def test_recarray_numpy_dataview_pickle():
# not masked, int32
y = np.array([(1, 2, 3, 4, 5), (5, 4, 3, 2, 1)],
dtype=[('', np.int32)] * 5)
view = recarray_numpy_dataview(y)
bstr = pickle.dumps(view)
view1 = pickle.loads(bstr)
assert_list_equal(list(v for v in view), list(v for v in view1))
# not masked, float32
y = np.array([(1, 2, 3, 4, 5), (5, 4, 3, 2, 1)],
dtype=[('', np.float32)] * 5)
view = recarray_numpy_dataview(y)
bstr = pickle.dumps(view)
view1 = pickle.loads(bstr)
assert_1d_lists_almost_equals(
list(v for v in view), list(v for v in view1))
# masked, int32
y = np.array([(1, 2, 3, 4, 5), (5, 4, 3, 2, 1)],
dtype=[('', np.int32)] * 5)
mask = [(False, False, False, False, True),
(True, False, True, True, False)]
y = ma.array(y, mask=mask)
view = recarray_numpy_dataview(y)
bstr = pickle.dumps(view)
view1 = pickle.loads(bstr)
# XXX(stephentu): masked arrays suck and don't implement equality
r = repr(list(v for v in view))
r1 = repr(list(v for v in view1))
assert_equals(r, r1)
# masked, float32
y = np.array([(1, 2, 3, 4, 5), (5, 4, 3, 2, 1)],
dtype=[('', np.float32)] * 5)
mask = [(False, False, False, False, False),
(False, False, False, False, False)]
y = ma.array(y, mask=mask)
view = recarray_numpy_dataview(y)
bstr = pickle.dumps(view)
view1 = pickle.loads(bstr)
assert_1d_lists_almost_equals(
list(v.data for v in view),
list(v.data for v in view1))
def test_recarray_numpy_dataview_pickle():
# not masked, int32
y = np.array([(1, 2, 3, 4, 5), (5, 4, 3, 2, 1)],
dtype=[('', np.int32)] * 5)
view = recarray_numpy_dataview(y)
bstr = pickle.dumps(view)
view1 = pickle.loads(bstr)
assert_list_equal(list(v for v in view), list(v for v in view1))
# not masked, float32
y = np.array([(1, 2, 3, 4, 5), (5, 4, 3, 2, 1)],
dtype=[('', np.float32)] * 5)
view = recarray_numpy_dataview(y)
bstr = pickle.dumps(view)
view1 = pickle.loads(bstr)
assert_1d_lists_almost_equals(list(v for v in view),
list(v for v in view1))
# masked, int32
y = np.array([(1, 2, 3, 4, 5), (5, 4, 3, 2, 1)],
dtype=[('', np.int32)] * 5)
mask = [(False, False, False, False, True),
(True, False, True, True, False)]
y = ma.array(y, mask=mask)
view = recarray_numpy_dataview(y)
bstr = pickle.dumps(view)
view1 = pickle.loads(bstr)
# XXX(stephentu): masked arrays suck and don't implement equality
r = repr(list(v for v in view))
r1 = repr(list(v for v in view1))
assert_equals(r, r1)
# masked, float32
y = np.array([(1, 2, 3, 4, 5), (5, 4, 3, 2, 1)],
dtype=[('', np.float32)] * 5)
mask = [(False, False, False, False, False),
(False, False, False, False, False)]
y = ma.array(y, mask=mask)
view = recarray_numpy_dataview(y)
bstr = pickle.dumps(view)
view1 = pickle.loads(bstr)
assert_1d_lists_almost_equals(list(v.data for v in view),
list(v.data for v in view1))
def test_recarray_numpy_dataview_subarray():
x = np.array([(1, (2., 3.)), (-1, (-3., 54.))],
dtype=[('', np.int32), ('', np.float32, (2, ))])
view = recarray_numpy_dataview(x)
assert_is_not_none(view)
assert_equals(view.size(), x.shape[0])
for a, b in zip(x, view):
assert_equals(a[0], b[0])
assert_equals(a[1].shape, b[1].shape)
for f, g in zip(a[1], b[1]):
assert_almost_equals(f, g)
def test_recarray_numpy_dataview_subarray():
x = np.array([(1, (2., 3.)), (-1, (-3., 54.))],
dtype=[('', np.int32), ('', np.float32, (2,))])
view = recarray_numpy_dataview(x)
assert_is_not_none(view)
assert_equals(view.size(), x.shape[0])
for a, b in zip(x, view):
assert_equals(a[0], b[0])
assert_equals(a[1].shape, b[1].shape)
for f, g in zip(a[1], b[1]):
assert_almost_equals(f, g)
def test_recarray_numpy_dataview_masked():
x = ma.masked_array(np.array([(True, False, True, True, True)],
dtype=[('', np.bool)] * 5),
mask=[(False, False, True, True, True)])
view = recarray_numpy_dataview(x)
assert_is_not_none(view)
assert_equals(view.size(), x.shape[0])
for a, b in zip(x, view):
assert_equals(a.mask, b.mask)
for mask, (aval, bval) in zip(a.mask, zip(a, b)):
if mask:
continue
assert_equals(aval, bval)
def test_recarray_numpy_dataview_masked():
x = ma.masked_array(
np.array([(True, False, True, True, True)], dtype=[('', np.bool)] * 5),
mask=[(False, False, True, True, True)])
view = recarray_numpy_dataview(x)
assert_is_not_none(view)
assert_equals(view.size(), x.shape[0])
for a, b in zip(x, view):
assert_equals(a.mask, b.mask)
for mask, (aval, bval) in zip(a.mask, zip(a, b)):
if mask:
continue
assert_equals(aval, bval)
def test_recarray_numpy_dataview():
x = np.array([(False, 32.), (True, 943.), (False, -32.)],
dtype=[('', bool), ('', float)])
view = recarray_numpy_dataview(x)
assert_is_not_none(view)
assert_equals(view.size(), x.shape[0])
assert_equals(len(view), x.shape[0])
for a, b in zip(x, view):
assert_equals(a[0], b[0])
assert_almost_equals(a[1], b[1])
acc = 0
for a in view:
acc += a[0]
assert_equals(acc, sum(e[0] for e in x))
def test_recarray_numpy_dataview():
x = np.array([(False, 32.), (True, 943.), (False, -32.)],
dtype=[('', bool), ('', float)])
view = recarray_numpy_dataview(x)
assert_is_not_none(view)
assert_equals(view.size(), x.shape[0])
assert_equals(len(view), x.shape[0])
for a, b in zip(x, view):
assert_equals(a[0], b[0])
assert_almost_equals(a[1], b[1])
acc = 0
for a in view:
acc += a[0]
assert_equals(acc, sum(e[0] for e in x))
def test_recarray_numpy_dataview_digest():
y = np.array([(1, 2, 3, 4, 5), (5, 4, 3, 2, 1)],
dtype=[('', np.int32)] * 5)
view = recarray_numpy_dataview(y)
view1 = recarray_numpy_dataview(y)
assert_equals(_hexdigest(view), _hexdigest(view1))
y1 = np.array([(1, 2, 3, 4, 6), (5, 4, 3, 2, 1)],
dtype=[('', np.int32)] * 5)
view = recarray_numpy_dataview(y)
view1 = recarray_numpy_dataview(y1)
assert_not_equals(_hexdigest(view), _hexdigest(view1))
y2 = np.array([(1, 2, 3, 4)], dtype=[('', np.int32)] * 4)
y3 = np.array([(1, 2), (3, 4)], dtype=[('', np.int32)] * 2)
view = recarray_numpy_dataview(y2)
view1 = recarray_numpy_dataview(y3)
assert_not_equals(_hexdigest(view), _hexdigest(view1))
def test_recarray_numpy_dataview_digest():
y = np.array([(1, 2, 3, 4, 5), (5, 4, 3, 2, 1)],
dtype=[('', np.int32)] * 5)
view = recarray_numpy_dataview(y)
view1 = recarray_numpy_dataview(y)
assert_equals(_hexdigest(view), _hexdigest(view1))
y1 = np.array([(1, 2, 3, 4, 6), (5, 4, 3, 2, 1)],
dtype=[('', np.int32)] * 5)
view = recarray_numpy_dataview(y)
view1 = recarray_numpy_dataview(y1)
assert_not_equals(_hexdigest(view), _hexdigest(view1))
y2 = np.array([(1, 2, 3, 4)],
dtype=[('', np.int32)] * 4)
y3 = np.array([(1, 2), (3, 4)],
dtype=[('', np.int32)] * 2)
view = recarray_numpy_dataview(y2)
view1 = recarray_numpy_dataview(y3)
assert_not_equals(_hexdigest(view), _hexdigest(view1))
