ephy_testing_data/spykingcircus/spykingcircus_example0/recording.params

### Note that depending on the file format selected, the parameters in the data section can vary
### You should refer to the documentation to know what are the needed parameters for a given
### file format. Otherwise, launch the code and a message will tell you what is needed

[data]
file_format    = numpy      # Can be raw_binary, openephys, hdf5, ... See >> spyking-circus help -i for more info
sampling_rate  = 32000.0
stream_mode    = None       # None by default. Can be multi-files, or anything depending to the file format
mapping        = /net/bs-filesvr01/export/group/hierlemann/Temp/Alessio/make_test_sorted_data/sorting_output/spykingcircus/probe.prb         # Mapping of the electrode (see http://spyking-circus.rtfd.ord)
suffix         =            # Suffix to add to generated files
global_tmp     = True       # should be False if local /tmp/ has enough space (better for clusters)
overwrite      = True       # Filter or remove artefacts on site (if write access is possible). Data are duplicated otherwise
parallel_hdf5  = True       # Use the parallel HDF5 feature (if available)

[detection]
radius         = auto       # Radius [in um] (if auto, read from the prb file)
N_t            = 3         # Width of the templates [in ms]
spike_thresh   = 6         # Threshold for spike detection
peaks          = negative         # Can be negative (default), positive or both

[filtering]
cut_off        = 300, auto  # Min and Max (auto=nyquist) cut off frequencies for the band pass butterworth filter [Hz]
filter         = True         # If True, then a low-pass filtering is performed
remove_median  = False      # If True, median over all channels is substracted to each channels (movement artifacts)

[triggers]
trig_file      =            # External stimuli to be considered as putative artefacts [in trig units] (see documentation)
trig_windows   =            # The time windows of those external stimuli [in trig units]
trig_unit      = ms         # The unit in which times are expressed: can be ms or timestep
clean_artefact = False      # If True, external artefacts induced by triggers will be suppressed from data
dead_file      =            # Portion of the signals that should be excluded from the analysis [in dead units]
dead_unit      = ms         # The unit in which times for dead regions are expressed: can be ms or timestep
ignore_times   = False      # If True, any spike in the dead regions will be ignored by the analysis
make_plots     =            # Generate sanity plots of the averaged artefacts [Nothing or None if no plots]

[whitening]
spatial        = True       # Perform spatial whitening
max_elts       = 1000         # Max number of events per electrode (should be compatible with nb_elts)
nb_elts        = 0.8        # Fraction of max_elts that should be obtained per electrode [0-1]
output_dim     = 5          # Can be in percent of variance explain, or num of dimensions for PCA on waveforms

[clustering]
extraction     = median-raw # Can be either median-raw (default) or mean-raw
sub_dim        = 10         # Number of dimensions to keep for local PCA per electrode
max_elts       = 10000         # Max number of events per electrode (should be compatible with nb_elts)
nb_elts        = 0.8        # Fraction of max_elts that should be obtained per electrode [0-1]
nb_repeats     = 3          # Number of passes used for the clustering
smart_search   = True       # Activate the smart search mode
merging_method = nd-bhatta  # Method to perform local merges (distance, dip, folding, nd-folding, bhatta, nd-bhatta)
merging_param  = default    # Merging parameter (see doc) (3 if distance, 0.5 if dip, 1e-3 if folding, 2 if bhatta)
sensitivity    = 3          # Single parameter for clustering sensitivity. The lower the more sensitive
cc_merge       = 0.95       # If CC between two templates is higher, they are merged
dispersion     = (5, 5)     # Min and Max dispersion allowed for amplitudes [in MAD]
make_plots     =            # Generate sanity plots of the clustering [Nothing or None if no plots]

[fitting]
amp_limits     = (0.3, 5)   # Amplitudes for the templates during spike detection [if not auto] (0.3, 5)
amp_auto       = True       # True if amplitudes are adjusted automatically for every templates
collect_all    = False      # If True, one garbage template per electrode is created, to store unfitted spikes
ratio_thresh   = 0.9        # Ratio of the spike_threshold used while fitting [0-1]. The lower the slower

[merging]
cc_overlap     = 0.75       # Only templates with CC higher than cc_overlap may be merged
cc_bin         = 2          # Bin size for computing CC [in ms]
default_lag    = 5          # Default length of the period to compute dip in the CC [ms]
auto_mode      = 0.75         # Between 0 (aggressive) and 1 (no merging). If empty, GUI is launched
remove_noise   = True       # If True, meta merging will remove obvious noise templates (weak amplitudes)
noise_limit    = 0.75       # Amplitude at which templates are classified as noise
sparsity_limit = 0          # Sparsity level (in percentage) for selecting templates as putative noise (in [0, 1])
time_rpv       = 5          # Time [in ms] to consider for Refraction Period Violations (RPV) (0 to disable)
rpv_threshold  = 0.02       # Percentage of RPV allowed while merging
merge_drifts   = True       # Try to automatically merge drifts, i.e. non overlapping spiking neurons
drift_limit    = 1          # Distance for drifts. The higher, the more non-overlapping the activities should be

[converting]
erase_all      = True       # If False, a prompt will ask you to export if export has already been done
export_pcs     = prompt     # Can be prompt [default] or in none, all, some
export_all     = False      # If True, unfitted spikes will be exported as the last Ne templates
sparse_export  = False      # For recent versions of phy, and large number of templates/channels

[validating]
nearest_elec   = auto       # Validation channel (e.g. electrode closest to the ground truth cell)
max_iter       = 200        # Maximum number of iterations of the stochastic gradient descent (SGD)
learning_rate  = 1.0e-3     # Initial learning rate which controls the step-size of the SGD
roc_sampling   = 10         # Number of points to estimate the ROC curve of the BEER estimate
test_size      = 0.3        # Portion of the dataset to include in the test split
radius_factor  = 0.5        # Radius factor to modulate physical radius during validation
juxta_dtype    = uint16     # Type of the juxtacellular data
juxta_thresh   = 6          # Threshold for juxtacellular detection
juxta_valley   = False      # True if juxta-cellular spikes are negative peaks
juxta_spikes   =            # If none, spikes are automatically detected based on juxta_thresh
filter         = True       # If the juxta channel need to be filtered or not
make_plots     = png        # Generate sanity plots of the validation [Nothing or None if no plots]

[extracting]
safety_time    = 1          # Temporal zone around which spikes are isolated [in ms]
max_elts       = 1000       # Max number of collected events per templates
output_dim     = 5          # Percentage of variance explained while performing PCA
cc_merge       = 0.975      # If CC between two templates is higher, they are merged
noise_thr      = 0.8        # Minimal amplitudes are such than amp*min(templates) < noise_thr*threshold

[noedits]
filter_done    = True              #!! AUTOMATICALLY EDITED: DO NOT MODIFY !!
artefacts_done = False      # Will become True automatically after removing artefacts
median_done    = False      # Will become True automatically after removing common median