import distl
import numpy as np

g = distl.gaussian(10, 2)

distl obeys the seed set in np.random.seed.

np.random.seed(1234)
g.sample()

8.255378595638142

np.random.seed(1234)
g.sample()

8.255378595638142

Alternatively, pass seed to sample, plot, or plot_sample.

g.sample(seed=1234)

8.255378595638142

g.sample()

10.62204778579605

The random seed is respected for all distribution types, including Histogram.

h = g.to_histogram()

h.sample()

11.994789009229821

h.sample(seed=1234)

8.185549956549941

h.sample(seed=1234)

8.185549956549941

If you want a random seed to be used to multiple calls in the same execution, you can access a random array of integers via get_random_seed which can then be passed on to either np.random.seed or sample.

seed = distl.get_random_seed()

g.sample(seed=seed)

6.561067923451439

g.sample(seed=seed)

6.561067923451439

g.sample(seed=distl.get_random_seed())

11.27810575248316