microstructpy.geometry.n_sphere.NSphere¶
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class
microstructpy.geometry.n_sphere.NSphere(**kwargs)[source]¶ Bases:
objectAn N-dimensional sphere.
This class represents a generic, n-dimensional sphere. It is defined by a center point and size parameter, which can be either radius or diameter.
If multiple size or position keywords are given, there is no guarantee whhich keywords are used to create the geometry.
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approximate()[source]¶ Approximate the n-sphere with itself
Other geometries can be approximated by a set of circles or spheres. For the n-sphere, this approximation is exact.
Returns: A list containing [(x, y, z, …, r)] Return type: list
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classmethod
best_fit(points)[source]¶ Find n-sphere of best fit for set of points.
This function takes a list of points and computes an n-sphere of best fit, in an algebraic sense. This method was developed using the a published writeup, which was extended from 2D to ND. [1]
Parameters: points (list, numpy.ndarray) – List of points to fit. Returns: An instance of the class that fits the points. Return type: NSphere [1] Circle fitting writup by Randy Bullock, https://dtcenter.org/met/users/docs/write_ups/circle_fit.pdf
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reflect(points)[source]¶ Reflect points across surface.
This function reflects a point or set of points across the surface of the n-sphere. Points at the center of the n-sphere are not reflected.
Parameters: points (list or numpy.ndarray) – Points to reflect. Returns: Reflected points. Return type: numpy.ndarray
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within(points)[source]¶ Test if points are within n-sphere.
This function tests whether a point or set of points are within the n-sphere. For the set of points, a list of booleans is returned to indicate which points are within the n-sphere.
Parameters: points (list or numpy.ndarray) – Point or list of points. Returns: Set to True for points in geometry. Return type: bool or numpy.ndarray
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