def test_multiple_files(self):
filename1 = os.path.dirname(os.path.realpath(__file__))
filename1 = os.path.join(filename1, 'testDataFiles',
'chimera_nonoise_2events_1levels.log')
filename2 = os.path.dirname(os.path.realpath(__file__))
filename2 = os.path.join(filename2, 'testDataFiles',
'chimera_nonoise_1event_2levels.log')
file_names = [filename1, filename2]
event_databases = find_events(file_names,
save_file_names=[
'_testMultipleFiles_1_9238.h5',
'_testMultipleFiles_2_9238.h5'
])
self.assertEqual(len(event_databases), 2)
h5file = ed.open_file(event_databases[0], mode='r')
self._test_chimera_no_noise_2events_1levels_wrapper(h5file)
h5file.close()
os.remove(event_databases[0])
h5file = ed.open_file(event_databases[1], mode='r')
self._test_chimera_no_noise_1event_2levels_helper(h5file)
h5file.close()
os.remove(event_databases[1])
def test_debug_option(self):
filename = os.path.dirname(os.path.realpath(__file__))
filename = tf.get_abs_path('chimera_nonoise_2events_1levels.log')
output_filename = '_test_debug_option.h5'
reader = get_reader_from_filename(filename)
data = [reader]
event_databases = find_events(data,
save_file_names=[output_filename],
debug=True)
data = reader.get_all_data()[0]
reader.close()
self.assertEqual(len(event_databases), 1)
h5file = ed.open_file(event_databases[0], mode='r')
self._test_chimera_no_noise_2events_1levels_wrapper(h5file)
# check that the file has the correct groups
groups = [x._v_name for x in h5file.walk_groups()]
self.assertIn('debug', groups, "No debug group in debug file.")
print "data:", h5file.root.debug.data[:]
np.testing.assert_array_equal(data, h5file.root.debug.data[0][:])
h5file.close()
os.remove(event_databases[0])
def test_debug_option(self):
filename = os.path.dirname(os.path.realpath(__file__))
filename = tf.get_abs_path('chimera_nonoise_2events_1levels.log')
output_filename = '_test_debug_option.h5'
reader = get_reader_from_filename(filename)
data = [reader]
event_databases = find_events(data,
save_file_names=[output_filename], debug=True)
data = reader.get_all_data()[0]
reader.close()
self.assertEqual(len(event_databases), 1)
h5file = ed.open_file(event_databases[0], mode='r')
self._test_chimera_no_noise_2events_1levels_wrapper(h5file)
# check that the file has the correct groups
groups = [x._v_name for x in h5file.walk_groups()]
self.assertIn('debug', groups, "No debug group in debug file.")
print "data:", h5file.root.debug.data[:]
np.testing.assert_array_equal(data, h5file.root.debug.data[0][:])
h5file.close()
os.remove(event_databases[0])
def test_good_thresholds(self, filename):
"""
Tests that we find the correct number of events when the starting and ending thresholds are appropriate.
"""
data_file = tf.get_abs_path('chimera_1event.log')
parameters = Parameters(threshold_strategy=AbsoluteChangeThresholdStrategy(2., 1.))
event_databases = find_events([data_file], parameters=parameters,
save_file_names=[filename], debug=True)
h5file = ed.open_file(filename, mode='r')
#Check the number of events
event_count = h5file.get_event_count()
self.assertEqual(event_count, 1, "Unexpected event count. Should be {0}, was {1}.".format(event_count, 0))
#Check the event length
sample_rate = h5file.get_sample_rate()
event_length = h5file.get_event_row(0)['event_length']/sample_rate
event_length_should_be = 0.00024
percent_diff = abs(event_length - event_length_should_be) / event_length_should_be
self.assertLessEqual(percent_diff, 0.05,
"Unexpected event length. Should be {0}, was {1}.".format(event_length_should_be,
event_length))
h5file.close()
def test_good_thresholds(self, filename):
"""
Tests that we find the correct number of events when the starting and ending thresholds are appropriate.
"""
data_file = tf.get_abs_path('chimera_1event.log')
parameters = Parameters(
threshold_strategy=AbsoluteChangeThresholdStrategy(2., 1.))
event_databases = find_events([data_file],
parameters=parameters,
save_file_names=[filename],
debug=True)
h5file = ed.open_file(filename, mode='r')
#Check the number of events
event_count = h5file.get_event_count()
self.assertEqual(
event_count, 1,
"Unexpected event count. Should be {0}, was {1}.".format(
event_count, 0))
#Check the event length
sample_rate = h5file.get_sample_rate()
event_length = h5file.get_event_row(0)['event_length'] / sample_rate
event_length_should_be = 0.00024
percent_diff = abs(event_length -
event_length_should_be) / event_length_should_be
self.assertLessEqual(
percent_diff, 0.05,
"Unexpected event length. Should be {0}, was {1}.".format(
event_length_should_be, event_length))
h5file.close()
def test_multiple_files(self):
filename1 = tf.get_abs_path('chimera_nonoise_2events_1levels.log')
filename2 = tf.get_abs_path('chimera_nonoise_1event_2levels.log')
file_names = [filename1, filename2]
event_databases = find_events(file_names,
save_file_names=['_testMultipleFiles_1_9238.h5', '_testMultipleFiles_2_9238.h5'])
self.assertEqual(len(event_databases), 2)
h5file = ed.open_file(event_databases[0], mode='r')
self._test_chimera_no_noise_2events_1levels_wrapper(h5file)
h5file.close()
os.remove(event_databases[0])
h5file = ed.open_file(event_databases[1], mode='r')
self._test_chimera_no_noise_1event_2levels_helper(h5file)
h5file.close()
os.remove(event_databases[1])
def _filter_wrap(tup):
# returns the output filename
filename = tup[0]
print "Starting file:", filename
ed = open_file(filename, mode='r')
output_filename = filename[:-3] + '.csv'
ed.to_csv(output_filename)
print "Done converting input {0} into output {1}.".format(
tup[0], output_filename)
return output_filename
def test_chimera_no_noise_1event_2levels(self):
filename = tf.get_abs_path('chimera_nonoise_1event_2levels.log')
event_database = find_events([filename], save_file_names=['_testChimera_nonoise_1Event_2Levels_9238.h5'])[0]
h5file = ed.open_file(event_database, mode='r')
self._test_chimera_no_noise_1event_2levels_helper(h5file)
h5file.close()
# delete the newly created event file
os.remove(event_database)
def test_chimera_no_noise_1event_2levels(self):
filename = os.path.dirname(os.path.realpath(__file__))
filename = os.path.join(filename, "testDataFiles", "chimera_nonoise_1event_2levels.log")
event_database = find_events([filename], save_file_names=["_testChimera_nonoise_1Event_2Levels_9238.h5"])[0]
h5file = ed.open_file(event_database, mode="r")
self._test_chimera_no_noise_1event_2levels_helper(h5file)
h5file.close()
# delete the newly created event file
os.remove(event_database)
def test_open_existing_empty_database(self):
"""
Tests opening an existing h5 file with an empty
EventsDatabase structure.
"""
self.database.close()
self.database = eD.open_file(self.filename)
self._test_initial_root(self.database)
self._test_empty_events_group()
def test_open_existing_empty_database(self):
"""
Tests opening an existing h5 file with an empty
EventsDatabase structure.
"""
self.database.close()
self.database = eD.open_file(self.filename)
self._test_initial_root(self.database)
self._test_empty_events_group()
def test_chimera_no_noise_1event_2levels(self):
filename = tf.get_abs_path('chimera_nonoise_1event_2levels.log')
event_database = find_events(
[filename],
save_file_names=['_testChimera_nonoise_1Event_2Levels_9238.h5'])[0]
h5file = ed.open_file(event_database, mode='r')
self._test_chimera_no_noise_1event_2levels_helper(h5file)
h5file.close()
# delete the newly created event file
os.remove(event_database)
def test_multiple_files(self):
filename1 = os.path.dirname(os.path.realpath(__file__))
filename1 = os.path.join(filename1, "testDataFiles", "chimera_nonoise_2events_1levels.log")
filename2 = os.path.dirname(os.path.realpath(__file__))
filename2 = os.path.join(filename2, "testDataFiles", "chimera_nonoise_1event_2levels.log")
file_names = [filename1, filename2]
event_databases = find_events(
file_names, save_file_names=["_testMultipleFiles_1_9238.h5", "_testMultipleFiles_2_9238.h5"]
)
self.assertEqual(len(event_databases), 2)
h5file = ed.open_file(event_databases[0], mode="r")
self._test_chimera_no_noise_2events_1levels_wrapper(h5file)
h5file.close()
os.remove(event_databases[0])
h5file = ed.open_file(event_databases[1], mode="r")
self._test_chimera_no_noise_1event_2levels_helper(h5file)
h5file.close()
os.remove(event_databases[1])
def test_open_existing_full_database(self):
"""
Tests opening an existing h5 file with events in
the EventDatabase structure.
"""
# Add to the raw_data matrix
raw_data = np.zeros((2, self.max_event_length))
raw_data[1][:] += 1
self.database.append_raw_data(raw_data)
# Add to the levels matrix
levels = raw_data + 1
self.database.append_levels(levels)
# Add to the level_lengths matrix
level_lengths = raw_data + 2
self.database.append_level_lengths(level_lengths)
# Add to the event table
event_row = self.database.get_event_table_row()
event_row['array_row'] = 1
event_row['event_start'] = 2
event_row['event_length'] = 3
event_row['n_levels'] = 4
event_row['raw_points_per_side'] = 5
event_row['baseline'] = 6
event_row['current_blockage'] = 7
event_row['area'] = 8
event_row.append()
# Close the file
self.database.flush()
self.database.close()
# Open the existing file
self.database = eD.open_file(self.filename, mode='r')
# Check the raw_data matrix
npt.assert_array_equal(raw_data, self.database.root.events.raw_data[:])
# Check the levels matrix
npt.assert_array_equal(levels, self.database.root.events.levels[:])
# Check the level_lengths matrix
npt.assert_array_equal(level_lengths,
self.database.root.events.level_lengths[:])
# Check the eventTable
row = self.database.root.events.eventTable[0]
self.assertEqual(row['array_row'], 1)
self.assertEqual(row['area'], 8)
def test_initialize_events_database_with_debug(self):
filename = 'test_initialize_events_database_with_debug.h5'
if os.path.exists(filename):
os.remove(filename)
n_points = 100
n_channels = 2
database = eD.open_file(filename,
mode='w',
debug=True,
n_points=n_points,
n_channels=n_channels)
self._test_initial_root(database)
self._test_empty_events_group(events_group=database.root.events)
# Make sure is debug
self.assertTrue(database.is_debug())
# Make sure the debug group is there.
names = [x._v_name for x in database.walk_groups()]
self.assertIn('debug', names, 'No debug group.')
debug_group = database.root.debug
# Make sure the debug group
debug_group_names = [
x._v_name for x in database.walk_nodes(debug_group)
]
print debug_group_names
self.assertIn('data', debug_group_names, 'No data matrix.')
self.assertIn('baseline', debug_group_names, 'No baseline matrix.')
self.assertIn('threshold_positive', debug_group_names,
'No positive threshold matrix.')
self.assertIn('threshold_negative', debug_group_names,
'No negative threshold matrix.')
# Make sure arrays are correct dimensions
self.assertEqual(debug_group.data.shape, (n_channels, n_points))
self.assertEqual(debug_group.baseline.shape, (n_channels, n_points))
self.assertEqual(debug_group.threshold_positive.shape,
(n_channels, n_points))
self.assertEqual(debug_group.threshold_negative.shape,
(n_channels, n_points))
# Check is in write mode
database.root.events.raw_data.append(np.zeros((1, 100)))
database.flush()
database.close()
os.remove(filename)
def test_chimera_no_noise_1event_2levels(self):
filename = os.path.dirname(os.path.realpath(__file__))
filename = os.path.join(filename, 'testDataFiles',
'chimera_nonoise_1event_2levels.log')
event_database = find_events(
[filename],
save_file_names=['_testChimera_nonoise_1Event_2Levels_9238.h5'])[0]
h5file = ed.open_file(event_database, mode='r')
self._test_chimera_no_noise_1event_2levels_helper(h5file)
h5file.close()
# delete the newly created event file
os.remove(event_database)
def test_open_existing_full_database(self):
"""
Tests opening an existing h5 file with events in
the EventDatabase structure.
"""
# Add to the raw_data matrix
raw_data = np.zeros((2, self.max_event_length))
raw_data[1][:] += 1
self.database.append_raw_data(raw_data)
# Add to the levels matrix
levels = raw_data + 1
self.database.append_levels(levels)
# Add to the level_lengths matrix
level_lengths = raw_data + 2
self.database.append_level_lengths(level_lengths)
# Add to the event table
event_row = self.database.get_event_table_row()
event_row['array_row'] = 1
event_row['event_start'] = 2
event_row['event_length'] = 3
event_row['n_levels'] = 4
event_row['raw_points_per_side'] = 5
event_row['baseline'] = 6
event_row['current_blockage'] = 7
event_row['area'] = 8
event_row.append()
# Close the file
self.database.flush()
self.database.close()
# Open the existing file
self.database = eD.open_file(self.filename, mode='r')
# Check the raw_data matrix
npt.assert_array_equal(raw_data, self.database.root.events.raw_data[:])
# Check the levels matrix
npt.assert_array_equal(levels, self.database.root.events.levels[:])
# Check the level_lengths matrix
npt.assert_array_equal(level_lengths, self.database.root.events.level_lengths[:])
# Check the eventTable
row = self.database.root.events.eventTable[0]
self.assertEqual(row['array_row'], 1)
self.assertEqual(row['area'], 8)
def test_chimera_no_noise_2events_1levels(self):
filename = tf.get_abs_path('chimera_nonoise_2events_1levels.log')
event_databases = find_events([filename], save_file_names=['_testChimera_nonoise_2events_1levels_9238.h5'])
self.assertEqual(len(event_databases), 1)
event_database = event_databases[0]
h5file = ed.open_file(event_database, mode='r')
self._test_chimera_no_noise_2events_1levels_wrapper(h5file)
h5file.close()
# delete the newly created event file
os.remove(event_database)
def test_saving_files(self):
filename = tf.get_abs_path('chimera_1event.log')
event_database = find_events([filename], save_file_names=['_testSavingFiles_9238.h5'])[0]
self.assertTrue(os.path.isfile(event_database))
h5file = ed.open_file(event_database, mode='r')
self.assertTrue(h5file.isopen)
h5file.close()
# delete the newly created event file
os.remove(event_database)
def test_saving_files(self):
filename = os.path.dirname(os.path.realpath(__file__))
filename = os.path.join(filename, "testDataFiles", "chimera_1event.log")
event_database = find_events([filename], save_file_names=["_testSavingFiles_9238.h5"])[0]
self.assertTrue(os.path.isfile(event_database))
h5file = ed.open_file(event_database, mode="r")
self.assertTrue(h5file.isopen)
h5file.close()
# delete the newly created event file
os.remove(event_database)
def test_chimera_no_noise_2events_1levels(self):
filename = tf.get_abs_path('chimera_nonoise_2events_1levels.log')
event_databases = find_events(
[filename],
save_file_names=['_testChimera_nonoise_2events_1levels_9238.h5'])
self.assertEqual(len(event_databases), 1)
event_database = event_databases[0]
h5file = ed.open_file(event_database, mode='r')
self._test_chimera_no_noise_2events_1levels_wrapper(h5file)
h5file.close()
# delete the newly created event file
os.remove(event_database)
def test_saving_files(self):
filename = tf.get_abs_path('chimera_1event.log')
event_database = find_events(
[filename], save_file_names=['_testSavingFiles_9238.h5'])[0]
self.assertTrue(os.path.isfile(event_database))
h5file = ed.open_file(event_database, mode='r')
self.assertTrue(h5file.isopen)
h5file.close()
# delete the newly created event file
os.remove(event_database)
def test_too_large_end_threshold(self, filename):
"""
Tests that we don't find events when the ending threshold is too large.
"""
data_file = tf.get_abs_path('chimera_1event.log')
parameters = Parameters(threshold_strategy=AbsoluteChangeThresholdStrategy(2., 1000.))
event_databases = find_events([data_file], parameters=parameters,
save_file_names=[filename], debug=True)
h5file = ed.open_file(filename, mode='r')
event_count = h5file.get_event_count()
self.assertEqual(event_count, 0, "Unexpected event count. Should be {0}, was {1}.".format(event_count, 0))
h5file.close()
def test_passing_reader(self):
"""
Tests that passing an open subtype of :py:class:`pypore.i_o.abstract_reader.AbstractReader` works.
"""
filename = os.path.dirname(os.path.realpath(__file__))
filename = os.path.join(filename, "testDataFiles", "chimera_nonoise_2events_1levels.log")
reader = get_reader_from_filename(filename)
data = [reader]
event_databases = find_events(data, save_file_names=["_test_passing_reader.h5"])
self.assertEqual(len(event_databases), 1)
h5file = ed.open_file(event_databases[0], mode="r")
self._test_chimera_no_noise_2events_1levels_wrapper(h5file)
h5file.close()
os.remove(event_databases[0])
def add_selections(self, file_names, params):
"""
Plots event statistics.
"""
files = []
counts = []
event_count = 0
for filename in file_names:
h5file = ed.open_file(filename, mode='r')
files.append(h5file)
count = h5file.get_event_count()
event_count += count
counts.append(count)
current_blockade = np.empty(event_count)
dwell_times = np.empty(event_count)
count = 0
for j, filex in enumerate(files):
event_table = filex.get_event_table()
sample_rate = filex.get_sample_rate()
for i, row in enumerate(event_table):
current_blockade[count + i] = row['current_blockage']
dwell_times[count + i] = row['event_length'] / sample_rate
count += counts[j]
color = params['color']
new_color = QtGui.QColor(color.red(), color.green(), color.blue(), 128)
self.plot_event_dur.add_histogram(dwell_times, color=new_color)
self.plot_event_depth.add_histogram(current_blockade, color=new_color)
scatter_item = ScatterPlotItem(size=10,
pen=mkPen(None),
brush=new_color,
files=file_names,
counts=counts)
scatter_item.setData(dwell_times, current_blockade)
self.plot_event_dur_event_depth.addItem(scatter_item)
scatter_item.sigClicked.connect(self.on_scatter_points_clicked)
for filex in files:
filex.close()
return
def test_passing_reader(self):
"""
Tests that passing an open subtype of :py:class:`pypore.i_o.abstract_reader.AbstractReader` works.
"""
filename = os.path.dirname(os.path.realpath(__file__))
filename = tf.get_abs_path('chimera_nonoise_2events_1levels.log')
reader = get_reader_from_filename(filename)
data = [reader]
event_databases = find_events(
data, save_file_names=['_test_passing_reader.h5'])
self.assertEqual(len(event_databases), 1)
h5file = ed.open_file(event_databases[0], mode='r')
self._test_chimera_no_noise_2events_1levels_wrapper(h5file)
h5file.close()
os.remove(event_databases[0])
def _on_eventview_file_item_doubleclick(self, item):
"""
"""
self.event_view_item = item
h5file = eD.open_file(item.get_file_name())
event_count = h5file.get_event_count()
if h5file.is_debug():
self.plot_debug(h5file)
h5file.close()
self.event_display_edit.setMaxLength(int(event_count / 10) + 1)
self.event_display_edit.setValidator(QtGui.QIntValidator(1, event_count, self.event_display_edit))
self.event_count_text.setText('/' + str(event_count))
self.event_display_edit.setText('')
self.event_display_edit.setText('1')
def plot_single_events(self, event):
"""
Plots the event on the plot with
"""
h5file = eD.open_file(self.event_view_item.get_file_name(), mode='r')
event_count = h5file.get_event_count()
for i in xrange(3):
for j in xrange(3):
pos = 3 * i + j
if pos + event >= event_count or pos + event < 0:
self.eventviewer_plots[pos].clear()
self.eventviewer_plots[pos].setTitle('')
else:
self.plot_single_event(h5file, event + pos, self.eventviewer_plots[pos])
self.eventviewer_plots[pos].setTitle('Event ' + str(event + pos + 1))
h5file.close()
def _on_eventview_file_item_doubleclick(self, item):
"""
"""
self.event_view_item = item
h5file = eD.open_file(item.get_file_name())
event_count = h5file.get_event_count()
if h5file.is_debug():
self.plot_debug(h5file)
h5file.close()
self.event_display_edit.setMaxLength(int(event_count / 10) + 1)
self.event_display_edit.setValidator(
QtGui.QIntValidator(1, event_count, self.event_display_edit))
self.event_count_text.setText('/' + str(event_count))
self.event_display_edit.setText('')
self.event_display_edit.setText('1')
def test_initialize_events_database_with_debug(self):
filename = 'test_initialize_events_database_with_debug.h5'
if os.path.exists(filename):
os.remove(filename)
n_points = 100
n_channels = 2
database = eD.open_file(filename, mode='w', debug=True, n_points=n_points, n_channels=n_channels)
self._test_initial_root(database)
self._test_empty_events_group(events_group=database.root.events)
# Make sure is debug
self.assertTrue(database.is_debug())
# Make sure the debug group is there.
names = [x._v_name for x in database.walk_groups()]
self.assertIn('debug', names, 'No debug group.')
debug_group = database.root.debug
# Make sure the debug group
debug_group_names = [x._v_name for x in database.walk_nodes(debug_group)]
print debug_group_names
self.assertIn('data', debug_group_names, 'No data matrix.')
self.assertIn('baseline', debug_group_names, 'No baseline matrix.')
self.assertIn('threshold_positive', debug_group_names, 'No positive threshold matrix.')
self.assertIn('threshold_negative', debug_group_names, 'No negative threshold matrix.')
# Make sure arrays are correct dimensions
self.assertEqual(debug_group.data.shape, (n_channels, n_points))
self.assertEqual(debug_group.baseline.shape, (n_channels, n_points))
self.assertEqual(debug_group.threshold_positive.shape, (n_channels, n_points))
self.assertEqual(debug_group.threshold_negative.shape, (n_channels, n_points))
# Check is in write mode
database.root.events.raw_data.append(np.zeros((1, 100)))
database.flush()
database.close()
os.remove(filename)
def add_selections(self, file_names, params):
"""
Plots event statistics.
"""
files = []
counts = []
event_count = 0
for filename in file_names:
h5file = ed.open_file(filename, mode='r')
files.append(h5file)
count = h5file.get_event_count()
event_count += count
counts.append(count)
current_blockade = np.empty(event_count)
dwell_times = np.empty(event_count)
count = 0
for j, filex in enumerate(files):
event_table = filex.get_event_table()
sample_rate = filex.get_sample_rate()
for i, row in enumerate(event_table):
current_blockade[count + i] = row['current_blockage']
dwell_times[count + i] = row['event_length'] / sample_rate
count += counts[j]
color = params['color']
new_color = QtGui.QColor(color.red(), color.green(), color.blue(), 128)
self.plot_event_dur.add_histogram(dwell_times, color=new_color)
self.plot_event_depth.add_histogram(current_blockade, color=new_color)
scatter_item = ScatterPlotItem(size=10, pen=mkPen(None), brush=new_color, files=file_names, counts=counts)
scatter_item.setData(dwell_times, current_blockade)
self.plot_event_dur_event_depth.addItem(scatter_item)
scatter_item.sigClicked.connect(self.on_scatter_points_clicked)
for filex in files:
filex.close()
return
def plot_single_events(self, event):
"""
Plots the event on the plot with
"""
h5file = eD.open_file(self.event_view_item.get_file_name(), mode='r')
event_count = h5file.get_event_count()
for i in xrange(3):
for j in xrange(3):
pos = 3 * i + j
if pos + event >= event_count or pos + event < 0:
self.eventviewer_plots[pos].clear()
self.eventviewer_plots[pos].setTitle('')
else:
self.plot_single_event(h5file, event + pos,
self.eventviewer_plots[pos])
self.eventviewer_plots[pos].setTitle('Event ' +
str(event + pos + 1))
h5file.close()
def move_event_display_by(self, count):
"""
Changes the event displayed on the event display plot to
current value + count
"""
h5_event_count = 0
try:
h5file = eD.open_file(self.event_view_item.get_file_name())
h5_event_count = h5file.get_event_count()
h5file.close()
except:
return
try:
event_count = int(self.event_display_edit.text())
if 0 < event_count + count <= h5_event_count:
self.event_display_edit.setText(str(event_count + count))
except ValueError:
# if we can't parse the event display text but there are events,
# just set to zero
if h5_event_count > 0:
self.event_display_edit.setText('1')
def move_event_display_by(self, count):
"""
Changes the event displayed on the event display plot to
current value + count
"""
h5_event_count = 0
try:
h5file = eD.open_file(self.event_view_item.get_file_name())
h5_event_count = h5file.get_event_count()
h5file.close()
except:
return
try:
event_count = int(self.event_display_edit.text())
if 0 < event_count + count <= h5_event_count:
self.event_display_edit.setText(str(event_count + count))
except ValueError:
# if we can't parse the event display text but there are events,
# just set to zero
if h5_event_count > 0:
self.event_display_edit.setText('1')
def test_chimera_no_noise_1event(self):
filename = os.path.dirname(os.path.realpath(__file__))
filename = os.path.join(filename, 'testDataFiles',
'chimera_nonoise_1event.log')
event_database = find_events(
[filename],
save_file_names=['_testChimera_nonoise_1Event_9238.h5'])[0]
h5file = ed.open_file(event_database, mode='r')
events = h5file.root.events
# check event table correct length
event_table = events.eventTable
self.assertTrue(event_table.nrows, 1)
# check raw data array correct length
raw_data_matrix = events.raw_data
self.assertEqual(raw_data_matrix.nrows, 1)
event_length = event_table[0]['event_length']
self.assertEqual(event_length, 1000)
# Make sure only 1 event with 1 level
levels_matrix = events.levels
self.assertEqual(levels_matrix.nrows, 1)
n_levels = event_table[0]['n_levels']
self.assertEqual(n_levels, 1)
levels = levels_matrix[0]
self.assertAlmostEqual(levels[0], 15.13955, 3)
# Check 1 event with 1 levelLength
lengths_matrix = events.level_lengths
self.assertEqual(lengths_matrix.nrows, 1)
lengths = lengths_matrix[0]
self.assertEqual(lengths[0], 1000)
h5file.close()
# delete the newly created event file
os.remove(event_database)
def test_too_large_end_threshold(self, filename):
"""
Tests that we don't find events when the ending threshold is too large.
"""
data_file = tf.get_abs_path('chimera_1event.log')
parameters = Parameters(
threshold_strategy=AbsoluteChangeThresholdStrategy(2., 1000.))
event_databases = find_events([data_file],
parameters=parameters,
save_file_names=[filename],
debug=True)
h5file = ed.open_file(filename, mode='r')
event_count = h5file.get_event_count()
self.assertEqual(
event_count, 0,
"Unexpected event count. Should be {0}, was {1}.".format(
event_count, 0))
h5file.close()
def test_chimera_no_noise_1event(self):
filename = os.path.dirname(os.path.realpath(__file__))
filename = os.path.join(filename, "testDataFiles", "chimera_nonoise_1event.log")
event_database = find_events([filename], save_file_names=["_testChimera_nonoise_1Event_9238.h5"])[0]
h5file = ed.open_file(event_database, mode="r")
events = h5file.root.events
# check event table correct length
event_table = events.eventTable
self.assertTrue(event_table.nrows, 1)
# check raw data array correct length
raw_data_matrix = events.raw_data
self.assertEqual(raw_data_matrix.nrows, 1)
event_length = event_table[0]["event_length"]
self.assertEqual(event_length, 1000)
# Make sure only 1 event with 1 level
levels_matrix = events.levels
self.assertEqual(levels_matrix.nrows, 1)
n_levels = event_table[0]["n_levels"]
self.assertEqual(n_levels, 1)
levels = levels_matrix[0]
self.assertAlmostEqual(levels[0], 15.13955, 3)
# Check 1 event with 1 levelLength
lengths_matrix = events.level_lengths
self.assertEqual(lengths_matrix.nrows, 1)
lengths = lengths_matrix[0]
self.assertEqual(lengths[0], 1000)
h5file.close()
# delete the newly created event file
os.remove(event_database)
def test_chimera_no_noise_1event(self):
filename = tf.get_abs_path('chimera_nonoise_1event.log')
event_database = find_events([filename], save_file_names=['_testChimera_nonoise_1Event_9238.h5'])[0]
h5file = ed.open_file(event_database, mode='r')
events = h5file.root.events
# check event table correct length
event_table = events.eventTable
self.assertTrue(event_table.nrows, 1)
# check raw data array correct length
raw_data_matrix = events.raw_data
self.assertEqual(raw_data_matrix.nrows, 1)
event_length = event_table[0]['event_length']
self.assertEqual(event_length, 1000)
# Make sure only 1 event with 1 level
levels_matrix = events.levels
self.assertEqual(levels_matrix.nrows, 1)
n_levels = event_table[0]['n_levels']
self.assertEqual(n_levels, 1)
levels = levels_matrix[0]
self.assertAlmostEqual(levels[0], 15.13955, 3)
# Check 1 event with 1 levelLength
lengths_matrix = events.level_lengths
self.assertEqual(lengths_matrix.nrows, 1)
lengths = lengths_matrix[0]
self.assertEqual(lengths[0], 1000)
h5file.close()
# delete the newly created event file
os.remove(event_database)
def on_scatter_points_clicked(self, plot, points):
"""
Callback for when a scatter plot points are clicked.
Highlights the points and un-highlights previously selected points.
plot should be a MyScatterPlotItem
points should be a MySpotItem
"""
for p in self.last_scatter_clicked:
p.resetPen()
# remove point we've already selected so we
# can select points behind it.
if p in points and len(points) > 1:
points.remove(p)
# print 'Points clicked:', points, plot
for point in points:
point.setPen('w', width=2)
self.last_scatter_clicked = [point]
break # only take first point
# Plot the new point clicked on the single event display
filename, position = plot.get_file_name_from_position(self.last_scatter_clicked[0].event_position)
h5file = ed.open_file(filename, mode='r')
row = h5file.get_event_row(position)
array_row = row['array_row']
sample_rate = h5file.get_sample_rate()
event_length = row['event_length']
raw_points_per_side = row['raw_points_per_side']
raw_data = h5file.get_raw_data_at(array_row)
n = len(raw_data)
times = np.linspace(0.0, 1.0 * n / sample_rate, n)
self.plot_scatter_select.clear()
self.plot_scatter_select.plot(times, raw_data)
# plot the event points in yellow
self.plot_scatter_select.plot(times[raw_points_per_side:raw_points_per_side + event_length],
raw_data[raw_points_per_side:raw_points_per_side + event_length], pen='y')
# Plot the cusum levels
n_levels = row['n_levels']
baseline = row['baseline']
# left, start-1, start,
levels = h5file.get_levels_at(array_row)
indices = h5file.get_level_lengths_at(array_row)
level_times = np.zeros(2 * n_levels + 4)
level_values = np.zeros(2 * n_levels + 4)
level_times[1] = 1.0 * (raw_points_per_side - 1) / sample_rate
level_values[0] = level_values[1] = baseline
i = 0
length = 0
for i in xrange(n_levels):
level_times[2 * i + 2] = times[raw_points_per_side] + 1.0 * length / sample_rate
level_values[2 * i + 2] = levels[i]
level_times[2 * i + 3] = times[raw_points_per_side] + 1.0 * (length + indices[i]) / sample_rate
level_values[2 * i + 3] = levels[i]
length += indices[i]
i += 1
level_times[2 * i + 2] = times[raw_points_per_side + event_length]
level_times[2 * i + 3] = times[n - 1]
level_values[2 * i + 2] = level_values[2 * i + 3] = baseline
self.plot_scatter_select.plot(level_times, level_values, pen='g')
h5file.close()
def on_scatter_points_clicked(self, plot, points):
"""
Callback for when a scatter plot points are clicked.
Highlights the points and un-highlights previously selected points.
plot should be a MyScatterPlotItem
points should be a MySpotItem
"""
for p in self.last_scatter_clicked:
p.resetPen()
# remove point we've already selected so we
# can select points behind it.
if p in points and len(points) > 1:
points.remove(p)
# print 'Points clicked:', points, plot
for point in points:
point.setPen('w', width=2)
self.last_scatter_clicked = [point]
break # only take first point
# Plot the new point clicked on the single event display
filename, position = plot.get_file_name_from_position(
self.last_scatter_clicked[0].event_position)
h5file = ed.open_file(filename, mode='r')
row = h5file.get_event_row(position)
array_row = row['array_row']
sample_rate = h5file.get_sample_rate()
event_length = row['event_length']
raw_points_per_side = row['raw_points_per_side']
raw_data = h5file.get_raw_data_at(array_row)
n = len(raw_data)
times = np.linspace(0.0, 1.0 * n / sample_rate, n)
self.plot_scatter_select.clear()
self.plot_scatter_select.plot(times, raw_data)
# plot the event points in yellow
self.plot_scatter_select.plot(
times[raw_points_per_side:raw_points_per_side + event_length],
raw_data[raw_points_per_side:raw_points_per_side + event_length],
pen='y')
# Plot the cusum levels
n_levels = row['n_levels']
baseline = row['baseline']
# left, start-1, start,
levels = h5file.get_levels_at(array_row)
indices = h5file.get_level_lengths_at(array_row)
level_times = np.zeros(2 * n_levels + 4)
level_values = np.zeros(2 * n_levels + 4)
level_times[1] = 1.0 * (raw_points_per_side - 1) / sample_rate
level_values[0] = level_values[1] = baseline
i = 0
length = 0
for i in xrange(n_levels):
level_times[
2 * i +
2] = times[raw_points_per_side] + 1.0 * length / sample_rate
level_values[2 * i + 2] = levels[i]
level_times[2 * i + 3] = times[raw_points_per_side] + 1.0 * (
length + indices[i]) / sample_rate
level_values[2 * i + 3] = levels[i]
length += indices[i]
i += 1
level_times[2 * i + 2] = times[raw_points_per_side + event_length]
level_times[2 * i + 3] = times[n - 1]
level_values[2 * i + 2] = level_values[2 * i + 3] = baseline
self.plot_scatter_select.plot(level_times, level_values, pen='g')
h5file.close()
def setUp(self):
self.filename = 'testEventDatabase_938247283278128.h5'
self.max_event_length = 100
self.database = eD.open_file(self.filename,
mode='w',
maxEventLength=self.max_event_length)
def setUp(self):
self.filename = 'testEventDatabase_938247283278128.h5'
self.max_event_length = 100
self.database = eD.open_file(self.filename, mode='w', maxEventLength=self.max_event_length)
