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概述
- np.random_sample()
importing numpy
import numpy as np
# output random value
out_val = np.random.random_sample()
print ("Output random float value : ", out_val)
Output random float value : 0.2450768662139805
import numpy as geek
# output array
out_arr = geek.random.random_sample(size =(1, 3))
print ("Output 2D Array filled with random floats : ", out_arr)
Output 2D Array filled with random floats : [[0.15468058 0.26536462 0.54954387]]
import numpy as geek
# output array
out_arr = geek.random.random_sample((3, 2, 1))
print ("Output 3D Array filled with random floats : ", out_arr)
Output 3D Array filled with random floats : [[[0.6380224 ]
[0.73029307]]
[[0.51149673]
[0.3413279 ]]
[[0.20853883]
[0.61981115]]]
- random.ranf()
# numpy.random.ranf() is one of the function for doing random sampling in numpy. It returns an array of specified shape
# and fills it with random floats in the half-open interval [0.0, 1.0).
import numpy as np
# output random float value
out_val = np.random.ranf()
print ("Output random float value : ", out_val)
Output random float value : 0.44112568416235265
# importing numpy
import numpy as np
# output array
out_arr = np.random.ranf(size =(2, 1))
print ("Output 2D Array filled with random floats : ", out_arr)
Output 2D Array filled with random floats : [[0.69303583]
[0.8020658 ]]
import numpy as geek
# output array
out_arr = geek.random.ranf((3, 3, 2))
print ("Output 3D Array filled with random floats : ", out_arr)
Output 3D Array filled with random floats : [[[0.50709171 0.02493862]
[0.51112692 0.8210353 ]
[0.98668934 0.20536282]]
[[0.0707417 0.38774696]
[0.01399582 0.14022261]
[0.47580447 0.70451949]]
[[0.07844355 0.28663839]
[0.84763223 0.98383207]
[0.6413255 0.63548128]]]
numpy.random.random.randint()
- np.bitwise-function
# Python code to demonstrate bitwise-function
import numpy as np
# construct an array of even and odd numbers
even = np.array([0, 2, 4, 6, 8, 16, 32])
odd = np.array([1, 3, 5, 7, 9, 17, 33])
# bitwise_and
print('bitwise_and of two arrays: ')
print(np.bitwise_and(even, odd))
# bitwise_or
print('bitwise_or of two arrays: ')
print(np.bitwise_or(even, odd))
# bitwise_xor
print('bitwise_xor of two arrays: ')
print(np.bitwise_xor(even, odd))
# invert or not
print('inversion of even no. array: ')
print(np.invert(even))
# left_shift
print('left_shift of even no. array: ')
print(np.left_shift(even, 1))
# right_shift
print('right_shift of even no. array: ')
print(np.right_shift(even, 1))
bitwise_and of two arrays:
[ 0 2 4 6 8 16 32]
bitwise_or of two arrays:
[ 1 3 5 7 9 17 33]
bitwise_xor of two arrays:
[1 1 1 1 1 1 1]
inversion of even no. array:
[ -1 -3 -5 -7 -9 -17 -33]
left_shift of even no. array:
[ 0 4 8 12 16 32 64]
right_shift of even no. array:
[ 0 1 2 3 4 8 16]
最后
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