grid = nd_grid()
creates an instance which will return a mesh-grid when indexed. The dimension and number of the output arrays are equal to the number of indexing dimensions. If the step length is not a complex number, then the stop is not inclusive.
However, if the step length is a complex number (e.g. 5j), then the integer part of its magnitude is interpreted as specifying the number of points to create between the start and stop values, where the stop value is inclusive.
If instantiated with an argument of sparse=True
, the mesh-grid is open (or not fleshed out) so that only one-dimension of each returned argument is greater than 1.
Two instances of nd_grid
are made available in the NumPy namespace, :None:None:`mgrid` and :None:None:`ogrid`, approximately defined as:
mgrid = nd_grid(sparse=False) ogrid = nd_grid(sparse=True)
Users should use these pre-defined instances instead of using nd_grid
directly.
Whether the grid is sparse or not. Default is False.
Construct a multi-dimensional "meshgrid".
The following pages refer to to this document either explicitly or contain code examples using this.
numpy.lib.index_tricks.nd_grid
numpy.lib.index_tricks.OGridClass
numpy.lib.index_tricks.MGridClass
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