feat: add wrapcauchy logpdf and pdf

docs/jax.scipy.rst

@@ -446,3 +446,12 @@ jax.scipy.stats.vonmises
 
    logpdf
    pdf
+
+jax.scipy.stats.wrapcauchy
+~~~~~~~~~~~~~~~~~~~~~~~~~~
+.. automodule:: jax.scipy.stats.wrapcauchy
+.. autosummary::
+  :toctree: _autosummary
+
+   logpdf
+   pdf

jax/_src/scipy/stats/wrapcauchy.py

@@ -0,0 +1,39 @@
+# Copyright 2023 The JAX Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+import scipy.stats as osp_stats
+from jax import lax
+import jax.numpy as jnp
+from jax._src.lax.lax import _const as _lax_const
+from jax._src.numpy.util import _wraps, promote_args_inexact
+from jax._src.typing import Array, ArrayLike
+
+
+@_wraps(osp_stats.wrapcauchy.logpdf, update_doc=False)
+def logpdf(x: ArrayLike, c: ArrayLike) -> Array:
+  x, c = promote_args_inexact('wrapcauchy.logpdf', x, c)
+  return jnp.where(
+    lax.gt(c, _lax_const(c, 0)) & lax.lt(c, _lax_const(c, 1)),
+    jnp.where(
+      lax.ge(x, _lax_const(x, 0)) & lax.le(x, _lax_const(x, jnp.pi * 2)),
+      jnp.log(1 - c * c) - jnp.log(2 * jnp.pi) - jnp.log(1 + c * c - 2 * c * jnp.cos(x)),
+      -jnp.inf,
+    ),
+    jnp.nan,
+  )
+
+@_wraps(osp_stats.wrapcauchy.pdf, update_doc=False)
+def pdf(x: ArrayLike, c: ArrayLike) -> Array:
+  return lax.exp(logpdf(x, c))

jax/scipy/stats/__init__.py

@@ -40,3 +40,4 @@ from jax.scipy.stats import truncnorm as truncnorm
 from jax._src.scipy.stats.kde import gaussian_kde as gaussian_kde
 from jax._src.scipy.stats._core import mode as mode, rankdata as rankdata
 from jax.scipy.stats import vonmises as vonmises
+from jax.scipy.stats import wrapcauchy as wrapcauchy

jax/scipy/stats/wrapcauchy.py

@@ -0,0 +1,21 @@
+# Copyright 2023 The JAX Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Note: import <name> as <name> is required for names to be exported.
+# See PEP 484 & https://github.com/google/jax/issues/7570
+
+from jax._src.scipy.stats.wrapcauchy import (
+  logpdf as logpdf,
+  pdf as pdf,
+)

tests/scipy_stats_test.py

@@ -80,6 +80,42 @@ class LaxBackedScipyStatsTests(jtu.JaxTestCase):
                             tol=1e-3)
       self._CompileAndCheck(lax_fun, args_maker)
 
+  @genNamedParametersNArgs(2)
+  def testWrappedCauchyPdf(self, shapes, dtypes):
+    rng = jtu.rand_default(self.rng())
+    rng_uniform = jtu.rand_uniform(self.rng(), low=1e-3, high=1 - 1e-3)
+    scipy_fun = osp_stats.wrapcauchy.pdf
+    lax_fun = lsp_stats.wrapcauchy.pdf
+
+    def args_maker():
+      x = rng(shapes[0], dtypes[0])
+      c = rng_uniform(shapes[1], dtypes[1])
+      return [x, c]
+
+    with jtu.strict_promotion_if_dtypes_match(dtypes):
+      self._CheckAgainstNumpy(scipy_fun, lax_fun, args_maker, check_dtypes=False,
+                              tol={np.float32: 1e-4})
+      self._CompileAndCheck(lax_fun, args_maker, tol={np.float32: 1e-5,
+                                                      np.float64: 1e-11})
+
+  @genNamedParametersNArgs(2)
+  def testWrappedCauchyLogPdf(self, shapes, dtypes):
+    rng = jtu.rand_default(self.rng())
+    rng_uniform = jtu.rand_uniform(self.rng(), low=1e-3, high=1 - 1e-3)
+    scipy_fun = osp_stats.wrapcauchy.logpdf
+    lax_fun = lsp_stats.wrapcauchy.logpdf
+
+    def args_maker():
+      x = rng(shapes[0], dtypes[0])
+      c = rng_uniform(shapes[1], dtypes[1])
+      return [x, c]
+
+    with jtu.strict_promotion_if_dtypes_match(dtypes):
+      self._CheckAgainstNumpy(scipy_fun, lax_fun, args_maker, check_dtypes=False,
+                              tol={np.float32: 1e-4})
+      self._CompileAndCheck(lax_fun, args_maker, tol={np.float32: 1e-5,
+                                                      np.float64: 1e-13})
+
   @genNamedParametersNArgs(3)
   def testPoissonLogPmf(self, shapes, dtypes):
     rng = jtu.rand_default(self.rng())