sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
30df48eee59bc5797be7b0f13f317f28e74e004c99d4a9495e9e98f336af8e6a | MATLAB | 1,542 | 36 | clear all
%%
%Define default parameters
[opt] = ParameterOptions();
%%
%Generate Pathway Amplitude & Gradient Waveform Dictionaries
%First Dictionary
[PathwaySignalFirstOrder,GwaveFirstOrder,TransFirstOrder] = PathwayOperatorOrder(opt,'First');
%Second Dictionary
[PathwaySignalHigherOrder,GwaveHigherOrder,TransHigherOr... |
34097c379da18ca181193cd9f85f7a4abe85539860848d3f5a1b4e084be7c522 | MATLAB | 1,542 | 48 | function IC = arrayToDims( I, dims, padEl )
% Pads or crops I appropriately so that size(IC)==dims.
%
% For each dimension d, if size(I,d) is larger then dims(d) then
% symmetrically crops along d (if cropping amount is odd crops one more
% unit from the start of the dimension). If size(I,d) is smaller then
% dims(d) ... |
f0ed651319cf2499bc3675077119ecba3fa6eaddf881f389803950086eb7ce6a | MATLAB | 1,542 | 44 | function avgs = getAvgByClass(A, classIDs)
% this function averages an array by 'type'. For example, class could be
% seizure, in which case the array elements will correspond to certain
% seizures and all elements corresponding to one seizure will be averaged.
% Same thing if the class was animal.
% Inputs:
% - A: a... |
594e37789d4baec3b5fda5cf30134acb7bb619048b2cd7ffd29b6b2c0594a5fc | MATLAB | 1,543 | 43 | function C = xcorrn( A, T, shape )
% n-dimensional cross-correlation. Generalized version of xcorr2.
%
% For 2 dimensional inputs this function is exactly the same as xcorr2, but
% also works in higher dimensions. Can also be more efficient because it
% performs convolution using convnFast. Note that xcorr2 is part o... |
89ee4f47012ec01d8b548d46baa619b5a1b6b3f41d43e3ce442895a49f97c39c | MATLAB | 1,543 | 29 | % Create coordinates of intersection contours and intersection edges
tissues = length(tissue);
PofYZ = cell(tissues, 1); % intersection nodes for a tissue
EofYZ = cell(tissues, 1); % edges formed by intersection nodes for a tissue
TofYZ = cell(tissues, 1); % intersected triangles
NofYZ = cell(tissues, 1);... |
9250ddb5f9555400deafd63e84612d0e2f04c99e6799a4b98b7c5a8307b28069 | MATLAB | 1,543 | 29 | % Create coordinates of intersection contours and intersection edges
tissues = length(tissue);
PofXZ = cell(tissues, 1); % intersection nodes for a tissue
EofXZ = cell(tissues, 1); % edges formed by intersection nodes for a tissue
TofXZ = cell(tissues, 1); % intersected triangles
NofXZ = cell(tissues, 1);... |
e85be58ae6a2668369312a1e4296171ca416e2b49b5d5888639ba8569a81c9ca | MATLAB | 1,543 | 52 | function varargout = plot_avSel5(vcf, avsd, summaryInfoTable, selSmltId, pcof1_act, pcof2_act, plRefSlop_act, id4col)
% similar to plot_avSel4, but with plot_avDis...2
% nsmlt = height(summaryInfoTable);
% for ksai = selSmltId
% ksai = k av id
% ksa = k av
for ksa = 1 : numel(selSmltId)
ksai = selSmltId(... |
81430860931f9eb986aa1dec35cf481779dfdd9319d0124b4ddcbb1e7b781f0a | MATLAB | 1,544 | 68 | function [meantheta,R,sigma,confangle,kappa]=anglemean(theta);
% calculates the mean of angles
%
% [meantheta,anglestrength,sigma,confangle,kappa]=anglemean(theta);
%
% anglestrength: can be thought of as the inverse variance. [varies between 0 and one]
% sigma: circular standard deviation
% confangle: a 95% co... |
83cc3556a310b9b32faa1bd1b9b8da626f5d8304efe75c9f18630750f4356fe5 | MATLAB | 1,544 | 43 | function opts = getGlobalDefaults()
% Returns a structure with default option values for Manopt.
%
% function opts = getGlobalDefaults()
%
% Returns a structure opts containing the global default options such as
% verbosity level etc. Typically, global defaults are overwritten by solver
% defaults, which are in ... |
a75a50b0080a700533bd414cee792dff0eb835dbbe43a0bbe8eb7a33ee2b52c8 | MATLAB | 1,544 | 49 | function fp = fmf_write_header( filename, header_size, version, ...
f_height, f_width, bytes_per_chunk, ...
max_n_frames, data_format)
% fp = fmf_write_header( filename, header_size, version,
% f_height, f_width, bytes_per_chunk,
%... |
7bb850c827697735f512d6284c9d4651d26e1cd9e0b8198f02cc01fbc1df3b48 | MATLAB | 1,545 | 72 | function synchrot = plot_syncro(synchro, chanlocs,cha,title,power)
% head plot, sincronia entre electrodos
% synchro = matriz de sincronia
% chanlocs = loacalizacionde electrodos
% chan = electrodos para plotear
%
xxx = 1%5;
yyy = 1%12;
if iscell(synchro)
meansyn = zeros(size(synchro{1}));
for i = 1:lengt... |
9f60cc4c7fe39d9fd668560bfe740ebdee3aad8fba193c3b7b73c6ef65d6751d | MATLAB | 1,545 | 47 | function [FM, xf] = ft_preproc_online_filter_apply(FM, x)
% function [FM, xf] = ft_preproc_online_filter_apply(FM, x)
%
% Passes signal x (channels times samples) through the filter,
% returns updated filter model (delay states) and filtered signal.
%
% See also FT_PREPROC_ONLINE_FILTER_INIT
% Copyright (C) 2010, Ste... |
a1538e6cd6b49b11e48268614a83ce583c04ae5dffb65c36dbe058a0f9d0bc3b | MATLAB | 1,545 | 55 | function [prep_data, data] = meg_getData(sqdfile,p)
% function [prep_data, data] = MEG_GETDATA(filename,parameters)
%
% INPUT
% filename: string path to sqd file
% p: structure of expt parameters
% OUTPUT
% data: time x channels x trials matrix
%
% Karen Tian
% January 2020
% dat = ft_read_data(sqdfile);
... |
f330d1fe5bd503733e4bfb601083d13f920c2ade28cd38b633dbb4eaaf333d72 | MATLAB | 1,545 | 44 | function CBIG_ASDf_checkJobStatus(progress_file, num_jobs, lag_time)
% CBIG_ASDf_checkJobStatus(progress_file, num_jobs, lag_time)
%
% This is a helper function that holds off the next jobs until submitted jobs
% are finished. Useful when the next job is dependent on the submitted
% jobs.
%
% Input:
% - progress_f... |
1251af74c20ce9db284ba8a9cff9746b2defed65702e3079e854252d151340bc | MATLAB | 1,546 | 43 | function IndividualROI = y_CheckIndividualROI(ROIDef, iSub, Flags)
% function IndividualROI = y_CheckIndividualROI(ROIDef, iSub, Flags)
% Check and get Individual ROI
% Input:
% ROIDef - ROIDef, any .txt definition would be checked
% Flags - can be: 'Seed_Time_Course_List:'; 'Seed_ROI_List:'; 'Covariable... |
3d7a7b05bdd6a4879c5273f4a385d015225604486b21dd4bb6c5f9f5e4f24175 | MATLAB | 1,546 | 53 | function [el, lab] = read_elec(fn)
% READ_ELEC reads "la/mu" electrode parameters from a MBF electrode file
% which are used to position them on a triangulated surface
%
% [el, lab] = read_elec(filename)
%
% where el = [tri, la, mu]
% and lab contains the electrode labels (if present)
%
% See also READ_TRI, TRANSFER_E... |
645aff9bca8d574fb7f6804bb77a4d5b58c66b2bf95cf4275f7c292b01ff9903 | MATLAB | 1,546 | 57 | function [pnt, tri] = read_off(fn)
% READ_OFF reads vertices and triangles from a OFF format triangulation file
%
% [pnt, tri] = read_off(filename)
%
% See also READ_TRI, READ_BND
% Copyright (C) 1998, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.fieldtriptoolbox.org
% for the documentation an... |
95628c95b56a90dfb6328b0a720b657cbcbd0167c295a14f728019a6e793a2e8 | MATLAB | 1,546 | 71 | function [counts,bin,centers] = histn(x,varargin)
% parse inputs
if length(varargin) < 1,
error('usage: [counts,bin] = histn(x,centers), [counts,bin] = histn(x,''edges'',edges)');
end
if ischar(varargin{1}),
if strcmpi(varargin{1},'edges') && length(varargin) >= 2,
edges = varargin{2};
nd = length(edges);... |
6dffb4aaa814bec97f0cdaf1d8c78fd96a7120af0b542cd2b22ea4a0ca16bce1 | MATLAB | 1,547 | 52 | %% trimdatacell
% Small utility to trim a dataCell to a given set of trials or channel row
% indices.
%
% INPUTS:
% dc
% - dataCell structure; either xtDataCell or ppDataCell
% TRIAL_LIST
% - Vector/Integer
% - Trial indices (dataCell columns) to include in trimmed dataCell
% CHANNEL_LIST
% ... |
725bac60a72a973b868d935fee4ce0f2d3dd6ee75c43e963d32a48c633aaf20c | MATLAB | 1,547 | 39 | function h_genericSettingCallback3(hObject, handles)
% this function try to setting the state variable for various fields so
% that coding is simplified.
% At some places, FV_settingQuality or FV_updateStateVar is used instead for enhanced
% functionalities.
global h_img3;
[currentInd, handles, currentStr... |
a9bbb78d8a78adc74c20aad8689a53ea99277de1956073c840939e2d6b5e976d | MATLAB | 1,547 | 43 | function [Stublinked, BlinkTimes] = Stublinks60(inputMat, SAMPLE_RATE)
% This code is a wrapper for stublinks.m, written by Sharif Kronemer
%SAMPLE_RATE = 1000;
DURATION = size(inputMat,2)./SAMPLE_RATE; %12000/1000 = 12
%Stublinked = zeros(size(inputMat)); %size 2 x 12000
%BlinkTimes = zeros(size(inputMat... |
abc958aa24c1d4cecba923310717c40ba80851c68f7f85cb39bd7e61627248e5 | MATLAB | 1,547 | 73 | % Visualize difference between KL(p,q) and KL(q,p) where p is a mix of two
% 2d Gaussians, and q is a single 2d Gaussian
% This is Figure bishop-5-4
%PMTKauthor Cody Severinski
clear all
mu = [-1,-1; 1,1];
Sigma = zeros(2,2,2);
Sigma(:,:,1) = [1/2,1/4;1/4,1];
Sigma(:,:,2) = [1/2,-1/4;-1/4,1];
SigmaKL = [3,2;2,3];
... |
27c4847ad1f5e1a76914fe6ccf1c3ffcfecf390252a4ffb7aa1293ff92889608 | MATLAB | 1,548 | 55 | function [dat_out,clindx,keepit] = iimg_cluster_prune(dat,datsig,volInfo)
% Prunes an image data vector (dat) assumed to contain suprathreshold
% contiguous clusters ("blobs") by saving only those blobs that have one or
% more significant (nonzero) elements in another image, datsig
%
% :Usage:
% ::
%
% [dat_out,cli... |
f8ac1c247c0ae66ddff84d01711584f5aab269152a3de38b45d16d7b05126487 | MATLAB | 1,548 | 45 | function extract_dropped_samples(varargin)
%extracts timestamps of samples dropped from Neuralynx file during the recording
%note that these samples must be removed at a later step in the pipeline,
%as during "drops" samples are drawn from the existing samples in the buffer and do not
%reflect real data.
if isempty(va... |
54a6d15a79b0df16097494a6875fec67ba4b18a70aff68873fab136397f18fd4 | MATLAB | 1,549 | 41 | function kout = breakup_seg(seg,th)
% splits up a segmentation into new unique disconnected labels
%
% Alexandru V. Avram, Ph.D.
% NIH 2022
%
if nargin<2
th = 100;
end
ct = 1; kout = seg*0;
CC = regionprops3(seg,'Centroid','VoxelIdxList','Volume');
for k = 1:length(CC.VoxelIdxList)
tmp = s... |
55d28d0f0b892f7a88280a35a76c087e69c748c59e0ce6ede2215499ef5f78ce | MATLAB | 1,549 | 40 | 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, H... |
999c531f9ff15fa2b6fb7ac18bd955a4a0dd3dad4278eafc3c9e378424bebd3e | MATLAB | 1,549 | 53 | function [yhat, py] = naiveBayesPredict(model, Xtest)
% Apply a Naive Bayes classifier
% We currently assume binary features
% For Gaussian features, use discrimAnalysis.
% yhat(i) = argmax_c p(y=c|Xtest(i,:), theta(c,:)), in 1:C
% py(i,c) = p(y=c|xi, params)
% This file is from pmtk3.googlecode.com
vectorized = tr... |
b1e4a21b7e831c8a2ed9640180d12801af3e5a23bf19c76678b3717d154f7ad9 | MATLAB | 1,549 | 48 | function t = subsasgn(t,s,b)
%SUBSASGN Subscripted reference for a ttensor.
%
% See also TTENSOR.
%
%MATLAB Tensor Toolbox.
%Copyright 2015, Sandia Corporation.
% This is the MATLAB Tensor Toolbox by T. Kolda, B. Bader, and others.
% http://www.sandia.gov/~tgkolda/TensorToolbox.
% Copyright (2015) Sandia Corporation... |
c320c91caec19ef98a313d2a686381cae1f6ac3630f2bbda1a6ca6f9a0d33189 | MATLAB | 1,549 | 36 | function [trl, event] = ft_trialfun_edf(cfg)
% FT_TRIALFUN_EDF is an example trial function. It searches for events of type "up"
% in an analog data channel, as indentified by thresholding. This threshold can be a
% hard threshold, i.e. a numeric, or flexibly defined by an executable string (e.g.,
% calculating the 'm... |
cde2d02743753498b86e3edf4f68bd287a7dfee79ed072dd39d099b52f982162 | MATLAB | 1,549 | 64 | clear;close all;clc;FS=22;
%pkg load image
% Co-ordinates and dispersions for the kernel
y=-81:80;
x=-86:85;
[X,Y]=meshgrid(x,y);
D=2;
t=1:30;
sigma2=4*D*t;
for j=1:length(t);
P{j}=exp(-(X.^2+Y.^2)/(4*D*t(j)))/(pi*4*D*t(j));
end
%%
% Затравочные иозображения с локализацией в 1 пиксель (разреше... |
744d1bc633d7165a72539952d598a5078643d81981450fd211da32f133c79829 | MATLAB | 1,550 | 32 |
% 1) Separation strategy
% Marker-Controlled Watershed Segmentation
% http://se.mathworks.com/help/images/examples/marker-controlled-watershed-segmentation.html
function [ nuclei_seg ] = segment_nuclei( nuclei_chnl )
% function: Short description
% Watershed segmentation
% https://blogs.mathworks.com/steve/2013/11... |
14ffd23ab9486afc580188cde1ff813267062e6c9e5d39e5aae3ad026ead788d | MATLAB | 1,551 | 50 | % RSKELF_CHOLSV Solve using generalized Cholesky factor from recursive
% skeletonization factorization.
%
% Typical complexity: about half that of RSKELF_SV.
%
% Y = RSKELF_CHOLSV(F,X) produces the matrix Y by applying the inverse of the
% generalized Cholesky factor C of the factored matrix F ... |
254885f8cff8822b2e6a903c4f6d518af33a29343491261be4a15fcf15458308 | MATLAB | 1,551 | 39 | function [config] = get_studydetails()
config = [];
% The location of the downloaded data
% eg: config.datadir = '/home/disk3/ajquinn/ds000117/';
config.datadir = ''; % <- edit this line
% The location of the downloaded scripts directory
% config.scriptdir = '/home/disk3/ajquinn/HMM_frontiers... |
60a85ad780ad26344ab1f34ba6d367f399fc88215c4ff5469887cc116630f861 | MATLAB | 1,551 | 43 | function [Nx, Ny, Nz] = GaussNormal(X,Y,Z,sigma)
%GaussNormal computes smoothened normal using Gaussian derivative
%
% GaussNormal(X,Y,Z,sigma)
%---------------------------------------------------------------------
% license
%-----------------------------------------------------------------... |
9ac036e6a86e7003728821447a320a338374d14aa82fa1569750ed06176cf78a | MATLAB | 1,551 | 62 | function C = mtimes(A,B)
%MTIMES Multiplies two tenmat objects.
%
% C = MTIMES(A,B) computes the product of A and B. The result is a
% TENMAT object and can be transformed into a tensor.
%
% C = MTIMES(A,B) is called for the syntax 'A * B' when A or B is a
% TENMAT object.
%
% See also TENMAT.
%
%MATLAB Tensor ... |
277fd9e617c8ff06a7b9187cb7ee22c1679a56ac22fbaba8a4ce68793d7e9339 | MATLAB | 1,552 | 64 | % assignSignal
% Assign signal from sigSL and sigRL
clear sl rl ylims
switch dim
case 'TinC'
sl = sigSL.TinC*1000;
rl = sigRL.TinC*1000;
ylims = [0 30];
if sub0 == 1
ylims = [0 20];
end
case 'TinI'
sl = sigSL.TinI*1000;
rl = sigR... |
86af6ac258e9e689957884ffbd39427d141245c25d13c75172080fc7d4a95b80 | MATLAB | 1,552 | 51 | % This program is free software; you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation; either version 2 of the License, or
% (at your option) any later version.
%
% This program is distributed in the hope that it will be useful,... |
a307d939ec13d31a4f11c50bd3b2fa3c0939e9d23c05c60e42a576e44d249e39 | MATLAB | 1,552 | 60 | function result = deflateimports(r)
import yaml.*;
result = recurse(r, 0, []);
end
function result = recurse(data, level, addit)
import yaml.*;
if iscell(data) && ~ismymatrix(data)
result = iter_cell(data, level, addit);
elseif isstruct(data)
result = iter_struct(data, level, addit);
else
... |
72460c435930c3d9d90f6b47164a38f5cbd4cd6f49f91edc120eadb0d41a27bd | MATLAB | 1,553 | 38 | function params = prepare_system_limits(params)
if params.gen.field_strength == 7
% 7T, SC72 gradient
lims = mr.opts('MaxGrad',65,'GradUnit','mT/m',...
'MaxSlew',200,'SlewUnit','T/m/s',...
'rfRingdownTime', 20e-6,'rfDeadtime', 100e-6,'adcDeadTime', 10e-6, 'B0',6.98); % To read it in VM I need ... |
eee3df2ed21ddffe05b09396fad980411cc23ad1da5bd0a7f39f4650f7f39b01 | MATLAB | 1,553 | 58 | CStr = textread('../filtered_transcripts.txt', '%s', 'delimiter', '\n');
%Load a sample file
data = load3DTif('/Users/Goody/Neuro/ExSeq/culture/input/sa0916dncv_round1_summed.tif');
gene_idx = 0;
gene_names = {};
gene_space = {};
transcript_locs= []; trans_idx =1;
%% Load all
for row_idx = 1:length(CS... |
0e334842536e6e9b41a4f5b4fc9aee901cd406af22ec9a4610e7577ae5e01121 | MATLAB | 1,554 | 27 | figure('Name', 'PEV Scatter', 'NumberTitle', 'off', 'color', [1, 1, 1], 'position', [360 50 600 400]); hold on;
clear h
rgb = [0.3 0.6 0.3; 0.1 0.4 0.5; 0.8 0.8 0; 0.5 0.2 0.2;];
% 1-way, z-score, 0.05 sign val: 1.645
signval = 1.645;
% non-significant
idx1 = avg_omega(:,1)<signval & avg_omega(:,2)<signval; n(1... |
53f5de3a78d77ad5db4539229752d1d810cde7fd870076e99079f614aa998e4e | MATLAB | 1,554 | 55 | % Function that computes the average subpopulation activity
% INPUTS:
% s0: spike times and indices of neurons which spike
% t_start: beginning of the timewindow we are interested in (ms)
% t_end: end of the timewindow we are interested in (ms)
% idxSelNeur: linear indices of the selected neurons
% bool_plot: 1 to plo... |
63bbec2a972b149f753468d6487d4c1cd532458fb8574fd0a4d4bb7e24115630 | MATLAB | 1,554 | 59 | %% Bootstrap demo for the MLE for a Bernoulli
%
%%
% This file is from pmtk3.googlecode.com
fs = 12;
setSeed(1);
theta = 0.7;
Ns = [10 100];
for Ni=1:length(Ns)
N = Ns(Ni);
B = 10000;
X = rand(1,N) < theta;
estimator = @(X) mean(X);
bmle = estimator(X);
mleBoot = zeros(1,B);
for b=1:B... |
6fcc43ed15fdf99acbd01877faf4908bd11060168f62a54ef39238cfbdcb5ae3 | MATLAB | 1,554 | 27 | figure('Name', 'PEV Scatter', 'NumberTitle', 'off', 'color', [1, 1, 1], 'position', [360 50 600 400]); hold on;
clear h
rgb = [0.3 0.6 0.3; 0.1 0.4 0.5; 0.8 0.8 0; 0.5 0.2 0.2;];
% 1-way, z-score, 0.05 sign val: 1.645
signval = 1.645;
% non-significant
idx1 = avg_omega(:,1)<signval & avg_omega(:,2)<signval; n(1... |
c0a0542033bdcf4d7f724d588fac58047f674bff19488741c651853aeaebae02 | MATLAB | 1,554 | 66 | function dy = CBIG_MFMem_rfMRI_mfm_ode1_4p(y,parameter,SC)
% dy = CBIG_MFMem_rfMRI_mfm_ode1_4p(y,parameter,SC)
% dy = CBIG_mfm_rfMRI_mfm_ode1_4p(y,parameter,SC)
%-----------------------------------------------------------------------------
% dy = CBIG_mfm_rfMRI_mfm_ode1(y,parameter,SC)
%
% Function for dynamica... |
e5cb8cb662391490105e4837e257d51263134671974f849f9b931db1c402faee | MATLAB | 1,554 | 45 | %% Generating the leading mode-n vectors
% The leading mode-n vectors are those vectors that span the subspace of
% the mode-n fibers. In other words, the left singular vectors of the
% n-mode matricization of X.
%% Using nvecs to calculate the leading mode-n vectors
% The |nvecs| command efficient computes the leadin... |
58a76eb8b67e061ba98675f3607b20c4956983033109ad555ba485458b53ced6 | MATLAB | 1,555 | 46 | function T = permute(T,order)
%PERMUTE Permute tensor dimensions.
%
% B = PERMUTE(A,ORDER) rearranges the dimensions of A so that they
% are in the order specified by the vector ORDER. The result has the
% same values of A, but the order of the subscripts needed to access
% any particular element are rearranged... |
49f562ad9f0a8581edcd1bd06dda4699c0e2d4142c88b88feed8f32e66e160cb | MATLAB | 1,556 | 50 | % Compare to Fasano & Franceschini simulations
n = [5 7 10 15 20 30 50 100 200 500 1000 2000 5000];
samples = 100;
Z = zeros(length(n),samples);
pval = zeros(length(n),samples);
for i = 1:length(n)
n(i)
tic;
for j = 1:samples
r1 = rand(n(i),2);
r2 = rand(n(i),2);
[p,D] = kste... |
defa39384a8f454d0d385b8b521c71f7a53d97c9297c1714f1b9b7144bacd629 | MATLAB | 1,556 | 43 | function [infos, status] = VBA_version()
% infos = VBA_version()
% return infos about the current version of the toolbox. It requires the
% toolbox to be installed using git (not by downlading the zip) to work properly:
% git clone git@github.com:MBB-team/VBA-toolbox.git
% OUT:
% - infos.path: path of the tool... |
1ef221b1845021d24c72b9593eec7073809a8906d8bac86f602072735709200b | MATLAB | 1,557 | 34 | function [max_run_jobs,max_run_jobs_downsampled] = concurrency_size_in_normalization_cuda(cond)
loadParameters;
if ~isfield(params,'NORM_MAX_RUN_JOBS')
main_mem_usage = params.MATLAB_PROC_CONTEXT;
job_worker_mem_usage = 4 * cond.imgsize_dbl + params.MATLAB_PROC_CONTEXT;
max_run_jobs = ... |
659b7311bfff5b64b352e2dd4e4735bf3c2ef48dd1f692f57752bb25aa0c556f | MATLAB | 1,558 | 40 | function [hs,ps] = forestApply( data, forest, maxDepth, minCount, best )
% Apply learned forest classifier.
%
% USAGE
% [hs,ps] = forestApply( data, forest, [maxDepth], [minCount], [best] )
%
% INPUTS
% data - [NxF] N length F feature vectors
% forest - learned forest classification model
% maxDepth - [] maxi... |
b8df9d4a799dfca7e672ee915accb171ccdc87868950090f96203ca0290f6902 | MATLAB | 1,558 | 59 | function paf = graph2paf(nodes, edges, sz, channelsOnly, sigma)
%GRAPH2PAF Converts a set of edges into part affinity fields.
% Usage:
% graph2paf(nodes, edges, sz, sigma)
%
% Args:
% nodes: set of points (N x 2)
% edges: indices into nodes defining directed edges (E x 2)
% sz: grid/image size (1 x 2)
% chan... |
9d6e87fe87ebf0229a647ec48abbe40593ade596add6cd91b06d79595f74d4fc | MATLAB | 1,559 | 33 | function [circle_centers, circle_radii] = generate_colony_centers_and_radii(num_circles, circle_size, circle_size_var, padding, inner_plate_radius, outer_plate_radius, min_border_distance)
circle_centers = zeros(num_circles, 2);
circle_radii = zeros(num_circles, 1);
pick_center = 1;
while pick_center <= num_circles
... |
d098114392c4c60f12c1ec5f8c52a873b497dd5d4dbd5fe70e0d1c3452c53431 | MATLAB | 1,559 | 52 | function filtsign = lan_fir2(LAN, min_freq, max_freq, chan)
% lan_fir2 realiza de forma intuitiva un filtro FIR sobre todos los canales
% especificados 'chan' en un entorno LAN, para uno o multiples trials, con
% un rollover constante de 0.5
% Los parametros min_xfreq y max_freq pueden ser [] o un número real:
% - Ban... |
d3af9102fa6ca5fa2b49e3923ed535ac94002c45cbe3330a6784f064309c3aee | MATLAB | 1,559 | 47 | %// temporary method for explicitly defining ppData components for OOP
%_______________________________________
% Copyright (C) 2024 Trevor S. Smith
% Drexel University College of Medicine
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as... |
456e7dd59daa6f03581ebb7a01a97dfd1aea21fdafd4a955a045b1ccd993e541 | MATLAB | 1,560 | 50 | function y = pinknoise(m, n)
% function: y = pinknoise(m, n)
% m - number of matrix rows
% n - number of matrix columns
% y - matrix with pink (flicker) noise samples
% with mu = 0 and sigma = 1 (columnwise)
% The function generates a matrix of pink (flicker) noise samples
% (columnwise). In terms of power at a co... |
56fe9a642a35d4697b4e79bd2cb02862b5294b3a0b471719890a8d8abcaf9d7e | MATLAB | 1,560 | 71 |
function convertFile2crabFormat(filename, file_ext)
% first check if it has already been converted
[~,a] = fileparts(filename.name);
if exist([filename.folder filesep a '.crab'],'file') == 2
disp('Already converted, skipping...')
return
end
self = crabsort(false);
self.path_name = filename.folder;
self.file_nam... |
a5a31cee9485eea1ce22346737f14bf4f0c8e9fcdef63d4dec869b0fb84dd581 | MATLAB | 1,560 | 58 | %% RosenBrock Demo
%
%%
%PMTKinteractive
%PMTKneedsOptimToolbox
% This file is from pmtk3.googlecode.com
% "A note on the extended rosenbrock function" Evol. Comp. 2006
% claims that for d=4 to 30 dims there are 2 local minima, at [1,1,...1] and
% and near [-1,1,...,1].
% Let us verify this for d=4 and d=5
%xstart =... |
c45ce928a9edc00b5bfad43332864c317a7d4219370060044d5344d5ae9e996e | MATLAB | 1,560 | 34 | function [max_run_jobs,max_run_jobs_downsampled] = concurrency_size_in_normalization(cond)
loadParameters;
if ~isfield(params,'NORM_MAX_RUN_JOBS')
main_mem_usage = params.MATLAB_PROC_CONTEXT;
job_worker_mem_usage = 6 * 4 * cond.imgsize_dbl + params.MATLAB_PROC_CONTEXT;
max_run_jobs = m... |
4277310c65b832017d6b767d1c62ba86cb047a4bfb8bbef29389abab9cb5596b | MATLAB | 1,561 | 41 |
function [rf_phase_offset,adc_phase_offset] = rf_adc_phase(params)
%% 3D RF and ADC phase
% This part is coming from ./Emily/RF_design/calcRFphase_3D.m
% I don't know how this works for 3D; I kinda know now
delta_x = 0;
Gslice = 9.5571;
Tpulse = 2560;
Asym = 0.5;
InitPhase = 90;
... |
8317a29b71192ed514ea4ccb299e2606ff165bccc057c28f2c10fb282cf14a7f | MATLAB | 1,561 | 66 | % demo GLM under multiple covariance components
% This demo exemplifies how to wrap the VBA model inversion scheme to make
% it estimate multipe covariance components within the context of a GLM
% analysis.
% function demo_covComp
Qy{1} = kron(diag([1;0;0]),eye(8));
Qy{2} = kron(diag([0;1;0]),eye(8));
Qy{3} = kron(di... |
b932ff199374819e1152cb25e19854e9b05508a5811a807139de4e1095808695 | MATLAB | 1,561 | 48 | function figName = createFigureName(toolName,targetFigureHandle)
% CREATEFIGURENAME(TOOLNAME, TARGETFIGUREHANDLE) creates a name for the figure
% created by the tool, TOOLNAME. The figure name, FIGNAME, will include
% TOOLNAME and the name of the figure on which the tool depends. TOOLNAME must
% be a string, and TARGE... |
c709c0c64c8ae7df96316d600d55a4a8870284b28d0551e49aea417c9bb51df2 | MATLAB | 1,561 | 72 | x = h5read('02_b3_000_000.hdf5','/estimates/F_dff');
x=xx;
b=size(x)
%x1=posTrials02
peak_num = [];
Prom = [];
peak_num = [];
Prom = [];
for l=1:b(2)
w=x(:,l);
figure
plot (w)
end
% ampD = [ampD Damp];
% Dcoord = [Dcoord DX]
% hold off
% end
%Damp=mean(w(DX-shag/2:DX+shag/2))
x1=[1:b(2)];
x2 = [];%%% tr... |
2000e26c89e42e8768de38253f3016b0da0efffd2cd0df74bc925320ceb9cb97 | MATLAB | 1,562 | 68 | % This program is free software; you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation; either version 2 of the License, or
% (at your option) any later version.
%
% This program is distributed in the hope that it will be useful,... |
38d9ab3662cc5aa18559211b46911e9b6a324743be41caeb4918c076b05e3adb | MATLAB | 1,562 | 39 | function generateAuthorLocReport()
%% Generate the html contributing author LOC report
% Create a table of authors and the total lines of code contributed
% PMTKneedsMatlab
% This file is from pmtk3.googlecode.com
dest = fullfile(pmtk3Root(), 'docs', 'authors');
pmtkRed = getConfigValue('PMTKred');
R = pmtkTagRep... |
7063bff46ee1468288bfafce2d9914f78947ed75fb68e3b0ede4fadb5d7e5ad8 | MATLAB | 1,562 | 53 | function ndx = sub2indv(siz,v,varargin)
%SUB2INDV Linear index from multiple subscripts.
% SUB2INDV is used to determine the equivalent single index
% corresponding to a given set of subscript values.
%
% IND = SUB2IND(SIZ,V) returns the linear index
% equivalent to the N subscripts in the arrays V = [I1,I2,...... |
074e8f00ac0ccfe186a46910d4396d1f4fec7fdbfd61d5bbe8790b58e1b3ada3 | MATLAB | 1,563 | 57 | %% Bayesian inference of the mean of a 2D Gaussian with fixed Sigma
%
%% Sample Data
% This file is from pmtk3.googlecode.com
setSeed(0);
muTrue = [0.5 0.5]';
Ctrue = 0.1*[2 1; 1 1];
mtrue.mu = muTrue;
mtrue.Sigma = Ctrue;
xyrange = [-1 1 -1 1];
ns = [10];
X = gaussSample(mtrue, ns(end));
... |
0f9de5bcb5a267a260086eaef7254af46b081005a85dee40e3b97b239b4547a8 | MATLAB | 1,563 | 42 | % PercentvarPerVariable
% Sarah West
% 8/4/22
% Calculates the percent variance of brain data (explanatory or "X" data)
% explained by each behavior variable (response or "Y" data) in a PLSR
% regression. Is run with RunAnalysis.
% Inputs:
% parameters.XL -- the loadings of each component/latent variable for the ex... |
3861a5e02a4bd82184a7c9d4f7d580f819dda257510a4cd3b6b1dee9f4bccb36 | MATLAB | 1,564 | 48 | function [impreds, stagauss] = predictGaussModel(mdlparams, imEnsemble, nrx, nry)
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
[ypix, xpix, Nims] = size(imEnsemble);
imenuse = reshape(imEnsemble(nry, nrx, :), [numel(nry)*numel(nrx), Nims]);
rfparams = [mdlparams.gaussparams 1];... |
df153068df1d4f940d4259af0f3db40b6a7140c9c48ed96074171a59edefd9ae | MATLAB | 1,564 | 47 | function [newCond, newCondinds] = ConditionIndexes(unique_cond,reginds)
% function [newCond, newCondinds] = ConditionIndexes(unique_cond,reginds)
% a function to return the conditions and the global conditions indices by
% a specified set of variable indices
% INPUT:
% unique_cond - C x P array listing all C possible... |
362030c8609668077dec7d30746f926d1047034b547206883f9b585c8190fce0 | MATLAB | 1,566 | 37 | function [BOUT_ENDS_AND_BEGINNINGS_indices,BOUT_ENDS_AND_BEGINNINGS]=GET_FEEDING_BURSTS(Onsets,...
diff_Onsets__or___IFI,Criterion_for_defining_regular_feeding,MINIMAL_NUMBER_OF_TOUCHES_IN_THE_BURSTS,Plot_raster_for_check_or_not)
%Onsets=ons1{ThisFly,Condition};
%IFI=IFIs1{ThisFly,Condition};
VARIABLE_TO_US... |
6afef7e50826487863ec5ac64ed8c1892348ff49e51dccef608bff62d56c6be8 | MATLAB | 1,566 | 66 | close all;
clear all;
clc;
F = csvread('filename.csv');
N=831; %number of cells
t=306; %number of frames in the moviedFoF_new=zeros(t,N);
dFoF=zeros(t,N);
x=linspace(2,t,t-1);
%To find fitting curve
figure(1);
plot(F);
t=1:t;
for i=1:N
fitting=fit(t.',F(:,i),'exp2');
F_corrected(:,i)=(F(:,i)-fit... |
014fddae01e488a3534b9313561fe82e84b14170c5d8ed4bcad2de1501a585bb | MATLAB | 1,567 | 54 | %% Example of parameter updating in a Beta-Binomial model
%
%%
% This file is from pmtk3.googlecode.com
data(1).a = 2; data(2).a = 2;
data(1).b = 2; data(2).b = 2;
data(1).N1 = 4; data(2).N1 = 40;
data(1).N0 = 1; data(2).N0 = 10;
data(3).a = 1; data(4).a = 1;
data(3).b = 1; data(4).b =... |
6ef9cf26d14acd63e40e9db8737dcd5edbf61ebc306eb124689835860ffdc612 | MATLAB | 1,567 | 63 | %% Bernoulli mixture model for mnist digits
%
%% Setup data
% This file is from pmtk3.googlecode.com
setSeed(0);
binary = true;
keepSparse = false;
Ntest = 1000;
Ntrain = 1000;
% Kvalues = [2, 10];
Kvalues = 2:15;
Kvalues = [20];
[Xtrain, ytrain, Xtest, ytest] = setupMnist('binary', binary, 'ntrain'... |
7a66fde5ec2bc48c1a1c92cf4697950d6e341a084e940dc858204b5ee22e80c9 | MATLAB | 1,567 | 51 | function [G,r] = calc_prob_gradient_with_positions(sites,L,invert_y,normalize,sites_jackknife,show_jk_avg,calc_significant_path_args)
if (nargin < 3) || isempty(invert_y)
invert_y = false;
end
if (nargin < 4) || isempty(normalize)
normalize = false;
end
if (nargin < 5) || isempty(sit... |
8de8b5a3c62940091f3f5dbf6c3f99fd2d4a1e737c0493dc74d1f493c5028e46 | MATLAB | 1,567 | 49 | function D = build_KLdiv(datadir, hmmdir, kerneldir, HMM_name, only_1st)
% D = build_KLdiv(datadir, hmmdir, kerneldir, HMM_name, only_1st)
%
% build symmetrised KL divergence matrix based on time-varying model (HMM)
% This requires that the group-level HMM has been fitted to the
% timecourses.
% The divergence matrix w... |
961ad6ca71ed80c45b32442138d829636f6ae5413aa3737d27750bebae4f27ae | MATLAB | 1,567 | 48 | function y = modefilt1( x, s )
% One-dimensional mode filtering.
%
% Applies a width s one-dimensional mode filter to vector x. That is each
% element of the output y(j) corresponds to the mode of x(j-r:j+r), where
% r~s/2. At boundary regions, y is calculated on smaller windows, for
% example y(1) is calculated over x... |
5945ee58a02dc96bca845027f16fa066b265f16e4160bf3a560a48211f7279a2 | MATLAB | 1,568 | 58 | function [indices minBoundBox numNonZero] = findZeros(mat);
%
%-----------------------------------------
% [indices minBoundBox numNonZero] = findZeros(mat)
%
% finds a square that is a power of 2 in size
% and includes the non-zero portions of
% the input matrix
%
% mat: input matrix
%
% indices: indices into the squ... |
92be97b8eaa4070ad37391b1a2e4d20b309a782d285e8000346d59e31ae21a4d | MATLAB | 1,568 | 47 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% topological_kmeans_init.m %%%
%%% Author: GN Ponasso (2024) %%%
%%% Calculate a well-spaced initial set of cluster centers for k-means %%%
%%%%%%%%%%%%%%%%... |
1911f3d38f0ba052186e25143d7b425cf903da25f5b89ad4759c8d20dd3d01d1 | MATLAB | 1,569 | 50 | Contents:
Main
-----------------------------------------
metamerTest.m - test script showing basic functionality
metamerOpts.m - create structure with options
metamerAnalysis.m - compute model parameters on an image
metamerSynthesis.m - synthesize a new image
Analysis
-----------------------------------------
wmean2.... |
6f653003cc7195f7fd519c6481b78089476bf2d950eec16fc2a344cb68e25cb2 | MATLAB | 1,569 | 23 | function StateSwitch_addSurroundingCues_visual(expInfo, screenInfo, indRun, indBlock, indTrial)
% adds the surrounding cues for the next flip
for indAtt = 1:4
CueImg = ['img_vis',filesep, expInfo.attNames{indAtt},'Q.png'];
[cueLoad,~,~] = imread(CueImg);
cue2Disp = Screen('MakeTexture',scree... |
510771a75fc906850bf4c34d8588e5e0a269edea42bceaaa9f62252af701dce8 | MATLAB | 1,570 | 50 | % Author: Birgit Nierula (Feb, 2020)
% nierula@cbs.mpg.de
%% SRMR1: Manual R-peak detection
% --> to use after automatic detection steps (SRMR1_01_prepro_1_automatic_Rpeakdetection.m)
% Adapted from Ulrike
% Usage of manual r-peak selection tool:
% Input: some eeglab data (set file) with peaks as additional events
% ... |
52869fbda62c933949218ec1e12465771937daa3a619cd960682068dfb97c5fd | MATLAB | 1,570 | 51 | function varargout = angle_between_vectors(v1,v2,in_deg,return_only_cos_theta)
% v1 is a row vector or a collection of 1 vector per row
% v2 is a row vector or a collection of 1 vector per row
% return
% theta: angle between v1 and v2 (or each row of v1 and the corresponding row of v2)
% CCW angles relative to v... |
2704bff0b71066a7271c08205b97dbbbb5bdd4c738426fa294d052c4e852d344 | MATLAB | 1,571 | 50 | function [pnt, tri] = ksphere(N)
% KSPHERE returns a triangulated sphere with K vertices that are
% approximately evenly distributed over the sphere.
%
% Use as
% [pnt, tri] = ksphere(K);
%
% This implements the recommended algorithm in spherical coordinates
% (theta, phi) according to "Distributing many points on ... |
470e89348a2f79086823e5bd1054e97cef80ca894da34d2b63de28e040f5412d | MATLAB | 1,571 | 50 | function [hist12, hist1, hist2]=mutual_histogram_double(I1,I2,Imin,Imax,nbins)
% This function makes a 2D joint histogram of 1D,2D...ND images
% and also calculates the seperate histograms of both images.
%
% Note! : For a value of 4.3, the histogram function will put 0.7 in bin 4
% and 0.3 in bin 5. This makes t... |
02520150f45524b30f4383fbf0b8b41cb15dec5c056da6a30c938d5685b5103f | MATLAB | 1,572 | 59 | %% Relative MSE plot
%PMTKneedsStatsToolbox ksdensity
%%
% This file is from pmtk3.googlecode.com
requireStatsToolbox
n = 1:50;
k0 = 0:3;
sigmaTrue = 13;
mu0 = 100;
thetaTrue = 112;
theta0 = 100;
mseThetaE = zeros(length(n), length(k0));
mseThetaB = zeros(length(n), length(k0));
for k=k0
w = (n./(n + k));
mseThet... |
54d115222546a62b0c2c8f9834beed4b81326c7e1310070fcc0dff739821fbea | MATLAB | 1,572 | 78 | function V = downsample(U)
% Try the 5x5 filter for building the pyramid:
% Now works with color images!
U = double(U);
[r,c,k] = size(U);
p = floor((r+1)/2); % row
q = floor((c+1)/2); % col
U2 = zeros(r+2,c+2,k);
for i=1:k
U2(:,:,i) = [U(:,:,i) U(:,end,i)*ones(1,2); ones(2,1)*U(end,:,i) U(end,end,i)*ones(2,2)... |
613a6e90d27ba62e3d526ba5fc2d1015d911e19958a30cdd4d8e8a9603af2b57 | MATLAB | 1,572 | 45 | %{
Copyright (c) 2025 Axion BioSystems, Inc.
Contact: support@axion-biosystems.com
All Rights Reserved
%}
classdef EventTag < Tag
%EVENTTAG Base class for tagged events in the file.Indicates
%time stamps for particular events
properties(SetAccess = private)
% SamplingFrequency: Sampling... |
6adee034d841811390d2e7f05f3fbbba32bac88dceef9759299056e9bfac89a0 | MATLAB | 1,572 | 1 | % TSLOADRAW Load a MEDPC file onto the Experiment structure
% TSLOADRAW(FILENAME) loads in the data from FILENAME into TSData. This
% function is the one to use in the fully automated regime, where the
% data are grabbed from the Backup folder in MedPC-IV rather than from
% the Data folder
function [ SUCCESS... |
906c740ae1cc3578cd47fc11c6d56c163f3d56171e5fdc0fb16207b6267f365b | MATLAB | 1,572 | 50 | function [feven,fodd] = filterGabor1d( r, sig, omega, show )
% Creates an even/odd pair of 1D Gabor filters.
%
% USAGE
% [feven,fodd] = filterGabor1d( r, sig, omega, [show] )
%
% INPUTS
% r - final filter will be 2r+1 (good choice for r is r=2*sig)
% sig - standard deviation of Gaussian mask
% omega - f... |
ac116915d391f40f56dfbbd8a081fe16d2e05edd92bfc481d32dcd0665f5120a | MATLAB | 1,572 | 48 | % Example of 3D affine registration using the fminunc optimizer.
% clean
clear all; close all; clc;
% Add all function paths
addpaths
% Get the volume data
[I1,I2]=get_example_data;
% Convert all volumes from single to double
I1=double(I1); I2=double(I2);
% First resize volume I1 to match size of vol... |
af174b3b3089f30a9246326678672cd06d57c2593f039adbb71d370096905bbd | MATLAB | 1,572 | 29 | function [ScaleBarLine,ScaleBarLabel]=Auto_ScaleBar_wText(ImageHeight,ImageWidth,PixelSize,ScaleBar_Size,ScaleBar_Unit,ScaleBar_FontSize,ScaleBar_Location,ScaleBar_LineWitdh,ScaleBar_LineColor,BufferRatio_X,BufferRatio_Y)
ScaleBar_Length=ScaleBar_Size/PixelSize;
if strcmp(ScaleBar_Location,'BL')
ScaleBa... |
85d1c2e5b045b7143b131dc2935a2ced194e6f7a26bede7b4e04d15b2d8b48a4 | MATLAB | 1,573 | 50 | function cspec = lan_cspec_load(LAN,chan,trial)
% IMPORTANT
% this script's purpose is to provide a single smoothed and normalized
% spectrogram, regardless of the output format (LAN.freq.powspctrm)
%
% chan : a SINGLE channel indicator
% trial : a SINGLE trial indicator
% cspec : smoothed and normalized SINGLE spectro... |
ac470e6832659b28553220d907344c213e6df4f875eec1191b9edce74748e3a3 | MATLAB | 1,573 | 53 | function compute_dwpli(params,bidsID,freqBand)
% Load EEG data and check that there are more than 10 epochs
data = load_preprocessed_data(params,bidsID);
assert(size(data.trial,2)>=10, 'Recording with less than 10 epochs');
% Band-pass filter the data in the relevant frequency band
cfg = [];
cfg.bpfilter = 'yes';
cfg.... |
2a8b62879fd6b10e644ff3f19ea828b24b575654ab753784fccdb0a5f5243327 | MATLAB | 1,574 | 81 | clear all;
%% Manually specify ROI names in 0_raw folder
ROInames = {
% 'S1ROI1';
% 'S1ROI2';
% 'S1ROI3';
% 'S1ROI4';
% % 'S1ROI5';
%
% 'S2ROI1';
% 'S2ROI2';
% 'S2ROI3';
% 'S2ROI4';
%
% 'S3ROI1';
% 'S3ROI2';
% 'S3ROI3';
% 'S3ROI4';
% %
% 'S4ROI1... |
74da588dfa4a22e3da11d3f5d86e78cef3b1135aebca606cd9308faed461c89f | MATLAB | 1,574 | 37 | function ROIoverlaps
% This script will combine all the individual ROIs, and using mricron to
% show color-code clusters depending on the amount of overlaps. written by
% Jin Wang 5/3/2019
addpath(genpath('/dors/gpc/JamesBooth/JBooth-Lab/BDL/LabTools/nifti')); % addpath the nifti function tools, for this script it is ... |
8f4a3858d2999b083b4e41e680142e505a6bbb26323abf7ec1c394f0ec9781d4 | MATLAB | 1,574 | 67 | function [table, M] = parsePMLtypoFile(fname)
% Parse the PML typos file and generate an html table
% listing the unique e-mail addresses and the number of each type of error
% found.
%
% **** Download the file as a csv ****
%
%% Example
% parsePMLtypoFile('C:\users\matt\Desktop\typos.csv');
% This file is from pmtk... |
de74d171938b95ea09707ca8338bc705886e2b37f9dd267b89617d5e2b196971 | MATLAB | 1,574 | 47 | function h = mysigstar_absolutepval(ax, xpos, ypos, pval, color, whichWay)
% replaces sigstar, which doesnt work anymore in matlab 2014b
if ~exist('ax', 'var'); ax = gca; end
if ~exist('color', 'var'); color = [ 0 0 0 ]; end
if ~exist('whichWay', 'var'), whichWay = 'down'; end
if numel(ypos) > 1,
assert(ypos(1) =... |
09ebeabf81f9d1023c193593840ea6aeed8ac1645be81934311d5e780dc45151 | MATLAB | 1,575 | 65 | % Same as logregMultinomKernelDemo, except uses KNN
% This produces plots of the decision boundaries in 2d.
% It uses the same data as knnClassifyDemo, but the plots look nicer.
% This file is from pmtk3.googlecode.com
function knnClassifyDemo2()
%% Setup Data
loadData('knnClassify3c'); % 500 samples from 2 classes
... |
5622184cd19612aa700689d2f977abeb2d769de26de6b5cc49303437797972c6 | MATLAB | 1,575 | 46 | % $$C\frac{dV}{dt}=-g_L(V-V_L)+g_L\Delta_T\exp\left(\frac{V-V_T}{\Delta_T}\right)+I$$
% Input defined at Line 30
clear; %clear all variables
% close all; %close all open figures
%DEFINE PARAMETERS
dt = 1/1000; %time step [ms]
t_end = 1200; %total time of run [ms]
t_StimStart = 100; %time to start injecting current [ms... |
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