(Nearly) Evenly select items from a list

I have a list of N elements, and I'd like to sample M (<= N) values which are as evenly spaced as possible. To be more specific, lets say the selection should minimize the differences in the spacings between sampled points. For example, lets say I'm constructing a boolean indexing array (i.e. in python) to select elements,

I tried the algorithm (from this similar, but different question: How do you split a list into evenly sized chunks?) :

q, r = divmod(N, M)
indices = [q*jj + min(jj, r) for jj in range(M)]

And sometimes that works well:

N=11 M=6
good_index = [0 1 0 1 0 1 0 1 0 1 0]

N=14 M=6
good_index = [0 1 1 0 1 1 0 1 0 1 0 1 0 1]

Here, the first example is trivial because the array can be evenly divided. The second example cannot be evenly divided, but the spacing between points is as similar as possible (2, 2, 1, 1, 1, 1).

But often it works poorly:

N=16 M=10
bad_index = [0 1 0 1 0 1 0 1 0 1 0 1 0 0 0 0]

N=14 M=10
bad_index = [0 1 0 1 0 1 0 1 0 0 0 0 0 0]

Because you have values piled up at the end.