Fixes by Eric Firing..

THANKS.txt

@@ -8,3 +8,4 @@ Fernando Perez for code snippets and ideas
 John Hunter for code snippets (from matplotlib)
 Chris Hanley for help with records.py, testing, and bug fixes.
 Travis Vaught and Joe Cooper for administration of scipy.org web site and SVN 
+Eric Firing for bugfixes.

scipy/base/function_base.py

@@ -553,31 +553,31 @@ def nanmin(x,axis=-1):
     """
     y = array(x)
     if not issubclass(y.dtype, _nx.integer):
-        y[isnan(x)] = nx.inf
+        y[isnan(x)] = _nx.inf
     return y.min(axis)
 
 def nanargmin(x,axis=-1):
     """Find the indices of the minimium over the given axis ignoring nans.
     """
     y = array(x)
     if not issubclass(y.dtype, _nx.integer):
-        y[isnan(x)] = nx.inf    
+        y[isnan(x)] = _nx.inf    
     return y.argmin(axis)    
 
 def nanmax(x,axis=-1):
     """Find the maximum over the given axis ignoring nans.
     """
     y = array(x)
     if not issubclass(y.dtype, _nx.integer):
-        y[isnan(x)] = -nx.inf    
+        y[isnan(x)] = -_nx.inf    
     return y.max(axis)    
 
 def nanargmax(x,axis=-1):
     """Find the maximum over the given axis ignoring nans.
     """
     y = array(x)
     if not issubclass(y.dtype, _nx.integer):
-        y[isnan(x)] = -nx.inf    
+        y[isnan(x)] = -_nx.inf    
     return y.argmax(axis)    
 
 def disp(mesg, device=None, linefeed=1):

scipy/base/matrix.py

@@ -1,6 +1,7 @@
 
 import numeric as N
 from numeric import ArrayType, concatenate, integer
+from type_check import isscalar
 from function_base import binary_repr
 import types
 import string as str_
@@ -103,20 +104,24 @@ def _update_meta(self, obj):
         return
 
     def __getitem__(self, index):
-        out = (self.A)[index]
-        # Need to swap if slice is on first index
+        out = N.ndarray.__getitem__(self, index)
+        # Need to swap if slice is on first inde
+        retscal = False
         try:
             n = len(index)
-            if (n > 1) and isinstance(index[0], types.SliceType):
-                if (isinstance(index[1], types.IntType) or
-                    isinstance(index[1], types.LongType) or
-                    isinstance(index[1], integer)):
-                    sh = out.shape
-                    out.shape = (sh[1], sh[0])
-                return matrix(out)
-            return out
+            if (n==2):
+                if isinstance(index[0], types.SliceType):
+                    if (isscalar(index[1])):
+                        sh = out.shape
+                        out.shape = (sh[1], sh[0])
+                else:
+                    if (isscalar(index[0])) and (isscalar(index[1])):
+                        retscal = True
         except TypeError:
-            return matrix(out)
+            pass
+        if retscal and out.shape == (1,1): # convert scalars
+            return out.A[0,0]
+        return out
 
     def __mul__(self, other):
         if isinstance(other, N.ndarray) and other.ndim == 0:

scipy/base/numeric.py

@@ -98,6 +98,7 @@ def convolve(a,v,mode='full'):
     return correlate(a,asarray(v)[::-1],mode)
 
 ndarray = multiarray.ndarray
+ndbigarray = multiarray.ndbigarray
 ufunc = type(sin)
 
 inner = multiarray.inner

scipy/base/numerictypes.py

@@ -333,9 +333,9 @@ def __getitem__(self, obj):
         return dict.__getitem__(self, obj2dtype(obj))
 
 cast = _castdict()
-ScalarType = [_types.IntType, _types.LongType, _types.FloatType,
-              _types.StringType, _types.UnicodeType, _types.ComplexType,
-              _types.BufferType]
+ScalarType = [_types.IntType, _types.FloatType,
+              _types.ComplexType, _types.LongType, _types.BooleanType,
+              _types.StringType, _types.UnicodeType, _types.BufferType]
 ScalarType.extend(_dtype2char_dict.keys())
 for key in _dtype2char_dict.keys():
     cast[key] = lambda x, k=key : array(x,copy=0).astype(k)

scipy/base/oldnumeric.py

@@ -188,6 +188,9 @@ def resize(a, new_shape):
     """resize(a,new_shape) returns a new array with the specified shape.
     The original array's total size can be any size. It
     fills the new array with repeated copies of a.
+
+    Note that a.resize(new_shape) will fill array with 0's
+    beyond current definition of a. 
     """
 
     a = ravel(a)

scipy/base/src/arraymethods.c

@@ -69,7 +69,10 @@ _reverse_shape(PyArray_Dims *newshape)
 	}
 }
 
-static char doc_reshape[] = "a.reshape(d1, d2, ..., dn).  Change the shape of a to be an n-dimensional array with dimensions given by d1...dn.  Note: the size specified for the new array must be exactly equal to the size of the  old one or an error will occur.";
+static char doc_reshape[] = \
+	"self.reshape(d1, d2, ..., dn) Return a new array from this one. \n" \
+	"\n  The new array must have the same number of elements as self. "\
+	"Also\n   a copy of the data only occurs if necessary.";
 
 static PyObject *
 array_reshape(PyArrayObject *self, PyObject *args) 
@@ -463,9 +466,10 @@ array_copy(PyArrayObject *self, PyObject *args)
         return _ARET(PyArray_Copy(self));
 }
 
-static char doc_resize[] = "m.resize(new_shape). Return a resized version "\
-	"of the array.\n\nMust own its own memory be single segment and not be referenced by "\
-	"other arrays.";
+static char doc_resize[] = "self.resize(new_shape).  "\
+	"Change size and shape of self inplace.\n"\
+	"\n    Array must own its own memory and not be referenced by other " \
+	"arrays\n    Returns None.";
 
 static PyObject *
 array_resize(PyArrayObject *self, PyObject *args) 
@@ -490,7 +494,9 @@ array_resize(PyArrayObject *self, PyObject *args)
 	}
 	ret = PyArray_Resize(self, &newshape);
         PyDimMem_FREE(newshape.ptr);
-        return _ARET(ret);
+	Py_DECREF(ret);
+	Py_INCREF(Py_None);
+	return Py_None;
 }
 
 static char doc_repeat[] = "a.repeat(repeats=, axis=None)";

scipy/base/src/multiarraymodule.c

@@ -3910,6 +3910,13 @@ DL_EXPORT(void) initmultiarray(void) {
 		return;
 
         PyArray_Type.tp_base = &PyBigArray_Type;
+
+        PyArray_Type.tp_as_mapping = &array_as_mapping;
+	/* Even though, this would be inherited, it needs to be set now
+	   so that the __getitem__ will map to the as_mapping descriptor
+	*/
+        PyArray_Type.tp_as_number = &array_as_number;               
+	/* For good measure */
 	PyArray_Type.tp_as_sequence = &array_as_sequence;
 	PyArray_Type.tp_as_buffer = &array_as_buffer;	
         PyArray_Type.tp_flags = (Py_TPFLAGS_DEFAULT