REF: stats: use a dist object as input and remove string API

Take a distribution object as input.

scipy/stats/unuran/__init__.py

@@ -1,4 +1,5 @@
 from .unuran_wrapper import (
     TransformedDensityRejection,
-    DiscreteAliasUrn
+    DiscreteAliasUrn,
+    GenericGenerator
 )

scipy/stats/unuran/unuran_wrapper.pyx.templ

@@ -474,7 +474,7 @@ cdef class Method:
             unur_urng_free(self.urng)
 
 
-cdef class GenericGenerator(Method):
+class GenericGenerator:
     """
     Generic generator to sample from a wide family of distributions.
 
@@ -486,8 +486,8 @@ cdef class GenericGenerator(Method):
     dist : str
         Distribution string. See [1]_ for allowed distribution keys and [2]_
         for the grammar of a distribution string.
-    method : str, optional
-        Method to use. See [3]_ for available methods. Default is 'auto'.
+    method : str
+        Method to use. Can be 'tdr' or 'dau'.
     domain : str, optional
         Domain o the distribution. Can be used to truncate the distributions.
     seed : int, BitGenerator, Generator, RandomState, SeedSequence, optional
@@ -496,101 +496,54 @@ cdef class GenericGenerator(Method):
     Other Parameters
     ----------------
     kwargs :
-        Other parameters that the Method takes. See [3]_ for all the available
-        methods and their parameters.
-
-    References
-    ----------
-    .. [1] UNU.RAN reference manual, Section 3.2.1, "Keys for Distribution String",
-           http://statmath.wu.ac.at/software/unuran/doc/unuran.html#KeysDistr
-    .. [2] UNU.RAN reference manual, Section 3.2, "Distribution String",
-           http://statmath.wu.ac.at/software/unuran/doc/unuran.html#StringDistr
-    .. [3] UNU.RAN reference manual, Section 3.4.1, "Keys for Method String",
-           http://statmath.wu.ac.at/software/unuran/doc/unuran.html#KeysMethod
+        Other parameters that the method takes.
 
     Examples
     --------
     >>> from scipy.stats import GenericGenerator
+    >>> 
+    >>> class Distribution:
+    ...     def pdf(self, x):
+    ...         return np.exp(-0.5 * x*x)
+    ...     def dpdf(self, x):
+    ...         return -x * np.exp(-0.5 * x*x)
+    ... 
+    >>> dist = Distribution()
 
-    To create a sampler for the normal distribution, do:
+    To create a sampler for this distribution, do:
 
-    >>> rng = GenericGenerator("normal")
+    >>> rng = GenericGenerator(dist, method="tdr")
 
-    Random variates can be sampled usin the `rvs` method:
+    Random variates can be sampled using the `rvs` method:
 
     >>> rvs = rng.rvs(100_000)
 
-    A method for sampling can also be specified by passing the `method`
-    parameter. In the example below, Transformed Density Rejection is used
-    as the method for sampling from the normal distirbution:
-
-    >>> rng = GenericGenerator("normal", method="tdr")
-
     It is also possible to truncate the distribution by passing the `domain`
     parameter and parameters of the `method` can be changed using keyword
     arguments:
 
-    >>> rng = GenericGenerator("normal", method="tdr", domain=(-5, 5), c=0.,
+    >>> rng = GenericGenerator(dist, method="tdr", domain=(-5, 5), c=0.,
     ...                        cpoints=(-4.5, -3.5, -2.5, 0.0, 2.5, 3.5, 4.5))
     >>> rvs = rng.rvs(100_000)
-
-    One can also change the parameters of the distributions. The below example
-    creates a samplers for the normal distribution with mean 6 and standard
-    deviation 4.25:
-
-    >>> rng = GenericGenerator("normal(6, 4.25)")
     """
+    _allmethods = {
+        'tdr': TransformedDensityRejection,
+        'dau': DiscreteAliasUrn
+    }
 
-    def __cinit__(self, dist, method="auto", domain=None, seed=None,
-                  **kwargs):
-        dist, method, domain, seed = self._validate_args(dist, method,
-                                                         domain, seed)
-        self._init_generator(dist, method, domain, seed, kwargs)
-
-    def _validate_args(self, dist, method, domain, seed):
-        dist = str(dist)
-        if dist == "":
-            raise ValueError("distribution string must not be empty")
+    def __init__(self, dist, method, domain=None, seed=None, **kwargs):
         method = str(method)
-        if domain is not None:
-            domain = tuple(domain)
-        return dist, method, domain, seed
-
-    cdef int _init_generator(self, dist, method, domain, seed,
-                             kwargs) except -1:
-        cdef:
-            ccallback_t callback
-            unuran_callback_t unur_callback
-            unur_urng *urng = NULL
-
-        cdef str distr_str = f"{dist}"
-        if domain is not None:
-            distr_str += f"; domain = {domain}"
-        cdef str meth_str = f"method = {method}"
-        for key, value in kwargs.items():
-            meth_str += f"; {key} = {value}"
-
-        self.callbacks = {}
-        self.params = ()
-
-        init_unuran_callback(&callback, &unur_callback, self.callbacks,
-                             self.params)
-        if setjmp(callback.error_buf) != 0:
-            release_unuran_callback(&callback, &unur_callback)
-            return -1
-
-        if seed is not None:
-            self.numpy_rng = get_numpy_rng(seed)
-            urng = get_urng(self.numpy_rng)
-
-        self.urng = urng
-        self.rng = unur_makegen_ssu(distr_str.encode('UTF-8'),
-                                    meth_str.encode('UTF-8'),
-                                    urng)
-
-        release_unuran_callback(&callback, &unur_callback)
-
-        return 0
+        if method.lower() not in self._allmethods:
+            raise ValueError(f"unknown method `{method}`")
+        method = method.lower()
+        self.method = self._allmethods[method](dist=dist, domain=domain,
+                                               seed=seed, **kwargs)
+
+        # add all the public attributes/methods to our generator.
+        for attrname in dir(self.method):
+            if not attrname.startswith("_"):
+                attr = getattr(self.method, attrname)
+                self.__dict__[attrname] = attr
 
 
 cdef class TransformedDensityRejection(Method):