def test_incremental_write(self):
data = DataSet1D(location=self.loc_provider, name='test_incremental')
location = data.location
data_copy = DataSet1D(False)
# # empty the data and mark it as unmodified
data.x_set[:] = float('nan')
data.y[:] = float('nan')
data.x_set.modified_range = None
data.y.modified_range = None
# simulate writing after every value comes in, even within
# one row (x comes first, it's the setpoint)
for i, (x, y) in enumerate(zip(data_copy.x_set, data_copy.y)):
data.x_set[i] = x
self.formatter.write(data)
data.y[i] = y
self.formatter.write(data)
data2 = DataSet(location=location, formatter=self.formatter)
data2.read()
self.checkArraysEqual(data2.arrays['x_set'], data_copy.arrays['x_set'])
self.checkArraysEqual(data2.arrays['y'], data_copy.arrays['y'])
self.formatter.close_file(data)
self.formatter.close_file(data2)
def test_reading_into_existing_data_array(self):
data = DataSet1D(location=self.loc_provider, name='test_read_existing')
# closing before file is written should not raise error
self.formatter.write(data)
data2 = DataSet(location=data.location, formatter=self.formatter)
d_array = DataArray(
name='dummy',
array_id='x_set', # existing array id in data
label='bla',
unit='a.u.',
is_setpoint=False,
set_arrays=(),
preset_data=np.zeros(5))
data2.add_array(d_array)
# test if d_array refers to same as array x_set in dataset
self.assertTrue(d_array is data2.arrays['x_set'])
data2.read()
# test if reading did not overwrite dataarray
self.assertTrue(d_array is data2.arrays['x_set'])
# Testing if data was correctly updated into dataset
self.checkArraysEqual(data2.arrays['x_set'], data.arrays['x_set'])
self.checkArraysEqual(data2.arrays['y'], data.arrays['y'])
self.formatter.close_file(data)
self.formatter.close_file(data2)
def test_from_server(self, gdm_mock):
mock_dm = MockDataManager()
gdm_mock.return_value = mock_dm
mock_dm.location = 'Mars'
mock_dm.live_data = MockLive()
# wrong location or False location - converts to local
data = DataSet(location='Jupiter',
data_manager=True,
mode=DataMode.PULL_FROM_SERVER)
self.assertEqual(data.mode, DataMode.LOCAL)
data = DataSet(location=False,
data_manager=True,
mode=DataMode.PULL_FROM_SERVER)
self.assertEqual(data.mode, DataMode.LOCAL)
# location matching server - stays in server mode
data = DataSet(location='Mars',
data_manager=True,
mode=DataMode.PULL_FROM_SERVER,
formatter=MockFormatter())
self.assertEqual(data.mode, DataMode.PULL_FROM_SERVER)
self.assertEqual(data.arrays, MockLive.arrays)
# cannot write except in LOCAL mode
with self.assertRaises(RuntimeError):
data.write()
# cannot finalize in PULL_FROM_SERVER mode
with self.assertRaises(RuntimeError):
data.finalize()
# now test when the server says it's not there anymore
mock_dm.location = 'Saturn'
data.sync()
self.assertEqual(data.mode, DataMode.LOCAL)
self.assertEqual(data.has_read_data, True)
# now it's LOCAL so we *can* write.
data.write()
self.assertEqual(data.has_written_data, True)
# location=False: write, read and sync are noops.
data.has_read_data = False
data.has_written_data = False
data.location = False
data.write()
data.read()
data.sync()
self.assertEqual(data.has_read_data, False)
self.assertEqual(data.has_written_data, False)
def test_full_write_read_2D(self):
"""
Test writing and reading a file back in
"""
data = DataSet2D(location=self.loc_provider, name='test2D')
self.formatter.write(data)
# Test reading the same file through the DataSet.read
data2 = DataSet(location=data.location, formatter=self.formatter)
data2.read()
self.checkArraysEqual(data2.x_set, data.x_set)
self.checkArraysEqual(data2.y_set, data.y_set)
self.checkArraysEqual(data2.z, data.z)
self.formatter.close_file(data)
self.formatter.close_file(data2)
def test_metadata_write_read(self):
"""
Test is based on the snapshot of the 1D dataset.
Having a more complex snapshot in the metadata would be a better test.
"""
data = DataSet1D(location=self.loc_provider, name='test_metadata')
data.snapshot() # gets the snapshot, not added upon init
self.formatter.write(data) # write_metadata is included in write
data2 = DataSet(location=data.location, formatter=self.formatter)
data2.read()
self.formatter.close_file(data)
self.formatter.close_file(data2)
metadata_equal, err_msg = compare_dictionaries(
data.metadata, data2.metadata,
'original_metadata', 'loaded_metadata')
self.assertTrue(metadata_equal, msg='\n'+err_msg)
def test_full_write_read_1D(self):
"""
Test writing and reading a file back in
"""
# location = self.locations[0]
data = DataSet1D(name='test1D_full_write', location=self.loc_provider)
# print('Data location:', os.path.abspath(data.location))
self.formatter.write(data)
# Used because the formatter has no nice find file method
# Test reading the same file through the DataSet.read
data2 = DataSet(location=data.location, formatter=self.formatter)
data2.read()
self.checkArraysEqual(data2.x_set, data.x_set)
self.checkArraysEqual(data2.y, data.y)
self.formatter.close_file(data)
self.formatter.close_file(data2)
def test_loop_writing_2D(self):
# pass
station = Station()
MockPar = MockParabola(name='Loop_writing_test_2D')
station.add_component(MockPar)
loop = Loop(MockPar.x[-100:100:20]).loop(MockPar.y[-50:50:10]).each(
MockPar.skewed_parabola)
data1 = loop.run(name='MockLoop_hdf5_test', formatter=self.formatter)
data2 = DataSet(location=data1.location, formatter=self.formatter)
data2.read()
for key in data2.arrays.keys():
self.checkArraysEqual(data2.arrays[key], data1.arrays[key])
metadata_equal, err_msg = compare_dictionaries(data1.metadata,
data2.metadata,
'original_metadata',
'loaded_metadata')
self.assertTrue(metadata_equal, msg='\n' + err_msg)
self.formatter.close_file(data1)
self.formatter.close_file(data2)
]
arrays4 = [data1, data2, data3]
data_set_2 = new_data(
arrays=arrays3,
location=None,
loc_record={
'name': 'T1',
'label': 'Vread_sweep'
},
io=NewIO,
)
data_set_2.save_metadata()
test_location = '2017-08-18/20-40-19_T1_Vread_sweep'
data_set_3 = DataSet(
location=test_location,
io=NewIO,
)
data_set_3.read()
AWGpara_array = data_set_3.arrays['AWGpara_set'].ndarray
index0_array = data_set_3.arrays['index0_set'].ndarray
digitizer_array = data_set_3.arrays['digitizer_digitizer'].ndarray
#
#print('loop.data_set: %s' % LP.data_set)
#
#data = LP.run()
#
