gexf export colors

Author: alexrd

csnanalysis/csn.py

@@ -39,11 +39,15 @@ def __init__(self, counts, symmetrize=False):
 
         # initialize networkX directed graph
         self.graph = nx.DiGraph()
-        labels = [{'label' : i, 'ID' : i, 'count' : int(totcounts[i][0])} for i in range(self.nnodes)]
+        labels = [{'label' : i, 'count' : int(totcounts[i][0])} for i in range(self.nnodes)]
         self.graph.add_nodes_from(zip(range(self.nnodes),labels))
         self.graph.add_weighted_edges_from(zip(self.transmat.col,self.transmat.row,self.transmat.data))
 
-    def to_gephi(self, cols='all', node_name='node.csv', edge_name='edge.csv', directed=False):
+        # remove self edges from graph
+        self_edges = [(i,i) for i in range(self.nnodes)]
+        self.graph.remove_edges_from(self_edges)
+
+    def to_gephi_csv(self, cols='all', node_name='node.csv', edge_name='edge.csv', directed=False):
         """
         Writes node and edge files for import into the Gephi network visualization program.
 
@@ -94,7 +98,39 @@ def add_attr(self, name, values):
             attr[i] = v
 
         nx.set_node_attributes(self.graph,values=attr,name=name)
+
+    def set_colors(self, rgb):
+        """
+        Adds colors to each node for gexf export of the graph.
+
+        rgb: A dict that stores the rgb values of each node.
+
+        Example: rgb['0']['r'] = 255
+                 rgb['0']['g'] = 0
+                 rgb['0']['b'] = 0
+        """
+        for node in rgb:
+            self.graph.node[node]['viz'] = {'color': {'r': rgb[node]['r'], 'g': rgb[node]['g'], 'b': rgb[node]['b'], 'a': 0}}
+
+    def colors_from_committors(self,comm):
+        """
+        Returns rgb dict using values of committor probabilities.
+        Very useful for 3-basin committors!
+
+        comm:  Numpy array of committors, as returns from self.calc_committors
+        """
+        highc = 255
+        nbasin = comm.shape[1]
+        rgb = {}
+        colors = ['r','g','b']
+        for node in range(self.nnodes):
+            maxc = comm[node,:].max()
+            for i in range(min(3,nbasin)):
+                rgb[node][colors[i]] = highc*comm[node,i]/maxc
+
+        return rgb
 
+            
     def trim(self, by_inflow=True, by_outflow=True, min_count=0):
         """
         Trims a graph to delete nodes that are not connected to the main
@@ -179,14 +215,15 @@ def calc_eig_weights(self,label='eig_weights'):
         if self.trim_transmat is None:
             # use full transition matrix
             full_wts = eig_weights(self.transmat)
-            self.add_attr(label, full_wts)
         else:
             # use trimmed transition matrix
             wts = eig_weights(self.trim_transmat)
             full_wts = np.zeros(self.nnodes,dtype=float)
             for i,ind in enumerate(self.trim_indices):
                 full_wts[ind] = wts[i]
-            self.add_attr(label, full_wts)
+
+        fw_float = [float(i) for i in full_wts]
+        self.add_attr(label, fw_float)
 
         return full_wts
 
@@ -203,15 +240,16 @@ def calc_mult_weights(self,label='mult_weights',tol=1e-6):
         if self.trim_transmat is None:
             # use full transition matrix
             full_wts = mult_weights(self.transmat,tol)
-            self.add_attr(label, full_wts)
         else:
             # use trimmed transition matrix
             wts = mult_weights(self.trim_transmat,tol)
             full_wts = np.zeros(self.nnodes,dtype=float)
             for i,ind in enumerate(self.trim_indices):
                 full_wts[ind] = wts[i]
-            self.add_attr(label, full_wts)
 
+        fw_float = [float(i) for i in full_wts]
+        self.add_attr(label, fw_float)
+            
         return full_wts
 
     def calc_committors(self,basins,labels=None,basin_labels=None,add_basins=False,tol=1e-6,maxstep=20):
@@ -245,15 +283,17 @@ def calc_committors(self,basins,labels=None,basin_labels=None,add_basins=False,t
         if labels is None:
             labels = ['p' + str(i) for i in range(len(basins))]
         for i,b in enumerate(basins):
-            self.add_attr(labels[i], full_comm[:,i])
+            fc_float = [float(i) for i in full_comm[:,i]]
+            self.add_attr(labels[i], fc_float)
 
         if add_basins:
             if basin_labels is None:
                 basin_labels = [str(i) for i in range(len(basins))]
             for i,b in enumerate(basins):
                 bvec = np.zeros(self.nnodes,dtype=int)
                 bvec[b] = 1
-                self.add_attr(basin_labels[i],bvec)
+                bv_int = [int(i) for i in bvec]
+                self.add_attr(basin_labels[i],bv_int)
 
         return full_comm
 

csnanalysis/matrix.py

@@ -137,7 +137,8 @@ def committor(transmat,basins,tol=1e-6,maxstep=20):
     """
 
     # make sink_matrix
-    sink_mat = make_sink(transmat,list(np.array(basins).flatten()))
+    flat_sink = [i for b in basins for i in b]
+    sink_mat = make_sink(transmat,flat_sink)
 
     sink_results = trans_mult_iter(sink_mat,tol,maxstep)
 

examples/state_U.dat

@@ -1 +1 @@
-4,11,29,56,57,67,115,213,251,252,299,301,303,305,327,340,404,504,537,560,573,583,627,631,639,683,704,708,717,765,844,867,923,940,941,1010,1068,1070,1105,1138,1151,1157,1162,1243,1256,1287,1344,1348,1382,1412,1428,1455,1490,1569,1596,1640,1690,1744,1758,1776,1805,1815,1817,1825,1893,1922,1930,1933,1936,1960,1989,1993,1994,2062,2066,2076,2097,2147,2171,2183,2185,2199,2212,2302,2320,2345,2389,2408,2430,2470,2481,2513,2517,2536,2542,2606,2608,2618,2723,2749,2811,2813,2830,2870,2917,2931,2963,2995,3075,3087,3169,3183,3204,3212,3214,3247,3249,3251,3269,3270,3278,3305,3357,3466,3475,3480,3501,3536,3593,3600,3604,3611,3740,3781,3794,3810,3868,3897,3907,3962,3967,3969,3979,3989
+4 11 29 56 57 67 115 213 251 252 299 301 303 305 327 340 404 504 537 560 573 583 627 631 639 683 704 708 717 765 844 867 923 940 941 1010 1068 1070 1105 1138 1151 1157 1162 1243 1256 1287 1344 1348 1382 1412 1428 1455 1490 1569 1596 1640 1690 1744 1758 1776 1805 1815 1817 1825 1893 1922 1930 1933 1936 1960 1989 1993 1994 2062 2066 2076 2097 2147 2171 2183 2185 2199 2212 2302 2320 2345 2389 2408 2430 2470 2481 2513 2517 2536 2542 2606 2608 2618 2723 2749 2811 2813 2830 2870 2917 2931 2963 2995 3075 3087 3169 3183 3204 3212 3214 3247 3249 3251 3269 3270 3278 3305 3357 3466 3475 3480 3501 3536 3593 3600 3604 3611 3740 3781 3794 3810 3868 3897 3907 3962 3967 3969 3979 3989