Commit 1d2e2ea4 authored by Chris Jewell's avatar Chris Jewell
Browse files

Added config-specified prior for gamma

parent aa8b0890
......@@ -90,11 +90,19 @@ if __name__ == "__main__":
########################################################
# Build the model, and then construct the MCMC kernels #
########################################################
def convert_priors(node):
if isinstance(node, dict):
for k, v in node.items():
node[k] = convert_priors(v)
return node
return float(node)
model = model_spec.CovidUK(
covariates=covar_data,
initial_state=initial_state,
initial_step=0,
num_steps=events.shape[1],
priors=convert_priors(config['mcmc']['prior']),
)
# Full joint log posterior distribution
......
......@@ -52,14 +52,14 @@ def impute_censored_events(cases):
:returns: a MxTx3 tensor of events where the first two indices of
the right-most dimension contain the imputed event times.
"""
ei_events, lag_ei = impute_previous_cases(cases, 0.44)
se_events, lag_se = impute_previous_cases(ei_events, 2.0)
ei_events, lag_ei = impute_previous_cases(cases, 0.25)
se_events, lag_se = impute_previous_cases(ei_events, 0.5)
ir_events = np.pad(cases, ((0, 0), (lag_ei + lag_se - 2, 0)))
ei_events = np.pad(ei_events, ((0, 0), (lag_se - 1, 0)))
return tf.stack([se_events, ei_events, ir_events], axis=-1)
def CovidUK(covariates, initial_state, initial_step, num_steps):
def CovidUK(covariates, initial_state, initial_step, num_steps, priors):
def beta1():
return tfd.Normal(
loc=tf.constant(0.0, dtype=DTYPE),
......@@ -85,8 +85,8 @@ def CovidUK(covariates, initial_state, initial_step, num_steps):
def gamma():
return tfd.Gamma(
concentration=tf.constant(100.0, dtype=DTYPE),
rate=tf.constant(400.0, dtype=DTYPE),
concentration=tf.constant(priors['gamma']['concentration'], dtype=DTYPE),
rate=tf.constant(priors['gamma']['rate'], dtype=DTYPE),
)
def seir(beta2, xi, gamma):
......
......@@ -1239,7 +1239,7 @@ python-versions = "*"
[[package]]
name = "regex"
version = "2020.10.15"
version = "2020.10.23"
description = "Alternative regular expression module, to replace re."
category = "dev"
optional = false
......@@ -1409,7 +1409,7 @@ test = ["pathlib2"]
[[package]]
name = "tf-estimator-nightly"
version = "2.4.0.dev2020102201"
version = "2.4.0.dev2020102301"
description = "TensorFlow Estimator."
category = "main"
optional = false
......@@ -2400,33 +2400,33 @@ qtpy = [
{file = "QtPy-1.9.0.tar.gz", hash = "sha256:2db72c44b55d0fe1407be8fba35c838ad0d6d3bb81f23007886dc1fc0f459c8d"},
]
regex = [
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{file = "regex-2020.10.23.tar.gz", hash = "sha256:2278453c6a76280b38855a263198961938108ea2333ee145c5168c36b8e2b376"},
]
requests = [
{file = "requests-2.24.0-py2.py3-none-any.whl", hash = "sha256:fe75cc94a9443b9246fc7049224f75604b113c36acb93f87b80ed42c44cbb898"},
......@@ -2526,7 +2526,7 @@ testpath = [
{file = "testpath-0.4.4.tar.gz", hash = "sha256:60e0a3261c149755f4399a1fff7d37523179a70fdc3abdf78de9fc2604aeec7e"},
]
tf-estimator-nightly = [
{file = "tf_estimator_nightly-2.4.0.dev2020102201-py2.py3-none-any.whl", hash = "sha256:76c09fde6f246bdc719971201c52c18897c053d1a6b343780830e82e50ff5c3c"},
{file = "tf_estimator_nightly-2.4.0.dev2020102301-py2.py3-none-any.whl", hash = "sha256:2aaae26018e49a2a145a453225ccb03b8297c43304a29ac69a4fd86b18c07ed7"},
]
tf-nightly = [
{file = "tf_nightly-2.4.0.dev20201021-cp36-cp36m-macosx_10_14_x86_64.whl", hash = "sha256:a876a9dbd172c26ffb18b03524596aa61c4f8588b9a6865883e8a04521d276ae"},
......
......@@ -41,7 +41,11 @@ mcmc:
num_bursts: 200
num_burst_samples: 1000
thin: 20
prior:
gamma:
concentration: 2.0
rate: 4.0
output:
results_dir: $global_scratch/covid19/
posterior: posterior.hd5
......
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