Avoid for-loops when getting mean of every positive-value-interval in an array

Question

I want to get the mean of every interval with values above a threshold. Obviously, I could do a loop and just look if the next value is under the threshold etc., but I was hoping that there would be an easier way. Do you have ideas that are similar to something like masking, but include the "interval"-problem?

Below are 2 pictures with the original data and what I want to obtain.

Before:

After:

My original idea was looping through my array, but as I want to do this about 10.000 times or more, I guess it's getting very time intensive.

Is there a way to get rid of the for loops?

transformed is a numpy array.

plt.figure()
plt.plot(transformed)
thresh=np.percentile(transformed,30)
plt.hlines(np.percentile(transformed,30),0,700)
transformed_copy=transformed
transformed_mask=[True if x>thresh else False for x in transformed_copy]
mean_arr=[]
for k in range(0,len(transformed)):
    if transformed_mask[k]==False:
        mean_all=np.mean(transformed_copy[mean_arr])
        for el in mean_arr:
            transformed_copy[el]=mean_all
        mean_arr=[]
    if transformed_mask[k]==True:
        mean_arr.append(k)
plt.plot(transformed_copy)

Output after loop: