek_forward_then_backward(self):
self.src_3.seek_to_fr(2)
f1 = self.src_3.read()
f2 = avutil_fr_at_idx(self.src_3.src, self.imagefile, 2)
self.assertTrue(np.array_equal(f1,f2))
self.src_3.seek_to_fr(1)
f1 = self.src_3.read()
f2 = avutil_fr_at_idx(self.src_3.src, self.imagefile, 1)
self.assertTrue(np.array_equal(f1,f2))
self.src_3.seek_to_fr(0)
f1 = self.src_3.read()
f2 = avutil_fr_at_idx(self.src_3.src, self.imagefile, 0)
self.assertTrue(np.array_equal(f1,f2))
3
Example 20
Project: attention-lvcsr Source File: test_opt.py
def test_append_inplace(self):
mySymbolicMatricesList = TypedListType(T.TensorType(
theano.config.floatX, (False, False)))()
mySymbolicMatrix = T.matrix()
z = Append()(mySymbolicMatricesList, mySymbolicMatrix)
m = theano.compile.mode.get_default_mode().including("typed_list_inplace_opt")
f = theano.function([In(mySymbolicMatricesList, borrow=True,
mutable=True),
In(mySymbolicMatrix, borrow=True,
mutable=True)], z, accept_inplace=True, mode=m)
self.assertTrue(f.maker.fgraph.toposort()[0].op.inplace)
x = rand_ranged_matrix(-1000, 1000, [100, 101])
y = rand_ranged_matrix(-1000, 1000, [100, 101])
self.assertTrue(numpy.array_equal(f([x], y), [x, y]))
3
Example 21
def jaccard(self, other):
'''
Estimate Jaccard similarity (resemblance) using this WeightedMinHash
and the other.
'''
if other.seed != self.seed:
raise ValueError("Cannot compute Jaccard given WeightedMinHash objects with\
different seeds")
if len(self) != len(other):
raise ValueError("Cannot compute Jaccard given WeightedMinHash objects with\
different numbers of hash values")
# Check how many pairs of (k, t) hashvalues are equal
intersection = 0
for this, that in zip(self.hashvalues, other.hashvalues):
if np.array_equal(this, that):
intersection += 1
return float(intersection) / float(len(self))
3
Example 22
Project: pyphi Source File: test_convert.py
def test_state_by_state2state_by_node():
result = convert.state_by_state2state_by_node(state_by_state)
expected = convert.to_n_dimensional(state_by_node)
print("Result:")
print(result)
print("Expected:")
print(expected)
assert np.array_equal(result, expected)
3
Example 23
Project: pyphi Source File: test_convert.py
def test_nondet_state_by_node2state_by_state():
# Test for nondeterministic TPM.
result = convert.state_by_node2state_by_state(state_by_node_nondet)
expected = state_by_state_nondet
print("Result:")
print(result)
print("Expected:")
print(expected)
assert np.array_equal(result, expected)
3
Example 24
Project: attention-lvcsr Source File: test_opt.py
def test_extend_inplace(self):
mySymbolicMatricesList1 = TypedListType(T.TensorType(
theano.config.floatX, (False, False)))()
mySymbolicMatricesList2 = TypedListType(T.TensorType(
theano.config.floatX, (False, False)))()
z = Extend()(mySymbolicMatricesList1, mySymbolicMatricesList2)
m = theano.compile.mode.get_default_mode().including("typed_list_inplace_opt")
f = theano.function([In(mySymbolicMatricesList1, borrow=True,
mutable=True), mySymbolicMatricesList2],
z, mode=m)
self.assertTrue(f.maker.fgraph.toposort()[0].op.inplace)
x = rand_ranged_matrix(-1000, 1000, [100, 101])
y = rand_ranged_matrix(-1000, 1000, [100, 101])
self.assertTrue(numpy.array_equal(f([x], [y]), [x, y]))
3
Example 25
def test_copy(self):
copy = self.dm_2x2.copy()
self.assertEqual(copy, self.dm_2x2)
self.assertFalse(copy.data is self.dm_2x2.data)
# deepcopy doesn't actually create a copy of the IDs because it is a
# tuple of strings, which is fully immutable.
self.assertTrue(copy.ids is self.dm_2x2.ids)
new_ids = ['hello', 'world']
copy.ids = new_ids
self.assertNotEqual(copy.ids, self.dm_2x2.ids)
copy = self.dm_2x2.copy()
copy.data[0, 1] = 0.0001
self.assertFalse(np.array_equal(copy.data, self.dm_2x2.data))
3
Example 26
Project: TensorVision Source File: test_utils.py
def test_soft_overlay_segmentation():
"""Test soft_overlay_segmentation."""
from tensorvision.utils import soft_overlay_segmentation
import scipy.ndimage
import numpy as np
seg_image = 'tensorvision/tests/Crocodylus-johnsoni-3-seg-prob.png'
original_image = 'tensorvision/tests/Crocodylus-johnsoni-3.jpg'
target_path = 'tensorvision/tests/croco-overlay-new-soft.png'
correct_path = 'tensorvision/tests/croco-overlay-soft.png'
input_image = scipy.misc.imread(original_image)
segmentation = scipy.misc.imread(seg_image) / 255.0
res = soft_overlay_segmentation(input_image, segmentation)
scipy.misc.imsave(target_path, res)
img1 = scipy.ndimage.imread(correct_path)
img2 = scipy.ndimage.imread(target_path)
assert np.array_equal(img1, img2)
3
Example 27
Project: orange3-text Source File: corpus.py
def __eq__(self, other):
def arrays_equal(a, b):
if sp.issparse(a) != sp.issparse(b):
return False
elif sp.issparse(a) and sp.issparse(b):
return (a != b).nnz == 0
else:
return np.array_equal(a, b)
return (self.text_features == other.text_features and
self._dictionary == other._dictionary and
np.array_equal(self._tokens, other._tokens) and
arrays_equal(self.X, other.X) and
arrays_equal(self.Y, other.Y) and
arrays_equal(self.metas, other.metas) and
np.array_equal(self.pos_tags, other.pos_tags) and
self.domain == other.domain and
self.ngram_range == other.ngram_range)
3
Example 28
Project: pyDive Source File: test_h5_ndarray.py
def test_h5_ndarray1(init_pyDive):
dataset = "particles/pos/x"
test_array = pyDive.h5.open(input_file, dataset)
ref_array = h5.File(input_file, "r")[dataset][:]
assert np.array_equal(ref_array, test_array.load().gather())
3
Example 29
Project: spark-tk Source File: create_dicom_test.py
def test_image_content_import_dcm_basic(self):
"""content test of image data for dicom"""
# load the files so we can compare with the dicom result
files = []
for filename in os.listdir(self.image_directory):
pixel_data = dicom.read_file(self.image_directory + filename).pixel_array
files.append(pixel_data)
# iterate through the data in the files and in the dicom frame
# and ensure that they match
image_pandas = self.dicom.pixeldata.to_pandas()["imagematrix"]
for dcm_image in image_pandas:
result = any(numpy.array_equal(dcm_image, file_image) for file_image in files)
self.assertTrue(result)
3
Example 30
def test(self):
op = numeric.Cuberoot()
out = op.shade([1, 1, 1])
self.assertTrue(np.array_equal(out, [1, 1, 1]))
a = np.array([[27],
[64],
[125]])
# Calculates in-place because of floating point round-off
expected = np.array([[pow(27, 1/3.0)],
[pow(64, 1/3.0)],
[pow(125, 1/3.0)]], dtype=float)
out = op.shade(a)
self.assertTrue(np.array_equal(out, expected),
"Unequal:\n %s \n = \n %s" % (out, expected))
3
Example 31
Project: attention-lvcsr Source File: test_type.py
def test_filter_sanity_check(self):
"""
Simple test on typed list type filter
"""
myType = TypedListType(T.TensorType(theano.config.floatX,
(False, False)))
x = rand_ranged_matrix(-1000, 1000, [100, 100])
self.assertTrue(numpy.array_equal(myType.filter([x]), [x]))
3
Example 32
def run_spread(self, spread, in_vals, expected):
op = numeric.Spread(factor=spread)
out = op.shade(in_vals)
self.assertTrue(np.array_equal(out, expected),
'incorrect value spreading\ni %s' % str(out))
3
Example 33
Project: spark-tk Source File: take_dicom_test.py
def test_image_content_take_dcm_basic(self):
"""content test of image data for dicom"""
# load the files so we can compare with the dicom result
files = []
for filename in os.listdir(self.image_directory):
pixel_data = dicom.read_file(self.image_directory + filename).pixel_array
files.append(pixel_data)
# iterate through the data in the files and in the dicom frame
# and ensure that they match
image_inspect = self.dicom.pixeldata.take(self.count)
for dcm_image in image_inspect:
result = any(numpy.array_equal(dcm_image[1], file_image) for file_image in files)
self.assertTrue(result)
3
Example 34
Project: deepchem Source File: test_datasets.py
def test_consistent_ordering(self):
"""Test that ordering of labels is consistent over time."""
solubility_dataset = dc.data.tests.load_solubility_data()
ids1 = solubility_dataset.ids
ids2 = solubility_dataset.ids
assert np.array_equal(ids1, ids2)
3
Example 35
Project: gensim Source File: test_sharded_corpus.py
def test_getitem(self):
_ = self.corpus[130]
# Does retrieving the item load the correct shard?
self.assertEqual(self.corpus.current_shard_n, 1)
item = self.corpus[220:227]
self.assertEqual((7, self.corpus.dim), item.shape)
self.assertEqual(self.corpus.current_shard_n, 2)
for i in xrange(220, 227):
self.assertTrue(numpy.array_equal(self.corpus[i], item[i-220]))
3
Example 36
Project: nolearn Source File: test_base.py
def test_save_params_to_path(self, net_fitted, X_test, y_pred):
path = '/tmp/test_lasagne_functional_mnist.params'
net_fitted.save_params_to(path)
net_loaded = clone(net_fitted)
net_loaded.load_params_from(path)
assert np.array_equal(net_loaded.predict(X_test), y_pred)
3
Example 37
def __eq__(self, other):
if self is other:
return True
if type(other) is not Polygon:
return False
point_count = len(self._points) if self._points is not None else 0
point_count2 = len(other.getPoints()) if other.getPoints() is not None else 0
if point_count != point_count2:
return False
return numpy.array_equal(self._points, other.getPoints())
3
Example 38
Project: diogenes Source File: test_modify.py
def test_col_val_eq_any(self):
M = cast_list_of_list_to_sa(
[[1,2,3], [1,3,4], [1,4,5]],
col_names=['height','weight', 'age'])
arguments = [{'func': col_val_eq_any, 'vals': None}]
M = remove_cols_where(M, arguments)
correct = cast_list_of_list_to_sa(
[[2,3], [3,4], [4,5]],
col_names=['weight', 'age'])
self.assertTrue(np.array_equal(M, correct))
3
Example 39
Project: butterflow Source File: test_source.py
def test_read_after_seek_to_fr_at_edges(self):
self.src_3.seek_to_fr(0)
f1 = self.src_3.read()
f2 = avutil_fr_at_idx(self.src_3.src, self.imagefile, 0)
self.assertTrue(np.array_equal(f1,f2))
self.src_3.seek_to_fr(2)
f1 = self.src_3.read()
f2 = avutil_fr_at_idx(self.src_3.src, self.imagefile, 2)
self.assertTrue(np.array_equal(f1,f2))
3
Example 40
Project: bhmm Source File: test_bhmm.py
def test_transition_matrix_stats(self):
import msmtools.analysis as msmana
# mean
Pmean = self.sampled_hmm_lag10.transition_matrix_mean
# test shape and consistency
assert np.array_equal(Pmean.shape, (self.nstates, self.nstates))
assert msmana.is_transition_matrix(Pmean)
# std
Pstd = self.sampled_hmm_lag10.transition_matrix_std
# test shape
assert np.array_equal(Pstd.shape, (self.nstates, self.nstates))
# conf
L, R = self.sampled_hmm_lag10.transition_matrix_conf
# test shape
assert np.array_equal(L.shape, (self.nstates, self.nstates))
assert np.array_equal(R.shape, (self.nstates, self.nstates))
# test consistency
assert np.all(L <= Pmean)
assert np.all(R >= Pmean)
3
Example 41
def __eq__(self, other):
'''
Check equivalence between two HyperLogLogs
'''
if self.p != other.p:
return False
if self.m != other.m:
return False
if not np.array_equal(self.reg, other.reg):
return False
return True
3
Example 42
Project: molecular-design-toolkit Source File: molecule.py
def get_property(self, name):
""" Return the given property if already calculated; raise NotCalculatedError otherwise
Args:
name (str): name of the property (e.g. 'potential_energy', 'forces', etc.)
Raises:
NotCalculatedError: If the molecular property has not yet been calculated at this
geometry
Returns:
object: the requested property
"""
if name in self.properties and np.array_equal(self.properties.positions, self.positions):
return self.properties[name]
else:
raise NotCalculatedError(
("The '{0}' property hasn't been calculated yet. "
"Calculate it with the molecule.calculate_{0}() method").format(name))
3
Example 43
def __eq__(self, other):
'''
Check equivalence between WeightedMinHash
'''
return self.seed == other.seed and \
np.array_equal(self.hashvalues, other.hashvalues)
3
Example 44
Project: pyphi Source File: test_convert.py
def test_to_n_dimensional():
N = state_by_node.shape[-1]
S = state_by_node.shape[0]
result = convert.to_n_dimensional(state_by_node)
for i in range(S):
state = convert.loli_index2state(i, N)
assert np.array_equal(result[state], state_by_node[i])
3
Example 45
Project: plip Source File: supplemental.py
def vecangle(v1, v2, deg=True):
"""Calculate the angle between two vectors
:param v1: coordinates of vector v1
:param v2: coordinates of vector v2
:returns : angle in degree or rad
"""
if np.array_equal(v1, v2):
return 0.0
dm = np.dot(v1, v2)
cm = np.linalg.norm(v1) * np.linalg.norm(v2)
angle = np.arccos(round(dm / cm, 10)) # Round here to prevent floating point errors
return np.degrees([angle, ])[0] if deg else angle
3
Example 46
def test_Raster():
import numpy as np
bounds = (244156, 1000258, 245114, 1000968)
r1 = Raster(raster, band=1).read(bounds)
with rasterio.open(raster) as src:
arr = src.read(1)
affine = src.affine
nodata = src.nodata
r2 = Raster(arr, affine, nodata, band=1).read(bounds)
# If the abstraction is correct, the arrays are equal
assert np.array_equal(r1.array, r2.array)
3
Example 47
Project: molecular-design-toolkit Source File: test_data_structures.py
def test_h2_cache_flush(h2_harmonic):
h2 = h2_harmonic
pe = h2.calc_potential_energy()
f = h2.forces
h2.atoms[0].x += 0.1285*u.ang
pe2 = h2.calc_potential_energy()
f2 = h2.forces
assert pe != pe2
assert not np.array_equal(f, f2)
3
Example 48
Project: attention-lvcsr Source File: test_opt.py
def test_remove_inplace(self):
mySymbolicMatricesList = TypedListType(T.TensorType(
theano.config.floatX, (False, False)))()
mySymbolicMatrix = T.matrix()
z = Remove()(mySymbolicMatricesList, mySymbolicMatrix)
m = theano.compile.mode.get_default_mode().including("typed_list_inplace_opt")
f = theano.function([In(mySymbolicMatricesList, borrow=True,
mutable=True), In(mySymbolicMatrix, borrow=True,
mutable=True)], z, accept_inplace=True, mode=m)
self.assertTrue(f.maker.fgraph.toposort()[0].op.inplace)
x = rand_ranged_matrix(-1000, 1000, [100, 101])
y = rand_ranged_matrix(-1000, 1000, [100, 101])
self.assertTrue(numpy.array_equal(f([x, y], y), [x]))
3
Example 49
def test_map_generic(sc):
x = arange(2*8*8).reshape(2, 8, 8)
b = array(x, sc)
c = b.chunk(size=(8, 5))
d = c.map_generic(lambda x: [0, 1]).toarray()
truth = empty(2*1*2, dtype=object)
for i in range(truth.shape[0]):
truth[i] = [0, 1]
truth = truth.reshape(2, 1, 2)
assert array_equal(d, truth)
3
Example 50
Project: pyDive Source File: multiple_axes.py
def is_distributed_like(self, other):
if self.distaxes == other.distaxes:
if all(np.array_equal(my_target_offsets, other_target_offsets) \
for my_target_offsets, other_target_offsets in zip(self.target_offsets, other.target_offsets)):
if self.target_ranks == other.target_ranks:
return True
return False