Changeset ed4aef2 in sasview for src/sans/fit/BumpsFitting.py

Timestamp:

May 6, 2014 9:34:46 AM (10 years ago)

Author:

pkienzle

Branches:

master, ESS_GUI, ESS_GUI_Docs, ESS_GUI_batch_fitting, ESS_GUI_bumps_abstraction, ESS_GUI_iss1116, ESS_GUI_iss879, ESS_GUI_iss959, ESS_GUI_opencl, ESS_GUI_ordering, ESS_GUI_sync_sascalc, costrafo411, magnetic_scatt, release-4.1.1, release-4.1.2, release-4.2.2, release_4.0.1, ticket-1009, ticket-1094-headless, ticket-1242-2d-resolution, ticket-1243, ticket-1249, ticket885, unittest-saveload

Children:

f121904

Parents:

644ca73

Message:

add panel for bumps results

File:

• src/sans/fit/BumpsFitting.py (modified) (5 diffs)

src/sans/fit/BumpsFitting.py

@@ -16 +16 @@
         self.handler = handler
         self.max_step = max_step
+
     def config_history(self, history):
         history.requires(time=1, value=2, point=1, step=1)
+
     def __call__(self, history):
         self.handler.progress(history.step[0], self.max_step)
@@ -23 +25 @@
             self.handler.improvement()
         self.handler.update_fit()
+
+class ConvergenceMonitor(object):
+    """
+    ConvergenceMonitor contains population summary statistics to show progress
+    of the fit.  This is a list [ (best, 0%, 25%, 50%, 75%, 100%) ] or
+    just a list [ (best, ) ] if population size is 1.
+    """
+    def __init__(self):
+        self.convergence = []
+
+    def config_history(self, history):
+        history.requires(value=1, population_values=1)
+
+    def __call__(self, history):
+        best = history.value[0]
+        try:
+            p = history.population_values[0]
+            n,p = len(p), numpy.sort(p)
+            QI,Qmid, = int(0.2*n),int(0.5*n)
+            self.convergence.append((best, p[0],p[QI],p[Qmid],p[-1-QI],p[-1]))
+        except:
+            self.convergence.append((best, ))
 
 class SasProblem(object):
@@ -257 +281 @@
             run_bumps(problem, result, ftol,
                       handler, curr_thread, msg_q)
-        else:
+        else: # scipy levenburg marquardt
             problem = SasProblem(param_list=self.param_list,
                                  model=model.model,
@@ -292 +316 @@
     if 'monitors' not in options:
         options['monitors'] = [BumpsMonitor(handler, max_steps)]
+    options['monitors'] += [ ConvergenceMonitor() ]
     options['ftol'] = ftol
     fitdriver = fitters.FitDriver(fitclass, problem=problem,
@@ -312 +337 @@
     result.success = True
     result.theory = problem.theory
+    # For the convergence plot
+    pop = numpy.asarray(options['monitors'][-1].convergence)
+    result.convergence = 2*pop/problem.dof
+    # Bumps uncertainty state
+    try: result.uncertainty_state = fitdriver.fitter.state
+    except AttributeError: pass
 
 def run_levenburg_marquardt(problem, result, ftol):