numpy.ndarray.flat() in Python
numpy.ndarray.flat() in Python
The numpy.ndarray.flat() returns a 1-D iterator over the array. This function is not a subclass of, Python’s built-in iterator object, otherwise it will act the same as a numpy.flatiter instance.
Syntax
ndarray.flat()
Parameter
NA
Return
This function returns a 1-D iteration of an array.
Example 1
# Python Program explaining # numpy.ndarray.flat() function import numpy as np # 1D iteration of 2D array arr = np.arange(20).reshape(4, 5) print("2D array : \n",arr ) # Using flat() to return 1D iterator over range print("Using Array: \n", arr.flat[2:8]) # Using flat() for 1D repersented array print("1D array: \n ->", arr.flat[3:15])
Output
2D array : [[ 0 1 2 3 4] [ 5 6 7 8 9] [10 11 12 13 14] [15 16 17 18 19]] Using Array: [2 3 4 5 6 7] 1D array: -> [ 3 4 5 6 7 8 9 10 11 12 13 14]
Example 2
# Python Program explaining # numpy.ndarray.flat() function import numpy as np # 1D iteration of 2D array array = np.arange(20).reshape(4, 5) print("2D array : \n",array ) # All values set to 1 array.flat = 1 print("Values set to 1 : \n", array) array.flat[3:6] = 8 array.flat[8:10] = 9 print("Altering the values in a range : \n", array)
Output
2D array : [[ 0 1 2 3 4] [ 5 6 7 8 9] [10 11 12 13 14] [15 16 17 18 19]] Values set to 1 : [[1 1 1 1 1] [1 1 1 1 1] [1 1 1 1 1] [1 1 1 1 1]] Altering the values in a range : [[1 1 1 8 8] [8 1 1 9 9] [1 1 1 1 1] [1 1 1 1 1]]