Api extras

docs/python-api.md

@@ -25,18 +25,19 @@ This page provides formal documentation for the `tsdate` Python API.
 
 ```{eval-rst}
 .. autofunction:: tsdate.date
-.. autofunction:: tsdate.discretised_dates
-.. autofunction:: tsdate.variational_dates
+.. autodata:: tsdate.core.estimation_methods
+   :no-value:
+.. autofunction:: tsdate.inside_outside
+.. autofunction:: tsdate.maximization
+.. autofunction:: tsdate.variational_gamma
 ```
 
 ## Prior and Time Discretisation Options
 
 ```{eval-rst}
 .. autofunction:: tsdate.build_prior_grid
 .. autofunction:: tsdate.build_parameter_grid
-
 .. autoclass:: tsdate.base.NodeGridValues
-
 .. autodata:: tsdate.base.DEFAULT_APPROX_PRIOR_SIZE
 ```
 

requirements.txt

@@ -6,7 +6,7 @@ tqdm
 daiquiri
 msprime>=1.0.0
 scipy
-numba>=0.58.0
+numba>=0.58.1
 appdirs
 pre-commit
 pytest

tests/test_functions.py

@@ -41,12 +41,11 @@
 from tsdate import base
 from tsdate.core import constrain_ages_topo
 from tsdate.core import date
-from tsdate.core import discretised_dates
-from tsdate.core import discretised_mean_var
+from tsdate.core import DiscreteTimeMethod
 from tsdate.core import InOutAlgorithms
+from tsdate.core import InsideOutsideMethod
 from tsdate.core import Likelihoods
 from tsdate.core import LogLikelihoods
-from tsdate.core import variational_dates
 from tsdate.core import VariationalLikelihoods
 from tsdate.demography import PopulationSizeHistory
 from tsdate.prior import ConditionalCoalescentTimes
@@ -797,14 +796,16 @@ def test_variational_prob_space(self):
     def test_variational_nosize(self):
         ts = utility_functions.two_tree_mutation_ts()
         with pytest.raises(ValueError, match="Must specify population size"):
-            variational_dates(ts, mutation_rate=1)
+            tsdate.variational_gamma(ts, mutation_rate=1)
 
     def test_variational_toomanysizes(self):
         ts = utility_functions.two_tree_mutation_ts()
         Ne = 1
         priors = tsdate.build_prior_grid(ts, Ne, np.array([0, 1.2, 2]))
         with pytest.raises(ValueError, match="Cannot specify"):
-            variational_dates(ts, mutation_rate=1, population_size=Ne, priors=priors)
+            tsdate.variational_gamma(
+                ts, mutation_rate=1, population_size=Ne, priors=priors
+            )
 
 
 class TestNodeGridValuesClass:
@@ -1604,14 +1605,14 @@ def test_bad_Ne(self):
 
 class TestDiscretisedMeanVar:
     """
-    Test discretised_mean_var works as expected
+    Test discretised mean_var works as expected
     """
 
     def test_discretised_mean_var(self):
         ts = utility_functions.single_tree_ts_n2()
         for distr in ("gamma", "lognorm"):
             posterior, algo = TestTotalFunctionalValueTree().find_posterior(ts, distr)
-            mn_post, vr_post = discretised_mean_var(ts, posterior)
+            mn_post, vr_post = DiscreteTimeMethod.mean_var(ts, posterior)
             assert np.array_equal(
                 mn_post,
                 [
@@ -1625,9 +1626,10 @@ def test_node_metadata_simulated_tree(self):
         larger_ts = msprime.simulate(
             10, mutation_rate=1, recombination_rate=1, length=20, random_seed=12
         )
-        mn_post, *_ = discretised_dates(
-            larger_ts, mutation_rate=None, population_size=10000, eps=1e-6
+        algorithm = InsideOutsideMethod(
+            larger_ts, mutation_rate=None, population_size=10000
         )
+        mn_post, *_ = algorithm.run(eps=1e-6, outside_standardize=True)
         dated_ts = date(larger_ts, population_size=10000, mutation_rate=None)
         metadata = dated_ts.tables.nodes.metadata
         metadata_offset = dated_ts.tables.nodes.metadata_offset
@@ -1840,9 +1842,8 @@ def test_node_selection_param(self):
     def test_sites_time_insideoutside(self):
         ts = utility_functions.two_tree_mutation_ts()
         dated = tsdate.date(ts, mutation_rate=None, population_size=1)
-        mn_post, *_ = discretised_dates(
-            ts, mutation_rate=None, population_size=1, eps=1e-6
-        )
+        algorithm = InsideOutsideMethod(ts, mutation_rate=None, population_size=1)
+        mn_post, *_ = algorithm.run(eps=1e-6, outside_standardize=True)
         assert np.array_equal(
             mn_post[ts.tables.mutations.node],
             tsdate.sites_time_from_ts(dated, unconstrained=True, min_time=0),
@@ -1945,9 +1946,10 @@ def test_sites_time_simulated(self):
         larger_ts = msprime.simulate(
             10, mutation_rate=1, recombination_rate=1, length=20, random_seed=12
         )
-        mn_post, *_ = discretised_dates(
+        algorithm = InsideOutsideMethod(
             larger_ts, mutation_rate=None, population_size=10000
         )
+        mn_post, *_ = algorithm.run(eps=1e-6, outside_standardize=True)
         dated = date(larger_ts, mutation_rate=None, population_size=10000)
         assert np.allclose(
             mn_post[larger_ts.tables.mutations.node],

tests/test_inference.py

@@ -121,14 +121,14 @@ def test_default_alternative_time_units(self):
 
     def test_no_posteriors(self):
         ts = utility_functions.two_tree_mutation_ts()
-        ts, posteriors = tsdate.date(
-            ts,
-            population_size=1,
-            return_posteriors=True,
-            method="maximization",
-            mutation_rate=1,
-        )
-        assert posteriors is None
+        with pytest.raises(ValueError, match="Cannot return posterior"):
+            tsdate.date(
+                ts,
+                population_size=1,
+                return_posteriors=True,
+                method="maximization",
+                mutation_rate=1,
+            )
 
     def test_discretised_posteriors(self):
         ts = utility_functions.two_tree_mutation_ts()
@@ -327,7 +327,7 @@ def test_non_contemporaneous(self):
             msprime.Sample(population=0, time=1.0),
         ]
         ts = msprime.simulate(samples=samples, Ne=1, mutation_rate=2, random_seed=12)
-        with pytest.raises(NotImplementedError):
+        with pytest.raises(ValueError, match="noncontemporaneous"):
             tsdate.date(ts, population_size=1, mutation_rate=2)
 
     def test_no_mutation_times(self):

tests/test_provenance.py

@@ -45,7 +45,7 @@ def test_date_cmd_recorded(self):
         assert dated_ts.num_provenances == num_provenances + 1
         rec = json.loads(dated_ts.provenance(-1).record)
         assert rec["software"]["name"] == "tsdate"
-        assert rec["parameters"]["command"] == "date"
+        assert rec["parameters"]["command"] == "inside_outside"
 
     def test_date_params_recorded(self):
         ts = utility_functions.single_tree_ts_n2()
@@ -57,7 +57,7 @@ def test_date_params_recorded(self):
         rec = json.loads(dated_ts.provenance(-1).record)
         assert np.isclose(rec["parameters"]["mutation_rate"], mu)
         assert np.isclose(rec["parameters"]["population_size"], Ne)
-        assert rec["parameters"]["method"] == "maximization"
+        assert rec["parameters"]["command"] == "maximization"
 
     @pytest.mark.parametrize(
         "popdict",
@@ -118,3 +118,29 @@ def test_preprocess_interval_recorded(self):
         assert deleted_intervals[0][0] < deleted_intervals[0][1]
         assert 40 < deleted_intervals[0][0] < 60
         assert 40 < deleted_intervals[0][1] < 60
+
+    @pytest.mark.parametrize("method", tsdate.core.estimation_methods.keys())
+    def test_named_methods(self, method):
+        ts = utility_functions.single_tree_ts_n2()
+        dated_ts = tsdate.date(ts, method=method, mutation_rate=0.1, population_size=10)
+        dated_ts2 = getattr(tsdate, method)(ts, mutation_rate=0.1, population_size=10)
+        rec = json.loads(dated_ts.provenance(-1).record)
+        assert rec["parameters"]["command"] == method
+        rec = json.loads(dated_ts2.provenance(-1).record)
+        assert rec["parameters"]["command"] == method
+
+    @pytest.mark.parametrize("method", tsdate.core.estimation_methods.keys())
+    def test_identical_methods(self, method):
+        ts = utility_functions.single_tree_ts_n2()
+        dated_ts = tsdate.date(
+            ts,
+            method=method,
+            mutation_rate=0.1,
+            population_size=10,
+            record_provenance=False,
+        )
+        dated_ts2 = getattr(tsdate, method)(
+            ts, mutation_rate=0.1, population_size=10, record_provenance=False
+        )
+        assert dated_ts.num_provenances == ts.num_provenances
+        assert dated_ts == dated_ts2

tsdate/__init__.py

@@ -21,10 +21,11 @@
 # SOFTWARE.
 from .cache import *  # NOQA: F401,F403
 from .core import date  # NOQA: F401
-from .core import discretised_dates  # NOQA: F401
-from .core import variational_dates  # NOQA: F401
-from .prior import build_grid as build_prior_grid  # NOQA: F401
+from .core import inside_outside  # NOQA: F401
+from .core import maximization  # NOQA: F401
+from .core import variational_gamma  # NOQA: F401
 from .prior import parameter_grid as build_parameter_grid  # NOQA: F401
+from .prior import prior_grid as build_prior_grid  # NOQA: F401
 from .provenance import __version__  # NOQA: F401
 from .util import add_sampledata_times  # NOQA: F401
 from .util import preprocess_ts  # NOQA: F401

tsdate/base.py

@@ -241,3 +241,9 @@ def fill_fixed(orig, fixed_data):
         else:
             new_obj.probability_space = probability_space
         return new_obj
+
+    def nonfixed_dict(self):
+        """
+        Return a dictionary mapping integer node ids to their data.
+        """
+        return {n: self[n] for n in self.nonfixed_nodes}

tsdate/cli.py

@@ -264,9 +264,10 @@ def run_date(args):
             progress=args.progress,
             probability_space=args.probability_space,
             num_threads=args.num_threads,
-            ignore_oldest_root=args.ignore_oldest,
         )
-        # TODO: error out if ignore_oldest_root is set,
+        if args.method == "inside_outside":
+            params["ignore_oldest_root"] = args.ignore_oldest  # For backwards compat
+        # TODO: remove and error out if ignore_oldest_root is set,
         # see https://github.com/tskit-dev/tsdate/issues/262
     dated_ts = tsdate.date(ts, args.mutation_rate, args.population_size, **params)
     dated_ts.dump(args.output)