def test_iter_datasets():
with h5.File('horton.scripts.test.test_hdf2csv.test_iter_datasets', driver='core', backing_store=False) as f:
fill_hdf5(f)
l = list(iter_datasets(f))
assert len(l) == 5
assert l[0][0] == 'bar/foo'
assert l[0][1] == f['bar/foo']
assert l[1][0] == 'test0'
assert l[1][1] == f['test0']
assert l[2][0] == 'test1'
assert l[2][1] == f['test1']
assert l[3][0] == 'test2'
assert l[3][1] == f['test2']
assert l[4][0] == 'zzz'
assert l[4][1] == f['zzz']
def test_iter_datasets():
with h5.File('horton.scripts.test.test_hdf2csv.test_iter_datasets', driver='core', backing_store=False) as f:
fill_hdf5(f)
l = list(iter_datasets(f))
assert len(l) == 5
assert l[0][0] == 'bar/foo'
assert l[0][1] == f['bar/foo']
assert l[1][0] == 'test0'
assert l[1][1] == f['test0']
assert l[2][0] == 'test1'
assert l[2][1] == f['test1']
assert l[3][0] == 'test2'
assert l[3][1] == f['test2']
assert l[4][0] == 'zzz'
assert l[4][1] == f['zzz']
def test_iter_datasets():
with h5.File("horton.scripts.test.test_hdf2csv.test_iter_datasets", driver="core", backing_store=False) as f:
fill_hdf5(f)
l = list(iter_datasets(f))
assert len(l) == 5
assert l[0][0] == "bar/foo"
assert l[0][1] == f["bar/foo"]
assert l[1][0] == "test0"
assert l[1][1] == f["test0"]
assert l[2][0] == "test1"
assert l[2][1] == f["test1"]
assert l[3][0] == "test2"
assert l[3][1] == f["test2"]
assert l[4][0] == "zzz"
assert l[4][1] == f["zzz"]
def main():
args = parse_args()
fn_h5, grp_name = parse_h5(args.h5, 'h5')
with LockedH5File(fn_h5, 'r') as fin, open(args.csv, 'w') as fout:
w = csv.writer(fout)
w.writerow(['Converted data from %s' % args.h5])
w.writerow([])
for name, dset in iter_datasets(fin[grp_name]):
if len(dset.shape) > 3:
if log.do_warning:
log.warn(
'Skipping %s because it has more than three axes.' %
name)
else:
log('Converting %s' % name)
w.writerow(['Dataset', name])
w.writerow(['Shape'] + list(dset.shape))
if len(dset.shape) == 0:
w.writerow([dset[()]])
elif len(dset.shape) == 1:
for value in dset:
w.writerow([value])
elif len(dset.shape) == 2:
for row in dset:
w.writerow([value for value in row])
elif len(dset.shape) == 3:
for array in dset:
l = []
for col in array.T:
for value in col:
l.append(value)
l.append('')
del l[-1]
w.writerow(l)
else:
w.writerow(['Skipped because ndim=%i>3' % len(dset.shape)])
w.writerow([])
def main():
args = parse_args()
fn_h5, grp_name = parse_h5(args.h5, 'h5')
with LockedH5File(fn_h5, 'r') as fin, open(args.csv, 'w') as fout:
w = csv.writer(fout)
w.writerow(['Converted data from %s' % args.h5])
w.writerow([])
for name, dset in iter_datasets(fin[grp_name]):
if len(dset.shape) > 3:
if log.do_warning:
log.warn('Skipping %s because it has more than three axes.' % name)
else:
log('Converting %s' % name)
w.writerow(['Dataset', name])
w.writerow(['Shape'] + list(dset.shape))
if len(dset.shape) == 0:
w.writerow([dset[()]])
elif len(dset.shape) == 1:
for value in dset:
w.writerow([value])
elif len(dset.shape) == 2:
for row in dset:
w.writerow([value for value in row])
elif len(dset.shape) == 3:
for array in dset:
l = []
for col in array.T:
for value in col:
l.append(value)
l.append('')
del l[-1]
w.writerow(l)
else:
w.writerow(['Skipped because ndim=%i>3' % len(dset.shape)])
w.writerow([])