AffineTransformation2D#
- class astropy.modeling.projections.AffineTransformation2D(matrix=Parameter('matrix', value=[[1. 0.] [0. 1.]]), translation=Parameter('translation', value=[0. 0.]), **kwargs)[source]#
 Bases:
ModelPerform an affine transformation in 2 dimensions.
- Parameters:
 - matrix
array A 2x2 matrix specifying the linear transformation to apply to the inputs
- translation
array A 2D vector (given as either a 2x1 or 1x2 array) specifying a translation to apply to the inputs
- matrix
 
Attributes Summary
This property is used to indicate what units or sets of units the evaluate method expects, and returns a dictionary mapping inputs to units (or
Noneif any units are accepted).Names of the parameters that describe models of this type.
Methods Summary
__call__(*inputs[, model_set_axis, ...])Evaluate this model using the given input(s) and the parameter values that were specified when the model was instantiated.
evaluate(x, y, matrix, translation)Apply the transformation to a set of 2D Cartesian coordinates given as two lists--one for the x coordinates and one for a y coordinates--or a single coordinate pair.
Attributes Documentation
- input_units#
 
- matrix = Parameter('matrix', value=[[1. 0.] [0. 1.]])#
 
- n_inputs = 2#
 
- n_outputs = 2#
 
- param_names = ('matrix', 'translation')#
 Names of the parameters that describe models of this type.
The parameters in this tuple are in the same order they should be passed in when initializing a model of a specific type. Some types of models, such as polynomial models, have a different number of parameters depending on some other property of the model, such as the degree.
When defining a custom model class the value of this attribute is automatically set by the
Parameterattributes defined in the class body.
- standard_broadcasting = False#
 
- translation = Parameter('translation', value=[0. 0.])#
 
Methods Documentation
- __call__(*inputs, model_set_axis=None, with_bounding_box=False, fill_value=nan, equivalencies=None, inputs_map=None, **new_inputs)#
 Evaluate this model using the given input(s) and the parameter values that were specified when the model was instantiated.