py3 + cleanup

src/dataset.py

@@ -387,11 +387,11 @@ class Dataset(object):
                         elif quantity == 'velocity':
                             candidates.append(trace.MultiplyResponse([
                                 x.response,
-                                tarce.DifferentiationResponse()]))
+                                trace.DifferentiationResponse()]))
                         elif quantity == 'acceleration':
                             candidates.append(trace.MultiplyResponse([
                                 x.response,
-                                tarce.DifferentiationResponse(2)]))
+                                trace.DifferentiationResponse(2)]))
                         else:
                             assert False
 

src/optimizers/highscore/optimizer.py

@@ -251,10 +251,9 @@ class Chains(object):
             self, problem, history, nchains, nlinks_cap,
             bootstrap_weights):
 
-        self.optimizer = optimizer
         self.problem = problem
         self.history = history
-        self.nchains = optimizer.nbootstrap + 1
+        self.nchains = nchains
         self.nlinks_cap = nlinks_cap
         self.chains_m = num.zeros(
             (self.nchains, nlinks_cap), num.float)
@@ -262,6 +261,7 @@ class Chains(object):
             (self.nchains, nlinks_cap), num.int)
         self.nlinks = 0
         self.accept_sum = num.zeros(self.nchains, dtype=num.int)
+        self.extend(0, history.nmodels, history.models)
         history.add_listener(self)
 
         self.bootstrap_weights = num.vstack((

src/optimizers/highscore/plot.py

@@ -4,7 +4,7 @@ import numpy as num
 from matplotlib import pyplot as plt
 
 from pyrocko.plot import mpl_init, mpl_margins
-from grond import plot
+from grond import plot, core
 
 
 class HighScoreOptimizerPlot(object):
@@ -99,9 +99,9 @@ class HighScoreOptimizerPlot(object):
 
             self.writer.setup(self.fig, self.movie_filename, dpi=200)
 
-        #if self.show:
-            #plt.ion()
-            #plt.show()
+        # if self.show:
+        #    plt.ion()
+        #    plt.show()
 
     def set_limits(self):
         self.axes.set_xlim(*self.xlim)
@@ -248,8 +248,7 @@ class HighScoreOptimizerPlot(object):
 
         if self.show:
             plt.show()
-            #plt.ioff()
-
+            # plt.ioff()
 
     def render(self):
         self.start()

src/problems/base.py

@@ -188,7 +188,7 @@ class Problem(Object):
 
     def random_uniform(self, xbounds):
         x = []
-        for i in xrange(self.nparameters):
+        for i in range(self.nparameters):
             x.append(num.random.uniform(xbounds[i, 0], xbounds[i, 1]))
 
         return num.array(x, dtype=num.float)

src/toy.py

@@ -137,7 +137,7 @@ def scenario(station_setup, noise_setup):
             east=float(easts[i]),
             depth=float(depths[i]),
             obs_distance=float(measured_distances[i]))
-        for i in xrange(n)]
+        for i in range(n)]
 
     return source, targets