Changeset 690

Timestamp:

09/04/17 02:52:52 (7 years ago)

Author:

konrad

Message:

Better (but not ideal) behavior for very big trees

File:

• mds-and-trees/tree-genealogy.py (modified) (5 diffs)

mds-and-trees/tree-genealogy.py

@@ -24 +24 @@
 
         self.colors = {
+            'white' :   {'r':100,   'g':100,    'b':100},
             'black' :   {'r':0,     'g':0,      'b':0},
             'red' :     {'r':100,   'g':0,      'b':0},
@@ -389 +390 @@
 
     def xmin_crowd_density(self, x1, x2, y):
-        x1_dist = 0
-        x2_dist = 0
+        # TODO experimental - requires further work to make it less 'jumpy' and more predictable
+        x1_dist_loc = 0
+        x2_dist_loc = 0
+        count_loc = 1
+        x1_dist_glob = 0
+        x2_dist_glob = 0
+        count_glob = 1
         miny = y-2000
         maxy = y+2000
@@ -402 +408 @@
 
         def include_pos(pos):
-            nonlocal x1_dist, x2_dist
-
+            nonlocal x1_dist_loc, x2_dist_loc, x1_dist_glob, x2_dist_glob, count_loc, count_glob
             dysq = (pos['y']-y)**2
             dx1 = pos['x']-x1
             dx2 = pos['x']-x2
 
-            x1_dist += math.sqrt(dysq + dx1**2)
-            x2_dist += math.sqrt(dysq + dx2**2)
+            d = math.fabs(pos['x'] - (x1+x2)/2)
+
+            if d < 10:
+                x1_dist_loc += math.sqrt(dysq + dx1**2)
+                x2_dist_loc += math.sqrt(dysq + dx2**2)
+                count_loc += 1
+            elif d > 20:
+                x1_dist_glob += math.sqrt(dysq + dx1**2)
+                x2_dist_glob += math.sqrt(dysq + dx2**2)
+                count_glob += 1
 
         # optimized to draw from all the nodes, if less than 10 nodes in the range
@@ -421 +434 @@
                     include_pos(pos)
 
-        return (x1 if x1_dist > x2_dist else x2)
+        # return ((x1 if x1_dist > x2_dist else x2)
+        #             if x1_dist < 10000 else
+        #         (x1 if x1_dist < x2_dist else x2))
+
+
+        return (x1 if (x1_dist_loc-x2_dist_loc)/count_loc-(x1_dist_glob-x2_dist_glob)/count_glob > 0  else x2)
+        #return (x1 if x1_dist +random.gauss(0, 0.00001) > x2_dist +random.gauss(0, 0.00001)  else x2)
         #print(x1_dist, x2_dist)
         #x1_dist = x1_dist**2
@@ -474 +493 @@
 
                     if self.JITTER:
-                        dissimilarity = (1-similarity) + random.gauss(0, 0.5) + 0.001
+                        dissimilarity = (1-similarity) + random.gauss(0, 0.01) + 0.001
                     else:
                         dissimilarity = (1-similarity) + 0.001