Fix latex rendering of variables with underscore in name

pymc/printing.py

@@ -58,6 +58,7 @@ def str_for_dist(
     if "latex" in formatting:
         if print_name is not None:
             print_name = r"\text{" + _latex_escape(print_name.strip("$")) + "}"
+            print_name = _format_underscore(print_name)
 
         op_name = (
             dist.owner.op._print_name[1]
@@ -114,6 +115,7 @@ def str_for_model(model: Model, formatting: str = "plain", include_params: bool
     if not var_reprs:
         return ""
     if "latex" in formatting:
+        var_reprs = [_format_underscore(x) for x in var_reprs]
         var_reprs = [
             var_repr.replace(r"\sim", r"&\sim &").strip("$")
             for var_repr in var_reprs
@@ -295,3 +297,26 @@ def _default_repr_pretty(obj: TensorVariable | Model, p, cycle):
 except (ModuleNotFoundError, AttributeError):
     # no ipython shell
     pass
+
+
+def _format_underscore(variable: str) -> str:
+    """
+    formats variables with underscores in its name by prefixing underscores by '\\'
+    ---
+    Params:
+        variable: The string representation of the variable in the model
+    """
+    if "_" not in variable:
+        return variable
+
+    inds = [i for i, ltr in enumerate(variable) if ltr == "_"]
+    var_len_original = len(variable)
+    var_len = None
+    for ind in inds:
+        if var_len:
+            if var_len != var_len_original:
+                ind = ind + (var_len - var_len_original)
+        if variable[ind - 1 : ind] != "\\":
+            variable = variable[:ind] + "\\" + variable[ind:]
+            var_len = len(variable)
+    return variable

tests/test_printing.py

@@ -11,6 +11,8 @@
 #   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 re
+
 import numpy as np
 
 from pytensor.tensor.random import normal
@@ -171,15 +173,15 @@ def setup_class(self):
                 r"$\text{mu} \sim \operatorname{Deterministic}(f(\text{beta},~\text{alpha}))$",
                 r"$\text{beta} \sim \operatorname{Normal}(0,~10)$",
                 r"$\text{Z} \sim \operatorname{MultivariateNormal}(f(),~f())$",
-                r"$\text{nb_with_p_n} \sim \operatorname{NegativeBinomial}(10,~\text{nbp})$",
+                r"$\text{nb\_with\_p\_n} \sim \operatorname{NegativeBinomial}(10,~\text{nbp})$",
                 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{nested\_mix} \sim \operatorname{MarginalMixture}(\text{w},"
                     r"~\operatorname{MarginalMixture}(f(),~\operatorname{DiracDelta}(0),~\operatorname{Poisson}(5)),"
                     r"~\operatorname{Censored}(\operatorname{Bernoulli}(0.5),~-1,~1))$"
                 ),
-                r"$\text{Y_obs} \sim \operatorname{Normal}(\text{mu},~\text{sigma})$",
+                r"$\text{Y\_obs} \sim \operatorname{Normal}(\text{mu},~\text{sigma})$",
                 r"$\text{pot} \sim \operatorname{Potential}(f(\text{beta},~\text{alpha}))$",
                 r"$\text{pred} \sim \operatorname{Deterministic}(f(\text{<normal>}))",
             ],
@@ -189,11 +191,11 @@ def setup_class(self):
                 r"$\text{mu} \sim \operatorname{Deterministic}$",
                 r"$\text{beta} \sim \operatorname{Normal}$",
                 r"$\text{Z} \sim \operatorname{MultivariateNormal}$",
-                r"$\text{nb_with_p_n} \sim \operatorname{NegativeBinomial}$",
+                r"$\text{nb\_with\_p\_n} \sim \operatorname{NegativeBinomial}$",
                 r"$\text{zip} \sim \operatorname{MarginalMixture}$",
                 r"$\text{w} \sim \operatorname{Dirichlet}$",
-                r"$\text{nested_mix} \sim \operatorname{MarginalMixture}$",
-                r"$\text{Y_obs} \sim \operatorname{Normal}$",
+                r"$\text{nested\_mix} \sim \operatorname{MarginalMixture}$",
+                r"$\text{Y\_obs} \sim \operatorname{Normal}$",
                 r"$\text{pot} \sim \operatorname{Potential}$",
                 r"$\text{pred} \sim \operatorname{Deterministic}",
             ],
@@ -256,7 +258,7 @@ def test_model_latex_repr_three_levels_model():
         "$$",
         "\\begin{array}{rcl}",
         "\\text{mu} &\\sim & \\operatorname{Normal}(0,~5)\\\\\\text{sigma} &\\sim & "
-        "\\operatorname{HalfCauchy}(0,~2.5)\\\\\\text{censored_normal} &\\sim & "
+        "\\operatorname{HalfCauchy}(0,~2.5)\\\\\\text{censored\\_normal} &\\sim & "
         "\\operatorname{Censored}(\\operatorname{Normal}(\\text{mu},~\\text{sigma}),~-2,~2)",
         "\\end{array}",
         "$$",
@@ -316,3 +318,25 @@ def random(rng, mu, size):
 
     str_repr = model.str_repr(include_params=False)
     assert str_repr == "\n".join(["x ~ CustomDistNormal", "y ~ CustomRandomNormal"])
+
+
+class TestLatexRepr:
+    @staticmethod
+    def simple_model() -> Model:
+        with Model() as simple_model:
+            error = HalfNormal("error", 0.5)
+            alpha_a = Normal("alpha_a", 0, 1)
+            Normal("y", alpha_a, error)
+        return simple_model
+
+    def test_latex_escaped_underscore(self):
+        """
+        Ensures that all underscores in model variable names are properly escaped for LaTeX representation
+        """
+        model = self.simple_model()
+        model_str = model.str_repr(formatting="latex")
+        underscores = re.finditer(r"_", model_str)
+        for match in underscores:
+            if match:
+                start = match.span(0)[0] - 1
+                assert model_str[start : start + 1] == "\\"