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github | canlab/Canlab_MKDA_MetaAnalysis-master | plot_points_on_montage.m | .m | Canlab_MKDA_MetaAnalysis-master/densityUtility3/plotting_functions/plot_points_on_montage.m | 10,714 | utf_8 | bc4c6fbd7ee380ac51a7166712b3b4bd | function [newax, pointhandles] = plot_points_on_montage(xyz, varargin)
% [newax, pointhandles] = plot_points_on_montage(xyz, varargin)
%
% Plots points on montage of slices
% - Solid brain slices or contour outlines
% - Points or text labels or both
% - Flexible slice spacing, colors, marker sizes/styles, axis layout (... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | meta_prob_activation.m | .m | Canlab_MKDA_MetaAnalysis-master/densityUtility3/Support_functions_density/meta_prob_activation.m | 6,553 | utf_8 | 25226cc6c7844bff299b6934aefbabbc | function [MC_Setup,activation_proportions,icon] = meta_prob_activation(DB,Xi,contrasts,connames,Xinms)
% [MC_Setup,activation_proportions,icon] = meta_prob_activation(DB,[X indicator mtx],[contrasts],[con. names],[Xinms])
%
% This function writes 'Activation_proportion.img'
% --a weighted map of the proportion of indep... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | meta_stochastic_activation_blobs.m | .m | Canlab_MKDA_MetaAnalysis-master/densityUtility3/Support_functions_density/meta_stochastic_activation_blobs.m | 3,948 | utf_8 | cf8f7de39e8c0b4ad27fd216f91c5493 | function [maxprop,uncor_prop,maxcsize] = meta_stochastic_activation_blobs(MC_Setup)
% MC_Setup = meta_stochastic_activation_blobs(DB)
%
% This function randomizes n contiguous blobs for each study within analysis mask
% and computes null-hypothesis weighted proportion of activated studies
% (contrasts)
% for whole-brai... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | meta_reconstruct_mask.m | .m | Canlab_MKDA_MetaAnalysis-master/densityUtility3/Support_functions_density/meta_reconstruct_mask.m | 1,472 | utf_8 | 5f0af7cd563f4f0271fe30ff9777087f | % reconstruct mask for a study, given indicator
% v2 = meta_reconstruct_mask(indic, xyzlist, V.dim(1:3), [use values], [V], [imagename]);
%
% This function returns 3D mask values and optionally writes an image file
% if V and imagename are entered as additional arguments
%
% dims are mask dimensions; V is spm_vol struc... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | meta_stochastic_activation.m | .m | Canlab_MKDA_MetaAnalysis-master/densityUtility3/Support_functions_density/meta_stochastic_activation.m | 1,879 | utf_8 | b40531780448226cd3ad5baddfbe00f1 | function [maxprop,uncor_prop,maxcsize] = meta_stochastic_activation(MC_Setup)
% MC_Setup = meta_stochastic_activation(DB)
%
% This function randomizes n locations for each study within analysis mask
% and computes null-hypothesis weighted proportion of activated studies
% (contrasts)
% for whole-brain FWE corrected Mon... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | density_results_table.m | .m | Canlab_MKDA_MetaAnalysis-master/densityUtility/density_plots_tables/density_results_table.m | 2,263 | utf_8 | 542088f71cfc205e577af1b3fd986ac7 | function density_results_table(OUT)
% density_results_table(OUT)
%
% prints table of results for density_pdf or density_diff_pdf
% Tor Wager
fprintf(1,'Density results for %s\n',OUT.fname)
fprintf(1,'Brain mask file: %s with %3.2f x %3.2f x %3.2f mm voxels',OUT.mask_file,OUT.voxsize(1),OUT.voxsize(2),OUT.voxsize... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | whole_brain_ptask_givena.m | .m | Canlab_MKDA_MetaAnalysis-master/densityUtility/density2_calculations/whole_brain_ptask_givena.m | 6,722 | utf_8 | 960019afe1f0029c338b1d2d61acad07 | function OUT = whole_brain_ptask_givena(OUT,varargin)
% OUT = whole_brain_ptask_givena(OUT,verbose level, mask image or threshold value(for pa_overall) )
% OUT = whole_brain_ptask_givena(OUT,2,.001)
% verbose flag
if length(varargin) > 0, vb = varargin{1};, else, vb = 1;, end
P = OUT.PP;
task_indicator = OUT.allcondin... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | dbcontrast2density.m | .m | Canlab_MKDA_MetaAnalysis-master/densityUtility/density2_calculations/dbcontrast2density.m | 12,544 | utf_8 | 1e6e65bfc3d58df6c4b01e3bc2771353 | function [dmt,clusters,dm,OUT] = dbcontrast2density(DB,u,varargin)
% function [dmt,clusters,dm,OUT] = dbcontrast2density(DB,u,[radius_mm],[testfieldname],[contrast over levels],[con_dens_images])
%
% XYZ is 3-column vector of coordinates
%
% Tor Wager 11/20/04
%
% step 1: read database
% step 2: database2clusters -- g... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | mask2density_gauss.m | .m | Canlab_MKDA_MetaAnalysis-master/densityUtility/density2_calculations/mask2density_gauss.m | 7,731 | utf_8 | 82c96dccea38a0816caf52b9e8fa6c6d | function dm = mask2density(mask,radius,varargin)
% function dm = mask2density(mask,radius,[opt] searchmask, [opt] sphere_vol)
%
% mask is the mask with ones where activation points are
% radius is in voxels
%
% optional arguments:
% 1 searchmask
% searchmask is the whole brain search space [optional]
% Mask and sea... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | pa_overall_threshold.m | .m | Canlab_MKDA_MetaAnalysis-master/densityUtility/density2_calculations/pa_overall_threshold.m | 1,679 | utf_8 | 1857b8594ebbaad08cbaf2948a04016e |
function pa_overall_threshold(studynames,allconditions,xyz,radius_mm,normby,mask)
%
% gets uncorrected and corrected p-values for prob of activation
%
% [allconditions,pointcounts,studynames,allcondindic,allcondnames] =
% dbcluster2indic(DB,DB,{testfield});
%
%
for i = 1:length(studynames)
wh = find(strc... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | dbcontrast2density copy.m | .m | Canlab_MKDA_MetaAnalysis-master/densityUtility/density2_calculations/dbcontrast2density copy.m | 11,887 | utf_8 | 066a36e14fdae153fe69a51ce1c70958 | function [dmt,clusters,dm,OUT] = dbcontrast2density(DB,u,varargin)
% function [dmt,clusters,dm,OUT] = dbcontrast2density(DB,u,[radius_mm],[testfieldname],[contrast over levels],[con_dens_images])
%
% XYZ is 3-column vector of coordinates
%
% Tor Wager 11/20/04
%
% step 1: read database
% step 2: database2clusters -- g... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | density.m | .m | Canlab_MKDA_MetaAnalysis-master/densityUtility/density_analysis_calculations/density.m | 10,551 | utf_8 | 0de454c43e953c61ee0be6054942af0b | function [dmt,clusters,dm,mask,CLU] = density(XYZ,u,varargin)
% function [dmt,clusters,dm,mask,CLU] = density(XYZ,u,[radius_mm],[output_filename],[zscores])
%
% XYZ is 3-column vector of coordinates
%
% Tor Wager 2/18/02
P = ['brain_avg152T1.img']; % 2 mm voxels
P = 'scalped_avg152T1_graymatter_smoothed.img';
if... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | density_diff.m | .m | Canlab_MKDA_MetaAnalysis-master/densityUtility/density_analysis_calculations/density_diff.m | 5,465 | utf_8 | 82db7c55027ba8f18bcc25df184730d8 | function [cl1,cl2,dmt,dmt2,d1,d2,mask,mask2] = density_diff(XYZ,u,XYZ2,u2,varargin)
% function [cl1,cl2,dmt,dmt2,d1,d2,mask,mask2] = density_diff(XYZ,u,XYZ2,u2,[radius_mm],[first outfile name],[2nd outfile name])
%
% function gets density from a list of XYZ coordinates
% in one condition of a meta-analysis
% and makes... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | mask2density.m | .m | Canlab_MKDA_MetaAnalysis-master/densityUtility/density_analysis_calculations/mask2density.m | 6,660 | utf_8 | a32e052314f9961dc1a7726bac60960a | function dm = mask2density(mask,radius,varargin)
% function dm = mask2density(mask,radius,[opt] searchmask, [opt] sphere_vol)
%
% mask is the mask with ones where activation points are
% radius is in voxels
%
% optional arguments:
% 1 searchmask
% searchmask is the whole brain search space [optional]
% Mas... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | fast_max_density.m | .m | Canlab_MKDA_MetaAnalysis-master/densityUtility/density_analysis_calculations/fast_max_density.m | 5,547 | utf_8 | 0fdac3c733d29ff1fed8e5a5bf4484bc | function [u,maxd,usum,maxsum] = fast_max_density(n,iterations,radius_mm,varargin)
% [u,maxd,usum,maxsum] = fast_max_density(n,iterations,radius_mm,[brain_mask_name])
%
% Improved faster algorithm for null-hypothesis monte carlo simulation
% Same results as density_pdf.m
%
% u = critical threshold at alpha = .05
% maxd ... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | rotateByEigen.m | .m | Canlab_MKDA_MetaAnalysis-master/confidence_volume/rotateByEigen.m | 1,214 | utf_8 | 6b7f567170f4b0c81df66c49300a7d6a |
%
% function to rotate a 3d object to a new orientation defined
% by an eigenvalue problem.
%
% inputs are either:
% X, Y, Z matrices defining points to rotate
% n x 3 pointlist of [X Y Z] values, with 2nd and 3rd args empty
%
% returns: structure with X Y Z rotated, and XYZ rotated pointlist
%
% results = rotat... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | Meta_tables_of_variables.m | .m | Canlab_MKDA_MetaAnalysis-master/Miscellaneous_Functions/Meta_tables_of_variables.m | 7,451 | utf_8 | efe1e518fc81d95c5c5f3a6fad3c2338 | function DB = Meta_tables_of_variables(DB)
% Constructs some tables for each variable, saved in DB.TABLES, so that we can easily see the levels and numbers of points & contrasts for each variable
%
% DB = Meta_tables_of_variables(DB)
%
% - Must run Meta_Setup.m first
% - Assumes each study has one and only one unique t... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | dbcluster_point_table.m | .m | Canlab_MKDA_MetaAnalysis-master/Miscellaneous_Functions/dbcluster_point_table.m | 2,622 | utf_8 | f3473d24efd4b40b63582c60f9784f91 | function dbcluster_point_table(cl)
% function dbcluster_point_table(cl)
% looks for Study or study field in clusters
% determines length, and looks for other fields of the same length
% uses specified fields in a particular order, then other fields
N = fieldnames(cl(1));
% reorder - reverse order, bottom rows are top... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | cluster_overlap_npm.m | .m | Canlab_MKDA_MetaAnalysis-master/cluster_overlap_monte_carlo/cluster_overlap_npm.m | 5,965 | utf_8 | 74a1313743f86d67b7b07ea94cad5813 | function [OUT] = cluster_overlap_npm(cl1,cl2,varargin)
% function [OUT] = cluster_overlap_npm(cl1,cl2,[mask_fname],[iterations])
% tor wager
% takes 2 clusters structures and determines overlap
% - then runs Monte Carlo simulation randomizing cluster
% centers within a mask
%
% Mask and input files must have the same... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | title_keywords.m | .m | Canlab_MKDA_MetaAnalysis-master/citation_plotter/title_keywords.m | 2,738 | utf_8 | edc8720ccf7205c7b9e581be80cbf4f9 | function [indic,scount,su,words] = title_keywords(titles2)
% [indic,scount,su,words] = title_keywords(titles2)
%
% given a string matrix, stores individual words in each row, and finds the most frequent words.
% Then stores a matrix of which rows have which of the most frequent words.
t = titles2;
% get all words in ... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | Meta_NBC.m | .m | Canlab_MKDA_MetaAnalysis-master/Meta_NBC/Meta_NBC.m | 2,617 | utf_8 | 7e1ebd3a39242a10fecad032a2a7c12c | function [nbc, data, group_data] = Meta_NBC(MC_Setup, terms, test_images)
% [nbc, data, group_data] = Meta_NBC(MC_Setup, terms, test_images)
%
% You will need:
% Inputs: a folder of text files with term labels
%
% MC_Setup = a database saved from an MKDA meta-analysis
% terms = {'pain', 'working.memory', 'emotion'};
% ... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | Meta_SVM_from_mkda.m | .m | Canlab_MKDA_MetaAnalysis-master/Meta_NBC/Meta_SVM_from_mkda.m | 21,231 | utf_8 | 07ec00d1f2470853e576730b0dd27c3d | function PRED = Meta_SVM_from_mkda(DB, fieldname, names_cell, varargin)
% Take output from Meta_Setup (DB) and
% runs a one-vs-one nonlinear SVM classifier, on labels of your choice.
%
% [nbc, data] = meta_SVM_from_mkda(MC_Setup, DB, fieldname, names_cell)
%
% Note: You need the spider package on your matlab path.
%
%... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | plot.m | .m | Canlab_MKDA_MetaAnalysis-master/Meta_NBC/@meta_dataset/plot.m | 8,248 | utf_8 | 0ca444a45ef723b542c04792710b9469 | function plot(metaobj, plotmethod)
% plot(metaobj, [plotmethod])
%
% Plot methods:
% ----------------------------------------
% Plot data matrix
% plot(fmri_data_object)
%
% Plot means by condition
% plot(fmri_data_object, 'means_for_unique_Y')
%
%
if nargin < 2
plotmethod = 'data';
end
switch plotmethod
% =... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | test.m | .m | Canlab_MKDA_MetaAnalysis-master/Meta_NBC/@meta_nbc/test.m | 6,032 | utf_8 | b978f8b3fa176f4b8bec3f508ab72a21 | function obj = test(obj, test_data, varargin)
% obj = test(obj, test_data, varargin)
%
% test_data should be voxels x maps matrix of test data
% can be either binary (i.e., meta-analysis peaks)
% or continuous (e.g., single-subject t- or contrast maps)
% Different methods are used for each data type.
%
%
dobinarize ... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | study_table2.m | .m | Canlab_MKDA_MetaAnalysis-master/studyplotUtility/study_table2.m | 2,119 | utf_8 | 3e04f44fd0e7c109647ce98a7f7b48e7 | function out = study_table(study,varargin)
% function out = study_table(study,varargin)
%
% prints a table of studies; input the study variable, and input columns, in order
% columns with ones and zeros are converted to X's or blanks.
% (not implemented yet; everything must be cell arrays of strings now)
%
% study is a... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | contingency_table.m | .m | Canlab_MKDA_MetaAnalysis-master/studyplotUtility/contingency_table.m | 2,943 | utf_8 | c2695b0f30a645c27fc0af6306ba9525 | function [pt,st] = contingency_table(varargin)
% function [pt,st] = contingency_table(varargin)
%
% makes 2-way contingency tables for pairs of variables
% varargin arguments are variables
% vars must be column cell array vectors containing strings
%
% pt: Table of point (coordinate) counts
% st: Table of unique study... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | study_table.m | .m | Canlab_MKDA_MetaAnalysis-master/studyplotUtility/study_table.m | 2,824 | utf_8 | 2e142d6579edd0402d7f1d7ad4c7fb64 | function study_table(study,varargin)
% function study_table(study,varargin)
%
% prints a table of studies; input the study variable, and input columns, in order
% columns with ones and zeros are converted to X's or blanks.
% (not implemented yet; everything must be cell arrays of strings now)
%
% study is assumed to be... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | pt_given_a_plot.m | .m | Canlab_MKDA_MetaAnalysis-master/plotting_functions/pt_given_a_plot.m | 2,685 | utf_8 | f7e981d383f9b11a34aa43069eb49e74 | function [ind,colors] = pt_given_a_plot(eff,p,legstr,varnamecode,regionnames)
% [indices, colors] = pt_given_a_plot(studycount,totalstudycount,code,varnamecode,regionnames)
%
% tmp =
% pt_given_a_plot(clnew.COUNTS.effpt_given_a,clnew.COUNTS.Ppt_given_a,levels,'PTplot_',clnew.COUNTS(1).clusternames);
%
% given counts, d... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | meta_add_spheres_in_rois.m | .m | Canlab_MKDA_MetaAnalysis-master/plotting_functions/meta_add_spheres_in_rois.m | 3,073 | utf_8 | 2654f006860a1ab832a4693132f8184a | function meta_add_spheres_in_rois(DB, varargin)
% Add spheres to selected ROIs
%
% [p, mesh_struct] = brainstem_slices_3d;
% meta_add_spheres_in_rois(PLOTINFO{1}, 'brainstem');
% colormap gray
%
% DB must be a DB or PLOTINFO struct with these fields:
% - colors
% - xyz
% - condf
%
% (for table)
% - nums
% - descrip
% -... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | dbcluster_contrast_table_xyz.m | .m | Canlab_MKDA_MetaAnalysis-master/cluster_multivariate/dbcluster_contrast_table_xyz.m | 6,393 | utf_8 | f9323ee68547219c8d89c0e626d9a12d | function OUT = db_cluster_table(clusters,DB,varargin)
% function OUT = db_cluster_table(clusters,DB,varargin)
%
% tor wager
% counts studies and contrasts in each cluster
%
% clusters is a struct in which XYZmm field has list of points
% --should be output of database2clusters, which contains all fields
% DB is databas... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | maxcor_npm.m | .m | Canlab_MKDA_MetaAnalysis-master/cluster_multivariate/maxcor_npm.m | 2,364 | utf_8 | 2d44088afe3abc999ab01b0bd254a7a8 | function [mc,stats] = maxcor_npm(X,perms,varargin);
% [mc,stats] = maxcor_npm(X,perms,[c],[MCD robust outlier removal])
%
% X data matrix, columns are variables, rows observations
% c contrast matrix for rotation of X prior to correlation
% contrasts should be rows
% -----------------------------------... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | permute_mtx.m | .m | Canlab_MKDA_MetaAnalysis-master/cluster_multivariate/permute_mtx.m | 12,244 | utf_8 | 52252cf12cf037300ef2220cbcac2d57 | function [OUT] = permute_mtx(data,varargin)
% [OUT] = permute_mtx(data,[meth],[verbose],[niter],[separator])
%
% tor wager
%
% PERMUTATION TEST FOR STOCHASTIC ASSOCIATION BETWEEN COLUMNS
% OF DATA (Ho)
%
% This function takes as input two matrices,
% an actual matrix of data
% an... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | dbcluster_contrast_table.m | .m | Canlab_MKDA_MetaAnalysis-master/cluster_multivariate/dbcluster_contrast_table.m | 8,463 | utf_8 | e961e1c10ed0d30b2738bbee69b78166 | function OUT = db_cluster_table(clusters,DB,varargin)
% function OUT = db_cluster_table(clusters,DB,varargin)
%
% tor wager
% counts studies and contrasts in each cluster
%
% clusters is a struct in which XYZmm field has list of points
% --should be output of database2clusters, which contains all fields
% DB is databas... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | db_cluster_burt_table.m | .m | Canlab_MKDA_MetaAnalysis-master/cluster_multivariate/db_cluster_burt_table.m | 7,918 | utf_8 | 4f4cf06abd54854aa6b2ca0138eae0a3 | function [OUT] = db_cluster_burt_table(clusters,fnames,DB)
% function [OUT] = db_cluster_burt_table(clusters,field list (cell array of strings),DB)
%
% tor wager
% Prints table of studies and lists whether they found activation in each cluster\
%
% warning: does not count separate CONTRASTS, just STUDIES.
% DB is a str... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | cluster_manova.m | .m | Canlab_MKDA_MetaAnalysis-master/cluster_multivariate/cluster_manova.m | 6,759 | utf_8 | 5cf41c3ea19a61206532ba5ebe4bac14 | function cluster_manova(clusters,fnames,varargin)
% function cluster_manova(clusters,fnames,verbose)
% tor wager
%
% clusters is output of clusters2database, with all fields
% from database
% fnames is cell array of strings with names to test
% e.g., {'Rule' 'Task'}
%
% uses stats toolbox
% example: cluster_manova(... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | fuzzy_conf_cluster.m | .m | Canlab_MKDA_MetaAnalysis-master/cluster_multivariate/fuzzy_conf_cluster.m | 3,253 | utf_8 | 862891358f894daaf49e1dfa0ef618df | function OUT = fuzzy_conf_cluster(im,xyz)
% OUT = fuzzy_conf_cluster(im,xyz)
%
% tor wager
%
% input:
% this function takes a set of indicator vectors (im)
% coded as 1's and 0's, and a list of varables (xyz)
%
% output:
% a permutation test for whether there are separate regions
% of the space defined by the colum... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | dbcluster_contrast_table2.m | .m | Canlab_MKDA_MetaAnalysis-master/cluster_multivariate/dbcluster_contrast_table2.m | 6,183 | utf_8 | 824e29b24785b6c5d405afe254a8b126 | function OUT = db_cluster_table(clusters,DB,varargin)
% function OUT = db_cluster_table(clusters,DB,varargin)
%
% tor wager
% counts studies and contrasts in each cluster
%
% clusters is a struct in which XYZmm field has list of points
% --should be output of database2clusters, which contains all fields
% DB is databas... |
github | canlab/Canlab_MKDA_MetaAnalysis-master | bootstrap_mtx.m | .m | Canlab_MKDA_MetaAnalysis-master/cluster_multivariate/bootstrap_mtx.m | 4,032 | utf_8 | c5cd31cf394de00d7487d2ebc2d02f31 | function [OUT] = bootstrap_mtx(data,e,varargin)
% [OUT] = bootstrap_mtx(data,e,[meth],[verbose],[niter])
%
% tor wager
%
% BOOTSTRAP TEST FOR SIG. DIFFERENCE IN COVARIANCE FROM e (Ho)
%
% This function takes as input two matrices,
% an actual matrix of data
% and an expected / null hypothesis
% covariance or correlatio... |
github | liuxianming/cs543_hw-master | boundaryBenchGraphs.m | .m | cs543_hw-master/HM1/hw1/prob_seg/util/boundaryBenchGraphs.m | 2,248 | utf_8 | c3a3b145b9fd12ba99efcb9df6ffac38 | function boundaryBenchGraphs(pbDir, iids)
% function boundaryBenchGraphs(pbDir)
%
% Create graphs, after boundaryBench(pbDir) has been run.
%
% See also boundaryBench.
%
% David Martin <dmartin@eecs.berkeley.edu>
% May 2003
fname = fullfile(pbDir,'scores.txt');
scores = dlmread(fname); % iid,thresh,r,p,f
f... |
github | liuxianming/cs543_hw-master | boundaryBench.m | .m | cs543_hw-master/HM1/hw1/prob_seg/util/boundaryBench.m | 3,743 | utf_8 | 00ac15375b4669323749195739e19485 | function boundaryBench(pbDir,iids,pres,nthresh,fast)
% function boundaryBench(pbDir,pres,nthresh,fast)
%
% Run the boundary detector benchmark on the Pb files found in
% pbDir for the BSDS test images.
%
% See also imgList, bsdsRoot.
%
% David Martin <dmartin@eecs.berkeley.edu>
% March 2003
if nargin<3, nth... |
github | liuxianming/cs543_hw-master | boundaryBenchGraphsMulti.m | .m | cs543_hw-master/HM1/hw1/prob_seg/util/boundaryBenchGraphsMulti.m | 3,482 | utf_8 | 0de26c4b8ac8f977b74078d8bf55f10e | function boundaryBenchGraphsMulti(baseDir, iidsTest)
% function boundaryBenchGraphsMulti(baseDir)
%
% See also boundaryBenchGraphs.
%
% David Martin <dmartin@eecs.berkeley.edu>
% July 2003
presentations = {''};
presNames = {''};
%presentations = {'gray','color'};
%presNames = {'Grayscale','Color'};
%iidsTe... |
github | liuxianming/cs543_hw-master | boundaryBenchHuman.m | .m | cs543_hw-master/HM1/hw1/prob_seg/util/boundaryBenchHuman.m | 2,673 | utf_8 | 581d9142391e4de622846c1cf478fc28 | function boundaryBenchHuman(pbRoot,pres, iids)
% function boundaryBenchHuman(pbRoot,pres)
%
% Compute the human precision/recall data for the BSDS test images.
%
% See also imgList, bsdsRoot.
%
% David Martin <dmartin@eecs.berkeley.edu>
% March 2003
%iids = imgList('test');
cR_total = 0;
sR_total = 0;
... |
github | liuxianming/cs543_hw-master | runThis.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p3/runThis.m | 2,545 | utf_8 | 44f52356d239c12c2633085c86b26db6 | function runThis()
%% Code for CS 543 Homework 4,gch = GraphCut('open', Dc, 10*Sc, Problem 3 - Graph Cut Segmentation
%
%----------------------------------------------------------------
close all;
addpath('./GCmex1.5/')
disp('Reading Image');
im = im2double(imread('cat.jpg'));
sz = size(im);
data = reshape(im, [sz(1) ... |
github | liuxianming/cs543_hw-master | GraphCut.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p3/GCmex1.5/GraphCut.m | 14,471 | utf_8 | 01f6bf97b8cc0b1cfe5e3250a8c3ba37 | function [gch, varargout] = GraphCut(mode, varargin)
%
% Performing Graph Cut energy minimization operations on a 2D grid.
%
% Usage:
% [gch ...] = GraphCut(mode, ...);
%
%
% Inputs:
% - mode: a string specifying mode of operation. See details below.
%
% Output:
% - gch: A handle to ... |
github | liuxianming/cs543_hw-master | collect_eval_bdry.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p1/BSR/bench/benchmarks/collect_eval_bdry.m | 4,045 | utf_8 | 9fed7e6659da0261305de3f92b4a9446 | function [ bestF, bestP, bestR, bestT, F_max, P_max, R_max, Area_PR] = collect_eval_bdry(pbDir)
% function [ bestF, bestP, bestR, bestT, F_max, P_max, R_max, Area_PR ] = collect_eval_bdry(pbDir)
%
% calculate P, R and F-measure from individual evaluation files
%
% Pablo Arbelaez <arbelaez@eecs.berkeley.edu>
f... |
github | liuxianming/cs543_hw-master | match_segmentations2.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p1/BSR/bench/benchmarks/match_segmentations2.m | 1,758 | utf_8 | 32c0a43565bb97cc551f6718eeeca2ee | function [sumRI sumVOI ] = match_segmentations2(seg, groundTruth)
% match a test segmentation to a set of ground-truth segmentations with the PROBABILISTIC RAND INDEX and VARIATION OF INFORMATION metrics.
sumRI = 0;
sumVOI = 0;
[tx, ty] = size(seg);
for s = 1 : numel(groundTruth)
gt = groundTruth{s}.Segme... |
github | liuxianming/cs543_hw-master | evaluateBenchmark.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p1/superpixel_benchmark/evaluateBenchmark.m | 3,028 | utf_8 | 2cd7527838b5de205f404cb1fa2b2e8e | % Superpixel Benchmark
% Copyright (C) 2012 Peer Neubert, peer.neubert@etit.tu-chemnitz.de
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your opti... |
github | liuxianming/cs543_hw-master | getUndersegmentationError.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p1/superpixel_benchmark/getUndersegmentationError.m | 3,518 | utf_8 | 9444ac362cac13431efcd14eec863ed4 | % Superpixel Benchmark
% Copyright (C) 2012 Peer Neubert, peer.neubert@etit.tu-chemnitz.de
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your opti... |
github | liuxianming/cs543_hw-master | evalBPF_plot.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p1/superpixel_benchmark/evalBPF_plot.m | 4,257 | utf_8 | c2f73f68f7f3d095d58ea9baec1ac8f5 | % Superpixel Benchmark
% Copyright (C) 2012 Peer Neubert, peer.neubert@etit.tu-chemnitz.de
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your opti... |
github | liuxianming/cs543_hw-master | loadBSDS500.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p1/superpixel_benchmark/loadBSDS500.m | 4,204 | utf_8 | 52364326e75d055255c2d778ba9afef6 | % Superpixel Benchmark
% Copyright (C) 2012 Peer Neubert, peer.neubert@etit.tu-chemnitz.de
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your opti... |
github | liuxianming/cs543_hw-master | parseBenchmarkParameterFile.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p1/superpixel_benchmark/parseBenchmarkParameterFile.m | 2,971 | utf_8 | 92c52df00bdcbef27314d96c0224b909 | % Superpixel Benchmark
% Copyright (C) 2012 Peer Neubert, peer.neubert@etit.tu-chemnitz.de
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your opti... |
github | liuxianming/cs543_hw-master | appplyTransform.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p1/superpixel_benchmark/appplyTransform.m | 1,740 | utf_8 | 136cb32ae30ebb5f94bc16ca0eeb241b | % Superpixel Benchmark
% Copyright (C) 2012 Peer Neubert, peer.neubert@etit.tu-chemnitz.de
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your opti... |
github | liuxianming/cs543_hw-master | multiLabelImage2boundaryImage.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p1/superpixel_benchmark/multiLabelImage2boundaryImage.m | 1,548 | utf_8 | 5ab8ac8b5747c8931fae12134c437401 | % Superpixel Benchmark
% Copyright (C) 2012 Peer Neubert, peer.neubert@etit.tu-chemnitz.de
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your opti... |
github | liuxianming/cs543_hw-master | getHighContrastColormap.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p1/superpixel_benchmark/getHighContrastColormap.m | 1,404 | utf_8 | 8471d9b6da27e728f75c6790990b6649 | % Superpixel Benchmark
% Copyright (C) 2012 Peer Neubert, peer.neubert@etit.tu-chemnitz.de
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your opti... |
github | liuxianming/cs543_hw-master | evaluateBenchmarkAffine.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p1/superpixel_benchmark/evaluateBenchmarkAffine.m | 4,899 | utf_8 | 8f7c342353d7249fb180d4ce031850a5 | % Superpixel Benchmark
% Copyright (C) 2012 Peer Neubert, peer.neubert@etit.tu-chemnitz.de
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your opti... |
github | liuxianming/cs543_hw-master | runAlgorithm.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p1/superpixel_benchmark/runAlgorithm.m | 4,212 | utf_8 | 4618189da95a5974bc37d4fd51526c3a | % runAlgorithm(filename)
%
% Load benchmark parameter file and run its algorithm and parameter
% setting. Results are stored to disk at the location specified in the
% bpf-file.
%
% Superpixel Benchmark
% Copyright (C) 2012 Peer Neubert, peer.neubert@etit.tu-chemnitz.de
%
% This program is free software: you can red... |
github | liuxianming/cs543_hw-master | prepareBoundaryRecallPlot.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p1/superpixel_benchmark/prepareBoundaryRecallPlot.m | 1,047 | utf_8 | 0dfedd840b028ac722c8288c97335509 | % Superpixel Benchmark
% Copyright (C) 2012 Peer Neubert, peer.neubert@etit.tu-chemnitz.de
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your opti... |
github | liuxianming/cs543_hw-master | prepareRuntimePlot.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p1/superpixel_benchmark/prepareRuntimePlot.m | 1,295 | utf_8 | dfcf2f99795f9f488dadece920099df6 | % Superpixel Benchmark
% Copyright (C) 2012 Peer Neubert, peer.neubert@etit.tu-chemnitz.de
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your opti... |
github | liuxianming/cs543_hw-master | runAlgorithmAffine.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p1/superpixel_benchmark/runAlgorithmAffine.m | 6,128 | utf_8 | 0912b650a2eb13c9e5073c068762a415 | % Superpixel Benchmark
% Copyright (C) 2012 Peer Neubert, peer.neubert@etit.tu-chemnitz.de
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your opti... |
github | liuxianming/cs543_hw-master | compareBoundaryImagesSimple.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p1/superpixel_benchmark/compareBoundaryImagesSimple.m | 2,311 | utf_8 | 99a0fac1997a0290586decc67de7c40a | % Superpixel Benchmark
% Copyright (C) 2012 Peer Neubert, peer.neubert@etit.tu-chemnitz.de
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your opti... |
github | liuxianming/cs543_hw-master | combineMultipleBoundaryImages.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p1/superpixel_benchmark/combineMultipleBoundaryImages.m | 1,273 | utf_8 | 37fbd357dd5c0be19676d8887256b024 | % Superpixel Benchmark
% Copyright (C) 2012 Peer Neubert, peer.neubert@etit.tu-chemnitz.de
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your opti... |
github | liuxianming/cs543_hw-master | parseAffineParameterFile.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p1/superpixel_benchmark/parseAffineParameterFile.m | 2,301 | utf_8 | 8267d58db149c3fc3266861d75fc5fd2 | % Superpixel Benchmark
% Copyright (C) 2012 Peer Neubert, peer.neubert@etit.tu-chemnitz.de
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your opti... |
github | liuxianming/cs543_hw-master | prepareUndersegmentationErrorPlot.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p1/superpixel_benchmark/prepareUndersegmentationErrorPlot.m | 1,073 | utf_8 | dc3fd415f896a50e8a641ec2ec23d8e9 | % Superpixel Benchmark
% Copyright (C) 2012 Peer Neubert, peer.neubert@etit.tu-chemnitz.de
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your opti... |
github | liuxianming/cs543_hw-master | runBenchmark.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p1/superpixel_benchmark/runBenchmark.m | 4,595 | utf_8 | c0a212a9a28a3af874e8f85331eac9b5 | % Superpixel Benchmark
% Copyright (C) 2012 Peer Neubert, peer.neubert@etit.tu-chemnitz.de
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your opti... |
github | liuxianming/cs543_hw-master | main_benchmark.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p1/superpixel_benchmark/main_benchmark.m | 1,035 | utf_8 | 55a73cbba20c008454601d4acf362374 | % Superpixel Benchmark
% Copyright (C) 2012 Peer Neubert, peer.neubert@etit.tu-chemnitz.de
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your opti... |
github | liuxianming/cs543_hw-master | runBenchmarkAffine.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p1/superpixel_benchmark/runBenchmarkAffine.m | 6,551 | utf_8 | 7a104dfee4b51baf5500842eeeee398e | % Superpixel Benchmark
% Copyright (C) 2012 Peer Neubert, peer.neubert@etit.tu-chemnitz.de
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your opti... |
github | liuxianming/cs543_hw-master | main_runAffine.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p1/superpixel_benchmark/main_runAffine.m | 1,517 | utf_8 | 189214808bddc7ab035aaf0b6701acbf | % Superpixel Benchmark
% Copyright (C) 2012 Peer Neubert, peer.neubert@etit.tu-chemnitz.de
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your opti... |
github | liuxianming/cs543_hw-master | segment_box.m | .m | cs543_hw-master/HM4/hw4_supp/hw4_supp/p1/superpixel_benchmark/segmentation_algorithms/segment_box.m | 952 | utf_8 | 068d2a097e0422d88582129cec7a3ff1 | % [S time] = segment_box(image, n)
%
% Perfom box segmentation
%
% Parameters
% image ... Matlab image
% n ... (approximate) number of superpixels
%
% Returns
% S ... segment image
% time ... execution time im ms of algorithm
%
function [S time] = segment_box(image,n)
if ~exist('n','... |
github | liuxianming/cs543_hw-master | plotmatches.m | .m | cs543_hw-master/HM3/hw3_codes/prob3/plotmatches.m | 10,221 | utf_8 | a701b7d74819dd725219aa884d6f7f18 | function h=plotmatches(I1,I2,P1,P2,matches,varargin)
% PLOTMATCHES Plot keypoint matches
% PLOTMATCHES(I1,I2,P1,P2,MATCHES) plots the two images I1 and I2
% and lines connecting the frames (keypoints) P1 and P2 as specified
% by MATCHES.
%
% P1 and P2 specify two sets of frames, one per column. The first
% t... |
github | chunyeow/openairinterface5g-master | gen_7_5_kHz.m | .m | openairinterface5g-master/openair1/PHY/MODULATION/gen_7_5_kHz.m | 3,298 | utf_8 | a08e730b234a112cbf6aac5b44c3af8b |
function [] = gen_7_5_kHz()
[s6_n2, s6_e2] = gen_sig(6);
[s15_n2, s15_e2] = gen_sig(15);
[s25_n2, s25_e2] = gen_sig(25);
[s50_n2, s50_e2] = gen_sig(50);
[s75_n2, s75_e2] = gen_sig(75);
[s100_n2, s100_e2] = gen_sig(100);
fd=fopen("kHz_7_5.h","w");
fprintf(fd,"s16 s6n_kHz_7_5[%d]__attribute__((aligned(16))) = {",lengt... |
github | chunyeow/openairinterface5g-master | f_tls_diag.m | .m | openairinterface5g-master/targets/PROJECTS/TDDREC/f_tls_diag.m | 1,272 | utf_8 | 443132469284a3d4d0b38bd5fb7d0522 | %
% PURPOSE : TLS solution for AX = B based on SVD assuming X is diagonal
%
% ARGUMENTS :
%
% A : observation of A
% B : observation of B
%
% OUTPUTS :
%
% X : TLS solution for X (Diagonal)
%
%**********************************************************************************************
% ... |
github | chunyeow/openairinterface5g-master | f_tls_ap.m | .m | openairinterface5g-master/targets/PROJECTS/TDDREC/f_tls_ap.m | 1,368 | utf_8 | 223603e551ebede67ff13452e95097b1 | %
% PURPOSE : TLS solution for AX = B based on alternative projection
%
% ARGUMENTS :
%
% A : observation of A
% B : observation of B
%
% OUTPUTS :
%
% X : TLS solution for X
%
%**********************************************************************************************
% ... |
github | chunyeow/openairinterface5g-master | f_ofdm_rx.m | .m | openairinterface5g-master/targets/PROJECTS/TDDREC/f_ofdm_rx.m | 1,545 | utf_8 | ade01596524abbe660fc84064cbb4724 | %
% PURPOSE : OFDM Receiver
%
% ARGUMENTS :
%
% m_sig_R : received signal with dimension ((d_N_FFT+d_N_CP)*d_N_ofdm) x d_N
% d_N_FFT : total carrier number
% d_N_CP : extented cyclic prefix
% d_N_OFDM : OFDM symbol number per frame
% v_active_rf : active RF antenna indicator
%
% OUTPUTS :
%
% m_sym_R ... |
github | chunyeow/openairinterface5g-master | f_ch_est.m | .m | openairinterface5g-master/targets/PROJECTS/TDDREC/f_ch_est.m | 1,711 | utf_8 | f583032bb1c37167a7ff2a029a629de9 | %
% PURPOSE : channel estimation using least square method
%
% ARGUMENTS :
%
% m_sym_T : transmitted symbol, d_N_f x d_N_ofdm x d_N_ant_act x d_N_meas
% m_sym_R : received symbol, d_N_f x d_N_ofdm x d_N_ant_act x d_N_meas
% d_N_meas : number of measurements
%
% OUTPUTS :
%
% m_H_est : estimation o... |
github | chunyeow/openairinterface5g-master | f_ofdm_tx.m | .m | openairinterface5g-master/targets/PROJECTS/TDDREC/f_ofdm_tx.m | 1,997 | utf_8 | 042917cd72b493f1384cbc5fa2fa2de5 | %
% PURPOSE : OFDM Transmitter
%
% ARGUMENTS :
%
% d_M : modulation order
% d_N_f : carrier number carrying data
% d_N_FFT : total carrier number
% d_N_CP : extented cyclic prefix
% d_N_OFDM : OFDM symbol number per frame
% v_active_rf : active RF antenna indicator
% d_amp : amplitude
%
% O... |
github | chunyeow/openairinterface5g-master | f_ofdm_rx.m | .m | openairinterface5g-master/targets/PROJECTS/TDDREC/v4_CH_EST/f_ofdm_rx.m | 1,545 | utf_8 | 798a54f027b266189ab1fdc57569dac1 | %
% PURPOSE : OFDM Receiver
%
% ARGUMENTS :
%
% m_sig_R : received signal with dimension ((d_N_FFT+d_N_CP)*d_N_ofdm) x d_N
% d_N_FFT : total carrier number
% d_N_CP : extented cyclic prefix
% d_N_OFDM : OFDM symbol number per frame
% v_active_rf : active RF antenna indicator
%
% OUTPUTS :
%
% m_sym_R ... |
github | chunyeow/openairinterface5g-master | f_ch_est.m | .m | openairinterface5g-master/targets/PROJECTS/TDDREC/v4_CH_EST/f_ch_est.m | 1,708 | utf_8 | ad1741afb57ea0bbc0da1f1f0d410ce6 |
% PURPOSE : channel estimation using least square method
%% ARGUMENTS :
%
% m_sym_T : transmitted symbol, d_N_f x d_N_ofdm x d_N_ant_act x d_N_meas
% m_sym_R : received symbol, d_N_f x d_N_ofdm x d_N_ant_act x d_N_meas
% d_N_meas : number of measurements
%
% OUTPUTS :
%
% m_H_est : estimation of s... |
github | chunyeow/openairinterface5g-master | f_ofdm_tx.m | .m | openairinterface5g-master/targets/PROJECTS/TDDREC/v4_CH_EST/f_ofdm_tx.m | 1,997 | utf_8 | 52b00cfe39a99e4f6d079fcc3cdad1f8 | %
% PURPOSE : OFDM Transmitter
%
% ARGUMENTS :
%
% d_M : modulation order
% d_N_f : carrier number carrying data
% d_N_FFT : total carrier number
% d_N_CP : extented cyclic prefix
% d_N_OFDM : OFDM symbol number per frame
% v_active_rf : active RF antenna indicator
% d_amp : amplitude
%
% O... |
github | chunyeow/openairinterface5g-master | genorthqpskseq.m | .m | openairinterface5g-master/targets/PROJECTS/TDDREC/v0/genorthqpskseq.m | 1,143 | utf_8 | 330b0dc2a723aa7a373d8a0cd01fcabb | # % Author: Mirsad Cirkic
# % Organisation: Eurecom (and Linkoping University)
# % E-mail: mirsad.cirkic@liu.se
function [carrierdata, s]=genorthqpskseq(Ns,N,amp)
if(N!=512*150)
error('The sequence length must be 76800.');
endif
s = zeros(N,Ns);
H=1; for k=1:log2(128) H=[H H; H -H]; end; H=H(:,1:120);
i=1; while... |
github | chunyeow/openairinterface5g-master | genrandpskseq.m | .m | openairinterface5g-master/targets/PROJECTS/TDDREC/v0/genrandpskseq.m | 776 | utf_8 | 5cb33d8e20311847ffaa652cf70a4865 | % Author: Mirsad Cirkic
% Organisation: Eurecom (and Linkoping University)
% E-mail: mirsad.cirkic@liu.se
function [carrierdata, s]=genrandpskseq(N,M,amp)
if(mod(N,640)~=0)
error('The sequence length must be divisible with 640.');
end
s = zeros(N,1);
MPSK=exp(sqrt(-1)*([1:M]*2*pi/M+pi/M));
% OFDM sequence with ... |
github | chunyeow/openairinterface5g-master | rfldec.m | .m | openairinterface5g-master/targets/ARCH/EXMIMO/USERSPACE/OCTAVE/rfldec.m | 363 | utf_8 | 24448e69682b1f6a6ea652c2426b08f7 | ## Decodes rf_local values: [ txi, txq, rxi, rxq ] = rfldec(rflocal)
## Author: Matthias Ihmig <ihmig@solstice>
## Created: 2012-12-05
function [ txi, txq, rxi, rxq ] = rfldec(rflocal)
txi = mod(floor( rflocal /1 ), 64)
txq = mod(floor( rflocal /64), 64)
rxi = mod(floor( rflocal /4096), 64)
rxq = mo... |
github | chunyeow/openairinterface5g-master | rfl.m | .m | openairinterface5g-master/targets/ARCH/EXMIMO/USERSPACE/OCTAVE/rfl.m | 225 | utf_8 | 9ad201a94d01db3e65ecedb02252ca19 | ## Composes rf_local values: rfl(txi, txq, rxi, rxq)
## Author: Matthias Ihmig <ihmig@solstice>
## Created: 2012-12-05
function [ ret ] = rfl(txi, txq, rxi, rxq)
ret = txi + txq*2^6 + rxi*2^12 + rxq*2^18;
endfunction
|
github | kaiqzhan/ardupilot-raspilot-master | RotToQuat.m | .m | ardupilot-raspilot-master/libraries/AP_NavEKF/Models/Common/RotToQuat.m | 288 | utf_8 | 9239706354267c8f5f2a29f992c07de9 | % convert froma rotation vector in radians to a quaternion
function quaternion = RotToQuat(rotVec)
vecLength = sqrt(rotVec(1)^2 + rotVec(2)^2 + rotVec(3)^2);
if vecLength < 1e-6
quaternion = [1;0;0;0];
else
quaternion = [cos(0.5*vecLength); rotVec/vecLength*sin(0.5*vecLength)];
end |
github | kaiqzhan/ardupilot-raspilot-master | NormQuat.m | .m | ardupilot-raspilot-master/libraries/AP_NavEKF/Models/Common/NormQuat.m | 198 | utf_8 | ed913e87efc9194a2c52b266fced8da7 | % normalise the quaternion
function quaternion = normQuat(quaternion)
quatMag = sqrt(quaternion(1)^2 + quaternion(2)^2 + quaternion(3)^2 + quaternion(4)^2);
quaternion(1:4) = quaternion / quatMag;
|
github | kaiqzhan/ardupilot-raspilot-master | QuatToEul.m | .m | ardupilot-raspilot-master/libraries/AP_NavEKF/Models/Common/QuatToEul.m | 436 | utf_8 | c19c9235052d99b8b943a7157e83fc94 | % Convert from a quaternion to a 321 Euler rotation sequence in radians
function Euler = QuatToEul(quat)
Euler = zeros(3,1);
Euler(1) = atan2(2*(quat(3)*quat(4)+quat(1)*quat(2)), quat(1)*quat(1) - quat(2)*quat(2) - quat(3)*quat(3) + quat(4)*quat(4));
Euler(2) = -asin(2*(quat(2)*quat(4)-quat(1)*quat(3)));
Euler(3) =... |
github | fuweixiao/cuda_inpainting-master | fillPatch.m | .m | cuda_inpainting-master/matlab/fillPatch.m | 987 | utf_8 | 5c526d2ab81973301f7a08e4a90a4722 | function [new_img] = fillPatch(old_img, nodeMidX, nodeMidY, listPatchX, listPatchY, label)
% patch & node size
radius = 16;
patchW = radius; patchH = radius;
nodeW = patchW / 2; nodeH = patchH / 2;
[hh, ww, len] = size(label);
new_img = old_img;
for i = 1:hh
for j = 1:ww
if (label <= 0)
display... |
github | fluongo/MATLAB_calcium-master | CellsortPlotPCspectrum_v2.m | .m | MATLAB_calcium-master/workflow/CellsortPlotPCspectrum_v2.m | 2,659 | utf_8 | 9e85199b8fe87b08f41d31e3b489551d | function [pcanorm] = CellsortPlotPCspectrum_v2(fn, CovEvals, PCuse)
% CellsortPlotPCspectrum(fn, CovEvals, PCuse)
%
% Plot the principal component (PC) spectrum and compare with the
% corresponding random-matrix noise floor
%
% Inputs:
% fn - movie file name. Must be in TIFF format.
% CovEvals - eigenvalues of the ... |
github | fluongo/MATLAB_calcium-master | CellsortPlotPCspectrum.m | .m | MATLAB_calcium-master/workflow/CellsortPlotPCspectrum.m | 2,464 | utf_8 | 18cfdd6e9244ddb043ebd7a86be73608 | function [pcanorm] = CellsortPlotPCspectrum(fn, CovEvals, PCuse)
% CellsortPlotPCspectrum(fn, CovEvals, PCuse)
%
% Plot the principal component (PC) spectrum and compare with the
% corresponding random-matrix noise floor
%
% Inputs:
% fn - movie file name. Must be in TIFF format.
% CovEvals - eigenvalues of the cov... |
github | fluongo/MATLAB_calcium-master | CellsortPCA_singleframes.m | .m | MATLAB_calcium-master/workflow/CellsortPCA_singleframes.m | 13,500 | utf_8 | 0b7534cdf1ae2051fb3a5ea67e078dfd | function [mixedsig, mixedfilters, CovEvals, covtrace, movm, ...
movtm] = CellsortPCA_singleframes(fn, flims, nPCs, dsamp, outputdir, badframes)
% [mixedsig, mixedfilters, CovEvals, covtrace, movm, movtm] = CellsortPCA(fn, flims, nPCs, dsamp, outputdir, badframes)
%
% CELLSORT
% Read TIFF movie data and perform sin... |
github | yu-jiang/Paper_Automatica2012_CTLTI-master | Jiang2012Automatica.m | .m | Paper_Automatica2012_CTLTI-master/Jiang2012Automatica.m | 5,918 | utf_8 | fd35bee11aa913b28195817b63cb117d | % Code for the paper "Computational adaptive optimal control with an
% application to a car engine control problem", Yu Jiang and Zhong-Ping
% Jiang,vol. 48, no. 10, pp. 2699-2704, Oct. 2012.
% Copyright 2011-2014 Yu Jiang, New York University.
function []=Jiang2012Automatica()
clc;
x_save=[];
t_save=[];
fla... |
github | yu-jiang/Paper_Automatica2012_CTLTI-master | Jiang2012Automatica_optimized_version.m | .m | Paper_Automatica2012_CTLTI-master/Jiang2012Automatica_optimized_version.m | 5,110 | utf_8 | dcbd4e40b52b0396bad43ba7c4e73062 | % Code for the paper "Computational adaptive optimal control with an
% application to a car engine control problem", Yu Jiang and Zhong-Ping
% Jiang,vol. 48, no. 10, pp. 2699-2704, Oct. 2012.
% Copyright 2011-2014 Yu Jiang, New York University.
function []=Jiang2012Automatica()
clc;
x_save=[];
t_save=[];
flag=1; % 1... |
github | Ciaran1981/SeAMS-master | imwritesc.m | .m | SeAMS-master/Utilities/MatlabFns/Misc/imwritesc.m | 1,398 | utf_8 | 68650e74e308c991970251d3bed6b85f | % IMWRITESC - Writes an image to file, rescaling if necessary.
%
% Usage: imwritesc(im,name)
%
% Floating point image values are rescaled to the range 0-1 so that no
% overflow occurs when writing 8-bit intensity values. The image format to
% use is determined by MATLAB from the file ending.
% If the image ... |
github | Ciaran1981/SeAMS-master | circlesineramp.m | .m | SeAMS-master/Utilities/MatlabFns/Misc/circlesineramp.m | 5,528 | utf_8 | 07bd0de1d4131398674bfe94cce19c1d | % CIRCLESINERAMP Generates test image for evaluating cyclic colour maps
%
% Usage: [im, alpha] = circlesineramp(sze, amp, wavelen, p, hole);
% [im, alpha] = circlesineramp;
%
% Arguments: sze - Size of test image. Defaults to 512x512.
% amp - Amplitude of sine wave. Defaults to pi/10
% ... |
github | Ciaran1981/SeAMS-master | showsurf.m | .m | SeAMS-master/Utilities/MatlabFns/Misc/showsurf.m | 3,887 | utf_8 | 1f50f8abbac642a925b579a58b8e724d | % SHOWSURF - shows parametric surface in a convenient way
%
% This function wraps up the commands I usually use to display a surface.
%
% The surface is displayed using SURFL with interpolated shading, in my
% favourite colormap of 'copper', with rotate3d on, and axis vis3d set.
%
% Usage can be any of the following
% ... |
github | Ciaran1981/SeAMS-master | randmap.m | .m | SeAMS-master/Utilities/MatlabFns/Misc/randmap.m | 731 | utf_8 | 620b6965c1e7db6de65c332753df18f4 | % RANDMAP Generates a colourmap of random colours
%
% Useful for displaying a labeled segmented image
%
% map = randmap(N)
%
% Argument: N - Number of elements in the colourmap. Default = 1024.
% This ensures images that have been segmented up to 1024
% regions will (well, are more l... |
github | Ciaran1981/SeAMS-master | viewlabspace2.m | .m | SeAMS-master/Utilities/MatlabFns/Misc/viewlabspace2.m | 5,039 | utf_8 | 27e0e43cd469627a1e9eefb0e5ad2119 | % VIEWLABSPACE2 Visualisation of L*a*b* space
%
% Usage: viewlabspace2(dtheta)
%
% Argument: dtheta - Optional specification of increment in angle of plane
% through L*a*b* space. Defaults to pi/30
%
% Function allows interactive viewing of a sequence of images corresponding to
% different ve... |
github | Ciaran1981/SeAMS-master | chirplin.m | .m | SeAMS-master/Utilities/MatlabFns/Misc/chirplin.m | 1,589 | utf_8 | ec0a1da79fe966d9276fbd30096a364d | % CHIRPLIN Generates linear chirp test image
%
% The test image consists of a linear chirp signal in the horizontal direction
% with the amplitude of the chirp being modulated from 1 at the top of the image
% to 0 at the bottom.
%
% Usage: im = chirplin(sze, f0, k, p)
%
% Arguments: sze - [rows cols] specifying s... |
github | Ciaran1981/SeAMS-master | supertorus.m | .m | SeAMS-master/Utilities/MatlabFns/Misc/supertorus.m | 2,444 | utf_8 | 91c1e7e27c0219d233582240dcb7c17e | % SUPERTORUS - generates a 'supertorus' surface
%
% Usage:
% [x,y,z] = supertorus(xscale, yscale, zscale, rad, e1, e2, n)
%
% Arguments:
% xscale, yscale, zscale - Scaling in the x, y and z directions.
% e1, e2 - Exponents of the x and y coords.
% rad - Mean radius of torus.... |
github | Ciaran1981/SeAMS-master | cmyk2rgb.m | .m | SeAMS-master/Utilities/MatlabFns/Misc/cmyk2rgb.m | 890 | utf_8 | 6d12e2501c39dec555e670c4190cf6e7 | % CMYK2RGB Basic conversion of CMYK colour table to RGB
%
% Usage: map = cmyk2rgb(cmyk)
%
% Argument: cmyk - N x 4 table of cmyk values (assumed 0 - Returns)
% 1: map - N x 3 table of RGB values
%
% Note that you can use MATLAB's functions MAKECFORM and APPLYCFORM to
% perform the conversion. However I find tha... |
github | Ciaran1981/SeAMS-master | graymap.m | .m | SeAMS-master/Utilities/MatlabFns/Misc/graymap.m | 865 | utf_8 | b4f07ef527be1d1937f6ade25c5c67ac | % GRAYMAP Generates a gray colourmap over a specified range
%
% Usage: map = graymap(gmin, gmax, N)
%
% Arguments: gmin, gmax - Minimum and maximum gray values desired in
% colourmap. Defaults are 0 and 1
% N - Number of elements in the colourmap. Default = 256.
%
% See al... |
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