scri.plotting

Classes

WaveformTimeScale(axis, **kwargs)

Methods

class scri.plotting.WaveformTimeScale(axis, **kwargs)

Methods

get_transform()	Return the .Transform object associated with this scale.
limit_range_for_scale(vmin, vmax, minpos)	Return the range vmin, vmax, restricted to the domain supported by this scale (if any).
set_default_locators_and_formatters(axis)	Set the locators and formatters of axis to instances suitable for this scale.

InvertedWaveformTimeTransform
WaveformTimeTransform

class InvertedWaveformTimeTransform(merger_stretch, t_initial, t_merger, t_ringdown, t_final)

Attributes:

depth

Return the number of transforms which have been chained together to form this Transform instance.

Methods

contains_branch(other)	Return whether the given transform is a sub-tree of this transform.
contains_branch_seperately(other_transform)	Return whether the given branch is a sub-tree of this transform on each separate dimension.
frozen()	Return a frozen copy of this transform node.
get_affine()	Get the affine part of this transform.
get_matrix()	Get the matrix for the affine part of this transform.
invalidate()	Invalidate this TransformNode and triggers an invalidation of its ancestors.
inverted()	Return the corresponding inverse transformation.
set_children(*children)	Set the children of the transform, to let the invalidation system know which transforms can invalidate this transform.
transform(values)	Apply this transformation on the given array of values.
transform_affine(values)	Apply only the affine part of this transformation on the given array of values.
transform_angles(angles, pts[, radians, pushoff])	Transform a set of angles anchored at specific locations.
transform_bbox(bbox)	Transform the given bounding box.
transform_non_affine(f_a)	Apply only the non-affine part of this transformation.
transform_path(path)	Apply the transform to .Path path, returning a new .Path.
transform_path_affine(path)	Apply the affine part of this transform to .Path path, returning a new .Path.
transform_path_non_affine(path)	Apply the non-affine part of this transform to .Path path, returning a new .Path.
transform_point(point)	Return a transformed point.

has_inverse = True

True if this transform has a corresponding inverse transform.

input_dims = 1

The number of input dimensions of this transform. Must be overridden (with integers) in the subclass.

inverted()

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.

is_separable = True

True if this transform is separable in the x- and y- dimensions.

output_dims = 1

The number of output dimensions of this transform. Must be overridden (with integers) in the subclass.

transform_non_affine(f_a)

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 an array of length input_dims or shape (N, input_dims).

Returns:

array

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

class WaveformTimeTransform(merger_stretch, t_initial, t_merger, t_ringdown, t_final)

Attributes:

depth

Return the number of transforms which have been chained together to form this Transform instance.

Methods

contains_branch(other)	Return whether the given transform is a sub-tree of this transform.
contains_branch_seperately(other_transform)	Return whether the given branch is a sub-tree of this transform on each separate dimension.
frozen()	Return a frozen copy of this transform node.
get_affine()	Get the affine part of this transform.
get_matrix()	Get the matrix for the affine part of this transform.
invalidate()	Invalidate this TransformNode and triggers an invalidation of its ancestors.
inverted()	Return the corresponding inverse transformation.
set_children(*children)	Set the children of the transform, to let the invalidation system know which transforms can invalidate this transform.
transform(values)	Apply this transformation on the given array of values.
transform_affine(values)	Apply only the affine part of this transformation on the given array of values.
transform_angles(angles, pts[, radians, pushoff])	Transform a set of angles anchored at specific locations.
transform_bbox(bbox)	Transform the given bounding box.
transform_non_affine(a)	Apply only the non-affine part of this transformation.
transform_path(path)	Apply the transform to .Path path, returning a new .Path.
transform_path_affine(path)	Apply the affine part of this transform to .Path path, returning a new .Path.
transform_path_non_affine(path)	Apply the non-affine part of this transform to .Path path, returning a new .Path.
transform_point(point)	Return a transformed point.

has_inverse = True

True if this transform has a corresponding inverse transform.

input_dims = 1

The number of input dimensions of this transform. Must be overridden (with integers) in the subclass.

inverted()

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.

is_separable = True

True if this transform is separable in the x- and y- dimensions.

output_dims = 1

The number of output dimensions of this transform. Must be overridden (with integers) in the subclass.

transform_non_affine(a)

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 an array of length input_dims or shape (N, input_dims).

Returns:

array

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

get_transform()

Return the .Transform object associated with this scale.

limit_range_for_scale(vmin, vmax, minpos)

Return the range vmin, vmax, restricted to the domain supported by this scale (if any).

minpos should be the minimum positive value in the data. This is used by log scales to determine a minimum value.

name = 'merger_zoom'

set_default_locators_and_formatters(axis)

Set the locators and formatters of axis to instances suitable for this scale.