def test_plot_hdf5(self):
# Add data to the archive
num_histograms = 4
data = [
[4, 1, 0],
[5, 2, 0],
[6, 3, 0],
[7, 4, 0],
]
# Store data
for _ in range(num_histograms):
with self.h:
for d in data:
self.h.append(d)
with temp_dir():
# Write data to HDF5 file
file_name = 'result.h5'
with h5py.File(file_name, 'w') as f:
self.managers.dataset_mgr.write_hdf5(f)
# Make analyzer object
a = HistogramAnalyzer(file_name, self.s.detection.get_state_detection_threshold())
# Call plot functions to see if no exceptions occur
a.plot_all_histograms()
a.plot_all_probabilities()
a.plot_all_mean_counts()
a.plot_all_state_probabilities()
def test_hdf5_read(self):
self._generate_hdf5_data()
with temp_dir():
# Write data to HDF5 file
file_name = 'result.h5'
with h5py.File(file_name, 'w') as f:
self.managers.dataset_mgr.write_hdf5(f)
# Read file with HistogramAnalyzer
a = HistogramAnalyzer(file_name, self.s.detection.get_state_detection_threshold())
# Compare analyzer to histogram context
self._compare_analyzer_to_context(a)
# Compare to analyzer from object source
b = HistogramAnalyzer(self.s, self.s.detection.get_state_detection_threshold())
self.assertListEqual(a.keys, b.keys, 'Keys did not match')
for key in a.keys:
for v, w in zip(a.histograms[key], b.histograms[key]):
self.assertListEqual(list(v), list(w), 'Histograms did not match')
for v, w in zip(a.probabilities[key], b.probabilities[key]):
self.assertListEqual(list(v), list(w), 'Probabilities did not match')
for v, w in zip(a.mean_counts[key], b.mean_counts[key]):
self.assertListEqual(list(v), list(w), 'Mean counts did not match')
for v, w in zip(a.stdev_counts[key], b.stdev_counts[key]):
self.assertListEqual(list(v), list(w), 'Stdev counts did not match')
for v, w in zip(a.raw[key], b.raw[key]):
self.assertListEqual(v.tolist(), w.tolist(), 'Raw counts did not match')
def test_hdf5_read_no_histogram_data(self):
self._generate_hdf5_data(keep_raw=False, add_legacy=False)
with temp_dir():
# Write data to HDF5 file
file_name = 'result.h5'
with h5py.File(file_name, 'w') as f:
self.managers.dataset_mgr.write_hdf5(f)
with self.assertRaises(KeyError, msg='Absence of histogram data did not raise'):
HistogramAnalyzer(file_name)
def test_plot(self):
# Add data to the archive
bin_width = 1 * us
bin_spacing = 1 * ns
offset = 5 * ns
data = [[16, 25, 56], [66, 84, 83], [45, 77, 96], [88, 63, 79]]
# Store data
with self.t:
self.t.append(data, bin_width, bin_spacing, offset)
with temp_dir():
# Make analyzer object
a = TimeResolvedAnalyzer(self.s)
# Call plot functions to see if no exceptions occur
a.plot_all_traces()
def setUp(self) -> None:
self._temp_dir = temp_dir()
self._temp_dir.__enter__()
# Create the system
ddb = enable_dax_sim(_DEVICE_DB.copy(),
enable=True,
output='vcd',
moninj_service=False)
self.managers = get_managers(ddb)
self.sys = _TestSystem(self.managers)
# Get the signal manager
self.sm: DaxSignalManager = typing.cast(VcdSignalManager,
get_signal_manager())
self.assertIsInstance(self.sm, VcdSignalManager)
def test_gtk_wave_save_generator(self):
with temp_dir():
ddb = enable_dax_sim(ddb=_DEVICE_DB.copy(),
enable=True,
output='vcd',
moninj_service=False)
with get_managers(ddb) as managers:
system = _TestSystem(managers)
self.assertTrue(system.dax_sim_enabled)
# Create GTKWave save generator object, which immediately writes the waves file
GTKWSaveGenerator(system)
# Manually close signal manager before leaving temp dir
get_signal_manager().close()
def test_hdf5_read_raw_and_legacy(self):
self._generate_hdf5_data(keep_raw=True, add_legacy=True)
with temp_dir():
# Write data to HDF5 file
file_name = 'result.h5'
with h5py.File(file_name, 'w') as f:
self.managers.dataset_mgr.write_hdf5(f)
# Read file with HistogramAnalyzer
a = HistogramAnalyzer(file_name, self.s.detection.get_state_detection_threshold())
# Verify raw attribute is available
self.assertTrue(hasattr(a, 'raw'), 'Expected attribute `raw`')
# Compare analyzer to histogram context
self._compare_analyzer_to_context(a)
def test_gtk_wave_save_generator_invalid_signal_manager(self):
with temp_dir():
ddb = enable_dax_sim(ddb=_DEVICE_DB.copy(),
enable=True,
output='null',
moninj_service=False)
with get_managers(ddb) as managers:
system = _TestSystem(managers)
self.assertTrue(system.dax_sim_enabled)
with self.assertRaises(
RuntimeError,
msg='Not using VCD signal manager did not raise'):
# Create GTKWave save generator object, which immediately writes the waves file
GTKWSaveGenerator(system)
# Manually close signal manager before leaving temp dir
get_signal_manager().close()
def test_hdf5_read(self):
# Add data to the archive
bin_width = 1 * us
bin_spacing = 1 * ns
offset = 5 * ns
data_0 = [[1, 2], [3, 4], [2, 6], [4, 5], [9, 9], [9, 7], [7, 8]]
data_1 = [[16, 25, 56], [66, 84, 83], [45, 77, 96], [88, 63, 79], [62, 93, 49], [29, 25, 7], [6, 17, 80]]
# Store data
with self.t:
self.t.append(data_0, bin_width, bin_spacing, offset)
self.t.config_dataset('foo')
with self.t:
self.t.append(data_1, bin_width, bin_spacing, offset)
with temp_dir():
# Write data to HDF5 file
file_name = 'result.h5'
with h5py.File(file_name, 'w') as f:
self.managers.dataset_mgr.write_hdf5(f)
# Read file with TimeResolvedAnalyzer
a = TimeResolvedAnalyzer(file_name)
# Compare results
self.assertListEqual(a.keys, self.t.get_keys(), 'Keys did not match')
for k in a.keys:
for v, w in zip(a.traces[k], self.t.get_traces(k)):
for c in TimeResolvedContext.DATASET_COLUMNS:
self.assertIn(c, v, 'Did not found expected dataset columns')
self.assertIn(c, w, 'Did not found expected dataset columns')
self.assertTrue(np.array_equal(v[c], w[c]), f'Column/data "{c}" of trace did not match')
# Compare to analyzer from object source
b = TimeResolvedAnalyzer(self.s)
self.assertListEqual(a.keys, b.keys, 'Keys did not match')
for k in a.keys:
for v, w in zip(a.traces[k], b.traces[k]):
for c in TimeResolvedContext.DATASET_COLUMNS:
self.assertIn(c, v, 'Did not found expected dataset columns')
self.assertIn(c, w, 'Did not found expected dataset columns')
self.assertTrue(np.array_equal(v[c], w[c]), f'Column/data "{c}" of trace did not match')
def test_plot_hdf5(self):
# Add data to the archive
bin_width = 1 * us
bin_spacing = 1 * ns
offset = 5 * ns
data = [[16, 25, 56], [66, 84, 83], [45, 77, 96], [88, 63, 79]]
# Store data
with self.t:
self.t.append(data, bin_width, bin_spacing, offset)
with temp_dir():
# Write data to HDF5 file
file_name = 'result.h5'
with h5py.File(file_name, 'w') as f:
self.managers.dataset_mgr.write_hdf5(f)
# Make analyzer object
a = TimeResolvedAnalyzer(file_name)
# Call plot functions to see if no exceptions occur
a.plot_all_traces()
def test_scan_reader(self):
self.scan.run()
with temp_dir():
# Write data to HDF5 file
file_name = 'result.h5'
with h5py.File(file_name, 'w') as f:
self.managers.dataset_mgr.write_hdf5(f)
# Read HDF5 file with scan reader
r = DaxScanReader(file_name)
# Verify if the data matches with the scan object
scannables = self.scan.get_scannables()
scan_points = self.scan.get_scan_points()
keys = list(scannables.keys())
self.assertSetEqual(set(r.keys), set(keys),
'Keys in reader did not match object keys')
for k in keys:
self.assertListEqual(
scannables[k], list(r.scannables[k]),
'Scannable in reader did not match object scannable')
self.assertListEqual(
scan_points[k], list(r.scan_points[k]),
'Scan points in reader did not match object scan points')
# Verify if the data matches with a scan reader using a different source
r_ = DaxScanReader(self.scan)
self.assertSetEqual(set(r.keys), set(r_.keys),
'Keys in readers did not match')
for k in r.keys:
self.assertListEqual(list(r_.scannables[k]),
list(r.scannables[k]),
'Scannable in readers did not match')
self.assertListEqual(list(r_.scan_points[k]),
list(r.scan_points[k]),
'Scan points in readers did not match')
def test_plot(self):
# Add data to the archive
num_histograms = 4
data = [
[4, 1, 0],
[5, 2, 0],
[6, 3, 0],
[7, 4, 0],
]
# Store data
for _ in range(num_histograms):
with self.h:
for d in data:
self.h.append(d)
with temp_dir():
# Make analyzer object
a = HistogramAnalyzer(self.s, self.s.detection.get_state_detection_threshold())
# Call plot functions to see if no exceptions occur
a.plot_all_histograms()
a.plot_all_probabilities()
a.plot_all_mean_counts()
a.plot_all_state_probabilities()
def test_relation_graphviz(self):
with temp_dir():
# We can not really test the contents of the graph at this moment
g = dax.util.introspect.RelationGraphviz(self.sys)
self.assertIsInstance(g, graphviz.Digraph)
def test_histogram_analyzer_module(self):
# The histogram analyzer requests an output file which will trigger the creation of an experiment output dir
# To prevent unnecessary directories after testing, we switch to a temp dir
with temp_dir():
HistogramAnalyzer(self.h)
def test_analyzer_system(self):
# The analyzer requests an output file which will trigger the creation of an experiment output dir
# To prevent unnecessary directories after testing, we switch to a temp dir
with temp_dir():
TimeResolvedAnalyzer(self.s)
