improve x_val (#440)

* improve x_val, find_ppf

* improve x_val

preliz/distributions/distributions.py

@@ -601,8 +601,11 @@ def xvals(self, support, n_points=1000):
         n_points : int
             Number of values to return.
         """
+        half_n_points = int(n_points / 2)
+
         if isinstance(support, tuple):
-            return self.ppf(np.linspace(*self.cdf(support), n_points))
+            even = np.linspace(*support, n_points)
+            uneven = self.ppf(np.linspace(*self.cdf(support), n_points))
         else:
             lower_ep, upper_ep = self.support
 
@@ -611,11 +614,10 @@ def xvals(self, support, n_points=1000):
             if not np.isfinite(upper_ep) or support == "restricted":
                 upper_ep = 0.9999
 
-            half_n_points = int(n_points / 2)
             even = np.linspace(*self.ppf([lower_ep, upper_ep]), half_n_points)
             uneven = self.ppf(np.linspace(lower_ep, upper_ep, half_n_points))
 
-            return np.sort(np.concatenate([even, uneven]))
+        return np.sort(np.concatenate([even, uneven]))
 
     def _fit_mle(self, sample, **kwargs):
         """