Formatting

AdditionalPDFs.py

 import numpy as np
 from scipy.stats import rv_discrete, uniform
 import scipy.special as sc
-
-
-from scipy.stats._distn_infrastructure import (
-        rv_discrete, get_distribution_names)
-
+from scipy.stats._distn_infrastructure import (rv_discrete, get_distribution_names)
 
 class gpd_gen(rv_discrete):
     def _argcheck(self, mu, lbda):
         return mu >= 0.0 and lbda >= 0.0 and lbda <= 1.0
 
     def _rvs(self, mu, lbda):
-        population = np.asarray(
-            self._random_state.poisson(mu, self._size)
-        )
+        population = np.asarray(self._random_state.poisson(mu, self._size))
         if population.shape == ():
             population = population.reshape(-1)
         offspring = population.copy()
         while np.any(offspring > 0):
             # probability dists are NOT ufuncs
             # print("offspring", offspring)
-            offspring[:] = [
-                self._random_state.poisson(m)
-                for m in lbda*offspring
-            ]
+            offspring[:] = [self._random_state.poisson(m) for m in lbda*offspring]
             population += offspring
         return population
 
@@ -41,10 +32,8 @@ class gpd_gen(rv_discrete):
         elif n == 2:
             return (mu/(1-lbda))**2+mu/(1-lbda)**3
 
-
 gpoisson = gpd_gen(name='gpoisson')
     
-    
 class borel_gen(rv_discrete):
     def _argcheck(self, mu):
         return ((mu > 0) & (mu<1))
@@ -82,7 +71,6 @@ class borel_gen(rv_discrete):
         
         return _rnd
 
-
     def _stats(self, mu):
         _mu = 1/(1-mu)
         _var = mu/(1-mu)**3
@@ -93,15 +81,9 @@ class borel_gen(rv_discrete):
         g2 = scipy._lib._util._lazywhere(mu_nonzero, (tmp,), lambda x: 3 + (1 + 8*x+6*x**2)/(x*(1-x)), np.inf)
         return _mu, _var, g1, g2
 
-
 borel= borel_gen(name='borel')
 
-  
-    
 class erlang_gen(rv_discrete):
-    
-    
-    
     def _pdf(self, x, a):
         # gamma.pdf(x, a) = x**(a-1) * exp(-x) / gamma(a)
         return np.exp(self._logpdf(x, a))
@@ -109,11 +91,6 @@ class erlang_gen(rv_discrete):
     def _logpdf(self, k, mu, nu):
         return sc.xlogy(a-1.0, x) - x - sc.gammaln(a)
 
-   
-    
-    
-  
-
 #     def _rvs(self, mu, nu, size=None, random_state=None):
 #         u = scipy.stats.uniform.rvs(loc=0, scale = 1, size=size)
 #         cum = np.cumsum([self._pmf(_k, mu, nu) for _k in range(0, 100)])