numpy masking/filtering

[nilamo]

I'm working on a project where I'm using numpy for generative art, and I've got a question with how to filter an array without copying the data (so the original array will still be edited by a change to the filtered version). It works great for index slices, but apparently copies the data if you slice using another array as a mask?

I'm hoping this is actually super simple, and I just don't know what word numpy calls it.

import numpy as np
from PIL import Image

# small image, all black
df = np.zeros((100, 100, 3), dtype=np.uint8)

mask = np.zeros((100, 100), dtype=bool)
band = 10
for rndx, row in enumerate(mask):
    for cndx, col in enumerate(mask[rndx]):
        if abs(cndx - rndx) <= band:
            mask[rndx, cndx] = True

use_working_method = False
if use_working_method:
    # red diagonal line
    df[mask, 0] = 255
else:
    view = df[mask, :]

    # ...sometime later
    view[:, 0] = 255

    # for reference, this does work:
    view1 = df[45:55, 45:55, :]
    view1[:, :, 2] = 255  # blue, centered


im = Image.fromarray(df)
im.show()