def test_toHDF5ListString(self):
"""Convert to HDF5, including a list of string in attributes"""
a = dm.SpaceData()
a.attrs['foo'] = ['hi']
dm.toHDF5(self.testfile, a, mode='a')
newobj = dm.fromHDF5(self.testfile)
self.assertEqual(a.attrs['foo'], newobj.attrs['foo'])
def test_HDF5Exceptions(self):
"""HDF5 has warnings and exceptions"""
dm.toHDF5(self.testfile, self.SDobj)
self.assertRaises(IOError, dm.toHDF5, self.testfile, self.SDobj, overwrite=False)
a = dm.SpaceData()
a['foo'] = 'bar' # not an allowed type for data
self.assertRaises(dm.DMWarning, dm.toHDF5, self.testfile, a)
def test_HDF5roundtrip2GZIP(self):
"""Data can go to hdf without altering datetimes in the datamodel with compression"""
a = dm.SpaceData()
a['foo'] = dm.SpaceData()
dm.toHDF5(self.testfile, a, compression='gzip')
newobj = dm.fromHDF5(self.testfile)
self.assertEqual(a['foo'], newobj['foo'])
a['bar'] = dm.dmarray([datetime.datetime(2000, 1, 1)])
dm.toHDF5(self.testfile, a, compression='gzip')
self.assertEqual(a['bar'], dm.dmarray([datetime.datetime(2000, 1, 1)]))
def test_HDF5roundtripGZIP(self):
"""Data can go to hdf and back with compression"""
dm.toHDF5(self.testfile, self.SDobj, compression='gzip')
newobj = dm.fromHDF5(self.testfile)
self.assertEqual(self.SDobj.attrs['global'], newobj.attrs['global'])
np.testing.assert_almost_equal(self.SDobj['var'], newobj['var'])
self.assertEqual(self.SDobj['var'].attrs['a'], newobj['var'].attrs['a'])
dm.toHDF5(self.testfile, self.SDobj, mode='a', compression='gzip')
newobj = dm.fromHDF5(self.testfile)
self.assertEqual(self.SDobj.attrs['global'], newobj.attrs['global'])
np.testing.assert_almost_equal(self.SDobj['var'], newobj['var'])
self.assertEqual(self.SDobj['var'].attrs['a'], newobj['var'].attrs['a'])
def test_HDF5roundtrip_method(self):
"""Data can go to hdf and back"""
self.SDobj.toHDF5(self.testfile)
newobj = dm.fromHDF5(self.testfile)
self.assertEqual(self.SDobj.attrs['global'], newobj.attrs['global'])
np.testing.assert_almost_equal(self.SDobj['var'], newobj['var'])
self.assertEqual(self.SDobj['var'].attrs['a'], newobj['var'].attrs['a'])
dm.toHDF5(self.testfile, self.SDobj, mode='a')
newobj = dm.fromHDF5(self.testfile)
self.assertEqual(self.SDobj.attrs['global'], newobj.attrs['global'])
np.testing.assert_almost_equal(self.SDobj['var'], newobj['var'])
self.assertEqual(self.SDobj['var'].attrs['a'], newobj['var'].attrs['a'])
def toHDF5(self, filepath, **kwargs):
'''
Save this DataModel to a HDF5 data file.
Attributes are not available without SpacePy.
'''
if USE_SPACEPY:
spdm.toHDF5(filepath, self, **kwargs)
else:
import h5py
path = '/'
if 'path' in kwargs:
path = kwargs['path']
h5file = h5py.File(filepath, mode='w')
for k, v in self.items():
h5file[path][k] = v
h5file.close()
def write(self, filename, hdf5=False):
if hdf5:
dm.toHDF5(filename, self.dat)
else:
dm.toJSONheadedASCII(filename, self.dat, order=['Epoch'] )
print(' Wrote {0}'.format(os.path.abspath(filename)))
def write(self, filename, hdf5=False):
if hdf5:
dm.toHDF5(filename, self.data)
else:
dm.toJSONheadedASCII(filename, self.data)
