20 August 2020
Code
# Import library
import numpy as np
# Create an array
x = np.array([[1,2,3,4],
[11,12,13,14],
[21,22,23,24],
[31,32,33,34]]
)
print('x:\n',x)
print("Shape:", x.shape)
x:
[[ 1 2 3 4]
[11 12 13 14]
[21 22 23 24]
[31 32 33 34]]
Shape: (4, 4)
.
Split with one integer:
Note: Splits array into equal size arrays along the axis. If that is not possible then an Error is raised. Try using np.array_split() listed below in that case.
# Split with one integer
# into equal parts
y0 = np.split(x, 2, axis=0) # integer is '2'
y1 = np.split(x, 2, axis=1) # integer is '2'
# Output
print("Split(x,2, axis=0):")
print(y0)
print(type(y0))
print('y0[0].shape:', y0[0].shape, '\n')
print("Split(x,2, axis=1):")
print(y1)
print(type(y1))
print('y1[0].shape:', y1[0].shape)
Split(x,2, axis=0):
[array([[ 1, 2, 3, 4],
[11, 12, 13, 14]]), array([[21, 22, 23, 24],
[31, 32, 33, 34]])]
<class 'list'>
y0[0].shape: (2, 4)
Split(x,2, axis=1):
[array([[ 1, 2],
[11, 12],
[21, 22],
[31, 32]]), array([[ 3, 4],
[13, 14],
[23, 24],
[33, 34]])]
<class 'list'>
y1[0].shape: (4, 2)
Split with one integer using np.array_split():
Note: Splits array into equal size array if possible, else unequal sizes.
# Using np.array_split()
# Split with one integer
# into equal parts if possible
# else unequal parts. Does not rais an Error
y0 = np.array_split(x, 2, axis=0) # integer is '2'
y1 = np.array_split(x, 2, axis=1) # integer is '2'
# Output
print("Split(x,2, axis=0):")
print(y0)
print(type(y0))
print('y0[0].shape:', y0[0].shape, '\n')
print("Split(x,2, axis=1):")
print(y1)
print(type(y1))
print('y1[0].shape:', y1[0].shape)
Split(x,2, axis=0):
[array([[ 1, 2, 3, 4],
[11, 12, 13, 14]]), array([[21, 22, 23, 24],
[31, 32, 33, 34]])]
<class 'list'>
y0[0].shape: (2, 4)
Split(x,2, axis=1):
[array([[ 1, 2],
[11, 12],
[21, 22],
[31, 32]]), array([[ 3, 4],
[13, 14],
[23, 24],
[33, 34]])]
<class 'list'>
y1[0].shape: (4, 2)
.
Split with 1-D array of sorted integers:
Note: Splits the array at given indices in the 1-D array
# Split with 1-D array of sorted integers
y0 = np.split(x, [1,3], axis=0)
y1 = np.split(x, [1,3], axis=1)
# Output
print("Split(x,2, axis=0):")
print(y0)
print(type(y0))
print('y0[0].shape:', y0[0].shape, '\n')
print("Split(x,2, axis=1):")
print(y1)
print(type(y1))
print('y1[0].shape:', y1[0].shape)
Split(x,2, axis=0):
[array([[1, 2, 3, 4]]), array([[11, 12, 13, 14],
[21, 22, 23, 24]]), array([[31, 32, 33, 34]])]
<class 'list'>
y0[0].shape: (1, 4)
Split(x,2, axis=1):
[array([[ 1],
[11],
[21],
[31]]), array([[ 2, 3],
[12, 13],
[22, 23],
[32, 33]]), array([[ 4],
[14],
[24],
[34]])]
<class 'list'>
y1[0].shape: (4, 1)
.
Using .hsplit():
Note: Same as .split() with axis=1
# hsplit
# split column-wise
hsi = np.hsplit(x, 2)
hsa = np.hsplit(x, [1,3])
# Output
print("hsplit (2):\n", hsi)
print('Length:',len(hsi), '\n')
print("hsplit ([1,3]):\n", hsa)
print('Length:',len(hsa), '\n')
hsplit (2):
[array([[ 1, 2],
[11, 12],
[21, 22],
[31, 32]]), array([[ 3, 4],
[13, 14],
[23, 24],
[33, 34]])]
Length: 2
hsplit ([1,3]):
[array([[ 1],
[11],
[21],
[31]]), array([[ 2, 3],
[12, 13],
[22, 23],
[32, 33]]), array([[ 4],
[14],
[24],
[34]])]
Length: 3
.
Using .vsplit():
Note: Same as .split() with axis=0
# vsplit
# split row-wise
hsi = np.vsplit(x, 2)
hsa = np.vsplit(x, [1,3])
# Output
print("vsplit (2):\n", hsi)
print('Length:',len(hsi), '\n')
print("vsplit ([1,3]):\n", hsa)
print('Length:',len(hsa), '\n')
vsplit (2):
[array([[ 1, 2, 3, 4],
[11, 12, 13, 14]]), array([[21, 22, 23, 24],
[31, 32, 33, 34]])]
Length: 2
vsplit ([1,3]):
[array([[1, 2, 3, 4]]), array([[11, 12, 13, 14],
[21, 22, 23, 24]]), array([[31, 32, 33, 34]])]
Length: 3
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