7 files changed, 64 insertions, 20 deletions
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py
index 0a1d05f77..618a93bb9 100644
--- a/numpy/lib/function_base.py
+++ b/numpy/lib/function_base.py
@@ -337,6 +337,11 @@ def histogramdd(sample, bins=10, range=None, normed=False, weights=None):
             smin[i] = smin[i] - .5
             smax[i] = smax[i] + .5
 
+    # avoid rounding issues for comparisons when dealing with inexact types
+    if np.issubdtype(sample.dtype, np.inexact):
+        edge_dt = sample.dtype
+    else:
+        edge_dt = float
     # Create edge arrays
     for i in arange(D):
         if isscalar(bins[i]):
@@ -345,9 +350,9 @@ def histogramdd(sample, bins=10, range=None, normed=False, weights=None):
                     "Element at index %s in `bins` should be a positive "
                     "integer." % i)
             nbin[i] = bins[i] + 2  # +2 for outlier bins
-            edges[i] = linspace(smin[i], smax[i], nbin[i]-1)
+            edges[i] = linspace(smin[i], smax[i], nbin[i]-1, dtype=edge_dt)
         else:
-            edges[i] = asarray(bins[i], float)
+            edges[i] = asarray(bins[i], edge_dt)
             nbin[i] = len(edges[i]) + 1  # +1 for outlier bins
         dedges[i] = diff(edges[i])
         if np.any(np.asarray(dedges[i]) <= 0):
diff --git a/numpy/lib/nanfunctions.py b/numpy/lib/nanfunctions.py
index f5ac35e54..7260a35b8 100644
--- a/numpy/lib/nanfunctions.py
+++ b/numpy/lib/nanfunctions.py
@@ -33,6 +33,10 @@ def _replace_nan(a, val):
     marking the locations where NaNs were present. If `a` is not of
     inexact type, do nothing and return `a` together with a mask of None.
 
+    Note that scalars will end up as array scalars, which is important
+    for using the result as the value of the out argument in some
+    operations.
+
     Parameters
     ----------
     a : array-like
@@ -1037,7 +1041,7 @@ def nanvar(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False):
         avg = _divide_by_count(avg, cnt)
 
         # Compute squared deviation from mean.
-        arr -= avg
+        np.subtract(arr, avg, out=arr, casting='unsafe')
         arr = _copyto(arr, 0, mask)
         if issubclass(arr.dtype.type, np.complexfloating):
             sqr = np.multiply(arr, arr.conj(), out=arr).real
diff --git a/numpy/lib/npyio.py b/numpy/lib/npyio.py
index fe855a71a..0e49dd31c 100644
--- a/numpy/lib/npyio.py
+++ b/numpy/lib/npyio.py
@@ -288,8 +288,7 @@ def load(file, mmap_mode=None):
     Parameters
     ----------
     file : file-like object or string
-        The file to read. Compressed files with the filename extension
-        ``.gz`` are acceptable. File-like objects must support the
+        The file to read. File-like objects must support the
         ``seek()`` and ``read()`` methods. Pickled files require that the
         file-like object support the ``readline()`` method as well.
     mmap_mode : {None, 'r+', 'r', 'w+', 'c'}, optional
diff --git a/numpy/lib/tests/test_function_base.py b/numpy/lib/tests/test_function_base.py
index ee38b3573..ac677a308 100644
--- a/numpy/lib/tests/test_function_base.py
+++ b/numpy/lib/tests/test_function_base.py
@@ -1070,6 +1070,13 @@ class TestHistogram(TestCase):
         h, b = histogram(a, weights=np.ones(10, float))
         assert_(issubdtype(h.dtype, float))
 
+    def test_f32_rounding(self):
+        # gh-4799, check that the rounding of the edges works with float32
+        x = np.array([276.318359  , -69.593948  , 21.329449], dtype=np.float32)
+        y = np.array([5005.689453, 4481.327637, 6010.369629], dtype=np.float32)
+        counts_hist, xedges, yedges = np.histogram2d(x, y, bins=100)
+        assert_equal(counts_hist.sum(), 3.)
+
     def test_weights(self):
         v = rand(100)
         w = np.ones(100) * 5
diff --git a/numpy/lib/tests/test_io.py b/numpy/lib/tests/test_io.py
index 49ad1ba5b..03e238261 100644
--- a/numpy/lib/tests/test_io.py
+++ b/numpy/lib/tests/test_io.py
@@ -4,9 +4,7 @@ import sys
 import gzip
 import os
 import threading
-import shutil
-import contextlib
-from tempfile import mkstemp, mkdtemp, NamedTemporaryFile
+from tempfile import mkstemp, NamedTemporaryFile
 import time
 import warnings
 import gc
@@ -24,13 +22,7 @@ from numpy.ma.testutils import (
     assert_raises, assert_raises_regex, run_module_suite
 )
 from numpy.testing import assert_warns, assert_, build_err_msg
-
-
-@contextlib.contextmanager
-def tempdir(change_dir=False):
-    tmpdir = mkdtemp()
-    yield tmpdir
-    shutil.rmtree(tmpdir)
+from numpy.testing.utils import tempdir
 
 
 class TextIO(BytesIO):
@@ -202,7 +194,7 @@ class TestSavezLoad(RoundtripTest, TestCase):
     def test_big_arrays(self):
         L = (1 << 31) + 100000
         a = np.empty(L, dtype=np.uint8)
-        with tempdir() as tmpdir:
+        with tempdir(prefix="numpy_test_big_arrays_") as tmpdir:
             tmp = os.path.join(tmpdir, "file.npz")
             np.savez(tmp, a=a)
             del a
@@ -311,7 +303,7 @@ class TestSavezLoad(RoundtripTest, TestCase):
         # Check that zipfile owns file and can close it.
         # This needs to pass a file name to load for the
         # test.
-        with tempdir() as tmpdir:
+        with tempdir(prefix="numpy_test_closing_zipfile_after_load_") as tmpdir:
             fd, tmp = mkstemp(suffix='.npz', dir=tmpdir)
             os.close(fd)
             np.savez(tmp, lab='place holder')
diff --git a/numpy/lib/tests/test_twodim_base.py b/numpy/lib/tests/test_twodim_base.py
index e9dbef70f..739061a5d 100644
--- a/numpy/lib/tests/test_twodim_base.py
+++ b/numpy/lib/tests/test_twodim_base.py
@@ -311,6 +311,40 @@ def test_tril_triu_ndim3():
         yield assert_equal, a_triu_observed.dtype, a.dtype
         yield assert_equal, a_tril_observed.dtype, a.dtype
 
+def test_tril_triu_with_inf():
+    # Issue 4859
+    arr = np.array([[1, 1, np.inf],
+                    [1, 1, 1],
+                    [np.inf, 1, 1]])
+    out_tril = np.array([[1, 0, 0],
+                         [1, 1, 0],
+                         [np.inf, 1, 1]])
+    out_triu = out_tril.T
+    assert_array_equal(np.triu(arr), out_triu)
+    assert_array_equal(np.tril(arr), out_tril)
+
+
+def test_tril_triu_dtype():
+    # Issue 4916
+    # tril and triu should return the same dtype as input
+    for c in np.typecodes['All']:
+        if c == 'V':
+            continue
+        arr = np.zeros((3, 3), dtype=c)
+        assert_equal(np.triu(arr).dtype, arr.dtype)
+        assert_equal(np.tril(arr).dtype, arr.dtype)
+
+    # check special cases
+    arr = np.array([['2001-01-01T12:00', '2002-02-03T13:56'],
+                    ['2004-01-01T12:00', '2003-01-03T13:45']],
+                   dtype='datetime64')
+    assert_equal(np.triu(arr).dtype, arr.dtype)
+    assert_equal(np.tril(arr).dtype, arr.dtype)
+
+    arr = np.zeros((3,3), dtype='f4,f4')
+    assert_equal(np.triu(arr).dtype, arr.dtype)
+    assert_equal(np.tril(arr).dtype, arr.dtype)
+
 
 def test_mask_indices():
     # simple test without offset
diff --git a/numpy/lib/twodim_base.py b/numpy/lib/twodim_base.py
index 2861e1c4a..40a140b6b 100644
--- a/numpy/lib/twodim_base.py
+++ b/numpy/lib/twodim_base.py
@@ -387,7 +387,6 @@ def tri(N, M=None, k=0, dtype=float):
     dtype : dtype, optional
         Data type of the returned array.  The default is float.
 
-
     Returns
     -------
     tri : ndarray of shape (N, M)
@@ -452,7 +451,9 @@ def tril(m, k=0):
 
     """
     m = asanyarray(m)
-    return multiply(tri(*m.shape[-2:], k=k, dtype=bool), m, dtype=m.dtype)
+    mask = tri(*m.shape[-2:], k=k, dtype=bool)
+
+    return where(mask, m, zeros(1, m.dtype))
 
 
 def triu(m, k=0):
@@ -478,7 +479,9 @@ def triu(m, k=0):
 
     """
     m = asanyarray(m)
-    return multiply(~tri(*m.shape[-2:], k=k-1, dtype=bool), m, dtype=m.dtype)
+    mask = tri(*m.shape[-2:], k=k-1, dtype=bool)
+
+    return where(mask, zeros(1, m.dtype), m)
 
 
 # Originally borrowed from John Hunter and matplotlib