How to transform negative elements to zero without a loop?

Question

If I have an array like

a = np.array([2, 3, -1, -4, 3]) 

I want to set all the negative elements to zero: [2, 3, 0, 0, 3]. How to do it with numpy without an explicit for? I need to use the modified a in a computation, for example

c = a * b 

where b is another array with the same length of the original a

Conclusion

import numpy as np from time import time  a = np.random.uniform(-1, 1, 20000000) t = time(); b = np.where(a>0, a, 0); print ("1. ", time() - t) a = np.random.uniform(-1, 1, 20000000) t = time(); b = a.clip(min=0); print ("2. ", time() - t) a = np.random.uniform(-1, 1, 20000000) t = time(); a[a < 0] = 0; print ("3. ", time() - t) a = np.random.uniform(-1, 1, 20000000) t = time(); a[np.where(a<0)] = 0; print ("4. ", time() - t) a = np.random.uniform(-1, 1, 20000000) t = time(); b = [max(x, 0) for x in a]; print ("5. ", time() - t) 

1. 1.38629984856
2. 0.516846179962 <- faster a.clip(min=0);
3. 0.615426063538
4. 0.944557905197
5. 51.7364809513

Answer 1

a = a.clip(min=0)