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 |
|---|---|---|---|---|---|---|---|---|
github | WagnerLab/ECoG_PPC_RecogMemory-master | groupLPCData2.m | .m | ECoG_PPC_RecogMemory-master/Analysis/groupLPCData2.m | 9,808 | utf_8 | be965f68969965740fee58961908d42e | function data = groupLPCData2(opts)
% groups LPC channel data by subject.
% takes outputs from calcERP or calcERSP
%
% dependencies:
% getBinSamps
% signtest2
% ranksum2
% data parameters
subjects = opts.subjects;
reference = opts.reference;
nRefChans = opts.nRefChans;
lockType = opts.lockT... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | plotHGPTracesByChan.m | .m | ECoG_PPC_RecogMemory-master/Plotting/plotHGPTracesByChan.m | 16,493 | utf_8 | f51cfabd5bad4c7b467fc5e772aa1610 |
function f = plotHGPTracesByChan(data1,data2,opts)
inkscapePath='/Applications/Inkscape.app/Contents/Resources/bin/inkscape';
SupPlotPath = ['~/Google ','Drive/Research/ECoG ','Manuscript/ECoG ', 'Manuscript Figures/supplement/'];
hemChans = ismember(data1.subjChans,find(strcmp(opts.hemId,opts.hem)))';
smooth... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | cMapGenerate.m | .m | ECoG_PPC_RecogMemory-master/Plotting/cMapGenerate.m | 709 | utf_8 | 68ada096194ec2bdcbbb9785cb9076c6 |
function map = cMapGenerate(Colors,levels)
% colors, 3 element vector
% positive color
% negative color
% neutral color
% levels, 4 element vector for linear scaling
% example:
% levels = [-3 -2; 2 2; 2 3];
% implies negColor to neutral and neutral to poscolor
nPoints = 1000;
%nLevels = size(levels,1);
nLe... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | plotSubROI_ERPs.m | .m | ECoG_PPC_RecogMemory-master/Plotting/plotSubROI_ERPs.m | 2,934 | utf_8 | f09a082a16d61d11b3184d60e46e601f |
function plotSubROI_ERPs(data,opts)
close all;
savePath = opts.plotPath;
type = opts.type;
band = opts.band;
measType = opts.measType ;
smoother = opts.smoother;
smootherSpan = opts.smootherSpan;
hemChans = ismember(data.subjChans,find(strcmp(opts.hemId,opts.hems)... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | renderChanWeights.m | .m | ECoG_PPC_RecogMemory-master/Plotting/renderChanWeights.m | 1,872 | utf_8 | d05bda72bee047023ad88dd3f4c2b09d |
function renderChanWeights(data)
% to do make defaults.
chanCoords = data.chanCoords;
weights = data.weights;
cortex = data.cortex;
hem = data.hemisphere;
renderType = data.renderType;
limits = data.limits;
switch renderType
case 'SmoothCh'
ctmr_gauss_plot(gca,cortex,chanCoords,we... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | renderChansFig1.m | .m | ECoG_PPC_RecogMemory-master/Plotting/renderChansFig1.m | 2,647 | utf_8 | 39da04c917e0d3f9abd6aaf2bfa6d313 | function renderChansFig1(data,opts)
%
% dependencies:
% ctmr_gauss_plot
% loc_view
% el_add
% label_add
inkscapePath='/Applications/Inkscape.app/Contents/Resources/bin/inkscape';
HEMS = {'l','r'};
nSubjs = numel(data.options.subjects);
extStr = [];
if opts.ROIColor
extStr = [extStr 'ROIid'];
end
if opts.... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | plotHGPTracesBySubj.m | .m | ECoG_PPC_RecogMemory-master/Plotting/plotHGPTracesBySubj.m | 3,725 | utf_8 | 72f49f7e99606fd653af2c94b12f5aad |
function f = plotHGPTracesBySubj(data1,data2,opts)
inkscapePath='/Applications/Inkscape.app/Contents/Resources/bin/inkscape';
plotPath = ['~/Google ','Drive/Research/ECoG ','Manuscript/ECoG ',... '
'Manuscript Figures/supplement/'];
Pthr = 0.05;
hemChans = ismember(data1.subjChans,find(strcmp(opts.hemId,o... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | renderCortex.m | .m | ECoG_PPC_RecogMemory-master/Plotting/renderCortex.m | 2,721 | utf_8 | 0524718d023de3d75868a75ef9ccff80 | function renderCortex(data,opts)
%
% dependencies:
% ctmr_gauss_plot
% loc_view
% el_add
% label_add
addpath('./Doras_rendering_scripts/render_brains/');
HEMS = {'l','r'};
nSubjs = numel(data.options.subjects);
extStr = [];
if opts.ROIColor
extStr = [extStr 'ROIid'];
end
if opts.subROIColor
extStr ... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | conditionBarPlotsWrapper.m | .m | ECoG_PPC_RecogMemory-master/Plotting/conditionBarPlotsWrapper.m | 1,043 | utf_8 | 673fc8a5f3614c956bbfbc70a2e378a0 |
function conditionBarPlotsWrapper (data, opts)
Bins = (data.Bins(:,1) >= opts.timeLims(1)) & (data.Bins(:,2) <= opts.timeLims(2));
colors = [];
colors{1} = [0.9 0.5 0.1]; % color for condition 1
colors{2} = [0.1 0.8 0.9]; % color for condition 2
ROInums = opts.ROInums; % 1-> IPS, 2-> SPL
hem = o... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | plotHGP_RTcorr.m | .m | ECoG_PPC_RecogMemory-master/Plotting/plotHGP_RTcorr.m | 4,009 | utf_8 | 5ad9ef5e2f5547b36ff39d3045777aff |
function f = plotHGP_RTcorr(data1,data2,opts)
inkscapePath='/Applications/Inkscape.app/Contents/Resources/bin/inkscape';
hemChans = ismember(data1.subjChans,find(strcmp(opts.hemId,opts.hem)))';
rois = {'IPS','SPL'};
chIdx{1} = data1.ROIid==1 & hemChans;
chIdx{2} = data1.ROIid==2 & hemChans;
f(1) = fig... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | plotFigure2.m | .m | ECoG_PPC_RecogMemory-master/Plotting/plotFigure2.m | 4,430 | utf_8 | 8c7c4d88b71af160a54e8faa444034b9 |
function f = plotFigure2(data1,data2,opts)
inkscapePath='/Applications/Inkscape.app/Contents/Resources/bin/inkscape';
hemChans = ismember(data1.subjChans,find(strcmp(opts.hemId,opts.hem)))';
smoother = opts.smoother;
smootherSpan= opts.smootherSpan;
rois = {'IPS','SPL'};
chIdx{1} = data1.ROIid==1 & he... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | plotFigure2a.m | .m | ECoG_PPC_RecogMemory-master/Plotting/plotFigure2a.m | 1,416 | utf_8 | b61fec05790d9c4cf51d17476b5bc6d9 |
function f = plotFigure2a(data1,data2,opts)
hemChans = ismember(data1.subjChans,find(strcmp(opts.hemId,opts.hems)))';
smoother = opts.smoother;
smootherSpan= opts.smootherSpan;
rois = {'IPS','SPL'};
chIdx{1} = data1.ROIid==1 & hemChans;
chIdx{2} = data1.ROIid==2 & hemChans;
f = figure(); clf;
set(g... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | plotHGPTracesFig.m | .m | ECoG_PPC_RecogMemory-master/Plotting/plotHGPTracesFig.m | 5,443 | utf_8 | ed5e8d5b049e96106f7126d61d7b95d8 |
function f = plotHGPTracesFig(data1,data2,opts)
inkscapePath='/Applications/Inkscape.app/Contents/Resources/bin/inkscape';
hemChans = ismember(data1.subjChans,find(strcmp(opts.hemId,opts.hem)))';
smoother = opts.smoother;
smootherSpan= opts.smootherSpan;
rois = {'IPS','SPL'};
subjs = find(strcmp(o... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | conditionBarMultiBandWrapper.m | .m | ECoG_PPC_RecogMemory-master/Plotting/conditionBarMultiBandWrapper.m | 1,907 | utf_8 | f03127e890214caee0e882c0705751da |
function conditionBarMultiBandWrapper (opts)
% plots the average power for each condition per band, for multiple bands.
colors = [];
colors{1} = [0.9 0.5 0.1]; % color for condition 1
colors{2} = [0.1 0.8 0.9]; % color for condition 2
bands = opts.bands;
nBands = numel(bands);
ROInum = opts.ROInums; % 1... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | calc_dPrime.m | .m | ECoG_PPC_RecogMemory-master/lib/calc_dPrime.m | 1,481 | utf_8 | 7415223866eaf7856248883a3df9f7c9 |
function [dPrime c] = calc_dPrime(hits, misses, fa, cr)
% [dPrime c] = calc_dPrime;
% JC 03/01/06
if nargin==0
fprintf('\n');
fprintf(' | YES | NO\n');
fprintf('---|--------------|--------------------\n');
fprintf('S1 | hits | misses\n');
fprintf('S2 | false-alarms | co... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | ts_adaptivezscore.m | .m | ECoG_PPC_RecogMemory-master/lib/ts_adaptivezscore.m | 1,991 | utf_8 | 8d30484d9e5a369166f3283396c310ce | % timeseries adaptive zscoring, for non-stationary signals
function [out,win_mean,win_std] = ts_adaptivezscore(varargin)
% inputs:
% (1) in: (1d vector of samples) input signal
% (2) wl: (# samples) window length in samples
% (3) sld_wl: (# samples) slding window length in samples
%
% outputs:
% (1) out: ... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | glmnet.m | .m | ECoG_PPC_RecogMemory-master/lib/glmnet_matlab/glmnet.m | 12,732 | utf_8 | 8c20f42d4ca1741def17b0bb113f1fd5 | function fit = glmnet(x, y, family, options)
%--------------------------------------------------------------------------
% glmnet.m: fit an elasticnet model path
%--------------------------------------------------------------------------
%
% DESCRIPTION:
% Fit a regularization path for the elasticnet at a grid of v... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | glmnetPlot.m | .m | ECoG_PPC_RecogMemory-master/lib/glmnet_matlab/glmnetPlot.m | 3,485 | utf_8 | 25bef119d3957074e024d7afafff205f | function glmnetPlot( x, xvar, label )
%--------------------------------------------------------------------------
% glmnetPlot.m: plot coefficients from a "glmnet" object
%--------------------------------------------------------------------------
%
% DESCRIPTION:
% Produces a coefficient profile plot fo the coeffic... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | glmnetPredict.m | .m | ECoG_PPC_RecogMemory-master/lib/glmnet_matlab/glmnetPredict.m | 9,332 | utf_8 | c04f049cedcee54c23b88e5d7faba858 | function result = glmnetPredict(object, type, newx, s)
%--------------------------------------------------------------------------
% glmnetPredict.m: make predictions from a "glmnet" object.
%--------------------------------------------------------------------------
%
% DESCRIPTION:
% Similar to other predict metho... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | cvglmnet2.m | .m | ECoG_PPC_RecogMemory-master/lib/glmnet_matlab/cvglmnet2.m | 4,902 | utf_8 | 1248ae954ea03a4fdd507a037b8b77b6 | function CVerr = cvglmnet2(x,y,nfolds,foldid,type,family,options,verbous)
% Do crossvalidation of glmnet model. The coordinate descent algorithm
% chooses a set of lambda to optimize over based on the input given in
% the options struct.Parameter tuning should be done in such a way that for
% a fixed alpha, a set of la... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | validation_function.m | .m | ECoG_PPC_RecogMemory-master/lib/libsvm-3.11/validation_function.m | 2,393 | utf_8 | cf03840c63d5971b9c1d550a2053a10a | function ret = validation_function(dec, labels);
labels = (labels >= 0) - (labels < 0);
valid_function = @(dec, labels) bac(dec, labels);
ret = valid_function(dec, labels);
%precision(dec, labels);
%recall(dec, labels);
%fscore(dec, labels);
%bac(dec, labels);
%auc(dec, labels);
%accuracy(dec, labels);
function ret = ... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | balancedBootStrapIdx.m | .m | ECoG_PPC_RecogMemory-master/Classification/balancedBootStrapIdx.m | 608 | utf_8 | 1f8fb26f3f71a4e830483d439e850527 |
function BootIdxMat = balancedBootStrapIdx(nBoots,nSamples,nF,class1Idx,class2Idx)
% returns a matrix of nSamples X nBoots; each column has the same number of
% class1 labels and class2 labels
nclass1 = numel(class1Idx);
nclass2 = numel(class2Idx);
if nSamples > 2 * min(nclass1,nclass2)
nSamples = 2 * min(nclass1... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | applyDTW_c.m | .m | ECoG_PPC_RecogMemory-master/Classification/applyDTW_c.m | 269 | utf_8 | be73ffaf794b1e8229686514c0c9fa20 |
function out = applyDTW_c(x,Y,w)
% applies dtw_c for x against every row of y using argument w, returns the
% loss vector out of with the same number of rows as Y
out = zeros(size(Y,1),1);
parfor ii = 1:size(Y,1)
out(ii) = dtw_c(x,Y(ii,:),w);
end
return
|
github | WagnerLab/ECoG_PPC_RecogMemory-master | ECoGClassify.m | .m | ECoG_PPC_RecogMemory-master/Classification/ECoGClassify.m | 9,778 | utf_8 | 101c4fa0f3014335a8f37138dddee51d |
function out = ECoGClassify(S)
% some important variables throught the code
% X = all data: training and test
% Y = classification labels
% N = number of trials
% P = number of features / predictors
% nFolds = number of XVal folds
% AG. last update Sept 23, 2013 -- nearest neig... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | SummaryClassification.m | .m | ECoG_PPC_RecogMemory-master/Classification/SummaryClassification.m | 8,417 | utf_8 | 07aa860fb5ffd4ffb5e704bbd78438f7 |
function data = SummaryClassification(data,opts)
% data = SummaryClassification(data,opts)
% function that groups the decoding results
% limits for random chance adjustment;
a= 0.49; b = 0.51;
nBoots = data.classificationParams.nBoots;
nSubjs = 8;
nFeatures = size(data.X,2)*numel(data.opts.bands);
% loa... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | getClassificationParams.m | .m | ECoG_PPC_RecogMemory-master/Classification/getClassificationParams.m | 7,269 | utf_8 | 2541dc03d3839d9f8dd6d5c4c3f659ca |
function params = getClassificationParams(tooboxNum)
% script to set classification parameters
params = [];
params.nFolds = 10; % number of XVal folds
ClassificationToolboxes = {'liblinear','libsvm','glmnet','NNDTW'};
params.toolbox = ClassificationToolboxes{tooboxNum};
params.options ... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | alg_ecogBatch_SS2.m | .m | ECoG_PPC_RecogMemory-master/BehavioralAnalysis/alg_ecogBatch_SS2.m | 6,737 | utf_8 | fd08deebda805cab8544acf5439a7b4c |
function alg_ecogBatch_SS2(subjnum,block,flags,basepath,bef_win,aft_win, overwrite,minfreq,maxfreq)
%
% Usage:
% ecogBatch('02','ST03_bl76','pfcdes');
%
% This batch function will call makeparSubj02AIN.m to generate a
% parameter file for the desired block, parSubj02AIN.mat, and store
% it in the RawData/block direct... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | SS2_analyze_ecog.m | .m | ECoG_PPC_RecogMemory-master/BehavioralAnalysis/SS2_analyze_ecog.m | 5,448 | utf_8 | 45a5b623c0cccc81fcb2f1b31d071fea | function [teststamps hcmf hmcfn hmcfnRT testRTs pairs S] = SS2_analyze_ecog(run,sub,path)
%ecog behavioral data analysis
%a.gonzl
%Aug 5,2011
%mapping of responses
% sub1 button pressed '+' -> [2] new
% '4' -> [1] old
%
% subject 2 had enough trials with confidence
% sub2 button pressed '+'... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | trial_conds.m | .m | ECoG_PPC_RecogMemory-master/BehavioralAnalysis/trial_conds.m | 2,046 | utf_8 | 6cc1d2c797c10be1cb19297c5b446c8c |
function out = trial_conds(conds,expt)
% this function creates a struct with condition vectors depending on the
% experiment
% it takes the vector conds, with the codes for what that trials represents
% and then it groups events with the same conditions or collapeses
% conditions of interest
if strcmp(expt,'SS3') ||... |
github | WagnerLab/ECoG_PPC_RecogMemory-master | SS2_analyzeEncodingBehavioral.m | .m | ECoG_PPC_RecogMemory-master/BehavioralAnalysis/SS2_analyzeEncodingBehavioral.m | 2,313 | utf_8 | 42a4978d1879069bceb4801a6ebaa6a5 |
function [out] = SS2_analyzeEncodingBehavioral(data,subjname, runnum)
% output
out = [];
out.data = data;
% subject button response condition mapping:
if strcmp(subjname,'SRb')
if (runnum < 4)
key1 = '5'; % abstract
key2 = '4'; % concrete
else
key1 = 'R'; % abstract
key2 = 'L'... |
github | muhammetasan/bilateralTextureFiltering-master | BilateralFilter.m | .m | bilateralTextureFiltering-master/BilateralFilter.m | 2,224 | utf_8 | 4341bbbf221400d385cfc3c1b4a1e695 | function J=BilateralFilter(I,G,sigma_d,sigma_r,filterSize)
filterRadius=ceil((filterSize-1)/2);
I=double(I)/255;
G=double(G)/255;
I=padarray(I,[filterRadius,filterRadius],'replicate');
G=padarray(G,[filterRadius,filterRadius],'replicate');
if( size(I,3)==1)
J=bftGrayImage(I,G,sigma_d,sigma_r,filterRadius);
elseif ... |
github | muhammetasan/bilateralTextureFiltering-master | calcPatchShiftPar.m | .m | bilateralTextureFiltering-master/calcPatchShiftPar.m | 529 | utf_8 | 532f77a0d9b706bafa16b341dfd59c01 | %THIS IS PARALLEL IMPLEMENTATION OF CALCGUIDE
function [G,totVarQ]=calcPatchShiftPar(Bq,totVarP,radius)
[rows,cols]=size(Bq);
G=Bq;
disp('Calculating G');
totVarQ=zeros(size(totVarP));
parfor y=radius+1:rows-radius
for x=radius+1:cols-radius
window=totVarP(y-radius:y+radius,x-radius:x+radius);
[~,index]=min... |
github | SharpWave/TENASPIS-master | image_registerX.m | .m | TENASPIS-master/image_registerX.m | 15,007 | utf_8 | fceddd6726bd93c1b7d42767733d5f40 | function [RegistrationInfoX, unique_filename] = image_registerX(animal_name, ...
base_date, base_session, reg_date, reg_session, varargin)
% RegistrationInfoX = image_registerX(mouse_name, base_date, base_session, ...
% reg_date, reg_session, ...)
%
% Copyright 2015 by David Sullivan and Nathaniel Kinsky
%%... |
github | SharpWave/TENASPIS-master | MakeCircMask.m | .m | TENASPIS-master/MakeCircMask.m | 2,264 | utf_8 | f3111c0eb36aed70cfaa364bd28c3953 | % Draw a cInMatrcle InMatn a matrInMatx usInMatng the InMatnteger mInMatdpoInMatnt cInMatrcle algorInMatthm
% Does not mInMatss or repeat pInMatxels
% Created by : Peter Bone
% Created : 19th March 2007
function out = MidpointCircle(Xdim,Ydim, radius, yc, xc)
InMat = zeros(Xdim,Ydim,'single');
value = 1;
x... |
github | SharpWave/TENASPIS-master | MidpointCircle.m | .m | TENASPIS-master/MidpointCircle.m | 1,283 | utf_8 | 45afeae420fb8d9a259f6edb6394c495 | % Draw a cInMatrcle InMatn a matrInMatx usInMatng the InMatnteger mInMatdpoInMatnt cInMatrcle algorInMatthm
% Does not mInMatss or repeat pInMatxels
% Created by : Peter Bone
% Created : 19th March 2007
function out = MidpointCircle(Xdim,Ydim, radius, xc, yc)
InMat = zeros(Xdim,Ydim,'single');
value = 1;
x... |
github | dtxe/moviEEG-master | patchline.m | .m | moviEEG-master/EEGmovie_pipeline/patchline.m | 3,884 | utf_8 | 9353589aba7114710e73909bed36b445 | % http://www.mathworks.com/matlabcentral/fileexchange/36953-patchline
function p = patchline(xs,ys,varargin)
% Plot lines as patches (efficiently)
%
% SYNTAX:
% patchline(xs,ys)
% patchline(xs,ys,zs,...)
% patchline(xs,ys,zs,'PropertyName',propertyvalue,...)
% p = patchline(...)
%
% PROPERTIES... |
github | dtxe/moviEEG-master | rParabEmd_nooutput.m | .m | moviEEG-master/EEGmovie_pipeline/rParabEmd_nooutput.m | 15,544 | UNKNOWN | a8ee543501c5c94f6a6327f560dff523 | % This program performs the Empirical Mode Decomposition accordingly to the paper
% �On the HHT, its problems, and some solutions�, Reference: Rato, R. T., Ortigueira, M. D., and Batista, A. G.,
% Mechanical Systems and Signal Processing , vol. 22, no. 6, pp. 1374-1394, August 2008.
%
%
% Authors: ... |
github | dtxe/moviEEG-master | gridfit.m | .m | moviEEG-master/EEGmovie_pipeline/gridfit.m | 34,029 | utf_8 | eaab1614a03a31ec91263a3d178c01f5 | % http://www.mathworks.com/matlabcentral/fileexchange/8998-surface-fitting-using-gridfit
function [zgrid,xgrid,ygrid] = gridfit(x,y,z,xnodes,ynodes,varargin)
% gridfit: estimates a surface on a 2d grid, based on scattered data
% Replicates are allowed. All methods extrapolate to the grid
% boundaries... |
github | jgte/matlab-sgp4-master | deltalongeci2ecef.m | .m | matlab-sgp4-master/deltalongeci2ecef.m | 2,844 | utf_8 | 2c77e89356235b8d3c1eab2a4e88d52f | function out=deltalongeci2ecef(jd)
out=gmst_wrapper(jd,0);
end
%this function spits out the GMST in degrees
function gmst=gmst_wrapper(jd,method)
if ~exist('method','var') || isempty(method)
method=0; %rad/s
end
%branch on method
switch method
case 0
max_method=4;
out=zeros(numel(jd),... |
github | jgte/matlab-sgp4-master | days2mdh.m | .m | matlab-sgp4-master/days2mdh.m | 2,354 | utf_8 | 8cdfc166a8db948efbba6794e23f219e | % ------------------------------------------------------------------------------
%
% function days2mdh
%
% this function converts the day of the year, days, to the equivalent month
% day, hour, minute and second.
%
% author : david vallado 719-573-2600 22 ... |
github | jgte/matlab-sgp4-master | dspace.m | .m | matlab-sgp4-master/dspace.m | 7,516 | utf_8 | fbc98ef9f67b75c148255fff569be445 | % -----------------------------------------------------------------------------
%
% procedure dspace
%
% this procedure provides deep space contributions to mean elements for
% perturbing third body. these effects have been averaged over one
% revolution of the sun and moon. ... |
github | jgte/matlab-sgp4-master | jday.m | .m | matlab-sgp4-master/jday.m | 1,629 | utf_8 | 0a9a66f7288921c6980adcdeacb189ae | % -----------------------------------------------------------------------------
%
% function jday.m
%
% this function finds the julian date given the year, month, day, and time.
%
% author : david vallado 719-573-2600 27 may 2002
%
% revisions
% ... |
github | jgte/matlab-sgp4-master | twoline2rv.m | .m | matlab-sgp4-master/twoline2rv.m | 7,396 | utf_8 | 32f6652e0051e28592094d6fdbc4bc8a | % -----------------------------------------------------------------------------
%
% procedure twoline2rv
%
% this function converts the two line element set character string data to
% variables and initializes the sgp4 variables. several intermediate varaibles
% and quantities a... |
github | jgte/matlab-sgp4-master | mag.m | .m | matlab-sgp4-master/mag.m | 994 | utf_8 | 692971fab2efc7cc1a386b571082890a | % ------------------------------------------------------------------------------
%
% function mag
%
% this function finds the magnitude of a vector. the tolerance is set to
% 0.000001, thus the 1.0e-12 for the squared test of underflows.
%
% author : david vallado ... |
github | jgte/matlab-sgp4-master | invjday.m | .m | matlab-sgp4-master/invjday.m | 2,362 | utf_8 | e7e4b1a947109a69d1f08f0dc38390f7 | % ------------------------------------------------------------------------------
%
% function invjday
%
% this function finds the year, month, day, hour, minute and second
% given the julian date. tu can be ut1, tdt, tdb, etc.
%
% author : david vallado 719-... |
github | jgte/matlab-sgp4-master | dscom.m | .m | matlab-sgp4-master/dscom.m | 8,536 | utf_8 | 9d59d451aa72b865cf7d6f6f4d1a3901 | % -----------------------------------------------------------------------------
%
% procedure dscom
%
% this procedure provides deep space common items used by both the secular
% and periodics subroutines. input is provided as shown. this routine
% used to be called dpper, bu... |
github | jgte/matlab-sgp4-master | initl.m | .m | matlab-sgp4-master/initl.m | 4,219 | utf_8 | be6446ba6d809103880622e1fcdb0891 | % -----------------------------------------------------------------------------
%
% procedure initl
%
% this procedure initializes the spg4 propagator. all the initialization is
% consolidated here instead of having multiple loops inside other routines.
%
% Author:
% Jeff Bec... |
github | jgte/matlab-sgp4-master | sgp4.m | .m | matlab-sgp4-master/sgp4.m | 12,190 | utf_8 | c674a097419ba073465e11d84001a6f2 | % -----------------------------------------------------------------------------
%
% procedure sgp4
%
% this procedure is the sgp4 prediction model from space command. this is an
% updated and combined version of sgp4 and sdp4, which were originally
% published separately in spa... |
github | jgte/matlab-sgp4-master | newtonm.m | .m | matlab-sgp4-master/newtonm.m | 4,575 | utf_8 | 9cc7d0f4413432be38d1ecfbff4cde6a | % ------------------------------------------------------------------------------
%
% function newtonm
%
% this function performs the newton rhapson iteration to find the
% eccentric anomaly given the mean anomaly. the true anomaly is also
% calculated.
%
% author : davi... |
github | jgte/matlab-sgp4-master | newtonnu.m | .m | matlab-sgp4-master/newtonnu.m | 3,106 | utf_8 | cfc9b5a76294cbe4e64d66f0d3f14110 | % ------------------------------------------------------------------------------
%
% function newtonnu
%
% this function solves keplers equation when the true anomaly is known.
% the mean and eccentric, parabolic, or hyperbolic anomaly is also found.
% the parabolic limit at 168 i... |
github | jgte/matlab-sgp4-master | sgp4init.m | .m | matlab-sgp4-master/sgp4init.m | 14,314 | utf_8 | f475a798cea0a8967df10387e69d3cf2 | % -----------------------------------------------------------------------------
%
% procedure sgp4init
%
% this procedure initializes variables for sgp4.
%
% Author:
% Jeff Beck
% beckja@alumni.lehigh.edu
% 1.0 (aug 7, 2006) - update for paper dav
% original comments fro... |
github | jgte/matlab-sgp4-master | dsinit.m | .m | matlab-sgp4-master/dsinit.m | 12,042 | utf_8 | 9aaf468c948e255df94b04d8c35ae837 | % -----------------------------------------------------------------------------
%
% procedure dsinit
%
% this procedure provides deep space contributions to mean motion dot due
% to geopotential resonance with half day and one day orbits.
%
% Author:
% Jeff Beck
% beckja@... |
github | jgte/matlab-sgp4-master | gstime.m | .m | matlab-sgp4-master/gstime.m | 1,549 | utf_8 | cbe037eb5fd7253e3123aa3b7862dc58 | % -----------------------------------------------------------------------------
%
% function gstime
%
% this function finds the greenwich sidereal time (iau-82).
%
% author : david vallado 719-573-2600 7 jun 2002
%
% revisions
% -
%
% in... |
github | jgte/matlab-sgp4-master | angl.m | .m | matlab-sgp4-master/angl.m | 1,369 | utf_8 | 6dbecfa78ac24bd4c0b0b2ea62658da3 | % ------------------------------------------------------------------------------
%
% function angl
%
% this function calculates the angle between two vectors. the output is
% set to 999999.1 to indicate an undefined value. be sure to check for
% this at the output phase.
%
% ... |
github | jgte/matlab-sgp4-master | getgravc.m | .m | matlab-sgp4-master/getgravc.m | 2,598 | utf_8 | e926817ff47badb1c533da0278da254e | % -----------------------------------------------------------------------------
%
% function getgravc
%
% this function gets constants for the propagator. note that mu is identified to
% facilitiate comparisons with newer models.
%
% author : david vallado 7... |
github | jgte/matlab-sgp4-master | rv2coe.m | .m | matlab-sgp4-master/rv2coe.m | 7,775 | utf_8 | 22b2d660f13821a2355ec72d146cd8ee | %
% ------------------------------------------------------------------------------
%
% function rv2coe
%
% this function finds the classical orbital elements given the geocentric
% equatorial position and velocity vectors.
%
% author : david vallado 719-57... |
github | jgte/matlab-sgp4-master | dpper.m | .m | matlab-sgp4-master/dpper.m | 6,697 | utf_8 | 8d08543e8cee2e1db23c88884502c0bf | % -----------------------------------------------------------------------------
%
% procedure dpper
%
% this procedure provides deep space long period periodic contributions
% to the mean elements. by design, these periodics are zero at epoch.
% this used to be dscom which i... |
github | whitelok/LearningBasedMatting_Matlab-master | getLap_iccv09_overlapping.m | .m | LearningBasedMatting_Matlab-master/code/learningBasedMatting/getLap_iccv09_overlapping.m | 3,500 | utf_8 | f397eddefa54d208049e24208a8c9d0d | function L=getLap_iccv09_overlapping(imdata,winsz,mask,lambda)
% L=getLap_iccv09_overlapping(imdata,winsz,mask,lambda) get the laplacian
% matrix based on imdata (image data) and winsz (local window size). See
% equations (6) and (11) in our iccv2009 paper.
%
% Input arguments:
% imdata: MxNxd matrix. Image size is Mx... |
github | firemodels/fds-master | mass_balance_reac.m | .m | fds-master/Utilities/Matlab/scripts/mass_balance_reac.m | 2,783 | utf_8 | e53887c472003e6d0b55e67ec56bf221 | % McDermott
% 10 July 2020
% mass_balance_reac.m
close all
clear all
plot_mass_balance('mass_balance_reac','Propane Mass Balance','PROPANE','C3H8');
plot_mass_balance('mass_balance_reac','Oxygen Mass Balance','OXYGEN','O2');
plot_mass_balance('mass_balance_reac','Nitrogen Mass Balance','NITROGEN','N2');
plot_mass_bal... |
github | firemodels/fds-master | slread.m | .m | fds-master/Utilities/Matlab/scripts/slread.m | 1,657 | utf_8 | 3c74440e56a787997c5ddbb81f3f015b | % Simo Hostikka
% 20 Oct 2008
% slread.m
%
% SLREAD Reads a FDS slice file
% [T,Time]=slread(fname,Tstart,Tend [,Tstep]);
% Tstart is start time
% Tend is end time
% Tstep is time step of dumps
%
% T contains the data
% Time contains the time points
function [... |
github | firemodels/fds-master | addverstr.m | .m | fds-master/Utilities/Matlab/scripts/addverstr.m | 1,788 | utf_8 | b64dd22b2e3fb5840b0166e1a7bc8273 | % McDermott
% 6-23-2015
% addverstr.m
function []=addverstr(ha,fn,pt,varargin)
VerStr_Scale_X = 0.60;
VerStr_Scale_Y = 1.05;
Font_Name = 'Times';
Font_Interpreter = 'TeX';
Font_Size = 10;
nvararg = length(varargin);
if nvararg>=1; VerStr_Scale_X = varargin{1}; end
if nvararg>=2; VerStr_Scale_Y ... |
github | firemodels/fds-master | stripcell.m | .m | fds-master/Utilities/Matlab/scripts/stripcell.m | 236 | utf_8 | 559840f621a84353189547e00f255492 | % McDermott
% 6-11-2009
% stripcell.m
%
% Stip cell array of empty cells
function [C] = stripcell(CELL_ARRAY)
i = 1;
for j=1:length(CELL_ARRAY)
if iscellstr(CELL_ARRAY(j))
C(i) = CELL_ARRAY(j);
i = i+1;
end
end |
github | firemodels/fds-master | velocity_signal.m | .m | fds-master/Utilities/Matlab/scripts/velocity_signal.m | 1,449 | utf_8 | 3204968ebdd167724f4dbbc11fc1b525 | % McDermott
% 3-5-10
% velocity_signal.m
function []=velocity_signal(devc_file,devc_col,vel_style,tmin,tmax,vmin,vmax,xaxis_title,yaxis_title, ...
title_label,text_label,signal_file,git_file)
M = csvread(devc_file,2,0);
range = find(M(:,1)>tmin & M(:,1)<tmax);
t = M(range,1);
W = M(range... |
github | firemodels/fds-master | sl3d_read.m | .m | fds-master/Utilities/Matlab/scripts/sl3d_read.m | 1,631 | utf_8 | 508d73a20ea9540f938be014c577984b | % McDermott
% 15 Aug 2019
% sl3d_read.m
%
% based on slread.m by Simo Hostikka
%
% SL3D_READ Reads an FDS 3D slice file
% [Q,Time]=sl3d_read(fname,Tstart,Tend [,Tstep]);
% Tstart is start time
% Tend is end time
% Tstep is time step of dumps
%
% Q contains the da... |
github | firemodels/fds-master | parseplus.m | .m | fds-master/Utilities/Matlab/scripts/parseplus.m | 285 | utf_8 | a44845d38f8a54b894b4c7b75baedabf | % McDermott
% 12-30-2015
% parseplus.m
%
% [S] = parseplus(character_string)
%
% Uses textscan to parse a character string that is delimited with a "+".
function [S] = parseplus(character_string)
cell_array = textscan(char(character_string),'%s','delimiter','+');
S = cell_array{:}'; |
github | firemodels/fds-master | energy_decay.m | .m | fds-master/Utilities/Matlab/scripts/energy_decay.m | 3,267 | utf_8 | 5badefef1f5a88057891b5878fc5176a | % McDermott
% 9-22-08
% energy_decay.m
%
% Plot energy decay for Comte-Bellot and Corrsin data
%
% [] = energy_decay(chid,N)
%
% chid = CHID from FDS input file
% N = number of cells in 1D
%
% Example>> energy_decay('csmag_32',32)
function [] = energy_decay(chid,N)
close all
addpath('../../Verification/Turbulence')
... |
github | firemodels/fds-master | arrows.m | .m | fds-master/Utilities/Matlab/scripts/arrows.m | 2,739 | utf_8 | 702541984a1b9e07aa047478a70c8a74 | %-------------------------------------------------------------------------%
% FILE: arrows.m
% AUTHOR: Max Gould
% LAST DATE EDITED: 27 June 2012
%-------------------------------------------------------------------------%
%-------------------------------------------------------------------------%
% Generate filled arr... |
github | firemodels/fds-master | friction_factor_calc.m | .m | fds-master/Utilities/Matlab/scripts/friction_factor_calc.m | 442 | utf_8 | abd3fcb8412a0d81a7bb23117cf6f0b2 | % McDermott
% 5-14-2009
% friction_factor_calc.m
function [f_fds,Re_H]=friction_factor_calc(dpdx,H,filename,varargin)
M = csvread(filename,2,0);
ubar = M(:,2);
if nargin==3
mu = max(M(:,4));
elseif nargin==4
mu = varargin{1};
end
rho = max(M(:,5));
U = ubar(length(ubar)); % steady state mean velocity (pla... |
github | firemodels/fds-master | plotspec_uvw.m | .m | fds-master/Utilities/Matlab/scripts/plotspec_uvw.m | 1,550 | utf_8 | 82bf0b927d6a7570bd9ecacc15ef5cb8 | % McDermott
% 9-10-10
% plotspec_uvw.m
function [handle]=plotspec_uvw(filename,marker_format)
if ~exist(filename)
display(['Error: File ' filename ' does not exist. Skipping case.'])
return
end
M = importdata(filename,',',1);
s = str2num(M.textdata{:});
n = s(2);
% convert to 3D array
p=0;
for k=1:n
for ... |
github | firemodels/fds-master | power_spectrum.m | .m | fds-master/Utilities/Matlab/scripts/power_spectrum.m | 2,734 | utf_8 | 3396b49a30faad0a1a35c239f9fa2495 | % McDermott
% 2-26-10
% power_spectrum.m
function []=power_spectrum(spectrum_file,dt_puff,slope_scale,xaxis_title,yaxis_title,xmin,xmax,ymin,ymax, ...
devc_file,devc_col,tmin,tmax,dt,spectrum_style,nyquist_style, ...
title1,title2,git_file)
M = csvread(devc_file,2... |
github | firemodels/fds-master | parsepipe.m | .m | fds-master/Utilities/Matlab/scripts/parsepipe.m | 278 | utf_8 | e75adaeaee09e1eba23691d0ff208575 | % McDermott
% 6-08-2009
% parsepipe.m
%
% [S] = parsepipe(character_string)
%
% Uses textscan to parse a character string that is delimited with a "|".
function [S] = parsepipe(character_string)
cell_array = textscan(character_string,'%s','delimiter','|');
S = cell_array{:}'; |
github | firemodels/fds-master | scatplot.m | .m | fds-master/Utilities/Matlab/scripts/scatplot.m | 19,128 | utf_8 | a98a11c2780f3ffbcb70c1f1dc27451b | % R. McDermott
% 7-06-2009
% scatplot.m
%
% Generate scatter plots. Must first run dataplot.m to generate
% saved_data and drange.
%
% [] = scatplot(saved_data, drange, Scatterplot_Inputs_File, Manuals_Dir)
%
% Arguments:
% saved_data - cell array of packed data, may be obtained by running
% the dataplot.m funct... |
github | firemodels/fds-master | radial_profile.m | .m | fds-master/Utilities/Matlab/scripts/radial_profile.m | 11,139 | utf_8 | 96d728febc602c5eaef140e80773d25b | % McDermott
% 2-15-10
% radial_profile.m
%
% Plot radial profile from experiment vs. FDS results (up to 5)
%
% Example:
%
% function []=radial_profile(plot_file,data_format,devc_col,error,error_type,tmin, ...
% xaxis_label,yaxis_label,title_label,text_label,legend_pos, ...
% ... |
github | firemodels/fds-master | mass_balance.m | .m | fds-master/Utilities/Matlab/scripts/mass_balance.m | 1,906 | utf_8 | 6d96f0d1a87356c40c4de0db3ae035e1 | % McDermott
% 05 Dec 2017
% mass_balance.m
close all
clear all
plot_mass_balance('mass_flux_wall_yindex','Primitive Species Mass Balance');
plot_mass_balance('mass_flux_wall_zindex','Lumped Species Mass Balance');
function [] = plot_mass_balance(chid,title_text)
plot_style
figure
set(gca,'Units',Plot_Units)
set(gc... |
github | firemodels/fds-master | mass_balance_gas_volume.m | .m | fds-master/Utilities/Matlab/scripts/mass_balance_gas_volume.m | 1,997 | utf_8 | 94c20f4bc6d0678c7191c07502eba786 | % McDermott
% 2 Dec 2021
% mass_balance_gas_volume.m
close all
clear all
plot_mass_balance('mass_balance_gas_volume','');
function [] = plot_mass_balance(chid,title_text)
plot_style
figure
set(gca,'Units',Plot_Units)
set(gca,'Position',[Plot_X Plot_Y Plot_Width Plot_Height])
ddir = '../../Verification/Species/';
M... |
github | firemodels/fds-master | level_set_ellipse.m | .m | fds-master/Utilities/Matlab/scripts/level_set_ellipse.m | 8,744 | utf_8 | a850e93c654600d967b13be7d671ca09 | % Mueller
% 11-01-2022
% level_set_ellipse.m
% This script calculates expected fire spread behavior with applied
% wind and slope, using an assumption of elliptical spread and the
% Rothermel fire spread model (Bova et al., 2016).
% Expected values are compared to FDS predictions using the level set mode
close all
cl... |
github | firemodels/fds-master | dvcread.m | .m | fds-master/Utilities/Matlab/scripts/dvcread.m | 1,541 | utf_8 | 3bc2eff9fe5ce4e38848b0284388e1a8 | % McDermott
% 6-02-2009
% dvcread.m
%
% function [H X] = dvcread(filename,header_row,data_row)
%
% header_row = row where header names are stored; names converted to H
% vector.
%
% data_row = row where numeric data starts
%
% X = matrix of numeric data; columns correspond to entries in H.
%
% Read a _devc.csv file for... |
github | firemodels/fds-master | read_prt5.m | .m | fds-master/Utilities/Matlab/scripts/read_prt5.m | 3,747 | utf_8 | c36b1c745f70ef6721e70d1846fcf1d0 | % Trettel and McDermott
% 7-5-11
% read_prt5.m
%
% This function reads the FDS 'part' file (*.prt5).
%
% Example:
%
% >> read_prt5('terminal_velocity.prt5','real*8')
%
% precision = 'real*4' if EB_PART_FILE=.FALSE. on the DUMP line
% precision = 'real*8' if EB_PART_FILE=.TRUE. on the DUMP line
%
% To read part files ge... |
github | firemodels/fds-master | compression_wave_soln.m | .m | fds-master/Utilities/Matlab/scripts/compression_wave_soln.m | 731 | utf_8 | 8004e30b2cfcd7c2a66ed14fbd7ecfc8 | % McDermott
% 4-8-10
% compression_wave_soln.m
function [rho] = compression_wave_soln(rho0,x,y,a,c,t);
b = sqrt(-1+a^2);
d = sqrt(-1+c^2);
x0 = 2*atan( b/a*tan( atan( (1+a*tan(x/2))/b ) - b*t/2 ) - 1/a );
y0 = 2*atan( d/c*tan( atan( (1+c*tan(y/2))/d ) - d*t/2 ) - 1/c );
Ix0 = log( -a^2 - cos( 2*atan( (1+a*tan(x0/2)... |
github | firemodels/fds-master | dataplot.m | .m | fds-master/Utilities/Matlab/scripts/dataplot.m | 29,092 | utf_8 | f4108c3598d74cdf14a63e6f730e6fc7 | % R. McDermott and C. Cruz and S. Hostikka
% 6-06-2012
% dataplot.m
%
% Detailed instructions can be found here:
% https://github.com/firemodels/fds/wiki/Using-the-Matlab-script-dataplot.m
%
% [saved_data, drange] = dataplot(Dataplot_Inputs_File, EXP_Dir, OUT_Dir, Manuals_Dir, [drange])
%
% Output:
%
% saved_data - ... |
github | firemodels/fds-master | reaction_rate.m | .m | fds-master/Utilities/Matlab/scripts/reaction_rate.m | 340 | utf_8 | 3856a8c034e2455109d3061b2d24bf9f | % McGrattan
% 8-10-09
% reaction_rate.m
%
% input:
% T = temperature (K)
% Y = mass fraction
%
% output:
% r = reaction rate
function r = reaction_rate(T,Y)
global dTdt
global R0
global E
global A
global residue
r(1) = -A(1).*Y(1)*exp(-E(1)./(R0.*T))./dTdt;
r(2) = -A(2).*Y(2)*exp(-E(2)./(R0.*T))./dTdt;
r(3) = -resid... |
github | firemodels/fds-master | parse.m | .m | fds-master/Utilities/Matlab/scripts/parse.m | 266 | utf_8 | cc0f9193fb2517584f78c7c1a0878953 | % McDermott
% 6-08-2009
% parse.m
%
% [S] = parse(character_string)
%
% Uses textscan to parse a character string that is delimited with a "|".
function [S] = parse(character_string)
cell_array = textscan(character_string,'%s','delimiter','|');
S = cell_array{:}'; |
github | firemodels/fds-master | blasius_analytic.m | .m | fds-master/Utilities/Matlab/scripts/blasius_analytic.m | 1,596 | utf_8 | 88e4cc113210b572d427429fc3aebd15 | % PARK HYUN WOOK, Yonsei University
% 8-15-2012
% blasius_analytic.m
function [eta,f,fp] = blasius_analytic(u0, zmax, mu, rho, x, steps, fpp_init)
% etamax = maximum eta for calculation
% steps = number of steps between 0 and etamax
% fppwall = initial (wall) value of 2nd derivative of Blasius function
% outputs:
% e... |
github | firemodels/fds-master | colebrook.m | .m | fds-master/Utilities/Matlab/scripts/colebrook.m | 569 | utf_8 | 8cbb966204f84fecfd6ce4b0e8b30cfb | % McDermott
% 2-23-09
% colebrook.m
%
% input:
% Re = Reynolds number
% RR = relative roughness
% ff = a guess for the value of f
% tol = convergence tolerance (relative error between f and ff)
%
% output:
% f = Moody friction factor based on Colebrook formula
%
% ref:
% Munson, Young and Okiishi, Fundamentals of Fluid... |
github | firemodels/fds-master | plotspec.m | .m | fds-master/Utilities/Matlab/scripts/plotspec.m | 3,880 | utf_8 | 84bd4e02e682fb0cc2708ca1d57fefff | % McDermott
% 4-22-2001 (modified 12-9-2010)
% plotspec.m
%
% Read and plot energy spectra for Comte-Bellot and Corrsin data
%
% [] = plotspec(chid,N)
%
% chid = CHID from FDS input file
% N = number of cells in 1D
%
% Example: >> plotspec('csmag_32',32)
function [] = plotspec(chid,N)
close all
% set FDS standard pl... |
github | firemodels/fds-master | backward_facing_step.m | .m | fds-master/Utilities/Matlab/scripts/backward_facing_step.m | 27,029 | utf_8 | cc6bd56584fc6d05eb2de3b3bb1ff84d | % Toms
% 8-8-14
% backward_facing_step.m
function main()
clear all
close all
disp('backward_facing_step ...')
expdir = '../../../exp/Backward_Facing_Step/';
datdir = '../../../out/Backward_Facing_Step/';
pltdir = '../../Manuals/FDS_Validation_Guide/SCRIPT_FIGURES/Backward_Facing_Step/';
rkappa = 1/.41;
B = 5.2;
rh... |
github | firemodels/fds-master | parse_fds_out.m | .m | fds-master/Utilities/Matlab/scripts/parse_fds_out.m | 2,122 | utf_8 | 8b806c0ecadd3d7b515933e1a7efb4d3 | % McDermott
% 12-6-2019
% parse_fds_out.m
%
% The basic plan is to start building this function and adding
% new values as needed. Follow the examples below.
%
% Note that if someone has changed even one space in the formating of the
% .out file, then there will be problems with this parser. So, beware
% that it is f... |
github | firemodels/fds-master | section2_soln.m | .m | fds-master/Utilities/Matlab/scripts/section2_soln.m | 488 | utf_8 | 13aae40bdea3cca6feecc283b5d6aa00 | % Antonellis
% 06-23-2010
% section2_soln.m
function [rho] = section2_soln(rho0,x,y,B,w,t);
x0 = 2*atan(tan(x/2)*exp(-B/w*sin(w*t)));
y0 = 2*atan(tan(y/2)*exp(-B/w*sin(w*t)));
q0 = log(rho0);
q = q0 + log((1 + (tan(x0/2)).^2.*exp(2*B/w*sin(w*t)))./(1+(tan(x0/2)).^2)) ...
+ log((1 + (tan(y0/2... |
github | firemodels/fds-master | shell_script_ansys.m | .m | fds-master/Utilities/Structural_Interaction/shell_script_ansys.m | 17,773 | utf_8 | fa03504cd657d30744b05c3d83d60c47 |
% This routine maps temperatures from a solid thermal FEA model to a
% structural shell element model. At, present output data are written out in
% ANSYS format. A sample of the output file written by this program is shown below for an element
% number 25383, which is a 3-layer shell element with 4 nodes:
%
% BFE,25... |
github | firemodels/fds-master | fds_to_ansys_data_mapping.m | .m | fds-master/Utilities/Structural_Interaction/fds_to_ansys_data_mapping.m | 13,169 | utf_8 | 4f222632bd3c33f6c7cd96e72c904bda |
% This program reads heat transfer FEA model data e.g., nodal coordinates
% and element connectivity to determine which nodes are on the boundary of
% the structural components.
%
% It then reads six sets of FDS boundary file data (in +x, -x, +y, -y, +z, -z )
% directions containing temperatures
% at gridpoints locate... |
github | firemodels/fds-master | beam_script_neutral.m | .m | fds-master/Utilities/Structural_Interaction/beam_script_neutral.m | 16,320 | utf_8 | 7b0683acd0e5c0fb8aec9cf7e6e5a44e |
% This routine maps temperatures from a solid thermal FEA model to a
% structural beam element model. This is is the second of the two routines for mapping
% results for beam elements. In this approach, transfer points coordinates are
% chosen along the beam cross section and the transfer point coordinates are ente... |
github | firemodels/fds-master | beam_script_ansys.m | .m | fds-master/Utilities/Structural_Interaction/beam_script_ansys.m | 18,748 | utf_8 | 2805ef786e925a0fdf4c023d8d1f3919 |
% This routine maps temperatures from a solid thermal FEA model to a
% structural beam element model. At, present the data are written out in
% ANSYS format. This is is the fist of the two routines for mapping
% results for beam elements. In this approach, 15 transfer points are
% chosen along the beam cross sectio... |
github | firemodels/fds-master | fds_bf_read.m | .m | fds-master/Utilities/Structural_Interaction/fds_bf_read.m | 2,502 | utf_8 | 0affa514ffa762df5dd35eb937418b93 | % This program reads FDS boundary file data (6 sets of data for +x, -x, +y,
% -y, +z, -z) and removes header information and text in the FDS boundary file
% A typical boundary file data generated by running the "FDS2ASCII" program
% after running a FDS simulation is shown (first few lines):
%
%Patch 6 3.00<x< 3 0.50<y... |
github | firemodels/fds-master | read_wobj.m | .m | fds-master/Utilities/CAD_Converters/read_wobj.m | 13,901 | utf_8 | 162d9ee86ede747eddd2835cb33f3739 | function OBJ=read_wobj(fullfilename)
% Read the objects from a Wavefront OBJ file
%
% OBJ=read_wobj(filename);
%
% OBJ struct containing:
%
% OBJ.vertices : Vertices coordinates
% OBJ.vertices_texture: Texture coordinates
% OBJ.vertices_normal : Normal vectors
% OBJ.vertices_point : Vertice data used for points and li... |
github | firemodels/fds-master | stlread.m | .m | fds-master/Utilities/CAD_Converters/stlread.m | 3,846 | utf_8 | 3b86da3a96dd464275ab78a6395fbe25 | function varargout = stlread(file)
% STLREAD imports geometry from an STL file into MATLAB.
% FV = STLREAD(FILENAME) imports triangular faces from the ASCII or binary
% STL file idicated by FILENAME, and returns the patch struct FV, with fields
% 'faces' and 'vertices'.
%
% [F,V] = STLREAD(FILENAME) returns... |
github | mmagnuski/braintools-master | cluster_from_folders.m | .m | braintools-master/clust/cluster_from_folders.m | 3,947 | utf_8 | bd0c855338c2a0b1deb1930552ebe80e | function varargout = cluster_from_folders(pth, chanconn, varargin)
% stat = cluster_from_folders(pth, chanconn, effect_name)
% CLUSTER_FROM_FOLDERS clusters data scattered across permutation folders
% TODO - unify cluster_this and cluster_main
% TODO - min_chan should be in varargin
min_chan = 2;
% dirnames:
lst = ... |
github | mmagnuski/braintools-master | ft_hastlbx.m | .m | braintools-master/clust/from fieldtrip/ft_hastlbx.m | 23,671 | utf_8 | d576450ac6a200cf5aa42d0e422e2dde | function [status] = ft_hastlbx(toolbox, autoadd, silent)
% FT_HASTOOLBOX tests whether an external toolbox is installed. Optionally
% it will try to determine the path to the toolbox and install it
% automatically.
%
% Use as
% [status] = ft_hastoolbox(toolbox, autoadd, silent)
%
% autoadd = 0 means that it will not... |
github | mmagnuski/braintools-master | maskitsweet.m | .m | braintools-master/plt/maskitsweet.m | 39,013 | utf_8 | edf0ca374418b8d29b6683496a56288c | function [outputs, handles] = maskitsweet(matri, mask, varargin)
% maskitsweet() allows to image a 2D matrix with transparency masking.
% this is most useful for time-frequency plots where nonsignificant
% values are 'shaded'.
%
% Usage:
% [output, handles] = maskitsweet(matr, mask);
% [output, handles] = maskitsweet(m... |
github | mmagnuski/braintools-master | eeg_path.m | .m | braintools-master/util/eeg_path.m | 6,016 | utf_8 | 4af928331d4ca00f6b5aa35d9f7a1850 | function eeg_path(type, varargin)
% adds path to eeglab functions
%
% ADDING PATH:
% eeg_path(1);
% OR: eeg_path('add');
% (as for now this is just code copied from EEGlab's eeglab.m, in the
% future it might be more elegant)
%
% REMOVING PATH:
% eeg_path(2);
% OR: eeg_path('rem');
% TODOs:
% [ ] restructure
% [ ] ... |
github | mmagnuski/braintools-master | whob.m | .m | braintools-master/util/whob.m | 7,405 | utf_8 | 11509aba265df99b4b42e0861a34be09 | % WHOB is a function that sorts the WHOS output according a user
% defined input (ie name, size, bytes, type etc.). The output also
% includes the FULL size rather than the #-D labels that TMW prefers. The
% output is also human readable and incorporates the use of b (byte), kn
% (kilobyte), Mb (megabyte), and Gb(giga... |
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