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-rw-r--r--numpy/lib/tests/test_arraypad.py15
-rw-r--r--numpy/lib/tests/test_format.py9
-rw-r--r--numpy/lib/tests/test_function_base.py36
-rw-r--r--numpy/lib/tests/test_histograms.py94
-rw-r--r--numpy/lib/tests/test_polynomial.py150
-rw-r--r--numpy/lib/tests/test_recfunctions.py16
-rw-r--r--numpy/lib/tests/test_shape_base.py9
-rw-r--r--numpy/lib/tests/test_twodim_base.py6
-rw-r--r--numpy/lib/tests/test_ufunclike.py15
9 files changed, 236 insertions, 114 deletions
diff --git a/numpy/lib/tests/test_arraypad.py b/numpy/lib/tests/test_arraypad.py
index 8ba0370b0..45d624781 100644
--- a/numpy/lib/tests/test_arraypad.py
+++ b/numpy/lib/tests/test_arraypad.py
@@ -1009,6 +1009,21 @@ class TestUnicodeInput(object):
assert_array_equal(a, b)
+class TestObjectInput(object):
+ def test_object_input(self):
+ # Regression test for issue gh-11395.
+ a = np.full((4, 3), None)
+ pad_amt = ((2, 3), (3, 2))
+ b = np.full((9, 8), None)
+ modes = ['edge',
+ 'symmetric',
+ 'reflect',
+ 'wrap',
+ ]
+ for mode in modes:
+ assert_array_equal(pad(a, pad_amt, mode=mode), b)
+
+
class TestValueError1(object):
def test_check_simple(self):
arr = np.arange(30)
diff --git a/numpy/lib/tests/test_format.py b/numpy/lib/tests/test_format.py
index 38a9b8000..c7869c582 100644
--- a/numpy/lib/tests/test_format.py
+++ b/numpy/lib/tests/test_format.py
@@ -479,7 +479,7 @@ def test_long_str():
@pytest.mark.slow
def test_memmap_roundtrip():
- # Fixme: test crashes nose on windows.
+ # Fixme: used to crash on windows
if not (sys.platform == 'win32' or sys.platform == 'cygwin'):
for arr in basic_arrays + record_arrays:
if arr.dtype.hasobject:
@@ -852,3 +852,10 @@ def test_large_archive():
new_a = np.load(f)["arr"]
assert_(a.shape == new_a.shape)
+
+
+def test_empty_npz():
+ # Test for gh-9989
+ fname = os.path.join(tempdir, "nothing.npz")
+ np.savez(fname)
+ np.load(fname)
diff --git a/numpy/lib/tests/test_function_base.py b/numpy/lib/tests/test_function_base.py
index 4103a9eb3..d5faed6ae 100644
--- a/numpy/lib/tests/test_function_base.py
+++ b/numpy/lib/tests/test_function_base.py
@@ -1043,6 +1043,16 @@ class TestAngle(object):
assert_array_almost_equal(y, yo, 11)
assert_array_almost_equal(z, zo, 11)
+ def test_subclass(self):
+ x = np.ma.array([1 + 3j, 1, np.sqrt(2)/2 * (1 + 1j)])
+ x[1] = np.ma.masked
+ expected = np.ma.array([np.arctan(3.0 / 1.0), 0, np.arctan(1.0)])
+ expected[1] = np.ma.masked
+ actual = angle(x)
+ assert_equal(type(actual), type(expected))
+ assert_equal(actual.mask, expected.mask)
+ assert_equal(actual, expected)
+
class TestTrimZeros(object):
@@ -1510,6 +1520,18 @@ class TestDigitize(object):
assert_(not isinstance(digitize(b, a, False), A))
assert_(not isinstance(digitize(b, a, True), A))
+ def test_large_integers_increasing(self):
+ # gh-11022
+ x = 2**54 # loses precision in a float
+ assert_equal(np.digitize(x, [x - 1, x + 1]), 1)
+
+ @pytest.mark.xfail(
+ reason="gh-11022: np.core.multiarray._monoticity loses precision")
+ def test_large_integers_decreasing(self):
+ # gh-11022
+ x = 2**54 # loses precision in a float
+ assert_equal(np.digitize(x, [x + 1, x - 1]), 1)
+
class TestUnwrap(object):
@@ -2237,6 +2259,14 @@ class TestInterp(object):
x0 = np.nan
assert_almost_equal(np.interp(x0, x, y), x0)
+ def test_non_finite_behavior(self):
+ x = [1, 2, 2.5, 3, 4]
+ xp = [1, 2, 3, 4]
+ fp = [1, 2, np.inf, 4]
+ assert_almost_equal(np.interp(x, xp, fp), [1, 2, np.inf, np.inf, 4])
+ fp = [1, 2, np.nan, 4]
+ assert_almost_equal(np.interp(x, xp, fp), [1, 2, np.nan, np.nan, 4])
+
def test_complex_interp(self):
# test complex interpolation
x = np.linspace(0, 1, 5)
@@ -2251,6 +2281,12 @@ class TestInterp(object):
x0 = 2.0
right = 2 + 3.0j
assert_almost_equal(np.interp(x0, x, y, right=right), right)
+ # test complex non finite
+ x = [1, 2, 2.5, 3, 4]
+ xp = [1, 2, 3, 4]
+ fp = [1, 2+1j, np.inf, 4]
+ y = [1, 2+1j, np.inf+0.5j, np.inf, 4]
+ assert_almost_equal(np.interp(x, xp, fp), y)
# test complex periodic
x = [-180, -170, -185, 185, -10, -5, 0, 365]
xp = [190, -190, 350, -350]
diff --git a/numpy/lib/tests/test_histograms.py b/numpy/lib/tests/test_histograms.py
index e16ae12c2..f136b5c81 100644
--- a/numpy/lib/tests/test_histograms.py
+++ b/numpy/lib/tests/test_histograms.py
@@ -40,20 +40,28 @@ class TestHistogram(object):
assert_allclose(e, np.array([1., 2.]))
def test_normed(self):
- # Check that the integral of the density equals 1.
- n = 100
- v = np.random.rand(n)
- a, b = histogram(v, normed=True)
- area = np.sum(a * np.diff(b))
- assert_almost_equal(area, 1)
+ sup = suppress_warnings()
+ with sup:
+ rec = sup.record(np.VisibleDeprecationWarning, '.*normed.*')
+ # Check that the integral of the density equals 1.
+ n = 100
+ v = np.random.rand(n)
+ a, b = histogram(v, normed=True)
+ area = np.sum(a * np.diff(b))
+ assert_almost_equal(area, 1)
+ assert_equal(len(rec), 1)
- # Check with non-constant bin widths (buggy but backwards
- # compatible)
- v = np.arange(10)
- bins = [0, 1, 5, 9, 10]
- a, b = histogram(v, bins, normed=True)
- area = np.sum(a * np.diff(b))
- assert_almost_equal(area, 1)
+ sup = suppress_warnings()
+ with sup:
+ rec = sup.record(np.VisibleDeprecationWarning, '.*normed.*')
+ # Check with non-constant bin widths (buggy but backwards
+ # compatible)
+ v = np.arange(10)
+ bins = [0, 1, 5, 9, 10]
+ a, b = histogram(v, bins, normed=True)
+ area = np.sum(a * np.diff(b))
+ assert_almost_equal(area, 1)
+ assert_equal(len(rec), 1)
def test_density(self):
# Check that the integral of the density equals 1.
@@ -70,6 +78,10 @@ class TestHistogram(object):
assert_array_equal(a, .1)
assert_equal(np.sum(a * np.diff(b)), 1)
+ # Test that passing False works too
+ a, b = histogram(v, bins, density=False)
+ assert_array_equal(a, [1, 2, 3, 4])
+
# Variale bin widths are especially useful to deal with
# infinities.
v = np.arange(10)
@@ -96,12 +108,12 @@ class TestHistogram(object):
assert_equal(h.sum(), 9)
# Normalization
- h, b = histogram(a, range=[1, 9], normed=True)
+ h, b = histogram(a, range=[1, 9], density=True)
assert_almost_equal((h * np.diff(b)).sum(), 1, decimal=15)
# Weights
w = np.arange(10) + .5
- h, b = histogram(a, range=[1, 9], weights=w, normed=True)
+ h, b = histogram(a, range=[1, 9], weights=w, density=True)
assert_equal((h * np.diff(b)).sum(), 1)
h, b = histogram(a, bins=8, range=[1, 9], weights=w)
@@ -113,7 +125,7 @@ class TestHistogram(object):
h, b = histogram(a)
assert_(np.issubdtype(h.dtype, np.integer))
- h, b = histogram(a, normed=True)
+ h, b = histogram(a, density=True)
assert_(np.issubdtype(h.dtype, np.floating))
h, b = histogram(a, weights=np.ones(10, int))
@@ -133,9 +145,9 @@ class TestHistogram(object):
v = np.random.rand(100)
w = np.ones(100) * 5
a, b = histogram(v)
- na, nb = histogram(v, normed=True)
+ na, nb = histogram(v, density=True)
wa, wb = histogram(v, weights=w)
- nwa, nwb = histogram(v, weights=w, normed=True)
+ nwa, nwb = histogram(v, weights=w, density=True)
assert_array_almost_equal(a * 5, wa)
assert_array_almost_equal(na, nwa)
@@ -149,7 +161,7 @@ class TestHistogram(object):
wa, wb = histogram([1, 2, 2, 4], bins=4, weights=[4, 3, 2, 1])
assert_array_equal(wa, [4, 5, 0, 1])
wa, wb = histogram(
- [1, 2, 2, 4], bins=4, weights=[4, 3, 2, 1], normed=True)
+ [1, 2, 2, 4], bins=4, weights=[4, 3, 2, 1], density=True)
assert_array_almost_equal(wa, np.array([4, 5, 0, 1]) / 10. / 3. * 4)
# Check weights with non-uniform bin widths
@@ -535,13 +547,13 @@ class TestHistogramdd(object):
# Check normalization
ed = [[-2, 0, 2], [0, 1, 2, 3], [0, 1, 2, 3]]
- H, edges = histogramdd(x, bins=ed, normed=True)
+ H, edges = histogramdd(x, bins=ed, density=True)
assert_(np.all(H == answer / 12.))
# Check that H has the correct shape.
H, edges = histogramdd(x, (2, 3, 4),
range=[[-1, 1], [0, 3], [0, 4]],
- normed=True)
+ density=True)
answer = np.array([[[0, 1, 0, 0], [0, 0, 1, 0], [1, 0, 0, 0]],
[[0, 1, 0, 0], [0, 0, 1, 0], [0, 0, 1, 0]]])
assert_array_almost_equal(H, answer / 6., 4)
@@ -587,10 +599,10 @@ class TestHistogramdd(object):
def test_weights(self):
v = np.random.rand(100, 2)
hist, edges = histogramdd(v)
- n_hist, edges = histogramdd(v, normed=True)
+ n_hist, edges = histogramdd(v, density=True)
w_hist, edges = histogramdd(v, weights=np.ones(100))
assert_array_equal(w_hist, hist)
- w_hist, edges = histogramdd(v, weights=np.ones(100) * 2, normed=True)
+ w_hist, edges = histogramdd(v, weights=np.ones(100) * 2, density=True)
assert_array_equal(w_hist, n_hist)
w_hist, edges = histogramdd(v, weights=np.ones(100, int) * 2)
assert_array_equal(w_hist, 2 * hist)
@@ -695,3 +707,39 @@ class TestHistogramdd(object):
hist, edges = histogramdd((x, y), bins=(x_edges, y_edges))
assert_equal(hist[0, 0], 1)
+
+ def test_density_non_uniform_2d(self):
+ # Defines the following grid:
+ #
+ # 0 2 8
+ # 0+-+-----+
+ # + | +
+ # + | +
+ # 6+-+-----+
+ # 8+-+-----+
+ x_edges = np.array([0, 2, 8])
+ y_edges = np.array([0, 6, 8])
+ relative_areas = np.array([
+ [3, 9],
+ [1, 3]])
+
+ # ensure the number of points in each region is proportional to its area
+ x = np.array([1] + [1]*3 + [7]*3 + [7]*9)
+ y = np.array([7] + [1]*3 + [7]*3 + [1]*9)
+
+ # sanity check that the above worked as intended
+ hist, edges = histogramdd((y, x), bins=(y_edges, x_edges))
+ assert_equal(hist, relative_areas)
+
+ # resulting histogram should be uniform, since counts and areas are propotional
+ hist, edges = histogramdd((y, x), bins=(y_edges, x_edges), density=True)
+ assert_equal(hist, 1 / (8*8))
+
+ def test_density_non_uniform_1d(self):
+ # compare to histogram to show the results are the same
+ v = np.arange(10)
+ bins = np.array([0, 1, 3, 6, 10])
+ hist, edges = histogram(v, bins, density=True)
+ hist_dd, edges_dd = histogramdd((v,), (bins,), density=True)
+ assert_equal(hist, hist_dd)
+ assert_equal(edges, edges_dd[0])
diff --git a/numpy/lib/tests/test_polynomial.py b/numpy/lib/tests/test_polynomial.py
index 7f6fca4a4..9f7c117a2 100644
--- a/numpy/lib/tests/test_polynomial.py
+++ b/numpy/lib/tests/test_polynomial.py
@@ -1,93 +1,79 @@
-'''
->>> p = np.poly1d([1.,2,3])
->>> p
-poly1d([1., 2., 3.])
->>> print(p)
- 2
-1 x + 2 x + 3
->>> q = np.poly1d([3.,2,1])
->>> q
-poly1d([3., 2., 1.])
->>> print(q)
- 2
-3 x + 2 x + 1
->>> print(np.poly1d([1.89999+2j, -3j, -5.12345678, 2+1j]))
- 3 2
-(1.9 + 2j) x - 3j x - 5.123 x + (2 + 1j)
->>> print(np.poly1d([-3, -2, -1]))
- 2
--3 x - 2 x - 1
-
->>> p(0)
-3.0
->>> p(5)
-38.0
->>> q(0)
-1.0
->>> q(5)
-86.0
-
->>> p * q
-poly1d([ 3., 8., 14., 8., 3.])
->>> p / q
-(poly1d([0.33333333]), poly1d([1.33333333, 2.66666667]))
->>> p + q
-poly1d([4., 4., 4.])
->>> p - q
-poly1d([-2., 0., 2.])
->>> p ** 4
-poly1d([ 1., 8., 36., 104., 214., 312., 324., 216., 81.])
-
->>> p(q)
-poly1d([ 9., 12., 16., 8., 6.])
->>> q(p)
-poly1d([ 3., 12., 32., 40., 34.])
-
->>> np.asarray(p)
-array([1., 2., 3.])
->>> len(p)
-2
-
->>> p[0], p[1], p[2], p[3]
-(3.0, 2.0, 1.0, 0)
-
->>> p.integ()
-poly1d([0.33333333, 1. , 3. , 0. ])
->>> p.integ(1)
-poly1d([0.33333333, 1. , 3. , 0. ])
->>> p.integ(5)
-poly1d([0.00039683, 0.00277778, 0.025 , 0. , 0. ,
- 0. , 0. , 0. ])
->>> p.deriv()
-poly1d([2., 2.])
->>> p.deriv(2)
-poly1d([2.])
-
->>> q = np.poly1d([1.,2,3], variable='y')
->>> print(q)
- 2
-1 y + 2 y + 3
->>> q = np.poly1d([1.,2,3], variable='lambda')
->>> print(q)
- 2
-1 lambda + 2 lambda + 3
-
->>> np.polydiv(np.poly1d([1,0,-1]), np.poly1d([1,1]))
-(poly1d([ 1., -1.]), poly1d([0.]))
-
-'''
from __future__ import division, absolute_import, print_function
import numpy as np
from numpy.testing import (
assert_, assert_equal, assert_array_equal, assert_almost_equal,
- assert_array_almost_equal, assert_raises, rundocs
+ assert_array_almost_equal, assert_raises
)
-class TestDocs(object):
- def test_doctests(self):
- return rundocs()
+class TestPolynomial(object):
+ def test_poly1d_str_and_repr(self):
+ p = np.poly1d([1., 2, 3])
+ assert_equal(repr(p), 'poly1d([1., 2., 3.])')
+ assert_equal(str(p),
+ ' 2\n'
+ '1 x + 2 x + 3')
+
+ q = np.poly1d([3., 2, 1])
+ assert_equal(repr(q), 'poly1d([3., 2., 1.])')
+ assert_equal(str(q),
+ ' 2\n'
+ '3 x + 2 x + 1')
+
+ r = np.poly1d([1.89999 + 2j, -3j, -5.12345678, 2 + 1j])
+ assert_equal(str(r),
+ ' 3 2\n'
+ '(1.9 + 2j) x - 3j x - 5.123 x + (2 + 1j)')
+
+ assert_equal(str(np.poly1d([-3, -2, -1])),
+ ' 2\n'
+ '-3 x - 2 x - 1')
+
+ def test_poly1d_resolution(self):
+ p = np.poly1d([1., 2, 3])
+ q = np.poly1d([3., 2, 1])
+ assert_equal(p(0), 3.0)
+ assert_equal(p(5), 38.0)
+ assert_equal(q(0), 1.0)
+ assert_equal(q(5), 86.0)
+
+ def test_poly1d_math(self):
+ # here we use some simple coeffs to make calculations easier
+ p = np.poly1d([1., 2, 4])
+ q = np.poly1d([4., 2, 1])
+ assert_equal(p/q, (np.poly1d([0.25]), np.poly1d([1.5, 3.75])))
+ assert_equal(p.integ(), np.poly1d([1/3, 1., 4., 0.]))
+ assert_equal(p.integ(1), np.poly1d([1/3, 1., 4., 0.]))
+
+ p = np.poly1d([1., 2, 3])
+ q = np.poly1d([3., 2, 1])
+ assert_equal(p * q, np.poly1d([3., 8., 14., 8., 3.]))
+ assert_equal(p + q, np.poly1d([4., 4., 4.]))
+ assert_equal(p - q, np.poly1d([-2., 0., 2.]))
+ assert_equal(p ** 4, np.poly1d([1., 8., 36., 104., 214., 312., 324., 216., 81.]))
+ assert_equal(p(q), np.poly1d([9., 12., 16., 8., 6.]))
+ assert_equal(q(p), np.poly1d([3., 12., 32., 40., 34.]))
+ assert_equal(p.deriv(), np.poly1d([2., 2.]))
+ assert_equal(p.deriv(2), np.poly1d([2.]))
+ assert_equal(np.polydiv(np.poly1d([1, 0, -1]), np.poly1d([1, 1])),
+ (np.poly1d([1., -1.]), np.poly1d([0.])))
+
+ def test_poly1d_misc(self):
+ p = np.poly1d([1., 2, 3])
+ assert_equal(np.asarray(p), np.array([1., 2., 3.]))
+ assert_equal(len(p), 2)
+ assert_equal((p[0], p[1], p[2], p[3]), (3.0, 2.0, 1.0, 0))
+
+ def test_poly1d_variable_arg(self):
+ q = np.poly1d([1., 2, 3], variable='y')
+ assert_equal(str(q),
+ ' 2\n'
+ '1 y + 2 y + 3')
+ q = np.poly1d([1., 2, 3], variable='lambda')
+ assert_equal(str(q),
+ ' 2\n'
+ '1 lambda + 2 lambda + 3')
def test_poly(self):
assert_array_almost_equal(np.poly([3, -np.sqrt(2), np.sqrt(2)]),
diff --git a/numpy/lib/tests/test_recfunctions.py b/numpy/lib/tests/test_recfunctions.py
index 219ae24fa..d4828bc1f 100644
--- a/numpy/lib/tests/test_recfunctions.py
+++ b/numpy/lib/tests/test_recfunctions.py
@@ -9,8 +9,8 @@ from numpy.ma.testutils import assert_equal
from numpy.testing import assert_, assert_raises
from numpy.lib.recfunctions import (
drop_fields, rename_fields, get_fieldstructure, recursive_fill_fields,
- find_duplicates, merge_arrays, append_fields, stack_arrays, join_by
- )
+ find_duplicates, merge_arrays, append_fields, stack_arrays, join_by,
+ repack_fields)
get_names = np.lib.recfunctions.get_names
get_names_flat = np.lib.recfunctions.get_names_flat
zip_descr = np.lib.recfunctions.zip_descr
@@ -192,6 +192,18 @@ class TestRecFunctions(object):
assert_equal(sorted(test[-1]), control)
assert_equal(test[0], a[test[-1]])
+ def test_repack_fields(self):
+ dt = np.dtype('u1,f4,i8', align=True)
+ a = np.zeros(2, dtype=dt)
+
+ assert_equal(repack_fields(dt), np.dtype('u1,f4,i8'))
+ assert_equal(repack_fields(a).itemsize, 13)
+ assert_equal(repack_fields(repack_fields(dt), align=True), dt)
+
+ # make sure type is preserved
+ dt = np.dtype((np.record, dt))
+ assert_(repack_fields(dt).type is np.record)
+
class TestRecursiveFillFields(object):
# Test recursive_fill_fields.
diff --git a/numpy/lib/tests/test_shape_base.py b/numpy/lib/tests/test_shape_base.py
index c95894f94..6d24dd624 100644
--- a/numpy/lib/tests/test_shape_base.py
+++ b/numpy/lib/tests/test_shape_base.py
@@ -293,6 +293,15 @@ class TestExpandDims(object):
assert_warns(DeprecationWarning, expand_dims, a, -6)
assert_warns(DeprecationWarning, expand_dims, a, 5)
+ def test_subclasses(self):
+ a = np.arange(10).reshape((2, 5))
+ a = np.ma.array(a, mask=a%3 == 0)
+
+ expanded = np.expand_dims(a, axis=1)
+ assert_(isinstance(expanded, np.ma.MaskedArray))
+ assert_equal(expanded.shape, (2, 1, 5))
+ assert_equal(expanded.mask.shape, (2, 1, 5))
+
class TestArraySplit(object):
def test_integer_0_split(self):
diff --git a/numpy/lib/tests/test_twodim_base.py b/numpy/lib/tests/test_twodim_base.py
index d3a072af3..bf93b4adb 100644
--- a/numpy/lib/tests/test_twodim_base.py
+++ b/numpy/lib/tests/test_twodim_base.py
@@ -208,7 +208,7 @@ class TestHistogram2d(object):
x = array([1, 1, 2, 3, 4, 4, 4, 5])
y = array([1, 3, 2, 0, 1, 2, 3, 4])
H, xed, yed = histogram2d(
- x, y, (6, 5), range=[[0, 6], [0, 5]], normed=True)
+ x, y, (6, 5), range=[[0, 6], [0, 5]], density=True)
answer = array(
[[0., 0, 0, 0, 0],
[0, 1, 0, 1, 0],
@@ -220,11 +220,11 @@ class TestHistogram2d(object):
assert_array_equal(xed, np.linspace(0, 6, 7))
assert_array_equal(yed, np.linspace(0, 5, 6))
- def test_norm(self):
+ def test_density(self):
x = array([1, 2, 3, 1, 2, 3, 1, 2, 3])
y = array([1, 1, 1, 2, 2, 2, 3, 3, 3])
H, xed, yed = histogram2d(
- x, y, [[1, 2, 3, 5], [1, 2, 3, 5]], normed=True)
+ x, y, [[1, 2, 3, 5], [1, 2, 3, 5]], density=True)
answer = array([[1, 1, .5],
[1, 1, .5],
[.5, .5, .25]])/9.
diff --git a/numpy/lib/tests/test_ufunclike.py b/numpy/lib/tests/test_ufunclike.py
index 5604b3744..0f06876a1 100644
--- a/numpy/lib/tests/test_ufunclike.py
+++ b/numpy/lib/tests/test_ufunclike.py
@@ -4,8 +4,8 @@ import numpy as np
import numpy.core as nx
import numpy.lib.ufunclike as ufl
from numpy.testing import (
- assert_, assert_equal, assert_array_equal, assert_warns
- )
+ assert_, assert_equal, assert_array_equal, assert_warns, assert_raises
+)
class TestUfunclike(object):
@@ -21,6 +21,10 @@ class TestUfunclike(object):
assert_equal(res, tgt)
assert_equal(out, tgt)
+ a = a.astype(np.complex)
+ with assert_raises(TypeError):
+ ufl.isposinf(a)
+
def test_isneginf(self):
a = nx.array([nx.inf, -nx.inf, nx.nan, 0.0, 3.0, -3.0])
out = nx.zeros(a.shape, bool)
@@ -32,6 +36,10 @@ class TestUfunclike(object):
assert_equal(res, tgt)
assert_equal(out, tgt)
+ a = a.astype(np.complex)
+ with assert_raises(TypeError):
+ ufl.isneginf(a)
+
def test_fix(self):
a = nx.array([[1.0, 1.1, 1.5, 1.8], [-1.0, -1.1, -1.5, -1.8]])
out = nx.zeros(a.shape, float)
@@ -52,7 +60,8 @@ class TestUfunclike(object):
return res
def __array_wrap__(self, obj, context=None):
- obj.metadata = self.metadata
+ if isinstance(obj, MyArray):
+ obj.metadata = self.metadata
return obj
def __array_finalize__(self, obj):
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