def test_generate_multiple(tmpdir, mock_generate):
spec = ScalarPotentialSpec(16, 2, correlation.IsotropicGaussian(0.1), 1.0)
spec.create = mock.Mock(side_effect=spec.create)
for p_file in generate_multiple(spec,
5,
options=None,
work_dir=str(tmpdir)):
spec.create.assert_called_once_with(p_file.file_name, options={})
spec.create.reset_mock()
assert p_file.file_name.startswith(str(tmpdir))
assert mock_generate.call_count() == 5
def test_scalar_potential_generate(tmpdir, mock_generate):
cor = correlation.IsotropicGaussian(1.0)
sp = ScalarPotentialSpec((25, 25), None, cor, 1.5)
target_file = str(tmpdir.join("target_file"))
result = sp.create(target_file, 25)
mock_generate.assert_called_once_with(target_file, 2, (25, 25), cor, 1.5,
25)
assert result.file_name == target_file
with mock.patch("branchedflowsim.potgen.generate") as potgen:
result = sp.create(target_file, 25, {"option": "value"})
potgen.assert_called_with(target_file,
2, (25, 25),
cor,
1.5,
25,
option="value")
assert result.file_name == target_file
def test_scalar_potential_spec():
cor = correlation.IsotropicGaussian(1.0)
sp = ScalarPotentialSpec((25, 25), None, cor, 1.5)
assert sp.shape == (25, 25)
assert sp.dimension == 2
assert sp.support == pytest.approx(np.ones(2))
assert sp.strength == 1.5
assert sp.correlation == cor
sp = ScalarPotentialSpec(12, 3, cor, 1.5)
assert sp.shape == (12, 12, 12)
assert sp.dimension == 3
assert sp.support == pytest.approx(np.ones(3))
assert sp.strength == 1.5
assert sp.correlation == cor
with pytest.raises(ValueError):
sp = ScalarPotentialSpec((25, 25), 3, cor, 1.5)
sp = ScalarPotentialSpec((25, 25), None, cor, 1.5)
assert sp.dimension == 2
def test_iso_gauss():
c = correlation.IsotropicGaussian(0.5)
assert c.args == ["-c", "gauss", "-l", "0.5"]
def test_trafo():
c = correlation.Transformed(correlation.AnisotropicGaussian(0.5, [1, 2]),
[1, 0, 0, 1])
assert type(c.base_correlation) == correlation.AnisotropicGaussian
assert c.transform == pytest.approx([1, 0, 0, 1])
assert c.args == [
"-c", "gauss", "1", "2", "--trafo", '"1 0 0 1"', "-l", "0.5"
]
correlations = [
correlation.Correlation("gauss", 0.5),
correlation.Parametrized("gauss", 0.5, "param"),
correlation.IsotropicGaussian(0.5),
correlation.AnisotropicGaussian(0.5, [1.0, 2.0, 2.0]),
correlation.CustomScript(0.5, "script",
OrderedDict([("arg", 5), ("param", 8)])),
correlation.Transformed(correlation.AnisotropicGaussian(0.5, [1, 2]),
[1, 0, 0, 1])
]
@pytest.mark.parametrize("corr", correlations)
def test_as_dict_round_trip(corr):
dict_rep = corr.as_dict
reconstructed = correlation.Correlation.from_dict(dict_rep)
assert corr == reconstructed