sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
345f6b7281f1123897676cf37f47cf620994e097cdbd6c1e385500f303be1339 | MATLAB | 396 | 15 | function S_final = get_finalTrainingStageSessions(S)
% get training stage 9 days in S struct and remove everything else
usethese = cellfun(@(s) isstruct(s), S.pd);
S_final = S;
S_final.pd = S.pd(usethese);
S_final.peh = S.peh(usethese);
stage = cell2mat(cellfun(@(sess) sess.TrainingStage(1), S_final.pd',...
Unifo... |
40d2b879ad40a7dc5d2f36d0a7c9dc3afcd2153c21ffa424ecedc9dc9c2bfd39 | MATLAB | 396 | 19 | function openface=volface(t)
%
% openface=volface(t)
%
% find the surface patches of a volume
%
% author: Qianqian Fang, <q.fang at neu.edu>
% date: 2009/10/13
%
% input:
% t: input, volumetric element list, dimension (ne,4)
%
% output:
% openface: list of faces of the specified volume
%
% -- this function is... |
458b59bd8ff97e4cf8f6b95ff71b1cce28ee52f08ca7ee02d17813d61c3e81f0 | MATLAB | 396 | 11 | clear; close all
% Read the table from the CSV file
data = readtable('[path-to...]/pruningComparisonsMatlab/stats/bright/overall/pruneChannelInfoTableCV.csv');
%% Average Channels and ROI_SNR by Age
% Calculate the average 'Channels' and 'ROI_SNR' for each unique value of 'Age'
averageData = groupsummary(data, 'Age',... |
7fa74f8a60e0d8f53277911614cd406adc189c041fe20c4e3071e533e544bff6 | MATLAB | 396 | 24 | function [lpp] = tapas_ti_lpp(y, x, u, theta, ptheta)
%% General prior probability.
%
% aponteeduardo@gmail.com
% copyright (C) 2016
%
flpp = ptheta.method_lpp;
ns = size(theta, 1);
nc = size(theta, 2);
lpp = zeros(1, nc);
for i = 1:nc
tlpp = zeros(ns, 1);
for j = 1:ns
tlpp(j) = flpp(y{j, i}, x{j, i... |
8fb4b3f9b8056918aeab25db3db4c0e6cc146e1b182472bff9e960cdd9b7f407 | MATLAB | 396 | 15 | function plot_fig1f(datadir)
% Plot event-aligned head speed and head angle relative to the central nose
% port for an example session.
%
% INPUTS
% datadir: file path of data downloaded from Zenodo. Link to download can
% be found in README.
load(fullfile(datadir, 'data-published-DLCdata', ...
'J063_AChDA_202302... |
242ba9caa860e92dd817fdfc4e90002bdf0a275c12480d8bbfcd8bae7d1314bb | MATLAB | 397 | 12 | %% p = sepiatest.test_root()
%
% Description: returns the absolute path of the test/ folder (parent of
% the +sepiatest package), used to locate test/references, test/tier1_smoke, etc.
%
function p = test_root()
thisFile = mfilename('fullpath'); % .../test/+sepiatest/test_root
packageDir = fileparts(thisFile); ... |
64125fcf558d362efb4ffc30e90e20d6e84227efc2fb7f6fc8721443994004c2 | MATLAB | 397 | 20 | function sh_TimexCorr(G_t,R_t,Fs)
step=1;
nstep=length(G_t)/(step*Fs);
for i=1:nstep
[r(:,i),lags] =xcorr(G_t(1+step*(i-1)*Fs:step*i*Fs),R_t(1+step*(i-1)*Fs:step*i*Fs),2*Fs,'coeff');
end
time=(1:nstep)';
fig=figure('defaultAxesFontSize',18);
imagesc(time,lags/Fs,r)
ylim([-1 1])
colorbar
caxis([-1 1])
xlabel... |
9d35f3a931f9bbd7e67fa66d7baf7d7bc3c0641be8e4c0d72a6f717871ca8839 | MATLAB | 397 | 14 | function SL = calcu_S(EA)
% S = (\prod_{i=M}^{2}e^{A_i\Dleta t},...,\prod_{i=M}^{t+1}e^{A_i\Dleta t},...I_N)
% Inputs: EA, N-by-N matrix, e^{A_i\Dleta t}
% Outputs: SL, N-by-N*M matrix
[row,col,num] = size(EA);
SL = eye(row,col);
panel = eye(row,col);
for k = 0:num-2
p = num-k... |
a260d2cf053871e59035fa22af6757c1c0f0565f3fcc94f70a13b5a05bfd4cf0 | MATLAB | 398 | 6 | function stream = request_analog(stub, node_name)
request_builder = javaMethod("newBuilder", "org.pesaranlab.thalamus_grpc.ThalamusOuterClass$AnalogRequest");
selector_builder = javaMethod("newBuilder", "org.pesaranlab.thalamus_grpc.ThalamusOuterClass$NodeSelector");
request = request_builder.setNode(selector_bui... |
b71e1cf45879bfcd73db1626d14ce3d02245272f0c2faeef88eb4efed58fee74 | MATLAB | 398 | 19 | function [alpha,lamda]=ImageAnalysis(app)
Name=[app.imfolder,app.ImageDropDown_4.Value];
C=imread(Name);
J=imcomplement(C);
Max_pvalue=255;% double(max(J(:)))
imshow(J)
AUX=imcrop;
ECS=AUX<90;
struct=AUX>=90;
count_ECS=sum(ECS,'all');
count_struct=sum(struct,'all');
alpha=(count_ECS/count_struct)*100;
alpha... |
c4a837cf6de44fde286ffcb4f23abed491222c1ddfab60d405525a9259166432 | MATLAB | 398 | 18 | function [DataF]=sh_bpFilter(Data, Fband, Fs)
% Fband=[0.5 100]-band or [inf 100]-low or [1 ing]-high
% updated SH-20210210
% Often single type are passed trough...
Data=double(Data);
if Fband(1)==inf
[b,a]=butter(4,Fband(2)/(Fs/2),'low');
elseif Fband(2)==inf
[b,a]=butter(4,Fband(1)/(Fs/2),'high');
else
... |
2d91eb2157611d1f5cf9899a19b054078c37c02a49695fb97233372a53a9ea3b | MATLAB | 399 | 15 | function str_short = getAbbreviation(str_long)
% return abbreviation (str_short) for long string (str_long) if found in the list below,
% else returns str_long
% (c) Jiri, Oct23
if strcmp(str_long, 'Default')
str_short = 'DMN';
elseif strcmp(str_long, 'Dorsal Attention')
str_short = 'DAN';
elseif strcmp(str_... |
3d9ecf599e198e9697332e768db28ec6c218dc7b2701e1ac6808e90209af05f5 | MATLAB | 399 | 20 | % This is just a quick test for sanity of "permcca.m".
% For the main simulation function, see "ccainf.m".
N = 50;
Ny = 8;
Nx = 12;
Nz = 15;
Nw = 3;
nR = 200;
nP = 200;
pfwer = zeros(nR,8);
for rep = 1:nR,
fprintf('%d\n',rep);
Y = randn(N,Ny);
X = randn(N,Nx);
Z = randn(N,Nz);
W = randn(N,Nw);
[... |
fe8942636f772a2216c52544ef7af157748ea914047d0728f01999fe16e7620b | MATLAB | 399 | 17 | function v = randomlyPermute(v)
% randomly permutes the elements of the input vector (v).
%__________________________________________________________________________
% Copyright (C) 2010 Medical Research Council
import rsa.*
import rsa.fig.*
import rsa.fmri.*
import rsa.rdm.*
import rsa.sim.*
import rsa.spm.*
import r... |
3b17437fbddc92126b812f599de7119820df5a75571f8f9c62e7217430d95544 | MATLAB | 400 | 19 |
function [reservoir, beta, H] = oesnn_uad(features, max_neurons)
reservoir = [];
for i = 1:size(features,1)
candidate = features(i,:);
reservoir = [reservoir; candidate];
if size(reservoir,1) > max_neurons
reservoir(1,:) = []; % remove oldest
end
end
% ELM
hidden_neurons = 100;
W = rand(size(... |
4e22134b6566c3cae515a3eebd9796bc46393b228be912f1de2ead271f2e0347 | MATLAB | 400 | 19 | %{
# fitted parameters for the autoregressive process (nmf deconvolution)
-> reso.ActivityTrace
---
g : blob # g1, g2, ... coefficients for the AR process
%}
classdef ActivityARCoefficients < dj.Computed
methods(Access=protected)
function makeTuples(self, key)
... |
907d6e97382763c912fe35172fea7441ea4ecb8272fa5a948d49ac33c6f9ba17 | MATLAB | 400 | 19 | %{
# fitted parameters for the autoregressive process (nmf deconvolution)
-> meso.ActivityTrace
---
g : blob # g1, g2, ... coefficients for the AR process
%}
classdef ActivityARCoefficients < dj.Computed
methods(Access=protected)
function makeTuples(self, key)
... |
0135106286eb4e5ed780da67a982869752b62fcdf1895ae563fdae6e54b95db6 | MATLAB | 401 | 19 | %{
# Fitted parameters for the autoregressive process (CNMF)
-> preprocess.ExtractRawTrace
---
g : longblob # array with g1, g2, ... values for the AR process
%}
classdef ExtractRawARCoefficients < dj.Imported
methods(Access=protected)
function makeTuples(self, key)... |
53f2f1f1d08d5d6e8617b34f2342a57b5c94926fbfd2979c7eb7155b2961a352 | MATLAB | 401 | 19 | %USING_HG2 Determine if the HG2 graphics pipeline is used
%
% tf = using_hg2(fig)
%
%IN:
% fig - handle to the figure in question.
%
%OUT:
% tf - boolean indicating whether the HG2 graphics pipeline is being used
% (true) or not (false).
function tf = using_hg2(fig)
try
if nargin < 1, fig = gcf; end... |
6b9e00a660d3e00830786b37abb42d52144e4dae19422b17d942c4ad683e8869 | MATLAB | 401 | 15 | file_prefix='Default_AttFar_ori_Ori1_0_Con1_0d5__';
data_folder = '/ix/chuang/des307/';
Ntr = 38000;
N = 2e4;
X = zeros(Ntr,N);
data = load([data_folder file_prefix 'cond1_1_1.mat']);
X(1:Ntr/2,:) = double(data.X1);
data = load([data_folder file_prefix 'cond2_1_1.mat']);
X(Ntr/2+1:Ntr,:) = double(data.X2);
fr = mean... |
6c3e5e1a81fb83f18dd746e3731e1aaa710fed1f069e41087423a006af6ecf9a | MATLAB | 401 | 18 | % this is an interactive script to determine crop ranges.
% download mean.nii locally
cd ~/Desktop
% load gradunwarp results
a1 = load_untouch_nii('mean.nii');
vol = double(a1.img);
imagesc(max(vol,[],3).^.4); axis image;
imagesc(squeeze(max(vol,[],2)).^.4); axis image;
temp = {[12 110] [20 104] [4 83]};
% test ... |
6db36ec087dd0ed3abf6ffd89786fae74d8a95436bd84771a70c710200cb7e8b | MATLAB | 401 | 16 | function H = poiss_entropy(lambda,kmax)
%calculates entropy of a poisson distribution with rate lambda and max
%number of events k
%
%inputs: lambda: n x 1 set of rate parameters
% kmax: max number of events that can occur in single time bin
Hsum = 0;
for j = 1:kmax
Hsum = Hsum + lambda.^(j)*log(factorial(j... |
891af98d988464e7fd07e5a6a8acee16e660bc0a535b472a12b165a6aa34fb49 | MATLAB | 401 | 16 | function TD = getMeanTD(P)
% Calcola la media della durata target per ciascun soggetto nella struttura P
% Gestisce sia durata in cell array che vettore
TD = nan(numel(P),1);
for s = 1:numel(P)
d = P(s).dur;
if isempty(d)
TD(s) = NaN;
elseif iscell(d)
TD(s) = mean(vertcat(d{:}), '... |
9b96c7325796c4a64fcaa850d28415677c3fa30efafd9bf6b3a65c7c1a6b2e2d | MATLAB | 401 | 17 | function Q2r=essential_closestRepresentative(Q1,Q2,varargin)
[tMin,~,Q2]=essential_distMinAngle(Q1,Q2,varargin{:});
NQ1=size(Q1,3);
NQ2=size(Q2,3);
if NQ1>1 && NQ2==1
Q2=repmat(Q2,[1 1 NQ1]);
end
NQ=max(NQ1,NQ2);
Q2r=zeros(size(Q2));
for iQ=1:NQ
t=tMin(iQ);
Rz=[cos(t) -sin(t) 0; sin(t) cos(t) 0; 0 0 1];
... |
82de8864323a0402267fcc6c6dd1b912e07f23776519d0260657e3037c1a617f | MATLAB | 402 | 18 | load surf_single_subj_T1
figure; p = patch('Faces',faces,'Vertices',vertices)
view(135,30)
set(p,'EdgeColor','none')
lighting gouraud;
alpha(.5); lighth = lightangle(45,30); axis off;
set(p,'FaceColor',[.2 .4 .7])
% camh = camlight;
daspect([1 1 1]);
%set(gcf,'Color',[0 0 0])
hold on
%a = ones(200,150);
%a = a + 75;
... |
8cfeef84278de7e99e10be8ebf0b322aa5abbb1189c980b0f4ea141da4288520 | MATLAB | 402 | 19 | function [t, tr, b, w] = sero_srr_sampling_direct(ts, n, z, do_interleaved)
if nargin < 1
[ts, n, z] = sero_srr_default_image_pars();
[t, tr, b, w] = sero_srr_sampling_direct(ts, n, z, 0);
clf
sero_srr_plot_sampling_stats(tr, b, w)
return
end
if nargin < 4
do_interleaved = 0;
end
a ... |
8ea93eb0dbd2cca851c5f633e4bb037662f022a0a46b4384eda6072187576c27 | MATLAB | 402 | 13 | %{
preprocess.MethodAod (lookup) #
-> preprocess.Method
---
description : varchar(60) #
high_pass_stop=null : float # (Hz)
low_pass_stop=null : float # (Hz)
subtracted_princ_comps : tinyint # ... |
9a6e23057b6771d4a14156b0afe35588abbbbf02dcb299f9e6a5d4431fc10d37 | MATLAB | 402 | 18 | function meta_check_contrasts(DB,testfield)
% meta_check_contrasts(DB,testfield)
%
% Checks to see if each unique Contrast has one and only one level of the
% selected variable.
for i = 1:length(DB.Contrast)
tmp = DB.(testfield)(DB.Contrast == i);
if length(unique(tmp)) > 1,
fprintf(1,'Warning! Cont... |
d4301887d0657a4689c3ff12a75fb94143ebdfe5b8f4ca25eaf441523e0ea678 | MATLAB | 402 | 16 | classdef nnspnorm < nntest
methods (Test)
function basic(test)
h = 13 ;
w = 17 ;
d = 4 ;
n = 5 ;
param = [3, 3, 0.1, 0.75] ;
x = test.randn(h,w,d,n) ;
y = vl_nnspnorm(x, param) ;
dzdy = test.rand(h, w, d, n) ;
dzdx = vl_nnspnorm(x, param, dzdy) ;
test.der... |
fabd7c163451c87d55d8bd518cfd705aea12c73e1dd1d223a2f706b24f8d9d13 | MATLAB | 402 | 16 | function grid_mreg_short(namei)
try
load(...) % load data
frex = logspace(log10(0.01),log10(5),50);
mregvoxels = randperm(68100,3405); % Uniform sampling non repeating
conv_bold = morlet_convolution(mreg_ts(:,mregvoxels)',10,frex,8);
conv_res = mean(abs(conv_bold).^2,3);
save(sprintf('...convmr... |
3ae7d6984654077447a4d1c379050720d80c21296ea9d09e9b49fb23ff4276e1 | MATLAB | 403 | 20 | function str = num2string_fixeddigit(num, d)
% num2string_fixeddigit - convert a number to string with a fixed number of digits
%
% str = num2string_fixeddigit(num, d);
%
% examples for d=3: 12.3->'012', 99->'099', 999->'999', 1200->'1200' (overflow).
%
% Copyright (c) 2004 Gabriel Peyré
num = round(num);
str... |
689bd13ac5096b4fbe669d2df535e551a85cd5d3b2714de65cb3e10395a72950 | MATLAB | 403 | 15 | function output = loadTargetClassifier(dataPath, mouse, session)
% Wrapper around targetClassifier
% Load preprocessed data
% This data is already subsampled to the best 100 neurons and the desired
% time points
load(sprintf('%s%s_%s_cueLocked', dataPath, mouse, session), 'neurons', 'M')
% Params
config = M.config;
co... |
b66901409dc818268804c9de585b4dfd5008285eddaa1bd748bd50faf5dab0e6 | MATLAB | 404 | 22 | %{
# single unit in the scan
-> reso.ScanInfo
-> shared.SegmentationMethod
unit_id : int # unique per scan & segmentation method
---
-> reso.ScanSet
-> reso.FluorescenceTrace
%}
classdef ScanSetUnit < dj.Computed
methods(Access=protected)
function makeTuples(self, ke... |
e612162fe69b18380f0b8fad308c4c6e7053a890fd4ea352f89d214e95344cf3 | MATLAB | 404 | 10 | function [MYsoundTargets_matrix] = soundtargetsRepeated(soundTargets)
cfg.design.soundTargets=zeros(size(soundTargets,1), (size(soundTargets,2)+size(soundTargets,2)));
for t=1:size(soundTargets,2)
cfg.design.soundTargets(:,2*t-1) =soundTargets(:,t);
cfg.design.soundTargets(:,2*t)=soundTargets(:,t);... |
fdbb5ce31a6047859563d46dbc53d5017ce68599c6d3d932c2ef098da4f92e77 | MATLAB | 404 | 22 | %{
# single unit in the scan
-> meso.ScanInfo
-> shared.SegmentationMethod
unit_id : int # unique per scan & segmentation method
---
-> meso.ScanSet
-> meso.FluorescenceTrace
%}
classdef ScanSetUnit < dj.Computed
methods(Access=protected)
function makeTuples(self, ke... |
0f0566560021fa56f1460fb99c06a9203daa872b6dd3860e30fb96589420de88 | MATLAB | 405 | 18 | function [R, B] = generate_reward(nswitches)
[R, B] = deal(cell(nswitches, 1));
for i = 1:nswitches
R{i} = [randsample(1:5, 40, true),...
randsample(1:3, 40, true),...
randsample(1:5, 40, true),...
randsample(3:5, 40, true)]';
B{i} = [ones(40, 1)*1;...
ones(40, 1)*3;...
... |
592ab89209bfd92738d5f4acf97efb9b474fd4c89d3e34bf1d618a8eff6a856a | MATLAB | 405 | 9 | function S = sero_srr_add_noise(S, SNR)
% function S = sero_srr_add_noise(S, SNR)
% ADD NOISE
% This application has the following interpretation.
% Given that the true signal is 1, the high resolution image has a signal
% to noise ration equal to SNR. The low resolution image has an snr that is
% higher by a factor of... |
8b1151740781ca5dffc3fb3ccbbf17289f0dd3b7ccd93306152d3b939ca1ac5f | MATLAB | 406 | 17 | %{
# parameters for computing unit retinotopy
unitret_id : int # method id for generating unit retinotopy
---
sigma : decimal(4,2) # sigma used for gaussian smoothing, 0 for no smoothing
%}
classdef UnitRetParam < dj.Lookup
properties
contents = {
1 0
... |
2a6c70404c177f4e6cf246486682c2f98830bf69eacd6bc8a7932e513ce84339 | MATLAB | 407 | 16 | function clims = getColorLimits(threeDimArray)
% returns color limits from 'threeDimArray'
% (c) Jiri, Jan11
yVals =[];
for ch1 = 1:size(threeDimArray)
for ch2 = 1:size(threeDimArray,2)
for ch3 = 1:size(threeDimArray,3)
yVals = cat(1, yVals, threeDimArray(ch1,ch2,ch3));
end
end
end... |
747c443bf214c14fd3892eb0d23ed231b7848324afb8975ff4fc768fe0b8f8cb | MATLAB | 407 | 17 | function indic = meta_stochastic_mask(xyzlist,n,r)
% indic = meta_stochastic_mask(xyzlist,n,r)
%
% Makes convolved spheres at n randomized locations within analysis mask
% Works in indicator (indic) format for speed
%
% tor wager
v = size(xyzlist,1);
wh = ceil(rand(n,1) .* v);
xyzvox = xyzlist(wh,:);
%indic = meta_f... |
a8f57e1fade550b9235bd4d02b2db8627fc96321ef633631ad58d87b1c38fcfd | MATLAB | 407 | 11 | function ce = CE(T)
%This function calculator is an estimate for a time series complexity [1] (A more complex time series has more peaks, valleys etc.).
% References [1] c, Gustavo EAPA, et al (2014). c. Data Mining and Knowledge Discovery 28.3 (2014): 634-669.
% original
ce = sqrt(sum(diff(T).^2));
%
%ce = sqrt(sum... |
c4dca3af13c116e9e01538257c3a246a5768894c07e2642e275792f065d4c095 | MATLAB | 407 | 19 | function [b] = get_rand_idx(num_idx,N,delta)
% Produce set of random integers with minimum intervals
% N = 10; % number of integers required
% delta = 2; % minimum difference required
a = randperm(num_idx);
idx = 1;
b = a(idx);
while(length(b) < N && idx < length(a))
idx = idx+1;
c = abs(b - a(idx)... |
65f8348abbb02fffe48f9f9963dcb6665b766007e31c65cf25e94e785c566206 | MATLAB | 408 | 19 | function varargout=fear_getLFPpath(lfpPath)
[lfpDir,sesName,~]=fileparts(lfpPath);
if ~exist(lfpPath,'file')
lfpDir=fullfile('/Volumes/My Passport for Mac/lfp/',sesName);
lfpPath=fullfile(lfpDir,[sesName,'.lfp']);
if ~exist(lfpPath,'file')
error('LFP file not found for %s',sesName)
end
end... |
8724f0e0be0fe4753b0b8c9caa4041200a48615fec1f8d30ea0710f41cd76923 | MATLAB | 408 | 21 | clear all; close all; clc;
% July 8, 2018, NB
n = 5;
p = 3;
k = 2;
M = rotationsfactory(n, k); %, true);
% M.retr = M.retr_qr;
% M.invretr = M.invretr_qr;
M.retr = M.retr_polar;
M.invretr = M.invretr_polar;
X = M.rand();
S = M.randvec(X);
S = M.lincomb(X, randn(1), S);
Y = M.retr(X, S);
V = M.invretr(X, Y);
fprintf... |
c1dabe55016d971c87ddba3fb996c3d6386ccbee29c4eeefee2d085a3f9774d4 | MATLAB | 408 | 17 | % This is the timer function to update the figure.
% Save as timerCallbackFcn.m
function timerCallbackFcn(hTimer, eventData, hfig, I, map)
figure(hfig);
% i is the frame index
persistent i;
if isempty(i), i=1; end
% display the i-th frame in the GIF
imshow(I(:,:,i),map);
% increm... |
f08892f815d1f74e1cd2d296a2015fb03e5b38ee4501e076204d57a8ffd6a191 | MATLAB | 408 | 24 | function x=nets_demean(x,dim)
% nets_demean(X)
% Removes the Average or mean value.
%
% nets_demean(X,DIM)
% Removes the mean along the dimension DIM of X.
if(nargin==1),
dim = 1;
if(size(x,1) > 1)
dim = 1;
elseif(size(x,2) > 1)
dim = 2;
end;
end;
dims = size(x);
dimsize = size(x,dim);
dimr... |
a9d650d279c5e8cc4a8bf3d2030379ee0e9b1a1b9150cc6d8a94f97576b40585 | MATLAB | 409 | 30 | function y = isinteger(x)
% ISINTEGER - True for natural numeric arrays
%
% test = isinteger(x)
%
% Where
%
% X is a numeric array.
%
% TEST is true if all the elements of X are integer numbers. Otherwise,
% TEST is false.
%
%
% See also: isnatural
y = isinteger(x);
if y,
return;
end
y =... |
d067d92f08d5147201c3f60b9a6b9ad7fba52cc0ca664f3271a7f681fc8fceb5 | MATLAB | 409 | 15 | %{
experiment.LaserCalibration (manual) # stores measured values from the laser power calibration
-> experiment.Rig
calibration_ts : timestamp # calibration timestamp -- automatic
---
-> experiment.Lens
-> experiment.Person
-> experiment.Software
pockel : mediumint # pockel setting
n... |
f5374475cf725c92e85a3af9ee30528f33c5b229c64907538b70c6b17026379e | MATLAB | 409 | 12 | %{
#
spike_method : tinyint # spike inference method
---
name : varchar(16) # short name to identify the spike inference method
details : varchar(255) # more details
language : enum('ma... |
4249a51ef11f74cbba9d82e2bf9124a189ce74891f913332833eba96a1e3bbb2 | MATLAB | 410 | 23 | %{
# set of units in the same scan
-> `pipeline_experiment`.`scan`
-> `pipeline_shared`.`#pipeline_version`
-> `pipeline_shared`.`#field`
-> `pipeline_shared`.`#channel`
-> `pipeline_shared`.`#segmentation_method`
---
-> fuse.Pipe
%}
classdef ScanSet < dj.Computed
methods(Access=protected)
function makeTuples(se... |
65a999cb55ec6bb99c5518cb3447cf55e974829ce3b3e0bfba62e9739a4c0e22 | MATLAB | 410 | 16 | function patchMatchCost(Patch1,Patch2,dInput, outputCost)
% compute the distance between patches from two subjects
%
A1 = load(Patch1); A2 = load(Patch2);
load(dInput);
A = zeros(size(A1.Patch,1),size(A2.Patch,1));
for i=1:size(A1.Patch,1)
for j=1:size(A2.Patch,1)
A(i,j) = d(A1.Patch{i,5},A2.Patch{j,5})*... |
5c51ffa21c2dec1a07024c1b0a01de0afb84ca7c9f92006a032225fe45aa2936 | MATLAB | 411 | 16 | classdef SoftMax < dagnn.ElementWise
methods
function outputs = forward(self, inputs, params)
outputs{1} = vl_nnsoftmax(inputs{1}) ;
end
function [derInputs, derParams] = backward(self, inputs, params, derOutputs)
derInputs{1} = vl_nnsoftmax(inputs{1}, derOutputs{1}) ;
derParams = {} ;
... |
9fa07eab34bb058b6bd428c295c1ea2d5eda366d1bfaef9828d5bcc621567e5b | MATLAB | 411 | 15 | function output = loadTargetXTClassifier(dataPath, mouse, session)
% Wrapper around targetXTClassifier
% Load preprocessed data
% This data is already subsampled to the best 100 neurons and the desired
% time points
load(sprintf('%s%s_%s_cueLockedXT', dataPath, mouse, session), 'neurons', 'M')
% Params
config = M.conf... |
962069e1d706e696612dee3dbacecd449ee11a8dbeca5058a2e43e3df5aa8e41 | MATLAB | 413 | 23 | function x=demean(x,dim)
% DEMEAN(X)
% Removes the Average or mean value.
%
% DEMEAN(X,DIM)
% Removes the mean along the dimension DIM of X.
if(nargin==1),
dim = 1;
if(size(x,1) > 1)
dim = 1;
elseif(size(x,2) > 1)
dim = 2;
end;
end;
dims = size(x);
dimsize = size(x,dim);
... |
b2b0a87048b0dfa3fc479d15ca12e01fe15e44834837b44caf3ca9b9c10a66c4 | MATLAB | 413 | 10 | function AddJavaClassPathInfoDynamics()
% Adds the path required for the infodynamics toolkit
% Required for the parallel workers, which don't always inherit the proper
% javaclasspath
computeDir = which('TS_Compute');
splits = regexp(computeDir,filesep);
hctsaDir = computeDir(1:splits(end-1));... |
4ad858e8abe458109a3bef3af64f508905a9591c9bdbf5ab7938206942f67270 | MATLAB | 414 | 16 | classdef SoftMax < dagnn_bc.ElementWise
methods
function outputs = forward(self, inputs, params)
outputs{1} = vl_nnsoftmax(inputs{1}) ;
end
function [derInputs, derParams] = backward(self, inputs, params, derOutputs)
derInputs{1} = vl_nnsoftmax(inputs{1}, derOutputs{1}) ;
derParams = {}... |
62b29f9c29d86bf456f23c0138ef1490bf3952aa24b5a937f37bbb1cba7b7c00 | MATLAB | 414 | 13 | function values = scaleSpectogram(values, spectrogramType, windowsize, samplerate)
switch spectrogramType
case 'Power Spectral Density'
win = hamming(windowsize);
values = abs(values).^2;
values = 1 / (samplerate * norm(win,2)^2) * values;
values(2:end-1) = 2*values(2:end-1);
... |
7da21fca023a27108339b3fa7db2376b1f0a5dd7911f20cdd5db502e7159324a | MATLAB | 414 | 17 | % (C) Copyright 2020 CPP visual motion localizer developpers
function varargout = postInitializationSetup(varargin)
% varargout = postInitializatinSetup(varargin)
% generic function to finalize some set up after psychtoolbox has been
% initialized
cfg = deal(varargin{:});
% Convert some values f... |
b992b40cd739e1716b53c51fa42def23e4761d2316d333ea3848baa158e3a510 | MATLAB | 414 | 22 | function [ibin] = bini(x,nbin,pbin)
if nargin < 3
pbin = 1/nbin;
end
if nargin < 2
error('Missing input arguments!');
end
if ~isvector(x)
error('Wrong input size!');
end
xbinbeg = quantile(x(:),linspace(0,1-pbin,nbin));
xbinend = quantile(x(:),linspace(pbin,1,nbin));
ibin = false(numel(x... |
cf2dc0df6be186e6210c0811bf174d100052125f447b49934460e3d5aba6b10e | MATLAB | 414 | 13 | function adjM = genRandSmallWorldNetwork(numNodes, K_edge, beta)
G = WattsStrogatz(numNodes, K_edge, beta); % generates symmetric (undirected) small-world network
adjM = full(adjacency(G));
numEdges = sum(sum(adjM == 1));
edgeWeights = rand(numEdges/2, 1);
adjM_U = triu(adjM);
adjM_U(adjM_U == 1) = edgeWeights;
adjM... |
da178c7a8e0f1294e728552b6ad34eed6c21f7afe54709d4ffe3a6a4cfc06190 | MATLAB | 414 | 21 | function [ix_dim,ix_tau,jx_act] = embed_trans_index(ix_act,M,D,mode)
if ~exist('mode','var'), mode = 0; end;
flg = zeros(M,D);
flg(ix_act) = 1;
% find active X-dim
ix_dim = find( sum(flg,2) > 0 );
% find active t-dim
if mode==0
ix_tau = find( sum(flg,1) > 0 );
else
ix_tau = 1:D;
end
% find activ... |
eb3f80cba7143eb3fdb45b60ec0312f71a3c69b2ac1ebc3507ebbec953f675eb | MATLAB | 414 | 22 | function ListSubjName(SubjsDir)
if nargin==0
SubjsDir= uigetdir([],'select a input folder') ;
end
[DirPath, fileN, extn] = fileparts(SubjsDir);
list = dir (SubjsDir) ;
if exist ([SubjsDir,filesep,'SubjList.txt'])
delete ([SubjsDir,filesep,'SubjList.txt']) ;
end
cd(DirPath)
for i = 3 : length(list)
... |
065a0b0eb3823401f4895a774e2fa65a191ef0585accabd29ba97aee619efed9 | MATLAB | 415 | 15 | % combineOnOffResponses.m - threshold and sum on-off RF phase responses
function complexResp = combineOnOffResponses(respP1,respP2,threshold)
% default: threshold opposing responses instead of squaring and summing
if ~exist('threshold','var'); threshold = 1; end
if threshold
respP1(respP1<0) = 0;
respP2(resp... |
6c78230bec562725e5096e24f3e44083fa6fe79a293f786e9f5a38c3153221b1 | MATLAB | 415 | 13 | % This script is taken from the old 'callback2' variable. It is called when
% the radio button 'resample' is selected on the main ARTwarp GUI figure,
% and enables the user to enter a value to the 'sample interval' field
% (un-dims the field)
h1 = findobj('Tag','resample');
h2 = findobj('Tag','sampleInterval');
s1 = g... |
dd2d53a76fee2c7a16df1a33cda1af7284d0ed372d6247362972e0ce2e47d3ea | MATLAB | 415 | 19 | %%%make averaged EMG
% SR, stampSR = kHz
% sttime,endtime = ms
%
function [edata] = avEMG(data,SR,stamp,stampSR,sttime,endtime)
if SR == stampSR
else
stamp = round(stamp.*SR./stampSR);
end
emg_row = [];
for trial = 1:max(size(stamp))
st=stamp(trial)+sttime*SR;
et=stamp(trial)+endtime*SR;
if st>1 &&... |
e282b601ff777efccbf26303abc9ab349d039cac280c96a9ece119494879cc0c | MATLAB | 415 | 12 | function stop = myoutput(x,optimvalues,state,ops)
% MYOUTPUT: a function to call during optimization for periodic saves
%
% ops must be a struct containing "savefreq", number of iterations
% between saves
%
savefreq = ops.savefreq;
stop = false;
iteration = optimvalues.iteration;
if rem(iteration... |
4a2e08e1f9002c4457968ab2df4bc26d85056ea6fe4c390996e0c14d44292e39 | MATLAB | 417 | 16 | function [rez] = Chan_template(rez,criteria)
N_clust = length(unique(rez.st(:,3)));
U = rez.U(:,:,1);
Chan = cell(N_clust,1);
Chan_score = cell(N_clust,1);
for i =1:N_clust
U(:,i) = U(:,i)/max(U(:,i));
id = find(U(:,i)>=criteria);
[~,chan_order] = sort(U(id,i),'descend');
Chan{i} = id(chan_order);... |
890a9aa8e4bab6f9a57b225e1be61ab361e25178272e0a92ba0704089716880b | MATLAB | 417 | 20 | function printConsoleSection( input_args )
%PRINTCONSOLESECTION( input_args )
%
% INPUT:
% input_args [string]: section title
%
% EXAMPLE:
% printConsoleSection( 'Hello World!' )
%
% === Jan Moelter, The University of Queensland, 2017 ===================
%
S_Z = 80;
fprintf( 1 , [ repmat( '_' , 1 , S_Z )... |
e5dc5266a06171192cca6b68e8417cdd3e8963b86605d9de704b1e16dfaa6228 | MATLAB | 418 | 17 | function eta=eta_squared(z)
%Compute similiarity between rows of z
%z=rand(10,100);
%z(2,:)=z(1,:)+randn(1,100)*0.3;
N=size(z,1);
p=size(z,2);
eta=zeros(N,N);
for i=1:N
mu=(repmat(z(i,:),N,1)+z)/2;
mu_bar=mean(mu,2);
eta(:,i)=sum((repmat(z(i,:),N,1)-mu).^2 + (z-mu).^2,2);
eta(:,i)=1... |
afd8d1ca249d784ce5a2b865ebe15e6d5edbb1ecc4e2ec2563012b9654b8157a | MATLAB | 419 | 25 | % (C) Copyright 2021 Remi Gau
clear;
clc;
% Sets up the environment for the analysis and add libraries to the path
initEnv();
%% Set options
opt = demoGetOption();
checkDependencies();
%% Run batches
reportBIDS(opt);
bidsCopyRawFolder(opt, 1);
bidsSTC(opt);
bidsSpatialPrepro(opt);
% The following do not run on ... |
b9130ce05fd31b36daf6502f660ed0ad03e1b7355f95ad5ba6fedd56f3da122a | MATLAB | 419 | 16 | function [rez] = Chan_cluster_M(rez,criteria)
N_clust = length(unique(rez.st(:,end)));
U = rez.U(:,:,1);
Chan = cell(N_clust,1);
Chan_score = cell(N_clust,1);
for i =1:N_clust
U(:,i) = U(:,i)/max(U(:,i));
id = find(U(:,i)>=criteria);
[~,chan_order] = sort(U(id,i),'descend');
Chan{i} = id(chan_orde... |
ca243985829d7adc334ef7bdfdfacdc16457e5dccb290916aa3c8f0f2911d0c2 | MATLAB | 419 | 20 | function [region, sensor] = standardizeInputs(region, sensor)
if strcmpi(region, 'dms')
region = 'DMS';
elseif strcmpi(region, 'dls')
region = 'DLS';
elseif strcmpi(region, 'nacc')
region = 'NAcc';
end
if strcmpi(sensor, 'da')
sensor = 'DA';
elseif strcmpi(sensor, 'ach')
sensor = 'ACh';
elseif strc... |
9440e363a730627c148e31e8a2604edcf4177005304c8ffc1fd885b46315af61 | MATLAB | 420 | 13 | function [P] = likelihood_fun_inv_curve(Ai,x0i,ni,Amean,Astd,x0mean,x0std,nmean,nstd,noiseStd,r,conc)
er = @(A,x0,n) r - A./(1+exp(-n.*(conc - x0)));
Per = @(A,x0,n) sum(log(1./sqrt(2 * pi * noiseStd.^2)) - 1/2 * er(A,x0,n).^2./noiseStd.^2);
PA = @(Ai,Amean,Astd) log(1./sqrt(2 * pi * Astd.^2)) -1/2*(Ai - Amean).^2/A... |
56dd6e6f321ce3a89fe7b6d2a2476c6275a51c0f857c422e298559603fbec947 | MATLAB | 421 | 17 | function [out]=istensor(M)
% ISTENSOR True if input is a 3D array.
% ISTENSOR(M) returns logical 1 (true) if M is a 1-by-n or n-by-1 vector,
% and logical 0 (false) otherwise.
%
% See also ISSCALAR, ISROW, ISCOLUMN, ISMATRIX, ISNUMERIC, ISLOGICAL,
% ISCHAR, ISEMPTY, SIZE.
% 2020-06-01: created by ... |
8b9611a4c2a20385ec401fb33676ea7ae94562fa7149b7607115489c712882cc | MATLAB | 421 | 12 | function [yfit,beta] = fitExponUtilityFunction(x,y,plotFlag)
% function [yfit,beta] = fitExponUtilityFunction(x,y,plotFlag)
%
% This function fits the logistic function implemented in the code
% exponUtilityFunction.m using ordinary least sqaures.
startBeta = [1 1];
func = 'exponUtilityFunction'; beta = lsqcurvefit(fu... |
960bd2e1aef0b103177629c4ac0f750860f9d8234a89a36e0dd44505a80c9e57 | MATLAB | 421 | 13 | function reset(obj)
%RESET Reset the DagNN
% RESET(obj) resets the DagNN obj. The function clears any intermediate value stored in the DagNN
% object, including parameter gradients. It also calls the reset
% function of every layer.
obj.clearParameterServer() ;
[obj.vars.value] = deal([]) ;
[obj.vars.der] = deal... |
060994da9cb2ceff6da729558476dbad227f1704eb05a3d451259ce1b1dcc7f6 | MATLAB | 422 | 21 | function plotSkeleton(posXYZ, plotParams, view)
% Configure plot
fig;
hA = gca;
hA.View = view;
axis(hA, 'equal');
axis off
hA.ZLim = [-18, 17];
hA.XLim = [-5, 65];
hA.YLim = [-25, 20];
% Loop over time points, adding offsets
for t = 1:size(posXYZ,1)
pos = posXYZ(t,:,:);
pos = pos - pos(:,:,15) + repmat([t * ... |
bfedc58524440253e7b94203dbae9c47b10a27faf32741cfc157361448ca8e41 | MATLAB | 422 | 20 | function [high_rats, low_rats, T] = HiloAcrossRats(thirdrew_arg,...
ratlist, Pstruct, Bstruct)
high_rats = cell(length(ratlist), 1);
low_rats = cell(length(ratlist), 1);
for rat = 1:length(ratlist)
ratname = ratlist{rat};
disp(ratname)
[high, low] = hilo_one_event(Bstruct.(ratname), ...
Ps... |
c1b4428c2f0c5ddfddfd2a0e946a1afa0251392b2d7cf155e161e913f7eb8136 | MATLAB | 422 | 15 | function [ahr, binvals] = bincell_to_submat(ahr_cell,binvals_cell)
% [ahr, binvals] = bincell_to_submat(ahr_cell,binvals_cell)
%
% summarizes celled ahr data into subject matrix
%
% jbh 2/26/21
N = length(ahr_cell);
binvals = unique(vertcat(binvals_cell{:}))';
ahr = nan(N,length(binvals));
for ss = 1:N
... |
c2d09ec11682e11f109aae3b6c059c4d7e2f28ec12695243486a97878d502538 | MATLAB | 422 | 25 | classdef euclidean < brca.dot.base
% FORMAT dot = brca.dot.euclidean()
%
% Euclidean inner product (dot)
properties
Lattice = 1
end
methods
function obj = euclidean()
end
function x = solve(~,x)
end
function x = dot(~,x,y)
x = x(:)'*y(:);
... |
ca8068f74e303e170c3c844aea22e64594b9115568bd0092b5d02b604435c865 | MATLAB | 422 | 21 | function [itiMdl, itiOpt, V, rpe, alpha, G] = generate_ph_mdl(...
R, alpha0, D)
[V, rpe, alpha, G] = deal(nan(size(R)));
V(1) = 2.5;
for tt = 1:length(R)
if tt == 1
G(tt) = 1;
else
G(tt) = abs(rpe(tt-1));
end
alpha(tt) = min(alpha0*G(tt), 1);
rpe(tt) = R(tt) - V(tt);
V(tt+1... |
0555e2eaf48e6d9008e335775f471e93246d5cf7250e5cb5144d6789de5d1775 | MATLAB | 423 | 15 | function [bval_arr_new, dwi_img_new] = bvalOrderFix(bval_arr,dwi_img)
disp(['Reordering B0 to start of imaging sequence'])
if size(bval_arr,1) > size(bval_arr,2)
bval_arr = bval_arr';
end
% bval_arr_new = [bval_arr(end) bval_arr(1:end-1)];
[bval_arr_new,idx] = sort(bval_arr);
% dwi_img_new = cat(... |
136991f694d0c1db0624eee6639367f922266846c174301b844cfc5b53962d03 | MATLAB | 423 | 15 | function [ output_args ] = meanActivityPattern( activityPatterns , activityThreshold )
%MEANACTIVITYPATTERN ( activityPatterns , activityThreshold )
%
%
% === Jan Moelter, The University of Queensland, 2018 ===================
%
%% AVERAGE ACTIVITY PATTERNS
output_args = mean( cell2mat( activityPatterns ) , 1 );
%%... |
1bb9bd9435451239c7f7fee10dc259bf6152734100ac2dcbfef2232a6f20c25f | MATLAB | 423 | 18 | % Compute the log intensity for the inverse link function g(f) = exp(-exp(-f)).
% Output range: 0 <= g(f) <= 1.
%
% The function can be used in GLM likelihoods such as likBeta.
%
% Copyright (c) by Hannes Nickisch, 2016-10-04.
function [lg,dlg,d2lg,d3lg] = glm_invlink_expexp(f)
lg = -exp(-f);
if nargout>1
dlg ... |
ff8bf7f002b08331dd72b9ff8e71179955d507d47f2fb5bb49c90671d77fca5e | MATLAB | 423 | 25 | function [htheta] = tapas_sem_seria_htheta()
%% Returns the standard hyperpriors.
%
% Input
%
% Output
% htheta -- Standard parameters of the sampler.
% htheta.pk is the precision kernel.
% aponteeduardo@gmail.com
% copyright (C) 2015
dim_theta = tapas_sem_seria_ndims();
% Precision kernel
hthe... |
894cc3575744409fdbb2ecb62d022addf2c0f8ee4d8be8a3ec8db84f02273520 | MATLAB | 424 | 14 | % info
name = 'ICLabel';
filetext = fileread('eegplugin_iclabel.m');
version = regexp(filetext, 'vers = ''ICLabel(\d+\.\d+\.?\d*)'';', 'tokens');
version = version{1}{1};
% enumerate files/directories
files = dir();
file_names = {files.name}';
file_names = file_names(cellfun(@isempty, ...
regexp(file_names,['^\.|\... |
a83f888576f6619e739e14bca01cf4871d2ca40d8f5557283be5fc13ab119461 | MATLAB | 424 | 26 | % plot_predict(ytest,ypred)
% time range for plot
%Tlim = [200 500];
[N,T,Ntr] = size(ytest);
yt = reshape(ytest,[N,T*Ntr]);
yp = reshape(ypred,[N,T*Ntr]);
% Plot prediction for test data
NY = 2; NX = 1;
nfig = 0;
for n=1:N
nfig = nfig+1;
if nfig > NX*NY, figure; nfig=1; end
subplot(NY,NX,nfi... |
e5551b59b153d8a0c3005a04543fba1a0c52122133f05e02881cee73f40789ee | MATLAB | 424 | 21 |
% Make this a script
1;
function res = logging_genStackTest(v)
if v > 4
res = strfcallstack();
return;
end
res = logging_genStackTest(v+1);
return;
% Check that genStackTest produces the preamble
v = logging_genStackTest(1);
teststr = sprintf('Stack trace:\n\tat');
assert(v(1:16) == teststr);
% Chec... |
6e627acd5bd0fb46d15d1220ca3431e98491ace0c9d4dc25e1f03ca5a3d06f29 | MATLAB | 425 | 12 | function [VRon] = VRmask(y, ythreshold)
% Creates a mask [VRon] for a given trace that is 1 if the Virtual Reality
% is turned on (0 if off).
% y: a vector of recorded positions indexed by frame numbers.
% Note that 1 unit of y equals 2 meters of real-world distance (as in the ball-VR system)
% ythreshold = y va... |
746bff392b973c94d90f39413d6584365b4cb677645360be985a513e1dddbbe8 | MATLAB | 425 | 23 | function out = gaussblur(im, rad)
out = zeros(size(im));
N = round(rad*5);
if mod(N,2)==0
N = N+1;
end
gaus2 = zeros(N,N);
midx = (N+1)/2;
midy = midx;
for x = 1:N
for y = 1:N
gaus2(x,y) = exp(-((x-midx)^2+(y-midy)^2)/(2*rad^2));
end
end
gaus2 = gaus2./sum(sum(gaus2));
for i =... |
0e4b0129552a66bf8104d5a7da5a06966270c19c49b0631800b7268bdef7a825 | MATLAB | 428 | 12 | %{
preprocess.SpikeMethod (lookup) #
spike_method : smallint # spike inference method
---
spike_method_name : varchar(16) # short name to identify the spike inference method
spike_method_details : varchar(255) # more details about
language ... |
1f4da7a3a06953518a68058f459cc5bb5f0cc5388907e3ba4ff7b0017dc3ac78 | MATLAB | 428 | 25 | %Numero de picos significativamente diferentes. LC
function [Y_Ren]=Npeaks(Y)
N=size(Y,2); %Número de picos
j=1;
for i=1:(N-1)
Ya=Y(:,i);
Yb=Y(:,i+1);
Yab=Ya-Yb;
Yab=abs(Yab);
if (sum(Yab)<=0.001) %Porcentaje de similitud
if (i==(N-1))
Y_Ren(:,j)=Ya;
end
e... |
123bb2cf42006a91208f05c25884e2f0e2b1fc65e9a32fa2fe2fb70b817d5001 | MATLAB | 429 | 16 | function r = genRandMatrix(vals, nRows, nCols)
% given vector of values vals, generates a matrix with elements randomly
% chosen from vals
% (c) Jiri, Apr11
% indexes
inds = 1:length(vals);
% matrix
r = nan(nRows,nCols);
for c = 1:nCols
r(:,c) = vals(round(linTransform(rand(nRows,1), [0 1], [min(inds)-0.5, max(i... |
b0896e4aa0febf3efc937b6068b2fcbe7f1dc741fafb90eb9d1dd0d58a66d859 | MATLAB | 429 | 21 | function dWU = alignWU(dWU, top,nt0min)
[nt0 ,~, Nfilt] = size(dWU);
dWU(isnan(dWU)) = 0;
for i = 1:Nfilt
if(isempty(nonzeros(dWU(:,:,i))))
else
[~, imax] = min(squeeze(dWU(:,top(i),i)));
dmax = -(imax - nt0min);
if(dmax>0)
dWU((dmax + 1):nt0,top(i), i) = dWU(1:nt0-dmax,top(i), i);
else... |
e0de7cab3bbc97536c4c790b00f89f1cb9081043ec5134bc682e1c5e66e55ad3 | MATLAB | 429 | 23 | function outvec = gauss(frames,sds)
% GAUSS - return a smooth Gaussian window
%
% Usage:
% >> outvector = gauss(frames,sds);
%
% Inputs:
% frames = window length
% sds = number of +/-std. deviations = steepness
% (~0+ -> flat; >>10 -> spike)
outvec = [];
if nargin < 2
help gauss
return
end
if ... |
e9d158b6eb74b564577611b6989e1f310e1f0bd47615222988a7efd136a3a815 | MATLAB | 430 | 18 | function vec_out = my_vector_shifter(vec_in,shift)
if abs(shift)>numel(vec_in)
error('the shift value you specified is bigger than the size of the vector!');
end
if shift==0
vec_out=vec_in;
elseif shift<0
end_point = vec_in(end);
vec_out = [vec_in(1-shift:end) end_point*ones(1,-shift)];
elsei... |
240b2ade46293be72f0262e119cffe30d4b67cf2f822b9726c35418361f89fbe | MATLAB | 431 | 21 | %{
# Pixelwise orientation response map
-> tune.OriDesign
-> tune.CaMovie
---
response_map : longblob # pixelwise normalized response
activity_map : longblob # root of sum of squares
%}
classdef OriMap < dj.Computed
methods(Access=protected)
... |
5a21167ff6277559ab795c460f468730f25724e004963bf6d433b5e2f9043681 | MATLAB | 431 | 17 | %{
aodpre.PreprocessMethod (lookup) # trace preprocessing
preprocess_id : tinyint # pre
---
preprocess_name : char(8) # brief description to be used in switch statements, etc
%}
classdef PreprocessMethod < dj.Relvar
methods
function fill(self)
... |
8dcf1610da3e2d323a7ff5dfd7a3e0f64e915c79b1934653d03b5a52f2da4734 | MATLAB | 431 | 19 |
function savePDF(figureHandle,name,directory)
if isempty(directory)
error('Sorry.. dont know where to save it...');
else
fullname=fullfile(directory,name);
if isfile(fullname)
% File exists.
delete(fullname);
else
% File does not exist.
orient(figureHandle,'landsca... |
1d5253cd7c3eac351cf23840ab31f526524e2101c4854b2a0ad2a443e33f624e | MATLAB | 433 | 12 | % create a channel map file
Nchannels = 32;
connected = true(Nchannels, 1);
chanMap = 1:Nchannels;
chanMap0ind = chanMap - 1;
xcoords = ones(Nchannels,1);
ycoords = [1:Nchannels]';
kcoords = ones(Nchannels,1); % grouping of channels (i.e. tetrode groups)
fs = 30000; % sampling frequency
save('C:\DATA\Spikes\... |
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