First changes to prepare to python 3.4

pymodelfit/__init__.py

@@ -25,5 +25,9 @@
           ('' if _bugfix is None else ('.'+str(_bugfix))) + \
           ('' if _release else 'dev')
 
-from core import *
-from builtins import * #do this to register all the builtins
+try:
+    from core import *
+    from builtins import * #do this to register all the builtins
+except:
+    from .core import *
+    from .builtins import * #do this to register all the builtins

pymodelfit/builtins.py

@@ -21,8 +21,12 @@
 
 import numpy as np
 #from core import * #includes pi
-from core import ParametricModel,FunctionModel,FunctionModel1DAuto, \
-                 DatacentricModel1DAuto,FunctionModel2DScalarAuto,register_model
+try:
+    from core import ParametricModel,FunctionModel,FunctionModel1DAuto, \
+                     DatacentricModel1DAuto,FunctionModel2DScalarAuto,register_model
+except:
+    from .core import ParametricModel,FunctionModel,FunctionModel1DAuto, \
+                     DatacentricModel1DAuto,FunctionModel2DScalarAuto,register_model
 from math import e,pi
 from abc import abstractmethod
 
@@ -1630,15 +1634,19 @@ def plot3d(self,data=np.array([(-1,1),(-1,1),(-1,1)]),n=10,
 
         M.mesh(x,y,self([x,y]),**kwargs)
         if showdata:
-            from operator import isMappingType
+            try:
+                from operator import isMappingType
+            except:
+                def isMappingType(x):
+                    return isinstance(x, collections.Mapping)
             if isMappingType(showdata):
                 M.points3d(*data,**showdata)
             else:
                 M.points3d(*data)
 
 #register everything in this module
 from inspect import isclass
-for o in locals().values():
+for o in list(locals().values()):
     if isclass(o) and not o.__name__.startswith('_') and issubclass(o,ParametricModel):
         if 'FunctionModel' not in o.__name__ and 'CompositeModel' not in o.__name__:
             register_model(o)

pymodelfit/core.py

@@ -24,8 +24,12 @@
 """
 
 from __future__ import division,with_statement
+from collections import Sequence
 from math import pi
 import numpy as np
+import sys
+import collections
+
 try:
     #requires Python 2.6
     from abc import ABCMeta
@@ -36,6 +40,26 @@
     abstractproperty = property
     ABCMeta = type
 
+try:
+    dict.iteritems
+except AttributeError:
+    # Python 3
+    basestring = str
+
+    def itervalues(d):
+        return iter(d.values())
+
+    def iteritems(d):
+        return iter(d.items())
+else:
+    # Python 2
+    def itervalues(d):
+        return d.itervalues()
+
+    def iteritems(d):
+        return d.iteritems()
+
+
 class ModelTypeError(Exception):
     """
     This exception indicates a problem with the value of the input
@@ -111,7 +135,8 @@ def _setData(self,val):
                     else:
                         ws = np.array(val[2],copy=False)
                     self._data = (ind,outd,ws)
-            except TypeError,e:
+            except TypeError:
+                e = sys.exc_info()[1]
                 e.args = ('invalid type for model data',)
                 raise
     data = property(_getData,_setData,doc="""
@@ -331,7 +356,8 @@ def __call__(cls,*args,**kwargs):
             objkwargs=dict([(k,kwargs.pop(k)) for k in kwargs.keys() if k not in cls._pars])
             try:
                 obj = super(AutoParamsMeta,AutoParamsMeta).__call__(cls,**objkwargs) #object __init__ is called here
-            except TypeError,e:
+            except TypeError:
+                e = sys.exc_info()[1]
                 if len(e.args)>0 and 'object.__new__() takes no parameters' == e.args[0]:
                     raise TypeError('invalid parameter in model constructor:'+str(objkwargs.keys()))
                 else:
@@ -591,7 +617,12 @@ def fitData(self,x=None,y=None,fixedpars='auto',weights=None,savedata=True,
         .. seealso:: :meth:`getMCMC`
         """
         from scipy import optimize as opt
-        from operator import isMappingType
+        try:
+            from operator import isMappingType
+        except:
+            def isMappingType(x):
+                return isinstance(x, collections.Mapping)
+
         from functools import partial
 
         self._fitchi2 = None #clear saved chi-squared if it exists
@@ -656,7 +687,11 @@ def fitData(self,x=None,y=None,fixedpars='auto',weights=None,savedata=True,
             res = fitter(x,y,fixedpars=fixedpars,weights=weights,**kwargs)
 
             #ensure that res is at least a tuple with parameters in elem 0
-            from operator import isSequenceType
+            try:
+                from operator import isSequenceType
+            except:
+                def isSequenceType(obj):
+                    return isinstance(obj, Sequence)
             if len(res)==0 or not isSequenceType(res[0]):
                 res = (res,)
 
@@ -1136,7 +1171,11 @@ def getMCMC(self,x,y,priors={},datamodel=None):
 
         """
         import pymc
-        from operator import isSequenceType
+        try:
+            from operator import isSequenceType
+        except:
+            def isSequenceType(obj):
+                return isinstance(obj, Sequence)
         from inspect import getargspec
         from types import MethodType
 
@@ -1572,9 +1611,9 @@ def inv(self,yval,*args,**kwargs):
             f = method
 
         if kwargs.pop('abs',False):
-            g = lambda(x):np.abs(self(x)-yval)
+            g = lambda x:np.abs(self(x)-yval)
         else:
-            g = lambda(x):self(x)-yval
+            g = lambda x:self(x)-yval
 
         return f(g,*args,**kwargs)
 
@@ -1783,7 +1822,12 @@ def plot(self,lower=None,upper=None,n=100,clf=True,logplot='',data='auto',
             `zorder` to 0.
 
         """
-        from operator import isMappingType
+        try:
+            from operator import isMappingType
+        except:
+            def isMappingType(x):
+                return isinstance(x, collections.Mapping)
+
         from .utils import mpl_context
 
         with mpl_context(clf=clf) as plt:
@@ -2516,7 +2560,11 @@ def __init__(self,models,extraparams=None,outputcontraction=None,
           linear interpolation, this takes the closest value.
 
         """
-        from operator import isMappingType
+        try:
+            from operator import isMappingType
+        except:
+            def isMappingType(x):
+                return isinstance(x, collections.Mapping)
 
         if len(models)==2 and isMappingType(models[1]):
             modtype = get_model_class(models[0])
@@ -3208,7 +3256,11 @@ def plot(self,datarange=None,nx=100,ny=100,clf=True,cb=True,data='auto',
         :except ValueError: if data is not present and `datarange` is None
 
         """
-        from operator import isMappingType
+        try:
+            from operator import isMappingType
+        except:
+            def isMappingType(x):
+                return isinstance(x, collections.Mapping)
         from .utils import mpl_context
 
         with mpl_context(clf=clf) as plt:
@@ -3284,7 +3336,11 @@ def plot3d(self,datarange=None,nx=100,ny=100,clf=True,cb=True,data='auto',**kwar
         See :meth:`plot` for meaning of the arguments
         """
         from enthought.mayavi import mlab as M
-        from operator import isMappingType
+        try:
+            from operator import isMappingType
+        except:
+            def isMappingType(x):
+                return isinstance(x, collections.Mapping)
 
         if data == 'auto':
             if self.data:
@@ -3778,7 +3834,9 @@ def get_model_instance(model,baseclass=None,nvarparams=1,**kwargs):
         return cls(*args,**kwargs)
 
 
-def list_models(include=None,exclude=None,baseclass=None,showabstract=False):
+def list_models(
+    include=None, exclude=None, baseclass=None, showabstract=False
+):
     """
     Lists the registered model objects in the package, possibly subject to
     constraints.
@@ -3808,17 +3866,23 @@ def list_models(include=None,exclude=None,baseclass=None,showabstract=False):
     See the :func:`register_model` docstring for examples.
 
     """
-    from operator import isSequenceType
-    from inspect import isclass,isabstract
+    try:
+        from operator import isSequenceType
+    except:
+        def isSequenceType(obj):
+            return isinstance(obj, Sequence)
+    from inspect import isclass, isabstract
 
-    res = [k for k,c in __model_registry.iteritems()
-                     if (baseclass is None or issubclass(c,baseclass))
-                     if (showabstract or not isabstract(c))]
+    res = [
+        k for k, c in iteritems(__model_registry)
+        if (baseclass is None or issubclass(c, baseclass))
+        if (showabstract or not isabstract(c))
+    ]
 
     if include is not None:
         if exclude is not None:
             raise TypeError("can't specify both included models and excluded models")
-        if isinstance(include,basestring):
+        if isinstance(include, basestring):
             include = include.split(',')
         elif not isSequenceType(include):
             include = [include]

pymodelfit/fitgui.py

@@ -18,7 +18,11 @@
 #TODO: change single select to click-to-do-action
 
 from __future__ import division,with_statement
+from collections import Sequence
 import numpy as np
+import sys
+import collections
+
 try: #this is the old-style import - below is for traits 4.x
     from enthought.traits.api import HasTraits,Instance,Int,Float,Bool,Button, \
                                      Event,Property,on_trait_change,Array,List, \
@@ -175,8 +179,17 @@ def _updatetraitparams_fired(self):
             setattr(self,p,getattr(m,p))
         self.paramchange = True
 
-    def _fitdata_fired(self,new):
-        from operator import isSequenceType,isMappingType
+    def _fitdata_fired(self, new):
+        try:
+            from operator import isSequenceType
+        except:
+            def isSequenceType(obj):
+                return isinstance(obj, Sequence)
+        try:
+            from operator import isMappingType
+        except:
+            def isMappingType(x):
+                return isinstance(x, collections.Mapping)
 
         if self.model is not None:
             if isSequenceType(new) and len(new) == 2:
@@ -208,8 +221,8 @@ def _fitdata_fired(self,new):
                 self.model.fitData(**kw)
                 self.updatetraitparams = True
                 self.lastfitfailure = None
-            except Exception,e:
-                self.lastfitfailure = e
+            except Exception:
+                self.lastfitfailure = sys.exc_info()[1]
 
     def _get_modelname(self):
         if self.model is None:
@@ -1060,4 +1073,4 @@ def fit_data(*args,**kwargs):
     if res:
         return fg.getModelObject()
     else:
-        return None
+        return None

setup.py

@@ -3,9 +3,23 @@
 from __future__ import division,with_statement
 
 from glob import glob
-from distribute_setup import use_setuptools
-use_setuptools()
-from setuptools import setup,find_packages
+#from distribute_setup import use_setuptools
+#use_setuptools()
+#from setuptools import setup,find_packages
+try:
+    import pkg_resources
+    try:
+        pkg_resources.require("setuptools>=0.6c5")
+    except pkg_resources.VersionConflict:
+        from ez_setup import use_setuptools
+        use_setuptools(version="0.6c5")
+    from setuptools import setup, Command,find_packages
+    _have_setuptools = True
+except ImportError:
+    # no setuptools installed
+    from distutils.core import setup, Command,find_packages
+    _have_setuptools = False
+
 from distutils.command.build_py import build_py as du_build_py
 
 from pymodelfit import version as versionstr
@@ -53,5 +67,6 @@ def finalize_options(self):
       license = 'Apache License 2.0',
       url='http:http://packages.python.org/PyModelFit/',
       long_description=descrip,
-      cmdclass = cmdclassd
+      cmdclass = cmdclassd,
+      use_2to3=True
      )