def metadata_from_file(file):
"""Read metadata of single .continuous file header/file stats. Checks if the file contains
complete records based on the size of the file as header size + integer multiples of records.
Args:
file: Path to .continuous file
Returns:
Dictionary with n_blocks, block_size, n_samples, sampling_rate fields.
"""
header = read_header(file)
fs = header['sampleRate']
n_record_bytes = int(os.path.getsize(file) - SIZE_HEADER)
n_blocks = n_record_bytes / SIZE_RECORD
if n_record_bytes % SIZE_RECORD != 0:
raise ValueError('File {} contains incomplete records!'.format(file))
n_samples = n_record_bytes - n_blocks * (SIZE_RECORD - SIZE_DATA)
logger.log(level=LOG_LEVEL_VERBOSE,
msg='{}, Fs = {:.2f}Hz, {} blocks, {} samples, {}'.format(
file, fs, n_blocks, n_samples,
util.fmt_time(n_samples / fs)))
return dict(n_blocks=int(n_blocks),
block_size=NUM_SAMPLES,
n_samples=int(n_samples),
sampling_rate=fs)
def plot_noise(noise_arr, thresholds, tetrode=None):
fig, ax = plt.subplots(4, 1, figsize=(18, 4), sharex=True)
# fig = plt.figure()
# ax = []
# ax[0] = plt.subplot2grid((8, 4), (0, 0))
# ax2 = plt.subplot2grid((8, 4), (0, 1), colspan=2)
# ax3 = plt.subplot2grid((8, 4), (1, 0), colspan=2, rowspan=2)
# ax4 = plt.subplot2grid((8, 4), (1, 2), rowspan=2)
title = 'Noise estimation (1.0 second bins) ' + ('' if tetrode is None else f'tetrode {tetrode}')
ax[0].set_title(title)
t = np.linspace(0, len(noise_arr), len(noise_arr))
# limits = np.min(np.percentile(noise_arr, 0, axis=0)), np.max(np.percentile(noise_arr, 99.99, axis=0))
limits = (np.min(noise_arr, axis=(0, 1)), np.max(noise_arr, axis=(0, 1)))
for n in range(4):
ax[n].plot(t, noise_arr[:, n], color='C' + str(n), alpha=.6, linewidth=1)
ax[n].set_ylabel('$\mu V$')
ax[n].set_ylim(limits)
ax[n].xaxis.set_major_formatter(plt.FuncFormatter(lambda x, p: fmt_time(x, millis=False)))
# draw thresholds
ax[n].axhline(thresholds[n], linestyle=':', color='gray')
ax[-1].set_xlabel('$Time$')
return fig
def on_mouse_double_click(self, event):
x, y = event.pos
x_r = x / self.size[0]
# y_r = y / self.size[1]
# TODO: use y-coordinate to guesstimate the channel id + amplitude at point
t_r = x_r * self.n_cols - math.floor(x_r * self.n_cols)
t_sample = (t_r * self.buffer_length + self.offset * 1024
) # self.cfg['HEADER']['block_size']
t_sec = t_sample / self.fs
self.logger.info('Sample {} @ {}, offset {}'.format(
int(t_sample), util.fmt_time(t_sec), self.offset))
def continuous_to_dat(target_metadata,
output_path,
channel_group,
file_mode='w',
chunk_records=1000,
duration=0,
dead_channel_ids=None,
zero_dead_channels=True):
start_t = time.time()
# Logging
file_handler = logging.FileHandler(output_path + '.log')
formatter = logging.Formatter('%(message)s')
file_handler.setFormatter(formatter)
logger.addHandler(file_handler)
logger.log(level=LOG_LEVEL_VERBOSE,
msg='Target metadata: {}'.format(
pformat(target_metadata, indent=2)))
# NOTE: Channel numbers zero-based in configuration, but not in file name space. Grml.
data_channel_ids = channel_group['channels']
ref_channel_ids = [rid for rid in channel_group['reference']
] if "reference" in channel_group else []
dead_channel_ids = [did for did in dead_channel_ids]
logger.debug("Zeroing dead channels: {}, dead (OE) channels: {}".format(
zero_dead_channels, dead_channel_ids))
dead_channels_indices = [
data_channel_ids.index(dc) for dc in dead_channel_ids
if dc in data_channel_ids
]
try:
logger.debug('Opening output file {} in filemode {}'.format(
output_path, file_mode + 'b'))
with ExitStack() as stack, open(output_path,
file_mode + 'b') as out_fid_dat:
data_duration = 0
# Loop over all sub-recordings
for sub_id, subset in target_metadata['SUBSETS'].items():
logger.debug('Converting sub_id {}'.format(sub_id))
data_file_paths = [
subset['FILES'][cid]['FILEPATH']
for cid in data_channel_ids
]
ref_file_paths = [
subset['FILES'][rid]['FILEPATH'] for rid in ref_channel_ids
]
logger.log(level=LOG_LEVEL_VERBOSE, msg=data_file_paths)
data_files = [
stack.enter_context(oe.ContinuousFile(f))
for f in data_file_paths
]
ref_files = [
stack.enter_context(oe.ContinuousFile(f))
for f in ref_file_paths
]
for oe_file in data_files:
logger.log(level=LOG_LEVEL_VERBOSE,
msg="Open data file: {}".format(
op.basename(oe_file.path)) +
LOG_STR_ITEM.format(header=oe_file.header))
for oe_file in ref_files:
logger.log(level=LOG_LEVEL_VERBOSE,
msg="Open reference file: {}".format(
op.basename(oe_file.path)) +
LOG_STR_ITEM.format(header=oe_file.header))
n_blocks = subset['JOINT_HEADERS']['n_blocks']
sampling_rate = subset['JOINT_HEADERS']['sampling_rate']
# buffer_size = subset['JOINT_HEADERS']['buffer_size']
block_size = subset['JOINT_HEADERS']['block_size']
# If duration limited, find max number of records that should be grabbed
records_left = n_blocks if not duration \
else min(n_blocks, int(duration * sampling_rate // block_size))
if records_left < 1:
epsilon = 1 / sampling_rate * block_size * 1000
logger.warning(
"Remaining duration limit ({:.0f} ms) less than duration of single block ({:.0f} ms). "
"Skipping target.".format(duration * 1000, epsilon))
return 0
# loop over all records, in chunk sizes
bytes_written = 0
pbar = tqdm.tqdm(total=records_left * 1024,
unit_scale=True,
unit='Samples')
while records_left:
count = min(records_left, chunk_records)
pbar.update(count * 1024)
logger.log(level=LOG_LEVEL_VERBOSE,
msg=DEBUG_STR_CHUNK.format(
count=count,
left=records_left,
num_records=n_blocks))
res = np.vstack([f.read_record(count) for f in data_files])
# reference channels if needed
if len(ref_channel_ids):
logger.debug(
DEBUG_STR_REREF.format(channels=ref_channel_ids))
res -= np.vstack([
f.read_record(count) for f in ref_files
]).mean(axis=0, dtype=np.int16)
# zero dead channels if needed
if len(dead_channels_indices) and zero_dead_channels:
zeros = np.zeros_like(res[0])
for dci in dead_channels_indices:
logger.debug(
DEBUG_STR_ZEROS.format(
flag=zero_dead_channels,
channel=data_channel_ids[dci]))
res[dci] = zeros
res.transpose().tofile(out_fid_dat)
records_left -= count
bytes_written += (count * 2048 * len(data_channel_ids))
pbar.close()
data_duration += bytes_written / (2 * sampling_rate *
len(data_channel_ids))
elapsed = time.time() - start_t
speed = bytes_written / elapsed
logger.debug(
'{appended} {channels} channels into "{op:s}"'.format(
appended=MODE_STR_PAST[file_mode],
channels=len(data_channel_ids),
op=os.path.abspath(output_path)))
logger.info(
'{n_channels} channels, {rec} blocks ({dur:s}, {bw:.2f} MB) in {et:.2f} s ({ts:.2f} MB/s)'
.format(n_channels=len(data_channel_ids),
rec=n_blocks - records_left,
dur=util.fmt_time(data_duration),
bw=bytes_written / 1e6,
et=elapsed,
ts=speed / 1e6))
# returning duration of data written, epsilon=1 sample, allows external loop to make proper judgement if
# going to next target makes sense via comparison. E.g. if time less than one sample short of
# duration limit.
logger.removeHandler(file_handler)
file_handler.close()
return data_duration
except IOError as e:
logger.exception('Operation failed: {error}'.format(error=e.strerror))
def main(args):
parser = argparse.ArgumentParser(
'Convert file formats/layouts. Default result is int16 .dat file.')
parser.add_argument('-v',
'--verbose',
action='store_true',
help="Verbose (debug) output")
# Input/output
parser.add_argument(
'target',
nargs='*',
default='.',
help=
"""Path/list of paths to directories containing raw .continuous data OR path
to .session definition file. Listing multiple files will result in data sets
being concatenated in listed order.""")
parser.add_argument(
'-o',
'--out_path',
help='Output file path Defaults to current working directory')
parser.add_argument('-P',
'--out_prefix',
help='Output file prefix. Default is name of target.')
parser.add_argument('-T',
'--template_fname',
help='Output file template. Default: {}'.format(
DEFAULT_SHORT_TEMPLATE))
parser.add_argument('-f',
'--format',
help='Output format. Default is: {}'.format(
list(FORMATS.keys())[2]),
choices=FORMATS.keys(),
default=list(FORMATS.keys())[2])
parser.add_argument('--fname_channels',
action='store_true',
help='Include original channel numbers in file names.')
# Channel arrangement
channel_group = parser.add_mutually_exclusive_group()
channel_group.add_argument('-c',
"--channel-count",
type=int,
help='Number of consecutive channels.')
channel_group.add_argument(
'-C',
"--channel-list",
nargs='*',
type=int,
help='List of channels in order they are to be merged.')
channel_group.add_argument('-l',
'--layout',
help="Path to klusta .probe file.")
parser.add_argument('-g',
'--channel-groups',
type=int,
nargs="+",
help="limit to only a subset of the channel groups")
parser.add_argument('-S',
'--split-groups',
action='store_true',
help='Split channel groups into separate files.')
parser.add_argument(
'-d',
'--dead-channels',
nargs='*',
type=int,
help='List of dead channels. If flag set, these will be set to zero.')
parser.add_argument('-z', '--zero-dead-channels', action='store_true')
parser.add_argument(
'--dry-run',
action='store_true',
help='Do not write data files (but still create prb/prm')
parser.add_argument('-p', "--params", help='Path to .params file.')
parser.add_argument('-D',
"--duration",
type=int,
help='Limit duration of recording (s)')
parser.add_argument('--remove-trailing-zeros', action='store_true')
parser.add_argument('--out_fname_template',
action='store_true',
help='Template for file naming.')
cli_args = parser.parse_args(args)
logger.debug('Arguments: {}'.format(cli_args))
if cli_args.remove_trailing_zeros:
raise NotImplementedError("Can't remove trailing zeros just yet.")
targets = [op.abspath(op.expanduser(t)) for t in cli_args.target]
formats = list(set([util.detect_format(target) for target in targets]))
# Input file format
logger.debug('Inputs found: {}'.format(formats))
format_input = formats[0]
assert len(formats) == 1
logger.debug('Using module: {}'.format(format_input.__name__))
# Output file format
format_output = FORMATS[cli_args.format.lower()]
logger.debug('Output module: {}'.format(format_output.__name__))
# Set up channel layout (channels, references, dead channels) from command line inputs or layout file
# List of bad channels, will be added to channel group dict
dead_channels = cli_args.dead_channels if cli_args.dead_channels is not None else []
# One of channel_count, channel_list, layout_file path from mutex parser group channel_group
layout = None
if cli_args.channel_count is not None:
channel_groups = {
0: {
'channels': list(range(cli_args.channel_count)),
'dead_channels': dead_channels
}
}
elif cli_args.channel_list is not None:
channel_groups = {
0: {
'channels': cli_args.channel_list,
'dead_channels': dead_channels
}
}
elif cli_args.layout is not None:
layout = util.run_prb(op.abspath(op.expanduser(cli_args.layout)))
logger.debug('Opened layout file {}'.format(layout))
if cli_args.split_groups:
channel_groups = layout['channel_groups']
if 'dead_channels' in layout:
if len(dead_channels) and (layout['dead_channels'] !=
dead_channels):
raise ValueError(
'Conflicting bad channel lists: args: {}, layout: {}'.
format(layout['dead_channels'], dead_channels))
dead_channels = layout['dead_channels']
if cli_args.channel_groups:
channel_groups = {
i: channel_groups[i]
for i in cli_args.channel_groups if i in channel_groups
}
else:
channels, dead_channels = util.flat_channel_list(layout)
logger.warning(
'Not splitting groups! Creating new monotonically increasing channel map.'
)
# make a new channel group by merging in the existing ones
channel_groups = {
0: {
'channels': channels,
'dead_channels': dead_channels
}
}
else:
logger.debug(
'No channels given on CLI, will try to get channel number from target later.'
)
channel_groups = None
# Generate configuration from input files found by the format
# This step already checks for the existence of the data files
# and can fail prematurely if the wrong naming template is being used
# This needs more work.
logger.debug('Getting metadata for all targets')
targets_metadata_list = [
format_input.metadata_from_target(t) for t in targets
]
if channel_groups is None:
target_channels = list(
set([ch for t in targets_metadata_list for ch in t['CHANNELS']]))
channel_groups = {
0: {
'channels': target_channels,
'dead_channels': dead_channels
}
}
# Output file path
if cli_args.out_path is None:
out_path = os.getcwd()
logger.info(
'Using current working directory "{}" as output path.'.format(
out_path))
else:
out_path = op.abspath(op.expanduser(cli_args.out_path))
# Create the output path if necessary
if len(out_path) and not op.exists(out_path):
os.mkdir(out_path)
logger.debug('Creating output path {}'.format(out_path))
out_fext = format_output.FMT_FEXT
out_prefix = cli_args.out_prefix if cli_args.out_prefix is not None else op.basename(
cli_args.target[0])
logger.debug('Prefix: {}'.format(out_prefix))
default_template = DEFAULT_FULL_TEMPLATE if cli_args.fname_channels else DEFAULT_SHORT_TEMPLATE
fname_template = default_template if cli_args.template_fname is None else cli_args.template_fname
logger.debug('Filename template: {}'.format(fname_template))
# +++++++++++++++++++++++++++++++++++++++++ MAIN LOOP ++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Iterates over all channel groups, calling continuous_to_dat for each to be bundled together
# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
total_duration_written = 0
for cg_id, channel_group in channel_groups.items():
logger.debug('channel group: {}'.format(channel_group))
# TODO: Check file name length, shorten if > 256 characters
# Possible parameters: outfile prefix [outfile], channel group id [cg_id]
# channel ranges from consecutive channels, for output file naming
crs = util.fmt_channel_ranges(channel_group['channels'])
output_basename = fname_template.format(prefix=out_prefix,
cg_id=cg_id,
crs=crs)
output_fname = ''.join([output_basename, out_fext])
output_file_path = op.join(out_path, output_fname)
duration_written = 0
# First target, file mode is write, after that, append to output file
for file_mode, target_metadata in enumerate(targets_metadata_list):
duration = None if cli_args.duration is None else cli_args.duration - duration_written
target_path = target_metadata['TARGET']
logger.debug(
'Starting conversion for target {}'.format(target_path))
if not cli_args.dry_run and WRITE_DATA:
duration_written += continuous_to_dat(
target_metadata=target_metadata,
output_path=output_file_path,
channel_group=channel_group,
dead_channel_ids=dead_channels,
zero_dead_channels=cli_args.zero_dead_channels,
file_mode='a' if file_mode else 'w',
duration=duration)
total_duration_written += duration_written
# create the per-group .prb files
# FIXME: Dead channels are big mess
with open(op.join(out_path, output_basename + '.prb'), 'w') as prb_out:
if cli_args.split_groups or (layout is None):
# One prb file per channel group
ch_out = channel_group['channels']
cg_out = {0: {'channels': list(range(len(ch_out)))}}
dead_channels = sorted(
[ch_out.index(dc) for dc in dead_channels if dc in ch_out])
else:
# Same channel groups, but with flat numbering
cg_out, dead_channels = util.monotonic_prb(layout)
prb_out.write('dead_channels = {}\n'.format(
pprint.pformat(dead_channels)))
prb_out.write('channel_groups = {}'.format(pprint.pformat(cg_out)))
# FIXME: Generation of .prm
# For now in separate script. Should take a .prm template that will be adjusted
# # Template parameter file
# prm_file_input = cli_args.params
# with open(op.join(out_path, output_basename + '.prm'), 'w') as prm_out:
# if prm_file_input:
# f = open(prm_file_input, 'r')
# prm_in = f.read()
# f.close()
# else:
# prm_in = pkgr.resource_string('config', 'default.prm').decode()
# prm_out.write(prm_in.format(experiment_name=output_basename,
# probe_file=output_basename + '.prb',
# raw_file=output_file_path,
# n_channels=len(channel_group['channels'])))
logger.debug('Done! Total data length written: {}'.format(
util.fmt_time(total_duration_written)))
def __init__(self,
target_path,
n_cols=1,
channels=None,
start=0,
dtype='int16',
*args,
**kwargs):
app.Canvas.__init__(self,
title=target_path,
keys='interactive',
size=(1900, 1000),
position=(0, 0),
app='pyqt5')
self.logger = logging.getLogger(__name__)
# Target configuration (format, sampling rate, sizes...)
self.target_path = target_path
self.logger.debug('Target path: {}'.format(target_path))
self.format = util.detect_format(self.target_path)
self.logger.debug('Target module: {}'.format(self.format))
assert self.format is not None
self.input_dtype = dtype
self.metadata = self._get_target_config(*args, **kwargs)
# TODO: Have .dat format join in on the new format fun...
if 'HEADER' in self.metadata:
self.logger.debug(
'Using legacy .dat file metadata dictionary layout')
self.fs = self.metadata['HEADER']['sampling_rate']
self.input_dtype = self.metadata['DTYPE']
self.n_samples_total = int(self.metadata['HEADER']['n_samples'])
self.n_channels = self.metadata['CHANNELS']['n_channels']
self.block_size = self.metadata['HEADER']['block_size']
elif 'SUBSETS' in self.metadata:
# FIXME: Only traverses first subset.
self.logger.debug('Using new style metadata dictionary layout')
# get number of channels and sampling rate from first subset
first_subset = next(iter(self.metadata['SUBSETS'].values()))
self.fs = first_subset['JOINT_HEADERS']['sampling_rate']
self.n_samples_total = int(
first_subset['JOINT_HEADERS']['n_samples'])
self.n_channels = len(first_subset['FILES'])
self.block_size = first_subset['JOINT_HEADERS']['block_size']
else:
raise ValueError('Unknown metadata format from target.')
self.logger.debug(
'From target: {:.2f} Hz, {} channels, {} samples, dtype={}'.format(
self.fs, self.n_channels, self.n_samples_total,
self.input_dtype))
self.channel_order = channels # if None: no particular order
# 300-6000 Hz Highpass filter
self.filter = util.butter_bandpass(300, 6000, self.fs)
self.apply_filter = False
self.duration_total = util.fmt_time(self.n_samples_total / self.fs)
# Buffer to store all the pre-loaded signals
self.buf = SharedBuffer.SharedBuffer()
self.buffer_length = BUFFER_LENGTH
self.buf.initialize(n_channels=self.n_channels,
n_samples=self.buffer_length,
np_dtype=BUFFER_DTYPE)
# Streamer to keep buffer filled
self.streamer = None
self.stream_queue = Queue()
self.start_streaming()
# Setup up viewport and viewing state variables
# running traces, looks cool, but useless for the most part
self.running = False
self.dirty = True
self.offset = int(start * self.fs / 1024)
self.drag_offset = 0
self.n_cols = int(n_cols)
self.n_rows = int(math.ceil(self.n_channels / self.n_cols))
self.logger.debug('col/row: {}, buffer_length: {}'.format(
(self.n_cols, self.n_rows), self.buffer_length))
# Most of the magic happens in the vertex shader, moving the samples into "position" using
# an affine transform based on number of columns and rows for the plot, scaling, etc.
self.program = gloo.Program(VERT_SHADER, FRAG_SHADER)
self._feed_shaders()
gloo.set_viewport(0, 0, *self.physical_size)
self._timer = app.Timer('auto', connect=self.on_timer, start=True)
gloo.set_state(clear_color='black',
blend=True,
blend_func=('src_alpha', 'one_minus_src_alpha'))
self.show()
