Merge pull request #1715 from pints-team/1706-access-models-etc

Adding methods to allow access to problems, models, etc underlying errors, priors, etc

Author: MichaelClerx

CHANGELOG.md

@@ -6,6 +6,7 @@ All notable changes to this project will be documented in this file.
 ## Unreleased
 
 ### Added
+- [#1715](https://github.com/pints-team/pints/pull/1715) Added methods `ProblemErrorMeasure.problem()`, `ProblemLogLikelihood.problem()`, `SingleOutputProblem.model()` and `MultiOutputProblem.model()`.
 ### Changed
 - [#1713](https://github.com/pints-team/pints/pull/1713) PINTS now requires matplotlib 2.2 or newer.
 ### Deprecated

pints/_core.py

@@ -170,10 +170,12 @@ def evaluateS1(self, parameters):
             np.asarray(dy).reshape((self._n_times, self._n_parameters))
         )
 
+    def model(self):
+        """ Returns the :class:`ForwardModel` underlying this problem. """
+        return self._model
+
     def n_outputs(self):
-        """
-        Returns the number of outputs for this problem (always 1).
-        """
+        """ Returns the number of outputs for this problem (always 1). """
         return 1
 
     def n_parameters(self):
@@ -281,6 +283,10 @@ def evaluateS1(self, parameters):
                 self._n_times, self._n_outputs, self._n_parameters)
         )
 
+    def model(self):
+        """ Returns the :class:`ForwardModel` underlying this problem. """
+        return self._model
+
     def n_outputs(self):
         """
         Returns the number of outputs for this problem.

pints/_error_measures.py

@@ -49,7 +49,7 @@ class ProblemErrorMeasure(ErrorMeasure):
     :class:`single<pints.SingleOutputProblem>` or
     :class:`multi-output<pints.MultiOutputProblem>` problems.
     """
-    def __init__(self, problem=None):
+    def __init__(self, problem):
         super(ProblemErrorMeasure, self).__init__()
         self._problem = problem
         self._times = problem.times()
@@ -62,6 +62,10 @@ def n_parameters(self):
         """ See :meth:`ErrorMeasure.n_parameters()`. """
         return self._n_parameters
 
+    def problem(self):
+        """ Returns the problem this error measure was defined on. """
+        return self._problem
+
 
 class MeanSquaredError(ProblemErrorMeasure):
     r"""

pints/_log_pdfs.py

@@ -321,6 +321,7 @@ class ProblemLogLikelihood(LogPDF):
     ----------
     problem
         The time-series problem this log-likelihood is defined for.
+
     """
     def __init__(self, problem):
         super(ProblemLogLikelihood, self).__init__()
@@ -334,6 +335,9 @@ def n_parameters(self):
         """ See :meth:`LogPDF.n_parameters()`. """
         return self._n_parameters
 
+    def problem(self):
+        return self._problem
+
 
 class LogPosterior(LogPDF):
     """

pints/tests/test_error_measures.py

@@ -496,6 +496,18 @@ def test_bad_constructor(self):
             pints.ProbabilityBasedError, MiniProblem())
 
 
+class TestProblemErrorMeasure(unittest.TestCase):
+    """ Tests shared methods of the ProblemErrorMeasure abstract class. """
+
+    def test_shared(self):
+        # Test underlying ProblemErrorMeasure method problem()
+
+        problem = MiniProblem()
+        error = pints.MeanSquaredError(problem)
+        self.assertIs(error.problem(), problem)
+        self.assertEqual(error.n_parameters(), problem.n_parameters())
+
+
 class TestRootMeanSquaredError(unittest.TestCase):
 
     @classmethod

pints/tests/test_log_likelihoods.py

@@ -2572,6 +2572,22 @@ def test_negative_sd(self):
         self.assertEqual(log_likelihood([1, 1, 0]), -np.inf)
 
 
+class TestProblemLogLikelihood(unittest.TestCase):
+    """ Test shared ProblemLogLikelihood methods. """
+
+    @classmethod
+    def setUpClass(cls):
+        cls.model = pints.toy.ConstantModel(1)
+        cls.times = np.array([1, 2, 3, 4])
+        cls.data = np.asarray([1.9, 2.1, 1.8, 2.2])
+
+    def test_shared_methods(self):
+        problem = pints.SingleOutputProblem(self.model, self.times, self.data)
+        log_likelihood = pints.GaussianKnownSigmaLogLikelihood(problem, 1.5)
+        self.assertEqual(log_likelihood.n_parameters(), problem.n_parameters())
+        self.assertIs(log_likelihood.problem(), problem)
+
+
 class TestScaledLogLikelihood(unittest.TestCase):
 
     @classmethod

pints/tests/test_multi_output_problem.py

@@ -35,6 +35,7 @@ def test_basics(self):
         self.assertEqual(problem.n_parameters(), model.n_parameters(), 2)
         self.assertEqual(problem.n_outputs(), model.n_outputs(), 3)
         self.assertEqual(problem.n_times(), len(times))
+        self.assertIs(problem.model(), model)
 
         # Test errors
         times[0] = -2

pints/tests/test_single_output_problem.py

@@ -32,6 +32,7 @@ def test_basics(self):
         self.assertEqual(problem.n_parameters(), model.n_parameters(), 2)
         self.assertEqual(problem.n_outputs(), model.n_outputs(), 1)
         self.assertEqual(problem.n_times(), len(times))
+        self.assertIs(problem.model(), model)
 
         # Test errors
         times[0] = -2