Identifying range of x array indices to set corresponding y array values to zero

Question

Say I have data in t and y arrays. I want to identify the array element indices between t=0.5 to t=1.5 and t=3 to t=4 in order to set the corresponding y values to zero (and put this in ynew array). I am having trouble with getting the indices into the empty array tnew, as I just get an output of [].

import numpy as np
import matplotlib.pyplot as plt

t = np.array([0,0.1,0.2,0.4,0.6,0.65,0.7,0.88,0.92,1.09,1.2,1.28,1.5,1.7,1.9,2.1,2.2,2.33,2.6,2.9,2.99,3.1,3.3,3.4,3.7,3.8,4,4.2])
y = t + 0.2*np.random.randn(len(t))

plt.plot(t,y,'o')
plt.show()

# want ranges t=0.5 to t=1.5 and t=3 to t=4 to have corresponding y=0 values:
for index, item in enumerate(t):
    tnew = [] # put index values here
    if item > 0.5 and item < 1.5:
        tnew.append(index)
        #print (index, item)
    elif item > 3 and item < 4:
        tnew.append(index)
        #print (index, item)

print (tnew)

Any ideas?

I want to end up plotting ynew vs tnew.

Answer 1

You just need to use the boolean indexing of numpy.

Add this line: y[((t>0.5)&(t<=1.5))|((t>3)&(t<=4))]=0.

Answer 2

Your problem is here:

for index, item in enumerate(t):
    tnew = [] # put index values here
    if item > 0.5 and item < 1.5:
        tnew.append(index)
        #print (index, item)
    elif item > 3 and item < 4:
        tnew.append(index)

You replace tnew with an empty list every time round the loop, so you will have at most one index (the last!) in it afterwards.

Instead, try:

tnew = []
for index, item in enumerate(t):
    if (0.5 < item < 1.5) or (3 < item < 4):
        tnew.append(index)

Or a list comprehension:

tnew = [index for index, item in enumerate(t) 
        if (0.5 < item < 1.5) or (3 < item < 4)]