def test_appending():
x = np.arange(3)
y = np.repeat(np.linspace(0, 1, 5).reshape(1, -1), 3, 0)
z = np.arange(y.size).reshape(y.shape)
data = dd.DataDict(
x=dict(values=x,
unit='A',
__info__='careful!',
__moreinfo__='more words in here'),
y=dict(values=y, unit='B'),
z=dict(values=z, axes=['x', 'y'], unit='C'),
__desc__='some description',
)
assert data.validate()
dds.datadict_to_hdf5(data, FN, append_mode=dds.AppendMode.none)
assert _clean_from_file(dds.datadict_from_hdf5(FN)) == data
data.add_data(x=[4],
y=np.linspace(0, 1, 5).reshape(1, -1),
z=np.arange(5).reshape(1, -1))
assert data.validate()
dds.datadict_to_hdf5(data, FN, append_mode=dds.AppendMode.new)
assert _clean_from_file(dds.datadict_from_hdf5(FN)) == data
dds.datadict_to_hdf5(data, FN, append_mode=dds.AppendMode.all)
ret = _clean_from_file(dds.datadict_from_hdf5(FN))
assert ret == (data + data)
def savetrace(self, avgnum=3, savedir=None, name=None):
if savedir == None:
savedir = easygui.diropenbox("Choose file location: ")
assert savedir != None
if name == None:
name = easygui.enterbox("Enter Trace Name: ")
assert name != None
elif savedir == "previous":
savedir = self.previous_save
assert savedir != None
data = dd.DataDict(
frequency=dict(unit='Hz'),
power=dict(axes=['frequency'], unit='dB'),
phase=dict(axes=['frequency'], unit='Degrees'),
)
prev_trform = self.trform()
with dds.DDH5Writer(savedir, data, name=name) as writer:
freqs = self.getSweepData() #1XN array, N in [1601,1000]
vnadata = np.array(
self.average(avgnum)) #2xN array, N in [1601, 1000]
writer.add_data(frequency=freqs,
power=vnadata[0],
phase=vnadata[1])
self.trform(prev_trform)
self.previous_save = savedir
def test_basic_storage_and_retrieval():
x = np.arange(3)
y = np.repeat(np.linspace(0, 1, 5).reshape(1, -1), 3, 0)
z = np.arange(y.size).reshape(y.shape)
data = dd.DataDict(
x=dict(values=x,
unit='A',
__info__='careful!',
__moreinfo__='more words in here'),
y=dict(values=y, unit='B'),
z=dict(values=z, axes=['x', 'y'], unit='C'),
__desc__='some description',
)
assert data.validate()
dds.datadict_to_hdf5(data, str(FILEPATH), append_mode=dds.AppendMode.none)
datafromfile = dds.datadict_from_hdf5(str(FILEPATH))
# hdf5 saving added a few extra metas that we need to ignore when
# comparing
datafromfile = _clean_from_file(datafromfile)
assert (data == datafromfile)
FILEPATH.unlink()
def savetrace(self, avgnum=1, savedir=None, name='CXA_trace'):
if savedir == None:
import easygui
savedir = easygui.diropenbox(
"Choose place to save trace information: ")
assert savedir != None
SA_data = self.get_data(count=avgnum)
data = dd.DataDict(
frequency=dict(unit='Hz'),
power=dict(axes=['frequency'], unit='dBm'),
)
with dds.DDH5Writer(savedir, data, name=name) as writer:
writer.add_data(frequency=SA_data[:, 0], power=SA_data[:, 1])
def test_loader_node(qtbot):
dds.DDH5Loader.useUi = False
x = np.arange(3)
y = np.repeat(np.linspace(0, 1, 5).reshape(1, -1), 3, 0)
z = np.arange(y.size).reshape(y.shape)
data = dd.DataDict(
x=dict(values=x,
unit='A',
__info__='careful!',
__moreinfo__='more words in here'),
y=dict(values=y, unit='B'),
z=dict(values=z, axes=['x', 'y'], unit='C'),
__desc__='some description',
)
assert data.validate()
dds.datadict_to_hdf5(data, str(FILEPATH), append_mode=dds.AppendMode.new)
assert _clean_from_file(dds.datadict_from_hdf5(str(FILEPATH))) == data
fc = linearFlowchart(('loader', dds.DDH5Loader))
node = fc.nodes()['loader']
assert fc.outputValues()['dataOut'] is None
with qtbot.waitSignal(node.loadingWorker.dataLoaded,
timeout=1000) as blocker:
node.filepath = str(FILEPATH)
out = fc.outputValues()['dataOut'].copy()
out.pop('__title__')
assert _clean_from_file(out) == data
data.add_data(x=[3],
y=np.linspace(0, 1, 5).reshape(1, -1),
z=np.arange(5).reshape(1, -1))
dds.datadict_to_hdf5(data, str(FILEPATH), append_mode=dds.AppendMode.new)
assert _clean_from_file(dds.datadict_from_hdf5(str(FILEPATH))) == data
out = fc.outputValues()['dataOut'].copy()
out.pop('__title__')
assert not _clean_from_file(out) == data
with qtbot.waitSignal(node.loadingWorker.dataLoaded,
timeout=1000) as blocker:
node.update()
out = fc.outputValues()['dataOut'].copy()
out.pop('__title__')
assert _clean_from_file(out) == data
FILEPATH.unlink()
def test_writer_with_large_data():
writer = _Writer()
ref_data = writer.mkdata()
ref_dataset = dd.DataDict(
x=dict(values=ref_data, unit='W'),
y=dict(values=ref_data**2, unit='T', axes=['x']),
)
ref_dataset['__dataset.name__'] = ''
writer.start()
writer.join()
dataset_from_file = dds.datadict_from_hdf5(writer.filepath)
assert (_clean_from_file(dataset_from_file) == ref_dataset)
rmtree('./TESTDATA')
def test_concurrent_write_and_read():
writer = _Writer()
ref_data = writer.mkdata()
ref_dataset = dd.DataDict(
x=dict(values=ref_data, unit='W'),
y=dict(values=ref_data**2, unit='T', axes=['x']),
)
ref_dataset['__dataset.name__'] = ''
writer.start()
while writer.is_alive():
time.sleep(2)
data_from_file = dds.datadict_from_hdf5(writer.filepath,
structure_only=True)
assert (data_from_file.structure(include_meta=False))
dataset_from_file = dds.datadict_from_hdf5(writer.filepath)
assert (_clean_from_file(dataset_from_file) == ref_dataset)
rmtree('./TESTDATA')