STY: Update exception style, easy ones.

33 files changed, 193 insertions, 193 deletions

diff --git a/numpy/core/defchararray.py b/numpy/core/defchararray.py
index 3facd08fa..850e2dae2 100644
--- a/numpy/core/defchararray.py
+++ b/numpy/core/defchararray.py
@@ -301,7 +301,7 @@ def multiply(a, i):
     a_arr = numpy.asarray(a)
     i_arr = numpy.asarray(i)
     if not issubclass(i_arr.dtype.type, integer):
-        raise ValueError, "Can only multiply by integers"
+        raise ValueError("Can only multiply by integers")
     out_size = _get_num_chars(a_arr) * max(long(i_arr.max()), 0)
     return _vec_string(
         a_arr, (a_arr.dtype.type, out_size), '__mul__', (i_arr,))
@@ -1660,7 +1660,7 @@ def isnumeric(a):
     unicode.isnumeric
     """
     if _use_unicode(a) != unicode_:
-        raise TypeError, "isnumeric is only available for Unicode strings and arrays"
+        raise TypeError("isnumeric is only available for Unicode strings and arrays")
     return _vec_string(a, bool_, 'isnumeric')
 
 def isdecimal(a):
@@ -1688,7 +1688,7 @@ def isdecimal(a):
     unicode.isdecimal
     """
     if _use_unicode(a) != unicode_:
-        raise TypeError, "isnumeric is only available for Unicode strings and arrays"
+        raise TypeError("isnumeric is only available for Unicode strings and arrays")
     return _vec_string(a, bool_, 'isdecimal')
 
 
@@ -1872,7 +1872,7 @@ class chararray(ndarray):
     def __array_finalize__(self, obj):
         # The b is a special case because it is used for reconstructing.
         if not _globalvar and self.dtype.char not in 'SUbc':
-            raise ValueError, "Can only create a chararray from string data."
+            raise ValueError("Can only create a chararray from string data.")
 
     def __getitem__(self, obj):
         val = ndarray.__getitem__(self, obj)
diff --git a/numpy/core/memmap.py b/numpy/core/memmap.py
index 844e13c4e..c445ee641 100644
--- a/numpy/core/memmap.py
+++ b/numpy/core/memmap.py
@@ -193,7 +193,7 @@ class memmap(ndarray):
             fid = open(filename, (mode == 'c' and 'r' or mode)+'b')
 
         if (mode == 'w+') and shape is None:
-            raise ValueError, "shape must be given"
+            raise ValueError("shape must be given")
 
         fid.seek(0, 2)
         flen = fid.tell()
diff --git a/numpy/core/numeric.py b/numpy/core/numeric.py
index 2dace5de1..6891ea768 100644
--- a/numpy/core/numeric.py
+++ b/numpy/core/numeric.py
@@ -977,7 +977,7 @@ def tensordot(a, b, axes=2):
             if axes_b[k] < 0:
                 axes_b[k] += ndb
     if not equal:
-        raise ValueError, "shape-mismatch for sum"
+        raise ValueError("shape-mismatch for sum")
 
     # Move the axes to sum over to the end of "a"
     # and to the front of "b"
@@ -2279,7 +2279,7 @@ def seterrcall(func):
     """
     if func is not None and not callable(func):
         if not hasattr(func, 'write') or not callable(func.write):
-            raise ValueError, "Only callable can be used as callback"
+            raise ValueError("Only callable can be used as callback")
     pyvals = umath.geterrobj()
     old = geterrcall()
     pyvals[2] = func
diff --git a/numpy/core/numerictypes.py b/numpy/core/numerictypes.py
index 8874667d8..7bdfd98c1 100644
--- a/numpy/core/numerictypes.py
+++ b/numpy/core/numerictypes.py
@@ -842,7 +842,7 @@ def sctype2char(sctype):
     """
     sctype = obj2sctype(sctype)
     if sctype is None:
-        raise ValueError, "unrecognized type"
+        raise ValueError("unrecognized type")
     return _sctype2char_dict[sctype]
 
 # Create dictionary of casting functions that wrap sequences
diff --git a/numpy/core/records.py b/numpy/core/records.py
index 58cead0d9..25d6f9513 100644
--- a/numpy/core/records.py
+++ b/numpy/core/records.py
@@ -149,7 +149,7 @@ class format_parser:
         """ Parse the field formats """
 
         if formats is None:
-            raise ValueError, "Need formats argument"
+            raise ValueError("Need formats argument")
         if isinstance(formats, list):
             if len(formats) < 2:
                 formats.append('')
@@ -528,7 +528,7 @@ def fromarrays(arrayList, dtype=None, shape=None, formats=None,
         formats = ''
         for obj in arrayList:
             if not isinstance(obj, ndarray):
-                raise ValueError, "item in the array list must be an ndarray."
+                raise ValueError("item in the array list must be an ndarray.")
             formats += _typestr[obj.dtype.type]
             if issubclass(obj.dtype.type, nt.flexible):
                 formats += `obj.itemsize`
@@ -618,7 +618,7 @@ def fromrecords(recList, dtype=None, shape=None, formats=None, names=None,
         if isinstance(shape, (int, long)):
             shape = (shape,)
         if len(shape) > 1:
-            raise ValueError, "Can only deal with 1-d array."
+            raise ValueError("Can only deal with 1-d array.")
         _array = recarray(shape, descr)
         for k in xrange(_array.size):
             _array[k] = tuple(recList[k])
@@ -639,7 +639,7 @@ def fromstring(datastring, dtype=None, shape=None, offset=0, formats=None,
 
 
     if dtype is None and formats is None:
-        raise ValueError, "Must have dtype= or formats="
+        raise ValueError("Must have dtype= or formats=")
 
     if dtype is not None:
         descr = sb.dtype(dtype)
diff --git a/numpy/ctypeslib.py b/numpy/ctypeslib.py
index 1fdf3c396..1868ee0c9 100644
--- a/numpy/ctypeslib.py
+++ b/numpy/ctypeslib.py
@@ -72,7 +72,7 @@ if ctypes is None:
             If ctypes is not available.
 
         """
-        raise ImportError, "ctypes is not available."
+        raise ImportError("ctypes is not available.")
     ctypes_load_library = _dummy
     load_library = _dummy
     as_ctypes = _dummy
@@ -163,7 +163,7 @@ class _ndptr(_ndptr_base):
     @classmethod
     def from_param(cls, obj):
         if not isinstance(obj, ndarray):
-            raise TypeError, "argument must be an ndarray"
+            raise TypeError("argument must be an ndarray")
         if cls._dtype_ is not None \
                and obj.dtype != cls._dtype_:
             raise TypeError, "array must have data type %s" % cls._dtype_
@@ -251,7 +251,7 @@ def ndpointer(dtype=None, ndim=None, shape=None, flags=None):
             try:
                 flags = [x.strip().upper() for x in flags]
             except:
-                raise TypeError, "invalid flags specification"
+                raise TypeError("invalid flags specification")
             num = _num_fromflags(flags)
     try:
         return _pointer_type_cache[(dtype, ndim, shape, num)]
diff --git a/numpy/f2py/tests/test_array_from_pyobj.py b/numpy/f2py/tests/test_array_from_pyobj.py
index ccf237ee1..e760e8e4e 100644
--- a/numpy/f2py/tests/test_array_from_pyobj.py
+++ b/numpy/f2py/tests/test_array_from_pyobj.py
@@ -301,7 +301,7 @@ class _test_shared_memory:
             if not str(msg).startswith('failed to initialize intent(inout|inplace|cache) array'):
                 raise
         else:
-            raise SystemError,'intent(inout) should have failed on sequence'
+            raise SystemError('intent(inout) should have failed on sequence')
 
     def test_f_inout_23seq(self):
         obj = array(self.num23seq,dtype=self.type.dtype,order='F')
@@ -317,7 +317,7 @@ class _test_shared_memory:
             if not str(msg).startswith('failed to initialize intent(inout) array'):
                 raise
         else:
-            raise SystemError,'intent(inout) should have failed on improper array'
+            raise SystemError('intent(inout) should have failed on improper array')
 
     def test_c_inout_23seq(self):
         obj = array(self.num23seq,dtype=self.type.dtype)
@@ -402,7 +402,7 @@ class _test_shared_memory:
                 if not str(msg).startswith('failed to initialize intent(cache) array'):
                     raise
             else:
-                raise SystemError,'intent(cache) should have failed on multisegmented array'
+                raise SystemError('intent(cache) should have failed on multisegmented array')
     def test_in_cache_from_2casttype_failure(self):
         for t in self.type.all_types():
             if t.elsize >= self.type.elsize:
@@ -415,7 +415,7 @@ class _test_shared_memory:
                 if not str(msg).startswith('failed to initialize intent(cache) array'):
                     raise
             else:
-                raise SystemError,'intent(cache) should have failed on smaller array'
+                raise SystemError('intent(cache) should have failed on smaller array')
 
     def test_cache_hidden(self):
         shape = (2,)
@@ -433,7 +433,7 @@ class _test_shared_memory:
             if not str(msg).startswith('failed to create intent(cache|hide)|optional array'):
                 raise
         else:
-            raise SystemError,'intent(cache) should have failed on undefined dimensions'
+            raise SystemError('intent(cache) should have failed on undefined dimensions')
 
     def test_hidden(self):
         shape = (2,)
@@ -460,7 +460,7 @@ class _test_shared_memory:
             if not str(msg).startswith('failed to create intent(cache|hide)|optional array'):
                 raise
         else:
-            raise SystemError,'intent(hide) should have failed on undefined dimensions'
+            raise SystemError('intent(hide) should have failed on undefined dimensions')
 
     def test_optional_none(self):
         shape = (2,)
diff --git a/numpy/fft/fftpack.py b/numpy/fft/fftpack.py
index 7f9ee57fd..2f19ba3d8 100644
--- a/numpy/fft/fftpack.py
+++ b/numpy/fft/fftpack.py
@@ -509,7 +509,7 @@ def _cook_nd_args(a, s=None, axes=None, invreal=0):
     if axes is None:
         axes = range(-len(s), 0)
     if len(s) != len(axes):
-        raise ValueError, "Shape and axes have different lengths."
+        raise ValueError("Shape and axes have different lengths.")
     if invreal and shapeless:
         s[axes[-1]] = (s[axes[-1]] - 1) * 2
     return s, axes
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py
index 0709499ea..df579a539 100644
--- a/numpy/lib/function_base.py
+++ b/numpy/lib/function_base.py
@@ -3049,7 +3049,7 @@ def _compute_qth_percentile(sorted, q, axis, out):
 
     q = q / 100.0
     if (q < 0) or (q > 1):
-        raise ValueError, "percentile must be either in the range [0,100]"
+        raise ValueError("percentile must be either in the range [0,100]")
 
     indexer = [slice(None)] * sorted.ndim
     Nx = sorted.shape[axis]
diff --git a/numpy/lib/index_tricks.py b/numpy/lib/index_tricks.py
index 69539d482..24c7bde90 100644
--- a/numpy/lib/index_tricks.py
+++ b/numpy/lib/index_tricks.py
@@ -70,7 +70,7 @@ def ix_(*args):
     for k in range(nd):
         new = _nx.asarray(args[k])
         if (new.ndim != 1):
-            raise ValueError, "Cross index must be 1 dimensional"
+            raise ValueError("Cross index must be 1 dimensional")
         if issubclass(new.dtype.type, _nx.bool_):
             new = new.nonzero()[0]
         baseshape[k] = len(new)
@@ -283,12 +283,12 @@ class AxisConcatenator(object):
                             trans1d = int(vec[2])
                         continue
                     except:
-                        raise ValueError, "unknown special directive"
+                        raise ValueError("unknown special directive")
                 try:
                     self.axis = int(key[k])
                     continue
                 except (ValueError, TypeError):
-                    raise ValueError, "unknown special directive"
+                    raise ValueError("unknown special directive")
             elif type(key[k]) in ScalarType:
                 newobj = array(key[k],ndmin=ndmin)
                 scalars.append(k)
diff --git a/numpy/lib/npyio.py b/numpy/lib/npyio.py
index 1dadc0d1a..da8074f97 100644
--- a/numpy/lib/npyio.py
+++ b/numpy/lib/npyio.py
@@ -45,7 +45,7 @@ def seek_gzip_factory(f):
                 offset = self.offset + offset
 
             if whence not in [0, 1]:
-                raise IOError, "Illegal argument"
+                raise IOError("Illegal argument")
 
             if offset < self.offset:
                 # for negative seek, rewind and do positive seek
diff --git a/numpy/lib/polynomial.py b/numpy/lib/polynomial.py
index 94da4784c..47078ae88 100644
--- a/numpy/lib/polynomial.py
+++ b/numpy/lib/polynomial.py
@@ -125,7 +125,7 @@ def poly(seq_of_zeros):
     elif len(sh) == 1:
         pass
     else:
-        raise ValueError, "input must be 1d or square 2d array."
+        raise ValueError("input must be 1d or square 2d array.")
 
     if len(seq_of_zeros) == 0:
         return 1.0
@@ -198,7 +198,7 @@ def roots(p):
     # If input is scalar, this makes it an array
     p = atleast_1d(p)
     if len(p.shape) != 1:
-        raise ValueError,"Input must be a rank-1 array."
+        raise ValueError("Input must be a rank-1 array.")
 
     # find non-zero array entries
     non_zero = NX.nonzero(NX.ravel(p))[0]
@@ -299,7 +299,7 @@ def polyint(p, m=1, k=None):
     """
     m = int(m)
     if m < 0:
-        raise ValueError, "Order of integral must be positive (see polyder)"
+        raise ValueError("Order of integral must be positive (see polyder)")
     if k is None:
         k = NX.zeros(m, float)
     k = atleast_1d(k)
@@ -377,7 +377,7 @@ def polyder(p, m=1):
     """
     m = int(m)
     if m < 0:
-        raise ValueError, "Order of derivative must be positive (see polyint)"
+        raise ValueError("Order of derivative must be positive (see polyint)")
 
     truepoly = isinstance(p, poly1d)
     p = NX.asarray(p)
@@ -531,15 +531,15 @@ def polyfit(x, y, deg, rcond=None, full=False):
 
     # check arguments.
     if deg < 0 :
-        raise ValueError, "expected deg >= 0"
+        raise ValueError("expected deg >= 0")
     if x.ndim != 1:
-        raise TypeError, "expected 1D vector for x"
+        raise TypeError("expected 1D vector for x")
     if x.size == 0:
-        raise TypeError, "expected non-empty vector for x"
+        raise TypeError("expected non-empty vector for x")
     if y.ndim < 1 or y.ndim > 2 :
-        raise TypeError, "expected 1D or 2D array for y"
+        raise TypeError("expected 1D or 2D array for y")
     if x.shape[0] != y.shape[0] :
-        raise TypeError, "expected x and y to have same length"
+        raise TypeError("expected x and y to have same length")
 
     # set rcond
     if rcond is None :
@@ -1010,7 +1010,7 @@ class poly1d(object):
             c_or_r = poly(c_or_r)
         c_or_r = atleast_1d(c_or_r)
         if len(c_or_r.shape) > 1:
-            raise ValueError, "Polynomial must be 1d only."
+            raise ValueError("Polynomial must be 1d only.")
         c_or_r = trim_zeros(c_or_r, trim='f')
         if len(c_or_r) == 0:
             c_or_r = NX.array([0.])
@@ -1125,7 +1125,7 @@ class poly1d(object):
 
     def __pow__(self, val):
         if not isscalar(val) or int(val) != val or val < 0:
-            raise ValueError, "Power to non-negative integers only."
+            raise ValueError("Power to non-negative integers only.")
         res = [1]
         for _ in range(val):
             res = polymul(self.coeffs, res)
@@ -1164,7 +1164,7 @@ class poly1d(object):
         return NX.any(self.coeffs != other.coeffs)
 
     def __setattr__(self, key, val):
-        raise ValueError, "Attributes cannot be changed this way."
+        raise ValueError("Attributes cannot be changed this way.")
 
     def __getattr__(self, key):
         if key in ['r', 'roots']:
@@ -1190,7 +1190,7 @@ class poly1d(object):
     def __setitem__(self, key, val):
         ind = self.order - key
         if key < 0:
-            raise ValueError, "Does not support negative powers."
+            raise ValueError("Does not support negative powers.")
         if key > self.order:
             zr = NX.zeros(key-self.order, self.coeffs.dtype)
             self.__dict__['coeffs'] = NX.concatenate((zr, self.coeffs))
diff --git a/numpy/lib/shape_base.py b/numpy/lib/shape_base.py
index 5ea2648cb..719cf0814 100644
--- a/numpy/lib/shape_base.py
+++ b/numpy/lib/shape_base.py
@@ -383,7 +383,7 @@ def array_split(ary,indices_or_sections,axis = 0):
     except TypeError: #indices_or_sections is a scalar, not an array.
         Nsections = int(indices_or_sections)
         if Nsections <= 0:
-            raise ValueError, 'number sections must be larger than 0.'
+            raise ValueError('number sections must be larger than 0.')
         Neach_section,extras = divmod(Ntotal,Nsections)
         section_sizes = [0] + \
                         extras * [Neach_section+1] + \
@@ -474,7 +474,7 @@ def split(ary,indices_or_sections,axis=0):
         sections = indices_or_sections
         N = ary.shape[axis]
         if N % sections:
-            raise ValueError, 'array split does not result in an equal division'
+            raise ValueError('array split does not result in an equal division')
     res = array_split(ary,indices_or_sections,axis)
     return res
 
@@ -534,7 +534,7 @@ def hsplit(ary,indices_or_sections):
 
     """
     if len(_nx.shape(ary)) == 0:
-        raise ValueError, 'hsplit only works on arrays of 1 or more dimensions'
+        raise ValueError('hsplit only works on arrays of 1 or more dimensions')
     if len(ary.shape) > 1:
         return split(ary,indices_or_sections,1)
     else:
@@ -588,7 +588,7 @@ def vsplit(ary,indices_or_sections):
 
     """
     if len(_nx.shape(ary)) < 2:
-        raise ValueError, 'vsplit only works on arrays of 2 or more dimensions'
+        raise ValueError('vsplit only works on arrays of 2 or more dimensions')
     return split(ary,indices_or_sections,0)
 
 def dsplit(ary,indices_or_sections):
@@ -633,7 +633,7 @@ def dsplit(ary,indices_or_sections):
 
     """
     if len(_nx.shape(ary)) < 3:
-        raise ValueError, 'vsplit only works on arrays of 3 or more dimensions'
+        raise ValueError('vsplit only works on arrays of 3 or more dimensions')
     return split(ary,indices_or_sections,2)
 
 def get_array_prepare(*args):
diff --git a/numpy/lib/type_check.py b/numpy/lib/type_check.py
index 024542ccc..0ce851fe4 100644
--- a/numpy/lib/type_check.py
+++ b/numpy/lib/type_check.py
@@ -607,10 +607,10 @@ def datetime_data(dtype):
     try:
         import ctypes
     except ImportError:
-        raise RuntimeError, "Cannot access date-time internals without ctypes installed"
+        raise RuntimeError("Cannot access date-time internals without ctypes installed")
 
     if dtype.kind not in ['m','M']:
-        raise ValueError, "Not a date-time dtype"
+        raise ValueError("Not a date-time dtype")
 
     obj = dtype.metadata[METADATA_DTSTR]
     class DATETIMEMETA(ctypes.Structure):
diff --git a/numpy/lib/user_array.py b/numpy/lib/user_array.py
index 43e9da3f2..01b0b1c19 100644
--- a/numpy/lib/user_array.py
+++ b/numpy/lib/user_array.py
@@ -149,7 +149,7 @@ class container(object):
         if len(self.shape) == 0:
             return func(self[0])
         else:
-            raise TypeError, "only rank-0 arrays can be converted to Python scalars."
+            raise TypeError("only rank-0 arrays can be converted to Python scalars.")
 
     def __complex__(self): return self._scalarfunc(complex)
     def __float__(self): return self._scalarfunc(float)
diff --git a/numpy/linalg/linalg.py b/numpy/linalg/linalg.py
index 87be0e8a3..043deb24f 100644
--- a/numpy/linalg/linalg.py
+++ b/numpy/linalg/linalg.py
@@ -57,7 +57,7 @@ class LinAlgError(Exception):
         in inv return wrap(solve(a, identity(a.shape[0], dtype=a.dtype)))
       File "...linalg.py", line 249,
         in solve
-        raise LinAlgError, 'Singular matrix'
+        raise LinAlgError('Singular matrix')
     numpy.linalg.linalg.LinAlgError: Singular matrix
 
     """
@@ -157,12 +157,12 @@ def _assertRank2(*arrays):
 def _assertSquareness(*arrays):
     for a in arrays:
         if max(a.shape) != min(a.shape):
-            raise LinAlgError, 'Array must be square'
+            raise LinAlgError('Array must be square')
 
 def _assertFinite(*arrays):
     for a in arrays:
         if not (isfinite(a).all()):
-            raise LinAlgError, "Array must not contain infs or NaNs"
+            raise LinAlgError("Array must not contain infs or NaNs")
 
 def _assertNonEmpty(*arrays):
     for a in arrays:
@@ -313,7 +313,7 @@ def solve(a, b):
     n_eq = a.shape[0]
     n_rhs = b.shape[1]
     if n_eq != b.shape[0]:
-        raise LinAlgError, 'Incompatible dimensions'
+        raise LinAlgError('Incompatible dimensions')
     t, result_t = _commonType(a, b)
 #    lapack_routine = _findLapackRoutine('gesv', t)
     if isComplexType(t):
@@ -325,7 +325,7 @@ def solve(a, b):
     pivots = zeros(n_eq, fortran_int)
     results = lapack_routine(n_eq, n_rhs, a, n_eq, pivots, b, n_eq, 0)
     if results['info'] > 0:
-        raise LinAlgError, 'Singular matrix'
+        raise LinAlgError('Singular matrix')
     if one_eq:
         return wrap(b.ravel().astype(result_t))
     else:
@@ -393,7 +393,7 @@ def tensorinv(a, ind=2):
         for k in oldshape[ind:]:
             prod *= k
     else:
-        raise ValueError, "Invalid ind argument."
+        raise ValueError("Invalid ind argument.")
     a = a.reshape(prod, -1)
     ia = inv(a)
     return ia.reshape(*invshape)
@@ -802,7 +802,7 @@ def eigvals(a):
             w = wr+1j*wi
             result_t = _complexType(result_t)
     if results['info'] > 0:
-        raise LinAlgError, 'Eigenvalues did not converge'
+        raise LinAlgError('Eigenvalues did not converge')
     return w.astype(result_t)
 
 
@@ -891,7 +891,7 @@ def eigvalsh(a, UPLO='L'):
         results = lapack_routine(_N, UPLO, n, a, n, w, work, lwork,
                                  iwork, liwork, 0)
     if results['info'] > 0:
-        raise LinAlgError, 'Eigenvalues did not converge'
+        raise LinAlgError('Eigenvalues did not converge')
     return w.astype(result_t)
 
 def _convertarray(a):
@@ -1061,7 +1061,7 @@ def eig(a):
             result_t = _complexType(result_t)
 
     if results['info'] > 0:
-        raise LinAlgError, 'Eigenvalues did not converge'
+        raise LinAlgError('Eigenvalues did not converge')
     vt = v.transpose().astype(result_t)
     return w.astype(result_t), wrap(vt)
 
@@ -1184,7 +1184,7 @@ def eigh(a, UPLO='L'):
         results = lapack_routine(_V, UPLO, n, a, n, w, work, lwork,
                 iwork, liwork, 0)
     if results['info'] > 0:
-        raise LinAlgError, 'Eigenvalues did not converge'
+        raise LinAlgError('Eigenvalues did not converge')
     at = a.transpose().astype(result_t)
     return w.astype(_realType(result_t)), wrap(at)
 
@@ -1317,7 +1317,7 @@ def svd(a, full_matrices=1, compute_uv=1):
         results = lapack_routine(option, m, n, a, m, s, u, m, vt, nvt,
                                  work, lwork, iwork, 0)
     if results['info'] > 0:
-        raise LinAlgError, 'SVD did not converge'
+        raise LinAlgError('SVD did not converge')
     s = s.astype(_realType(result_t))
     if compute_uv:
         u = u.transpose().astype(result_t)
@@ -1627,7 +1627,7 @@ def slogdet(a):
     results = lapack_routine(n, n, a, n, pivots, 0)
     info = results['info']
     if (info < 0):
-        raise TypeError, "Illegal input to Fortran routine"
+        raise TypeError("Illegal input to Fortran routine")
     elif (info > 0):
         return (t(0.0), _realType(t)(-Inf))
     sign = 1. - 2. * (add.reduce(pivots != arange(1, n + 1)) % 2)
@@ -1771,7 +1771,7 @@ def lstsq(a, b, rcond=-1):
     n_rhs = b.shape[1]
     ldb = max(n, m)
     if m != b.shape[0]:
-        raise LinAlgError, 'Incompatible dimensions'
+        raise LinAlgError('Incompatible dimensions')
     t, result_t = _commonType(a, b)
     result_real_t = _realType(result_t)
     real_t = _linalgRealType(t)
@@ -1812,7 +1812,7 @@ def lstsq(a, b, rcond=-1):
         results = lapack_routine(m, n, n_rhs, a, m, bstar, ldb, s, rcond,
                                  0, work, lwork, iwork, 0)
     if results['info'] > 0:
-        raise LinAlgError, 'SVD did not converge in Linear Least Squares'
+        raise LinAlgError('SVD did not converge in Linear Least Squares')
     resids = array([], result_real_t)
     if is_1d:
         x = array(ravel(bstar)[:n], dtype=result_t, copy=True)
@@ -1959,7 +1959,7 @@ def norm(x, ord=None):
             try:
                 ord + 1
             except TypeError:
-                raise ValueError, "Invalid norm order for vectors."
+                raise ValueError("Invalid norm order for vectors.")
             return ((abs(x)**ord).sum())**(1.0/ord)
     elif nd == 2:
         if ord == 2:
@@ -1977,6 +1977,6 @@ def norm(x, ord=None):
         elif ord in ['fro','f']:
             return sqrt(add.reduce((x.conj() * x).real.ravel()))
         else:
-            raise ValueError, "Invalid norm order for matrices."
+            raise ValueError("Invalid norm order for matrices.")
     else:
-        raise ValueError, "Improper number of dimensions to norm."
+        raise ValueError("Improper number of dimensions to norm.")
diff --git a/numpy/ma/core.py b/numpy/ma/core.py
index 936df17f3..1ea40d417 100644
--- a/numpy/ma/core.py
+++ b/numpy/ma/core.py
@@ -2976,7 +2976,7 @@ class MaskedArray(ndarray):
 
         """
         if self is masked:
-            raise MaskError, 'Cannot alter the masked element.'
+            raise MaskError('Cannot alter the masked element.')
         # This test is useful, but we should keep things light...
 #        if getmask(indx) is not nomask:
 #            msg = "Masked arrays must be filled before they can be used as indices!"
@@ -3792,7 +3792,7 @@ class MaskedArray(ndarray):
             raise TypeError("Only length-1 arrays can be converted "\
                             "to Python scalars")
         elif self._mask:
-            raise MaskError, 'Cannot convert masked element to a Python int.'
+            raise MaskError('Cannot convert masked element to a Python int.')
         return int(self.item())
 
 
@@ -5992,7 +5992,7 @@ def power(a, b, third=None):
 
     """
     if third is not None:
-        raise MaskError, "3-argument power not supported."
+        raise MaskError("3-argument power not supported.")
     # Get the masks
     ma = getmask(a)
     mb = getmask(b)
@@ -6536,7 +6536,7 @@ def where (condition, x=None, y=None):
     if x is None and y is None:
         return filled(condition, 0).nonzero()
     elif x is None or y is None:
-        raise ValueError, "Either both or neither x and y should be given."
+        raise ValueError("Either both or neither x and y should be given.")
     # Get the condition ...............
     fc = filled(condition, 0).astype(MaskType)
     notfc = np.logical_not(fc)
diff --git a/numpy/ma/extras.py b/numpy/ma/extras.py
index 1c28eadb8..27abcb2c1 100644
--- a/numpy/ma/extras.py
+++ b/numpy/ma/extras.py
@@ -533,7 +533,7 @@ def average(a, axis=None, weights=None, returned=False):
                     d = add.reduce(w, axis, dtype=float)
                     del w, r
                 else:
-                    raise ValueError, 'average: weights wrong shape.'
+                    raise ValueError('average: weights wrong shape.')
         else:
             if weights is None:
                 n = add.reduce(a, axis, dtype=float)
@@ -556,7 +556,7 @@ def average(a, axis=None, weights=None, returned=False):
                     n = add.reduce(a * w, axis, dtype=float)
                     d = add.reduce(w, axis, dtype=float)
                 else:
-                    raise ValueError, 'average: weights wrong shape.'
+                    raise ValueError('average: weights wrong shape.')
                 del w
     if n is masked or d is masked:
         return masked
@@ -718,7 +718,7 @@ def compress_rowcols(x, axis=None):
     """
     x = asarray(x)
     if x.ndim != 2:
-        raise NotImplementedError, "compress2d works for 2D arrays only."
+        raise NotImplementedError("compress2d works for 2D arrays only.")
     m = getmask(x)
     # Nothing is masked: return x
     if m is nomask or not m.any():
@@ -842,7 +842,7 @@ def mask_rowcols(a, axis=None):
     """
     a = asarray(a)
     if a.ndim != 2:
-        raise NotImplementedError, "compress2d works for 2D arrays only."
+        raise NotImplementedError("compress2d works for 2D arrays only.")
     m = getmask(a)
     # Nothing is masked: return a
     if m is nomask or not m.any():
@@ -1429,7 +1429,7 @@ class MAxisConcatenator(AxisConcatenator):
 
     def __getitem__(self, key):
         if isinstance(key, str):
-            raise MAError, "Unavailable for masked array."
+            raise MAError("Unavailable for masked array.")
         if type(key) is not tuple:
             key = (key,)
         objs = []
@@ -1459,7 +1459,7 @@ class MAxisConcatenator(AxisConcatenator):
                     self.axis = int(key[k])
                     continue
                 except (ValueError, TypeError):
-                    raise ValueError, "Unknown special directive"
+                    raise ValueError("Unknown special directive")
             elif type(key[k]) in np.ScalarType:
                 newobj = asarray([key[k]])
                 scalars.append(k)
@@ -1706,7 +1706,7 @@ def notmasked_contiguous(a, axis=None):
     a = asarray(a)
     nd = a.ndim
     if nd > 2:
-        raise NotImplementedError, "Currently limited to atmost 2D array."
+        raise NotImplementedError("Currently limited to atmost 2D array.")
     if axis is None or nd == 1:
         return flatnotmasked_contiguous(a)
     #
@@ -1863,7 +1863,7 @@ def polyfit(x, y, deg, rcond=None, full=False):
         else:
             m = mx
     else:
-        raise TypeError, "Expected a 1D or 2D array for y!"
+        raise TypeError("Expected a 1D or 2D array for y!")
     if m is not nomask:
         x[m] = y[m] = masked
     # Set rcond
diff --git a/numpy/ma/mrecords.py b/numpy/ma/mrecords.py
index 79fa6e15b..9e06908b2 100644
--- a/numpy/ma/mrecords.py
+++ b/numpy/ma/mrecords.py
@@ -589,7 +589,7 @@ on the first line. An exception is raised if the file is 3D or more.
     if len(arr.shape) == 2 :
         arr = arr[0]
     elif len(arr.shape) > 2:
-        raise ValueError, "The array should be 2D at most!"
+        raise ValueError("The array should be 2D at most!")
     # Start the conversion loop .......
     for f in arr:
         try:
@@ -623,7 +623,7 @@ def openfile(fname):
     if f.readline()[:2] != "\\x":
         f.seek(0, 0)
         return f
-    raise NotImplementedError, "Wow, binary file"
+    raise NotImplementedError("Wow, binary file")
 
 
 def fromtextfile(fname, delimitor=None, commentchar='#', missingchar='',
diff --git a/numpy/matrixlib/defmatrix.py b/numpy/matrixlib/defmatrix.py
index a5aa84f6d..a46f2dab0 100644
--- a/numpy/matrixlib/defmatrix.py
+++ b/numpy/matrixlib/defmatrix.py
@@ -47,7 +47,7 @@ def _convert_from_string(data):
         if count == 0:
             Ncols = len(newrow)
         elif len(newrow) != Ncols:
-            raise ValueError, "Rows not the same size."
+            raise ValueError("Rows not the same size.")
         count += 1
         newdata.append(newrow)
     return newdata
@@ -258,7 +258,7 @@ class matrix(N.ndarray):
         ndim = arr.ndim
         shape = arr.shape
         if (ndim > 2):
-            raise ValueError, "matrix must be 2-dimensional"
+            raise ValueError("matrix must be 2-dimensional")
         elif ndim == 0:
             shape = (1,1)
         elif ndim == 1:
@@ -289,7 +289,7 @@ class matrix(N.ndarray):
                 self.shape = newshape
                 return
             elif (ndim > 2):
-                raise ValueError, "shape too large to be a matrix."
+                raise ValueError("shape too large to be a matrix.")
         else:
             newshape = self.shape
         if ndim == 0:
@@ -373,7 +373,7 @@ class matrix(N.ndarray):
         elif axis==1:
             return self.transpose()
         else:
-            raise ValueError, "unsupported axis"
+            raise ValueError("unsupported axis")
 
     # Necessary because base-class tolist expects dimension
     #  reduction by x[0]
diff --git a/numpy/oldnumeric/arrayfns.py b/numpy/oldnumeric/arrayfns.py
index 230b200a9..683ed309d 100644
--- a/numpy/oldnumeric/arrayfns.py
+++ b/numpy/oldnumeric/arrayfns.py
@@ -14,9 +14,9 @@ class error(Exception):
 def array_set(vals1, indices, vals2):
     indices = asarray(indices)
     if indices.ndim != 1:
-        raise ValueError, "index array must be 1-d"
+        raise ValueError("index array must be 1-d")
     if not isinstance(vals1, np.ndarray):
-        raise TypeError, "vals1 must be an ndarray"
+        raise TypeError("vals1 must be an ndarray")
     vals1 = asarray(vals1)
     vals2 = asarray(vals2)
     if vals1.ndim != vals2.ndim or vals1.ndim < 1:
@@ -43,14 +43,14 @@ def interp(y, x, z, typ=None):
 def nz(x):
     x = asarray(x,dtype=np.ubyte)
     if x.ndim != 1:
-        raise TypeError, "intput must have 1 dimension."
+        raise TypeError("intput must have 1 dimension.")
     indxs = np.flatnonzero(x != 0)
     return indxs[-1].item()+1
 
 def reverse(x, n):
     x = asarray(x,dtype='d')
     if x.ndim != 2:
-        raise ValueError, "input must be 2-d"
+        raise ValueError("input must be 2-d")
     y = np.empty_like(x)
     if n == 0:
         y[...] = x[::-1,:]
@@ -71,7 +71,7 @@ def zmin_zmax(z, ireg):
     z = asarray(z, dtype=float)
     ireg = asarray(ireg, dtype=int)
     if z.shape != ireg.shape or z.ndim != 2:
-        raise ValueError, "z and ireg must be the same shape and 2-d"
+        raise ValueError("z and ireg must be the same shape and 2-d")
     ix, iy = np.nonzero(ireg)
     # Now, add more indices
     x1m = ix - 1
diff --git a/numpy/oldnumeric/compat.py b/numpy/oldnumeric/compat.py
index 607dd0b90..083a1fa15 100644
--- a/numpy/oldnumeric/compat.py
+++ b/numpy/oldnumeric/compat.py
@@ -112,6 +112,6 @@ else:
 
 class Pickler(pickle.Pickler):
     def __init__(self, *args, **kwds):
-        raise NotImplementedError, "Don't pickle new arrays with this"
+        raise NotImplementedError("Don't pickle new arrays with this")
     def save_array(self, object):
-        raise NotImplementedError, "Don't pickle new arrays with this"
+        raise NotImplementedError("Don't pickle new arrays with this")
diff --git a/numpy/oldnumeric/functions.py b/numpy/oldnumeric/functions.py
index 5b2b1a8bf..db62f7cb5 100644
--- a/numpy/oldnumeric/functions.py
+++ b/numpy/oldnumeric/functions.py
@@ -91,7 +91,7 @@ def nonzero(a):
     if len(res) == 1:
         return res[0]
     else:
-        raise ValueError, "Input argument must be 1d"
+        raise ValueError("Input argument must be 1d")
 
 def reshape(a, shape):
     return np.reshape(a, shape)
diff --git a/numpy/oldnumeric/ma.py b/numpy/oldnumeric/ma.py
index 1284c6019..d30f673a8 100644
--- a/numpy/oldnumeric/ma.py
+++ b/numpy/oldnumeric/ma.py
@@ -122,7 +122,7 @@ def minimum_fill_value (obj):
         if x in typecodes['UnsignedInteger']:
             return sys.maxint
     else:
-        raise TypeError, 'Unsuitable type for calculating minimum.'
+        raise TypeError('Unsuitable type for calculating minimum.')
 
 def maximum_fill_value (obj):
     "Function to calculate default fill value suitable for taking maxima."
@@ -139,7 +139,7 @@ def maximum_fill_value (obj):
         if x in typecodes['UnsignedInteger']:
             return 0
     else:
-        raise TypeError, 'Unsuitable type for calculating maximum.'
+        raise TypeError('Unsuitable type for calculating maximum.')
 
 def set_fill_value (a, fill_value):
     "Set fill value of a if it is a masked array."
@@ -598,7 +598,7 @@ class MaskedArray (object):
                         self._data = fromnumeric.resize(self._data, self._mask.shape)
                         self._data.shape = self._mask.shape
                     else:
-                        raise MAError, "Mask and data not compatible."
+                        raise MAError("Mask and data not compatible.")
                 elif nm == 1 and shape(self._mask) != shape(self._data):
                     self.unshare_mask()
                     self._mask.shape = self._data.shape
@@ -786,14 +786,14 @@ array(data = %(data)s,
         "Convert self to float."
         self.unmask()
         if self._mask is not nomask:
-            raise MAError, 'Cannot convert masked element to a Python float.'
+            raise MAError('Cannot convert masked element to a Python float.')
         return float(self.data.item())
 
     def __int__(self):
         "Convert self to int."
         self.unmask()
         if self._mask is not nomask:
-            raise MAError, 'Cannot convert masked element to a Python int.'
+            raise MAError('Cannot convert masked element to a Python int.')
         return int(self.data.item())
 
     def __getitem__(self, i):
@@ -827,7 +827,7 @@ array(data = %(data)s,
         "Set item described by index. If value is masked, mask those locations."
         d = self._data
         if self is masked:
-            raise MAError, 'Cannot alter masked elements.'
+            raise MAError('Cannot alter masked elements.')
         if value is masked:
             if self._mask is nomask:
                 self._mask = make_mask_none(d.shape)
@@ -973,14 +973,14 @@ array(data = %(data)s,
             if t1 in typecodes['Integer']:
                 f = f.astype(t)
             else:
-                raise TypeError, 'Incorrect type for in-place operation.'
+                raise TypeError('Incorrect type for in-place operation.')
         elif t in typecodes['Float']:
             if t1 in typecodes['Integer']:
                 f = f.astype(t)
             elif t1 in typecodes['Float']:
                 f = f.astype(t)
             else:
-                raise TypeError, 'Incorrect type for in-place operation.'
+                raise TypeError('Incorrect type for in-place operation.')
         elif t in typecodes['Complex']:
             if t1 in typecodes['Integer']:
                 f = f.astype(t)
@@ -989,9 +989,9 @@ array(data = %(data)s,
             elif t1 in typecodes['Complex']:
                 f = f.astype(t)
             else:
-                raise TypeError, 'Incorrect type for in-place operation.'
+                raise TypeError('Incorrect type for in-place operation.')
         else:
-            raise TypeError, 'Incorrect type for in-place operation.'
+            raise TypeError('Incorrect type for in-place operation.')
 
         if self._mask is nomask:
             self._data += f
@@ -1016,14 +1016,14 @@ array(data = %(data)s,
             if t1 in typecodes['Integer']:
                 f = f.astype(t)
             else:
-                raise TypeError, 'Incorrect type for in-place operation.'
+                raise TypeError('Incorrect type for in-place operation.')
         elif t in typecodes['Float']:
             if t1 in typecodes['Integer']:
                 f = f.astype(t)
             elif t1 in typecodes['Float']:
                 f = f.astype(t)
             else:
-                raise TypeError, 'Incorrect type for in-place operation.'
+                raise TypeError('Incorrect type for in-place operation.')
         elif t in typecodes['Complex']:
             if t1 in typecodes['Integer']:
                 f = f.astype(t)
@@ -1032,9 +1032,9 @@ array(data = %(data)s,
             elif t1 in typecodes['Complex']:
                 f = f.astype(t)
             else:
-                raise TypeError, 'Incorrect type for in-place operation.'
+                raise TypeError('Incorrect type for in-place operation.')
         else:
-            raise TypeError, 'Incorrect type for in-place operation.'
+            raise TypeError('Incorrect type for in-place operation.')
 
         if self._mask is nomask:
             self._data *= f
@@ -1059,14 +1059,14 @@ array(data = %(data)s,
             if t1 in typecodes['Integer']:
                 f = f.astype(t)
             else:
-                raise TypeError, 'Incorrect type for in-place operation.'
+                raise TypeError('Incorrect type for in-place operation.')
         elif t in typecodes['Float']:
             if t1 in typecodes['Integer']:
                 f = f.astype(t)
             elif t1 in typecodes['Float']:
                 f = f.astype(t)
             else:
-                raise TypeError, 'Incorrect type for in-place operation.'
+                raise TypeError('Incorrect type for in-place operation.')
         elif t in typecodes['Complex']:
             if t1 in typecodes['Integer']:
                 f = f.astype(t)
@@ -1075,9 +1075,9 @@ array(data = %(data)s,
             elif t1 in typecodes['Complex']:
                 f = f.astype(t)
             else:
-                raise TypeError, 'Incorrect type for in-place operation.'
+                raise TypeError('Incorrect type for in-place operation.')
         else:
-            raise TypeError, 'Incorrect type for in-place operation.'
+            raise TypeError('Incorrect type for in-place operation.')
 
         if self._mask is nomask:
             self._data -= f
@@ -1104,14 +1104,14 @@ array(data = %(data)s,
             if t1 in typecodes['Integer']:
                 f = f.astype(t)
             else:
-                raise TypeError, 'Incorrect type for in-place operation.'
+                raise TypeError('Incorrect type for in-place operation.')
         elif t in typecodes['Float']:
             if t1 in typecodes['Integer']:
                 f = f.astype(t)
             elif t1 in typecodes['Float']:
                 f = f.astype(t)
             else:
-                raise TypeError, 'Incorrect type for in-place operation.'
+                raise TypeError('Incorrect type for in-place operation.')
         elif t in typecodes['Complex']:
             if t1 in typecodes['Integer']:
                 f = f.astype(t)
@@ -1120,9 +1120,9 @@ array(data = %(data)s,
             elif t1 in typecodes['Complex']:
                 f = f.astype(t)
             else:
-                raise TypeError, 'Incorrect type for in-place operation.'
+                raise TypeError('Incorrect type for in-place operation.')
         else:
-            raise TypeError, 'Incorrect type for in-place operation.'
+            raise TypeError('Incorrect type for in-place operation.')
         mo = getmask(other)
         result = divide(self, masked_array(f, mask=mo))
         self._data = result.data
@@ -1567,7 +1567,7 @@ def count (a, axis = None):
 def power (a, b, third=None):
     "a**b"
     if third is not None:
-        raise MAError, "3-argument power not supported."
+        raise MAError("3-argument power not supported.")
     ma = getmask(a)
     mb = getmask(b)
     m = mask_or(ma, mb)
@@ -1665,7 +1665,7 @@ def new_average (a, axis=None, weights=None, returned = 0):
                     d = add.reduce(w, axis)
                     del w, r
                 else:
-                    raise ValueError, 'average: weights wrong shape.'
+                    raise ValueError('average: weights wrong shape.')
         else:
             if weights is None:
                 n = add.reduce(a, axis)
@@ -1688,7 +1688,7 @@ def new_average (a, axis=None, weights=None, returned = 0):
                     n = add.reduce(a*w, axis)
                     d = add.reduce(w, axis)
                 else:
-                    raise ValueError, 'average: weights wrong shape.'
+                    raise ValueError('average: weights wrong shape.')
                 del w
     #print n, d, repr(mask), repr(weights)
     if n is masked or d is masked: return masked
@@ -2135,7 +2135,7 @@ from types import MethodType
 def _m(f):
     return MethodType(f, None, array)
 def not_implemented(*args, **kwds):
-    raise NotImplementedError, "not yet implemented for numpy.ma arrays"
+    raise NotImplementedError("not yet implemented for numpy.ma arrays")
 array.all = _m(alltrue)
 array.any = _m(sometrue)
 array.argmax = _m(argmax)
diff --git a/numpy/oldnumeric/matrix.py b/numpy/oldnumeric/matrix.py
index 5f8c1ca5e..ddd612266 100644
--- a/numpy/oldnumeric/matrix.py
+++ b/numpy/oldnumeric/matrix.py
@@ -41,7 +41,7 @@ def _convert_from_string(data):
         if count == 0:
             Ncols = len(newrow)
         elif len(newrow) != Ncols:
-            raise ValueError, "Rows not the same size."
+            raise ValueError("Rows not the same size.")
         count += 1
         newdata.append(newrow)
     return newdata
diff --git a/numpy/oldnumeric/random_array.py b/numpy/oldnumeric/random_array.py
index e84aedf1e..ffae79616 100644
--- a/numpy/oldnumeric/random_array.py
+++ b/numpy/oldnumeric/random_array.py
@@ -41,12 +41,12 @@ def randint(minimum, maximum=None, shape=[]):
     """randint(min, max, shape=[]) = random integers >=min, < max
     If max not given, random integers >= 0, <min"""
     if not isinstance(minimum, int):
-        raise ArgumentError, "randint requires first argument integer"
+        raise ArgumentError("randint requires first argument integer")
     if maximum is None:
         maximum = minimum
         minimum = 0
     if not isinstance(maximum, int):
-        raise ArgumentError, "randint requires second argument integer"
+        raise ArgumentError("randint requires second argument integer")
     a = ((maximum-minimum)* random(shape))
     if isinstance(a, np.ndarray):
         return minimum + a.astype(np.int)
diff --git a/numpy/polynomial/chebyshev.py b/numpy/polynomial/chebyshev.py
index 6b1edf497..a6482fc72 100644
--- a/numpy/polynomial/chebyshev.py
+++ b/numpy/polynomial/chebyshev.py
@@ -892,9 +892,9 @@ def chebder(cs, m=1, scl=1) :
     cnt = int(m)
 
     if cnt != m:
-        raise ValueError, "The order of derivation must be integer"
+        raise ValueError("The order of derivation must be integer")
     if cnt < 0 :
-        raise ValueError, "The order of derivation must be non-negative"
+        raise ValueError("The order of derivation must be non-negative")
 
     # cs is a trimmed copy
     [cs] = pu.as_series([cs])
@@ -991,11 +991,11 @@ def chebint(cs, m=1, k=[], lbnd=0, scl=1):
         k = [k]
 
     if cnt != m:
-        raise ValueError, "The order of integration must be integer"
+        raise ValueError("The order of integration must be integer")
     if cnt < 0 :
-        raise ValueError, "The order of integration must be non-negative"
+        raise ValueError("The order of integration must be non-negative")
     if len(k) > cnt :
-        raise ValueError, "Too many integration constants"
+        raise ValueError("Too many integration constants")
 
     # cs is a trimmed copy
     [cs] = pu.as_series([cs])
@@ -1226,15 +1226,15 @@ def chebfit(x, y, deg, rcond=None, full=False, w=None):
 
     # check arguments.
     if deg < 0 :
-        raise ValueError, "expected deg >= 0"
+        raise ValueError("expected deg >= 0")
     if x.ndim != 1:
-        raise TypeError, "expected 1D vector for x"
+        raise TypeError("expected 1D vector for x")
     if x.size == 0:
-        raise TypeError, "expected non-empty vector for x"
+        raise TypeError("expected non-empty vector for x")
     if y.ndim < 1 or y.ndim > 2 :
-        raise TypeError, "expected 1D or 2D array for y"
+        raise TypeError("expected 1D or 2D array for y")
     if len(x) != len(y):
-        raise TypeError, "expected x and y to have same length"
+        raise TypeError("expected x and y to have same length")
 
     # set up the least squares matrices
     lhs = chebvander(x, deg)
@@ -1242,9 +1242,9 @@ def chebfit(x, y, deg, rcond=None, full=False, w=None):
     if w is not None:
         w = np.asarray(w) + 0.0
         if w.ndim != 1:
-            raise TypeError, "expected 1D vector for w"
+            raise TypeError("expected 1D vector for w")
         if len(x) != len(w):
-            raise TypeError, "expected x and w to have same length"
+            raise TypeError("expected x and w to have same length")
         # apply weights
         if rhs.ndim == 2:
             lhs *= w[:, np.newaxis]
diff --git a/numpy/polynomial/hermite.py b/numpy/polynomial/hermite.py
index d266a6453..c3ff42b6c 100644
--- a/numpy/polynomial/hermite.py
+++ b/numpy/polynomial/hermite.py
@@ -665,9 +665,9 @@ def hermder(cs, m=1, scl=1) :
     cnt = int(m)
 
     if cnt != m:
-        raise ValueError, "The order of derivation must be integer"
+        raise ValueError("The order of derivation must be integer")
     if cnt < 0 :
-        raise ValueError, "The order of derivation must be non-negative"
+        raise ValueError("The order of derivation must be non-negative")
 
     # cs is a trimmed copy
     [cs] = pu.as_series([cs])
@@ -766,11 +766,11 @@ def hermint(cs, m=1, k=[], lbnd=0, scl=1):
         k = [k]
 
     if cnt != m:
-        raise ValueError, "The order of integration must be integer"
+        raise ValueError("The order of integration must be integer")
     if cnt < 0 :
-        raise ValueError, "The order of integration must be non-negative"
+        raise ValueError("The order of integration must be non-negative")
     if len(k) > cnt :
-        raise ValueError, "Too many integration constants"
+        raise ValueError("Too many integration constants")
 
     # cs is a trimmed copy
     [cs] = pu.as_series([cs])
@@ -1029,15 +1029,15 @@ def hermfit(x, y, deg, rcond=None, full=False, w=None):
 
     # check arguments.
     if deg < 0 :
-        raise ValueError, "expected deg >= 0"
+        raise ValueError("expected deg >= 0")
     if x.ndim != 1:
-        raise TypeError, "expected 1D vector for x"
+        raise TypeError("expected 1D vector for x")
     if x.size == 0:
-        raise TypeError, "expected non-empty vector for x"
+        raise TypeError("expected non-empty vector for x")
     if y.ndim < 1 or y.ndim > 2 :
-        raise TypeError, "expected 1D or 2D array for y"
+        raise TypeError("expected 1D or 2D array for y")
     if len(x) != len(y):
-        raise TypeError, "expected x and y to have same length"
+        raise TypeError("expected x and y to have same length")
 
     # set up the least squares matrices
     lhs = hermvander(x, deg)
@@ -1045,9 +1045,9 @@ def hermfit(x, y, deg, rcond=None, full=False, w=None):
     if w is not None:
         w = np.asarray(w) + 0.0
         if w.ndim != 1:
-            raise TypeError, "expected 1D vector for w"
+            raise TypeError("expected 1D vector for w")
         if len(x) != len(w):
-            raise TypeError, "expected x and w to have same length"
+            raise TypeError("expected x and w to have same length")
         # apply weights
         if rhs.ndim == 2:
             lhs *= w[:, np.newaxis]
diff --git a/numpy/polynomial/hermite_e.py b/numpy/polynomial/hermite_e.py
index e644e345a..be3c65a32 100644
--- a/numpy/polynomial/hermite_e.py
+++ b/numpy/polynomial/hermite_e.py
@@ -663,9 +663,9 @@ def hermeder(cs, m=1, scl=1) :
     cnt = int(m)
 
     if cnt != m:
-        raise ValueError, "The order of derivation must be integer"
+        raise ValueError("The order of derivation must be integer")
     if cnt < 0 :
-        raise ValueError, "The order of derivation must be non-negative"
+        raise ValueError("The order of derivation must be non-negative")
 
     # cs is a trimmed copy
     [cs] = pu.as_series([cs])
@@ -764,11 +764,11 @@ def hermeint(cs, m=1, k=[], lbnd=0, scl=1):
         k = [k]
 
     if cnt != m:
-        raise ValueError, "The order of integration must be integer"
+        raise ValueError("The order of integration must be integer")
     if cnt < 0 :
-        raise ValueError, "The order of integration must be non-negative"
+        raise ValueError("The order of integration must be non-negative")
     if len(k) > cnt :
-        raise ValueError, "Too many integration constants"
+        raise ValueError("Too many integration constants")
 
     # cs is a trimmed copy
     [cs] = pu.as_series([cs])
@@ -1025,15 +1025,15 @@ def hermefit(x, y, deg, rcond=None, full=False, w=None):
 
     # check arguments.
     if deg < 0 :
-        raise ValueError, "expected deg >= 0"
+        raise ValueError("expected deg >= 0")
     if x.ndim != 1:
-        raise TypeError, "expected 1D vector for x"
+        raise TypeError("expected 1D vector for x")
     if x.size == 0:
-        raise TypeError, "expected non-empty vector for x"
+        raise TypeError("expected non-empty vector for x")
     if y.ndim < 1 or y.ndim > 2 :
-        raise TypeError, "expected 1D or 2D array for y"
+        raise TypeError("expected 1D or 2D array for y")
     if len(x) != len(y):
-        raise TypeError, "expected x and y to have same length"
+        raise TypeError("expected x and y to have same length")
 
     # set up the least squares matrices
     lhs = hermevander(x, deg)
@@ -1041,9 +1041,9 @@ def hermefit(x, y, deg, rcond=None, full=False, w=None):
     if w is not None:
         w = np.asarray(w) + 0.0
         if w.ndim != 1:
-            raise TypeError, "expected 1D vector for w"
+            raise TypeError("expected 1D vector for w")
         if len(x) != len(w):
-            raise TypeError, "expected x and w to have same length"
+            raise TypeError("expected x and w to have same length")
         # apply weights
         if rhs.ndim == 2:
             lhs *= w[:, np.newaxis]
diff --git a/numpy/polynomial/laguerre.py b/numpy/polynomial/laguerre.py
index b6389bf63..1a75d4af4 100644
--- a/numpy/polynomial/laguerre.py
+++ b/numpy/polynomial/laguerre.py
@@ -662,9 +662,9 @@ def lagder(cs, m=1, scl=1) :
     cnt = int(m)
 
     if cnt != m:
-        raise ValueError, "The order of derivation must be integer"
+        raise ValueError("The order of derivation must be integer")
     if cnt < 0 :
-        raise ValueError, "The order of derivation must be non-negative"
+        raise ValueError("The order of derivation must be non-negative")
 
     # cs is a trimmed copy
     [cs] = pu.as_series([cs])
@@ -764,11 +764,11 @@ def lagint(cs, m=1, k=[], lbnd=0, scl=1):
         k = [k]
 
     if cnt != m:
-        raise ValueError, "The order of integration must be integer"
+        raise ValueError("The order of integration must be integer")
     if cnt < 0 :
-        raise ValueError, "The order of integration must be non-negative"
+        raise ValueError("The order of integration must be non-negative")
     if len(k) > cnt :
-        raise ValueError, "Too many integration constants"
+        raise ValueError("Too many integration constants")
 
     # cs is a trimmed copy
     [cs] = pu.as_series([cs])
@@ -1026,15 +1026,15 @@ def lagfit(x, y, deg, rcond=None, full=False, w=None):
 
     # check arguments.
     if deg < 0 :
-        raise ValueError, "expected deg >= 0"
+        raise ValueError("expected deg >= 0")
     if x.ndim != 1:
-        raise TypeError, "expected 1D vector for x"
+        raise TypeError("expected 1D vector for x")
     if x.size == 0:
-        raise TypeError, "expected non-empty vector for x"
+        raise TypeError("expected non-empty vector for x")
     if y.ndim < 1 or y.ndim > 2 :
-        raise TypeError, "expected 1D or 2D array for y"
+        raise TypeError("expected 1D or 2D array for y")
     if len(x) != len(y):
-        raise TypeError, "expected x and y to have same length"
+        raise TypeError("expected x and y to have same length")
 
     # set up the least squares matrices
     lhs = lagvander(x, deg)
@@ -1042,9 +1042,9 @@ def lagfit(x, y, deg, rcond=None, full=False, w=None):
     if w is not None:
         w = np.asarray(w) + 0.0
         if w.ndim != 1:
-            raise TypeError, "expected 1D vector for w"
+            raise TypeError("expected 1D vector for w")
         if len(x) != len(w):
-            raise TypeError, "expected x and w to have same length"
+            raise TypeError("expected x and w to have same length")
         # apply weights
         if rhs.ndim == 2:
             lhs *= w[:, np.newaxis]
diff --git a/numpy/polynomial/legendre.py b/numpy/polynomial/legendre.py
index 3ea68a5e6..e5b9ffe87 100644
--- a/numpy/polynomial/legendre.py
+++ b/numpy/polynomial/legendre.py
@@ -679,9 +679,9 @@ def legder(cs, m=1, scl=1) :
     cnt = int(m)
 
     if cnt != m:
-        raise ValueError, "The order of derivation must be integer"
+        raise ValueError("The order of derivation must be integer")
     if cnt < 0 :
-        raise ValueError, "The order of derivation must be non-negative"
+        raise ValueError("The order of derivation must be non-negative")
 
     # cs is a trimmed copy
     [cs] = pu.as_series([cs])
@@ -783,11 +783,11 @@ def legint(cs, m=1, k=[], lbnd=0, scl=1):
         k = [k]
 
     if cnt != m:
-        raise ValueError, "The order of integration must be integer"
+        raise ValueError("The order of integration must be integer")
     if cnt < 0 :
-        raise ValueError, "The order of integration must be non-negative"
+        raise ValueError("The order of integration must be non-negative")
     if len(k) > cnt :
-        raise ValueError, "Too many integration constants"
+        raise ValueError("Too many integration constants")
 
     # cs is a trimmed copy
     [cs] = pu.as_series([cs])
@@ -1023,15 +1023,15 @@ def legfit(x, y, deg, rcond=None, full=False, w=None):
 
     # check arguments.
     if deg < 0 :
-        raise ValueError, "expected deg >= 0"
+        raise ValueError("expected deg >= 0")
     if x.ndim != 1:
-        raise TypeError, "expected 1D vector for x"
+        raise TypeError("expected 1D vector for x")
     if x.size == 0:
-        raise TypeError, "expected non-empty vector for x"
+        raise TypeError("expected non-empty vector for x")
     if y.ndim < 1 or y.ndim > 2 :
-        raise TypeError, "expected 1D or 2D array for y"
+        raise TypeError("expected 1D or 2D array for y")
     if len(x) != len(y):
-        raise TypeError, "expected x and y to have same length"
+        raise TypeError("expected x and y to have same length")
 
     # set up the least squares matrices
     lhs = legvander(x, deg)
@@ -1039,9 +1039,9 @@ def legfit(x, y, deg, rcond=None, full=False, w=None):
     if w is not None:
         w = np.asarray(w) + 0.0
         if w.ndim != 1:
-            raise TypeError, "expected 1D vector for w"
+            raise TypeError("expected 1D vector for w")
         if len(x) != len(w):
-            raise TypeError, "expected x and w to have same length"
+            raise TypeError("expected x and w to have same length")
         # apply weights
         if rhs.ndim == 2:
             lhs *= w[:, np.newaxis]
diff --git a/numpy/polynomial/polynomial.py b/numpy/polynomial/polynomial.py
index 3efe25920..181716ad4 100644
--- a/numpy/polynomial/polynomial.py
+++ b/numpy/polynomial/polynomial.py
@@ -491,9 +491,9 @@ def polyder(cs, m=1, scl=1):
     cnt = int(m)
 
     if cnt != m:
-        raise ValueError, "The order of derivation must be integer"
+        raise ValueError("The order of derivation must be integer")
     if cnt < 0:
-        raise ValueError, "The order of derivation must be non-negative"
+        raise ValueError("The order of derivation must be non-negative")
 
     # cs is a trimmed copy
     [cs] = pu.as_series([cs])
@@ -584,11 +584,11 @@ def polyint(cs, m=1, k=[], lbnd=0, scl=1):
         k = [k]
 
     if cnt != m:
-        raise ValueError, "The order of integration must be integer"
+        raise ValueError("The order of integration must be integer")
     if cnt < 0 :
-        raise ValueError, "The order of integration must be non-negative"
+        raise ValueError("The order of integration must be non-negative")
     if len(k) > cnt :
-        raise ValueError, "Too many integration constants"
+        raise ValueError("Too many integration constants")
 
     # cs is a trimmed copy
     [cs] = pu.as_series([cs])
@@ -825,15 +825,15 @@ def polyfit(x, y, deg, rcond=None, full=False, w=None):
 
     # check arguments.
     if deg < 0 :
-        raise ValueError, "expected deg >= 0"
+        raise ValueError("expected deg >= 0")
     if x.ndim != 1:
-        raise TypeError, "expected 1D vector for x"
+        raise TypeError("expected 1D vector for x")
     if x.size == 0:
-        raise TypeError, "expected non-empty vector for x"
+        raise TypeError("expected non-empty vector for x")
     if y.ndim < 1 or y.ndim > 2 :
-        raise TypeError, "expected 1D or 2D array for y"
+        raise TypeError("expected 1D or 2D array for y")
     if len(x) != len(y):
-        raise TypeError, "expected x and y to have same length"
+        raise TypeError("expected x and y to have same length")
 
     # set up the least squares matrices
     lhs = polyvander(x, deg)
@@ -841,9 +841,9 @@ def polyfit(x, y, deg, rcond=None, full=False, w=None):
     if w is not None:
         w = np.asarray(w) + 0.0
         if w.ndim != 1:
-            raise TypeError, "expected 1D vector for w"
+            raise TypeError("expected 1D vector for w")
         if len(x) != len(w):
-            raise TypeError, "expected x and w to have same length"
+            raise TypeError("expected x and w to have same length")
         # apply weights
         if rhs.ndim == 2:
             lhs *= w[:, np.newaxis]
diff --git a/numpy/testing/nosetester.py b/numpy/testing/nosetester.py
index 5ead74980..26118eda2 100644
--- a/numpy/testing/nosetester.py
+++ b/numpy/testing/nosetester.py
@@ -174,7 +174,7 @@ class NoseTester(object):
         argv = [__file__, self.package_path, '-s']
         if label and label != 'full':
             if not isinstance(label, basestring):
-                raise TypeError, 'Selection label should be a string'
+                raise TypeError('Selection label should be a string')
             if label == 'fast':
                 label = 'not slow'
             argv += ['-A', label]