EvaluationSpace2D

class sherpa.models.regrid.EvaluationSpace2D(x=None, y=None, xhi=None, yhi=None)[source] [edit on github]

Bases: object

Class for 2D Evaluation Spaces. An Evaluation Space is a set of data axes representing the data space over which a model can be evaluated.

A 2D Evaluation Space has two axes, x and y.

Attributes Summary

end The enf of the dataset.
grid Return the grid representation of this dataset.
is_ascending Is the dataset ascending?
is_empty Is the dataset empty?
is_integrated Is the grid integrated?
shape
start The start of the dataset.

Methods Summary

overlaps(other) Check if this evaluation space overlaps with another Note that this is more stringent for 2D, as the boundaries need to coincide in this case.
zeros_like() Utility function that returns an array of zeros that has the same shape as the dataset.

Attributes Documentation

end

The enf of the dataset.

Returns:The end of the x and y axis arrays, respectively
Return type:tuple
grid

Return the grid representation of this dataset. The grid is always a tuple, even if the dataset is 1-D and not integrated. This is due to the existing architecture of Sherpa’s model classes and the fact that there is no signature difference among 1-D and 2-D models, as 1-D models can receive 1 or 2 arrays and 2-D models can receive 2 or 4 arrays.

The x and y arrays in the grid are one-dimentional representations of the meshgrid obtained from the x and y axis arrays, as in numpy.meshgrid(x, y)[0].ravel()

Returns:A tuple representing the x and y axes. The tuple will contain four arrays if the dataset is integrated, two otherwise.
Return type:tuple
is_ascending

Is the dataset ascending?

Returns:True if the axis is ascending, False otherwise, for the x and y axes respectively
Return type:tuple(bool)
is_empty

Is the dataset empty?

Returns:True if the x axis or y axis are empty, False otherwise
Return type:bool
is_integrated

Is the grid integrated?

Returns:True if the axes are integrated, False otherwise.
Return type:bool
shape
start

The start of the dataset.

Returns:The start of the x and y axis arrays, respectively
Return type:tuple

Methods Documentation

overlaps(other)[source] [edit on github]

Check if this evaluation space overlaps with another Note that this is more stringent for 2D, as the boundaries need to coincide in this case.

Parameters:other (EvaluationSpace2D) –
Returns:True if they overlap, False if not
Return type:bool
zeros_like()[source] [edit on github]

Utility function that returns an array of zeros that has the same shape as the dataset.

Returns:
Return type:array