bug fix

Author: Jan8be

metadynminer/__init__.py

@@ -2202,20 +2202,18 @@ def findminima2(self, temp=300.0, energy_unit="kJ/mol", max_iteration=10000):
 
             print("Searching for the nearest local minima... ")
             iteration = 0
-            old_m_fes = m_fes
             while 0.0 in m_fes[:]:
                 iteration += 1
-                if iteration > 10000:
+                if iteration > max_iteration:
                     print("Warning: Maximum number of iterations reached when searching. ")
                     break
                 for i in range(self.fes.shape[0]):
                     m_fes[i] = m_fes[int(dirs[i])]
-                if np.all(np.equal(old_m_fes, m_fes)):
-                    print("Warning: some of the FES bins were not associated to any local minimum. ")
-                    break
-                old_m_fes = m_fes
-            if iteration <= 10000:
+            if iteration <= max_iteration:
                 print("Done.")
+            if 0.0 in m_fes[:]:
+                print("Warning: some of the FES bins were not associated to any local minimum. ")
+
             self.minima = np.array(minima_list)
             self.m_fes = m_fes
 
@@ -2255,19 +2253,22 @@ def findminima2(self, temp=300.0, energy_unit="kJ/mol", max_iteration=10000):
                             okoli[ii,jj] = self.fes[int(a_indexes[ii,jj,0]),int(a_indexes[ii,jj,1])]
 
                     m_i, m_j = np.unravel_index(np.argmin(okoli), okoli.shape, order='C')
-                    
-                    dirs[i,j, 0] = a_indexes[m_i,m_j,0]
-                    dirs[i,j, 1] = a_indexes[m_i,m_j,1]
-                    if self.fes[i,j] == self.fes[int(a_indexes[m_i,m_j,0]), int(a_indexes[m_i, m_j, 1])] and not np.all(okoli == np.min(okoli)):
-                        minima_count += 1
-                        m_fes[i,j] = minima_count
-                        min_cv1 = (((i)/self.res)*(cv1max-cv1min))+cv1min
-                        min_cv2 = (((j)/self.res)*(cv2max-cv2min))+cv2min
-                        minima_list.append([self.fes[i,j],i,j, min_cv1, min_cv2])
+
+                    if not np.all(okoli == np.min(okoli)):
+                        dirs[i,j, 0] = a_indexes[m_i,m_j,0]
+                        dirs[i,j, 1] = a_indexes[m_i,m_j,1]
+                        if self.fes[i,j] == self.fes[int(a_indexes[m_i,m_j,0]), int(a_indexes[m_i, m_j, 1])]:
+                            minima_count += 1
+                            m_fes[i,j] = minima_count
+                            min_cv1 = (((i)/self.res)*(cv1max-cv1min))+cv1min
+                            min_cv2 = (((j)/self.res)*(cv2max-cv2min))+cv2min
+                            minima_list.append([self.fes[i,j],i,j, min_cv1, min_cv2])
+                    else:
+                        dirs[i,j, 0] = i
+                        dirs[i,j, 1] = j
 
             print("Searching for the nearest local minima... ")
             iteration = 0
-            old_m_fes = m_fes
             while 0.0 in m_fes[:,:]:
                 iteration += 1
                 if iteration > max_iteration:
@@ -2276,12 +2277,11 @@ def findminima2(self, temp=300.0, energy_unit="kJ/mol", max_iteration=10000):
                 for i in range(self.fes.shape[0]):
                     for j in range(self.fes.shape[1]):
                         m_fes[i,j] = m_fes[int(dirs[i,j,0]), int(dirs[i,j,1])]
-                if np.all(np.equal(old_m_fes, m_fes)):
-                    print("Warning: some of the FES bins were not associated to any local minimum. ")
-                    break
-                old_m_fes = m_fes
-            if iteration <= 10000:
-                print("Done.")
+            if iteration <= max_iteration:
+                print("Done.")  
+            if 0.0 in m_fes[:,:]:
+                print("Warning: some of the FES bins were not associated to any local minimum. ")
+            
             self.minima = np.array(minima_list)
             self.m_fes = m_fes
 
@@ -2338,22 +2338,20 @@ def findminima2(self, temp=300.0, energy_unit="kJ/mol", max_iteration=10000):
 
             print("Searching for the nearest local minima... ")
             iteration = 0
-            old_m_fes = m_fes
             while 0.0 in m_fes[:,:,:]:
                 iteration += 1
-                if iteration > 10000:
+                if iteration > max_iteration:
                     print("Warning: Maximum number of iterations reached when searching. ")
                     break
                 for i in range(self.fes.shape[0]):
                     for j in range(self.fes.shape[1]):
                         for k in range(self.fes.shape[2]):
                             m_fes[i,j,k] = m_fes[int(dirs[i,j,k,0]), int(dirs[i,j,k,1]),int(dirs[i,j,k,2])]
-                if np.all(np.equal(old_m_fes, m_fes)):
-                    print("Warning: some of the FES bins were not associated to any local minimum. ")
-                    break
-                old_m_fes = m_fes
-            if iteration <= 10000:
+            if iteration <= max_iteration:
                 print("Done.")
+            if 0.0 in m_fes[:,:,:]:
+                print("Warning: some of the FES bins were not associated to any local minimum. ")
+
             self.minima = np.array(minima_list)
             self.m_fes = m_fes
 

tests/test_fep.py

@@ -5,7 +5,7 @@
 import numpy as np
 
 def test_1p():
-    expected = np.array([ 385.17567651, 1528.33533688])
+    expected = np.array([ 385.17552302, 1528.3351816 ])
     #load hills
     h1 = mm.Hills(name="./data/acealanme1d", periodic=[True])
     #find minima on FES
@@ -16,7 +16,7 @@ def test_1p():
     assert(np.allclose(fep, expected, 1e-3))
 
 def test_2p():
-    expected = np.array([ 371.9108889 ,  629.40182382, 1252.17936501, 3040.47957346])
+    expected = np.array([ 371.91080136,  629.40164896, 1289.9170257, 1252.1794877, 3040.4783994 ])
     #load hills
     h2 = mm.Hills(name="./data/acealanme", periodic=[True, True])
     #find minima on FES
@@ -27,10 +27,10 @@ def test_2p():
     assert(np.allclose(fep, expected, 1e-3))
 
 def test_3p():
-    expected = np.array([  -41.67918722,  -135.41854014,   243.58920429,  1060.11504292,
-        2378.11540026,  6513.85008335,  6598.73851877,  6418.38484675,
-        7694.86520632,  7869.748866  ,  8185.64504805,  8250.71152005,
-        9633.41481942, 12238.44803989])
+    expected = np.array([  -41.67860026,   243.58946343,  1237.95317909,  1060.11536049,
+        2378.11588445,  6418.3849335 ,  6513.84977833,  7869.74886734,
+        7694.86571792,  8185.64534757,  8250.71114721,  9633.41434977,
+       12238.44830729])
     #load hills
     h3 = mm.Hills(name="./data/acealanme3d", periodic=[True, True, True])
     #find minima on FES