EvaluationSpace2D¶
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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
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end
¶ The enf of the dataset.
Returns: The end of the x and y axis arrays, respectively Return type: tuple
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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
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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)
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is_empty
¶ Is the dataset empty?
Returns: True if the x axis or y axis are empty, False otherwise Return type: bool
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is_integrated
¶ Is the grid integrated?
Returns: True if the axes are integrated, False otherwise. Return type: bool
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shape
¶
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start
¶ The start of the dataset.
Returns: The start of the x and y axis arrays, respectively Return type: tuple
Methods Documentation
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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
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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
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