sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
b5e6ecc0ba4de3d56b8236de4f52269b148c91876fc3fc03278d0e85f81735fa | MATLAB | 107 | 5 | % showtimes
plot(nor1(MALAB_used_mem),'r'); hold on;
plot(nor1(Tload1),'g');
plot(nor1(Tcorr1),'b');
|
ea2a536683f9546ca8ac2a1a2e163c54f8b708e7fc1e96daa9bf1601df96fdd5 | MATLAB | 107 | 7 | function [g] = cellgte(c,t)
%cellgte.m %3/14/21
g = cellfun(@(x) x >= t, c,'UniformOutput',false);
end
|
5db032aabedc7694133ede6f3671086088f6fd60f48298e4c3f73fe88a7c5caa | MATLAB | 111 | 7 | function [s] = cellsum(c,dim)
%cellsum.m %3/13/21
s = cellfun(@(x) sum(x,dim),c,'UniformOutput',false);
end
|
956d9864fd72d01cc8a9419565cfa8f6de9de7b085d2a09e80a95744a083971f | MATLAB | 111 | 6 | % try sytem calls
img = screencapture(0, 'Position', [1285 0 1900 1023]);
figure(80)
image(img);
savefig( |
9e8ed71285de4b3a864a8d1731b222b28f34bc3261b5f5b9c9dbea2ee88f136f | MATLAB | 111 | 6 | function [newX, scaleFact] = scaleFunc(X)
scaleFact = prctile(abs(X(:)),95);
newX = X ./ scaleFact;
end |
e524755570b1cb606ee8eb0766bce404a2a7dcb02044529fe4994447e22f88bc | MATLAB | 111 | 9 | function [T] = tagFirst(V)
T = zeros(size(V));
ix = find(V);
if ~isempty(ix)
T(ix(1)) = V(ix(1));
end
end |
0238108b5025c3a16ccac61ac3ee78634e701f384b4ebd2f67cb101cc9b44e05 | MATLAB | 113 | 6 |
function seed_e_idxes=my_randperm(seed_e_idxes)
seed_e_idxes=seed_e_idxes(randperm(length(seed_e_idxes)));
end |
e38548dc70e60ab4145587d7a5e911144ba396175cb93cbc708726ff738697ea | MATLAB | 113 | 4 | addpath /home/kristin/FLIES/data/multiplespecies/;
setmultispeciesmovienames;
DISPLAYAREAS = true;
fixmanymovies; |
fa277d4830c1560b745657df2b39d9e9575f9b69b0640aaec1e4efb0c5ceebe6 | MATLAB | 113 | 7 | function [s] = cellnnz(c)
%cellnnz.m %3/13/21
s = cell2mat(cellfun(@(x) nnz(x),c,'UniformOutput',false));
end
|
9052fbeb5ba6d5870ca887d964ba7d6b2612498393425ba87fa716cbf1e41b44 | MATLAB | 115 | 4 | function sampNum = getSampleNumber(filename)
[C, ~] = strsplit(filename, {'_', '.'});
sampNum = str2double(C{2});
|
6ba372e6b2d097432638c3e9caf70c76f2153896c1f0f3c415b0de7a3601b0f6 | MATLAB | 116 | 9 | % x^2+y^2=r^2
% (x-x0)^2+y^2=r^2
% (16-r)^2+6^2=r^2
%
% 16^2-32r+r^2+36=r^2
r = (16^2-36)/32
a = pi*r^2
|
6fc6d2c5354762c6c4cd1c15ffccaad91d60019cbb70897be1695b8499e2895e | MATLAB | 116 | 11 |
function my_imshow(img_data)
try
imshow(img_data);
catch err_info
disp('image cannot display!');
end
end |
d5232cd5d326c2ccb998e99f5a48f2895d0ee3fac5372afd6fba20ac09579c96 | MATLAB | 118 | 10 |
function my_diary_flush()
tmp_status=get(0,'Diary');
if strcmp(tmp_status, 'on')
diary off
diary on
end
end |
b26cd9c2e786519c8926ddaf53b918350cd305ae03c8edc06ba1127a6e9b8787 | MATLAB | 119 | 6 | function [U,V] = means_e(T_training, m, n)
e = .5 * mean(at_training(:,3));
U = e * ones(m,1);
V = e * ones(n,1);
|
c7b15fd9de585637518e43919e43450f9b1a205476e7a40d4b270bf1bfb0d3e9 | MATLAB | 120 | 5 | function loss = hamming_loss(Y,F)
[dummy label] = max(Y,[],2);
[dummy est] = max(F,[],2);
loss = sum(label~=est); |
0100ccc8df66807b9a22df74dd402ac573b3bf88c92deac2d1eafe1c8d96667a | MATLAB | 121 | 3 | function mltp_plot_bfo_90_session_grouped(obj, session)
mltp_plot_bfo_general_session_grouped(obj, session, 90);
end
|
23dedc4b9c8ca509ea6c84939f5e1d3906e85e488d119c074b95d36f3680be75 | MATLAB | 121 | 3 | function mlgp_plot_bfo_90_session_grouped(obj, session)
mlgp_plot_bfo_general_session_grouped(obj, session, 90);
end
|
153f6c6a994ae3bfc876e3521f5367d250194f75054a95f46919a5db5a0e12c6 | MATLAB | 122 | 4 | function nonan = nanfree(x)
% returns a shorter vector with all nan places removed
nonan = x(~isnan(x) & ~isinf(x));
|
7059508351e29da1d738c826faaf6214d875a206d2172b3949ca24d468d91cf3 | MATLAB | 122 | 5 |
function loglin = loglinspace(xmin, xmax, npnts)
loglin = 10.^(linspace(log10(xmin), log10(xmax), npnts));
end
|
9efa869387acbc34f2ddc1599dbfce7266d88308d25823afb300869406afdf39 | MATLAB | 123 | 5 |
function activeNeighbours = getActiveNeighbours(active, network)
activeNeighbours = intersect(active, network);
end
|
c7dbd5fcc8767257f194fad005af997f9be151df2b444f13c396b71c2d5fd649 | MATLAB | 123 | 3 | function mltp_plot_bfo_180_session_grouped(obj, session)
mltp_plot_bfo_general_session_grouped(obj, session, 180);
end
|
030fd0c569e092c07e9d0214dfe55e3e57dbe007f99baad44a2cedd66bec1e45 | MATLAB | 124 | 4 | function [parent, name] = fileparts2(path)
[parent, base, ext] = fileparts(path) ;
name = horzcat(base, ext) ;
end
|
eb7f9fc22b61cca872695f0b3d21285181c4020e630abdb0865d02d3bb62d301 | MATLAB | 124 | 7 | function clim = getImageLimits(im)
if max(abs(im(:))) == 0
clim = [-1 1];
else
clim = max(abs(im(:))) * [-1 1];
end |
fd31dbc7de825310d6cf3215c2395905fab445254a2bb30e6203e730959ddcdf | MATLAB | 124 | 7 | function img = normalizzaImg(I)
I = double(I);
minimo = min(I(:));
I = I - minimo;
massimo = max(I(:));
img = I / massimo;
|
3fb07289a378d229220a014a2679f3de32263e8c3a1f4a1d3a6f0c81cb71752b | MATLAB | 128 | 4 | function [output] = mygrid(limit1, limit2, N)
output = limit1 + [0:N-1]*(limit2-limit1)/N + 0.5*(limit2-limit1)/N;
end
|
4e2ad9464dbd1d4de30cf0d345367b4764d2bcf3689edbac5c95874c856cf44f | MATLAB | 129 | 3 | function samples = ml_stats_gen_uniform_samples(nSamples, xMin, xMax)
samples = xMin + (xMax - xMin) * rand(1,nSamples);
end
|
6f27891af6639027236718beea9b56f1ce413ddd7d7e88e174026bf44fd7ba94 | MATLAB | 129 | 2 | % calibrate tracking results: convert from pixels to mms, frames to seconds
[CONVERTUNITS_SUCCEEDED,savename] = convert_units_f;
|
c5e07ed0aea449be70f8c1d403e161f115818e9626667af2cfa035170a5de9ab | MATLAB | 129 | 6 | function SONMarkerDisplay(in)
% SONMarkerDisplay is used by sigTOOL and is not part of the stand-alone
% SON library
return
end |
64fedeebe6e530f0f308469346d978e90c95b8ee775d6ca1233d1332148ab51d | MATLAB | 134 | 6 | function SONMarkerDisplay(in)
% SONMarkerDisplay is used by sigTOOL and is not part of the stand-alone
% SON library
return
end |
1cb2a4162ef943949b9c3dd6a7d07510a4729d81aad9f4e105090164575c3cab | MATLAB | 135 | 3 | function mltp_plot_bfo_90_placey_session_grouped(obj, session)
mltp_plot_bfo_general_placey_session_grouped(obj, session, 90);
end
|
31575099f48e730157162be62170bd28c5b712c0c9974a851098c0d55308ea68 | MATLAB | 135 | 8 |
function flag=my_any(one_exclude_flags)
flag=any(one_exclude_flags);
if(numel(flag)>1)
flag=my_any(flag);
end
end |
ea89d8b7c12c1686f822b864fee90e6c453945640af00d53dffe360a3a31dc2b | MATLAB | 135 | 10 | function [Histr] = Hist(lag,spike)
Histr = zeros(length(spike)-lag,lag);
for i=1:lag
Histr(:,i) = spike(lag-i+1:end-i);
end
end
|
65d6e8878cc2ebf90017968ab182f06ddba59fcd8cd9e4132570fc477efd1b5e | MATLAB | 137 | 9 |
function input_info=cnn_layer_dummy_backward(input_info, layer, work_info_batch, output_info)
input_info.dzdx=output_info.dzdx;
end |
0a6ec18b14659f3a217f92670429e53cbce3803546172ef4cdb0afebea3427e7 | MATLAB | 138 | 7 | function boxes = Blobs2Boxes(blobs)
boxes = zeros(length(blobs), 4);
for i=1:length(blobs)
boxes(i,:) = blobs{i}.rect;
end
|
5494232913e9974d6596b0e1710c40e54a2e425d418c27345174873e7b4bddc5 | MATLAB | 139 | 10 | function res = TVOP()
%res = TVOP()
%
% Implements a spatial finite-differencing operator.
%
res.adjoint = 0;
res = class(res,'TVOP');
|
02f3b41a4edcecef7beea1514b58e2c607c0c08e2b8b4bdbee4ebd5c28139d0d | MATLAB | 140 | 10 | function A=quotes_if_space(A)
if A(1)=='"'
else
if sum(ismember(A,' '))>0
A=['"' A '"'];
end
end |
69cfb582576da5fa66736f90eee2fa2edd1e3b22f7d4cf87dc16a0fe14478d56 | MATLAB | 142 | 9 | function dx=deriv(x);
ss=size(x);
dx=diff(x);
if diff(ss)<0,
dx = [dx; dx(length(dx))];
else
dx = [dx, dx(length(dx))];
end
|
5f06e5d3a5e8121cbbc258fca1b948061c777e99112f8069840f1f17b7b84188 | MATLAB | 146 | 4 | function [Z] = ml_bs_occupancy_xy(bs, x, y)
% Computes the occupancy for the positions in (x,y)
Z = ml_bs_accumulate_xy(bs, x, y, 1);
end
|
a5bc36b4ed3c39239ac4133c35b50579fcb055abe8be630ca0ab220333e87355 | MATLAB | 148 | 6 | function [out]= zscore_norm(in, range1, range2)
mu=mean(in(range1:range2));
sigma=std(in(range1:range2));
out=(in-mu)/sigma;
end
|
d7aa1c3587c4fd0f95810948b45f6b25b8dd416d2d3ad7e9d4ad871c1779f68d | MATLAB | 149 | 9 | function[final_redcells]=add_redcells(redcell_vect,toadd)
for i =1:length(toadd)
redcell_vect(toadd(i))=1;
end
final_redcells=redcell_vect;
|
32164ae78949cc815f794a7fd297263a32ea5e92b8ac0583cc10241aa227d4ea | MATLAB | 150 | 7 | function mkdir_pers(directory, savefile)
if savefile
if exist(directory, 'dir') ~= 7
mkdir(directory);
end %if exist
end %if savefile |
509b71b288d9aa46ba7c13334cb35555b3c5a45c0dfc6617d3c51f272f5c1dd9 | MATLAB | 150 | 9 | function y = rmvNanCol(x,dim);
if nargin<2, dim=2; end;
if dim==1,x=x'; end
nanm = nanmean(x);
y=x(:,~isnan(nanm));
if dim==1,x=x'; end
|
b2fd5272b4502ebcf31bd9a46bff4dce9e85a9508f8eb2796d8fa8ea34b523bd | MATLAB | 150 | 8 | function xx = suptitle( txt )
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
title(txt);
xx=-1;
return;
end
|
b5b3aa1c6d6a68b58fb298669b6d24258773d9a63fda663b8ebed575cb5eeab0 | MATLAB | 150 | 9 | % mglOpen();
initScreen;
mglClearScreen(22);
mglFlush();
mglEyelinkOpen();
mglScreenCoordinates();
mglEyelinkSetup();
mglEyelinkClose();
% mglClose(); |
b6fee8e051f9e4c53749b4979b8188d328baff159632fd0801f4ef5d73ae919a | MATLAB | 150 | 8 |
function output_info=cnn_layer_dummy_forward(input_info, layer, work_info_batch)
output_info.is_group_data=false;
output_info.x=input_info.x;
end
|
550b3348125893924aa367c93788df1743bbec3a20a7b56850361977cabc118d | MATLAB | 151 | 6 | % getSourceFigData
% select the panel of interest, and then run this script.
h = findobj(gca,'Type','line')
x=get(h,'Xdata');
y=get(h,'Ydata');
|
29bbfeddc2bc515cce4b4f67a8744071a77b5328367e8399b70a97fa3b796733 | MATLAB | 152 | 10 | function[final_redcells]=sub_redcells(redcell_vect,toadd)
for i =1:length(toadd)
redcell_vect(toadd(i))=0;
end
final_redcells=redcell_vect;
end |
ceb8a7f5fb4f08bbb8b6d6d6d522b09b7b213321b7b322cf2229f02c0a811851 | MATLAB | 152 | 8 | % maximize current figure
function maximize(hf)
if ~exist('hf','var')
hf = gcf;
end
set(hf,'Units','normalized','outerposition',[0 0 1 1])
drawnow; |
7d588fcb4acac0cee8b7c7bdcfa16cb77a5d490043449f879a16d44859720004 | MATLAB | 153 | 4 | function SC = set_PG_ND(SC)
SC = flip_m(SC,'ND');
SC = change_exposure(SC,'PG',SC.PG_settings.ND_exp);
SC = laser_set(SC.laser_settings.laser_PG_ND,SC);
|
d8736eb5147dfb1e2bcdb4ec367dff33d5682b74d985e47b4660492c32e50d49 | MATLAB | 153 | 4 | function SC = set_PG_BP(SC)
SC = flip_m(SC,'BP');
SC = change_exposure(SC,'PG',SC.PG_settings.BP_exp);
SC = laser_set(SC.laser_settings.laser_PG_BP,SC);
|
450fdc56a088bc8f3e710fb5b3ae1b8dbb549635e2b878cffe2da1b10486f8a9 | MATLAB | 154 | 13 |
function x=move_to_cpu_values(x)
if iscell(x)
for tmp_idx=1:length(x)
x{tmp_idx}=gather(x{tmp_idx});
end
else
x=gather(x);
end
end |
285525ad397af3a54a6c1a25a1a40bb99edb22e2c46014f5df6b580adcd70b24 | MATLAB | 155 | 8 | function fun = ForwProbV1(x,ynn_v,tv,no)
ynn_v_r = x(1:no*tv);
ynn_v_r = reshape(ynn_v_r,size(ynn_v));
fun = sum((ynn_v - ynn_v_r).^2,'all');
end |
8bfac11843e98e4ea9676d093dbf8ae8e9d3b3f663d83984c23e16624806f672 | MATLAB | 155 | 10 | function x = logit(p)
% x = logit(p)
%
% Compute logit function:
% x = log(p./(1-p));
%
% Input: p \in (0,1)
% Output: x \in Reals
x = log(p./(1-p));
|
0863d7fa307ad2bd28eaccdfb49866b0d451c1fd04bbfe5079c60698a82ea9be | MATLAB | 156 | 6 | function h = ml_egomaps_draw_circle(x,y,r)
th = 0:pi/50:2*pi;
xunit = r * cos(th) + x;
yunit = r * sin(th) + y;
h = plot(xunit, yunit, 'k-');
end % function |
160d17a12338126160405ae4dbeaa85531cc425429020f18d7dfd835a4f4c1f7 | MATLAB | 157 | 7 | function [rr,ii] = mp2ri( mm, pp )
% Pass in the magnitude and phase and return
% the real and imaginary data
rr = mm .* cos( pp );
ii = mm .* sin( pp );
|
1f1aca5446b780caa88879a0cf7f26ef2a6c01a4d9b987d058b52f3f0ee25d8c | MATLAB | 157 | 6 | function y =LTP_D_func(temp,a,b,c,d,e,f,g,lam,p_d)
if p_d == 1
y = (a*tanh((temp/b)-c)).*(temp>=b*c);
else
y = d*exp(-(temp+e)/lam) + f*temp - g;
end |
ee36d544047e0ec8029d97ff676090c354c6ba5e0f2375606a4a586216423ba6 | MATLAB | 157 | 9 | function [I] = maxind(x,dim)
%maxind.m 8/3/21
% for when it is useful to not have to have I be the 2nd output
% inputs: x, dim
[v,I] = max(x,[],dim);
end
|
56b8c1a666e850598363dcdb3f16feaa09038f0d50e75ba73f6ee8707713bead | MATLAB | 158 | 8 | function showStructLabel( slabel)
for j = 1 : pixNum,
segs_pertree = slabel(:,:, j, :);
figure(i);
montage2(segs_pertree * 255);
end
end
|
6353eac63e403e84927f993801c16c6330fc344f911f8688be4e8e5b87305de8 | MATLAB | 158 | 13 |
function x=move_to_gpu_values(x)
if iscell(x)
for tmp_idx=1:length(x)
x{tmp_idx}=gpuArray(x{tmp_idx});
end
else
x=gpuArray(x);
end
end |
6c6268fb666b553fdb4b4e60417c16491a4bced0343e2c33cb6133045d8da874 | MATLAB | 159 | 11 |
% main_script
chamber_dim = 15; % or choices=15,45,135
model02_main_script;
model03_cross_section_XY;
model03_cross_section_XZ;
model03_cross_section_YZ;
|
b9c9a8282d40fa3534c991281ef611ea454c99d3e581bec88887244fe4c4e429 | MATLAB | 159 | 7 | function [mm,pp] = ri2mp( rr, ii )
% Pass in the real and imaginary data and return
% magnitude and phase
mm = abs( rr + 1i * ii );
pp = atan2( ii, rr );
|
26a0d71d3d84f89f38e74d081409c035bbbe98ddd760f73c51782e0ab10bd385 | MATLAB | 161 | 4 | function [edgesX, edgesY] = ml_it_edges_xy_uniform_density(x,y)
edgesX = ml_it_edges_x_uniform_density(x);
edgesY = ml_it_edges_x_uniform_density(y);
end |
4653e909ff55f98c228d1a93545ec0a9951fed3fe31cc89ec47e59181d3f154c | MATLAB | 162 | 9 | function lengths = returnCellLengths(x)
L = length(x(:));
lengths = zeros(size(x));
for i=1:L
lengths(i) = length(x{i}(:));
end
|
0758c3ff6ff1727ea5659d89acd463662e22b9b35212b6bb91932c2c69ae1b3a | MATLAB | 164 | 8 | function [controlFit] = controlFit (dat1, dat2)
reg = polyfit(dat2, dat1, 1); %dat1 is signal, dat2 is control
a = reg(1);
b = reg(2);
controlFit = a.*dat2 + b; |
50996562a4913023fa805af441f69a784c8ce25845fa8dff9cb0997db0b5335b | MATLAB | 165 | 11 | %% import and plotting functions
fn=('130625_001.2.wcp');
out=import_wcp(fn,'debug')
%%
plot_wcp(out,'recordings',10:20)
plot_wcp(out)
plot_wcp(fn)
|
6944cad3bc03e8fc9a1329589b59acabf7f9956cd0d97c1dabd01fb80ced58f5 | MATLAB | 165 | 7 | function result = fif(test, result_if_true, result_if_false)
if test ,
result = result_if_true ;
else
result = result_if_false ;
end
end
|
8de8e2e72cf0e5e0468249f405b633a1b186a14d059a1f325476dc37629c7198 | MATLAB | 165 | 11 | function C=My_colour_palette
C=[158 1 66;
213 62 79;
252 141 89;
254 224 139;
230 245 152;
153 213 148;
50 136 189;
94 79 162]./255;
end |
95a24bfd8db6303c1dcbccb94ae8411f91b448769f1ffd65865bc3c5c0181a07 | MATLAB | 167 | 9 | function indexes = randSample(N, fac)
indexes = false(1, N);
for i = 1 : numel(indexes)
if mod(i, fac) == 0
indexes(i) = true;
end %if mod
end %for i |
a8946deff9e104e3ee0feb0b35e9ee62e21c3fd0df78fda80fafee848efd68b0 | MATLAB | 167 | 8 | function [vc] = toCol(v)
%toCol.m
% vector to col orientation if not already
assert(isvector(v),'this function assumes a vector input')
vc = reshape(v,[],1);
end %fn |
b517d06c55a803c73cdb1c4fc476f3a27da51961092125e5143d94c0a5ee67b3 | MATLAB | 169 | 7 | function step = computeStepFromScale(scale)
if scale == 0
step = 2^scale;
else %if gaborBank(g).scale == 0
step = 2^scale * 3/2;
end %if gaborBank(g).scale == 0 |
25a14330972e2e739a4e1bf50e3d5a8254d84e238f090a2c599cf9e7320f7e25 | MATLAB | 171 | 6 | function W = exp_weight(X)
norm = X(:, 1) + 0.0001;
numer = exp(bsxfun(@rdivide, -X, norm));
denom = sum(numer, 2);
W = bsxfun(@rdivide, numer, denom);
end |
0288d02226cad28cc066deb5851ce39d26f14c6c15f5f9ca741afe967d7c574c | MATLAB | 173 | 12 | function w = precompute_dpss
% assume 1 second and 1000 Hz sampling rate
s = 1:0.5:50;
n = 1000;
w = cell(size(s));
for i=1:length(s)
w{i} = dpss(n, n*s(i)/1000);
end
|
648fa796f71846b76d4000fcea5e6e3c09b7620184904bae3de8128ec640ed38 | MATLAB | 173 | 9 | function out = sampleFromMatrix(data,N)
L = length(data(:,1));
if L <= N
out = data;
else
q = randperm(L);
out = data(q(1:N),:);
end |
7605115d2f26a76807bd3e89d6abb99f65eb9c3aa9745f31f8c60e35b3194c89 | MATLAB | 173 | 8 | function in = inrange(chan, range)
% function in = inrange(chan, range)
%
% Return logic if chan is within range
%
% RST 2006-04-05
in = chan > range(1) & chan < range(2);
|
6612379de10006a0e4f4e52fe89a60f0c8c3b3a841ed2ac0b8048158792923c0 | MATLAB | 174 | 13 |
function b_set=my_random_sample(a_set, sample_num)
a_num=length(a_set);
if a_num>sample_num
b_set=a_set(randsample(a_num, sample_num));
else
b_set=a_set;
end
end |
9d43763d8d3aa15dfb192d0082f7e197bf4bef20ebe8cd5efc39dfbfc78ee4da | MATLAB | 175 | 8 |
function [x,y] = getcirc(cx, cy, radius)
theta = linspace(0,2*pi,100); %you can increase this if this isn't enough yet
x=cx + radius*cos(theta);
y=cy + radius*sin(theta);
|
f7a4f7ac27f94ed56f95282c5b028773efa09e385e994942b201aed4ea7e207b | MATLAB | 175 | 4 | function y =dopa_func(temp,thresh_size,d_0)
y = (temp-(d_0+thresh_size/2)).*(temp>=(d_0+thresh_size/2))...
+ (temp -(d_0-thresh_size/2)).*(temp<=(d_0-thresh_size/2)) ;
end |
36709b586fda9dcaddf25c8ff6e2187aa5a39d55dbeab85177f3cc58364f6b09 | MATLAB | 176 | 5 | function [positionProbMap] = ml_placefield_positionprobmap(dwellTimeMap)
% Location probability, p(x,y)
positionProbMap = dwellTimeMap / sum(dwellTimeMap, 'all');
end
|
21bcd9576b088ca62608a22a0380ab1ac96c7f3993dba39f79fd601bfb29b0af | MATLAB | 177 | 5 | % Marc Normandin, Muzzio Lab, Psychological & Brain Sciences, University of Iowa, 2024
function [fieldNames] = helper_possibleScalar3FieldNames()
fieldNames = {'map'};
end
|
1ab6f13266ef2acd2769d50b56303ad593a63147724da2ca95376a0d039f8eef | MATLAB | 178 | 11 |
function labeledFrame = labelSingleFrame(clusters, Ncells)
labeledFrame = zeros(1, Ncells);
for i = 1:length(clusters)
labeledFrame(clusters{i}) = i;
end
end
|
e3489881d3d454af052c5311560181655cad9af389fae8f4ce3d65114a1087d4 | MATLAB | 178 | 16 | %% Dendritic analysis guide Alex
%% Align using app
%% Make DFs
%% Make ROIs
%% Prep ephys
edit cutEPNikon
% Saves ephys for each image as 'epData'
%%
|
9adc6664c1f8f91c55c6a5c49657d01b51d9a0c9ba72ba4e452638a3b70e798f | MATLAB | 179 | 4 | function v = isdummytrk(trk)
v = (any(isnan(trk.x)) || length( trk.x ) == 0);
% if v, fprintf( 1, '%d of %d are NaN\n', length(find(isnan(trk.x))), length(trk.x) ); end %%%%%%%%
|
d81718d6e63a89a9652b49f481318b97bcfd4d150a2c672e4ba01686d450207d | MATLAB | 179 | 13 | function [newA] = insertValue(A,V,ix)
% assumes vector
tmpA = toCol(A);
newA = [tmpA(1:ix-1); V; tmpA(ix:end)];
if ~iscolumn(A)
newA = newA';
end
end
|
b7d800c70d14f1227a25926276bb410f0c7ba9031118fc6beab82c295db7e96b | MATLAB | 180 | 14 | function [subY] = sub_sqrt_y(Y,Nc);
Y = sqrt(Y);
neurons = 1:size(Y,1);
if Nc==0
Nc=size(Y,1);
end
neurons = neurons(randperm(size(Y,1)));
subY=Y(neurons(1:Nc),:);
end
|
e856b59b573fe463cdbe968f57fdfc440af0d15a6fe6a94340fb76e2340c4920 | MATLAB | 180 | 13 | %
%
%
function [] = mglEyelinkCMDPrintF(message, varargin)
%
%
%
formattedMessage = sprintf(message, varargin{:});
mglPrivateEyelinkCMDPrintF(formattedMessage);
end
|
6b89ab5d01516d707d7a0b300124f3298ebe630701f518a7a7ecf92e4e6995e9 | MATLAB | 182 | 10 | % aslDefaultCallback.m
%
% usage: aslDefaultCallback()
% by: justin gardner
% date: 09/04/10
% purpose:
%
function [task msc] = aslDefaultCallback(task,msc)
|
6d30f4fea31e075485d3ee42cbeef5dc927613498b553f2773b03029915e95e9 | MATLAB | 182 | 10 | function out = shuffledMatrix(x)
N = length(x(:,1));
L = length(x(1,:));
out = zeros(N,L);
for i=1:L
q = randperm(N);
out(:,i) = x(q,i);
end |
9d5adef3bf0cfd5b7e3f4f3e7b6f468c525819eedd53d03466bb4a4dba9a318b | MATLAB | 182 | 14 |
function make_ref_obj(input_var)
if isa(input_var, 'ref_obj')
return;
end
one_mutable=ref_obj;
one_mutable.ref=input_var;
assignin('caller', inputname(1), one_mutable);
end |
1a76498a5b2b7f366ec5e40b52e8ffc0845feaa9e3d4450a372728149ebc46c6 | MATLAB | 183 | 10 | %
% main_script.m
% Comment: Just run this script and it will create the model
%
model02_main_script;
model03_cross_section_XY;
model03_cross_section_XZ;
model03_cross_section_YZ;
|
aa22ffcf3e76d4097a977bd9238289287823eb9e45268218ebec0ab752785f46 | MATLAB | 183 | 8 | function [amp] = rmsamplitude(eeg)
%ALPHAPOWER Calculates log band power in the alpha (8-13Hz) band of an
% EEG signal.
eeg = sqrt(sum((eeg./mean(eeg)).^2));
amp = sum(eeg.^2);
end
|
10d708214e053a44599b59dfda5fc4fab888ee852be2f5c42e324d4a6e46d906 | MATLAB | 184 | 17 |
function ret = corr(a, b)
if nargin == 2
ret = corrcoef(a, b);
elseif nargin == 4
ret = corrcoef(a, b, c, d);
else
error('*** unsupported case');
end
|
782d05213929ea705cce984095e57a977d8bc6a21ab45ef334da01e9f4255946 | MATLAB | 184 | 12 |
function ret = rmse_full(A, U, X, V)
if ~size(V)
V= U;
end
di = A - U * X * V';
ret = sum(sum(conj(di) .* di)) / prod(size(A))
if isnan(ret) | isinf(ret), error('***'); end
|
ba4082a2f59bf54d8e6e7f2a8a4d12fd33b2513a206fe128fb82874553758f44 | MATLAB | 184 | 11 | figure(1); clf;
zmat=ones(8,8);
for ii=1:8,
zmat(:,ii) = ii;
end
zmat(:,ii+1) = zmat(:,ii);
zmat(ii+1,:) = zmat(ii,:);
surf(zmat)
view(0,-90);
colormap('jet');
colorbar
|
c4c14cd51a538125b2e1c31c4231a6dedfe37ad6a858cf37902359182f07d922 | MATLAB | 184 | 7 | function [] = renameParsedVariables(p)
fnToRename = fieldnames(p.Results);
for ff = 1:length(fnToRename)
eval([sprintf('%s = p.Results.(fnToRename{ff});', fnToRename{ff})]);
end
|
53b7390f48c8e5266901f5b527e3f9f8b8b038e4059e246336925591f390a4d9 | MATLAB | 187 | 6 | function output = GliomaImmunotherapyEndpoint(input)
% For optimal control using GPOPS-II
% used in the code GBMoptimalcontrol.m
Cf = input.phase.finalstate(1);
output.objective = Cf;
|
7e3c5db87a87ffef744ffeb45d1f595d6abb04251b140bf7e56a828be46c5823 | MATLAB | 187 | 9 | function display(ipa)
% INPLACE/DISPLAY Display an inplace array from the command line.
%
% Example:
% ipa = inplace(ones(5));
% ipa
disp([inputname(1), ' = ']);
disp(ipa.get_a()); |
2daf18aba06da9f9767d7a76a6196b85caee31aa4d9997009da3512e6b394461 | MATLAB | 188 | 8 | function writelog(LogFile, LogText, perm)
% writing to log file for cluster version
if nargin < 3
perm = 'a';
end
fID = fopen(LogFile, perm);
fprintf(fID, LogText);
fclose(fID); |
33ce745d144ff6c0a6b74634e232dead832b76971ef1c46022a4fd98ef8e1016 | MATLAB | 188 | 6 | function R2adj = computeAdjustedR2(data,prediction,numExplanatoryParams)
R2 = computeCoD(data,prediction);
n = size(data,1);
R2adj = ( (1 - R2)*(n-1) ) ./ (n - numExplanatoryParams -1); |
59f641b4d720358b3931c6b2bb0cdb842ea2a595b0c5f454f1d4e119186b8d92 | MATLAB | 188 | 15 |
val =
2x2x4 struct array with fields:
Ns
sts
NsShuf
stsShuf
ShufStd
SpikesExcluded
ShufAll
ShufAllNs
sts2dShufAll
sts2dShufAllNs
|
75fa8cd43250fcc12e176ad9fd2ade666ce39072cd5b9fdc3f742964d729f593 | MATLAB | 188 | 4 | function v = isalive(track,f)
v = ~isdummytrk(track) && track.firstframe <= f && track.endframe >= f;
% if isdummytrk(track), fprintf( 1, 'track at frame %d is dummy\n', f ); end %%%%%%%
|
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