A suggestion for the Python part of things is to use numpy arrays to represent the matrices (and possibly the arrays too). But to be honest, you should not be concerned with that right now. That C-code looks ugly. Apart from that, different languages use different approaches to achieve the same thing. That is what makes such conversions hard. Try to get an understanding of the algorithm it implements (supposing that is what it does) and write that down in a language-agnostic way. Then think how you would implement that in Python.
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A suggestion for the Python part of things is to use numpy arrays to represent the matrices (and possibly the arrays too). But to be honest, you should not be concerned with that right now. That C-code looks ugly. Apart from that, different languages use different approaches to achieve the same thing. That is what makes such conversions hard. Try to get an understanding of the algorithm it implements (supposing that is what it does) and write that down in a language-agnostic way. Then think how you would implement that in Python.
In your translation, the first thing I would worry about is making sensical variable names, particularly for those arrays. Regardless, much of that translates directly.
Nwt and Ndt are 2D arrays, Nt is a one dimensional array. It looks like you're looping over all the 'columns' in the z array, and generating a random number for each one. Then you increment whichever column was picked in Nwt (row w[i]), Ndt (row d[i]) and Nt. The actual random value is stashed in z.
#Literal translation
for i in range(N):
t = Random.randint(0,T) #Not sure on this... but it seems likely.
z[i] = t
Nwt[w[i]][t] += 1
Ndt[d[i]][t] += 1
Nt[t] += 1
#In place of w= ivec(N);
w = [0]*N
d = [0]*N
z = [0]*N
#In place of Nwt = dmat(W,T)
Nwt = [[0.0] * T] * W
Ndt = [[0.0] * T] * D
EDIT: corrected w/d/z initialization from "n" to "N"
Note that there are still some things wrong here, since it looks like N must equal W, and D... so tread carefully.