fix #4216: str and latex representations for Bound variables (#4217)

* handling of parameters equal to None

* improved type juggling of bounds

* updating str repr for bounded variables

* adding bounded variable to str/_repr_latex test

* updating test

* black formatting

* removing unused import

* change string to r-string

Author: Spaak

pymc3/distributions/bound.py

@@ -16,7 +16,6 @@
 
 import numpy as np
 import theano.tensor as tt
-import theano
 
 from pymc3.distributions.distribution import (
     Distribution,
@@ -28,6 +27,8 @@
 from pymc3.distributions import transforms
 from pymc3.distributions.dist_math import bound
 
+from pymc3.theanof import floatX
+
 __all__ = ["Bound"]
 
 
@@ -148,6 +149,25 @@ def random(self, point=None, size=None):
                 not_broadcast_kwargs={"point": point},
             )
 
+    def _distr_parameters_for_repr(self):
+        return ["lower", "upper"]
+
+    def _distr_name_for_repr(self):
+        return "Bound"
+
+    def _str_repr(self, **kwargs):
+        distr_repr = self._wrapped._str_repr(**{**kwargs, "dist": self._wrapped})
+        if "formatting" in kwargs and kwargs["formatting"] == "latex":
+            distr_repr = distr_repr[distr_repr.index(r" \sim") + 6 :]
+        else:
+            distr_repr = distr_repr[distr_repr.index(" ~") + 3 :]
+        self_repr = super()._str_repr(**kwargs)
+
+        if "formatting" in kwargs and kwargs["formatting"] == "latex":
+            return self_repr + " -- " + distr_repr
+        else:
+            return self_repr + "-" + distr_repr
+
 
 class _DiscreteBounded(_Bounded, Discrete):
     def __init__(self, distribution, lower, upper, transform="infer", *args, **kwargs):
@@ -187,12 +207,10 @@ class _ContinuousBounded(_Bounded, Continuous):
     """
 
     def __init__(self, distribution, lower, upper, transform="infer", *args, **kwargs):
-        dtype = kwargs.get("dtype", theano.config.floatX)
-
         if lower is not None:
-            lower = tt.as_tensor_variable(lower).astype(dtype)
+            lower = tt.as_tensor_variable(floatX(lower))
         if upper is not None:
-            upper = tt.as_tensor_variable(upper).astype(dtype)
+            upper = tt.as_tensor_variable(floatX(upper))
 
         if transform == "infer":
             if lower is None and upper is None:

pymc3/tests/test_distributions.py

@@ -1779,16 +1779,20 @@ def setup_class(self):
             # Expected value of outcome
             mu = Deterministic("mu", floatX(alpha + tt.dot(X, b)))
 
+            # add a bounded variable as well
+            bound_var = Bound(Normal, lower=1.0)("bound_var", mu=0, sigma=10)
+
             # Likelihood (sampling distribution) of observations
             Y_obs = Normal("Y_obs", mu=mu, sigma=sigma, observed=Y)
-        self.distributions = [alpha, sigma, mu, b, Z, Y_obs]
+        self.distributions = [alpha, sigma, mu, b, Z, Y_obs, bound_var]
         self.expected_latex = (
             r"$\text{alpha} \sim \text{Normal}(\mathit{mu}=0.0,~\mathit{sigma}=10.0)$",
             r"$\text{sigma} \sim \text{HalfNormal}(\mathit{sigma}=1.0)$",
             r"$\text{mu} \sim \text{Deterministic}(\text{alpha},~\text{Constant},~\text{beta})$",
             r"$\text{beta} \sim \text{Normal}(\mathit{mu}=0.0,~\mathit{sigma}=10.0)$",
             r"$\text{Z} \sim \text{MvNormal}(\mathit{mu}=array,~\mathit{chol_cov}=array)$",
             r"$\text{Y_obs} \sim \text{Normal}(\mathit{mu}=\text{mu},~\mathit{sigma}=f(\text{sigma}))$",
+            r"$\text{bound_var} \sim \text{Bound}(\mathit{lower}=1.0,~\mathit{upper}=\text{None})$ -- \text{Normal}(\mathit{mu}=0.0,~\mathit{sigma}=10.0)$",
         )
         self.expected_str = (
             r"alpha ~ Normal(mu=0.0, sigma=10.0)",
@@ -1797,6 +1801,7 @@ def setup_class(self):
             r"beta ~ Normal(mu=0.0, sigma=10.0)",
             r"Z ~ MvNormal(mu=array, chol_cov=array)",
             r"Y_obs ~ Normal(mu=mu, sigma=f(sigma))",
+            r"bound_var ~ Bound(lower=1.0, upper=None)-Normal(mu=0.0, sigma=10.0)",
         )
 
     def test__repr_latex_(self):

pymc3/util.py

@@ -128,8 +128,8 @@ def get_default_varnames(var_iterator, include_transformed):
 
 def get_repr_for_variable(variable, formatting="plain"):
     """Build a human-readable string representation for a variable."""
-    name = variable.name
-    if name is None:
+    name = variable.name if variable is not None else None
+    if name is None and variable is not None:
         if hasattr(variable, "get_parents"):
             try:
                 names = [