plateform stringclasses 1
value | repo_name stringlengths 13 113 | name stringlengths 3 74 | ext stringclasses 1
value | path stringlengths 12 229 | size int64 23 843k | source_encoding stringclasses 9
values | md5 stringlengths 32 32 | text stringlengths 23 843k |
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github | xyza11808/MATLAB-master | sagittalSlices.m | .m | MATLAB-master/allenCCF-master/Browsing Functions/sagittalSlices.m | 1,105 | utf_8 | 5be36b230a9720ed29249e9ac3687ca4 |
function [f,h, whichSlice] = sagittalSlices(tv, ccfCoords, f)
if nargin<3
f = figure;
p = get(f, 'Position');
set(f, 'Position', [p(1) p(2) 1597 700]);
set(f, 'Color', 'k');
slicesExist = false;
else
slicesExist = true;
end
slicePoints = 0.25:0.25:3.0; %mm
bregma = allenCCFbre... |
github | xyza11808/MATLAB-master | AtlasTransformBrowser.m | .m | MATLAB-master/allenCCF-master/Browsing Functions/AtlasTransformBrowser.m | 53,464 | utf_8 | f8ecdec397a9435aa47ac603a9b67c6d | function f = allenAtlasBrowser(f, templateVolume, annotationVolume, structureTree, slice_figure, save_location, save_suffix, plane)
% ------------------------------------------------
% Browser for the allen atlas ccf data in matlab.
% ------------------------------------------------
%
% Inputs templateVolume, annotatio... |
github | xyza11808/MATLAB-master | HistologyCropper.m | .m | MATLAB-master/allenCCF-master/Histology Functions/HistologyCropper.m | 4,439 | utf_8 | c35653c00fba7ed8c64d59b68b2ba4b3 | function HistologyCropper(histology_figure, save_folder, image_file_names, reference_size, save_file_name, use_already_downsampled_image)
% set up histology figure
ud_histology.file_num = 1;
ud_histology.num_files = length(image_file_names);
ud_histology.slice_num = ones(length(image_file_names),1);
ud_histology.save_... |
github | xyza11808/MATLAB-master | SliceFlipper.m | .m | MATLAB-master/allenCCF-master/Histology Functions/SliceFlipper.m | 7,857 | utf_8 | 52cdeaba9791844aa003a698e16d6dac | function SliceFlipper(slice_figure, folder_processed_images, reference_size)
% crop, sharpen, and flip slice images
processed_images = dir([folder_processed_images filesep '*tif']);
ud.processed_image_names = natsortfiles({processed_images.name});
ud.total_num_files = size(processed_images,1); disp(['found ' num2str(u... |
github | xyza11808/MATLAB-master | HistologyBrowser.m | .m | MATLAB-master/allenCCF-master/Histology Functions/HistologyBrowser.m | 6,443 | utf_8 | a32b38d3dc2e73f79df5e7be800b38aa | function HistologyBrowser(histology_figure, save_folder, image_folder, image_file_names, folder_processed_images, image_file_are_individual_slices, ...
use_already_downsampled_image, microns_per_pixel, microns_per_pixel_after_downsampling, gain)
% display image and set up user controls for contrast cha... |
github | xyza11808/MATLAB-master | applyCARtoDat.m | .m | MATLAB-master/spikes-master/preprocessing/applyCARtoDat.m | 1,860 | utf_8 | 3bd79728bd4d3de571f8efe113750fc4 |
function medianTrace = applyCARtoDat(filename, nChansTotal, outputDir)
% Subtracts median of each channel, then subtracts median of each time
% point.
%
% filename should include the extension
% outputDir is optional, by default will write to the directory of the input file
%
% should make chunk size as big as poss... |
github | xyza11808/MATLAB-master | extractMedianWFs.m | .m | MATLAB-master/spikes-master/preprocessing/extractMedianWFs.m | 1,766 | utf_8 | 0e7943bc3113db2f00eb8f7476492a71 |
function medWFs = extractMedianWFs(clu, st, Fs, datPath, dataType, dataSize, chanMap, gain)
% medWFs = extractMedianWFs(clu, st, cids, cgs, Fs, datPath, dataType, dataSize, chanMap, gain)
%
% - medWFs [nClusters, nChannels, nSamples] will be median waveforms of
% every cluster represented in clu
% -- note: if you... |
github | xyza11808/MATLAB-master | applyCorrection.m | .m | MATLAB-master/spikes-master/preprocessing/applyCorrection.m | 253 | utf_8 | 2b83703b2c329ba39402319ea6f08e40 |
function outData = applyCorrection(inData, b)
% function outData = applyCorrection(inData, b)
%
% align a timeseries according to correction factors ("b") made with
% companion function "makeCorrection"
outData = [inData(:) ones(size(inData(:)))]*b;
|
github | xyza11808/MATLAB-master | xml2struct.m | .m | MATLAB-master/spikes-master/preprocessing/xml2struct.m | 6,773 | utf_8 | 0194599f7bac6b67c42391f372b5ff91 | function [ s ] = xml2struct( file )
%Convert xml file into a MATLAB structure
% [ s ] = xml2struct( file )
%
% A file containing:
% <XMLname attrib1="Some value">
% <Element>Some text</Element>
% <DifferentElement attrib2="2">Some more text</Element>
% <DifferentElement attrib3="2" attrib4="1">Even more text</Dif... |
github | xyza11808/MATLAB-master | extractSyncChannel.m | .m | MATLAB-master/spikes-master/preprocessing/extractSyncChannel.m | 346 | utf_8 | b1cbecfb5fffe117a1537a0762c38bbe |
function syncDat = extractSyncChannel(folder, numChans, syncChanIndex)
% extraChanIndices are 1-indexed
dataFiles = dir(fullfile(folder,'*.lf.bin'));
for d = 1:length(dataFiles)
filename = fullfile(folder, dataFiles(d).name);
syncDat = extractSyncChannelFromFile(filename, numChans, syncChanIndex);
... |
github | xyza11808/MATLAB-master | spikeGLXdigitalParse.m | .m | MATLAB-master/spikes-master/preprocessing/spikeGLXdigitalParse.m | 1,326 | utf_8 | fb7a98c4253a58e883878e44211c3cb9 |
function eventTimes = spikeGLXdigitalParse(digitalChannel, Fs)
% function eventTimes = spikeGLXdigitalParse(digitalChannel, Fs)
%
% returns the event times of all 16 digital inputs recorded by SpikeGLX
% They are returned in a length=16 cell array. Each cell has three cells,
% which contain the times of all events (so... |
github | xyza11808/MATLAB-master | readSpikeGLXmeta.m | .m | MATLAB-master/spikes-master/preprocessing/readSpikeGLXmeta.m | 2,586 | utf_8 | 948def0d1296138f402899f709a5ec26 |
function S = readSpikeGLXmeta(vcFname)
% function S = readSpikeGLXmeta(vcFname)
%
% returns a struct containing the contents of a SpikeGLX-generated .meta
% file.
%
% From James Jun, 2016-12-31
S = [];
viRef_imec3 = [37 76 113 152 189 228 265 304 341 380];
% Read file
if nargin < 1
[FileName,PathName,FilterInde... |
github | xyza11808/MATLAB-master | loadSync.m | .m | MATLAB-master/spikes-master/preprocessing/loadSync.m | 1,996 | utf_8 | 61ccc3b5af32b6e5d6a3fb3685655462 |
function [syncData, detectedFlips, eventTimes] = loadSync(mouseName, thisDate, tag)
%function syncData = loadSync(mouseName, thisDate, tag)
%
% load the sync channel data from a phase3 probe recorded with spikeglx
% rootE = dat.expPath(mouseName, thisDate, 1, 'main', 'master');
% root = fileparts(rootE);
root = getR... |
github | xyza11808/MATLAB-master | extractSyncChannelFromFile.m | .m | MATLAB-master/spikes-master/preprocessing/extractSyncChannelFromFile.m | 1,052 | utf_8 | c8588810ad7c986c0fe782055fde3a79 |
function syncDat = extractSyncChannelFromFile(filename, numChans, syncChanIndex)
% extraChanIndices are 1-indexed
maxReadSize = 1e9;
d = dir(filename);
[folder,fn] = fileparts(filename);
syncFname = fullfile(folder, [fn '_sync.dat']);
fidOut = fopen(syncFname, 'w');
fprintf(1,' loading %s\n', filename);
fid = f... |
github | xyza11808/MATLAB-master | makeCorrection.m | .m | MATLAB-master/spikes-master/preprocessing/makeCorrection.m | 1,536 | utf_8 | b35a195ab14568c7267b5db883afd15e |
function [corrFun, b] = makeCorrection(correctTo, correctFrom, makePlots)
% function [corrFun, b] = makeCorrection(correctTo, correctFrom, makePlots)
%
% make a function that linearly predicts correctTo from correctFrom, both vectors of same
% length
% - now can attempt to fit for cases with vectors of different lengt... |
github | xyza11808/MATLAB-master | totalMinDiffs.m | .m | MATLAB-master/spikes-master/preprocessing/helpers/totalMinDiffs.m | 334 | utf_8 | e65d70ab3e6063dadd1a19310d7440b8 |
function t = totalMinDiffs(b, predictTo, predictFrom)
myPred = [predictFrom(:) ones(size(predictFrom(:)))]*b;
md = findMinDiffs(myPred, predictTo).^2;
% throw away the worst N where N is the number of excess elements in the
% longer vector
mds = sort(md);
md = mds(1:min(length(predictTo), length(predictFrom)));
... |
github | xyza11808/MATLAB-master | findMinDiffs.m | .m | MATLAB-master/spikes-master/preprocessing/helpers/findMinDiffs.m | 751 | utf_8 | a6ad33605c6399bc369bb3c5af61cab4 |
function d = findMinDiffs(A, B)
%function d = findMinDiffs(A, B)
% from https://uk.mathworks.com/matlabcentral/answers/79466-find-minimum-difference-between-matrices
%
% finds the entry in B which is closest to each entry in A and return the
% distance
B = sort(B(:)); %make B vector and sort for binning conveni... |
github | xyza11808/MATLAB-master | splitGLXBinFile.m | .m | MATLAB-master/spikes-master/preprocessing/imecPhase3/splitGLXBinFile.m | 1,455 | utf_8 | ce7da65be94517debf654deff7a55a78 |
function splitGLXBinFile(filename, nChansTotal, subNames, subRanges, downsampleFactors, varargin)
% for opt4:
% splitGLXBinFile(filename,553,{'AP', 'LFP', 'sync'}, {1:276,277:552,553}, [1 10 10])
% for opt1,2,3:
% splitGLXBinFile(filename,769,{'AP', 'LFP', 'sync'}, {1:384,385:768,769}, [1 10 10])
%
% Exclude the '.b... |
github | xyza11808/MATLAB-master | makeForPRBimecP3.m | .m | MATLAB-master/spikes-master/preprocessing/imecPhase3/makeForPRBimecP3.m | 569 | utf_8 | d9d6de23b6bad7329af6fbd31df22d67 |
function [chanMap, chanMap0ind, xcoords, ycoords, connected, shankInd] = makeForPRBimecP3(opt)
if opt==4
nCh = 276;
refList = [37 76 113 152 189 228 265];
else
nCh = 384;
refList = [37 76 113 152 189 228 265 304 341 380];
end
chanMap = (1:nCh)';
chanMap0ind = chanMap-1;
connected = true(size(chanMap... |
github | xyza11808/MATLAB-master | extractSyncChan.m | .m | MATLAB-master/spikes-master/preprocessing/imecPhase3/extractSyncChan.m | 593 | utf_8 | acb8c6255a7063d0f9d09764a40bbcfe |
function syncData = extractSyncChan(lfpFilename)
% syncData = function extractSyncChan(lfpFilename)
%
% extracts the synchronization channel from a neuropixels phase3 data file
% assumes it is channel 385 out of 385, and that data type is int16
[path, fname, ext] = fileparts(lfpFilename);
syncOut = fullfile(path, [f... |
github | xyza11808/MATLAB-master | writeToParamsPy.m | .m | MATLAB-master/spikes-master/preprocessing/phyHelpers/writeToParamsPy.m | 559 | utf_8 | 5bc988a593d63fdc1411fb855db1cef9 |
function writeToParamsPy(filename, fieldName, value)
% function writeToParamsPy(filename, fieldName, value)
% write a row in a params.py file. Will append to the end.
if isstr(value)
value = ['''' value '''']; % add a single quote on both sides
elseif value==true
value = 'True';
elseif value==false;
valu... |
github | xyza11808/MATLAB-master | sparsePCs.m | .m | MATLAB-master/spikes-master/preprocessing/phyHelpers/sparsePCs.m | 1,690 | utf_8 | 5ad65067d07103fc2d362c6ae735f113 |
function S = sparsePCs(pcFeat,pcFeatInd, spikeTemplates, varargin)
%function S = sparsePCs(pdFeat,pcFeatInd, spikeTemplates[, nPCsPerChan, nPCchans])
% make a sparse matrix version of the pc features
% - nPCsPerChan is the number of PCs per channel to keep, usually 3 (but use
% fewer for memory reasons)
% - nPCchans ... |
github | xyza11808/MATLAB-master | addGainToParamsPy.m | .m | MATLAB-master/spikes-master/preprocessing/phyHelpers/addGainToParamsPy.m | 903 | utf_8 | ddbaea31afad77fdf2ea8689df9d40d3 |
function addGainToParamsPy(ksDir, rawDir)
paramsFn = fullfile(ksDir, 'params.py');
p = loadParamsPy(paramsFn);
if ~isfield(p, 'gain')
[~, rawFn] = fileparts(p.dat_path);
if strcmp(rawFn(end-3:end), '_CAR')
metaFn = [rawFn(1:end-4) '.meta'];
else
metaFn = [rawFn '.meta'];
end
metaPa... |
github | xyza11808/MATLAB-master | loadAllKsDir.m | .m | MATLAB-master/spikes-master/preprocessing/phyHelpers/loadAllKsDir.m | 1,598 | utf_8 | 122176e5c8447ff1fd4fb82652fa5583 |
function sp = loadAllKsDir(mouseName, thisDate)
% function sp = loadAllKsDir(mouseName, thisDate)
% load all the spikes from a day into one struct, aligning them to each
% other
root = getRootDir(mouseName, thisDate);
alignDir = fullfile(root, 'alignments');
[tags, hasEphys] = getEphysTags(mouseName, thisDate);
... |
github | xyza11808/MATLAB-master | writeBordersCSV.m | .m | MATLAB-master/spikes-master/preprocessing/phyHelpers/writeBordersCSV.m | 261 | utf_8 | 29e8e99ca826cbd9d23cab021f4194bd |
function writeBordersCSV(borders, fn)
fid = fopen(fn, 'w');
fprintf(fid, 'area\tlowerBorder\tupperBorder\r\n');
fn = fields(borders);
for f = 1:length(fn)
fprintf(fid, '%s\t%d\t%d\r\n', fn{f}, borders.(fn{f})(1), borders.(fn{f})(2));
end
fclose(fid); |
github | xyza11808/MATLAB-master | loadParamsPy.m | .m | MATLAB-master/spikes-master/preprocessing/phyHelpers/loadParamsPy.m | 1,511 | utf_8 | 9cea31b53624c87a878a46868135dea0 |
function S = loadParamsPy(fn)
% Loads a phy-style "params.py" into a matlab struct. The params.py is
% python code but just a series of assignments, so most of it will run
% directly in matlab
%
% now based on text2struct from James Jun, 2016-12-31, modified slightly by
% N. Steinmetz.
fid = fopen(fn, 'r');
mcFileM... |
github | xyza11808/MATLAB-master | readClusterGroupsCSV.m | .m | MATLAB-master/spikes-master/preprocessing/phyHelpers/readClusterGroupsCSV.m | 668 | utf_8 | ef027ef1778d6a73b430333d65109f5d |
function [cids, cgs] = readClusterGroupsCSV(filename)
%function [cids, cgs] = readClusterGroupsCSV(filename)
% cids is length nClusters, the cluster ID numbers
% cgs is length nClusters, the "cluster group":
% - 0 = noise
% - 1 = mua
% - 2 = good
% - 3 = unsorted
fid = fopen(filename);
C = textscan(fid, '%s%s');
fcl... |
github | xyza11808/MATLAB-master | getMetaFname.m | .m | MATLAB-master/spikes-master/preprocessing/phyHelpers/getMetaFname.m | 590 | utf_8 | f74190b5e26efa07ca861d4381dc37ac |
function fn = getMetaFname(ksDir, rawDir, type)
% function fn = getMetaFname(ksDir, rawDir, type)
%
% type is either 'LFP', or 'AP'
% expects that params.py is in ksDir, and
paramsFn = fullfile(ksDir, 'params.py');
p = loadParamsPy(paramsFn);
[~, rawFn] = fileparts(p.dat_path);
if strcmp(rawFn(end-3:end), '_CAR')
... |
github | xyza11808/MATLAB-master | sparsePCsTopPC.m | .m | MATLAB-master/spikes-master/preprocessing/phyHelpers/sparsePCsTopPC.m | 650 | utf_8 | 48b00c06cf299af62fcdc5bcd608d050 |
function S = sparsePCsTopPC(pcFeat,pcFeatInd, spikeTemplates)
%function S = sparsePCs(pdFeat,pcFeatInd)
% make a sparse matrix version of the pc features
% for the moment, only the top PC
nPCchans = size(pcFeat,3);
nSpikes = size(pcFeat,1);
nTemplates = size(pcFeatInd,1);
nChannels = double(max(pcFeatInd(:))+1);
th... |
github | xyza11808/MATLAB-master | loadKSdir.m | .m | MATLAB-master/spikes-master/preprocessing/phyHelpers/loadKSdir.m | 2,608 | utf_8 | 23dd1b40a75ce6dd5b14862b8c30e9e4 |
function spikeStruct = loadKSdir(ksDir, varargin)
if ~isempty(varargin)
params = varargin{1};
else
params = [];
end
if ~isfield(params, 'excludeNoise')
params.excludeNoise = true;
end
if ~isfield(params, 'loadPCs')
params.loadPCs = false;
end
% load spike data
spikeStruct = loadParamsPy(fullfile(k... |
github | xyza11808/MATLAB-master | writePhyTSV.m | .m | MATLAB-master/spikes-master/preprocessing/phyHelpers/writePhyTSV.m | 1,001 | utf_8 | 9c872b07c51de72a79ccc1cc68fab0a1 |
function writePhyTSV(ksDir, labelName, cids, vals)
% function writePhyTSV(ksDir, labelName, cids, vals)
% Writes a .tsv file that phy can read to apply a new sortable column in cluster
% view. E.g. calculate the amplitude of every template and use this to
% write a .tsv file that will allow you to sort by that amplit... |
github | xyza11808/MATLAB-master | sparseNoiseRF.m | .m | MATLAB-master/spikes-master/analysis/sparseNoiseRF.m | 6,174 | utf_8 | d45e3bcb027ab378b5574e6c88e3c682 |
function [rfMap, stats, allPSTH, spikeCounts] = sparseNoiseRF(spikeTimes, stimTimes, stimPositions, params)
% function [rfmap, stats] = sparseNoiseRF(spikeTimes, stimTimes, stimPositions, params)
%
% Assumes that stimPositions describe a rectangle and are evenly spaced.
%
% - spikeTimes is nSpikes x 1
% - stimTimes i... |
github | xyza11808/MATLAB-master | rocArea.m | .m | MATLAB-master/spikes-master/analysis/rocArea.m | 1,211 | utf_8 | 55f2ffb2d6bd6cb600003e8d24b88566 |
function [rocOut, tpr, fpr] = rocArea(values1, values2)
% function [rocOut, tpr, fpr] = rocArea(values1, values2)
%
% "values2" should have the larger mean, if you want it to return a value
% greater than 0.5.
if isempty(values1) && isempty(values2)
rocOut = NaN;
tpr = [];
fpr = [];
return;
end
% ... |
github | xyza11808/MATLAB-master | psthAndBA.m | .m | MATLAB-master/spikes-master/analysis/psthAndBA.m | 1,502 | utf_8 | 098ce93397e7b11a160c6018f1bbf6fc |
function [psth, bins, rasterX, rasterY, spikeCounts, binnedArray] = psthAndBA(spikeTimes, eventTimes, window, psthBinSize)
% function [psth, bins, rasterX, rasterY, spikeCounts, binnedArray] = psthAndBA(spikeTimes, eventTimes, window, psthBinSize)
%
% Fast computation of psth and spike counts in a window relative to ... |
github | xyza11808/MATLAB-master | ksDriftmap.m | .m | MATLAB-master/spikes-master/analysis/ksDriftmap.m | 4,051 | utf_8 | 54363ded01dc21757bd173bd6da59216 | % Inputs/outputs: mostly self explanatory
% localizedSpikesOnly (false by default) - if true, only spikes with no discrepancy between depth and site are returned.
function [spikeTimes, spikeAmps, spikeDepths, spikeSites] = ksDriftmap(ksDir, localizedSpikesOnly)
if nargin < 2
localizedSpikesOnly = false;
end
clear... |
github | xyza11808/MATLAB-master | templatePositionsAmplitudes.m | .m | MATLAB-master/spikes-master/analysis/templatePositionsAmplitudes.m | 3,474 | utf_8 | 27d6732c4874d96669721bdf6f4e7574 |
function [spikeUnscaledAmps, spikeDepths, templateDepths, tempAmps, tempsUnW, templateDuration, waveforms] = templatePositionsAmplitudes(temps, winv, ycoords, spikeTemplates, tempScalingAmps)
% function [spikeAmps, spikeDepths, templateDepths, tempAmps, tempsUnW, templateDuration, waveforms] = templatePositionsAmplitu... |
github | xyza11808/MATLAB-master | computeSpikeWidths.m | .m | MATLAB-master/spikes-master/analysis/computeSpikeWidths.m | 1,034 | utf_8 | 0593c1a293fded49b4fa7a59caa3801d |
function [spikeWidths, tempWidths, clusterWidths] = computeSpikeWidths(tempsUnW, spikeTemplates, varargin)
% function [spikeWidths, tempWidths, clusterWidths] = computeSpikeWidths(tempsUnW, spikeTemplates[, clu])
% Computes spike widths in samples, according to widths of each template
% If you pass clu, will also com... |
github | xyza11808/MATLAB-master | makeAllBA.m | .m | MATLAB-master/spikes-master/analysis/makeAllBA.m | 2,320 | utf_8 | 9cf003966c347d57bc0edccbbc1b10fa |
function [allba, bins] = makeAllBA(st, clu, eventTimes, binSize, win)
binBorders = win(1):binSize:win(2);
numBins = length(binBorders)-1;
bins = binBorders(1:end-1)+binSize/2;
% now using histdiffMulti.
clu = clu-min(clu)+1; % make sure they are all positive
cIDs = unique(clu); nC = numel(cIDs);
clu = clu(st>min(... |
github | xyza11808/MATLAB-master | slidingChoiceProbability.m | .m | MATLAB-master/spikes-master/analysis/slidingChoiceProbability.m | 1,512 | utf_8 | bf87fd0d7450b09595f5edaf705c4918 |
function [cp, t, rs] = slidingChoiceProbability(ba, baBinSize, cpBinSize, trLabels)
% function [cp, t, rs] = slidingChoiceProbability(ba, baBinSize, cpBinSize, trLabels)
% Choice probability (i.e. area under ROC curve between spike counts in a
% bin) using a sliding window. Input argument "ba" is a "binnedArray" from... |
github | xyza11808/MATLAB-master | myACG.m | .m | MATLAB-master/spikes-master/analysis/myACG.m | 2,472 | utf_8 | a4f981a2020b2efadda994bb43b43503 |
function [xLin, nLin, xLog, nLog] = myACG(st, axLin, axLog)
% function [xLin, nLin, xLog, nLog] = myACG(st, axLin, axLog)
%
% Computes an autocorrelogram with both linear and log bins
%
% axLin and axLog are optional but if provided will produce a plot in each
binSize = 0.0005;
b = 0.0001:binSize:1; % start at a te... |
github | xyza11808/MATLAB-master | timestampsToBinned.m | .m | MATLAB-master/spikes-master/analysis/timestampsToBinned.m | 967 | utf_8 | 5c2ac0a6185b9f402f9c1fc855e223fe |
function [binArray, binCenters] = timestampsToBinned(timeStamps, referencePoints, binSize, window)
% [binArray, binCenters] = timestampsToBinned(timeStamps, referencePoints, binSize,
% window)
%
% Returns an array of binned spike counts. If you use a large enough
% binSize, it may well be possible that there is more... |
github | xyza11808/MATLAB-master | trueSpikeSNR.m | .m | MATLAB-master/spikes-master/analysis/trueSpikeSNR.m | 3,546 | utf_8 | f63c1d91084de7ab6f62f280d1fd3313 |
function snr = trueSpikeSNR(datPars, spikeTimes)
% todo:
% - dim reduce then reconstruct the waveform with some svd, to avoid
% getting a false boost from overfitting best would be cross-validating
% (i.e. for each spike use only the mean determined from the other
% spikes). Could do this by subtracting the spike o... |
github | xyza11808/MATLAB-master | psthByDepth.m | .m | MATLAB-master/spikes-master/analysis/psthByDepth.m | 1,519 | utf_8 | 72aaaae1e8dd9072c6955a646bd2b878 |
function [timeBins, depthBins, allP, normVals] = psthByDepth(spikeTimes, spikeDepths, depthBinSize, timeBinSize, eventTimes, win, bslWin, varargin)
% function [timeBins, depthBins, allP] = psthByDepth(spikeTimes, ...
% spikeDepths, depthBinSize, timeBinSize, eventTimes, win, bslWin[, bslEvents])
%
% Computes PSTH s... |
github | xyza11808/MATLAB-master | computeRawRMS.m | .m | MATLAB-master/spikes-master/analysis/computeRawRMS.m | 1,112 | utf_8 | 677e4c505c9b60a5fbd8c5c3f8c45195 |
function [rmsPerChannel, madPerChannel] = computeRawRMS(ksDir, gainFactor, rawDir)
% function [rmsPerChannel, madPerChannel] = computeRawRMS(ksDir, gain[, rawDir])
%
% for spikeglx: gainFactor = 0.6/512/gainSetting*1e6;
%
% ksDir is directory of kilosort results
% gainFactor will multiply the raw data
% rawDir is l... |
github | xyza11808/MATLAB-master | lfpBandPower.m | .m | MATLAB-master/spikes-master/analysis/lfpBandPower.m | 1,796 | utf_8 | d420ca92c9414f6fa8465c84f41bce30 |
function [lfpByChannel, allPowerEst, F, allPowerVar] = lfpBandPower(lfpFilename, lfpFs, nChansInFile, freqBand)
% function [lfpByChannel, allPowerEst, F] = lfpBandPower(lfpFilename, lfpFs, nChansInFile, freqBand)
% Computes the power in particular bands, and across all frequencies, across the recording
% samples 10 s... |
github | xyza11808/MATLAB-master | eventLockedAvg.m | .m | MATLAB-master/spikes-master/analysis/eventLockedAvg.m | 2,450 | utf_8 | 56190afe22e31c1a8e8ea7d44057d4bd |
function [avgPeriEventV, winSamps, periEventV, sortedLabels] = eventLockedAvg(V, t, eventTimes, eventLabels, calcWin)
% function [avgPeriEventV, periEventV] = eventLockedAvg(V, t, eventTimes, eventLabels, calcWin)
%
% Inputs:
% - V: nTraces x nTimePoints
% - t: 1 x nTimePoints, the time points of each sample in V
% -... |
github | xyza11808/MATLAB-master | clusterAverage.m | .m | MATLAB-master/spikes-master/analysis/clusterAverage.m | 926 | utf_8 | 70028b183792bf538953450a17460200 |
function clusterQuantity = clusterAverage(clu, spikeQuantity)
% function clusterQuantity = clusterAverage(clu, spikeQuantity)
%
% get the average of some quantity across spikes in each cluster, given the
% quantity for each spike
%
% e.g.
% > clusterDepths = clusterAverage(clu, spikeDepths);
%
% clu and spikeQuantit... |
github | xyza11808/MATLAB-master | readDat.m | .m | MATLAB-master/spikes-master/analysis/readDat.m | 650 | utf_8 | aa98bab7a806b0490908a0ab44907cb5 |
function dat = readDat(filename, numChans, varargin)
% takes the same amount of time to read through for just one channel, but
% you don't run into memory problems that way if the file is too big.
requestedChan = [];
if ~isempty(varargin)
requestedChan = varargin{1};
end
fid = fopen(filename);
if isempty(requ... |
github | xyza11808/MATLAB-master | spikeTrigLFP.m | .m | MATLAB-master/spikes-master/analysis/spikeTrigLFP.m | 1,365 | utf_8 | 5637d904b608166154eb4300295bcc36 |
function mnLFP = spikeTrigLFP(tLFP, lfpdat, theseST, winAroundSpike)
% function mnLFP = spikeTrigLFP(tLFP, lfpdat, theseST, winAroundSpike)
%
% returns nChannels x nTimePoints mean spike-triggered LFP.
%
% Inputs:
% - tLFP - 1 x nLFP - vector of time points at which the lfp was sampled
% (s)
% - lfpdat - nChannels x... |
github | xyza11808/MATLAB-master | kilosortPredictData.m | .m | MATLAB-master/spikes-master/analysis/kilosortPredictData.m | 3,343 | utf_8 | 473c3f39bf0267cfba72f7c83be9ff83 |
function predData = kilosortPredictData(predictSamps, temps, spikeTimes, ...
spikeTemplates, spikeAmps, invWhiteMat)
% function predData = kilosortPredictData(predictSamps, temps, spikeTimes, ...
% spikeTemplates, spikeAmps, invWhiteMat)
%
% Given kilosort output, determine what kilosort thought the raw data
... |
github | xyza11808/MATLAB-master | replaceMissingSitesP3.m | .m | MATLAB-master/spikes-master/analysis/replaceMissingSitesP3.m | 772 | utf_8 | 12f8f37e0b6bd3909ff6b0a691747809 |
function [newData, newXC, newYC] = replaceMissingSitesP3(data, xc, yc)
sigma = 20;
data = data(:);
missingXC = repmat([43 27]', 5, 1);
missingYC = [1:10]'*380;
missingData = zeros(size(missingXC));
for m = 1:length(missingXC)
x = missingXC(m); y = missingYC(m);
dists = sqrt((x-xc).^2+(y-yc).^2)... |
github | xyza11808/MATLAB-master | findTempForEachClu.m | .m | MATLAB-master/spikes-master/analysis/findTempForEachClu.m | 1,303 | utf_8 | fb87b0c525ab8e593b84f27364efdb66 |
function tempPerClu = findTempForEachClu(clu, spikeTemplates)
% function tempPerClu = findTempForEachClu(clu, spikeTemplates)
%
% determine which template "corresponds to" each cluster, meaning, which
% template is most represented for each cluster
%
% output:
% - tempPerClu: a vector such that tempPerClu(clusterID) =... |
github | xyza11808/MATLAB-master | schmittTimes.m | .m | MATLAB-master/spikes-master/analysis/helpers/schmittTimes.m | 413 | utf_8 | a83c51d12ed8ff9d30f61f64025f62bf |
function [flipTimes, flipsUp, flipsDown] = schmittTimes(t, sig, thresh)
% function [flipTimes, flipsUp, flipsDown] = schmittTimes(t, sig, thresh)
%
% thresh is [low high]
t = t(:); % make column
sig = sig(:);
schmittSig = schmitt(sig, thresh);
flipsDown = t(schmittSig(1:end-1)==1 & schmittSig(2:end)==-1);
flipsUp ... |
github | xyza11808/MATLAB-master | eventTrigTrace.m | .m | MATLAB-master/spikes-master/analysis/helpers/eventTrigTrace.m | 1,054 | utf_8 | 6fe7b638d9eae86c06ee4bec2adbea6e |
function [mn, stdErr, winSamps, allTraces] = eventTrigTrace(traceT, trace, eventTimes, win, varargin)
% function [mn, stdev, allTraces] = eventTrigTrace(traceT, trace, eventTimes, win[, ops])
%
% ops.Fs allows you to pick a different timescale of the average than of
% the original trace, otherwise will use from the o... |
github | xyza11808/MATLAB-master | myGaussWin.m | .m | MATLAB-master/spikes-master/analysis/helpers/myGaussWin.m | 271 | utf_8 | 3447340e9925cf4cc755e1cfc9e3be15 |
function gw = myGaussWin(stdev, Fs)
% function gw = myGaussWin(stdev, Fs)
% A gaussian window with specified stdev in units relative to the sampling
% frequency, and normalized in amplitude
stdevSamps = round(stdev*Fs);
gw = gausswin(stdevSamps*6,3);
gw = gw./sum(gw);
|
github | xyza11808/MATLAB-master | countUnique.m | .m | MATLAB-master/spikes-master/analysis/helpers/countUnique.m | 192 | utf_8 | 06818fad678f6ec59a82bb54144b9885 |
function [values,instances] = countUnique(x)
% function [values,instances] = countUnique(x)
y = sort(x(:));
p = find([true;diff(y)~=0;true]);
values = y(p(1:end-1));
instances = diff(p); |
github | xyza11808/MATLAB-master | simpleWFplot.m | .m | MATLAB-master/spikes-master/visualization/simpleWFplot.m | 556 | utf_8 | 10ee3b90280d9227e25c46dd8129d85b |
function simpleWFplot(wf, coords, nWFtoPlot)
wf = wf(:,20:end-5);
wfAmps = max(wf')-min(wf');
[~,maxCh] = max(wfAmps);
chDists = ((coords(maxCh,1)-coords(:,1)).^2+(coords(maxCh,2)-coords(:,2)).^2).^0.5;
[~,nearestCh] = sort(chDists);
for n = 1:nWFtoPlot
plot((0:size(wf,2)-1)*0.4+coords(nearestCh(n),1), ...
... |
github | xyza11808/MATLAB-master | plotAsPhase3.m | .m | MATLAB-master/spikes-master/visualization/plotAsPhase3.m | 1,641 | utf_8 | 58f44d4b7b20fa3f5e061b21d5e7bdf2 |
function plotMat = plotAsPhase3(data,xc, yc)
% data is a vector of length nChans
[data, xc, yc] = replaceMissingSitesP3(data, xc, yc);
data = data(:); % is column now
% turn xc into inds
uxc = unique(xc);
for u = 1:length(uxc)
xc(xc==uxc(u))=u;
end
% turn yc into inds - here *assuming* a regular scale
% ycDiff... |
github | xyza11808/MATLAB-master | eventsAlignedRasters.m | .m | MATLAB-master/spikes-master/visualization/eventsAlignedRasters.m | 1,781 | utf_8 | 8db424b3e6de5771977e9ae58b0e4802 |
function eventsAlignedRasters(spikeTimes, eventTimes, eventNames, windows)
% function eventsAlignedRasters(eventTimes, spikeTimes, eventNames, windows)
%
% plots rasters of the spikes aligned to each of multiple events, with
% relative times of the other events indicated.
% - spikeTimes is a vector
% - other three ar... |
github | xyza11808/MATLAB-master | quickMovieSpikes.m | .m | MATLAB-master/spikes-master/visualization/quickMovieSpikes.m | 612 | utf_8 | 5caddfca1733f13dfcfbcd70e4764c45 |
function quickMovieSpikes(mouseName, thisDate, tag, type)
% determine which timeline to use
% load spikes
expPath = dat.expPath(mouseName, thisDate, expNum, 'main', 'master');
% load traces
load(dat.expFilePath(mouseName, thisDate, expNum, 'Timeline', 'master'));
traces = prepareTimelineTraces(Timeline);
% loa... |
github | xyza11808/MATLAB-master | quickMovieSpikesALF.m | .m | MATLAB-master/spikes-master/visualization/quickMovieSpikesALF.m | 3,162 | utf_8 | 5c95b840bafca6a1f34ade35a0915a68 |
function quickMovieSpikesALF(mouseName, thisDate, expNum, tag, type)
root = fileparts(dat.expPath(mouseName, thisDate, 1, 'main', 'master'));
alfDir = fullfile(root, 'alf');
% load traces
traceNames = {'eye.area', 'lickSignal.trace', 'wheel.velocity'};
for tInd = 1:length(traceNames)
tr = readNPY(fullfile(alf... |
github | xyza11808/MATLAB-master | plotAsProbe.m | .m | MATLAB-master/spikes-master/visualization/plotAsProbe.m | 837 | utf_8 | 9969548b81a054e0d743db2d4dbbd5d6 |
function plotAsProbe(data, xc, yc, cm, sqSizeX, sqSizeY)
% data is vector, same lenght as xc and yc
% cm is colormap, size [n x 3]
%
% other usage: if data is empty and cm's first dimension is the same length
% as xc and yc, then use those colors literally
sqCoordsX = [-sqSizeX/2 sqSizeX/2 sqSizeX/2 -sqSizeX/2];
sqC... |
github | xyza11808/MATLAB-master | plotWaveform.m | .m | MATLAB-master/spikes-master/visualization/plotWaveform.m | 763 | utf_8 | 449be20bd4a4ddd9d74ed0b4f5b4f442 |
function plotWaveform(wf, xcoords, ycoords, xScale, yScale, thresh, color, varargin)
% wf is nChan x nTimePoints
% color must be 3-element vector
if ~isempty(thresh)
chanAmps = max(wf,[],2)-min(wf, [], 2);
maxAmp = max(chanAmps);
inclChans = chanAmps>maxAmp*thresh;
else
inclChans = true(size(xcoords)... |
github | xyza11808/MATLAB-master | evRastersGUI.m | .m | MATLAB-master/spikes-master/visualization/evRastersGUI.m | 25,805 | utf_8 | fa13c6c19bdaa9a687bd6ff3cf080677 |
function f = evRastersGUI(st, clu, cweA, cwtA, moveData, lickTimes, anatData)
% function evRastersGUI(st, clu, cweA, cwtA, moveData, lickTimes, anatData)
%
% Displays rasters and PSTHs for individual units in the choiceworld task
%
% Inputs:
% - st - vector of spike times
% - clu - vector of cluster identities
% - cw... |
github | xyza11808/MATLAB-master | rasterAndPSTHbyCond.m | .m | MATLAB-master/spikes-master/visualization/rasterAndPSTHbyCond.m | 1,868 | utf_8 | 5f82d5bd49df439aa231c953e88c71eb |
function rasterAndPSTHbyCond(st, evTimes, evGroups, win, sm, colors, axR, axP)
% sm is smoothing window size in sec
% axR and axP are axes for rasters and psth's
%% - compute psths
binSize = 0.0005;
[~,ii] = sort(evTimes);
[~,revii] = sort(ii);
[~, bins, ~, ~, ~, ba] = psthAndBA(...
st, evTimes, win+[-0.1 0.1], ... |
github | xyza11808/MATLAB-master | popRasterViewer.m | .m | MATLAB-master/spikes-master/visualization/popRasterViewer.m | 15,595 | utf_8 | 795baaa4c10451fbb710391f84da7cfa |
function popRasterViewer(sp, eventData, traces, auxVid, pars)
%
% Viewer for ephys data collected during the task
%
% Displays:
% - Rasters from multiple probes
% -- Can make raster y-axis into cluster identity (sorted by depth) or probe depth
% -- Can make raster colorization be different things, like depth or spike
... |
github | xyza11808/MATLAB-master | movieWithTracesSpikes.m | .m | MATLAB-master/spikes-master/visualization/movieWithTracesSpikes.m | 15,392 | utf_8 | 4bb5108701cd64afe75cfcc5f441d023 |
% todo
% - implement pixel traces
% - implement version with raster
% - smoothing
% - normalization
% - implement 'g' for go to specific time
function movieWithTracesSpikes(spikeTimes, spikeClu, traces, auxVid, anatData, pars)
% function movieWithTracesSpikes(spikeTimes, spikeClu, traces, auxVid, pars)
% - spikeTime... |
github | xyza11808/MATLAB-master | psthViewer.m | .m | MATLAB-master/spikes-master/visualization/psthViewer.m | 9,581 | utf_8 | 563aa5e55edffb74208cde799cd889a9 |
function psthViewer(spikeTimes, clu, eventTimes, window, trGroups)
% function psthViewer(spikeTimes, clu, eventTimes, window, trGroups)
%
% Controls:
% - c: dialog box to pick a new cluster ID number
% - t: toggle showing psth traces for each grouping variable or just the
% overall. If showing just overall, raster is... |
github | xyza11808/MATLAB-master | eventsAlignedRasters2.m | .m | MATLAB-master/spikes-master/visualization/eventsAlignedRasters2.m | 1,339 | utf_8 | 09bab6ce1c6257f6fbfb2495104d0ff4 |
function [bins, ba] = eventsAlignedRasters2(st, eventTimes, trOrder, thisWindow, otherEvents, axRaster, axPSTH)
if isempty(trOrder)
trOrder = 1:numel(eventTimes);
end
psthBinSize = 0.0001;
smoothWinStd = 0.01;
smoothWin = myGaussWin(smoothWinStd, 1/psthBinSize);
nTimes = length(eventTimes);
windowExp = thisWind... |
github | xyza11808/MATLAB-master | plotDriftmap.m | .m | MATLAB-master/spikes-master/visualization/plotDriftmap.m | 4,296 | utf_8 | a7339aa90aa6ac6de66f302a4547d9bd | % Inputs: spikeTimes, spikeAmps, spikeYpos - names self explanatory
% opt - optional, empty by default; 'mark' - will mark detected drifts, 'show' - will generate a different plot,
% where only large spikes are used, and the detection of drift locations is demonstrated
function plotDriftmap(spike... |
github | xyza11808/MATLAB-master | eventsAlignedRastersWithGrouping.m | .m | MATLAB-master/spikes-master/visualization/eventsAlignedRastersWithGrouping.m | 2,836 | utf_8 | 6b7e3b616077c1162fdd719497d5d3a0 |
function eventsAlignedRastersWithGrouping(spikeTimes, eventTimes, params)
% function eventsAlignedRasters(eventTimes, spikeTimes, params)
%
% plots rasters of the spikes aligned to each of multiple events, with
% relative times of the other events indicated.
% - spikeTimes is a vector
% - eventTimes is cell arrays, o... |
github | xyza11808/MATLAB-master | computeWFampsOverDepth.m | .m | MATLAB-master/spikes-master/visualization/computeWFampsOverDepth.m | 491 | utf_8 | 356f75ca41432ec41dfed3bc5da8a850 |
function [pdfs, cdfs] = computeWFampsOverDepth(spikeAmps, spikeDepths, ampBins, depthBins, recordingDur)
nDbins = length(depthBins)-1;
nAbins = length(ampBins)-1;
pdfs = zeros(nDbins, nAbins);
cdfs = zeros(nDbins, nAbins);
for b = 1:length(depthBins)-1
h = histc(spikeAmps(spikeDepths>depthBins(b) & spikeDepths<=... |
github | xyza11808/MATLAB-master | makepretty.m | .m | MATLAB-master/spikes-master/visualization/helpers/makepretty.m | 575 | utf_8 | 903e10baa38a3689472896dd1281f20c |
function makepretty()
% set some graphical attributes of the current axis
set(get(gca, 'XLabel'), 'FontSize', 17);
set(get(gca, 'YLabel'), 'FontSize', 17);
set(gca, 'FontSize', 13);
set(get(gca, 'Title'), 'FontSize', 20);
ch = get(gca, 'Children');
for c = 1:length(ch)
thisChild = ch(c);
if strcmp('line',... |
github | xyza11808/MATLAB-master | colorcet.m | .m | MATLAB-master/spikes-master/visualization/helpers/colorcet.m | 510,830 | utf_8 | d8ee688a2a1354d858c757af2ef10600 | % COLORCET - Perceptually uniform color maps
%
% Usage 1: Generate a colour map and apply it to the current figure.
% >> colorcet(name);
%
% Usage 2: Return a colour map and its description.
% >> [map, descriptorname, description] = colorcet(name);
%
% Usage 3: Get a list of all possible colour maps.
% >> colorcet
%... |
github | xyza11808/MATLAB-master | rasterize.m | .m | MATLAB-master/spikes-master/visualization/helpers/rasterize.m | 404 | utf_8 | 82661f868e21d94797f5b97a00f7b144 |
function [xOut, yOut] = rasterize(timeStamps, varargin)
%function [xOut, yOut] = rasterize(timeStamps[, minVal, maxVal])
if ~isempty(varargin)
minVal = varargin{1};
maxVal = varargin{2};
else
minVal = 0;
maxVal = 1;
end
xOut = nan(1,length(timeStamps)*3);
xOut(1:3:end) = timeStamps;
xOut(2:3:end) =... |
github | xyza11808/MATLAB-master | computeAndPlotWFampHist.m | .m | MATLAB-master/spikes-master/visualization/+ks/computeAndPlotWFampHist.m | 2,038 | utf_8 | b71f8337e9ba00c1663efbcf811b20bb |
function [pdfs, cdfs, ampBins, depthBins] = computeAndPlotWFampHist(ksDir, varargin)
% function [pdfs, cdfs, ampBins, depthBins] = computeAndPlotWFampHist(kilosortDirectory[, ampBins, depthBins])
if ~isempty(varargin)
ampBins = varargin{1};
depthBins = varargin{2};
else
ampBins = [];
depthBins = [];
... |
github | xyza11808/MATLAB-master | sphere_sampling.m | .m | MATLAB-master/sometoolbox/toolbox_alpert/sphere_sampling.m | 4,270 | utf_8 | 266924d242f54957933e749b7181ba5c | function [Points,L,diam,topcol,botcol] = sphere_sampling(N,lrounded,angles,mrounded,ipl)
% sphere_sampling - sample points on a sphere.
%
% [Points,L,diam] = sphere_sampling(N,lrounded,angles,mrounded,ipl)
% $Revision: 1.1 $ Paul Leopardi 2003-10-13
% Make angles=1 the default
% $Revision: 1.1 $ Paul Leopardi ... |
github | xyza11808/MATLAB-master | load_signal.m | .m | MATLAB-master/sometoolbox/toolbox_alpert/toolbox/load_signal.m | 11,947 | utf_8 | db55dbee0917dfa39660ddb07583f1e6 | function y = load_signal(name, n, options)
% load_signal - load a 1D signal
%
% y = load_signal(name, n, options);
%
% name is a string that can be :
% 'regular' (options.alpha gives regularity)
% 'step', 'rand',
% 'gaussiannoise' (options.sigma gives width of filtering in pixels),
% [natural signals]
% 't... |
github | xyza11808/MATLAB-master | load_image.m | .m | MATLAB-master/sometoolbox/toolbox_alpert/toolbox/load_image.m | 20,337 | utf_8 | 68382a18d724933d0ab0372f752ed2cc | function M = load_image(type, n, options)
% load_image - load benchmark images.
%
% M = load_image(name, n, options);
%
% name can be:
% Synthetic images:
% 'chessboard1', 'chessboard', 'square', 'squareregular', 'disk', 'diskregular', 'quaterdisk', '3contours', 'line',
% 'line_vertical', 'line_horiz... |
github | xyza11808/MATLAB-master | perform_farthest_point_sampling.m | .m | MATLAB-master/sometoolbox/toolbox_fast_marching/perform_farthest_point_sampling.m | 3,253 | utf_8 | 271c5c1557a202369b41332981b02b64 | function [points,D] = perform_farthest_point_sampling( W, points, npoints, options )
% perform_farthest_point_sampling - samples points using farthest seeding strategy
%
% points = perform_farthest_point_sampling( W, points, npoints );
%
% points can be [] or can be a (2,npts) matrix of already computed
% sam... |
github | xyza11808/MATLAB-master | perform_farthest_point_sampling_mesh.m | .m | MATLAB-master/sometoolbox/toolbox_fast_marching/perform_farthest_point_sampling_mesh.m | 1,797 | utf_8 | 3e863c0d0d0a4b012240b09688d4c8ef | function [points,D] = perform_farthest_point_sampling_mesh( vertex,faces, points, nbr_iter, options )
% perform_farthest_point_sampling - samples points using farthest seeding strategy
%
% [points,D] = perform_farthest_point_sampling_mesh( vertex,faces, points, nbr_iter, options );
%
% points can be [] or can be a (... |
github | xyza11808/MATLAB-master | divgrad.m | .m | MATLAB-master/sometoolbox/toolbox_fast_marching/divgrad.m | 1,749 | utf_8 | 531f368d44593d78a30eea65ad3a8134 | function G = divgrad(M,options)
% divgrad - compute either gradient or divergence.
%
% G = divgrad(M);
%
% if M is a 2D array, compute gradient,
% if M is a 3D array, compute divergence.
% Use centered finite differences.
%
% Copyright (c) 2007 Gabriel Peyre
options.null = 0;
if size(M,3)==2
G = mydiv(... |
github | xyza11808/MATLAB-master | compute_voronoi_triangulation.m | .m | MATLAB-master/sometoolbox/toolbox_fast_marching/compute_voronoi_triangulation.m | 2,806 | utf_8 | 6ed546707daebe1eb6f945f8834ceb61 | function faces = compute_voronoi_triangulation(Q, vertex)
% compute_voronoi_triangulation - compute a triangulation
%
% face = compute_voronoi_triangulation(Q);
%
% Q is a Voronoi partition function, computed using
% perform_fast_marching.
% face(:,i) is the ith face.
%
% Works in 2D and in 3D.
%
% Cop... |
github | xyza11808/MATLAB-master | vol3d.m | .m | MATLAB-master/sometoolbox/toolbox_fast_marching/vol3d.m | 5,700 | utf_8 | d4c8aeec81bea6ff37ed75bb28e20663 | function [model] = vol3d(varargin)
%H = VOL3D Volume render 3-D data.
% VOL3D uses the orthogonal plane 2-D texture mapping technique for
% volume rending 3-D data in OpenGL. Use the 'texture' option to fine
% tune the texture mapping technique. This function is best used with
% fast OpenGL hardware.
%
% H = vol3d('... |
github | xyza11808/MATLAB-master | compute_geodesic_mesh.m | .m | MATLAB-master/sometoolbox/toolbox_fast_marching/compute_geodesic_mesh.m | 4,234 | utf_8 | f3e2ddf4b7d47f9f8d9226288e74c5d7 | function [path,vlist,plist] = compute_geodesic_mesh(D, vertex, face, x, options)
% compute_geodesic_mesh - extract a discrete geodesic on a mesh
%
% [path,vlist,plist] = compute_geodesic_mesh(D, vertex, face, x, options);
%
% D is the set of geodesic distances.
%
% path is a 3D curve that is the shortest path st... |
github | xyza11808/MATLAB-master | load_image.m | .m | MATLAB-master/sometoolbox/toolbox_fast_marching/toolbox/load_image.m | 18,777 | utf_8 | 46b5ed29e3aa2b0736eb6fb78a3ed113 | function M = load_image(type, n, options)
% load_image - load benchmark images.
%
% M = load_image(name, n, options);
%
% name can be:
% Synthetic images:
% 'chessboard1', 'chessboard', 'square', 'squareregular', 'disk', 'diskregular', 'quaterdisk', '3contours', 'line',
% 'line_vertical', 'line_horiz... |
github | xyza11808/MATLAB-master | check_face_vertex.m | .m | MATLAB-master/sometoolbox/toolbox_fast_marching/toolbox/check_face_vertex.m | 630 | utf_8 | 5112ad0482fa3700123a6c770f8eb622 | function [vertex,face] = check_face_vertex(vertex,face, options)
% check_face_vertex - check that vertices and faces have the correct size
%
% [vertex,face] = check_face_vertex(vertex,face);
%
% Copyright (c) 2007 Gabriel Peyre
vertex = check_size(vertex);
face = check_size(face);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
f... |
github | xyza11808/MATLAB-master | perform_dr_spingarn.m | .m | MATLAB-master/sometoolbox/toolbox_optim/perform_dr_spingarn.m | 1,205 | utf_8 | 22a1d91cc8116c7c7255f83c6faba8a7 | function [x,R] = perform_dr_spingarn(x, ProxF, options)
% perform_dr_spingarn - Douglas Rachford algorithm for the sum of >=2 functions
%
% [x,R] = perform_dr_spingarn(x,ProxF,options);
%
% Solves
% min_x sum_i F_i(x)
% where F_i are proper convex functions, with an easy to compute
% proximal mapping.
%... |
github | xyza11808/MATLAB-master | perform_wavortho_transf.m | .m | MATLAB-master/sometoolbox/toolbox_optim/toolbox/perform_wavortho_transf.m | 2,618 | utf_8 | 916e69c67df707f99eb83398091ff107 | function f = perform_wavortho_transf(f,Jmin,dir,options)
% perform_wavortho_transf - compute orthogonal wavelet transform
%
% fw = perform_wavortho_transf(f,Jmin,dir,options);
%
% You can give the filter in options.h.
%
% Works in arbitrary dimension.
%
% Copyright (c) 2009 Gabriel Peyre
options.null = 0;
h =... |
github | xyza11808/MATLAB-master | load_image.m | .m | MATLAB-master/sometoolbox/toolbox_optim/toolbox/load_image.m | 20,769 | utf_8 | 1e7385317f656bdec8213321748edab7 | function M = load_image(type, n, options)
% load_image - load benchmark images.
%
% M = load_image(name, n, options);
%
% name can be:
% Synthetic images:
% 'chessboard1', 'chessboard', 'square', 'squareregular', 'disk', 'diskregular', 'quaterdisk', '3contours', 'line',
% 'line_vertical', 'line_horiz... |
github | xyza11808/MATLAB-master | load_signal.m | .m | MATLAB-master/sometoolbox/toolbox_signal/load_signal.m | 11,947 | utf_8 | db55dbee0917dfa39660ddb07583f1e6 | function y = load_signal(name, n, options)
% load_signal - load a 1D signal
%
% y = load_signal(name, n, options);
%
% name is a string that can be :
% 'regular' (options.alpha gives regularity)
% 'step', 'rand',
% 'gaussiannoise' (options.sigma gives width of filtering in pixels),
% [natural signals]
% 't... |
github | xyza11808/MATLAB-master | perform_kmeans.m | .m | MATLAB-master/sometoolbox/toolbox_signal/perform_kmeans.m | 15,346 | utf_8 | 18099d3ffa3630eef50cad1030080937 | function [B,seeds,E] = perform_kmeans(X,nbCluster,options)
% perform_kmeans - perform the k-means clustering algorithm.
%
% [B,seeds] = perform_kmeans(X,nbCluster,options);
%
% 'X' is a [d,n] matrix where d is the dimension of the space
% and n is the number of points (that live in R^d).
% 'nbCluster' is t... |
github | xyza11808/MATLAB-master | perform_dct_transform.m | .m | MATLAB-master/sometoolbox/toolbox_signal/perform_dct_transform.m | 7,750 | utf_8 | 07f7ce84cf4f6dfc91ad645a17eab05c | function y = perform_dct_transform(x,dir)
% perform_dct_transform - discrete cosine transform
%
% y = perform_dct_transform(x,dir);
%
% Copyright (c) 2006 Gabriel Peyre
if size(x,1)==1 || size(x,2)==1
% 1D transform
if dir==1
y = dct(x);
else
y = idct(x);
end
else
if dir==1
... |
github | xyza11808/MATLAB-master | compute_skewness.m | .m | MATLAB-master/sometoolbox/toolbox_signal/compute_skewness.m | 2,307 | utf_8 | d2c1ae20ba7df193f8d0fbc04183a069 | function s = compute_skewness(x,center_mean)
% compute_skewness compute the Skewness.
% returns the sample skewness of the values in X. For a
% vector input, S is the third central moment of X, divided by the cube
% of its standard deviation. For a matrix input, S is a row vector
% containing the sample ske... |
github | xyza11808/MATLAB-master | compute_kurtosis.m | .m | MATLAB-master/sometoolbox/toolbox_signal/compute_kurtosis.m | 2,413 | utf_8 | 787c7a07ebed6e9c2396228b98b42bae | function k = compute_kurtosis(x, center_mean)
%compute_kurtosis - compute the Kurtosis.
%
% returns the sample kurtosis of the values in X. For a
% vector input, K is the fourth central moment of X, divided by fourth
% power of its standard deviation. For a matrix input, K is a row vector
% containing the sa... |
github | xyza11808/MATLAB-master | compute_histogram_distance.m | .m | MATLAB-master/sometoolbox/toolbox_signal/compute_histogram_distance.m | 1,926 | utf_8 | 8d2e4fb98f34f913571462dc3fec7fe2 | function D = compute_histogram_distance(H, options)
% compute_histogram_distance - compute distance between histograms
%
% D = compute_histogram_distance(H, options);
%
% H(:,i) is the ith histogram.
% D(i,g) is the distance between histogram i and j.
%
% options.histmetric is the metric used to compute the distan... |
github | xyza11808/MATLAB-master | compute_histogram_rbf.m | .m | MATLAB-master/sometoolbox/toolbox_signal/compute_histogram_rbf.m | 2,360 | utf_8 | db90055f55a69747e4b061c873ac0365 | function h = compute_histogram_rbf(f, sigma, x, options)
% compute_histogram_rbf - parzen windows density estimation
%
% h = compute_histogram_rbf(f, sigma, x);
%
% f is the signal, h is an estimate of the histogram,
% where h(i) is the density of the estimation around value x(i).
%
% sigma is the bandwidth u... |
github | xyza11808/MATLAB-master | compute_distance_matrix.m | .m | MATLAB-master/sometoolbox/toolbox_signal/compute_distance_matrix.m | 2,221 | utf_8 | f3352ca2f82567aeeb83e8713deb91f5 | function dist = compute_distance_matrix(X,x)
% compute_distance_matrix - compute pairwise distance matrix.
%
% D = compute_distance_matrix(X);
% or
% D = compute_distance_matrix(X,x, metric);
% (set x=X)
%
% We have D(i,j)=|X(:,i)-x(:,j)|^2.
%
% Copyright (c) 2004 Gabriel Peyre
[D,N] = size(X);
try
... |
github | xyza11808/MATLAB-master | mad.m | .m | MATLAB-master/sometoolbox/toolbox_signal/mad.m | 7,680 | utf_8 | 1fff5e4e7dffd038def5d5f2dfbdf111 | function y = mad(x,flag)
%MAD Mean/median absolute deviation.
% Y = MAD(X) returns the mean absolute deviation of the values in X. For
% vector input, Y is MEAN(ABS(X-MEAN(X)). For a matrix input, Y is a row
% vector containing the mean absolute deviation of each column of X. For
% N-D arrays, MAD operates ... |
github | xyza11808/MATLAB-master | perform_moment_equalization.m | .m | MATLAB-master/sometoolbox/toolbox_signal/perform_moment_equalization.m | 11,438 | utf_8 | 56f1977353f73c1b7af33015235c9826 | function x = perform_moment_equalization(x,y,numdim, options)
% perform_kurtosis_equalization - equalize moments of order 1,2,3,4.
%
% x = perform_moment_equalization(x,y,numdim,options);
%
% (numdim=1 by default).
%
% Equalizes the mean, variance, skewness and kurtosis.
% Set options.xx=0 to avoid equalizing ... |
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