Hello,
Currently I'm trying to limit the number of spike to be sorted in WaveClus.
To get 39 spike events per one channel, I adjusted the value of 'par.max_spikes_plot = 39;' and 'par.max_spk = 39;' and it doesn't work.
Is there any available options to make it possible?
Below is my WaveClus parameter options. (I have tuned other values for precise spike sorting.)
% LOAD PARAMS
par.segments_length = 5; % length (in minutes) of segments in which the data is cutted (default 5min).
par.sr = 30000; % sampling rate (in Hz). This parameter will be only used if the data file don't have a sr.
% PLOTTING PARAMETERS
par.cont_segment = true;
par.max_spikes_plot = 39; % max. number of spikes to be plotted
par.print2file = true; % If is not true, print the figure (only for batch scripts).
par.cont_plot_samples = 100000; % number of samples used in the one-minute (maximum) sample of continuous data to plot.
par.to_plot_std = 1; % # of std from mean to plot
par.all_classes_ax = 'mean'; % 'mean'/'all'. If it's 'mean' only the mean waveforms will be ploted in the axes with all the classes
par.plot_feature_stats = false;
% SPC PARAMETERS
par.mintemp = 0.00; % minimum temperature for SPC
par.maxtemp = 0.251; % maximum temperature for SPC
par.tempstep = 0.01; % temperature steps
par.SWCycles = 100; % SPC iterations for each temperature (default 100)
par.KNearNeighb = 11; % number of nearest neighbors for SPC
par.min_clus = 30; % minimum size of a cluster (default 60)
par.randomseed = 0; % if 0, random seed is taken as the clock value (default 0)
%par.randomseed = 147; % If not 0, random seed
%par.temp_plot = 'lin'; % temperature plot in linear scale
par.temp_plot = 'log'; % temperature plot in log scale
par.c_ov = 0.7; % Overlapping coefficient to use for the inclusion criterion.
par.elbow_min = 0.4; %Thr_border parameter for regime border detection.
% DETECTION PARAMETERS
par.tmax = 'all'; % maximum time to load
%par.tmax= 180; % maximum time to load (in sec)
par.tmin= 0; % starting time for loading (in sec)
par.w_pre = 20; % number of pre-event data points stored (default 20)
par.w_post = 44; % number of post-event data points stored (default 44))
par.alignment_window = 10; % number of points around the sample expected to be the maximum
par.stdmin = 6; % minimum threshold for detection
par.stdmax = 50; % maximum threshold for detection
par.detect_fmin = 300; % high pass filter for detection
par.detect_fmax = 2000; % low pass filter for detection (default 1000)
par.detect_order = 4; % filter order for detection. 0 to disable the filter.
par.sort_fmin = 300; % high pass filter for sorting
par.sort_fmax = 2000; % low pass filter for sorting (default 3000)
par.sort_order = 2; % filter order for sorting. 0 to disable the filter.
par.ref_ms = 150.0; % detector dead time, minimum refractory period (in ms)
par.detection = 'pos'; % type of threshold ('pos','neg','both')
% par.detection = 'neg';
% par.detection = 'both';
% INTERPOLATION PARAMETERS
par.int_factor = 5; % interpolation factor
par.interpolation = 'y'; % interpolation with cubic splines (default)
% par.interpolation = 'n';
% FEATURES PARAMETERS
par.min_inputs = 10; % number of inputs to the clustering
par.max_inputs = 0.75; % number of inputs to the clustering. if < 1 it will the that proportion of the maximum.
par.scales = 4; % number of scales for the wavelet decomposition
par.features = 'wav'; % type of feature ('wav' or 'pca')
%par.features = 'pca'
% FORCE MEMBERSHIP PARAMETERS
par.template_sdnum = 3; % max radius of cluster in std devs.
par.template_k = 10; % # of nearest neighbors
par.template_k_min = 10; % min # of nn for vote
%par.template_type = 'mahal'; % nn, center, ml, mahal
par.template_type = 'center'; % nn, center, ml, mahal
par.force_feature = 'spk'; % feature use for forcing (whole spike shape)
%par.force_feature = 'wav'; % feature use for forcing (wavelet coefficients).
par.force_auto = true; %automatically force membership (only for batch scripts).
% TEMPLATE MATCHING
par.match = 'y'; % for template matching
%par.match = 'n'; % for no template matching
par.max_spk = 39; % max. # of spikes before starting templ. match.
par.permut = 'y'; % for selection of random 'par.max_spk' spikes before starting templ. match.
% par.permut = 'n'; % for selection of the first 'par.max_spk' spikes before starting templ. match.
% HISTOGRAM PARAMETERS
par.nbins = 100; % # of bins for the ISI histograms
par.bin_step = 1; % percentage number of bins to plot