I want to check if a numpy array is multidimensional or not?
V = [[ -7.94627203e+01 -1.81562235e+02 -3.05418070e+02 -2.38451033e+02][ 9.43740653e+01 1.69312771e+02 1.68545575e+01 -1.44450299e+02][ 5.61599000e+00 8.76135909e+01 1.18959245e+02 -1.44049237e+02]]
How can I do that in numpy?
Use the .ndim property of the ndarray:
>>> a = np.array([[ -7.94627203e+01, -1.81562235e+02, -3.05418070e+02, -2.38451033e+02],[ 9.43740653e+01, 1.69312771e+02, 1.68545575e+01, -1.44450299e+02],[ 5.61599000e+00, 8.76135909e+01, 1.18959245e+02, -1.44049237e+02]])
>>> a.ndim
2
In some cases, you should also add np.squeeze() to make sure there are no "empty" dimensions
>>> a = np.array([[1,2,3]])
>>> a.ndim
2
>>> a = np.squeeze(a)
>>> a .ndim
1
You can use .shape property too, which gives you a tuple containing the length of each dimension. Therefore, to get the dimension using .shape you could aswell call len() on the resulting tuple:
import numpy as np
a = np.array([1,2,3])
b = np.array([[1,2,3]])
c = np.array([[1,2,3],[2,4,6],[3,6,9]])
print("a={}".format(a))
print("a.shape: {}; len(a.shape): {}".format(a.shape, len(a.shape)))
print("b={}".format(b))
print("b.shape: {}; len(b.shape): {}".format(b.shape, len(b.shape)))
print(c)
print("c.shape: {}; len(c.shape): {}".format(c.shape, len(c.shape)))
Output:
a=[1 2 3]
a.shape: (3,); len(a.shape): 1
b=[[1 2 3]]
b.shape: (1, 3); len(b.shape): 2
[[1 2 3]
[2 4 6]
[3 6 9]]
c.shape: (3, 3); len(c.shape): 2
