The code below shows how to
1. Define array a as type = float 32. (aka Single in Matlab)
2. Create empty array of zeros b as the same shape and type as a
3. Apply min/max limits to a and the clipped results to b
4. Make a copy of a as c and apply the same min/max clipping limits.
import numpy as np
#Array of float32. Without dtype, the default is float64.
a = np.array([0.21, 0.92, 0.89, 1.67, -0.12],dtype=np.float32)
#Create b with the same dimension as a
b = np.zeros(a.shape,dtype=a.dtype)
#clip
np.clip(a,0,1,out=b);
#make a copy of a as c. If use = c, the content of a will change with c.
c = a.copy()
c[c>1]=1
c[c<0]=0
Variable explorer results with Spyder:
Reference:
Single-precision floating-point (Wikipedia)
