Apply suggestions from code review

Co-authored-by: Paul Romano <paul.k.romano@gmail.com>

docs/source/io_formats/settings.rst

@@ -641,7 +641,7 @@ variable and whose sub-elements/attributes are as follows:
   For a "rational" distribution, ``parameters`` should be given as three real
   numbers :math:`a` and :math:`b` that define the interval :math:`[a,b]` over
   which random variates are sampled and :math:`n` that defines the exponent of
-  the probability distribution :math:`p(x)=x^n`
+  the probability distribution :math:`p(x)=c x^n`
 
   For a "discrete" or "tabular" distribution, ``parameters`` provides the
   :math:`(x,p)` pairs defining the discrete/tabular distribution. All :math:`x`

include/openmc/distribution.h

@@ -87,7 +87,9 @@ private:
 class Rational : public Distribution {
 public:
   explicit Rational(pugi::xml_node node);
-  Rational(double a, double b, double n) : offset_{std::pow(a, n+1)}, span_{std::pow(b, n+1) - offset_}, ninv_{1/(n+1)} {};
+  Rational(double a, double b, double n)
+    : offset_ {std::pow(a, n + 1)}, span_ {std::pow(b, n + 1) - offset_},
+      ninv_ {1/(n+1)} {};
 
   //! Sample a value from the distribution
   //! \param seed Pseudorandom number seed pointer
@@ -95,12 +97,12 @@ public:
   double sample(uint64_t* seed) const;
 
   double a() const { return std::pow(offset_, ninv_); }
-  double b() const { return std::pow(offset_+span_, ninv_); }
-  double n() const { return 1/ninv_-1; }
+  double b() const { return std::pow(offset_ + span_, ninv_); }
+  double n() const { return 1 / ninv_ - 1; }
 private:
-  double offset_; //!< Lower bound of distribution
-  double span_; //!< Upper bound of distribution
-  double ninv_; //!< inverse Exponent of distribution
+  double offset_; //!< a^(n+1)
+  double span_; //!< b^(n+1) - a^(n+1)
+  double ninv_; //!< 1/(n+1)
 };
 
 //==============================================================================

openmc/stats/univariate.py

@@ -246,6 +246,8 @@ class Uniform(Univariate):
 
 class Rational(Univariate):
     """Distribution with power law probability over a finite interval [a,b]
+    
+    The power law distribution has density function :math:`p(x) dx = c x^n dx`.
 
     Parameters
     ----------
@@ -254,7 +256,8 @@ class Rational(Univariate):
     b : float, optional
         Upper bound of the sampling interval. Defaults to unity.
     n : float, optional
-        power law exponent. Defaults to zero, which is eqivalent to an uniform distribution
+        Power law exponent. Defaults to zero, which is equivalent to a uniform
+        distribution.
 
     Attributes
     ----------
@@ -289,17 +292,17 @@ class Rational(Univariate):
 
     @a.setter
     def a(self, a):
-        cv.check_type('Uniform a', a, Real)
+        cv.check_type('interval lower bound', a, Real)
         self._a = a
 
     @b.setter
     def b(self, b):
-        cv.check_type('Uniform b', b, Real)
+        cv.check_type('interval upper bound', b, Real)
         self._b = b
 
     @n.setter
     def n(self, n):
-        cv.check_type('Uniform n', n, Real)
+        cv.check_type('power law exponent', n, Real)
         self._n = n
 
     def to_xml_element(self, element_name):
@@ -313,12 +316,12 @@ class Rational(Univariate):
         Returns
         -------
         element : xml.etree.ElementTree.Element
-            XML element containing uniform distribution data
+            XML element containing distribution data
 
         """
         element = ET.Element(element_name)
         element.set("type", "rational")
-        element.set("parameters", '{} {} {}'.format(self.a, self.b, self.n))
+        element.set("parameters", f'{self.a} {self.b} {self.n}')
         return element
 
     @classmethod
@@ -333,7 +336,7 @@ class Rational(Univariate):
         Returns
         -------
         openmc.stats.Rational
-            Uniform distribution generated from XML element
+            Distribution generated from XML element
 
         """
         params = get_text(elem, 'parameters').split()

src/distribution.cpp

@@ -101,9 +101,9 @@ Rational::Rational(pugi::xml_node node)
   const double b = params.at(1);
   const double n = params.at(2);
 
-  offset_ = std::pow(a, n+1);
+  offset_ = std::pow(a, n + 1);
   span_ = std::pow(b, n + 1) - offset_;
-  ninv_ = 1/(n+1);
+  ninv_ = 1 / (n + 1);
 }
 
 double Rational::sample(uint64_t* seed) const