EvaluationSpace1D¶

class sherpa.models.regrid.EvaluationSpace1D(x=None, xhi=None)[source] [edit on github]¶

Bases: object

Class for 1D Evaluation Spaces. An Evaluation Space is a set of data axes representing the data space over which a model can be evaluated.

A 1D Evaluation Space has only one axis.

Attributes Summary

`end`	The end 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?
`midpoint_grid`	Return a single array representing the dataset.
`start`	The start of the dataset.

Methods Summary

`join`(other)	Join this dataset with another one.
`overlaps`(other)	Check if this evaluation space overlaps with another :param other: :type other: EvaluationSpace1D
`zeros_like`()	Utility function that returns an array of zeros that has the same shape as the dataset.

Attributes Documentation

end¶

The end of the dataset.

Returns:	The end of the x axis array
Return type:	number

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.

Returns:	A tuple representing the x axis. The tuple will contain two arrays if the dataset is integrated, one otherwise.
Return type:	tuple

is_ascending¶

Is the dataset ascending?

Returns:	True if the x axis is ascending, False otherwise.
Return type:	bool

is_empty¶

Is the dataset empty?

Returns:	True if the x axis is empty, False otherwise
Return type:	bool

is_integrated¶

Is the grid integrated?

Returns:	True if the x axis is integrated, False otherwise.
Return type:	bool

midpoint_grid¶

Return a single array representing the dataset.

Returns:	Return the average point of the bins of integrated axes, for each bin, or the non-integrated x axis array.
Return type:	array

start¶

The start of the dataset.

Returns:	The start of the x axis array
Return type:	number

Methods Documentation

join(other)[source] [edit on github]¶

Join this dataset with another one. The axes are sorted, unique elements are selected and then concatenated. The selection of unique elements is required to make sure Sherpa’s interpolators can deal with the resulting dataset’s space.

Parameters:	other (EvaluationSpace1D) – The dataset to join with self.
Returns:
Return type:	EvaluationSpace1D

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

Check if this evaluation space overlaps with another :param other: :type other: EvaluationSpace1D

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