Index: /issm/trunk-jpl/src/m/classes/qmu.py
===================================================================
--- /issm/trunk-jpl/src/m/classes/qmu.py	(revision 25648)
+++ /issm/trunk-jpl/src/m/classes/qmu.py	(revision 25649)
@@ -1,3 +1,4 @@
 import numpy as np
+
 from collections import OrderedDict
 from dakota_method import *
@@ -6,4 +7,5 @@
 from IssmConfig import *
 from MatlabFuncs import *
+from qmustatistics import qmustatistics
 from WriteData import WriteData
 
@@ -25,5 +27,5 @@
         self.method = OrderedDict()
         self.params = OrderedStruct()
-        self.statistics = OrderedStruct() # TODO: Replace this with 'qmustatistics()' once class is translated
+        self.statistics = qmustatistics()
         self.results = OrderedDict()
         self.numberofresponses = 0
@@ -218,6 +220,4 @@
             flag = False
         WriteData(fid, prefix, 'data', flag, 'name', 'md.qmu.mass_flux_segments_present', 'format', 'Boolean')
-        # TODO: Uncomment this and remove the following line once qmustatistics class is translated
-        #self.statistics.marshall
-        WriteData(fid,prefix,'name','md.qmu.statistics','data',0,'format','Boolean');
+        self.statistics.marshall(prefix, md, fid)
     # }}}
Index: /issm/trunk-jpl/src/m/classes/qmustatistics.m
===================================================================
--- /issm/trunk-jpl/src/m/classes/qmustatistics.m	(revision 25648)
+++ /issm/trunk-jpl/src/m/classes/qmustatistics.m	(revision 25649)
@@ -72,5 +72,5 @@
 				for s=1:length(m.steps),
 					if m.steps(s)<=0,
-						error(sprintf('qmustatistics consistency check error: qmu.statistics.method(%i).steps(%i) should be >0!',i,s));
+						error(sprintf('qmustatistics consistency check error: qmu.statistics.method(%i).steps(%i) should be > 0!',i,s));
 					end
 					if m.steps(s)> md.mesh.numberofvertices
Index: /issm/trunk-jpl/src/m/classes/qmustatistics.py
===================================================================
--- /issm/trunk-jpl/src/m/classes/qmustatistics.py	(revision 25649)
+++ /issm/trunk-jpl/src/m/classes/qmustatistics.py	(revision 25649)
@@ -0,0 +1,137 @@
+# NOTE: Uncomment 
+
+import numpy as np
+
+from helpers import *
+from WriteData import WriteData
+
+
+class qmustatistics(object):
+    """QMUSTATISTICS class definition
+
+    Usage:
+        stats = qmustatistics()
+    """
+
+    def __init__(self, *args):  #{{{
+        self.nfiles_per_directory   = 5 # Number of files per output directory
+        self.ndirectories           = 50 # Number of output directories; should be < numcpus
+
+        self.method = [{}]
+        self.method[0]['name'] = 'None'
+        self.method[0]['fields'] = []
+        self.method[0]['steps'] = []
+        self.method[0]['nbins'] = np.nan
+        self.method[0]['indices'] = []
+
+        # name : name of method, one of 'None', 'Histogram', 'SampleSeries', or 'MeanVariance'
+        # fields : fields for the statistics being requested, ex: 'Sealevel', 'BslrIce', 'BsrlHydro'
+        # steps : time steps at which each field statistic is computed, ex: [1, 2, 5, 20] or [range(1:100)]
+        # nbins : number of bins for 'Histgogram' statistics
+        # indices : vertex indices at which to retrieve samples
+
+        nargs = len(args)
+
+        if nargs == 0:
+            # Create a default object
+            self.setdefaultparameters()
+        elif nargs == 1:
+            # NOTE: The following has not been tested. Remove this note when it has.
+            inputstruct = args[0]
+            list1 = properties('qmustatistics')
+            list2 = fieldnames(inputstruct)
+            for i in range(len(list1)):
+                fieldname = list1[i]
+                if fieldname in list2:
+                    setattr(self, fieldname, getattr(inputstruct, fieldname))
+        else:
+            raise Exception('constructor not supported')
+    #}}}
+
+    def __repr__(self):  # {{{
+        s = '{}\n'.format('qmustatistics: post-Dakota run processing of QMU statistics:')
+
+        if self.method[0]['name'] == 'None':
+            return
+
+        s += '{}\n'.format(fielddisplay(self, 'nfiles_per_directory', 'number of files per output directory'))
+        s += '{}\n'.format(fielddisplay(self, 'ndirectories', 'number of output directories; should be < numcpus'))
+
+        for i in range(len(self.method)):
+            s += '{}\n'.format('   method # {}'.format(i))
+            s += '{}\n'.format(self.method[i])
+
+        return s
+    #}}}
+
+    def setdefaultparameters(self):  # {{{
+        self.method[0]['name'] = 'None'
+        self.nfiles_per_directory   = 5 # Number of files per output directory
+        self.ndirectories           = 50 # Number of output directories; should be < numcpus
+    #}}}
+
+    @staticmethod
+    def checkconsistency(self, md, solution, analyses):  # {{{
+        # Early return
+        if md.qmu.isdakota == 0:
+            return
+        if self.method[0]['name'] == 'None':
+            return
+
+        # Checks
+        md = checkfield(md, 'fieldname', 'qmu.statistics.nfiles_per_directory', '>=', 1)
+        if self.ndirectories > md.cluster.np:
+            raise Exception('qmustatistics consistency check: number of cluster CPUs should be > number of output directories')
+        if self.ndirectories * self.nfiles_per_directory != md.qmu.method.params.sample:
+            raise Exception('qmustatistics consistency check: number of directories x number of files per directory should be == to number of samples requested!')
+        for i in range(len(self.method)):
+            m = self.method[i]
+            if m.name == 'Histogram':
+                md = checkfield(md, 'fieldname', 'qmu.statistics.method[{}].nbins'.format(i), '>=', 1, '<=', md.qmu.method.params.samples)
+            for f in range(len(m['fields'])):
+                if not isinstance(m['fields'][f], str):
+                    raise Exception('qmustatistics consistency check error: qmu.statistics.method[{}][\'fields\'[{}] is not a string!'.format(i, f))
+            for s in range(len(m['steps'])):
+                if m['steps'][s] <= 0:
+                    raise Exception('qmustatistics consistency check error: qmu.statistics.method[{}][\'steps\'[{}] should be > 0!'.format(i, s))
+                if m['steps'][s] > md.mesh.numberofvertices:
+                    raise Exception('qmustatistics consistency check error: qmu.statistics.method[{}][\'steps\'[{}] should be < md.mesh.numberofvertices!'.format(i, s))
+    #}}}
+
+    def defaultoutputs(self, md): #{{{
+        outputs = []
+        return outputs
+    #}}}
+
+    def marshall(self, prefix, md, fid): #{{{
+        if self.method[0]['name'] == 'None':
+            WriteData(fid, prefix, 'name', 'md.qmu.statistics', 'data', 0, 'format', 'Boolean')
+            statistics = 0
+            return
+        else:
+            WriteData(fid, prefix, 'name', 'md.qmu.statistics', 'data', 1, 'format', 'Boolean')
+            statistics = 1
+
+        if statistics:
+            WriteData(fid, prefix, 'name', 'md.qmu.statistics.nfiles_per_directory', 'data', self.nfiles_per_directory, 'format', 'Integer')
+            WriteData(fid, prefix, 'name', 'md.qmu.statistics.ndirectories', 'data', self.ndirectories, 'format', 'Integer')
+            WriteData(fid, prefix, 'name', 'md.qmu.statistics.numstatistics', 'data', len(self.method), 'format', 'Integer')
+            for i in range(len(self.method)):
+                m = self.method[i]
+                WriteData(fid, prefix, 'name', 'md.qmu.statistics.method[{}][\'name\']'.format(i), 'data', m['name'], 'Format', 'String')
+                WriteData(fid, prefix, 'data', m['fields'], 'name', 'md.qmu.statistics.method[{}][\'fields\']'.format(i), 'format', 'StringArray')
+                WriteData(fid, prefix, 'data', m['steps'], 'name', 'md.qmu.statistics.method[{}][\'steps\']'.format(i), 'format', 'IntMat', 'mattype', 3)
+
+                if m['name'] == 'Histogram':
+                    WriteData(fid, prefix, 'name', 'md.qmu.statistics.method[{}][\'nbins\']'.format(i), 'data', m['nbins'], 'format', 'Integer')
+                elif m['name'] == 'MeanVariance':
+                    pass # do nothing
+                elif m['name'] == 'SampleSeries':
+                    WriteData(fid, prefix, 'data', m['indices'], 'name', 'md.qmu.statistics.method[{}][\'indices\']'.format(i), 'format', 'IntMat', 'mattype', 3)
+                else:
+                    raise Exception('qmustatistics marshall error message: unknown type ''{}'' for qmu.statistics.method[{}]'.format(m['name'], i))
+    #}}}
+
+    def extrude(self, md): #{{{
+        return self
+    #}}}