Merge branch 'master' of https://github.com/numpy/numpy into patch-2

8 files changed, 153 insertions, 54 deletions

diff --git a/numpy/lib/_iotools.py b/numpy/lib/_iotools.py
index 7921b4116..2f2a4bc57 100644
--- a/numpy/lib/_iotools.py
+++ b/numpy/lib/_iotools.py
@@ -203,13 +203,17 @@ class LineSplitter(object):
             self._handyman = _handyman
     #
     def _delimited_splitter(self, line):
-        line = line.split(self.comments)[0].strip(asbytes(" \r\n"))
+        if self.comments is not None:
+            line = line.split(self.comments)[0]
+        line = line.strip(asbytes(" \r\n"))
         if not line:
             return []
         return line.split(self.delimiter)
     #
     def _fixedwidth_splitter(self, line):
-        line = line.split(self.comments)[0].strip(asbytes("\r\n"))
+        if self.comments is not None:
+            line = line.split(self.comments)[0]
+        line = line.strip(asbytes("\r\n"))
         if not line:
             return []
         fixed = self.delimiter
@@ -217,7 +221,8 @@ class LineSplitter(object):
         return [line[s] for s in slices]
     #
     def _variablewidth_splitter(self, line):
-        line = line.split(self.comments)[0]
+        if self.comments is not None:
+            line = line.split(self.comments)[0]
         if not line:
             return []
         slices = self.delimiter
diff --git a/numpy/lib/arraysetops.py b/numpy/lib/arraysetops.py
index 91dd96f9c..20a0e7151 100644
--- a/numpy/lib/arraysetops.py
+++ b/numpy/lib/arraysetops.py
@@ -44,7 +44,7 @@ def ediff1d(ary, to_end=None, to_begin=None):
 
     Returns
     -------
-    ed : ndarray
+    ediff1d : ndarray
         The differences. Loosely, this is ``ary.flat[1:] - ary.flat[:-1]``.
 
     See Also
@@ -212,7 +212,7 @@ def intersect1d(ar1, ar2, assume_unique=False):
 
     Returns
     -------
-    out : ndarray
+    intersect1d : ndarray
         Sorted 1D array of common and unique elements.
 
     See Also
@@ -251,7 +251,7 @@ def setxor1d(ar1, ar2, assume_unique=False):
 
     Returns
     -------
-    xor : ndarray
+    setxor1d : ndarray
         Sorted 1D array of unique values that are in only one of the input
         arrays.
 
@@ -287,7 +287,7 @@ def in1d(ar1, ar2, assume_unique=False):
 
     Parameters
     ----------
-    ar1 : array_like, shape (M,)
+    ar1 : (M,) array_like
         Input array.
     ar2 : array_like
         The values against which to test each value of `ar1`.
@@ -297,8 +297,8 @@ def in1d(ar1, ar2, assume_unique=False):
 
     Returns
     -------
-    mask : ndarray of bools, shape(M,)
-        The values `ar1[mask]` are in `ar2`.
+    in1d : (M,) ndarray, bool
+        The values `ar1[in1d]` are in `ar2`.
 
     See Also
     --------
@@ -365,7 +365,7 @@ def union1d(ar1, ar2):
 
     Returns
     -------
-    union : ndarray
+    union1d : ndarray
         Unique, sorted union of the input arrays.
 
     See Also
@@ -399,7 +399,7 @@ def setdiff1d(ar1, ar2, assume_unique=False):
 
     Returns
     -------
-    difference : ndarray
+    setdiff1d : ndarray
         Sorted 1D array of values in `ar1` that are not in `ar2`.
 
     See Also
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py
index f3df3b96b..a0781ebf9 100644
--- a/numpy/lib/function_base.py
+++ b/numpy/lib/function_base.py
@@ -843,7 +843,7 @@ def gradient(f, *varargs):
 
     Returns
     -------
-    g : ndarray
+    gradient : ndarray
       N arrays of the same shape as `f` giving the derivative of `f` with
       respect to each dimension.
 
@@ -948,7 +948,7 @@ def diff(a, n=1, axis=-1):
 
     Returns
     -------
-    out : ndarray
+    diff : ndarray
         The `n` order differences. The shape of the output is the same as `a`
         except along `axis` where the dimension is smaller by `n`.
 
@@ -1284,6 +1284,11 @@ def extract(condition, arr):
     arr : array_like
         Input array of the same size as `condition`.
 
+    Returns
+    -------
+    extract : ndarray
+        Rank 1 array of values from `arr` where `condition` is True.
+
     See Also
     --------
     take, put, copyto, compress
@@ -1316,9 +1321,10 @@ def place(arr, mask, vals):
     """
     Change elements of an array based on conditional and input values.
 
-    Similar to ``np.copyto(arr, vals, where=mask)``, the difference is that `place`
-    uses the first N elements of `vals`, where N is the number of True values
-    in `mask`, while `copyto` uses the elements where `mask` is True.
+    Similar to ``np.copyto(arr, vals, where=mask)``, the difference is that
+    `place` uses the first N elements of `vals`, where N is the number of
+    True values in `mask`, while `copyto` uses the elements where `mask`
+    is True.
 
     Note that `extract` does the exact opposite of `place`.
 
@@ -2713,7 +2719,7 @@ def kaiser(M,beta):
 
     A beta value of 14 is probably a good starting point. Note that as beta
     gets large, the window narrows, and so the number of samples needs to be
-    large enough to sample the increasingly narrow spike, otherwise nans will
+    large enough to sample the increasingly narrow spike, otherwise NaNs will
     get returned.
 
     Most references to the Kaiser window come from the signal processing
diff --git a/numpy/lib/npyio.py b/numpy/lib/npyio.py
index 221529929..b63003f80 100644
--- a/numpy/lib/npyio.py
+++ b/numpy/lib/npyio.py
@@ -359,7 +359,6 @@ def load(file, mmap_mode=None):
         own_fid = True
     elif isinstance(file, gzip.GzipFile):
         fid = seek_gzip_factory(file)
-        own_fid = True
     else:
         fid = file
 
@@ -371,7 +370,7 @@ def load(file, mmap_mode=None):
         fid.seek(-N, 1) # back-up
         if magic.startswith(_ZIP_PREFIX):  # zip-file (assume .npz)
             own_fid = False
-            return NpzFile(fid, own_fid=True)
+            return NpzFile(fid, own_fid=own_fid)
         elif magic == format.MAGIC_PREFIX: # .npy file
             if mmap_mode:
                 return format.open_memmap(file, mode=mmap_mode)
@@ -471,8 +470,7 @@ def savez(file, *args, **kwds):
     --------
     save : Save a single array to a binary file in NumPy format.
     savetxt : Save an array to a file as plain text.
-    numpy.savez_compressed : Save several arrays into a compressed .npz file
-    format
+    savez_compressed : Save several arrays into a compressed .npz file format
 
     Notes
     -----
@@ -1293,7 +1291,8 @@ def genfromtxt(fname, dtype=float, comments='#', delimiter=None,
 
     """
     # Py3 data conversions to bytes, for convenience
-    comments = asbytes(comments)
+    if comments is not None:
+        comments = asbytes(comments)
     if isinstance(delimiter, unicode):
         delimiter = asbytes(delimiter)
     if isinstance(missing, unicode):
diff --git a/numpy/lib/src/_compiled_base.c b/numpy/lib/src/_compiled_base.c
index c31ee5cd8..d389b7f8e 100644
--- a/numpy/lib/src/_compiled_base.c
+++ b/numpy/lib/src/_compiled_base.c
@@ -7,6 +7,10 @@
 #include "numpy/ufuncobject.h"
 #include "string.h"
 
+#if (PY_VERSION_HEX < 0x02060000)
+#define Py_TYPE(o)    (((PyObject*)(o))->ob_type)
+#endif
+
 static npy_intp
 incr_slot_(double x, double *bins, npy_intp lbins)
 {
@@ -670,7 +674,10 @@ arr_interp(PyObject *NPY_UNUSED(self), PyObject *args, PyObject *kwdict)
 
     /* only pre-calculate slopes if there are relatively few of them. */
     if (lenxp <= lenx) {
-        slopes = (double *) PyDataMem_NEW((lenxp - 1)*sizeof(double));
+        slopes = (double *) PyArray_malloc((lenxp - 1)*sizeof(double));
+        if (! slopes) {
+            goto fail;
+        }
         NPY_BEGIN_ALLOW_THREADS;
         for (i = 0; i < lenxp - 1; i++) {
             slopes[i] = (dy[i + 1] - dy[i])/(dx[i + 1] - dx[i]);
@@ -692,7 +699,7 @@ arr_interp(PyObject *NPY_UNUSED(self), PyObject *args, PyObject *kwdict)
             }
         }
         NPY_END_ALLOW_THREADS;
-        PyDataMem_FREE(slopes);
+        PyArray_free(slopes);
     }
     else {
         NPY_BEGIN_ALLOW_THREADS;
diff --git a/numpy/lib/tests/test_arraysetops.py b/numpy/lib/tests/test_arraysetops.py
index e40c155a4..b0d2ca7c3 100644
--- a/numpy/lib/tests/test_arraysetops.py
+++ b/numpy/lib/tests/test_arraysetops.py
@@ -8,31 +8,62 @@ from numpy.lib.arraysetops import *
 
 import warnings
 
-class TestAso(TestCase):
-    def test_unique( self ):
-        a = np.array( [5, 7, 1, 2, 1, 5, 7] )
-
-        ec = np.array( [1, 2, 5, 7] )
-        c = unique( a )
-        assert_array_equal( c, ec )
-
-        vals, indices = unique( a, return_index=True )
+class TestSetOps(TestCase):
 
 
-        ed = np.array( [2, 3, 0, 1] )
-        assert_array_equal(vals, ec)
-        assert_array_equal(indices, ed)
-
-        vals, ind0, ind1 = unique( a, return_index=True,
-                                     return_inverse=True )
-
+    def test_unique( self ):
 
-        ee = np.array( [2, 3, 0, 1, 0, 2, 3] )
-        assert_array_equal(vals, ec)
-        assert_array_equal(ind0, ed)
-        assert_array_equal(ind1, ee)
+        def check_all(a, b, i1, i2, dt):
+            msg = "check values failed for type '%s'" % dt
+            v = unique(a)
+            assert_array_equal(v, b, msg)
+
+            msg = "check indexes failed for type '%s'" % dt
+            v, j = unique(a, 1, 0)
+            assert_array_equal(v, b, msg)
+            assert_array_equal(j, i1, msg)
+
+            msg = "check reverse indexes failed for type '%s'" % dt
+            v, j = unique(a, 0, 1)
+            assert_array_equal(v, b, msg)
+            assert_array_equal(j, i2, msg)
+
+            msg = "check with all indexes failed for type '%s'" % dt
+            v, j1, j2 = unique(a, 1, 1)
+            assert_array_equal(v, b, msg)
+            assert_array_equal(j1, i1, msg)
+            assert_array_equal(j2, i2, msg)
+
+        a = [5, 7, 1, 2, 1, 5, 7]*10
+        b = [1, 2, 5, 7]
+        i1 = [2, 3, 0, 1]
+        i2 = [2, 3, 0, 1, 0, 2, 3]*10
+
+        # test for numeric arrays
+        types = []
+        types.extend(np.typecodes['AllInteger'])
+        types.extend(np.typecodes['AllFloat'])
+        types.append('datetime64[D]')
+        types.append('timedelta64[D]')
+        for dt in types:
+            aa = np.array(a, dt)
+            bb = np.array(b, dt)
+            check_all(aa, bb, i1, i2, dt)
+
+        # test for object arrays
+        dt = 'O'
+        aa = np.empty(len(a), dt)
+        aa[:] = a
+        bb = np.empty(len(b), dt)
+        bb[:] = b
+        check_all(aa, bb, i1, i2, dt)
+
+        # test for structured arrays
+        dt = [('', 'i'), ('', 'i')]
+        aa = np.array(zip(a,a), dt)
+        bb = np.array(zip(b,b), dt)
+        check_all(aa, bb, i1, i2, dt)
 
-        assert_array_equal([], unique([]))
 
     def test_intersect1d( self ):
         # unique inputs
diff --git a/numpy/lib/tests/test_io.py b/numpy/lib/tests/test_io.py
index 8922070df..f8caeedb6 100644
--- a/numpy/lib/tests/test_io.py
+++ b/numpy/lib/tests/test_io.py
@@ -167,6 +167,52 @@ class TestSavezLoad(RoundtripTest, TestCase):
         if errors:
             raise AssertionError(errors)
 
+    def test_not_closing_opened_fid(self):
+        # Test that issue #2178 is fixed:
+        # verify could seek on 'loaded' file
+
+        fd, tmp = mkstemp(suffix='.npz')
+        os.close(fd)
+        try:
+            fp = open(tmp, 'wb')
+            np.savez(fp, data='LOVELY LOAD')
+            fp.close()
+
+            fp = open(tmp, 'rb', 10000)
+            fp.seek(0)
+            assert_(not fp.closed)
+            _ = np.load(fp)['data']
+            assert_(not fp.closed)        # must not get closed by .load(opened fp)
+            fp.seek(0)
+            assert_(not fp.closed)
+
+        finally:
+            fp.close()
+            os.remove(tmp)
+
+    def test_closing_fid(self):
+        # Test that issue #1517 (too many opened files) remains closed
+        # It might be a "week" test since failed to get triggered on
+        # e.g. Debian sid of 2012 Jul 05 but was reported to
+        # trigger the failure on Ubuntu 10.04:
+        # http://projects.scipy.org/numpy/ticket/1517#comment:2
+        fd, tmp = mkstemp(suffix='.npz')
+        os.close(fd)
+
+        try:
+            fp = open(tmp, 'wb')
+            np.savez(fp, data='LOVELY LOAD')
+            fp.close()
+
+            for i in range(1, 1025):
+                try:
+                    np.load(tmp)["data"]
+                except Exception, e:
+                    raise AssertionError("Failed to load data from a file: %s" % e)
+        finally:
+            os.remove(tmp)
+
+
 class TestSaveTxt(TestCase):
     def test_array(self):
         a = np.array([[1, 2], [3, 4]], float)
@@ -1381,8 +1427,6 @@ M   33  21.99
                              usecols=("A", "C", "E"), names=True)
         assert_equal(test.dtype.names, ctrl_names)
 
-
-
     def test_fixed_width_names(self):
         "Test fix-width w/ names"
         data = "    A    B   C\n    0    1 2.3\n   45   67   9."
@@ -1406,6 +1450,14 @@ M   33  21.99
         test = np.ndfromtxt(StringIO(data), **kwargs)
         assert_equal(test, ctrl)
 
+    def test_comments_is_none(self):
+        # Github issue 329 (None was previously being converted to 'None').
+        test = np.genfromtxt(StringIO("test1,testNonetherestofthedata"),
+                             dtype=None, comments=None, delimiter=',')
+        assert_equal(test[1], asbytes('testNonetherestofthedata'))
+        test = np.genfromtxt(StringIO("test1, testNonetherestofthedata"),
+                             dtype=None, comments=None, delimiter=',')
+        assert_equal(test[1], asbytes(' testNonetherestofthedata'))
 
     def test_recfromtxt(self):
         #
@@ -1426,7 +1478,6 @@ M   33  21.99
         assert_equal(test.mask, control.mask)
         assert_equal(test.A, [0, 2])
 
-
     def test_recfromcsv(self):
         #
         data = StringIO('A,B\n0,1\n2,3')
diff --git a/numpy/lib/type_check.py b/numpy/lib/type_check.py
index c116c7e4a..e22d63156 100644
--- a/numpy/lib/type_check.py
+++ b/numpy/lib/type_check.py
@@ -233,11 +233,10 @@ def isreal(x):
 
 def iscomplexobj(x):
     """
-    Return True if x is a complex type or an array of complex numbers.
+    Check for a complex type or an array of complex numbers.
 
-    The type of the input is checked, not the value. So even if the input
-    has an imaginary part equal to zero, `iscomplexobj` evaluates to True
-    if the data type is complex.
+    The type of the input is checked, not the value. Even if the input
+    has an imaginary part equal to zero, `iscomplexobj` evaluates to True.
 
     Parameters
     ----------
@@ -246,8 +245,9 @@ def iscomplexobj(x):
 
     Returns
     -------
-    y : bool
-        The return value, True if `x` is of a complex type.
+    iscomplexobj : bool
+        The return value, True if `x` is of a complex type or has at least
+        one complex element.
 
     See Also
     --------