diff --git a/pylot/core/util/pdf.py b/pylot/core/util/pdf.py
index 71ccfaa6..0f848633 100644
--- a/pylot/core/util/pdf.py
+++ b/pylot/core/util/pdf.py
@@ -295,18 +295,44 @@ class ProbabilityDensityFunction(object):
         return self.data[find_nearest(self.axis, value)] * self.incr
 
     def quantile(self, prob_value, eps=0.01):
+        '''
+        Function can loop infinite because the pdf does not have enough resolution for small epsilon.
+        example:
+
+        pdfs[1]['P'].quantile(0.4)
+        printing (l, r,  m,  prob_value, self.prob_lt_val(m), diff)
+        (1413410073.2067008, 1413410073.3557007, 1413410073.2812009, 0.4, 0.1439571627967223, 0.2560428372032777)
+        (1413410073.2812009, 1413410073.3557007, 1413410073.3184509, 0.4, 1.0029471675557042, -0.60294716755570421)
+        (1413410073.2812009, 1413410073.3184509, 1413410073.2998259, 0.4, 0.95737816620865313, -0.5573781662086531)
+        (1413410073.2812009, 1413410073.2998259, 1413410073.2905135, 0.4, 0.43642464167700817, -0.036424641677008152)
+        (1413410073.2812009, 1413410073.2905135, 1413410073.2858572, 0.4, 0.26658460954149427, 0.13341539045850576)
+        (1413410073.2858572, 1413410073.2905135, 1413410073.2881854, 0.4, 0.34109285366651082, 0.058907146333489202)
+        (1413410073.2881854, 1413410073.2905135, 1413410073.2893496, 0.4, 0.38582585185826251, 0.014174148141737508)
+        (1413410073.2893496, 1413410073.2905135, 1413410073.2899315, 0.4, 0.43642464167700817, -0.036424641677008152)
+        (1413410073.2893496, 1413410073.2899315, 1413410073.2896404, 0.4, 0.38582585185826251, 0.014174148141737508)
+        (1413410073.2896404, 1413410073.2899315, 1413410073.2897859, 0.4, 0.43642464167700817, -0.036424641677008152)
+        (1413410073.2896404, 1413410073.2897859, 1413410073.2897131, 0.4, 0.43642464167700817, -0.036424641677008152)
+        (1413410073.2896404, 1413410073.2897131, 1413410073.2896767, 0.4, 0.38582585185826251, 0.014174148141737508)
+        (1413410073.2896767, 1413410073.2897131, 1413410073.2896948, 0.4, 0.38582585185826251, 0.014174148141737508)
+
+        :param prob_value:
+        :param eps:
+        :return:
+        '''
         l = self.axis[0]
         r = self.axis[-1]
         m = (r + l) / 2
         diff = prob_value - self.prob_lt_val(m)
+
         while abs(diff) > eps:
+            print (l,r,m,prob_value,self.prob_lt_val(m),diff)
             if diff > 0:
                 l = m
             else:
                 r = m
             m = (r + l) / 2
             diff = prob_value - self.prob_lt_val(m)
-            print(m, prob_value, self.prob_lt_val(m))
+            #print(m, prob_value, self.prob_lt_val(m))
         return m
 
     def quantile_distance(self, prob_value):