如何使用numpy在Python中展平一個矩陣？

In this article, we will show you how to flatten a matrix using the NumPy library in python.

numpy.ndarray.flatten()函數

The numpy module includes a function called numpy.ndarray.flatten() that returns a one-dimensional copy of the array rather than a two-dimensional or multi-dimensional array.

ndarray.flatten(order='C')

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order − 'C', 'F', 'A', 'K' (可選)

• 當我們將排序參數設定為

  'C，'時，陣列會按行主序展平。

• When the 'F' is set, the array is flattened in

  column-major order.

• #只有當 'a' 在記憶體中是Fortran連續的，且順序參數設定為 'A' 時，陣列才會以列主序展開。最終順序為 'K'，以與記憶體中元素出現的順序相同的順序展開數組。此參數預設為 'C'。

Return Value − Returns a flattened 1-D matrix

• 使用import關鍵字，匯入帶有別名(np)的

  numpy模組。

• 使用

  numpy.array()函數（傳回一個ndarray。ndarray是滿足給定要求的陣列物件），透過將2維數組（2行，2列）作為參數傳遞給它來創建一個numpy數組。

• 列印給定的二維矩陣。

• 在輸入矩陣上套用 numpy 模組的

  flatten() 函數（將矩陣壓平為一維） ，將輸入的二維矩陣壓平為一維矩陣。

• 列印輸入矩陣的結果扁平化矩陣。

# importing numpy module with an alias name
import numpy as np

# creating a 2-Dimensional(2x2) numpy matrix
inputMatrix = np.array([[3, 5], [4, 8]])

# printing the input 2D matrix
print("The input numpy matrix:")
print(inputMatrix)

# flattening the 2D matrix to one-dimensional matrix
flattenMatrix = inputMatrix.flatten()

# printing the resultant flattened matrix
print("Resultant flattened matrix:")
print(flattenMatrix)

The input numpy matrix:
[[3 5]
[4 8]]
Resultant flattened matrix:
[3 5 4 8]

• Use the

  numpy.array() function(returns a ndarray. The ndarray is an array object that satisfies the given requirements), for creating a numpy array by passing the 4-Dimensional array (4rows, 4columns) as an argument to it.

• 印出給定的4維矩陣。

• 透過將NumPy陣列的長度與自身相乘來計算矩陣的元素數。這些值表示所需的列數。

• Use the

  reshape() function(reshapes an array without affecting its data) to reshape the array and flatten the input matrix(4D) to a one-dimensional matrix.

• #都
  ##列印輸入矩陣的結果扁平化矩陣。

# importing numpy module with an alias name
import numpy as np

# creating a 4-Dimensional(4x4) numpy matrix
inputMatrix = np.array([[1, 2, 3, 97],
   [4, 5, 6, 98],
   [7, 8, 9, 99],
   [10, 11, 12, 100]])

# Getting the total Number of elements of the matrix
matrixSize = len(inputMatrix) * len(inputMatrix)

# printing the input 4D matrix
print("The input numpy matrix:")
print(inputMatrix)

# reshaping the array and flattening the 4D matrix to a one-dimensional matrix

# here (1,matrixSize(16)) says 1 row and 16 columns(Number of elements)
flattenMatrix= np.reshape(inputMatrix, (1, matrixSize))

# printing the resultant flattened matrix
print("Resultant flattened matrix:")
print(flattenMatrix)

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The input numpy matrix:
[[  1   2   3  97]
 [  4   5   6  98]
 [  7   8   9  99]
 [ 10  11  12 100]]
Resultant flattened matrix:
[[  1   2   3  97   4   5   6  98   7   8   9  99  10  11  12 100]]

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# importing NumPy module with an alias name
import numpy as np

# creating a NumPy matrix (4x4 matrix) using matrix() method
inputMatrix = np.matrix('[11, 1, 8, 2; 11, 3, 9 ,1; 1, 2, 3, 4; 9, 8, 7, 6]')

# printing the input 4D matrix
print("The input numpy matrix:")
print(inputMatrix)

# flattening the 4D matrix to one-dimensional matrix
flattenMatrix = inputMatrix.flatten()

# printing the resultant flattened matrix
print("Resultant flattened matrix:")
print(flattenMatrix)

The input numpy matrix:
[[11  1  8  2]
 [11  3  9  1]
 [ 1  2  3  4]
 [ 9  8  7  6]]
Resultant flattened matrix:
[[11  1  8  2 11  3  9  1  1  2  3  4  9  8  7  6]]

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