Updated representation.

src/probabilistic_model/distributions/distributions.py

@@ -20,6 +20,13 @@ class UnivariateDistribution(ProbabilisticModel):
     def __init__(self, variable: Variable):
         super().__init__([variable])
 
+    @property
+    def representation(self) -> str:
+        """
+        The symbol used to represent this distribution.
+        """
+        return self.__class__.__name__
+
     @property
     def variable(self) -> Variable:
         """
@@ -216,6 +223,7 @@ def plot(self) -> List:
 
         return traces
 
+
 class DiscreteDistribution(UnivariateDistribution):
     """
     Abstract base class for univariate discrete distributions.
@@ -452,7 +460,7 @@ def __hash__(self):
 
     @property
     def representation(self):
-        return f"DiracDelta({self.location}, {self.density_cap})"
+        return f"δ({self.location}, {self.density_cap})"
 
     def __copy__(self):
         return self.__class__(self.variable, self.location, self.density_cap)

src/probabilistic_model/distributions/gaussian.py

@@ -141,7 +141,7 @@ def __eq__(self, other):
 
     @property
     def representation(self):
-        return f"\N{MATHEMATICAL SCRIPT CAPITAL N}(\u03BC={self.mean},\u03C3\u00b2={self.variance})"
+        return f"N({self.mean}, {self.variance})"
 
     def __copy__(self):
         return self.__class__(self.variable, self.mean, self.variance)
@@ -281,7 +281,7 @@ def __eq__(self, other):
 
     @property
     def representation(self):
-        return f"\N{MATHEMATICAL SCRIPT CAPITAL N}(\u03BC={self.mean},\u03C3\u00b2={self.variance}|{self.interval})"
+        return f"N({self.mean},{self.variance} | {self.interval})"
 
     def __copy__(self):
         return self.__class__(self.variable, self.interval, self.mean, self.variance)

src/probabilistic_model/distributions/uniform.py

@@ -107,7 +107,7 @@ def __eq__(self, other):
 
     @property
     def representation(self):
-        return f"\N{MATHEMATICAL SCRIPT CAPITAL U}{self.interval}"
+        return f"U({self.interval})"
 
     def __copy__(self):
         return self.__class__(self.variable, self.interval)

src/probabilistic_model/probabilistic_circuit/distributions/uniform.py

@@ -23,7 +23,6 @@ def __init__(self, variable: Continuous, interval: portion.Interval, parent=None
         super().__init__(variable, interval)
         ContinuousDistribution.__init__(self, variable, parent=parent)
 
-
     def conditional_from_simple_interval(self, interval: portion.Interval) -> Tuple[
         Optional[Union[DeterministicSumUnit, Self]], float]: