Here are the examples of the python api numpy.allclose taken from open source projects. By voting up you can indicate which examples are most useful and appropriate.
178 Examples
5
Example 1
Project: oq-hazardlib Source File: geodetic_test.py
def test_zero_distance(self):
lon, lat, depth, azimuth = 12, 34, 56, 78
lons, lats, depths = geodetic.npoints_towards(
lon, lat, depth, azimuth, hdist=0, vdist=0, npoints=5
)
expected_lons = [lon] * 5
expected_lats = [lat] * 5
expected_depths = [depth] * 5
self.assertTrue(numpy.allclose(lons, expected_lons))
self.assertTrue(numpy.allclose(lats, expected_lats))
self.assertTrue(numpy.allclose(depths, expected_depths))
5
Example 2
Project: gensim Source File: test_word2vec.py
def models_equal(self, model, model2):
self.assertEqual(len(model.vocab), len(model2.vocab))
self.assertTrue(numpy.allclose(model.syn0, model2.syn0))
if model.hs:
self.assertTrue(numpy.allclose(model.syn1, model2.syn1))
if model.negative:
self.assertTrue(numpy.allclose(model.syn1neg, model2.syn1neg))
most_common_word = max(model.vocab.items(), key=lambda item: item[1].count)[0]
self.assertTrue(numpy.allclose(model[most_common_word], model2[most_common_word]))
5
Example 3
Project: pyscf Source File: test_addons.py
def test_sort_mo_by_irrep(self):
mc1 = mcscf.CASSCF(mfr, 8, 4)
mo0 = mcscf.sort_mo_by_irrep(mc1, mfr.mo_coeff, {'E1ux':2, 'E1uy':2, 'E1gx':2, 'E1gy':2})
mo1 = mcscf.sort_mo_by_irrep(mc1, mfr.mo_coeff, {2:2, 3:2, 6:2, 7:2}, {2:0, 3:0, 6:0, 7:0})
mo2 = mcscf.sort_mo_by_irrep(mc1, mfr.mo_coeff, (0,0,2,2,0,0,2,2))
mo3 = mcscf.sort_mo_by_irrep(mc1, mfr.mo_coeff, {'E1ux':2, 'E1uy':2, 2:2, 3:2})
self.assertTrue(numpy.allclose(mo0, mo1))
self.assertTrue(numpy.allclose(mo0, mo2))
self.assertTrue(numpy.allclose(mo0, mo3))
5
Example 4
def testPersistence(self):
fname = testfile()
model = self.model
model.save(fname)
model2 = lsimodel.LsiModel.load(fname)
self.assertEqual(model.num_topics, model2.num_topics)
self.assertTrue(numpy.allclose(model.projection.u, model2.projection.u))
self.assertTrue(numpy.allclose(model.projection.s, model2.projection.s))
tstvec = []
self.assertTrue(numpy.allclose(model[tstvec], model2[tstvec])) # try projecting an empty vector
5
Example 5
def check(self):
script = self.script
src = script.engine.current_scene.children[0]
i1, i2, i3 = src.children[0].children[1:]
assert i1.ipw.plane_orientation == 'x_axes'
assert numpy.allclose(i1.ipw.center, (0, 31.5, 31.5))
rng = i1.ipw.reslice_output.point_data.scalars.range
assert numpy.allclose(rng, (-0.2, 1.0), atol=0.1)
assert i2.ipw.plane_orientation == 'y_axes'
assert numpy.allclose(i2.ipw.center, (31.5, 0, 31.5))
rng = i2.ipw.reslice_output.point_data.scalars.range
assert numpy.allclose(rng, (-0.2, 1.0), atol=0.1)
assert i3.ipw.plane_orientation == 'z_axes'
assert numpy.allclose(i3.ipw.center, (31.5, 31.5, 0))
rng = i3.ipw.reslice_output.point_data.scalars.range
assert numpy.allclose(rng, (-0.2, 1.0), atol=0.1)
5
Example 6
def check(self):
"""Do the actual testing."""
s=self.scene
src = s.children[0]
i1, i2, i3 = src.children[0].children[1:]
self.assertEqual(i1.ipw.plane_orientation,'x_axes')
self.assertEqual(numpy.allclose(i1.ipw.center, (0, 31.5, 31.5)),True)
self.assertEqual( i2.ipw.plane_orientation,'y_axes')
self.assertEqual(numpy.allclose(i2.ipw.center, (31.5, 0, 31.5)),True)
self.assertEqual(i3.ipw.plane_orientation,'z_axes')
self.assertEqual( numpy.allclose(i3.ipw.center, (31.5, 31.5, 0)),True)
5
Example 7
Project: oq-hazardlib Source File: geodetic_test.py
def test_same_points(self):
lon, lat, depth = 1.2, 3.4, 5.6
lons, lats, depths = geodetic.npoints_between(
lon, lat, depth, lon, lat, depth, npoints=7
)
expected_lons = [lon] * 7
expected_lats = [lat] * 7
expected_depths = [depth] * 7
self.assertTrue(numpy.allclose(lons, expected_lons))
self.assertTrue(numpy.allclose(lats, expected_lats))
self.assertTrue(numpy.allclose(depths, expected_depths))
5
Example 8
Project: topical_word_embeddings Source File: test_models.py
def testLargeMmap(self):
model = ldamodel.LdaModel(self.corpus, num_topics=2)
# simulate storing large arrays separately
model.save(testfile(), sep_limit=0)
model2 = ldamodel.LdaModel.load(testfile())
self.assertEqual(model.num_topics, model2.num_topics)
self.assertTrue(numpy.allclose(model.expElogbeta, model2.expElogbeta))
tstvec = []
self.assertTrue(numpy.allclose(model[tstvec], model2[tstvec])) # try projecting an empty vector
# test loading the large model arrays with mmap
model2 = ldamodel.LdaModel.load(testfile(), mmap='r')
self.assertEqual(model.num_topics, model2.num_topics)
self.assertTrue(numpy.allclose(model.expElogbeta, model2.expElogbeta))
tstvec = []
self.assertTrue(numpy.allclose(model[tstvec], model2[tstvec])) # try projecting an empty vector
5
Example 9
def testPersistence(self):
model = lsimodel.LsiModel(self.corpus, num_topics=2)
model.save(testfile())
model2 = lsimodel.LsiModel.load(testfile())
self.assertEqual(model.num_topics, model2.num_topics)
self.assertTrue(numpy.allclose(model.projection.u, model2.projection.u))
self.assertTrue(numpy.allclose(model.projection.s, model2.projection.s))
tstvec = []
self.assertTrue(numpy.allclose(model[tstvec], model2[tstvec])) # try projecting an empty vector
5
Example 10
def testPersistenceCompressed(self):
fname = testfile() + '.gz'
model = self.model
model.save(fname)
model2 = lsimodel.LsiModel.load(fname, mmap=None)
self.assertEqual(model.num_topics, model2.num_topics)
self.assertTrue(numpy.allclose(model.projection.u, model2.projection.u))
self.assertTrue(numpy.allclose(model.projection.s, model2.projection.s))
tstvec = []
self.assertTrue(numpy.allclose(model[tstvec], model2[tstvec])) # try projecting an empty vector
3
Example 11
Project: tract_querier Source File: test_tractography.py
def equal_tracts_data(a, b):
if set(a.keys()) != set(b.keys()):
return False
for k in a.keys():
v1 = a[k]
v2 = b[k]
if isinstance(v1, str) and isinstance(v2, str) and v1 == v2:
continue
elif not isinstance(v1, str) and not isinstance(v2, str):
for t1, t2 in izip(a[k], b[k]):
if not (len(t1) == len(t2) and allclose(t1, t2)):
return False
else:
return False
return True
3
Example 12
def _check_lu_result(p, l, u, A):
assert np.allclose(p.dot(l).dot(u), A)
# check triangulars
assert np.allclose(l, np.tril(l.compute()))
assert np.allclose(u, np.triu(u.compute()))
3
Example 13
def test_grad_identity():
fun = lambda x : x
df = grad(fun)
ddf = grad(df)
assert np.allclose(df(2.0), 1.0)
assert np.allclose(ddf(2.0), 0.0)
3
Example 14
def test_getitem(self):
M = Mesh.TreeMesh([4,4])
M.refine(1)
assert M.nC == 4
assert len(M) == M.nC
assert np.allclose(M[0].center, [0.25,0.25])
actual = [[0,0],[0.5,0],[0,0.5],[0.5,0.5]]
for i, n in enumerate(M[0].nodes):
assert np.allclose(M._gridN[n,:], actual[i])
3
Example 15
Project: pypcd Source File: test_pypcd.py
def test_ascii_bin1(ascii_pcd_fname, bin_pcd_fname):
import pypcd
apc1 = pypcd.point_cloud_from_path(ascii_pcd_fname)
bpc1 = pypcd.point_cloud_from_path(bin_pcd_fname)
am = cloud_centroid(apc1)
bm = cloud_centroid(bpc1)
assert( np.allclose(am, bm) )
3
Example 16
Project: yandex-tank Source File: test_test.py
def test_random_split(data):
dataframes = list(random_split(data))
assert len(dataframes) > 1
concatinated = pd.concat(dataframes)
assert len(concatinated) == len(data), "We did not lose anything"
assert np.allclose(concatinated.values,
data.values), "We did not corrupt the data"
3
Example 17
def test_getitem(self):
""" Is getitem adapted correctly?
"""
value = self.context['depth']
desired = self.convert_out(array((20., 30., 40., 50.)))
self.assertEqual(len(value), 4)
self.assertTrue(allclose(value, desired))
3
Example 18
def allclose(self, a, b, rtol=1e-05, atol=1e-08):
adist = a.distribution
bdist = b.distribution
if not adist.is_compatible(bdist):
raise ValueError("%r and %r have incompatible distributions.")
def local_allclose(la, lb, rtol, atol):
from numpy import allclose
return allclose(la.ndarray, lb.ndarray, rtol, atol)
local_results = self.apply(local_allclose,
(a.key, b.key, rtol, atol),
targets=a.targets)
return all(local_results)
3
Example 19
def allclose(a, b):
"""
Test that a and b are close and match in shape.
Parameters
----------
a : ndarray
First array to check
b : ndarray
First array to check
"""
from numpy import allclose
return (a.shape == b.shape) and allclose(a, b)
3
Example 20
def __eq__(self, other):
if not isinstance(other, Detector):
return False
for key in ['name', 'sampling_rate', 'multiplex', 'lowcut', 'highcut',
'filt_order', 'dimension', 'stachans']:
if not self.__getattribute__(key) == other.__getattribute__(key):
return False
for key in ['data', 'u', 'v', 'sigma']:
list_item = self.__getattribute__(key)
other_list = other.__getattribute__(key)
if not len(list_item) == len(other_list):
return False
for item, other_item in zip(list_item, other_list):
if not np.allclose(item, other_item):
return False
return True
3
Example 21
Project: karta Source File: grid_tests.py
def test_profile(self):
path = karta.Line([(15.0, 15.0), (1484.0, 1484.0)], crs=karta.crs.Cartesian)
pts, z = self.rast.profile(path, resolution=42.426406871192853, method="nearest")
expected = self.rast[:,:].diagonal()
self.assertEqual(len(pts), 49)
self.assertTrue(np.allclose(z, expected))
return
3
Example 22
Project: pandashells Source File: p_regress_tests.py
@patch(
'pandashells.bin.p_regress.sys.argv',
'p.regress -m y~x --fit'.split())
@patch('pandashells.bin.p_regress.io_lib.df_to_output')
@patch('pandashells.bin.p_regress.io_lib.df_from_input')
def test_cli_fit(self, df_from_input_mock, df_to_output_mock):
df_in = pd.DataFrame({
'x': range(1, 101),
'y': range(1, 101),
})
df_from_input_mock.return_value = df_in
main()
df_out = df_to_output_mock.call_args_list[0][0][1]
self.assertTrue(np.allclose(df_out.y, df_out.fit_))
self.assertTrue(np.allclose(df_out.y * 0, df_out.resid_))
3
Example 23
Project: spectral Source File: detectors.py
def test_mf_windowed_target_eq_one(self):
'''Windowed Matched Filter response of target pixel should be one.'''
X = self.data[:10, :10, :]
ij = (3, 3)
y = spy.matched_filter(X, X[ij], window=(3,7), cov=self.background.cov)
np.allclose(1, y[ij])
3
Example 24
Project: tfr Source File: spectrogram_test.py
def test_window_should_be_normalized():
def assert_ok(size):
w = create_window(size)
assert np.allclose(energy(w), len(w))
assert np.allclose(mean_power(w), 1.0)
for size in [16, 100, 512, 777, 4096]:
yield assert_ok, size
3
Example 25
def test_output():
n, tempfilename = tempfile.mkstemp()
audio.output(tempfilename, format='WAV')
new_samples, new_sample_rate = librosa.load(tempfilename, sr=audio.sample_rate)
os.unlink(tempfilename)
assert np.allclose(audio.sample_rate, new_sample_rate)
assert np.allclose(audio.raw_samples, new_samples, rtol=1e-3, atol=1e-4)
3
Example 26
Project: GPflow Source File: test_conditionals.py
def test_whiten(self):
"""
make sure that predicting using the whitened representation is the
sameas the non-whitened one.
"""
with self.k.tf_mode():
K = self.k.K(self.X) + eye(self.num_data) * 1e-6
L = tf.cholesky(K)
V = tf.matrix_triangular_solve(L, self.F, lower=True)
Fstar_mean, Fstar_var = GPflow.conditionals.gp_predict(self.Xs, self.X, self.k, self.F)
Fstar_w_mean, Fstar_w_var = GPflow.conditionals.gp_predict_whitened(self.Xs, self.X, self.k, V)
mean1, var1 = tf.Session().run([Fstar_w_mean, Fstar_w_var], feed_dict=self.feed_dict)
mean2, var2 = tf.Session().run([Fstar_mean, Fstar_var], feed_dict=self.feed_dict)
self.assertTrue(np.allclose(mean1, mean2, 1e-6, 1e-6)) # TODO: should tolerance be type dependent?
self.assertTrue(np.allclose(var1, var2, 1e-6, 1e-6))
3
Example 27
Project: yatsm Source File: test__cusum.py
def test_cusum_OLS(test_data, strucchange_cusum_OLS):
""" Tested against strucchange 1.5.1
"""
y = test_data.pop('y')
X = test_data
# Test sending pandas
result = cu.cusum_OLS(X, y)
assert np.allclose(result.score, strucchange_cusum_OLS[0])
assert np.allclose(result.pvalue, strucchange_cusum_OLS[1])
# And ndarray and xarray
result = cu.cusum_OLS(X.values, xr.DataArray(y, dims=['time']))
assert np.allclose(result.score, strucchange_cusum_OLS[0])
assert np.allclose(result.pvalue, strucchange_cusum_OLS[1])
3
Example 28
Project: pypar Source File: test_calculate_region.py
def test2(self):
kmax = 32
M = N = 5
real_min = -2.0
real_max = 1.0
imag_min = -1.5
imag_max = 1.5
A = calculate_region(real_min, real_max,
imag_min, imag_max, kmax, M, N)
assert numpy.allclose(A,
[[1, 1, 1, 1, 1],
[1, 3, 5, 5, 3],
[2, 4, 9, 9, 4],
[2, 9, 32, 32, 9],
[2, 3, 15, 15, 3]])
3
Example 29
def is_reversible(P):
""" Returns if P is reversible on its weakly connected sets """
import msmtools.analysis as msmana
# treat each weakly connected set separately
sets = connected_sets(P, strong=False)
for s in sets:
Ps = P[s, :][:, s]
if not msmana.is_transition_matrix(Ps):
return False # isn't even a transition matrix!
pi = msmana.stationary_distribution(Ps)
X = pi[:, None] * Ps
if not np.allclose(X, X.T):
return False
# survived.
return True
3
Example 30
Project: deepchem Source File: test_basic.py
def testRDKitDescriptors(self):
"""
Test simple descriptors.
"""
descriptors = self.engine([self.mol])
assert np.allclose(
descriptors[0, self.engine.descriptors.index('ExactMolWt')], 180,
atol=0.1)
3
Example 31
Project: word2gauss Source File: test_embeddings.py
def _num_grad_check(self, embed, eps, rtol):
[(dmu, ndmu), (dsigma, ndsigma)] = numerical_grad(embed, 0, 1, eps)
for ij in [0, 1]:
self.assertTrue(
np.allclose(dmu[ij], ndmu[ij], rtol=rtol))
self.assertTrue(
np.allclose(dsigma[ij], ndsigma[ij], rtol=rtol))
3
Example 32
Project: opt_einsum Source File: test_input.py
def test_ellipse_input1():
string = '...a->...'
views = build_views(string)
ein = contract(string, *views, optimize=False)
opt = contract(views[0], [Ellipsis, 0], [Ellipsis])
assert np.allclose(ein, opt)
3
Example 33
def test_proto():
import os
filename = './temp_proto.lopq'
m = make_random_model()
m.export_proto(filename)
m2 = LOPQModel.load_proto(filename)
assert_equal(m.V, m2.V)
assert_equal(m.M, m2.M)
assert_equal(m.subquantizer_clusters, m2.subquantizer_clusters)
assert_true(np.allclose(m.Cs[0], m2.Cs[0]))
assert_true(np.allclose(m.Rs[0], m2.Rs[0]))
assert_true(np.allclose(m.mus[0], m2.mus[0]))
assert_true(np.allclose(m.subquantizers[0][0], m.subquantizers[0][0]))
os.remove(filename)
3
Example 34
Project: skll Source File: test_featureset.py
@attr('have_pandas')
def test_featureset_creation_from_dataframe_without_labels_with_vectorizer():
(expected, current) = featureset_creation_from_dataframe_helper(False, True)
# Directly comparing FeatureSet objects fails here because both sets
# of labels are all nan when labels isn't specified, and arrays of
# all nan are not equal to each other.
# Based off of FeatureSet.__eq__()
assert (expected.name == current.name and
(expected.ids == current.ids).all() and
expected.vectorizer == current.vectorizer and
np.allclose(expected.features.data,
current.features.data,
rtol=1e-6) and
np.all(np.isnan(expected.labels)) and
np.all(np.isnan(current.labels)))
3
Example 35
Project: chempy Source File: test_ode.py
@requires('numpy', 'pyodesys')
def test_SpecialFraction():
k, kprime = 3.142, 2.718
rsys = _get_SpecialFraction_rsys(k, kprime)
odesys = get_odesys(rsys, include_params=True)[0]
c0 = {'H2': 13, 'Br2': 17, 'HBr': 19}
r = k*c0['H2']*c0['Br2']**(3/2)/(c0['Br2'] + kprime*c0['HBr'])
ref = rsys.as_per_substance_array({'H2': -r, 'Br2': -r, 'HBr': 2*r})
res = odesys.f_cb(0, rsys.as_per_substance_array(c0))
assert np.allclose(res, ref)
3
Example 36
Project: cesium Source File: test_time_series.py
def test_time_series_init_1d():
t, m, e = sample_time_series(channels=1)
ts = TimeSeries(t, m, e)
assert ts.time.shape == t.shape and np.allclose(ts.time, t)
assert ts.measurement.shape == m.shape and np.allclose(ts.measurement, m)
assert ts.error.shape == e.shape and np.allclose(ts.error, e)
assert ts.n_channels == 1
3
Example 37
Project: discomll Source File: tests_classification.py
def test_log_reg_thetas(self):
# python tests_classification.py Tests_Classification.test_log_reg_thetas
from discomll.classification import logistic_regression
train_data1 = datasets.ex4_orange()
train_data2 = datasets.ex4_discomll()
lr = Orange.classification.logreg.LogRegFitter_Cholesky(train_data1)
thetas1 = lr[1]
thetas_url = logistic_regression.fit(train_data2)
thetas2 = [v for k, v in result_iterator(thetas_url["logreg_fitmodel"]) if k == "thetas"]
self.assertTrue(np.allclose(thetas1, thetas2))
3
Example 38
Project: symengine.py Source File: test_lambdify.py
def test_array_out():
if not HAVE_NUMPY: # nosetests work-around
return
if sys.version_info[0] < 3:
return # requires Py3
args, exprs, inp, check = _get_array()
lmb = se.Lambdify(args, exprs)
out1 = array.array('d', [0]*len(exprs))
out2 = lmb(inp, out1)
# Ensure buffer points to still data point:
assert out1.buffer_info()[0] == out2.__array_interface__['data'][0]
check(out1)
check(out2)
out2[:] = -1
assert np.allclose(out1[:], [-1]*len(exprs))
3
Example 39
Project: chemlab Source File: test_io.py
def test_read_xyz():
df = datafile('tests/data/sulphoxide.xyz')
mol1 = df.read('molecule')
df = datafile('/tmp/t.xyz', mode="w")
df.write('molecule', mol1)
df = datafile('/tmp/t.xyz', mode="rb")
mol2 = df.read('molecule')
assert np.allclose(mol1.r_array, mol2.r_array)
assert all(mol1.type_array == mol2.type_array)
3
Example 40
Project: pyhawkes Source File: parents.py
def _check_EZ(self):
"""
Check that Z adds up to the correct amount
:return:
"""
for Sk, EZk in zip(self.Ss, self.EZ):
assert np.allclose(Sk, EZk.sum(1))
3
Example 41
def test_scoring():
m = pwm.FrequencyMatrix.from_rows( ['A','C','G','T'], get_ctcf_rows() )
# Stormo method
sm = m.to_stormo_scoring_matrix()
# Forward matches
assert allclose( sm.score_string( "AATCACCACCTCCTGGCAGG" )[0], -156.8261261 )
assert allclose( sm.score_string( "TGCCTGCCTCTGTAGGCTCC" )[0], -128.8106842 )
assert allclose( sm.score_string( "GTTGCCAGTTGGGGGAAGCA" )[0], 4.65049839 )
assert allclose( sm.score_string( "GCAGACACCAGGTGGTTCAG" )[0], 1.60168743 )
# Reverse matches
rc = sm.reverse_complement()
assert allclose( rc.score_string( "AATCACCACCTCCTGGCAGG" )[0], 0.014178276062 )
assert allclose( rc.score_string( "TGCCTGCCTCTGTAGGCTCC" )[0], 0.723828315735 )
assert allclose( rc.score_string( "GTTGCCAGTTGGGGGAAGCA" )[0], -126.99407196 )
assert allclose( rc.score_string( "GCAGACACCAGGTGGTTCAG" )[0], -86.9560623169 )
# Nothing valid
assert isnan( sm.score_string_with_gaps( "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX" ) ).all()
# Too short
assert isnan( sm.score_string( "TTTT" ) ).all()
3
Example 42
Project: gala Source File: test_all_builtin.py
def test_against_triaxial(self):
other = LeeSutoTriaxialNFWPotential(units=galactic,
v_c=0.35, r_s=12.,
a=1., b=1., c=1.)
v1 = other.value(self.w0[:3])
v2 = self.potential.value(self.w0[:3])
assert np.allclose(v1.value,v2.value)
a1 = other.gradient(self.w0[:3])
a2 = self.potential.gradient(self.w0[:3])
assert np.allclose(a1.value,a2.value)
3
Example 43
Project: calliope Source File: test_io.py
def verify_solution_integrity(model_solution, solution_from_disk, tempdir):
# Check whether the two are the same
np.allclose(model_solution['e_cap'], solution_from_disk['e_cap'])
# Check that config AttrDict has been deserialized
assert(solution_from_disk.attrs['config_run'].output.path == tempdir)
3
Example 44
Project: hickle Source File: test_hickle.py
def test_legacy_hickles():
try:
a = load("hickle_1_1_0.hkl")
b = load("hickle_1_3_0.hkl")
import h5py
d = h5py.File("hickle_1_1_0.hkl")["data"]["a"][:]
d2 = h5py.File("hickle_1_3_0.hkl")["data"]["a"][:]
assert np.allclose(d, a["a"])
assert np.allclose(d2, b["a"])
except IOError:
# For travis-CI
a = load("tests/hickle_1_1_0.hkl")
b = load("tests/hickle_1_3_0.hkl")
print a
print b
3
Example 45
Project: abstract_rendering Source File: fast_project.py
def report_diffs(a, b, name):
last_dim = a.shape[1]
if not np.allclose(a, b):
for i in range(1, last_dim):
if not np.allclose(a[:,i], b[:,i]):
print('%s::%d fails \nc:\n%s != %s\n' %
(name, i, str(a[:,i]), str(b[:,i])))
3
Example 46
Project: pysb Source File: test_simulator_scipy.py
def test_y0_as_list(self):
"""Test y0 with list of initial conditions"""
# Test the initials getter method before anything is changed
assert np.allclose(self.sim.initials[0:3],
[ic[1].value for ic in
self.model.initial_conditions])
initials = [10, 20, 0, 0]
simres = self.sim.run(initials=initials)
assert np.allclose(self.sim.initials, initials)
assert np.allclose(simres.observables['A_free'][0], 10)
3
Example 47
Project: SERT Source File: query.py
def compute_normalised_entropy(distribution, base=2):
assert distribution.ndim == 2
assert np.allclose(distribution.sum(axis=1), 1.0)
entropies = [
math_utils.entropy(distribution[i, :], base=base, normalize=True)
for i in range(distribution.shape[0])]
return entropies
3
Example 48
Project: scikit-image Source File: test_warps.py
def test_warp_identity():
img = img_as_float(rgb2gray(data.astronaut()))
assert len(img.shape) == 2
assert np.allclose(img, warp(img, AffineTransform(rotation=0)))
assert not np.allclose(img, warp(img, AffineTransform(rotation=0.1)))
rgb_img = np.transpose(np.asarray([img, np.zeros_like(img), img]),
(1, 2, 0))
warped_rgb_img = warp(rgb_img, AffineTransform(rotation=0.1))
assert np.allclose(rgb_img, warp(rgb_img, AffineTransform(rotation=0)))
assert not np.allclose(rgb_img, warped_rgb_img)
# assert no cross-talk between bands
assert np.all(0 == warped_rgb_img[:, :, 1])
3
Example 49
Project: thunder Source File: test_base.py
def test_repartition(eng):
if eng is not None:
data = images.fromlist([array([1, 1]), array([2, 2]), array([3, 3]), array([4, 4]),
array([5, 5]), array([6, 6]), array([7, 7]), array([8, 8]),
array([9, 9]), array([10, 10]), array([11, 11]), array([12, 12])],
engine=eng, npartitions=10)
assert allclose(data.first(), array([1, 1]))
assert isinstance(data.first(), (ndarray, generic))
data = data.repartition(3)
assert allclose(data.first(), array([1, 1]))
data = series.fromlist([array([1, 1]), array([2, 2]), array([3, 3]), array([4, 4]),
array([5, 5]), array([6, 6]), array([7, 7]), array([8, 8]),
array([9, 9]), array([10, 10]), array([11, 11]), array([12, 12])],
engine=eng, npartitions=10)
assert allclose(data.first(), array([1, 1]))
data = data.repartition(3)
assert allclose(data.first(), array([1, 1]))
assert isinstance(data.first(), (ndarray, generic))
3
Example 50
def test_allow_short(self):
returns, cov_mat, avg_rets = create_test_data()
calc_weights = pfopt.min_var_portfolio(cov_mat, allow_short=True).values
exp_weights = [0.29428401463312454, 0.19221716939564482, 0.13820233202108606,
0.20879490895467365, 0.16650157499547097]
self.assertTrue(np.allclose(calc_weights, exp_weights))