classmatplotlib.transforms.BlendedGenericTransform(x_transform, y_transform, **kwargs)[source]
 
Bases: matplotlib.transforms._BlendedMixin, matplotlib.transforms.Transform A "blended" transform uses one transform for the x-direction, and another transform for the y-direction. This "generic" version can handle any given child transform in the x- and y-directions. Create a new "blended" transform using x_transform to transform the x-axis and y_transform to transform the y-axis. You will generally not call this constructor directly but use the blended_transform_factory function instead, which can determine automatically which kind of blended transform to create.   __init__(x_transform, y_transform, **kwargs)[source]
 
Create a new "blended" transform using x_transform to transform the x-axis and y_transform to transform the y-axis. You will generally not call this constructor directly but use the blended_transform_factory function instead, which can determine automatically which kind of blended transform to create. 
   __module__='matplotlib.transforms'

   contains_branch(other)[source]
 
Return whether the given transform is a sub-tree of this transform. This routine uses transform equality to identify sub-trees, therefore in many situations it is object id which will be used. For the case where the given transform represents the whole of this transform, returns True. 
   propertydepth
 
Return the number of transforms which have been chained together to form this Transform instance.  Note For the special case of a Composite transform, the maximum depth of the two is returned.  
   frozen()[source]
 
Return a frozen copy of this transform node. The frozen copy will not be updated when its children change. Useful for storing a previously known state of a transform where copy.deepcopy() might normally be used. 
   get_affine()[source]
 
Get the affine part of this transform. 
   propertyhas_inverse
 
bool(x) -> bool Returns True when the argument x is true, False otherwise. The builtins True and False are the only two instances of the class bool. The class bool is a subclass of the class int, and cannot be subclassed. 
   input_dims=2
 
The number of input dimensions of this transform. Must be overridden (with integers) in the subclass. 
   inverted()[source]
 
Return the corresponding inverse transformation. It holds x == self.inverted().transform(self.transform(x)). The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy. 
   propertyis_affine
 
bool(x) -> bool Returns True when the argument x is true, False otherwise. The builtins True and False are the only two instances of the class bool. The class bool is a subclass of the class int, and cannot be subclassed. 
   is_separable=True
 
True if this transform is separable in the x- and y- dimensions. 
   output_dims=2
 
The number of output dimensions of this transform. Must be overridden (with integers) in the subclass. 
   pass_through=True
 
If pass_through is True, all ancestors will always be invalidated, even if 'self' is already invalid. 
   transform_non_affine(points)[source]
 
Apply only the non-affine part of this transformation. transform(values) is always equivalent to transform_affine(transform_non_affine(values)). In non-affine transformations, this is generally equivalent to transform(values). In affine transformations, this is always a no-op.  Parameters 
 
valuesarray


The input values as NumPy array of length input_dims or shape (N x input_dims).    Returns 
 array

The output values as NumPy array of length input_dims or shape (N x output_dims), depending on the input.