diff --git a/bilby/core/prior/dict.py b/bilby/core/prior/dict.py
index 67bdb813abc2aaad7518cd9b07721067d50455cd..7a9a8e5dcb88176b9c5622ab2082e20597974ef9 100644
--- a/bilby/core/prior/dict.py
+++ b/bilby/core/prior/dict.py
@@ -491,6 +491,21 @@ class PriorDict(dict):
constrained_ln_prob[keep] = ln_prob[keep] + np.log(ratio)
return constrained_ln_prob
+ def cdf(self, sample):
+ """Evaluate the cumulative distribution function at the provided points
+
+ Parameters
+ ----------
+ sample: dict, pandas.DataFrame
+ Dictionary of the samples of which to calculate the CDF
+
+ Returns
+ -------
+ dict, pandas.DataFrame: Dictionary containing the CDF values
+
+ """
+ return sample.__class__({key: self[key].cdf(sample) for key, sample in sample.items()})
+
def rescale(self, keys, theta):
"""Rescale samples from unit cube to prior
@@ -654,9 +669,7 @@ class ConditionalPriorDict(PriorDict):
float: Joint probability of all individual sample probabilities
"""
- self._check_resolved()
- for key, value in sample.items():
- self[key].least_recently_sampled = value
+ self._prepare_evaluation(*zip(*sample.items()))
res = [self[key].prob(sample[key], **self.get_required_variables(key)) for key in sample]
return np.product(res, **kwargs)
@@ -675,12 +688,15 @@ class ConditionalPriorDict(PriorDict):
float: Joint log probability of all the individual sample probabilities
"""
- self._check_resolved()
- for key, value in sample.items():
- self[key].least_recently_sampled = value
+ self._prepare_evaluation(*zip(*sample.items()))
res = [self[key].ln_prob(sample[key], **self.get_required_variables(key)) for key in sample]
return np.sum(res, axis=axis)
+ def cdf(self, sample):
+ self._prepare_evaluation(*zip(*sample.items()))
+ res = {key: self[key].cdf(sample[key], **self.get_required_variables(key)) for key in sample}
+ return sample.__class__(res)
+
def rescale(self, keys, theta):
"""Rescale samples from unit cube to prior
@@ -695,12 +711,14 @@ class ConditionalPriorDict(PriorDict):
=======
list: List of floats containing the rescaled sample
"""
+ keys = list(keys)
+ theta = list(theta)
self._check_resolved()
self._update_rescale_keys(keys)
result = dict()
for key, index in zip(self.sorted_keys_without_fixed_parameters, self._rescale_indexes):
- required_variables = {k: result[k] for k in getattr(self[key], 'required_variables', [])}
- result[key] = self[key].rescale(theta[index], **required_variables)
+ result[key] = self[key].rescale(theta[index], **self.get_required_variables(key))
+ self[key].least_recently_sampled = result[key]
return [result[key] for key in keys]
def _update_rescale_keys(self, keys):
@@ -708,6 +726,11 @@ class ConditionalPriorDict(PriorDict):
self._rescale_indexes = [keys.index(element) for element in self.sorted_keys_without_fixed_parameters]
self._least_recently_rescaled_keys = keys
+ def _prepare_evaluation(self, keys, theta):
+ self._check_resolved()
+ for key, value in zip(keys, theta):
+ self[key].least_recently_sampled = value
+
def _check_resolved(self):
if not self._resolved:
raise IllegalConditionsException("The current set of priors contains unresolveable conditions.")
diff --git a/test/core/prior/conditional_test.py b/test/core/prior/conditional_test.py
index a76f10a4fa379d34b4fe35499a76fb4005506741..3e2c5d051cedfe93ee401424020ee5958e98d7a9 100644
--- a/test/core/prior/conditional_test.py
+++ b/test/core/prior/conditional_test.py
@@ -1,6 +1,7 @@
import unittest
import mock
+import numpy as np
import bilby
@@ -170,13 +171,13 @@ class TestConditionalPrior(unittest.TestCase):
class TestConditionalPriorDict(unittest.TestCase):
def setUp(self):
def condition_func_1(reference_parameters, var_0):
- return reference_parameters
+ return dict(minimum=reference_parameters["minimum"], maximum=var_0)
def condition_func_2(reference_parameters, var_0, var_1):
- return reference_parameters
+ return dict(minimum=reference_parameters["minimum"], maximum=var_1)
def condition_func_3(reference_parameters, var_1, var_2):
- return reference_parameters
+ return dict(minimum=reference_parameters["minimum"], maximum=var_2)
self.minimum = 0
self.maximum = 1
@@ -203,7 +204,8 @@ class TestConditionalPriorDict(unittest.TestCase):
self.conditional_priors_manually_set_items = (
bilby.core.prior.ConditionalPriorDict()
)
- self.test_sample = dict(var_0=0.3, var_1=0.4, var_2=0.5, var_3=0.4)
+ self.test_sample = dict(var_0=0.7, var_1=0.6, var_2=0.5, var_3=0.4)
+ self.test_value = 1 / np.prod([self.test_sample[f"var_{ii}"] for ii in range(3)])
for key, value in dict(
var_0=self.prior_0,
var_1=self.prior_1,
@@ -254,7 +256,7 @@ class TestConditionalPriorDict(unittest.TestCase):
)
def test_prob(self):
- self.assertEqual(1, self.conditional_priors.prob(sample=self.test_sample))
+ self.assertEqual(self.test_value, self.conditional_priors.prob(sample=self.test_sample))
def test_prob_illegal_conditions(self):
del self.conditional_priors["var_0"]
@@ -262,7 +264,7 @@ class TestConditionalPriorDict(unittest.TestCase):
self.conditional_priors.prob(sample=self.test_sample)
def test_ln_prob(self):
- self.assertEqual(0, self.conditional_priors.ln_prob(sample=self.test_sample))
+ self.assertEqual(np.log(self.test_value), self.conditional_priors.ln_prob(sample=self.test_sample))
def test_ln_prob_illegal_conditions(self):
del self.conditional_priors["var_0"]
@@ -273,7 +275,7 @@ class TestConditionalPriorDict(unittest.TestCase):
with mock.patch("numpy.random.uniform") as m:
m.return_value = 0.5
self.assertDictEqual(
- dict(var_0=0.5, var_1=0.5, var_2=0.5, var_3=0.5),
+ dict(var_0=0.5, var_1=0.5 ** 2, var_2=0.5 ** 3, var_3=0.5 ** 4),
self.conditional_priors.sample_subset(
keys=["var_0", "var_1", "var_2", "var_3"]
),
@@ -301,31 +303,6 @@ class TestConditionalPriorDict(unittest.TestCase):
print(priors.sample(2))
def test_rescale(self):
- def condition_func_1_rescale(reference_parameters, var_0):
- if var_0 == 0.5:
- return dict(minimum=reference_parameters["minimum"], maximum=1)
- return reference_parameters
-
- def condition_func_2_rescale(reference_parameters, var_0, var_1):
- if var_0 == 0.5 and var_1 == 0.5:
- return dict(minimum=reference_parameters["minimum"], maximum=1)
- return reference_parameters
-
- def condition_func_3_rescale(reference_parameters, var_1, var_2):
- if var_1 == 0.5 and var_2 == 0.5:
- return dict(minimum=reference_parameters["minimum"], maximum=1)
- return reference_parameters
-
- self.prior_0 = bilby.core.prior.Uniform(minimum=self.minimum, maximum=1)
- self.prior_1 = bilby.core.prior.ConditionalUniform(
- condition_func=condition_func_1_rescale, minimum=self.minimum, maximum=2
- )
- self.prior_2 = bilby.core.prior.ConditionalUniform(
- condition_func=condition_func_2_rescale, minimum=self.minimum, maximum=2
- )
- self.prior_3 = bilby.core.prior.ConditionalUniform(
- condition_func=condition_func_3_rescale, minimum=self.minimum, maximum=2
- )
self.conditional_priors = bilby.core.prior.ConditionalPriorDict(
dict(
var_3=self.prior_3,
@@ -334,11 +311,28 @@ class TestConditionalPriorDict(unittest.TestCase):
var_1=self.prior_1,
)
)
- ref_variables = [0.5, 0.5, 0.5, 0.5]
+ ref_variables = self.test_sample.values()
res = self.conditional_priors.rescale(
- keys=list(self.test_sample.keys()), theta=ref_variables
+ keys=self.test_sample.keys(), theta=ref_variables
+ )
+ expected = [self.test_sample["var_0"]]
+ for ii in range(1, 4):
+ expected.append(expected[-1] * self.test_sample[f"var_{ii}"])
+ self.assertListEqual(expected, res)
+
+ def test_cdf(self):
+ """
+ Test that the CDF method is the inverse of the rescale method.
+
+ Note that the format of inputs/outputs is different between the two methods.
+ """
+ sample = self.conditional_priors.sample()
+ self.assertEqual(
+ self.conditional_priors.rescale(
+ sample.keys(),
+ self.conditional_priors.cdf(sample=sample).values()
+ ), list(sample.values())
)
- self.assertListEqual(ref_variables, res)
def test_rescale_illegal_conditions(self):
del self.conditional_priors["var_0"]
diff --git a/test/core/prior/dict_test.py b/test/core/prior/dict_test.py
index 546bcd4652cb592755630a4d356cda1517f1203f..3b8487fa1f49ea9c25459c738cc16e58252a5f76 100644
--- a/test/core/prior/dict_test.py
+++ b/test/core/prior/dict_test.py
@@ -298,6 +298,20 @@ class TestPriorDict(unittest.TestCase):
),
)
+ def test_cdf(self):
+ """
+ Test that the CDF method is the inverse of the rescale method.
+
+ Note that the format of inputs/outputs is different between the two methods.
+ """
+ sample = self.prior_set_from_dict.sample()
+ self.assertEqual(
+ self.prior_set_from_dict.rescale(
+ sample.keys(),
+ self.prior_set_from_dict.cdf(sample=sample).values()
+ ), list(sample.values())
+ )
+
def test_redundancy(self):
for key in self.prior_set_from_dict.keys():
self.assertFalse(self.prior_set_from_dict.test_redundancy(key=key))