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Flipping features #19

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Flipping features #19

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47 changes: 31 additions & 16 deletions spikedetekt2/core/main.py
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Original file line number Diff line number Diff line change
Expand Up @@ -129,6 +129,21 @@ def save_features(experiment, **prm):
features = project_pcs(waveform, pcs)
spikes.features_masks[i,:,0] = features.ravel()

# Flip the PCs.
# First, compute the mean features.
features_mean = spikes.features_masks[::step, :, 0].mean(axis=0)
to_flip = features_mean < 0
to_flip_ind = np.nonzero(to_flip)[0]
if len(to_flip_ind) > 0:
# Flip the features.
spikes.features_masks[:, to_flip_ind, 0] *= -1
pcs = experiment.channel_groups[chgrp]._node.pca_waveforms
# Find the channels to flip.
channels_to_flip = to_flip[0:pcs.shape[-1]:npcs]
channels_to_flip_ind = np.nonzero(channels_to_flip)[0]
# Flip the PCs.
pcs[..., channels_to_flip_ind] *= -1


# -----------------------------------------------------------------------------
# File logger
Expand All @@ -147,7 +162,7 @@ def close_file_logger(LOGGER_FILE):
# -----------------------------------------------------------------------------
# Main loop
# -----------------------------------------------------------------------------
def run(raw_data=None, experiment=None, prm=None, probe=None,
def run(raw_data=None, experiment=None, prm=None, probe=None,
_debug=False, convert_only=False):
"""This main function takes raw data (either as a RawReader, or a path
to a filename, or an array) and executes the main algorithm (filtering,
Expand Down Expand Up @@ -181,19 +196,19 @@ def run(raw_data=None, experiment=None, prm=None, probe=None,

# Get the bandpass filter.
filter = bandpass_filter(**prm)

if not (convert_only and first_chunk_detected):
# Compute the strong threshold across excerpts uniformly scattered across the
# whole recording.
threshold = get_threshold(raw_data, filter=filter,
threshold = get_threshold(raw_data, filter=filter,
channels=probe.channels, **prm)
assert not np.isnan(threshold.weak).any()
assert not np.isnan(threshold.strong).any()
debug("Threshold: " + str(threshold))

# Debug module.
diagnostics_script_path = prm.get('diagnostics_script_path', None)

# Progress bar.
progress_bar = ProgressReporter(period=30.)
nspikes = 0
Expand Down Expand Up @@ -235,44 +250,44 @@ def run(raw_data=None, experiment=None, prm=None, probe=None,
chunk_low = decimate(chunk_raw)
chunk_low_keep = chunk_low[i//16:j//16,:]
experiment.recordings[chunk.recording].low.append(convert_dtype(chunk_low_keep, np.int16))

if not (convert_only and first_chunk_detected):
# Apply thresholds.
chunk_detect, chunk_threshold = apply_threshold(chunk_fil,
chunk_detect, chunk_threshold = apply_threshold(chunk_fil,
threshold=threshold, **prm)

# Remove dead channels.
dead = np.setdiff1d(np.arange(nchannels), probe.channels)
chunk_detect[:,dead] = 0
chunk_threshold.strong[:,dead] = 0
chunk_threshold.weak[:,dead] = 0

# Find connected component (strong threshold). Return list of
# Component instances.
components = connected_components(
chunk_strong=chunk_threshold.strong,
chunk_weak=chunk_threshold.weak,
chunk_strong=chunk_threshold.strong,
chunk_weak=chunk_threshold.weak,
probe_adjacency_list=probe.adjacency_list,
chunk=chunk, **prm)

# Now we extract the spike in each component.
waveforms = extract_waveforms(chunk_detect=chunk_detect,
threshold=threshold, chunk_fil=chunk_fil, chunk_raw=chunk_raw,
threshold=threshold, chunk_fil=chunk_fil, chunk_raw=chunk_raw,
probe=probe, components=components, **prm)

# DEBUG module.
# Execute the debug script.
if diagnostics_script_path:
execfile(diagnostics_script_path)

# Log number of spikes in the chunk.
nspikes += len(waveforms)

# We sort waveforms by increasing order of fractional time.
[add_waveform(experiment, waveform) for waveform in sorted(waveforms)]

first_chunk_detected = True

# Update the progress bar.
progress_bar.update(rec/float(nrecs) + (float(s_end) / (nsamples*nrecs)),
'%d spikes found.' % (nspikes))
Expand Down