Commit 5dee7c9f authored by Chris Jewell's avatar Chris Jewell
Browse files

Repo tidy

parent cf4d5a4a
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......@@ -305,18 +305,26 @@ if __name__ == "__main__":
print("Initial logpi:", logp(*current_state))
# theta_scale = tf.constant(
# [
# [1.12e-3, 1.67e-4, 1.61e-4],
# [1.67e-4, 7.41e-4, 4.68e-5],
# [1.61e-4, 4.68e-5, 1.28e-4],
# ],
# dtype=DTYPE,
# )
theta_scale = tf.constant(
[
[1.12e-3, 1.67e-4, 1.61e-4],
[1.67e-4, 7.41e-4, 4.68e-5],
[1.61e-4, 4.68e-5, 1.28e-4],
[2.21e-05, -5.33e-05, 4.21e-06],
[-5.33e-05, 3.66e-04, 1.45e-05],
[4.21e-06, 1.45e-05, 1.52e-05],
],
dtype=DTYPE,
)
theta_scale = theta_scale * 0.2 / theta_scale.shape[0]
)
theta_scale = theta_scale * 1.0 / theta_scale.shape[0]
xi_scale = tf.eye(current_state[1].shape[0], dtype=DTYPE)
xi_scale = xi_scale * 0.0001 / xi_scale.shape[0]
xi_scale = xi_scale * 0.0002 / xi_scale.shape[0]
# We loop over successive calls to sample because we have to dump results
# to disc, or else end OOM (even on a 32GB system).
......
......@@ -74,7 +74,7 @@ def CovidUK(covariates, initial_state, initial_step, num_steps):
)
def xi():
sigma = tf.constant(0.01, dtype=DTYPE)
sigma = tf.constant(0.4, dtype=DTYPE)
phi = tf.constant(24.0, dtype=DTYPE)
kernel = tfp.math.psd_kernels.MaternThreeHalves(sigma, phi)
idx_pts = tf.cast(tf.range(num_steps // XI_FREQ) * XI_FREQ, dtype=DTYPE)
......
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