Fix latex repr of symbolic distributions

pymc/printing.py

@@ -58,7 +58,7 @@ def str_for_dist(
 
     if "latex" in formatting:
         if print_name is not None:
-            print_name = r"\text{" + _latex_escape(dist.name) + "}"
+            print_name = r"\text{" + _latex_escape(dist.name.strip("$")) + "}"
 
         op_name = (
             dist.owner.op._print_name[1]
@@ -67,9 +67,11 @@ def str_for_dist(
         )
         if include_params:
             if print_name:
-                return r"${} \sim {}({})$".format(print_name, op_name, ",~".join(dist_args))
+                return r"${} \sim {}({})$".format(
+                    print_name, op_name, ",~".join([d.strip("$") for d in dist_args])
+                )
             else:
-                return r"${}({})$".format(op_name, ",~".join(dist_args))
+                return r"${}({})$".format(op_name, ",~".join([d.strip("$") for d in dist_args]))
 
         else:
             if print_name:
@@ -138,7 +140,7 @@ def str_for_potential_or_deterministic(
     LaTeX or plain, optionally with distribution parameter values included."""
     print_name = var.name if var.name is not None else "<unnamed>"
     if "latex" in formatting:
-        print_name = r"\text{" + _latex_escape(print_name) + "}"
+        print_name = r"\text{" + _latex_escape(print_name.strip("$")) + "}"
         if include_params:
             return rf"${print_name} \sim \operatorname{{{dist_name}}}({_str_for_expression(var, formatting=formatting)})$"
         else:
@@ -182,7 +184,7 @@ def _str_for_input_rv(var: Variable, formatting: str) -> str:
         else str_for_dist(var, formatting=formatting, include_params=True)
     )
     if "latex" in formatting:
-        return r"\text{" + _latex_escape(_str) + "}"
+        return _latex_text_format(_latex_escape(_str.strip("$")))
     else:
         return _str
 
@@ -215,9 +217,20 @@ def _expand(x):
     names = [x.name for x in parents]
 
     if "latex" in formatting:
-        return r"f(" + ",~".join([r"\text{" + _latex_escape(n) + "}" for n in names]) + ")"
+        return (
+            r"f("
+            + ",~".join([_latex_text_format(_latex_escape(n.strip("$"))) for n in names])
+            + ")"
+        )
+    else:
+        return r"f(" + ", ".join([n.strip("$") for n in names]) + ")"
+
+
+def _latex_text_format(text: str) -> str:
+    if r"\operatorname{" in text:
+        return text
     else:
-        return r"f(" + ", ".join(names) + ")"
+        return r"\text{" + text + "}"
 
 
 def _latex_escape(text: str) -> str:

pymc/tests/test_printing.py

@@ -1,6 +1,6 @@
 import numpy as np
 
-from pymc import Bernoulli, Censored, Mixture
+from pymc import Bernoulli, Censored, HalfCauchy, Mixture, StudentT
 from pymc.aesaraf import floatX
 from pymc.distributions import (
     Dirichlet,
@@ -130,12 +130,12 @@ def setup_class(self):
                 r"$\text{beta} \sim \operatorname{Normal}(0,~10)$",
                 r"$\text{Z} \sim \operatorname{MvNormal}(f(),~f())$",
                 r"$\text{nb_with_p_n} \sim \operatorname{NegBinom}(10,~\text{nbp})$",
-                r"$\text{zip} \sim \operatorname{MarginalMixture}(f(),~\text{\$\operatorname{DiracDelta}(0)\$},~\text{\$\operatorname{Poisson}(5)\$})$",
+                r"$\text{zip} \sim \operatorname{MarginalMixture}(f(),~\operatorname{DiracDelta}(0),~\operatorname{Poisson}(5))$",
                 r"$\text{w} \sim \operatorname{Dirichlet}(\text{<constant>})$",
                 (
                     r"$\text{nested_mix} \sim \operatorname{MarginalMixture}(\text{w},"
-                    r"~\text{\$\operatorname{MarginalMixture}(f(),~\text{\\$\operatorname{DiracDelta}(0)\\$},~\text{\\$\operatorname{Poisson}(5)\\$})\$},"
-                    r"~\text{\$\operatorname{Censored}(\text{\\$\operatorname{Bern}(0.5)\\$},~-1,~1)\$})$"
+                    r"~\operatorname{MarginalMixture}(f(),~\operatorname{DiracDelta}(0),~\operatorname{Poisson}(5)),"
+                    r"~\operatorname{Censored}(\operatorname{Bern}(0.5),~-1,~1))$"
                 ),
                 r"$\text{Y_obs} \sim \operatorname{Normal}(\text{mu},~\text{sigma})$",
                 r"$\text{pot} \sim \operatorname{Potential}(f(\text{beta},~\text{alpha}))$",
@@ -178,3 +178,43 @@ def test_str_repr(self):
                         assert segment in model_text
                 else:
                     assert text in model_text
+
+
+def test_model_latex_repr_three_levels_model():
+    with Model() as censored_model:
+        mu = Normal("mu", 0.0, 5.0)
+        sigma = HalfCauchy("sigma", 2.5)
+        normal_dist = Normal.dist(mu=mu, sigma=sigma)
+        censored_normal = Censored(
+            "censored_normal", normal_dist, lower=-2.0, upper=2.0, observed=[1, 0, 0.5]
+        )
+
+    latex_repr = censored_model.str_repr(formatting="latex")
+    expected = [
+        "$$",
+        "\\begin{array}{rcl}",
+        "\\text{mu} &\\sim & \\operatorname{Normal}(0,~5)\\\\\\text{sigma} &\\sim & "
+        "\\operatorname{HalfCauchy}(0,~2.5)\\\\\\text{censored_normal} &\\sim & "
+        "\\operatorname{Censored}(\\operatorname{Normal}(\\text{mu},~\\text{sigma}),~-2,~2)",
+        "\\end{array}",
+        "$$",
+    ]
+    assert [line.strip() for line in latex_repr.split("\n")] == expected
+
+
+def test_model_latex_repr_mixture_model():
+    with Model() as mix_model:
+        w = Dirichlet("w", [1, 1])
+        mix = Mixture("mix", w=w, comp_dists=[Normal.dist(0.0, 5.0), StudentT.dist(7.0)])
+
+    latex_repr = mix_model.str_repr(formatting="latex")
+    expected = [
+        "$$",
+        "\\begin{array}{rcl}",
+        "\\text{w} &\\sim & "
+        "\\operatorname{Dirichlet}(\\text{<constant>})\\\\\\text{mix} &\\sim & "
+        "\\operatorname{MarginalMixture}(\\text{w},~\\operatorname{Normal}(0,~5),~\\operatorname{StudentT}(7,~0,~1))",
+        "\\end{array}",
+        "$$",
+    ]
+    assert [line.strip() for line in latex_repr.split("\n")] == expected