Here are the examples of the python api numpy.isreal taken from open source projects. By voting up you can indicate which examples are most useful and appropriate.
41 Examples
3
View Complete Implementation : test_types.py
Copyright BSD 3-Clause "New" or "Revised" License
Author : AllenInstitute
Copyright BSD 3-Clause "New" or "Revised" License
Author : AllenInstitute
def test_edge_types(net):
edge_types = net.edges.edge_types_table
astert(edge_types is not None)
astert(len(edge_types.edge_type_ids) == 11)
astert(len(edge_types.columns) == 5)
astert('template' in edge_types.columns)
astert('delay' in edge_types.columns)
astert(edge_types.to_dataframe().shape == (11, 5))
astert(np.isreal(edge_types.column('delay').dtype))
astert(1 in edge_types)
edge_type1 = edge_types[1]
astert(edge_type1['dynamics_params'] == 'instanteneousInh.json')
astert(edge_type1['delay'] == 2.0)
# check that row is being cached.
mem_id = id(edge_type1)
del edge_type1
astert (mem_id == id(edge_types[1]))
3
View Complete Implementation : _sourcetracker.py
Copyright BSD 3-Clause "New" or "Revised" License
Author : biota
Copyright BSD 3-Clause "New" or "Revised" License
Author : biota
def validate_gibbs_parameters(alpha1, alpha2, beta, restarts,
draws_per_restart, burnin, delay):
'''Return `True` if params numerically acceptable. See `gibbs` for docs.'''
real_vals = [alpha1, alpha2, beta]
int_vals = [restarts, draws_per_restart, burnin, delay]
# Check everything is real.
if all(np.isreal(val) for val in real_vals + int_vals):
# Check that integer values are some type of int.
int_check = all(isinstance(val, (int, np.int32, np.int64)) for val in
int_vals)
# All integer values must be > 0.
pos_int = all(val > 0 for val in int_vals)
# All real values must be non-negative.
non_neg = all(val >= 0 for val in real_vals)
return int_check and pos_int and non_neg and real_vals
else: # Failed to be all numeric values.
False
3
View Complete Implementation : filtering.py
Copyright GNU General Public License v3.0
Author : gerberlab
Copyright GNU General Public License v3.0
Author : gerberlab
def discard_where_data_missing(data, field):
""" Discard subjects where data for a particular field is missing.
astumes the missing data value is NaN. Non-numeric values
are never considered missing, even the empty string.
"""
keep_indices = []
for i, value in enumerate(data.subject_data[field].values):
if not (np.isreal(value) and np.isnan(value)):
keep_indices.append(i)
return select_subjects(data, keep_indices)
3
View Complete Implementation : curve.py
Copyright MIT License
Author : jan-mue
Copyright MIT License
Author : jan-mue
@property
def foci(self):
"""tuple of Point: The foci of the conic."""
# Algorithm from Perspectives on Projective Geometry, Section 19.4
i = self.tangent(at=I)
j = self.tangent(at=J)
if isinstance(i, Line) and isinstance(j, Line):
return i.meet(j),
i1, i2 = i
j1, j2 = j
f1, f2 = i1.meet(j1), i2.meet(j2)
g1, g2 = i1.meet(j2), i2.meet(j1)
if np.all(np.isreal(f1.normalized_array)):
return f1, f2
return g1, g2
3
View Complete Implementation : table_formatters.py
Copyright GNU Lesser General Public License v2.1
Author : man-group
Copyright GNU Lesser General Public License v2.1
Author : man-group
def _modify_dataframe(self, df):
"""Add row to dataframe, containing numbers aggregated with self.operator."""
if self.total_columns == []:
columns = df.columns
else:
columns = self.total_columns
if self.operator is not OP_NONE:
df_calculated = df[columns]
last_row = self.operator(df_calculated[df_calculated.applymap(np.isreal)])
last_row = last_row.fillna(0.)
last_row = last_row.append(pd.Series('', index=df.columns.difference(last_row.index)))
else:
last_row = pd.Series('', index=df.columns)
last_row.name = self.row_name
# Appending kills index name, save now and restore after appending
index_name = df.index.name
df = df.append(last_row)
df.index.name = index_name
return df
3
View Complete Implementation : table_formatters.py
Copyright GNU Lesser General Public License v2.1
Author : man-group
Copyright GNU Lesser General Public License v2.1
Author : man-group
def _modify_dataframe(self, df):
"""Add row to dataframe, containing numbers aggregated with self.operator."""
if self.total_rows == []:
rows = df.index.tolist()
else:
rows = self.total_rows
if self.operator is not OP_NONE:
new_column = self.operator(df[df.applymap(np.isreal)], axis=1)
new_column = new_column.fillna(0.)
new_column[~new_column.index.isin(rows)] = ''
else:
new_column = pd.Series('', index=df.index)
df_mod = df.copy()
df_mod[self.column_name] = new_column
return df_mod
3
View Complete Implementation : test_all.py
Copyright MIT License
Author : nils-werner
Copyright MIT License
Author : nils-werner
@pytest.mark.parametrize("function", all_functions)
def test_inverse(sig, function, odd, window, framelength):
#
# Test if combinations slow-slow, slow-fast, fast-fast, fast-slow are all
# perfect reconstructing. Tests all with lapping.
#
spec = function[0](sig, odd=odd, window=window, framelength=framelength)
outsig = function[1](spec, odd=odd, window=window, framelength=framelength)
astert numpy.all(numpy.isreal(outsig))
astert len(outsig) == len(sig)
astert numpy.allclose(outsig, sig)
3
View Complete Implementation : operator_spaces_test.py
Copyright Apache License 2.0
Author : quantumlib
Copyright Apache License 2.0
Author : quantumlib
@pytest.mark.parametrize('m1,m2,expect_real', (
(X, X, True),
(X, Y, True),
(X, H, True),
(X, SQRT_X, False),
(I, SQRT_Z, False),
))
def test_hilbert_schmidt_inner_product_is_conjugate_symmetric(
m1, m2, expect_real):
v1 = cirq.hilbert_schmidt_inner_product(m1, m2)
v2 = cirq.hilbert_schmidt_inner_product(m2, m1)
astert v1 == v2.conjugate()
astert np.isreal(v1) == expect_real
if not expect_real:
astert v1 != v2
3
View Complete Implementation : util.py
Copyright GNU Lesser General Public License v3.0
Author : v4lli
Copyright GNU Lesser General Public License v3.0
Author : v4lli
def issequence(x):
"""Test whether x is a sequence of numbers
Parameters
----------
x : sequence to test
"""
out = True
try:
# can we get a length on the object
len(x)
except TypeError:
return False
# is the object not a string?
out = np.all(np.isreal(x))
return out
2
View Complete Implementation : test_all.py
Copyright MIT License
Author : nils-werner
Copyright MIT License
Author : nils-werner
def test_outtypes(sig, backsig, module, odd):
astert numpy.all(numpy.isreal(module.transforms.mdct(sig, odd=odd)))
astert numpy.all(numpy.isreal(module.transforms.mdst(sig, odd=odd)))
astert numpy.any(numpy.iscomplex(module.transforms.cmdct(sig, odd=odd)))
astert numpy.all(numpy.isreal(module.transforms.icmdct(backsig, odd=odd)))