Basic tests

Author: WardBrian

cmdstanpy/model.py

@@ -1709,7 +1709,6 @@ def laplace_sample(
         timeout: Optional[float] = None,
         opt_args: Optional[Dict[str, Any]] = None,
     ) -> CmdStanLaplace:
-
         if cmdstan_version_before(2, 32, self.exe_info()):
             raise ValueError(
                 "Method 'laplace_sample' not available for CmdStan versions "
@@ -1741,14 +1740,23 @@ def laplace_sample(
                 ) from e
         elif not isinstance(mode, CmdStanMLE):
             cmdstan_mode = from_csv(mode)  # type: ignore  # we check below
-            if cmdstan_mode.runset.method != Method.OPTIMIZE:
-                raise ValueError(
-                    "Mode must be a CmdStanMLE or a path to an optimize CSV"
-                )
         else:
             cmdstan_mode = mode
 
-        # TODO: jacobian warnings on mismatch
+        if cmdstan_mode.runset.method != Method.OPTIMIZE:
+            raise ValueError(
+                "Mode must be a CmdStanMLE or a path to an optimize CSV"
+            )
+
+        mode_jacobian = (
+            cmdstan_mode.runset._args.method_args.jacobian  # type: ignore
+        )
+        if mode_jacobian != jacobian:
+            raise ValueError(
+                "Jacobian argument to optimize and laplace must match!\n"
+                f"Laplace was run with jacobian={jacobian},\n"
+                f"but optimize was run with jacobian={mode_jacobian}"
+            )
 
         laplace_args = LaplaceArgs(
             cmdstan_mode.runset.csv_files[0], draws, jacobian

cmdstanpy/stanfit/laplace.py

@@ -251,6 +251,24 @@ def __repr__(self) -> str:
         )
         return rep
 
+    def __getattr__(self, attr: str) -> np.ndarray:
+        """Synonymous with ``fit.stan_variable(attr)"""
+        if attr.startswith("_"):
+            raise AttributeError(f"Unknown variable name {attr}")
+        try:
+            return self.stan_variable(attr)
+        except ValueError as e:
+            # pylint: disable=raise-missing-from
+            raise AttributeError(*e.args)
+
+    def __getstate__(self) -> dict:
+        # This function returns the mapping of objects to serialize with pickle.
+        # See https://docs.python.org/3/library/pickle.html#object.__getstate__
+        # for details. We call _assemble_draws to ensure posterior samples have
+        # been loaded prior to serialization.
+        self._assemble_draws()
+        return self.__dict__
+
     @property
     def column_names(self) -> Tuple[str, ...]:
         """

test/test_laplace.py

@@ -2,6 +2,9 @@
 
 import os
 
+import numpy as np
+import pytest
+
 import cmdstanpy
 
 HERE = os.path.dirname(os.path.abspath(__file__))
@@ -14,6 +17,7 @@ def test_laplace_from_csv():
     fit = model.laplace_sample(
         data={},
         mode=os.path.join(DATAFILES_PATH, 'optimize', 'rosenbrock_mle.csv'),
+        jacobian=False,
     )
     assert 'x' in fit.stan_variables()
     assert 'y' in fit.stan_variables()
@@ -23,8 +27,38 @@ def test_laplace_from_csv():
 def test_laplace_runs_opt():
     model_file = os.path.join(DATAFILES_PATH, 'optimize', 'rosenbrock.stan')
     model = cmdstanpy.CmdStanModel(stan_file=model_file)
-    fit1 = model.laplace_sample(data={}, seed=1234)
+    fit1 = model.laplace_sample(data={}, seed=1234, opt_args={'iter': 1003})
     assert isinstance(fit1.mode, cmdstanpy.CmdStanMLE)
 
     assert fit1.mode.metadata.cmdstan_config['seed'] == 1234
     assert fit1._metadata.cmdstan_config['seed'] == 1234
+    assert fit1.mode.metadata.cmdstan_config['iter'] == 1003
+
+
+def test_laplace_bad_jacobian_mismatch():
+    model_file = os.path.join(DATAFILES_PATH, 'optimize', 'rosenbrock.stan')
+    model = cmdstanpy.CmdStanModel(stan_file=model_file)
+    with pytest.raises(ValueError):
+        model.laplace_sample(
+            data={},
+            mode=os.path.join(DATAFILES_PATH, 'optimize', 'rosenbrock_mle.csv'),
+            jacobian=True,
+        )
+
+
+def test_laplace_outputs():
+    model_file = os.path.join(DATAFILES_PATH, 'optimize', 'rosenbrock.stan')
+    model = cmdstanpy.CmdStanModel(stan_file=model_file)
+    fit = model.laplace_sample(data={}, seed=1234, draws=123)
+
+    variables = fit.stan_variables()
+    assert 'x' in variables
+    assert 'y' in variables
+    assert variables['x'].shape == (123,)
+
+    np.testing.assert_array_equal(variables['x'], fit.x)
+
+    fit_pd = fit.draws_pd()
+    assert 'x' in fit_pd.columns
+    assert 'y' in fit_pd.columns
+    assert fit_pd['x'].shape == (123,)