Numpy Min Max

Python Numpy Max Min
Numpy Min Max Value
Numpy Min Max Average
Numpy Minimum

Overiew:

この記事では「【NumPy入門 np.max】最大値を取り出すnp.max,np.nanmax,np.maximum 」といった内容について、誰でも理解できるように解説します。この記事を読めば、あなたの悩みが解決するだけじゃなく、新たな気付きも発見できることでしょう。お悩みの方はぜひご一読ください。. Numpy.amax Python’s numpy module provides a function to get the maximum value from a Numpy array i.e. Numpy.amax(a, axis=None, out=None, keepdims=, initial=).

The min() and max() functions of numpy.ndarray returns the minimum and maximum values of an ndarray object.

The return value of min() and max() functions is based on the axis specified.

If no axis is specified the value returned is based on all the elements of the array.

Axis of an ndarray is explained in the section cummulative sum and cummulative product functions of ndarray.

Example-ndarray.min(), ndarray.max():

The example provided calls min() and max() functions on ndarray objects four times each.

Once with no axis specified
Thrice with axis values specified - the axis values are 0, 1 and 2.

Python Numpy Max Min

Since the ndarray object is a 3-dimensional array object it has 3 indexes.

The dimension of the ndarray object is given by the tuple (3,3,4).

That is the ndarray object has three 2-dimensional arrays of shape (3,4).

Numpy Min Max Value

# Example Python program for finding the min value along the given axis of an ndarray

# Import numpy module

import numpy as np

# Import standard library module random

import random

# Create a 3-Dimensional ndarray object

array_3d = np.array([[[1,1,1,1],

[2,2,2,2],

[3,3,3,3]],

[[4,4,4,4], Vsco film free download mac.

[5,5,5,5],

[6,6,6,6]],

[[7,7,7,7],

[8,8,8,8],

[9,9,9,9]]]

)

# Print the 3-Dimensional Array

print('Input ndarray:')

print(array_3d)

print('Shape of the ndarray:')

print(array_3d.shape)

print('Number of dimensions/axis of the ndarray:')

print(array_3d.ndim)

# Print the minimum value of the whole array - without considering the axis parameter

print('Minimum value in the whole array:%d'%(array_3d.min()))

# Print the minimum value for axis = 0

print('Minimum value along the axis 0:')

print(array_3d.min(axis=0))

# Print the minimum value for axis = 1

print('Minimum value along the axis 1:')

print(array_3d.min(axis=1))

# Print the minimum value for axis = 2

print('Minimum value along the axis 2:')

print(array_3d.min(axis=2))

# Print the maximum value of the whole array - without considering the axis parameter

print('Maximum value in the whole array:%d'%(array_3d.max()))

# Print the maximum value for axis = 0

print('Maximum value along the axis 0:')

print(array_3d.max(axis=0))

# Print the maximum value for axis = 1

print('Maximum value along the axis 1:')

print(array_3d.max(axis=1))

# Print the maximum value for axis = 2

print('Maximum value along the axis 2:')

print(array_3d.max(axis=2))

Numpy Min Max Average

Output:

Numpy Minimum

Input ndarray:

[[[1 1 1 1]

[2 2 2 2]

[3 3 3 3]]

[[4 4 4 4]

[5 5 5 5]

[6 6 6 6]]

[[7 7 7 7]

[8 8 8 8]

[9 9 9 9]]]

Shape of the ndarray:

(3, 3, 4)

Number of dimensions/axis of the ndarray:

Minimum value in the whole array:1

Minimum value along the axis 0:

[[1 1 1 1]

[2 2 2 2]

[3 3 3 3]]

Minimum value along the axis 1:

[[1 1 1 1]

Download cs go free mac. [4 4 4 4]

[7 7 7 7]]

Minimum value along the axis 2:

[[1 2 3]

[4 5 6]

[7 8 9]]

Maximum value in the whole array:9

Maximum value along the axis 0:

[[7 7 7 7]

[8 8 8 8]

[9 9 9 9]]

Maximum value along the axis 1:

[[3 3 3 3]

[6 6 6 6]

[9 9 9 9]]

Maximum value along the axis 2:

[[1 2 3]

[4 5 6]

[7 8 9]]