def unit_spike_trains():
return glia.read_spyking_results("tests/data/gratings.result.hdf5", sampling_rate())
def unit_spike_trains():
return glia.read_spyking_results("tests/data/gratings.result.hdf5",
sampling_rate())
def analyze(ctx,
filename,
trigger,
threshold,
eyecandy,
ignore_extra=False,
fix_missing=False,
output=None,
notebook=None,
configuration=None,
verbose=False,
debug=False,
processes=None,
by_channel=False,
integrity_filter=0.0,
analog_idx=1,
default_channel_map=False,
dev=False):
"""Analyze data recorded with eyecandy.
This command/function preprocesses the data & aligns stimuli to ephys
recording.
"""
print("version 0.5.1")
init_logging(filename, processes, verbose, debug)
#### FILEPATHS
logger.debug(str(filename) + " " + str(os.path.curdir))
if not os.path.isfile(filename):
try:
filename = glia.match_filename(filename, "txt")
except:
filename = glia.match_filename(filename, "bxr")
data_directory, data_name = os.path.split(filename)
name, extension = os.path.splitext(data_name)
analog_file = os.path.join(data_directory, name + '.analog')
if not os.path.isfile(analog_file):
# use 3brain analog file
analog_file = os.path.join(data_directory, name + '.analog.brw')
stimulus_file = os.path.join(data_directory, name + ".stim")
ctx.obj = {"filename": os.path.join(data_directory, name)}
print(f"Analyzing {name}")
if configuration != None:
with open(configuration, 'r') as f:
user_config = yaml.safe_load(f)
config.user_config = user_config
if "analog_calibration" in user_config:
config.analog_calibration = user_config["analog_calibration"]
if "notebook" in user_config:
notebook = user_config["notebook"]
if "eyecandy" in user_config:
eyecandy = user_config["eyecandy"]
if "processes" in user_config:
processes = user_config["processes"]
if "integrity_filter" in user_config:
integrity_filter = user_config["integrity_filter"]
if "by_channel" in user_config:
by_channel = user_config["by_channel"]
if not notebook:
notebook = glia.find_notebook(data_directory)
lab_notebook = glia.open_lab_notebook(notebook)
logger.info(name)
experiment_protocol = glia.get_experiment_protocol(lab_notebook, name)
flicker_version = experiment_protocol["flickerVersion"]
#### LOAD STIMULUS
try:
metadata, stimulus_list, method = glia.read_stimulus(stimulus_file)
ctx.obj["stimulus_list"] = stimulus_list
ctx.obj["metadata"] = metadata
# assert method=='analog-flicker'
except:
print(
"No .stim file found. Creating from .analog file.".format(trigger))
if flicker_version == 0.3:
metadata, stimulus_list = glia.create_stimuli(
analog_file, stimulus_file, notebook, name, eyecandy,
analog_idx, ignore_extra, config.analog_calibration, threshold)
ctx.obj["stimulus_list"] = stimulus_list
ctx.obj["metadata"] = metadata
print('finished creating .stim file')
elif trigger == "ttl":
raise ValueError('not implemented')
else:
raise ValueError("invalid trigger: {}".format(trigger))
# look for .frames file
try:
lab_notebook_notype = glia.open_lab_notebook(notebook,
convert_types=False)
protocol_notype = glia.get_experiment_protocol(lab_notebook_notype,
name)
date_prefix = os.path.join(data_directory,
protocol_notype['date'].replace(':', '_'))
frames_file = date_prefix + "_eyecandy_frames.log"
video_file = date_prefix + "_eyecandy.mkv"
frame_log = pd.read_csv(frames_file)
frame_log = frame_log[:-1] # last frame is not encoded for some reason
ctx.obj["frame_log"] = frame_log
ctx.obj["video_file"] = video_file
except Exception as e:
extype, value, tb = sys.exc_info()
traceback.print_exc()
print(e)
ctx.obj["frame_log"] = None
ctx.obj["video_file"] = None
print("Attempting to continue without frame log...")
#### LOAD SPIKES
spyking_regex = re.compile('.*\.result.hdf5$')
eye = experiment_protocol['eye']
experiment_n = experiment_protocol['experimentNumber']
date = experiment_protocol['date'].date().strftime("%y%m%d")
retina_id = date + '_R' + eye + '_E' + experiment_n
if extension == ".txt":
ctx.obj["units"] = glia.read_plexon_txt_file(filename, retina_id,
channel_map)
elif extension == ".bxr":
if default_channel_map:
channel_map_3brain = config.channel_map_3brain
else:
channel_map_3brain = None
ctx.obj["units"] = glia.read_3brain_spikes(filename,
retina_id,
channel_map_3brain,
truncate=dev)
elif re.match(spyking_regex, filename):
ctx.obj["units"] = glia.read_spyking_results(filename)
else:
raise ValueError(
'could not read {}. Is it a plexon or spyking circus file?')
#### DATA MUNGING OPTIONS
if integrity_filter > 0.0:
good_units = solid.filter_units_by_accuracy(ctx.obj["units"],
ctx.obj['stimulus_list'],
integrity_filter)
filter_good_units = glia.f_filter(lambda u, v: u in good_units)
ctx.obj["units"] = filter_good_units(ctx.obj["units"])
if by_channel:
ctx.obj["units"] = glia.combine_units_by_channel(ctx.obj["units"])
# prepare_output
plot_directory = os.path.join(data_directory, name + "-plots")
config.plot_directory = plot_directory
os.makedirs(plot_directory, exist_ok=True)
os.chmod(plot_directory, 0o777)
if output == "pdf":
logger.debug("Outputting pdf")
ctx.obj["retina_pdf"] = PdfPages(
glia.plot_pdf_path(plot_directory, "retina"))
ctx.obj["unit_pdfs"] = glia.open_pdfs(plot_directory,
list(ctx.obj["units"].keys()),
Unit.name_lookup())
# c connotes 'continuation' for continuation passing style
ctx.obj["c_unit_fig"] = partial(glia.add_to_unit_pdfs,
unit_pdfs=ctx.obj["unit_pdfs"])
ctx.obj["c_retina_fig"] = lambda x: ctx.obj["retina_pdf"].savefig(x)
elif output == "png":
logger.debug("Outputting png")
ctx.obj["c_unit_fig"] = glia.save_unit_fig
ctx.obj["c_retina_fig"] = glia.save_retina_fig
os.makedirs(os.path.join(plot_directory, "00-all"), exist_ok=True)
for unit_id in ctx.obj["units"].keys():
name = unit_id
os.makedirs(os.path.join(plot_directory, name), exist_ok=True)
def analyze(ctx, filename, trigger, threshold, eyecandy, ignore_extra=False,
fix_missing=False, window_height=None, window_width=None, output=None, notebook=None,
calibration=None, distance=None):
"""Analyze data recorded with eyecandy.
"""
ctx.obj = {}
data_directory, data_name = os.path.split(filename)
name, extension = os.path.splitext(data_name)
analog_file = os.path.join(data_directory, name +'.analog')
stimulus_file = os.path.join(data_directory, name + ".stimulus")
spyking_regex = re.compile('.*\.result.hdf5$')
if extension == ".txt":
ctx.obj["units"] = glia.read_plexon_txt_file(filename,filename)
elif re.match(spyking_regex, filename):
ctx.obj["units"] = glia.read_spyking_results(filename)
else:
raise ValueError('could not read {}. Is it a plexon or spyking circus file?')
if not notebook:
notebooks = glob(os.path.join(data_directory, '*.yml')) + \
glob(os.path.join(data_directory, '*.yaml'))
if len(notebooks)==0:
raise ValueError("no lab notebooks (.yml) were found. Either add to directory," \
"or specify file path with -n.")
notebook=notebooks[0]
lab_notebook = glia.open_lab_notebook(notebook)
experiment_protocol = glia.get_experiment_protocol(lab_notebook, name)
flicker_version = experiment_protocol["flickerVersion"]
try:
ctx.obj["stimulus_list"] = glia.load_stimulus(stimulus_file)
except OSError:
print("No .stimulus file found. Attempting to create from .analog file.".format(trigger))
if flicker_version==0.3:
ctx.obj["stimulus_list"] = glia.create_stimulus_list_v0_4(
analog_file, stimulus_file, notebook, name, eyecandy, ignore_extra,
calibration, distance)
elif trigger == "legacy":
ctx.obj["stimulus_list"] = glia.legacy_create_stimulus_list_from_flicker(
analog_file, stimulus_file, notebook, name, eyecandy, ignore_extra, threshold, window_height, window_width)
elif trigger == "flicker":
ctx.obj["stimulus_list"] = glia.create_stimulus_list_from_flicker(
analog_file, stimulus_file, notebook, name, eyecandy, ignore_extra, threshold, fix_missing, window_height, window_width)
elif trigger == "fix":
ctx.obj["stimulus_list"] = glia.alternate_create_stimulus_list_from_flicker(
analog_file, stimulus_file, notebook, name, eyecandy, ignore_extra, threshold, window_height, window_width,
fix_missing=True)
elif trigger == "detect-solid":
ctx.obj["stimulus_list"] = glia.create_stimulus_list_from_SOLID(
analog_file, stimulus_file, notebook, name, eyecandy, ignore_extra, threshold, window_height, window_width)
elif trigger == "ttl":
raise ValueError('not implemented')
else:
raise ValueError("invalid trigger: {}".format(trigger))
# prepare_output
plot_directory = os.path.join(data_directory, name+"-plots")
try:
os.makedirs(plot_directory)
os.chmod(plot_directory, 0o777)
except OSError as exception:
if exception.errno != errno.EEXIST:
raise
if output == "pdf":
ctx.obj["retina_pdf"] = PdfPages(glia.plot_pdf_path(plot_directory, "retina"))
ctx.obj["unit_pdfs"] = glia.open_pdfs(plot_directory, list(ctx.obj["units"].keys()), Unit.name_lookup())
# c connotes 'continuation'
ctx.obj["c_add_unit_figures"] = partial(glia.add_to_unit_pdfs,
unit_pdfs=ctx.obj["unit_pdfs"])
ctx.obj["c_add_retina_figure"] = lambda x: ctx.obj["retina_pdf"].savefig(x)
elif output == "png":
raise ValueError("not implemented")
