REF remove 2to3

la/deflarry.py

@@ -126,7 +126,7 @@ def __init__(self, x, label=None, dtype=None, validate=True):
                     count = {}
                     for li in l:
                         count[li] = count.get(li, 0) + 1
-                    for key, value in count.iteritems():
+                    for key, value in count.items():
                         if value > 1:
                             break
                     msg = "Elements of label not unique along axis %d. "
@@ -2695,9 +2695,9 @@ def maplabel(self, func, axis=None, copy=True):
             y = self
         if axis is None:
             for ax in range(y.ndim):
-                y.label[ax] = map(func, y.label[ax])
+                y.label[ax] = list(map(func, y.label[ax]))
         else:
-            y.label[axis] = map(func, y.label[axis])
+            y.label[axis] = list(map(func, y.label[axis]))
         return y
 
     # Moving window statistics ----------------------------------------------
@@ -4480,9 +4480,9 @@ def totuples(self):
 
         """
         yf = self.flatten()
-        z = zip(*yf.label[0])
+        z = list(zip(*yf.label[0]))
         z.append(yf.x.tolist())
-        return zip(*z)
+        return list(zip(*z))
 
     @staticmethod
     def fromtuples(data):
@@ -4551,7 +4551,7 @@ def fromtuples(data):
             return larry([])
         else:
             # Split data into label and x
-            labels = zip(*data)
+            labels = list(zip(*data))
             xs = labels.pop(-1)
             # Determine labels, shape, and index into array
             x, label = fromlists(xs, labels)
@@ -4629,7 +4629,7 @@ def fromlist(data):
         if len(data) == 0:
             return larry([])
         else:
-            x, label = fromlists(data[0], zip(*data[1]))
+            x, label = fromlists(data[0], list(zip(*data[1])))
             return larry(x, label)
 
     def todict(self):
@@ -4699,7 +4699,7 @@ def fromdict(data):
                [ 3.,  4.]])
 
         """
-        return larry.fromlist([data.values(), data.keys()])
+        return larry.fromlist([list(data.values()), list(data.keys())])
 
     def tocsv(self, filename, delimiter=','):
         """
@@ -5166,7 +5166,7 @@ def slicemaker(index, labelindex, axis):
 def labels2indices(label, labels):
     "Convert list of labels to indices"
     try:
-        indices = map(label.index, labels)
+        indices = list(map(label.index, labels))
     except ValueError:
         raise ValueError('Could not map label to index value.')
     return indices

la/flabel.py

@@ -1,12 +1,5 @@
 "label (list of lists) functions"
 
-try:
-    import itertools.izip as zip
-except ImportError:  # Python 3
-    pass
-
-import numpy as np
-
 try:
     # The c version is faster...
     from la.cflabel import listmap

la/io.py

@@ -636,11 +636,11 @@ def _load_label(group, ndim):
             labellist = g[:].tolist()
             datetime_type = group[str(i)].attrs['datetime_type']
             if datetime_type == 'date':
-                labellist = map(datetime.date.fromordinal, labellist)
+                labellist = list(map(datetime.date.fromordinal, labellist))
             elif datetime_type == 'time':
-                labellist = map(tuple2time, labellist)
+                labellist = list(map(tuple2time, labellist))
             elif datetime_type == 'datetime':
-                labellist = map(tuple2datetime, labellist)
+                labellist = list(map(tuple2datetime, labellist))
         label.append(labellist)
     return label
 
@@ -658,14 +658,14 @@ def _list2array(x):
         msg += 'same type.'
         raise TypeError(msg)
     if type0 == datetime.date:
-        x = map(datetime.date.toordinal, x)
+        x = list(map(datetime.date.toordinal, x))
         datetime_type = 'date'
     elif type0 == datetime.time:
-        x = map(time2tuple, x)
+        x = list(map(time2tuple, x))
         datetime_type = 'time'
         dtype = "i4,i4,i4,i4"
     elif type0 == datetime.datetime:
-        x = map(datetime2tuple, x)
+        x = list(map(datetime2tuple, x))
         datetime_type = 'datetime'
         dtype = ','.join(["i4" for i in range(len(x[0]))])
     return np.asarray(x, dtype=dtype), datetime_type

la/tests/all_nan_test.py

@@ -25,7 +25,7 @@ def functions():
 def test_all_nan(): 
     "Test larry methods for proper handling of all NaN input"      
     err_msg = "%s did not return NaN"
-    for parameters, methods in functions().iteritems():
+    for parameters, methods in functions().items():
         for method in methods:
             with np.errstate(invalid='ignore', divide='ignore'):
                 actual = getattr(lar(), method)(*parameters)                    

la/tests/deflarry_nose_test.py

@@ -2,8 +2,12 @@
 # For support of python 2.5
 from __future__ import with_statement
 
+try:
+    from cStringIO import StringIO
+except ImportError: # Python 3
+    from io import StringIO
+
 from copy import deepcopy
-from StringIO import StringIO
 
 import numpy as np
 nan = np.nan

la/tests/deflarry_test.py

@@ -3538,7 +3538,7 @@ def take_test():
         y = la.rand(*shape)
         for axis in range(y.ndim):
             for i in range(1, y.shape[axis]):
-                idx = range(i)[::-1]
+                idx = list(range(i))[::-1]
                 ytake = y.take(idx, axis=axis)
                 index = [slice(None)] * y.ndim
                 index[axis] = idx

la/tests/empty_larry_test.py

@@ -186,7 +186,7 @@ def test_reduce_shape():
     msg = 'larry.%s failed for shape %s and axis %s'
     for method in reduce_methods():
         for shape in get_shapes():
-            axeslist = [None] + range(len(shape))
+            axeslist = [None] + list(range(len(shape)))
             for axis in axeslist:
                 arr = np.zeros(shape)
                 npmethod = getattr(arr, method['np'])

la/tests/flabel_test.py

@@ -20,7 +20,7 @@ def listmap_test():
     msg = "listmap failed on list1=%s and list2=%s and ignore_unmappable=%s"
     for i in range(100):
         np.random.shuffle(list2)
-        idx1 = map(list1.index, list2)
+        idx1 = list(map(list1.index, list2))
         idx2 = listmap(list1, list2)
         ignore_unmappable = False
         yield assert_equal, idx1, idx2, msg % (list1, list2, ignore_unmappable)
@@ -34,7 +34,7 @@ def listmap_unmappable_test():
         list1 = list(range(6))
         list2 = list(range(5))
         np.random.shuffle(list2)
-        idx1 = map(list1.index, list2)
+        idx1 = list(map(list1.index, list2))
         list2 = ['unmappable #1'] + list2 + ['unmappable #2']
         ignore_unmappable = True
         idx2 = listmap(list1, list2, ignore_unmappable=ignore_unmappable)
@@ -56,7 +56,7 @@ def listmap_fill_test():
     msg = "listmap_fill failed on list1=%s and list2=%s"
     for i in range(100):
         np.random.shuffle(list2)
-        idx1 = map(list1.index, list2)
+        idx1 = list(map(list1.index, list2))
         idx2, ignore = listmap_fill(list1, list2)
         yield assert_equal, idx1, idx2, msg % (list1, list2)            
 

la/util/misc.py

@@ -210,4 +210,3 @@ def fromlists(xs, labels):
         x.fill(np.nan)
         x[index] = xs 
     return x, label 
-

la/util/resample.py

@@ -53,7 +53,7 @@ def cross_validation(n, kfold, shuffle=None):
         raise ValueError("`kfold` must be two or greater.")
     if kfold > n:
         raise ValueError("`kfold` cannot be greater than `n`")
-    index = range(n)
+    index = list(range(n))
     if shuffle is None:
         np.random.shuffle(index)
     else:

la/util/tests/misc_test.py

@@ -30,7 +30,7 @@ def test_isa():
     t[(np.array(1)[()], 6)]   = (True,  False)
     t[(np.array(1.1)[()], 7)] = (False, True)
     t[(1j, 8)]                = (False, False)
-    for key, value in t.iteritems():
+    for key, value in t.items():
         key = key[0]
         msg = '\nisint(' + str(key) + ')'
         yield assert_equal, isint(key), value[0], msg

setup.py

@@ -4,11 +4,6 @@
 from distutils.core import setup
 from distutils.extension import Extension
 
-try:
-    from distutils.command.build_py import build_py_2to3 as build_py
-except ImportError:
-    from distutils.command.build_py import build_py
-
 CLASSIFIERS = ["Development Status :: 4 - Beta",
                "Environment :: Console",
                "Intended Audience :: Science/Research",
@@ -79,7 +74,6 @@
           package_data=PACKAGE_DATA,
           requires=REQUIRES,
           ext_modules = [Extension("la.cflabel", ["la/src/cflabel.c"])],
-          cmdclass={'build_py': build_py}
          )
 except SystemExit:
     # Probably clistmap.c failed to compile, so use slower python version
@@ -102,5 +96,4 @@
           packages=PACKAGES,
           package_data=PACKAGE_DATA,
           requires=REQUIRES,
-          cmdclass={'build_py': build_py}
          )