how to normalize a 1d numpy array
# Foe 1d array
an_array = np.array([0.1,0.2,0.3,0.4,0.5])
norm = np.linalg.norm(an_array)
normal_array = an_array/norm
print(normal_array)
#[0.2,0.4,0.6,0.8,1] (Should be, I didin't run the code)
how to normalize a 1d numpy array
# Foe 1d array
an_array = np.array([0.1,0.2,0.3,0.4,0.5])
norm = np.linalg.norm(an_array)
normal_array = an_array/norm
print(normal_array)
#[0.2,0.4,0.6,0.8,1] (Should be, I didin't run the code)
how to scale an array between two values python
import numpy as np
a = np.random.rand(3,2)
# Normalised [0,1]
b = (a - np.min(a))/np.ptp(a)
# Normalised [0,255] as integer: don't forget the parenthesis before astype(int)
c = (255*(a - np.min(a))/np.ptp(a)).astype(int)
# Normalised [-1,1]
d = 2.*(a - np.min(a))/np.ptp(a)-1
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