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Creation | np.meshgrid()

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Method:

np.meshgrid(xi, copy=True, sparse=False, indexing='xy'*)

Generates coordinate matrices from coordinate vectors.

Returns:

(np.ndarray¹, np.ndarray² ..., np.ndarrayⁿ)

Parameters:

xi: array-like*-

One or more 1D arrays representing the coordinates.

import numpy as np
x = np.array([1, 2, 3])
y = np.array([4, 5])
a, b = np.meshgrid(x, y)
print(a)
print(b)
'''
Output:
[[1 2 3]
 [1 2 3]]
[[4 4 4]
 [5 5 5]]
'''

copy: (True or False), Optional-

If True (default), return copies of the arrays. If False, return views. Please refer to np.array(copy=) for a better explnation along with examples.

sparse: (True or False), Optional-

If True, returns a sparse grid (default False).

sparse = False (default) +

A regular array is generated from coordinate vectors.

import numpy as np
x = np.array([1, 2, 3])
y = np.array([4, 5])
a, b = np.meshgrid(x, y, sparse=False)
print(a)
print(b)
'''
Output:
[[1 2 3]
 [1 2 3]]
[[4 4 4]
 [5 5 5]]
'''

sparse = True (default) +

A sparse matrix is returned from coordinate vectors.

import numpy as np
x = np.array([1, 2, 3])
y = np.array([4, 5])
a, b = np.meshgrid(x, y, sparse=True)
print(a)
print(b)
'''
Output:
[[1 2 3]]
[[4]
 [5]]
'''

indexing: ('xy' or 'ij') Optional-

Determines the ordering of the indices.

indexing = 'xy' (default) +

'xy' for matrix indexing.

import numpy as np
x = np.array([1, 2, 3])
y = np.array([4, 5])
a, b = np.meshgrid(x, y, indexing='xy')
print(a)
print(b)
'''
Output:
[[1 2 3]
 [1 2 3]]
[[4 4 4]
 [5 5 5]]
'''

indexing = 'ij' +

'ij' for Cartesian indexing.

import numpy as np
x = np.array([1, 2, 3])
y = np.array([4, 5])
a, b = np.meshgrid(x, y, indexing='ij')
print(a)
print(b)
'''
Output:
[[1 1]
 [2 2]
 [3 3]]
[[4 5]
 [4 5]
 [4 5]]
'''

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Creation | np.meshgrid()

Method:

np.meshgrid(*xi, copy=True, sparse=False, indexing='xy')

Generates coordinate matrices from coordinate vectors.

Returns:

(np.ndarray1, np.ndarray2 ..., np.ndarrayn)

Parameters:

*xi: array-like-

copy: (True or False), Optional-

sparse: (True or False), Optional-

sparse = False (default) +

sparse = True (default) +

indexing: ('xy' or 'ij') Optional-

indexing = 'xy' (default) +

indexing = 'ij' +

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np.meshgrid(xi, copy=True, sparse=False, indexing='xy'*)

(np.ndarray¹, np.ndarray² ..., np.ndarrayⁿ)

xi: array-like*-