WISH: [option to] make np.floor(), np.ceil(), np.trunc() etc return arrays with dtype=int

I’m trying to plot two quantities against each other but they are sampled at different intervals. I tried plt.plot(array1, array2[np.floor(array1time / array2interval)]). However, np.floor returns a float array so I need to cast the result to an integer type first.

This seems a bit silly. Is there any reason why someone would depend on the result of floor() being a floating point number?

[jennirinker]

In case anyone would like a work-around, you can easily cast to an integer array after floor is called:

import numpy as np
x = np.arange(10) / 2
xfloor_int = np.floor(x).astype(int)  # array of ints

[chatcannon]

@jennirinker That’s a great suggestion. It does exactly what I originally wanted, is not any more verbose, and doesn’t require any changes to numpy. Thank you.