I have a weird problem with iterators, which I can't figure out. I have a complicated numerical routine returning a generator object (or after some changes to the code an
islice). Afterwards I check, the results as I know that the results must have a negative imaginary part:
import numpy as np threshold = 1e-8 # just check up to some numerical accuracy results = result_generator(**inputs) is_valid = [np.all(_result.imag < threshold) for _result in results] print("Number of valid results: ", is_valid.count(True))
(Sorry for not giving an executable code, but I can't come up with a simple code at the moment.) The problem is now, that this returns one valid solution. If I change the code to
import numpy as np threshold = 1e-8 # just check up to some numerical accuracy results = list(result_generator(**inputs)) is_valid = [np.all(_result.imag < threshold) for _result in results] print("Number of valid results: ", is_valid.count(True))
using a list instead of a generator, I get zero valid solution. I can however not wrap my head around what is different and thus have no idea how to debug the problem. If I go through the debugger and print out the result with the corresponding index the results are even different, the one of the generator is correct, the one of the list is wrong.
Here the numerical function:
def result_generator(z, iw, coeff, n_min, n_max): assert n_min >= 1 assert n_min < n_max if n_min % 2: # index must be even n_min += 1 id1 = np.ones_like(z, dtype=complex) A0, A1 = 0.*id1, coeff*id1 A2 = coeff * id1 B2 = 1. * id1 multiplier = np.subtract.outer(z, iw[:-1])*coeff[1:] multiplier = np.moveaxis(multiplier, -1, 0).copy() def _iteration(multiplier_im): multiplier_im = multiplier_im/B2 A2[:] = A1 + multiplier_im*A0 B2[:] = 1. + multiplier_im A0[:] = A1 A1[:] = A2 / B2 return A1 complete_iterations = (_iteration(multiplier_im) for multiplier_im in multiplier) return islice(complete_iterations, n_min, n_max, 2)
You're yielding the same array over and over instead of making new arrays. When you call
list, you get a list of references to the same array, and that array is in its final state. When you don't call
list, you examine the array in the state the generator yields it, each time it's yielded.
Stop reusing the same array over and over.