def get_events(self, channel, times=None, raw_indices=None, event_indices=(None, None),
use_scaling=True):
"""Parse channel event data.
:param channel: channel number int
:param times: tuple of floats (start_second, end_second)
:param raw_indices: tuple of ints (start_index, end_index)
:param event_indices: tuple of ints (start_index, end_index)
:param use_scaling: if True, scale the current level
.. note::
Exactly one of the slice keyword arguments needs to be specified,
as the method will override them in the order of times
> raw_indices > event_indices.
"""
event_data = self.__event_data__.format(channel)
ev = self[event_data]
if times is not None:
raw_indices = self._time_interval_to_index(channel, times)
if raw_indices is not None:
event_indices = np.searchsorted(ev['start'], raw_indices)
data = _sanitize_data_for_reading(ev[event_indices[0]:event_indices[1]])
# Change variance to stdv column
data['variance'] = np.sqrt(data['variance'])
data.dtype.names = ['stdv' if n == 'variance' else n for n in data.dtype.names]
if use_scaling:
return self._scale(channel, data)
else:
return data
def test_015_fastq(self):
""" Test fastq assembly and writing """
fastq = '@unknown\n{}\n+\n{}\n'.format(self.seq, self.qstring)
self.assertEqual(
_sanitize_data_for_reading(
self.fh['/Analyses/Basecall_1D_000/BaseCalled_template/Fastq'][
()]), fastq)
def get_state_changes(self, channel):
"""Parse channel state changes.
:param channel: channel number int
"""
if not self.has_states(channel):
raise KeyError(
'Channel {} does not contain state data.'.format(channel))
if hasattr(self, '_cached_state_changes'):
if channel in self._cached_state_changes:
return self._cached_state_changes[channel]
else:
self._cached_state_changes = {}
# state data is enumerated
col = 'summary_state'
data = self[self.__state_data__.format(channel)]
enum_map = h5py.check_dtype(enum=data.dtype[col])
enum_to_state = _clean_attrs({v: k for k, v in enum_map.items()})
# translate ints into strings
states = np.array([enum_to_state[key] for key in data[col]])
try:
data = np.array(data['approx_raw_index'])
except ValueError: #not a KeyError: see h5py/_hl/dataset.pyc in readtime_dtype(basetype, names)
data = np.array(data['acquisition_raw_index'])
if len(data) > 0:
data = data.astype([('approx_raw_index', data.dtype)], copy=False)
data = append_fields(
data, ['approx_raw_index_end', 'summary_state'],
[np.roll(data['approx_raw_index'], -1), states],
usemask=False)
# set end of last state to something approximating infinity (the largest u64 int).
data['approx_raw_index_end'][-1] = -1
else: # some channels don't contain channel state data, just create a dummy array
data = np.array([],
dtype=[('approx_raw_index', '<u8'),
('approx_raw_index_end', '<u8'),
('summary_state', 'S28')])
self._cached_state_changes[channel] = data
return _sanitize_data_for_reading(data)
