made the plotter script dump out both timing and rms info.

gmsh/03_plotter.py

@@ -1,25 +1,69 @@
 import sys
+import os
 import sqlite3
+
+from interp.tools import rms
+
 import numpy as np
 
-con = sqlite3.connect(sys.argv[1])
+from   optparse    import OptionParser
-cur = con.cursor()
+
+if __name__ == '__main__':
+  parser = OptionParser(usage = "usage: %s [options] <db file>")
+
+  parser.add_option("-R", "--resolution",
+    type="int", dest="res", default=1,
+    help="resolution (for constant resolution charts) (default: %default)")
+
+  parser.add_option("-t", "--time",
+    action="store_true", dest="time", default=False,
+    help="write out timing results (default: %default)")
+
+  parser.add_option("-T", "--time-by-res",
+    action="store_true", dest="time", default=False,
+    help="write out timing (default: %default)")
+
+  parser.add_option("-r", "--rms",
+    action="store_true", dest="rms", default=False,
+    help="write out rms output (default: %default)")
 
 
-orders = np.array(cur.execute('select distinct ord from results').fetchall())[:,0]
+  (options, args) = parser.parse_args()
-eps    = np.array(cur.execute('select distinct ep  from results').fetchall())[:,0]
+  if len(args) != 1:
-res    = np.array(cur.execute('select distinct res from results').fetchall())[:,0]
+    parser.print_usage()
-print "#", orders, eps
+    sys.exit(1)
 
-with open('time.out', 'w') as time_file:
+  con = sqlite3.connect(args[0])
-  for ep in eps:
+  cur = con.cursor()
-    time_file.write("%d " % ep)
-    for order in orders:
-      cur_results = cur.execute('select time from results where res = 1 and ep = ? and ord = ?',
-                               (int(ep),int(order)))
-      cur_time = np.array(cur_results.fetchall()).mean()
-      time_file.write("%e " % cur_time)
-    time_file.write("\n")
 
 
-print "%e" % np.array(cur.execute('select abs(exact - final) from results').fetchall()).mean()
+  resolutions = np.array(cur.execute('select distinct res from results').fetchall())[:,0]
+  orders      = np.array(cur.execute('select distinct ord from results').fetchall())[:,0]
+  extrapoints = np.array(cur.execute('select distinct ep  from results').fetchall())[:,0]
+  print "# i found these resolutions %s, orders: %s, and extra points: %s" % (resolutions, orders, extrapoints)
+
+  if options.time:
+    for ep in extrapoints:
+      print "%d " % (ep,),
+      for order in orders:
+        for res in resolutions:
+          cur_results = cur.execute('select time from results where res = ? and ep = ? and ord = ?',
+                                   (int(res), int(ep),int(order)))
+          cur_time = np.array(cur_results.fetchall()).mean()
+          print "%e " % (cur_time,),
+
+      print
+
+
+  # print "%e" % np.array(cur.execute('select abs(exact - final) from results').fetchall()).mean()
+  if options.rms:
+    for ep in extrapoints:
+      print "%d " % (ep,),
+      for order in orders:
+        for res in resolutions:
+          cur_results = cur.execute('select abs(exact - final) from results where res = ? and ep = ? and ord = ?',
+                                   (int(res), int(ep),int(order)))
+          cur_time = rms(np.array(cur_results.fetchall()))
+          print "%e " % (cur_time,),
+
+      print