diff --git a/conf.py b/conf.py
index 9582fe1f391e3a08d073c3b905dec6644e3c19c7..3836f837d928278de1ba025d6c8527d229216456 100644
--- a/conf.py
+++ b/conf.py
@@ -1,5 +1,11 @@
 import numpy as np
 
+def test():
+    bt = np.arange(265, 275)
+    thr = np.array([267, 270, 273, 1, 1])
+    c = conf_test(bt, thr)
+    print(c)
+
 
 def conf_test(rad, thr):
     '''
@@ -29,20 +35,20 @@ def conf_test(rad, thr):
         thr = np.full((rad.shape[0], 4), thr[:4]).T
 
     coeff = np.power(2, (thr[3] - 1))
-    hicut = thr[0, :]
+    hicut = thr[2, :]
     beta = thr[1, :]
-    locut = thr[2, :]
+    locut = thr[0, :]
     power = thr[3, :]
     confidence = np.zeros(rad.shape)
 
     alpha, gamma = np.empty(rad.shape), np.empty(rad.shape)
     flipped = np.zeros(rad.shape)
 
-    gamma[hicut > locut] = thr[0, hicut > locut]
-    alpha[hicut > locut] = thr[2, hicut > locut]
+    gamma[hicut > locut] = thr[2, hicut > locut]
+    alpha[hicut > locut] = thr[0, hicut > locut]
     flipped[hicut > locut] = 0
-    gamma[hicut < locut] = thr[2, hicut < locut]
-    alpha[hicut < locut] = thr[0, hicut < locut]
+    gamma[hicut < locut] = thr[0, hicut < locut]
+    alpha[hicut < locut] = thr[2, hicut < locut]
     flipped[hicut < locut] = 1
 
     # Rad between alpha and beta
@@ -51,13 +57,13 @@ def conf_test(rad, thr):
     idx = np.nonzero((rad <= beta) & (flipped == 0))
     confidence[idx] = coeff[idx] * np.power(s1[idx], power[idx])
     idx = np.nonzero((rad <= beta) & (flipped == 1))
-    confidence[idx] = coeff[idx] * np.power(s1[idx], power[idx])
+    confidence[idx] = 1.0 - coeff[idx] * np.power(s1[idx], power[idx])
 
     # Rad between beta and gamma
     range_ = 2. * (beta - gamma)
-    s1 = (rad - alpha) / range_
+    s1 = (rad - gamma) / range_
     idx = np.nonzero((rad > beta) & (flipped == 0))
-    confidence[idx] = coeff[idx] * np.power(s1[idx], power[idx])
+    confidence[idx] = 1.0 - coeff[idx] * np.power(s1[idx], power[idx])
     idx = np.nonzero((rad > beta) & (flipped == 1))
     confidence[idx] = coeff[idx] * np.power(s1[idx], power[idx])
 
@@ -176,3 +182,7 @@ def conf_test_dble(rad, coeffs):
     confidence[confidence < 0] = 0
 
     return confidence
+
+
+if __name__ == "__main__":
+    test()