The numpy.meshgrid() function in Python is used to return the coordinate matrices from given coordinate vectors.
numpy.meshgrid(*xi, copy=True, sparse=False, indexing='xy')
The numpy.meshgrid() function takes the following parameter values:
x1, x2,..., xn: these represent the 1-D arrays, which also represent the coordinates of a grid.indexing: this represents the default, Cartesian (xy), or matrix (ij) indexing of the output. This is optional.sparse: this takes a Boolean value. If True, the shape of the returned coordinate array for dimension i is reduced from (N1, ..., Ni, ..., Nn) to (1, ..., 1, Ni, 1, ..., 1). This is optional.copy: this takes a Boolean value. If False, a view into the original arrays are returned in order to conserve memory. The default value is False. This is optional.The numpy.meshgrid() function returns X1, X2,...XN arrays.
import numpy as np# creating the array_like objectsnx, ny = (2, 3)# implementing the linespace functionx = np.linspace(0, 1, nx)y = np.linspace(0, 1, ny)xv, yv = np.meshgrid(x, y, copy = True, sparse = False, indexing ='xy' )print(xv)print(yv)
Here is a line-by-line explanation of the code above:
numpy library.nx and ny.linspace() function, we return evenly spaced numbers over a specified interval starting from 0 to 1 for the nx and ny array-like objects.meshgrid() function on the matrices xv and yvxv and yv.