update

MathGen.py

@@ -12,10 +12,6 @@ import logging
 from subprocess import call
 
 
-#logging.warning('Watch out!')  # will print a message to the console
-#logging.info('I told you so')  # will not print anything
-
-
 class mathPage:
     def __init__(self, mathID, verbose=False):
         """
@@ -809,8 +805,11 @@ class mathGenealogy(Graph):
         adv = []
         for a in res:
             if a > 0:
-                cur.execute(query, (a,))
-                advID = cur.fetchall()[0][0]
+                try:
+                    cur.execute(query, (a,))
+                    advID = cur.fetchall()[0][0]
+                except IndexError:
+                    logging.warning(f"No entry for {a}")
                 adv.append(advID)
         return(tuple(adv))
     
@@ -1196,7 +1195,7 @@ class mathGenealogy(Graph):
         else:
             fn = filename
         if bgcolor != "white":
-            self.__backColor = bgcolor
+            self.__graphOptions['bgcolor'] = bgcolor
         if not filename:
             filename = "tmp_"+str(random.randint(1,9999999))
         self.save(fn+".dot")

README.md

@@ -4,4 +4,4 @@ Python Project to generate genealogical graphs using the data from the Mathemati
 This is a completely new implementation of a project I did in 2019 to generate a poster of a friend's academic family tree as a present for his defense.
 
 ## Status
-At the moment only the basic functionality of downloading info from the Mathematics Genealogy Project from their website and storing this data in a SQLite3 database is implemented.
+Documentation is missing.

example.py

@@ -0,0 +1,50 @@
+from MathGen import *
+
+"""
+Generate the genealogical graph of the four Fields medalists of 2022:
+- Hugo Duminil-Copin
+- June Huh
+- James Maynard
+- Maryna Viazovska
+"""
+
+
+DuminilCopin_ID   = 168435
+Huh_ID             = 185855
+Maynard_ID         = 178890
+Viazovska_ID       = 201884
+
+IDs = [DuminilCopin_ID, Huh_ID, Maynard_ID, Viazovska_ID]
+
+# Define different color pallettes for graph drawing
+cols = ["#b3cde3","#ccebc5","#decbe4","#fed9a6","#ffffcc","#e5d8bd","#fddaec","#fbb4ae"]
+cols2 = ["#00202e","#003f5c","#2c4875","#8a508f","#bc5090","#ff6361","#ff8531","#ffa600","#ffd380"]
+cols3 = ["#ffadad","#ffd6a5","#fdffb6","#caffbf","#9bf6ff","#a0c4ff","#bdb2ff","#ffc6ff"]
+cols4 = ['#8dd3c7','#ffffb3','#bebada','#fb8072','#80b1d3','#fdb462','#b3de69','#fccde5','#d9d9d9']
+
+def test():
+    # initialize the genealogy
+    G = mathGenealogy("example.db")
+
+    # add all ancestors and descendants of the starting vertices to the graph
+
+    for ID in IDs:
+        G.add_ancestors(ID)       
+        G.add_descendants(ID)
+
+    # pin all starting vertices at the same level    
+    G.fixed_level(IDs)
+
+    # Color the graph 
+    G.color_graph_CSS(cols1)
+    # Draw the graph
+    G.draw_graph("example.dot", "pdf", clean=False)
+    return(G)
+
+def redraw(color, graph):
+    graph.color_graph_CSS(color)
+    graph.draw_graph("example.dot")
+
+if __name__ == "__main__":
+#    testDB = mathDB("test.db")
+    G = test()