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rng working with previous gaslim versions #6

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rng working with previous gaslim versions #6

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11 changes: 6 additions & 5 deletions galsim_hub/generative_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -90,19 +90,20 @@ def sample(self, cat, noise=None, rng=None, x_interpolant=None, k_interpolant=N
# Populate feed dictionary with input data
feed_dict={self.inputs[k]: cat[k] for k in self.quantities}

# If not provided, create a RNG
# If not provided, create a RNG with random seed. If you want reproducible results, give a rng with controled seed in the sample args.
if rng is None:
rng = galsim.BaseDeviate(rng)
orig_rng = rng.duplicate()
rng = galsim.GaussianDeviate(seed=None, mean=0.0, sigma=1.0)

''' We never use that right ? '''
# orig_rng = rng.duplicate()

# Look for requested random_variables
if 'random_normal' in self.random_variables:
# Draw a random normal from the galsim RNG
noise_shape = self.module.get_input_info_dict()['random_normal'].get_shape()
noise_shape = [len(cat)] + [noise_shape[i+1].value for i in range(len(noise_shape)-1)]
noise_array = np.empty(np.prod(noise_shape), dtype=float)
gd = galsim.random.GaussianDeviate(rng, sigma=1)
gd.generate(noise_array)
rng.generate(noise_array)
feed_dict[self.inputs['random_normal']] = noise_array.reshape(noise_shape).astype('float32')

# Run the graph
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