def convolve_models(model, kernel, mode='convolve_fft', **kwargs):
"""
Convolve two models using `~astropy.convolution.convolve_fft`.
Parameters
----------
model : `~astropy.modeling.core.Model`
Functional model
kernel : `~astropy.modeling.core.Model`
Convolution kernel
mode : str
Keyword representing which function to use for convolution.
* 'convolve_fft' : use `~astropy.convolution.convolve_fft` function.
* 'convolve' : use `~astropy.convolution.convolve`.
**kwargs : dict
Keyword arguments to me passed either to `~astropy.convolution.convolve`
or `~astropy.convolution.convolve_fft` depending on ``mode``.
Returns
-------
default : `~astropy.modeling.core.CompoundModel`
Convolved model
"""
if mode == 'convolve_fft':
operator = SPECIAL_OPERATORS.add('convolve_fft', partial(convolve_fft, **kwargs))
elif mode == 'convolve':
operator = SPECIAL_OPERATORS.add('convolve', partial(convolve, **kwargs))
else:
raise ValueError(f'Mode {mode} is not supported.')
return CompoundModel(operator, model, kernel)
def test_fix_inputs_invalid():
g1 = Gaussian2D(1, 0, 0, 1, 2)
with pytest.raises(ValueError):
fix_inputs(g1, {'x0': 0, 0: 0})
with pytest.raises(ValueError):
fix_inputs(g1, (0, 1))
with pytest.raises(ValueError):
fix_inputs(g1, {3: 2})
with pytest.raises(ValueError):
fix_inputs(g1, {np.int32(3): 2})
with pytest.raises(ValueError):
fix_inputs(g1, {np.int64(3): 2})
with pytest.raises(ValueError):
fix_inputs(g1, {'w': 2})
with pytest.raises(ModelDefinitionError):
CompoundModel('#', g1, g1)
with pytest.raises(ValueError):
gg1 = fix_inputs(g1, {0: 1})
gg1(2, y=2)
with pytest.raises(ValueError):
gg1 = fix_inputs(g1, {np.int32(0): 1})
gg1(2, y=2)
with pytest.raises(ValueError):
gg1 = fix_inputs(g1, {np.int64(0): 1})
gg1(2, y=2)
def from_tree_tagged(cls, node, ctx):
tag = node._tag[node._tag.rfind('/') + 1:]
tag = tag[:tag.rfind('-')]
oper = _tag_to_method_mapping[tag]
left = node['forward'][0]
if not isinstance(left, Model):
raise TypeError(f"Unknown model type '{node['forward'][0]._tag}'")
right = node['forward'][1]
if (not isinstance(right, Model)
and not (oper == 'fix_inputs' and isinstance(right, dict))):
raise TypeError(f"Unknown model type '{node['forward'][1]._tag}'")
if oper == 'fix_inputs':
right = dict(zip(right['keys'], right['values']))
model = CompoundModel('fix_inputs', left, right)
else:
model = getattr(left, oper)(right)
return cls._from_tree_base_transform_members(model, node, ctx)
def from_tree_transform(self, node):
tag = node._tag[node._tag.rfind('/') + 1:]
tag = tag[:tag.rfind('-')]
oper = _tag_to_method_mapping[tag]
left = node['forward'][0]
if not isinstance(left, Model):
raise TypeError("Unknown model type '{0}'".format(
node['forward'][0]._tag))
right = node['forward'][1]
if (not isinstance(right, Model)
and not (oper == 'fix_inputs' and isinstance(right, dict))):
raise TypeError("Unknown model type '{0}'".format(
node['forward'][1]._tag))
if oper == 'fix_inputs':
right = dict(zip(right['keys'], right['values']))
model = CompoundModel('fix_inputs', left, right)
else:
model = getattr(left, oper)(right)
return model
def from_tree_tagged(cls, node, ctx):
tag = node._tag[node._tag.rfind('/') + 1:]
tag = tag[:tag.rfind('-')]
oper = _tag_to_method_mapping[tag]
left = yamlutil.tagged_tree_to_custom_tree(node['forward'][0], ctx)
if not isinstance(left, Model):
raise TypeError("Unknown model type '{0}'".format(
node['forward'][0]._tag))
right = yamlutil.tagged_tree_to_custom_tree(node['forward'][1], ctx)
if not isinstance(right, Model) and \
not (oper == 'fix_inputs' and isinstance(right, dict)):
raise TypeError("Unknown model type '{0}'".format(
node['forward'][1]._tag))
if oper == 'fix_inputs':
right = dict(zip(right['keys'], right['values']))
model = CompoundModel('fix_inputs', left, right)
else:
model = getattr(left, oper)(right)
model = cls._from_tree_base_transform_members(model, node, ctx)
model.map_parameters()
return model
def from_yaml_tree_transform(self, node, tag, ctx):
from astropy.modeling.core import Model, CompoundModel
oper = _TAG_NAME_TO_MODEL_METHOD[tag.rsplit("/", 1)[-1].rsplit("-", 1)[0]]
left = node["forward"][0]
if not isinstance(left, Model):
raise TypeError("Unknown model type '{0}'".format(
node["forward"][0]._tag))
right = node["forward"][1]
if (not isinstance(right, Model) and
not (oper == "fix_inputs" and isinstance(right, dict))):
raise TypeError("Unknown model type '{0}'".format(
node["forward"][1]._tag))
if oper == "fix_inputs":
right = dict(zip(right["keys"], right["values"]))
model = CompoundModel("fix_inputs", left, right)
else:
model = getattr(left, oper)(right)
return model