sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
b5343edef89d8d46662cb14efab675736ebd8ef50d3fe5a06b73bd53ba0358c3 | MATLAB | 1,336 | 36 | %EARTH Black-green-white colormap
%
% Examples:
% map = earth;
% map = earth(len);
% B = earth(A);
% B = earth(A, lims);
%
% A black to white colormap with several distinct shades, most of which
% have a green or brown tint. This colormap converts linearly to grayscale
% when printed in black & white... |
b652cde092804b8f0189103e0900b7a2c9f8acf162c091da8d32f677993916d0 | MATLAB | 1,336 | 39 | function [x, y, center_x, center_y, radius] = calc_geometry(doShow, handles)
%%% Function that calculates the radius and the center of the RIFF given
% port location, stored in offline file 'six_mid_points_binned.mat'
if(nargin > 1) % When calc_geometry.m is called from the RatTracker, supplied by the 'handles' ... |
7f3b40909f611d25b0de04e90829432ae6c61980de0f488044285cebfc933453 | MATLAB | 1,337 | 60 | function [audio_ts, audio, video_ts, video] = extractmedia(fl, time_start, time_stop)
% default to empty
if ~exist('time_start', 'var')
time_start = [];
end
if ~exist('time_stop', 'var')
time_stop = [];
end
% use mex file to extract time stamps and aligned audio
info = extractaudio(fl);
audio_ts = info.audio_... |
c65ba1e9fec74d45ac5e0a55a75309021805875d6b8535f97260c64c59714c5a | MATLAB | 1,337 | 60 | function [audio_ts, audio, video_ts, video] = extractmedia(fl, time_start, time_stop)
% default to empty
if ~exist('time_start', 'var')
time_start = [];
end
if ~exist('time_stop', 'var')
time_stop = [];
end
% use mex file to extract time stamps and aligned audio
info = extractaudio(fl);
audio_ts = info.audio_... |
729f2655eedb8ae0327b123259cdf3614ee69c305971ac5cc28864251b7e226c | MATLAB | 1,339 | 30 | function [image_arr, LED_arr] = remove_last_black_frames_with_no_LED(image_arr, LED_arr)
% Function remove_last_black_frames_with_no_LED removes empty images and their corresponding emtpy LED
% values from the image array
%
% Inputs:
% image_arr - (PxPxN matrix) - images of rats with LEDs in t... |
e0a2f8c402f3e0a096d81e35a2d3b2727dd161d883335ce004b1b4edc6de03a4 | MATLAB | 1,342 | 40 | function m_sig = set(m_sig,varargin)
% SET Set Main_signal properties and return the updated object
% Property names are:
% Level_comp, STime_comp, ETime_comp, Ramp_comp, Envelope_list.
property_argin = varargin;
while length(property_argin) >= 2,
prop = property_argin{1};
if ~isa(prop,'char')
treat_err... |
bf2ab514199f261d59aab6fe3e321cca58e90aecf4b1fd074ac00686feda537c | MATLAB | 1,343 | 38 | function samp_points=synth(sig,samp_rate,trial_dur,varargin)
% SYNTH is GAP synth function.
% SAMP_POINTS=SYNTH(SIG,SAMP_RATE,TRIAL_DUR,VARARGIN) Samples the signal
% according to the givan SAMP_RATE and TRIAL_DUR. Returns the sampled
% points.
switch nargin
case 4
params=varargin{:};
if ~(isempty... |
cad6d2ff737b4b8b7e424692c28eac532dcb478bb1255afa0e4f5d9fbb9314e8 | MATLAB | 1,346 | 39 | function plot_paired_graphs(data, ylabel_string, ylimit)
number_subjects = size(data,1);
%data = data(:,2:end) - repmat(data(:,1),1,size(data,2)-1);
figure
ax = axes;
bar(1, mean(data(:,1,1)), 'BarWidth', 1);
hold
bar(2, mean(data(:,1,2)), 'BarWidth', 1);
for i=2:size(data,2)
bar(3*(i-1)+1, mean(data(:,i,1)), '... |
93db6b97b81932eab9d69db46656ec0510b9c76b1b0c7f5d2b5f1cf88d6d4613 | MATLAB | 1,347 | 49 | %load PET/SPECT data
load('PETdata_HCP.mat')
%permutation 5000 times
permN = 5000;
%%
%load brain statistic values permuted 5000 times
load('t_perm_5000_area_l5.mat')
%percentage of missing: allowed missing rate in each HCP region
pert = 0.5;
%region size
n = zeros(length(dn),1);
%spearman's correlation
s... |
7d5192a19d24d06d5a0ff98f24ec17dcab6332da88528e3654f084b9622fa3d8 | MATLAB | 1,352 | 47 | function [countsNoNoise] = gui_FFTfilter(counts, gauss_blur_radius, spectral_radius, scaling_factor)
% Scale the image
image = counts * scaling_factor;
% Mean of all values
mean_value = mean(image(:));
% Center the distribution
image = image - mean_value;
% Add custom blur
... |
cd127a7a78c2375149ffc5d065a0327023e4851aa025f2111d295310f2e0a4fe | MATLAB | 1,355 | 40 | % r = getRadAvg(im)
% ---------------------------------------
%
% Return the radial average of input square image im
%
% Inputs:
% im Square image
%
% Outputs:
% r Radial average
%
% ---------------------------------------
%
% Copyright © 2018 Adrien Descloux - adrien.descloux@epfl.ch,
% Ecole Po... |
7588a67dea7f7d8418001756b684ad2b30b1fbddd5f2cfecad9cad17bd809bda | MATLAB | 1,362 | 41 | function [p_past,p_joint,p_present] = est_p_table(X,N_s,tau, pow_vec)
%-------------------------------------------------------------------------------------------------
% PURPOSE: estimate probability distributions of past (p_past), present (p_present) and
% joint distribution of past and present (joint) from discret... |
29112e818a754931440764c4f267e7e61d6bfa1f6533e363dc0ec43e603c3399 | MATLAB | 1,365 | 55 | function tint=tInterval_Calc(vect, CI)
% tInterval_Calc - confidence interval based on the t-distribution
%
% function tint = NBP.tInterval_Calc(vect, CI)
%
%
% Purpose
% Calculate the t-interval about the mean to a given confidence
% level (CI). Note that nans do not contribute to the calculation
% of the sample size ... |
4327d4bfaad8bd1b54f59b114409a42f56eea49c388e31d8ace46f26f2f36f46 | MATLAB | 1,375 | 32 | function val=get(l_coord,prop_name)
% GET Get Line Coordinator property from the specified object
% and return the value. Property names are:
% Coordinator - the coordinator object
% Basic_line - the Basic line this Coordinator handle
% Components - list of the components of the Basic line this Coordinator handle
% Nu... |
a1aa9519903f688b26bba624ac31bc7666aab146a61c4fdd957d116ef741cb37 | MATLAB | 1,378 | 49 | % Time-frequency analysis
% 'TF' is time-frequency spectra of data.
% 'TF' will be a matrix (time * frequency)
% 'data' should be a vector
% 'sf' is a sampling rate
% 'wnd_size' is a window size of data
% 'baseline' is a period for baseline correction of analysis
% 'f_scale' is a freqeuncy resolution of analysi... |
dc0bbf0fd0a671cf6352a9705ffe468cfb2b205f557f0d57e16ec9642e46c921 | MATLAB | 1,378 | 44 | function [areaTable, centData] = setFuncArea(inputvector)
loclen = inputvector(1)-3;
locx = inputvector(2:loclen/2+1);
locy = inputvector(loclen/2+2:loclen+1);
x0 = round(mean(locx));%inputvector(loclen+2); % center x
y0 = round(mean(locy));%inputvector(loclen+3); % center y
R = inputvector(loclen+4); % radius another ... |
f4222cc77b223617e88f29ef3267f0ba07d0509b5e1e2184e6f1111ca6c0ea8d | MATLAB | 1,378 | 57 | function result=linept(matrice, X1, Y1, X2, Y2)
% Connect two pixels in a matrice with 1
%
% Command line
% ------------
% result=linept(matrice, X1, Y1, X2, Y2)
% matrice : matrice where I'll write
% (X1, Y1), (X2, Y2) : points to connect
% result : matrix + the line
%
% Note
% ----
% matrice can c... |
0568b6fcea3fdba124c3f1c86c373dd4ead252f6cc53fd6afa9acf6488eaf82c | MATLAB | 1,380 | 35 | %% Fowlkes-Mallows by N Clusters
stabilityFigure = figure();
hold on;
for iMeas = 1:5
d1 = RSdata.d.(ephysMeasures{iMeas});
Badj = (d1.clustB-d1.clustEB)./(1-d1.clustEB);
q = quantile(Badj,[.25 .5 .75],2);
errorbar(d1.clustNs(1:13)+(iMeas-3)/10,q((1:13),2),q((1:13),2)-q((1:13),1),q((1:13),3)-q(... |
439a1af127ed34558843d8f55dda3552fd80eb8d3aa002bb3b1e55f226094b30 | MATLAB | 1,382 | 46 |
function [] = SampleNplot(temp, figN)
timez = temp.input;
auc = temp.aucs;
acc = temp.accs;
spec = temp.specs;
sens = temp.senss;
xs = temp.xxs;
ys = temp.yys;
figure(figN); hold off; clf;
intervals= linspace(0, 1, 1000);
mean_curve =[];
for j=1:size(xs,1)
figure(figN); plot(xs{j... |
7ac1080e6def9fa7251b326059bf329bc9d32d394ef1da93fe357cbc2b447034 | MATLAB | 1,385 | 75 | function fb_plot_3dtime(DATA,T,varargin)
%fb_plot_3dtime plots a 3-d trajectory over time using a colormap.
%
% fb_plot_3dtime(DATA,T,varargin)
%
% DATA
% samples x dimensions matrix with at least 3 dimensions containing
% the data to plot
%
% T
% nsamples vector that specifies the point in time associated with
% each... |
fbcc39d61fc7cf9a0ae8ea016fd304439d10e12afaa4db3ead797dfb13abe88b | MATLAB | 1,386 | 41 | function comp = Freq_comp(varargin)
% Freq_comp_comp class constructor.
% c= Freq_comp_comp(STATIC_VALUE) creates a Freq_comp object which is a
% Signal component representing it's frequency.
global FREQ_COMP_DEFAULT;
FREQ_COMP_DEFAULT=1500;
if nargin==0
comp.name='Freq_comp';
s_comp=Sig_comp(FREQ_C... |
9f236afc342db88c1164d7ced06432e4b434d6491b52f0f464d80a7bdda48a4e | MATLAB | 1,387 | 47 | %%
% This is the analytical derivative of the Siegert function, as found in
% Helias, M., Tetzlaff T., and Diesmann, M. (2013; Appendix)
%
% Contains both the drates/dmu and drates/sigma terms
%%
function [W_stability] = Siegert_stability_analytical(firing_rates, mu_ext, var_ext,...
tau_m,tau_r,V_th,V_r,J,Npop,J_si... |
f3ec5543c82e2abb05e71c2cd168fc375c4cde28b195e19849f095cc0ca36f89 | MATLAB | 1,388 | 38 | function [embedMn,embedSD,embedDistMn,embedDistSD,embedDistCorr,elbows,pctNan,eVals,bootEmb] = bootstrapEmbedding(adjMat,nBoot,embedArgs)
nNode = size(adjMat,1);
nSubj = size(adjMat,3);
meanAdjMat = mean(adjMat,3,'omitNan');
meanEmb = Embedding(meanAdjMat,embedArgs{:});
meanEmbDistVec = ecogu... |
72a8d9d7f208e0e9e6f24e16d4351840f698da29c681026a7472f7b1bf35271d | MATLAB | 1,390 | 61 |
clc
close all
clear
figure('Units','normalized','OuterPosition',[.1 .1 .08 .2])
plotit(68)
figure('Units','normalized','OuterPosition',[.18 .1 .08 .2])
plotit(28)
figure('Units','normalized','OuterPosition',[.26 .1 .08 .2])
plotit(12)
% =========================================================
function plotit(n... |
6e64ef3673ee834fec199af9da1abf709b170620208af7d9a4c02af45a233da3 | MATLAB | 1,395 | 39 | function values = get_trial_values(s_comp,varargin)
% GET_TRIAL_VALUES(S_COMP) returns an array of values that would be generated for
% this Signal component (s_comp) according to it's internal state.
% values = GET_TRIAL_VALUES(S_COMP,RANDOM_INDICES_ARRAY) returns an array of values
% for the given Signal component w... |
1c2bc01cf161ba7ddc95b2f538e7f4abc9ed46f3b00603da8e3d52cd3cb1f7bc | MATLAB | 1,399 | 45 | for ind=1:1
%/
[Result,pData,DataCapture] =AO_GetChannelData(10256);
if(DataCapture~=0)
DataCapture=0;
spk = pData(1:DataCapture);
spk=double(spk);
spkBlocks = reshape(spk,spk(1),length(spk)/spk(1));
spkTimeStamps = spkBlocks(5:6,:);
blockNum=1;
firstTSSpk=bin2dec([dec2bin(mod(double(spkTimeStamps(2,blockNum)),2^16... |
fd7d73e40031d36bf2fcb278e4f1ba1c1a5fc051db4c7c32894273817413f4bc | MATLAB | 1,401 | 56 | %% std ratio of pursuit directions
% Fig. 3, e-f
% load behavioral data
load('behavior.mat');
% behavioral result - Monkey A
direction = direction_day_prior_A;
ab1c100=[];ab2c100=[];ab1c008=[];ab2c008=[];
for a = 1:size(direction,1)
ab1c100 = [ab1c100; std(direction{a,1})];
ab2c100 = [ab2c100; std(direction{... |
4effc01db4cc9e512797d6f3844d98af867946338f9f24d4e6d548ba08d07740 | MATLAB | 1,410 | 48 | function res=check_meta_params(meta,varargin)
% res=CHECK_PARAMS(PARAM1,VAL1...) checks the validity for a MetaBlock object.
% Checks that PARAM1 field can hold the given VAL1 value and the same for
% PARAM2,VAL2 and so on.
% If all params are legal - returns 1. Otherwise returns 0.
global META_RUN_MODE_NAMES;
res=1;... |
805a6315972525bbaac1bab56b15e2b18e0dad5bee8fc4ed6e6dc7a821eddb4c | MATLAB | 1,413 | 48 | clear
close all
PostSetup('BrockHome')
flag_SaveFigs = false;
global STIMDIR
cd(STIMDIR)
load('151221_E_eD_LFP')
brfsTrials = strcmp(STIM.task,'brfs');
% spectrogram conventions
nfft = 2^8;
rsampt = 0.0010; % 1 kHz
frange = [1 100]; % look at 1 to 100 Hz only
fs = floor(1/rsampt);
overlap = nfft-1;
poststim = 1:120... |
f24d093dd951ae88dbea24ab55d8352a197b8b99370317eb5927a21a9e043375 | MATLAB | 1,419 | 48 | function remapSegmentationLabels( in_seg_nii, in_label_mapping, output_label_mapping, out_folder)
%Remaps segmentation labels using a label mapping text file, writing out
%individual images and a combined label image. The input indices, in the label
%mapping text file are assumed to be the line numbers (1:end).
%in_... |
8bd6bac237bdc777e61fd2292c14985b8ebfb351a2e6bed35f18504d7e693a97 | MATLAB | 1,420 | 42 | % cc = getCorrcoef(I1,I2,c1,c2)
% ---------------------------------------
%
% Return the normalized correlation coefficient expressed in Fourier space
%
% Inputs:
% I1 Complex Fourier transfom of image 1
% I2 Complex Fourier transfom of image 2
%
% Outputs:
% cc Normalized cross-correlation... |
7f7c8b218bb493445216e7982c3cf8ab32e3b911c5899a9ae657805dafcd5582 | MATLAB | 1,421 | 79 | function [mu,mask]=kmeans(ima,k)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% kmeans image segmentation
%
% Input:
% ima: grey color image
% k: Number of classes
% Output:
% mu: vector of class means
% mask: clasification image mask
%
% Autho... |
f7b659aa93682a3144fbae98e46937b76683bb0408bf574cf0742b6b48c9bd07 | MATLAB | 1,424 | 36 | function [fedback] = estimateFeedback(feedback_bin,digital_chans_tsv, D, interpMethod)
% Read field that was fedback to the OPMs, reorder the channels and
% interpolate to match the analogue output
% If no method specified, use linear interpolation
if nargin < 4
interpMethod = 'linear';
end
% Read digital chann... |
7c288f714a92aeb7fc87fca847c845bd201ef5981610f7dcc13cec6355b3cd1b | MATLAB | 1,427 | 33 | function [dataset, first_scale_factor] = txt2mat_crop(input_dir, target_pixel_spacing)
% TXT2MAT - Convert txt to matrix or other format
% A simple function for converting .txt to .mat from zemax
% input:
% input_dir: a string of input directory
% target_pixel_spacing: actual sensor pixel pitch value
% output:
% ... |
d3954fca37f072739daadbf674247aa9517959cae5da4ebbcd3a7d335a63cd67 | MATLAB | 1,429 | 34 | % Adds a composite channel to a csv file, ensuring repeat access of composite in ez_segment GUI
function composite_to_csv(pipeline_data, composite_channel_name)
%get path names to points
point_paths = keys(pipeline_data.points.pathsToPoints);
pt_path = point_paths{1};
%obtain csv file (csv_filepath) ... |
5c5b8842fb9f5d6961751befddab398c247f190f001ddd97885bcf0d0ff2ef24 | MATLAB | 1,432 | 37 | function output = ASLSmoothImage(data, spatialdim, FWHM, voxelsize)
% ClinicalASL toolbox 2023, JCWSiero
% can handle NaNs, 2D and 3D gaussian smoothing
sigma = FWHM/2.355;
inplanevoxelsize = voxelsize(1);
data_smooth = zeros(size(data));
if spatialdim == 2
disp(['Smoothing 2D - can handle NaNs: FWHM(mm) =... |
222f89407a15c44a7e2443b1e6d3da1260eac1f791e4038abdb4cc6926d820b3 | MATLAB | 1,440 | 47 | function probs = Cov_comp(X,tau,isjoint)
%-----------------------------------------------------------------------
% FUNCTION: Cov_comp.m
% PURPOSE: Compute covarance matrices from time series data X
%
% INPUTS:
% X: time series data in the form (units X time)
% tau: time lag between past and present... |
f1a009464c4d4c5bc714c728acfe6df6004a81b5ea5a7b2421ab85e2ec746b3a | MATLAB | 1,440 | 35 | function [centroids_labeled,unique_type_match,type_merged]=type_labeling(centroids,real_type,cluster_type)
%for each centroid, find most commonly assigned real type
for t=1:max(cluster_type)
type_label(t)=mode(real_type(cluster_type==t));
end
%check whether several centrois received the same label
[found_... |
89d21ff10c5fa995c0ec5c7f4aee7fab1e0480e3a1b63eb84e1946c8db81824c | MATLAB | 1,443 | 44 | function ttl_times = DT_get_ttls_from_logger_table(table_events, result_folder)
% JN 2018-12-20
% function extracts all TTL values and times
idx1 = table_events.EventType == 'Digital in';
idx2 = contains(table_events.Details, 'Digital input port status');
mode = 'status';
% JN 2018-12-30
% test whether we are workin... |
a89bf24316b43f1cfb2f5b7d52957bc468013338cb68a503fae0d8d9ba4de1c0 | MATLAB | 1,443 | 45 | % Test ExtendChanSampleFactory.m
% Author: Lasse Osterhagen
% Create mock AudioObjectSampleFactories
mockFactory1Row.makeAudioObjectSamples = @(a,b) b; % return rawSamples
mockFactory1Row.calcRequiredSamples = 0;
mockFactory2Rows.makeAudioObjectSamples = @(a,b) [b; b+1];
% return [rawSamples; rawSamples+1]
mo... |
2df7ae78c00a61039b230422272973f0e55f18654bc9f3c4483ae4ef2babadce | MATLAB | 1,445 | 46 | classdef SimpleNoiseSampleSource < SampleSource
%SIMPLENOISESAMPLESOURCE generates uniform distributed white noise.
% This is a very simple sample source for test purposes only. It should
% not be used in psychophysic experiments, because the level and the
% frequency distribution will depend on the sound equipme... |
b310768d9d9c1f8b34a3b032bff9489bcd36bdfce1a4c1451aaaaeae5d039b63 | MATLAB | 1,447 | 33 | function preprocess_functional_parcellation_zscore(subjectdir, atlas_filename, filename, atlas)
k = strfind(subjectdir,'subject');
sub = [subjectdir(k:end),' - '];
% clear k
% This is simply helping with the text that will be displayed as the
% function is running. 'sub' is a string with the name of the subject... |
e195f44e866c00834cdfab4f2d37f2e408beb89c5c3d3883e24a43366fffa913 | MATLAB | 1,449 | 37 |
% /// Neurons with only shared bins (1)
% load classification performance as plotted in fig.4A
load xx_108_4_single_e2o_perf
exe2obs_cell = cellfun(@mean, test,'UniformOutput',false);
exe2obs = cell2mat(exe2obs_cell);
exe2obs = exe2obs-100/3;
load xx_108_4_single_o2o_perf
obs2obs_cell = cellfun(@mean, verif,'UniformO... |
5db3b39e2e165e6413a918dd16a0f7929a71b21ccf15d0aeb723a5c9db62a1df | MATLAB | 1,451 | 50 | classdef ToneStimulus < Stimulus
%TONESTIMULUS is a stimulus that represents a sine tone.
% Input arguments:
% id=0,
% startDelay=0, % sec
% target=Target.Yes_Reward,
% 'duration', 0.500, % sec
% 'frequency', 10000, % Hz
% 'level', 60 ... |
440c897041a9adff562e0a09c572f2a0dd7b952e01f8a6ac1b6ee4c3464a665e | MATLAB | 1,455 | 57 | function group = micca_full_connected_set(C,indx_sample,thresh)
%
% group = full_connected_set(C,indx_sample,thresh)
%
tmp = triu(C,1);
[pairs, I] = sort(abs(tmp(:)), 'descend');
[x y] = ind2sub(size(C),I);
i = 1;
nb_group = 0;
group = indx_sample*0;
while(sum(group == 0) > 0 && i<=length(pairs) && pairs(i) > thresh)... |
b3a141f7c3145cb18b30dddcbe9bf1fff9ab771517229efa5426b82687ac59f1 | MATLAB | 1,456 | 60 | classdef PunishState < ExperimentState
%PUNISHSTATE : not used at the moment.
% Author: Lasse Osterhagen
properties
% Time out as punishment when the subject descends on no-target
% trials
punishTimeOut = 12;
end
properties (Access = protected)
... |
0394d9e964ef6e1538cdc9cc4464135ea831c892133cb3e4986d9ad4bb9f484a | MATLAB | 1,457 | 34 | function output = ASLLookLockerCorrectionFactor_mDelayPCASL(SUBJECT)
% ClinicalASL toolbox 2023, JCWSiero
% compute Look Locker scaling per PLD
flipangle = SUBJECT.FLIPANGLE;
M0=1;
T1blood= SUBJECT.T1b*1000; % in ms
PLD = SUBJECT.PLDS*1000; %in ms
t = 1:1:PLD(end)*1.1;
deltaPLD=mean(diff(PLD));
T1effblood=1/... |
95f83299632e21d0d61407a496cb757d5d56aed96a62bfd8b3eeaa32261685e0 | MATLAB | 1,457 | 39 | function [db2ETA, db2ETSD, inNEvt, db1Time] = NS_ETA(db2LFP, inSampleRate, in1EventIdx, db1WinSec)
% Synopsis:
% [DB2ET_AV, DB2ET_SD] = NS_ETA(DB2LFP, INSAMPLERATE, IN1EVENTIDX, DB1WINSEC)
%
%Calculate the event triggered average DB2ET_AV and S.D. DB2ET_SD of the
%signal DB2LFP (a channel x time-sample matrix) sampl... |
75877f1aeed6021e4190380828ce2f0d62a104e24a238269168b4010a4358db1 | MATLAB | 1,458 | 40 | function m_sig = Main_signal(varargin)
% Main_signal class constructor.
% Main_signal(name) constructs a signal with a given name.
% Main_signal is the base class of all signals that are not envelopes.
% Every main signal has a Level component, start time, end time and ramp
% length components that define th... |
31414d3732221ef4a492ce4f5338b84272090e0cca4812da59d77f1bb9ecca23 | MATLAB | 1,460 | 50 | % This scripts loads the statistical results for the age effects on cortical
% thickness and plots the t-values (TFCE-corrected) for significant vertices
%
% Written by Christina Stier, 2022
% load folders and assign file names
analysis_dir = ('/home/uni10/nmri/projects/cstier/aging_pipeline');
results_dir = '/home/u... |
a42932a868ffe05f9f60d304e7be980db51585d3064723844479644ef33e8205 | MATLAB | 1,460 | 49 | function val = get_sweep_param(s_comp,prop_name)
% GET Get s_comp's sweep property from the specified signal component
% and return the value.
% val = get_sweep_param(s_comp,prop_name) returns s_comp prop_name.
% Property names are:
% Sdata, Sdata_formula, Edata, Edata_formula, Num_data, Num_data_formula,
% Reps, Reps... |
ac32ac195ac9ea8313edc1f6ede4d0d200332fd965181807e8e40fe64b66f585 | MATLAB | 1,462 | 39 | function [out_db] = load_body_direcs(rat_dir, first_subsample_ind, subsampling_inds)
% Function predicted_rat_body_points.mat() reads the sounds_table.mat that is produced by the pipeline.
%
% Inputs:
% rat_dir - (str) - Location of the sounds_table.mat, inside the experiment folder
%
% O... |
14267e7a3400d02c94e9c2a88e8f100585fb9d8aa2ee68f17316e9e92e06b588 | MATLAB | 1,464 | 45 | function [total_struct] = create_table_from_all_csvs(file_names)
% Function create_table_from_all_csvs extracts the events from all the .csvs to a single struct.
% It auto-iterates over the three .csv if a single experiment and stores all events in a single
% struct.
%
% Inputs:
% dir_name - (directory, str) - Rep... |
a680a8651a701b535b10b5a6bc3b23760f298aaf13b630660ceca1889a174511 | MATLAB | 1,472 | 52 | % Time-frequency analysis
% 'TF' is the time-frequency spectra of data.
% 'TF' will be a matrix (time * frequency)
% 'data' should be a vector
% 'sf' is a sampling rate
% 'wnd_size' is the window size of the data
% 'baseline' is a period for baseline correction of analysis
% 'f_scale' is a frequency resolution ... |
73685895bda6694e87afb50c5aa9fd9f554d773ea225dbe7815a05a1f66e360d | MATLAB | 1,475 | 36 | function generatePanels_Fig05(Fig05)
%% Arousal State Transitions
transNames=fieldnames(Fig05.arousalTransitions);
for transNum=1:length(transNames)
theHbT=mean(Fig05.arousalTransitions.(transNames{transNum}).IOS.forepaw.dHbT,1);
theEMG=mean(Fig05.arousalTransitions.(transNames{transNum}).EMG.EMGPower,1)... |
2ca2aca320aeea96f87948eb4c5d1bb8dc54b4573648af193dbff2082429f289 | MATLAB | 1,477 | 48 | %% Tuning amplitude and half-width
% Preferred direction was calculated using both wide and narrow prior block data.
load('AmpHW.mat');
% Tuning amplitude and half-width
whAmp = [data.A.whAmp; data.B.whAmp];
nhAmp = [data.A.nhAmp; data.B.nhAmp];
wlAmp = [data.A.wlAmp; data.B.wlAmp];
nlAmp = [data.A.nlAmp; data.B.nlAm... |
a59fbab429e976aba746495f764b8a4e3ded364b1aa3ef75d7742f11a0881d7a | MATLAB | 1,482 | 30 | % Reads all the .txt files for one condition that is in one
% folder.
function tensor=read_condition_tensor(data_dir,condition_name)
if exist(fullfile(strcat('conditions_data_',data_dir(end-2:end-1)),strcat(condition_name,'.mat')), 'file') == 2
load (fullfile(strcat('conditions_data_',data_dir(end-2:... |
572ac785eb88227054ace3cfbdce797e423883fd2729435b4613ea81e04843f3 | MATLAB | 1,483 | 40 | function file = File_comp(varargin)
% File_comp class constructor.
% c= File_comp(STATIC_VALUE) creates a File_comp object which is a
% Signal component representing the file name containing a pre-synthesized signal.
global FILE_FILE_COMP_DEFAULT BASEDIR_FILE_COMP_DEFAULT
FILE_FILE_COMP_DEFAULT='';
BASEDIR_FILE... |
72a5aff41cc3253a4be7e65c53d0771446f787ab309abda16fa662f96a86c0a4 | MATLAB | 1,484 | 35 | function val = get(s_coord,prop_name)
% GET Get Signal Coordinator property from the specified object
% and return the value. Property names are:
% Coordinator - the coordinator object
% Main_signal - the Main Signal this Coordinator handle
% Name - of the main signal
% Components - list of the components of the Main S... |
b6a0db481c5560ea7c8f2bf65c40f1a177997d9d37af8c3febf7d9f5c5d0b863 | MATLAB | 1,485 | 43 | function samp_points=synth(sig,samp_rate,trial_dur,varargin)
% SYNTH is NB synth function.
% SAMP_POINTS=SYNTH(SIG,SAMP_RATE,TRIAL_DUR,VARARGIN) Samples the signal
% according to the givan SAMP_RATE and TRIAL_DUR. Returns the sampled
% points.
% varargin holds the requested parameters for the NB signal.
% If varargin... |
c931df7066dc71d8ab72fca613c19c9c7f14b6b5454e48e6ad1720736eddc8a9 | MATLAB | 1,489 | 23 | function T1Processing(SUBJECT, filename)
% ClinicalASL toolbox 2023, JCWSiero
if isfile([SUBJECT.ANATOMYdir '/T1_brain_seg_0.nii.gz']) % check if T1 segmentation has been performed
disp('Segmentation has already been performed');
else % perform T1 anatomy brain extraction and tissue segmentation
disp('Pe... |
40ad62536b78867c8539263ef84efc1c2b930b387293ba5a7dd8bc2555777808 | MATLAB | 1,490 | 29 | function [SUBJECT] = ASLExtractParamsPARREC(SUBJECT)
% ClinicalASL toolbox 2023, JCWSiero
%%%%% 3. Scan information %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
SUBJECT.TR = 5.5;% TR in s
SUBJECT.TE = 10.8;% TE in ms
SUBJECT.NPLDS = 5; % Amount of PLD's
SUBJECT.NDYNS = 24; % number of repeated volumes i... |
9e25eabb5c081415a19bc6da03555438597b1135e1664deb9c47988f178b0b9a | MATLAB | 1,495 | 46 | templateSize = 11; % square template
imgWidth = 320; % rectangular image
imgHeight = 240;
template = rand(templateSize); % template with random entries
img = rand(imgHeight, imgWidth); % similarly for the image
% randomly embed the template inside the img
embedX = round(rand*(imgWidth-templateSize-1)+1);
... |
7e5dfe0cde96ec3bc3236023747b73ce9c02a825cd13b376c0504433b811d7f7 | MATLAB | 1,499 | 40 | function runExampleGapSession()
%RUNEXAMPLEGAPSESSION demonstrates a gap detection experiment.
% The function will open two windows:
% 1. The experiment control window lets you start, stop, and save an
% experimental session.
% 2. The key press interface GUI, which is the input device for the
% subject to all... |
f08cbb742c8726040edd40409b3c7a123d15fe31ce03443e63d3acae9d82240a | MATLAB | 1,501 | 54 | function mode_data = get_data_mode(swp,rand_indices_arr)
% mode_data =GET_DATA_MODE (swp,rand_indices_arr) returns
% an array of randomly chosen values from the vector of values
% generated for the specified Sweep object according to it's STEP,
% range(SDATA,EDATA),NUM_DATA and REPS.
% The order in which the values wi... |
c5ba973222b87ab1f663bab1be30be4d3de6e2bfc09b5af52b92f87eb2847557 | MATLAB | 1,504 | 43 | function plot_4bars_withinError_only(data, t_values, reference, ylabel_string, ylimit)
figure
for effect=1:3
number_subjects = size(data{effect},1);
for i=1:4
if i~=reference(effect)
SD(i)=compute_sd_from_t(mean(data{effect}(:,reference(effect)) - data{effect}(:,i)), t_values{effect}(i), 1... |
995160aed12ced6f07b6ba2865abd7ed42385ecd96fa9294e801ccd714f3ebb1 | MATLAB | 1,507 | 68 | function [T, paramBBN] = createBBNblock(Told,paramBBNold,pr, nstims)
% pr = struct('speaker',[],'samp_rate',[],'trial_dur',[],'stime',[],'etime',[],'ramp',[],'att',[],'nstims',[]);
Tsize = size(Told,1);
paramsize = size(paramBBNold,1);
if pr.nstims
nstims = pr.nstims;
% else
% nstims = 280;
end
type = cell(nst... |
ebc08bc0b69eeef17f70698c89a82de64ffb47ed54b15e47ab89925f01c38a31 | MATLAB | 1,507 | 38 | function C = conv2fft(varargin)
% C = conv2fft(A, B)
% C = conv2fft(H1, H2, A)
%
% C = CONV2FFT(A, B) performs the 2-D convolution of matrices A and B.
% If [ma,na] = size(A), [mb,nb] = size(B), and [mc,nc] = size(C), then
% mc = max([ma+mb-1,ma,mb]) and nc = max([na+nb-1,na,nb]).
%
% C = CONV2FFT(H1, H2, A) fi... |
a2b271f25cd540f0df529a8b7858daadd67e3c5b041bf06a9facf0ce1ffda8b8 | MATLAB | 1,509 | 65 | %load data
%friendship
load('friend_baseline.mat')
%mental health
load('cbcl_baseline.mat')
%cognition
load('tbss_baseline.mat')
%covariates
load('cov_beh.mat')
%the number of friends is log-transformed and mean centered
cf_log = log10(res_b(:,6)+1);
cf_log_r = cf_log-mean(cf_log);
DV = [cbcl,tbss];
va... |
855d649cf88a6fb26b139cce484a1d9d6b2346238180138f52f197181b832bf8 | MATLAB | 1,511 | 44 | % get_ears_level: Currently, just return the attenuation level of each
% channel
% ELN 311214
function [levels_arr,relevant_pa5]=get_ears_level(line,atten_arr)
levels_arr=atten_arr;
relevant_pa5=1:4;
%
% right_ear=get(line,'Right_ear');
% left_ear=get(line,'Left_ear');
% right_synth_chans=get_synth_chans(line,right_ea... |
e4db6a9c452bc2a69576819aee6c85c8f92672d16e7ca03bae40d7dc79515f32 | MATLAB | 1,511 | 42 | %TEMP Blue-pale-dark red colormap
%
% Examples:
% map = temp
% map = temp(len)
% B = temp(A)
% B = temp(A, lims)
%
% A colormap designed by Light & Bartlein for visualizing data such as
% temperature, with good contrast for colorblind viewers.
%
% The function can additionally be used to convert a r... |
ca9db2518833e0d674e5e3264f786b24f644856054303589f55ca83662a7fc71 | MATLAB | 1,513 | 30 | function T1fromPLD=ASLT1fromPLDCompute(DATA4D, MASK, TIMEARRAY)
% ClinicalASL toolbox 2023, JCWSiero
% compute T1w image from multi-delay PCASL (Look-Locker) PLD (not the PLD) data across the different PLDs
% we observe that the PLD across PLDs show a exponential decay that depends on T1
% take natural log and fit for ... |
f8abe7aa512c40186d90b6b4db86c69e8e9281422f158c13b10b5189c2f8ed3c | MATLAB | 1,513 | 50 | %IMSC Wrapper function to SC which replicates display behaviour of IMAGESC
%
% Examples:
% imsc(I, varargin)
% imsc(x, y, I, varargin)
% h = imsc(...)
%
% IN:
% x - 1xJ vector of x-axis bounds. If x(1) > x(2) the image is flipped
% left-right. If J > 2 then only the first and last values are us... |
f92cfa3a1549cfa6e184a53ea69468ab5e814e49b0cd948c3207e2880936ee2d | MATLAB | 1,513 | 56 | function sem=SEM_calc(vect, CI)
% SEM_calc - standard error of the mean, confidence interval
%
% function sem = NBP.SEM_calc(vect, CI)
%
% Purpose
% Calculate the standard error the mean to a given confidence
% interval (CI). Note that nans do not contribute to the
% calculation of the sample size and are ignored for ... |
b26e0908f59c388013e84661ee62dd1e78e7fbdbd50914bfe907c7d51328348a | MATLAB | 1,514 | 33 | function [classifiedTrials, classNames] = classifyBlockedTrials(trials, audioObjects)
%CLASSIFYBLOCKEDTRIALS classifies trials by enclosing AudioObjects.
% Arguments:
% trials - an array of trials
% audioObjects - an array of non-trial AudioObjects
%
% Returns:
% classifiedTrials - a cell column with each cel... |
9b9756d3e1f708979fdf467b4a113dc15c585d0c6a9b8052b4822a87ec573c1d | MATLAB | 1,520 | 40 | function write_trial_data_vals(out,line_num,chan_num,signal_table,trial_num_in_line,handles)
fid=get(out,'Fid');
if fid==-1
return;
end
% ## we use table instead of metablock ## Out_Manager,run_line_index,p,chan_table,cur_trial_index,handles
% meta=get(out,'Metablock');
% line=get_line(meta,line_num);
% line_trials... |
0211f3178a9f5022cac250d5f772e5c9c633c8d62800fa86000c434c84b81aea | MATLAB | 1,521 | 54 | function swp = set(swp,varargin)
% SET Set Sweep properties and return the updated object
% Property names are:
% Sdata, Sdata_formula, Edata, Edata_formula, Num_data, Num_data_formula,
% Reps, Reps_formula, Mode, Step.
orig_swp=swp;
property_argin = varargin;
while length(property_argin) >= 2,
prop = property_ar... |
2781d4046b568be181bcf5ed7dbb8b49f7a14e324dc02f6f84e6adae64cd4e2f | MATLAB | 1,522 | 32 | function [] = MIBIevaluateBackgroundParameters(points)
global pipeline_data;
for i=1:numel(points)
point = pipeline_data.points.get('name', points{i});
countsAllSFiltCRSum = point.counts;
labels = point.labels;
bgChannel = pipeline_data.bgChannel;
evalChanne... |
08f5ab794ca8bd62cb506d584e2b332758da28f30aafb16359b032557b40ae1c | MATLAB | 1,526 | 50 | function h = BWR(m)
% red-yellow-white-cyan-blue color map
% BWR(M) returns an M-by-3 matrix containing the colormap.
% BWR, by itself, is the same length as the current figure's
% colormap. If no figure exists, it creates one as long as MATLAB defautly does.
%-----------------------
% Syntax
%-----------... |
dcd2f8d6008fdf0c33314d24349ab079306842ee02d96b0cb4cc08ee573286c1 | MATLAB | 1,526 | 30 | function T1fromM0=ASLT1fromM0Compute(DATA4D, MASK, TIMEARRAY)
% ClinicalASL toolbox 2023, JCWSiero
% compute T1w image from multi-delay PCASL (Look-Locker) M0 data across the different PLDs
% we observe that the M0 across PLDs show a exponential decay that depends on T1
% take natural log and fit for 'T1'
dims =... |
a2edc229145dee92629a82aff6262c2afb122906cc798488e7033b18071494e2 | MATLAB | 1,528 | 46 | function h = BWR2(m)
% red-white-blue color map
% BWR2(M) returns an M-by-3 matrix containing the colormap.
% BWR2, by itself, is the same length as the current figure's
% colormap. If no figure exists, it creates one as long as MATLAB defautly does.
%-----------------------
% Syntax
%--------------------... |
a6915e8a5de25cfe49e36258a262142bd00b0c37a4263b5737f55d61cffcb670 | MATLAB | 1,528 | 94 |
close all
figure();
cell = 1;
clear G_c;
clear G_uc;
clear G;
days = [1 2 3 4 5]
colr = {'r' 'g' 'b' 'm' 'y' };
figcount = 1;
for ii = days; % [1 3 4 6 8];
color = char(colr(figcount));
clear G_c;
clear G_uc;
clear G;
pdata = ROI_dat{ii};
counter = 1;
for cell = 1:size(pdata.raw_dat,1);
for ... |
d3d0f00cab6b4452dacdd804a9e42d885630bcd029629bd86180075a9ff9c4d7 | MATLAB | 1,533 | 51 | function plot_cluster_stats(all_axes, stat_data, param)
% JN 2020-12-14
% JN 2021-01-29
rel_cols = {'N_slow', 'N_pos', 'N_neg'};
for irat = 1:2
ax = all_axes{irat};
grid on
rel_data = stat_data(stat_data.Rat == irat + 3, rel_cols);
plotdata = flip(table2array(rel_data), 1);
plotdata = plotdata./sum... |
91d80d501cf4d182beca4327d903d1e4306112266dbd19e2d0e759fdd5bdeb03 | MATLAB | 1,534 | 21 | function [SUBJECT] = ASLExtractParamsDICOM_vTR(SUBJECT, filename)
% ClinicalASL toolbox 2023, JCWSiero
tic
disp(' Reading DICOM info... ')
info = dicominfo(fullfile(SUBJECT.DICOMdir, filename));
elapsedTime = toc;
disp(['..this took: ' num2str(round(elapsedTime)) ' s'])
%%%%% 3. Scan information %%%%%%%%%%%%... |
6c3845ab77dbced95e2be366f7c309e47fba773e4d5e45cb225c964c6eafc0f5 | MATLAB | 1,537 | 32 | function [] = MIBIevaluateBackgroundParameters_3(points)
global pipeline_data;
for i=1:numel(points)
point = pipeline_data.points.get('name', points{i});
countsAllSFiltCRSum = point.counts;
labels = point.labels;
bgChannel = pipeline_data.bgChannel;
evalChan... |
d67770f71f9fb1e77cda5953339bb214f9e407d8f3350081dcb79dd4a0290a6f | MATLAB | 1,539 | 57 | load("timeseries.Yeo2011.mm316.mat");
disp(size(subjects));
is_negative = 0;
for m = 1:316
subject_mx645 = subjects(m).mx645;
subject_mx1400 = subjects(m).mx1400;
subject_std2500 = subjects(m).std2500;
[rows, columns] = size(subject_mx645);
count_negative = 0;
for i = 1:rows
for j=1:col... |
527d066148901ec1c4eea78581c5864b530cc23d02560ee9cab29e4bf2d4be38 | MATLAB | 1,543 | 68 |
clc
clear
close all
load xx_108_4_single_e2o_perf
exe2obs_cell = cellfun(@mean, test,'UniformOutput',false);
exe2obs = cell2mat(exe2obs_cell);
exe2obs = exe2obs-100/3;
load xx_108_4_single_o2o_perf
obs2obs_cell = cellfun(@mean, verif,'UniformOutput',false);
obs2obs = cell2mat(obs2obs_cell);
obs2obs = ... |
951869049802ce1e49f9e0ebbbfbe17b262c292eb5162a96809b487879252c7b | MATLAB | 1,543 | 32 | function [] = MIBIevaluateBackgroundParameters_graded(points)
global pipeline_data;
for i=1:numel(points)
point = pipeline_data.points.get('name', points{i});
countsAllSFiltCRSum = point.counts;
labels = point.labels;
bgChannel = pipeline_data.bgChannel;
eva... |
223705b1fae2f97c1516980333e98019222ac7e5eac6043b15889c6155434e76 | MATLAB | 1,549 | 73 | function roi_ave=fb_plot_roi_peaktime(ROI_MU,ROI_TIME,ROI_STATS,MOV_DATA,varargin)
%fb_select_roi selects an arbitrary number of roi's for plotting
%
%
%
%
%
roi_colors='jet';
filt_alpha=5;
filt_rad=15;
lims=.05;
nparams=length(varargin);
if mod(nparams,2)>0
error('Parameters must be specified as parameter/value pa... |
60e8c6b08e079b6d0bb12ee29f87ca72ee3fc968c7d9db77f10b11246ff202c5 | MATLAB | 1,555 | 50 | %All used PET/SPECT data are publicaly available and downloaded from
%https://github.com/juryxy/JuSpace/tree/JuSpace_v1.3/JuSpace_v1.3/PETatlas
%Data path
path = '';
%PET/SPECT name
ls = dir(fullfile(path,'data'));
dn = cell(length(ls)-2,1);
for i = 1:length(ls)-2
dn{i} = ls(i+2).name;
end
%HCP templ... |
f5df0d29177c730a648d2c3ec7558b72632664e0c23cd736cef750c4d747e522 | MATLAB | 1,556 | 61 | function [Final_img, Count] = MIRO_Collaborative_Wiener_dct(noisyImg,BasicImg,Transforms,sigma_g,parameters)%#codegen
%% initialization
width = size(noisyImg,2);
height = size(noisyImg,1);
block_Size = parameters(1);
blk_step = parameters(7);
beta = parameters(8);
lambda_W = parameters(9); % lambda Wiener
adaptive_... |
cc40e1af3dfc399807aa38f5f67f2187c5c0f37859feb78ee4f4b1262346db3e | MATLAB | 1,569 | 35 | function numUnits = idxBreakdown(IDX,ERR)
% Total number of multi-unit channels
totalN = length(IDX.allV1) + length(ERR);
% Number of sessions
penetrationInIDX = {IDX.allV1.penetration}.';
penetrationInIDX_unique = unique(penetrationInIDX); % N = 14
penetrationInERR = {ERR.penetration}.';
penetrationInERR_unique = uni... |
5c25867ba9947079056259b3fd88a8caad15f362d4afcb9c2787f263e4e808b1 | MATLAB | 1,572 | 48 |
function [Result] = AO_StartConnection(DspMac,PcMac,AdpaterIndex)
%% Function to connect Matlab to the SnR/Neuro Omega
%% DspMac array of 6 hex, this is the mac address of the Snr/Neuro Omega system (dsp)
%% PcMac array of 6 hex, this is the mac address of the pc which run is
%running matlab. This value must be d... |
808d0e214d99b5fb42c5e71e536d6bf4b2e469880c46cdee0250ea14192ac4da | MATLAB | 1,572 | 42 | function [slice_id] = find_loc_of_point(p, c_p, r, slices)
% FIND_LOC_OF_POINT finds the RIFF slice that the point belongs to, according
% to the geometry of the RIFF and the internal wall locations.
%
% Usage:
% >> [x, y] = getpts; RIFF_geo = load('RIFF_geometry.mat'); slices = load('RIFF_slices', 'slices');
... |
36aeec3a5a408a9c66eac507c68342ec4e84c1bc845fa75418091d42270aa104 | MATLAB | 1,574 | 31 |
figure;
%% All days averaged fathers vs mothers
subplot('Position',[0.2 0.61 0.2 0.17]);
shadedErrorBar([],CAMKII_mean_z_score_all_days_all_mice_enters_the_nest,{@mean,@stderrm},'c')
yticks([-2 -1 0 1 2 3 4]);yticklabels({'-2' '-1' '0' '1' '2' '3' '4'});xticks([0 844 1688 2532]);xticklabels({'-8' '-4' '0' '4'});xlim(... |
09d1b802f94bac7b32260adf224c8be50723e5190c8de3ed95ae026e28554754 | MATLAB | 1,575 | 54 | function expdata = run_from_database(expdata)
% JN 2019-04-02
% JN 2020-04-23
% run pipeline from a CSV file of session information
session_table = get_session_table(expdata.experimenter, expdata.year, ...
expdata.month);
idx = (session_table.Experimenter == expdata.experimenter) & ...
(session_table.Year == ... |
29fd95e3c8ea8d89662222c2f2379eaf6fafa5cfa4efd2beb8cd64d06174459d | MATLAB | 1,575 | 49 | function val = get(s_comp,prop_name)
% GET Get s_comp property from the specified object
% and return the value. Property names are:
% Input_method, Static_value, Value_formula, Static_reps, Reps_formula,
% Seq_values, Seq_values_str, Coord_index, Index_formula, Wrap, Fixed_num_data,
% Sweep, Seq_values, Seq_values_st... |
7111f04138552f0f82c31e98c3d03f8bfde39c4e01d4f017e5aeb957a0ffb5cc | MATLAB | 1,575 | 72 | % FullTimeClassicBRFS - update to use Gramm
clear
close all
PostSetup('Neuropixel')
flag_SaveFigs = false;
anaName = 'IDX_iScienceSubmission_EyeAndOriTuned';
%% Get IDX
global IDXDIR
cd(IDXDIR)
if ~exist(strcat(IDXDIR,strcat(filesep,anaName,'.mat')),'file')
IDX_iScienceSubmission
end
load(strcat(IDXDIR,strca... |
f3514b33ac7530d306586bf8c918469e9b8d77d4f2075609e417918b043dac53 | MATLAB | 1,580 | 50 | % val = clamp(val,minval,maxval)
% ---------------------------------------
%
% Clamp an nd-array between minval and maxval
%
% Inputs:
% val Input matrix
% minval Any value of val smaller than minval will be made equal to minval
% maxval Any value of val larger than maxval will be made equal to maxval... |
542c86f038d44926cdef189b6fc5a015fae035ed8c97d37ca74856d77f8a8241 | MATLAB | 1,583 | 67 | function [kcMax, SNR] = ResolutionFinder(image)
%% set path and load some data
% addpath('funcs')
% image = img0;%double(loadData('test_image.tif'));
if mod(size(image,1),2) == 1
image(end,:) = [];
end
if mod(size(image,2),2) == 1
image(:,end) = [];
end
tile_size = 64;
if size(image,3) == 1 && size(image,1... |
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