def test_h5py_datasets():
# this one stores and reloads all datasets in the warehouse
rc_ds = saveload_warehouse()
# global checks
assert_equal(len(datasets), len(rc_ds))
assert_equal(sorted(datasets.keys()), sorted(rc_ds.keys()))
# check each one
for d in datasets:
ds = datasets[d]
ds2 = rc_ds[d]
assert_array_equal(ds.samples, ds2.samples)
# we can check all sa and fa attrs
for attr in ds.sa:
assert_array_equal(ds.sa[attr].value, ds2.sa[attr].value)
for attr in ds.fa:
assert_array_equal(ds.fa[attr].value, ds2.fa[attr].value)
# with datasets attributes it is more difficult, but we'll do some
assert_equal(len(ds.a), len(ds2.a))
assert_equal(sorted(ds.a.keys()), sorted(ds2.a.keys()))
if 'mapper' in ds.a:
# since we have no __equal__ do at least some comparison
if __debug__:
# debug mode needs special test as it enhances the repr output
# with module info and id() appendix for objects
assert_equal('#'.join(repr(ds.a.mapper).split('#')[:-1]),
'#'.join(repr(ds2.a.mapper).split('#')[:-1]))
else:
assert_equal(repr(ds.a.mapper), repr(ds2.a.mapper))
def test_h5py_datasets():
# this one stores and reloads all datasets in the warehouse
rc_ds = saveload_warehouse()
# global checks
assert_equal(len(datasets), len(rc_ds))
assert_equal(sorted(datasets.keys()), sorted(rc_ds.keys()))
# check each one
for d in datasets:
ds = datasets[d]
ds2 = rc_ds[d]
assert_array_equal(ds.samples, ds2.samples)
# we can check all sa and fa attrs
for attr in ds.sa:
assert_array_equal(ds.sa[attr].value, ds2.sa[attr].value)
for attr in ds.fa:
assert_array_equal(ds.fa[attr].value, ds2.fa[attr].value)
# with datasets attributes it is more difficult, but we'll do some
assert_equal(len(ds.a), len(ds2.a))
assert_equal(sorted(ds.a.keys()), sorted(ds2.a.keys()))
if 'mapper' in ds.a:
# since we have no __equal__ do at least some comparison
assert_equal(repr(ds.a.mapper), repr(ds2.a.mapper))
def test_h5py_datasets():
# this one stores and reloads all datasets in the warehouse
rc_ds = saveload_warehouse()
# global checks
assert_equal(len(datasets), len(rc_ds))
assert_equal(sorted(datasets.keys()), sorted(rc_ds.keys()))
# check each one
for d in datasets:
ds = datasets[d]
ds2 = rc_ds[d]
assert_array_equal(ds.samples, ds2.samples)
# we can check all sa and fa attrs
for attr in ds.sa:
assert_array_equal(ds.sa[attr].value, ds2.sa[attr].value)
for attr in ds.fa:
assert_array_equal(ds.fa[attr].value, ds2.fa[attr].value)
# with datasets attributes it is more difficult, but we'll do some
assert_equal(len(ds.a), len(ds2.a))
assert_equal(sorted(ds.a.keys()), sorted(ds2.a.keys()))
if 'mapper' in ds.a:
# since we have no __equal__ do at least some comparison
assert_equal(repr(ds.a.mapper), repr(ds2.a.mapper))
