Merge branch 'neurostuff:master' into enh-stouffer

.github/workflows/testing.yml

@@ -39,7 +39,7 @@ jobs:
       fail-fast: false
       matrix:
         os: ["ubuntu-latest", "macos-latest"]
-        python-version: ["3.8", "3.9"]
+        python-version: ["3.8", "3.9", "3.10"]
 
     name: ${{ matrix.os }} with Python ${{ matrix.python-version }}
     defaults:

docs/installation.rst

@@ -16,4 +16,4 @@ If you want to use the most up-to-date version, you can install from the ``maste
     pip install git+https://github.com/neurostuff/PyMARE.git
 
 PyMARE requires Python >=3.6 and a number of packages.
-For a complete list, please see the file ``setup.cfg``.
+For a complete list, please see ``setup.cfg``.

pymare/core.py

@@ -59,7 +59,6 @@ class Dataset:
     def __init__(
         self, y=None, v=None, X=None, n=None, data=None, X_names=None, add_intercept=True
     ):
-
         if y is None and data is None:
             raise ValueError(
                 "If no y values are provided, a pandas DataFrame "

pymare/effectsize/base.py

@@ -90,7 +90,6 @@ class EffectSizeConverter(metaclass=ABCMeta):
     """Base class for effect size converters."""
 
     def __init__(self, data=None, **kwargs):
-
         kwargs = {k: v for k, v in kwargs.items() if v is not None}
 
         if data is not None:
@@ -509,7 +508,6 @@ def compute_measure(
 
     # Select or infer converter class
     if comparison == "infer":
-
         one_samp_inputs = {"m", "sd", "n", "r"}
         two_samp_inputs = {"m1", "m2", "sd1", "sd2", "n1", "n2"}
 

pymare/effectsize/expressions.py

@@ -91,7 +91,6 @@ def df_search(sym, exprs, known, visited):
         results = []
 
         for exp in exp_dict[sym]:
-
             candidates = []
 
             sym_names = set(s.name for s in exp.symbols)

pymare/estimators/estimators.py

@@ -1,5 +1,6 @@
 """Meta-regression estimator classes."""
 
+import sys
 from abc import ABCMeta, abstractmethod
 from inspect import getfullargspec
 from warnings import warn
@@ -553,8 +554,8 @@ class StanMetaRegression(BaseEstimator):
 
     Warning
     -------
-    With changes to Stan in version 3, which requires Python 3.7, this class no longer works for
-    Python 3.7+. We will try to fix it in the future.
+    :obj:`~pymare.estimators.StanMetaRegression` uses Pystan 3, which requires Python 3.7.
+    Pystan 3 should not be used with PyMARE and Python 3.6 or earlier.
     """
 
     _result_cls = BayesianMetaRegressionResults
@@ -564,6 +565,13 @@ def __init__(self, **sampling_kwargs):
         self.model = None
         self.result_ = None
 
+        if sys.version_info < (3, 7):
+            raise RuntimeError(
+                "StanMetaRegression uses Pystan 3, which requires python 3.7 or higher. "
+                f"You are running Python {sys.version_info.major}.{sys.version_info.minor}. "
+                "Pystan 3 should not be used with PyMARE and Python 3.6 or earlier."
+            )
+
     def compile(self):
         """Compile the Stan model."""
         # Note: we deliberately use a centered parameterization for the
@@ -575,7 +583,7 @@ def compile(self):
             int<lower=1> N;
             int<lower=1> K;
             vector[N] y;
-            int<lower=1,upper=K> id[N];
+            array[N] int<lower=1,upper=K> id;
             int<lower=1> C;
             matrix[K, C] X;
             vector[N] sigma;
@@ -595,13 +603,11 @@ def compile(self):
         }
         """
         try:
-            from pystan import StanModel
+            import stan
         except ImportError:
-            raise ImportError(
-                "Please install pystan or, if using Python 3.7+, switch to Python 3.6."
-            )
+            raise ImportError("Please install pystan.")
 
-        self.model = StanModel(model_code=spec)
+        self.model = stan.build(spec, data=self.data)
 
     def fit(self, y, v, X, groups=None):
         """Run the Stan sampler and return results.
@@ -645,9 +651,6 @@ def fit(self, y, v, X, groups=None):
                 "shape {}.".format(y.shape)
             )
 
-        if self.model is None:
-            self.compile()
-
         N = y.shape[0]
         groups = groups or np.arange(1, N + 1, dtype=int)
         K = len(np.unique(groups))
@@ -662,7 +665,12 @@ def fit(self, y, v, X, groups=None):
             "sigma": v.ravel(),
         }
 
-        self.result_ = self.model.sampling(data=data, **self.sampling_kwargs)
+        self.data = data
+
+        if self.model is None:
+            self.compile()
+
+        self.result_ = self.model.sample(**self.sampling_kwargs)
         return self
 
     def summary(self, ci=95):

pymare/results.py

@@ -332,7 +332,6 @@ def permutation_test(self, n_perm=1000):
 
         # Loop over parallel datasets
         for i in range(n_datasets):
-
             y = self.dataset.y[:, i]
             y_perm = np.repeat(y[:, None], n_perm, axis=1)
 
@@ -472,7 +471,6 @@ def permutation_test(self, n_perm=1000):
 
         # Loop over parallel datasets
         for i in range(n_datasets):
-
             y = self.dataset.y[:, i]
             y_perm = np.repeat(y[:, None], n_perm, axis=1)
 

pymare/tests/test_stan_estimators.py

@@ -1,15 +1,17 @@
 """Tests for estimators that use stan."""
 
+import sys
+
 import pytest
 
 from pymare.estimators import StanMetaRegression
 
 
-@pytest.mark.skip(reason="StanMetaRegression won't work with Python 3.7+.")
+@pytest.mark.skipif(sys.version_info < (3, 7), reason="requires python 3.7 or higher")
 def test_stan_estimator(dataset):
     """Run smoke test for StanMetaRegression."""
     # no ground truth here, so we use sanity checks and rough bounds
-    est = StanMetaRegression(iter=3000).fit_dataset(dataset)
+    est = StanMetaRegression(num_samples=3000).fit_dataset(dataset)
     results = est.summary()
     assert "BayesianMetaRegressionResults" == results.__class__.__name__
     summary = results.summary(["beta", "tau2"])
@@ -19,9 +21,17 @@ def test_stan_estimator(dataset):
     assert 3 < tau2 < 5
 
 
-@pytest.mark.skip(reason="StanMetaRegression won't work with Python 3.7+.")
+@pytest.mark.skipif(sys.version_info < (3, 7), reason="requires python 3.7 or higher")
 def test_stan_2d_input_failure(dataset_2d):
     """Run smoke test for StanMetaRegression on 2D data."""
     with pytest.raises(ValueError) as exc:
-        StanMetaRegression(iter=500).fit_dataset(dataset_2d)
+        StanMetaRegression(num_samples=500).fit_dataset(dataset_2d)
     assert str(exc.value).startswith("The StanMetaRegression")
+
+
+def test_stan_python_36_failure(dataset):
+    """Run smoke test for StanMetaRegression with Python 3.6."""
+    if sys.version_info < (3, 7):
+        # Raise error if StanMetaRegression is initialize with python 3.6 or lower
+        with pytest.raises(RuntimeError):
+            StanMetaRegression(num_samples=3000).fit_dataset(dataset)

setup.cfg

@@ -30,14 +30,15 @@ classifiers =
     Operating System :: OS Independent
     Programming Language :: Python :: 3.8
     Programming Language :: Python :: 3.9
+    Programming Language :: Python :: 3.10
     Topic :: Scientific/Engineering
 
 [options]
 python_requires = >= 3.8
 install_requires =
     numpy>=1.8.0
     pandas
-    scipy
+    scipy<1.13.0  # https://github.com/arviz-devs/arviz/issues/2336
     sympy
     wrapt
 packages = find:
@@ -74,6 +75,7 @@ stan =
 all =
     %(doc)s
     %(tests)s
+    %(stan)s
 
 [options.package_data]
 * =