sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
90846367a29dcc6b67cd3fe965ca76f118f38504b409738e8bc00bb7d58917d8 | MATLAB | 28,497 | 508 | %_______________________________________________________________________
%
% Configuration for running StateSwitch experiment
%_______________________________________________________________________
%
% Output
%
% expInfo | configuration for state switch word version (struct)
% Written by Julian Kosciessa (kosciessa@m... |
3f72cc9f328b690e172af09857c01d93a5228efe5983300f8a79676355762d0d | MATLAB | 28,637 | 797 | function ft_write_data(filename, dat, varargin)
% FT_WRITE_DATA exports electrophysiological data such as EEG to a file.
%
% Use as
% ft_write_data(filename, dat, ...)
%
% The specified filename can contain the filename extension. If it has no filename
% extension not, it will be added automatically.
%
% Additional ... |
136550a5dc167cfb10f0c52978987764bbdd1e9eb4080a1ff69d4485dfa7f549 | MATLAB | 28,738 | 690 | function [ avw, machine ] = avw_img_read(fileprefix,IMGorient,machine,verbose)
% avw_img_read - read Analyze format data image (*.img)
%
% [ avw, machine ] = avw_img_read(fileprefix,[orient],[machine],[verbose])
%
% fileprefix - a string, the filename without the .img extension
%
% orient - read a specified orientatio... |
a75628e923bffee8b09d87cc72053b4ba84339029bfa445533ee60b7f64295a2 | MATLAB | 28,844 | 470 | %% muscle GCaMP 1P imaging for seeing inhibition of high pre-stim activity as in Extended Data Fig. 8b-c
% This works with folder arrangement as in glue muscle imaging
subFolders = dir(pwd);
realSubFolders = subFolders([subFolders.isdir]');
realSubFolders = realSubFolders(3:end);
% remove unwanted folders like... |
0ce491d09dfd47bd5c5ae5ed06bbee7f6947873ff385afa3392e8d5d95519a99 | MATLAB | 28,874 | 968 | function mwizard(file)
%MWIZARD - M2HTML Graphical User Interface
% MWIZARD launches a Matlab GUI front-end to edit parameters
% that are then used by M2HTML to generate HTML documentation.
% MWIZARD(FILE) allows to specify a mat-file FILE from which
% default parameters are extracted and can be updated.
%
% For... |
ca7b3446f602f78b811d477e6db4dee10231be9b210aa2606048a37a3e31f957 | MATLAB | 28,906 | 1,039 | %% input args
DATASET = 'sh';
switch DATASET
case 'bub'
ppbasefile = 'ppbase.mat';
outdir = 'mftsbub_out_20181101T090301';
ppbase = load(ppbasefile);
lblfile = ppbase.lblfile;
ld = load(lblfile,'-mat');
hmdirs = ppbase.lblfilehmdirs;
case 'sh'
outdirs = {
'out_1_90_20181108T083... |
4001f931960a1236830ee5f66a57a04a2ff4d6f374da3cce890b7c81d794881e | MATLAB | 28,911 | 655 | function [EEG] = PAA(EEG,ChOI,badData,allSleepStages,badSleepstages,lightsTags)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% This function performs Period Amplitude Analysis (PAA) on EEGlab data to
% detect and measure slow waves. The events are marked on the EEG, saved
% as a new da... |
f861c2417a4473fcfc7bf7d240a87be475c4e5658fdabff1de25c2f9e772795b | MATLAB | 28,942 | 513 | %_______________________________________________________________________
%
% Configuration for running StateSwitch experiment
%_______________________________________________________________________
%
% Output
%
% expInfo | configuration for state switch word version (struct)
% Written by Julian Kosciessa (kosciessa@m... |
c64727145cf1682ed50404369f8ec8f7bff21a08d44a65f99ba2dbc6fd357708 | MATLAB | 29,012 | 542 | %To Do
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
49641589b30182ed3549ad39db98e00401155ea2c4ef4762bebdb48c1d01367b | MATLAB | 29,020 | 810 | %EXPORT_FIG Exports figures suitable for publication
%
% Examples:
% im = export_fig
% [im alpha] = export_fig
% export_fig filename
% export_fig filename -format1 -format2
% export_fig ... -nocrop
% export_fig ... -transparent
% export_fig ... -native
% export_fig ... -m<val>
% export_fig ... -r<val... |
a267cbec080e24359ebdb1857b699e9a7c716da411e096ff2a3cf90946290862 | MATLAB | 29,028 | 623 | function boney = tbx_cfg_boney
% Configuration file for boney toolbox batches.
% _________________________________________________________________________
% ###### Please write more about this ...
% _________________________________________________________________________
% Robert Dahnke 2023
%
%#ok<*AGROW,*INUSD>
g... |
8cae71a5a93b59b3665c5235db58a3a246879f34c50d91c6add451bcb093a84a | MATLAB | 29,098 | 859 | function [group,fittedP,stats] = meg_plotPhaseHistogram(mdlFit,paramNames,figDir,mdlFitType)
% function meg_plotPhaseHistogram(mdlFit,figDir,mdlFitType)
% mdlFitType can be 'separate' 'yoked_fixedFreq' 'yoked'
%% Setup
plotFigs = 1;
saveFigs = 1;
edges = 0:pi/24:2*pi; % 24 bins, try 12 bins -pi to pi? to match the bo... |
e2f65ce61afe16b7808be1a0e5cabc948309bd38e99a21ce532390b1c37cd139 | MATLAB | 29,111 | 601 | % This function takes a subregional spike and port structure and first
% creates a GLM predictor variable matrix containing the levels of the
% Sample Identity, Choice Identity, and Outcome Identity predictor
% variables for each neuron based on the session that neuron came from.
% It also creates a 200ms time bin ... |
65af41fbd03eecfc2586962da9f217db678a5e1fbe2ba3b1123b788fef166131 | MATLAB | 29,171 | 906 | function MakeQTMovie(cmd,arg, arg2)
% function MakeQTMovie(cmd, arg, arg2)
% Create a QuickTime movie from a bunch of figures (and an optional sound).
%
% Syntax: MakeQTMovie cmd [arg]
% The following commands are supported:
% addfigure - Add snapshot of current figure to movie
% addaxes - Add snapshot of curre... |
97c23947b8b356f6881eb38f2f3193babb7813ce726ffca084f47604c3e45e14 | MATLAB | 29,253 | 767 | % AUTHORSHIP
% Primary Developer: Stephen Meehan <swmeehan@stanford.edu>
% Math Lead & Secondary Developer: Connor Meehan <connor.gw.meehan@gmail.com>
% Bioinformatics Lead: Wayne Moore <wmoore@stanford.edu>
% Provided by the Herzenberg Lab at Stanford University
% License: BSD 3 clause
%
classdef WebDo... |
5e5af281b33e41caa6e95cfdd667cb64f25fc1872754808ee037bc3a5e7509f2 | MATLAB | 29,263 | 839 | function [cfg] = ft_checkconfig(cfg, varargin)
% FT_CHECKCONFIG checks the input cfg of the main FieldTrip functions
% in three steps.
%
% 1: It checks whether the cfg contains all the required options, it gives
% a warning when renamed or deprecated options are used, and it makes sure
% no forbidden options are used.... |
0d97b819f03110194df7796d44a73be495ce6e419f039a085209b7b86d658d05 | MATLAB | 29,307 | 637 | function [S] = Paradigm_MRI(S)
% Usage: [S] = Paradigm_MRI(S)
%
% Inputs:
% : S - struct containing very important info (screen, subject, colors,
% textures, trigger, response box, eyetracker, etc)
%
% Outputs:
% : S - struct containing time of start, end and trigger of the
% stimulation, key presses... |
d9ab34a611c71f7f4db0faa13dc12f7440aedfa79ca165b1877658729f7a2e37 | MATLAB | 29,333 | 727 | classdef meshWrapper < surfaceFitting.surfaceFitter
% Generate a SurfaceOfInterest object with atlas containing conformal
% charts from an externally produced triangular mesh representation of
% a surface.
%---------------------------------------------------------------------
% license
... |
613d86dd891d8d48b458810aa0307f3a5625c7ac19b07571cc6d9a294b95479c | MATLAB | 29,370 | 747 | function [interp] = ft_sourceinterpolate(cfg, functional, anatomical)
% FT_SOURCEINTERPOLATE interpolates source activity or statistical maps onto the
% voxels or vertices of an anatomical description of the brain. Both the functional
% and the anatomical data can either describe a volumetric 3D regular grid, a
% tri... |
3f859c087dba452e222b4cf8aff3955765bda19c2d77db0eb4d8f2f2c13a933e | MATLAB | 29,404 | 690 | function varargout = DPABINet_GTA(varargin)
% DPABINET_CONSTRUCTION MATLAB code for DPABINet_GTA.fig
% DPABINET_CONSTRUCTION, by itself, creates a new DPABINET_CONSTRUCTION or raises the existing
% singleton*.
%
% H = DPABINET_CONSTRUCTION returns the handle to a new DPABINET_CONSTRUCTION or the handle t... |
5a9456387fbbae2b2c5a1d75f4b35744ff62df2607291c763866cc70a2c9e6c4 | MATLAB | 29,405 | 578 | function [log_odd] = log_odd_bayesian_analysis(folders,timebin,posbin)
% Input:
% Folders: Each Folder is data for a session
% Timebin: 0.02 or 1
% 0.02 -> 20ms time bin
% 1 -> 1 event time bin
% posbin: [] or 1
% [] -> 20 position bin per track (will load extracted_place_field_BAYESIAN)
% 1 -> 1 position bin per track... |
ccdf743c31070d530c2da65cc95227cc4e02613ed0d73d22ded51c1930556c08 | MATLAB | 29,405 | 963 | function ConvertSpykingCircus2Neurosuite(basepath,basename)
% Converts hdf5 files from SpykingCircus into klusters-compatible
% fet,res,clu,spk files. Works on all shanks of a recording. Assumes a
% 16bit .dat and an .xml file is present in "basepath" (home folder) and
% that they are named basename.dat and basename... |
1ceca47593e2f093e86e9dc85273583b825633d58f603b562e7fe22861e0ce07 | MATLAB | 29,445 | 526 | %_______________________________________________________________________
%
% Configuration for running dotsExperiment
% Note that this is the configuration script for a single attribute during
% the training/psychophysics phase of the experiment.
% JQK July 2017 (kosciessa@mpib-berlin.mpg.de)
%_________________________... |
f4a9ad51b349a9373f3639e51e55d92d5422ddf463ae92a35a0c5004054121e4 | MATLAB | 29,468 | 803 | %EXPORT_FIG Exports figures suitable for publication
%
% Examples:
% im = export_fig
% [im alpha] = export_fig
% export_fig filename
% export_fig filename -format1 -format2
% export_fig ... -nocrop
% export_fig ... -transparent
% export_fig ... -native
% export_fig ... -m<val>
% export_fig... |
7963dbbc0701f55d34f6e112f4d5f82f09f3efe58d6e9525965591fd71ed1883 | MATLAB | 29,519 | 838 | function avw_img_write(avw, fileprefix, IMGorient, machine, verbose)
% avw_img_write - write Analyze image files (*.img)
%
% avw_img_write(avw,fileprefix,[IMGorient],[machine],[verbose])
%
% avw.img - a 3D matrix of image data (double precision).
% avw.hdr - a struct with image data parameters. If
% ... |
a647d7f299018eb55b1539c9f67efa858c9f00a27a4402adb58771db37150b09 | MATLAB | 29,523 | 1,092 | clear srcinfo
ns = 4000;
srcinfo.sources = rand(3,ns);
srcinfo.charges = rand(1,ns);
nt = 3999;
targ = rand(3,nt);
eps = 1e-5;
ntests = 54;
ipass = zeros(ntests,1);
errs = zeros(ntests,1);
ntest = 10;
stmp = srcinfo.sources(:,1:ntest);
ttmp = targ(:,1:ntest);
itest = 1;
% Test sources to sources, charge, pot
pg ... |
5a0e6be865c1eab16519dddb7ddb33c54d669b3c20f67c08568a2f5f87da42ae | MATLAB | 29,537 | 696 | function [status] = ft_hastoolbox(toolbox, autoadd, silent)
% FT_HASTOOLBOX tests whether an external toolbox is installed. Optionally
% it will try to determine the path to the toolbox and install it
% automatically.
%
% Use as
% [status] = ft_hastoolbox(toolbox, autoadd, silent)
%
% autoadd = 0 means that it will ... |
9b067dceed8e106a0fa9e0f41b2dfa67a9fbc226fdf819548329f90ca9b322a3 | MATLAB | 29,574 | 679 | function [accuracy,accuracy2,responseData_group] = group_analysis (subjects,runs,dates, plotLevel)
rootDir = pathToExpt;
nSubj = length(subjects);
responseData_group = [];
if ~exist('dates','var')
date = [];
end
if ~exist('plotLevel','var')
plotLevel = 3; % 1 plot everything --> 3 plot minimal
end
for n = 1... |
7639ae866df1341071f8b72fc5ce9b15ab523d52fa62c636fa65f3e7b20ad339 | MATLAB | 29,576 | 522 | %_______________________________________________________________________
%
% Configuration for running StateSwitch experiment
%_______________________________________________________________________
%
% Output
%
% expInfo | configuration for state switch word version (struct)
% Written by Julian Kosciessa (kosciessa@m... |
b613cc5c236ddb8d9939800f775daead11f417f58ab6fca911ec391c87c08c0c | MATLAB | 29,638 | 844 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% analyze and calibrate random weight and random input dataset (through lay1)
load('random_lay01_preprocessed.mat');
nitall = 100000;
pd_sz = [5 10];
led_sz = [8 8];
nmask = 10;
nsamp = 20;
target_neg3 = target_neg2-reshape(zeroim_o... |
18879842a619cc88690af883eca0d7c6c0a27e83caebae2780b318a255da817b | MATLAB | 29,639 | 699 | function [cfg] = ft_multiplotTFR(cfg, data)
% FT_MULTIPLOTTFR plots the time-frequency representations of power or coherence
% in a topographical layout. The plots of the indivual sensors are arranged
% according to their location specified in the layout.
%
% Use as
% ft_multiplotTFR(cfg, data)
%
% The data can be a... |
72ee6efaf03e73ae261c22e91831408df02eee74d677b38fdba0a22fff362aba | MATLAB | 29,679 | 551 | function dualColour_Module()
% Use data and listbox as global variables (access from anywhere).
global data listbox
% Make a new figure, and set its properties.
figure();
set(gcf,'name','Colocalization Module','NumberTitle','off','color','k','units','normalized','position',[0.25 0.2 0.5 0.6],'menubar','none','... |
3dffc8b87f820d50bb19486a5e7ab7d8b00d597663416144d357bf684f07d836 | MATLAB | 29,717 | 767 | function AnalyzeFaceScratchMotor()
Convert();
% Possible args: {'SUA','Pop','ERA','Decode'};
AllAction();
end
function Convert()
%% Body spec
fn ={};
tl = {};
% filename = {...
% '20150318-120247-120401-TextTraining',...
% '20150318-120247-121134-TextTraining',...
% '20150427-103200-1033... |
1804f27b6f7597c04f8c018a172caaa10fa12a0b4d4579e53be8a98a91aa514d | MATLAB | 29,761 | 629 | % Example 1
% Script #1
%
% Script_01_IMAP_Beta_v2_2c.m
%
% This script does the following (*):
%
% - Applies the function RA_equaltrials_Beta_GH001.m to your
% previously epoched datasets.
% - Creates both individual (equated)averaged ERPs and the grand averaged ERP.
% - Exports counting stats per both con... |
0a9fd228641d815f92ccd81794e175e1b415ce334716673cbf264e177e2d5e88 | MATLAB | 29,813 | 576 | function Behavior = LickTaskBehavior(seizurePaths, seizureCell, params, varargin)
% this function extracts all the behavioral infromation used later for
% analysis. The notation [n] refers to the length n of arrays when
% applicable.
% INPUTS:
% - seizurePaths [nSeizures]: a string array with the full paths to the
% ... |
3fba21961f036f78c280f4bec865146e3131b8ba6396751916a0ba7505b65b99 | MATLAB | 29,853 | 838 | function avw_img_write(avw, fileprefix, IMGorient, machine, verbose)
% avw_img_write - write Analyze image files (*.img)
%
% avw_img_write(avw,fileprefix,[IMGorient],[machine],[verbose])
%
% avw.img - a 3D matrix of image data (double precision).
% avw.hdr - a struct with image data parameters. If
% ... |
4ee49fd09274688124cbbcec8b8f99c86bcc521f3bd5bac45c04b8d042c0abfe | MATLAB | 29,884 | 881 | function jbm_synapsescoringengine(tag,handles)
global jbm;
global h_img3;
global synScore;
jbm.scoringData.versionInfo.version = '2.0';
jbm.scoringData.versionInfo.conventions = ['\n\n0 = absent \n1 = shaft (blue) \n2 = spine (purple) \n3 = unsure (cyan) \n4 = spine no psd (yellow) \n\n']... |
cb3d3c96ab1e9742f344147a5de7404a55ef6fff3fdf6f5f280ec14af0e40381 | MATLAB | 29,891 | 653 | function model = simulateHeatDistribution(model)
% Simulates temperature evolution due to absorption of light and
% diffusion of heat through the cuboid based on output of runMonteCarlo.m.
% Also calculates Arrhenius-based thermal damage.
%
% checking on macOS whether the mex-file is quarantined and cl... |
4a9e17bdb6c57f4b4b3988f45caff70ce074169e20adca8eb97edb2cc47c61e6 | MATLAB | 29,905 | 873 |
%% data locations
%
% DATASET = 3;
%
% switch DATASET,
%
% case 1,
% experiment_name = '7_7_13_47D05AD_81B12DBD_x_Chrimsonattp18__fly_0019_trial_002';
%
% frontviewmatfile = fullfile('/groups/branson/bransonlab/projects/flyHeadTracking/CNNTrackingResults20160409',sprintf('%s.mat',experiment_name));
% ... |
2ef44db7588441053ae5a1f31b0756b3e90fbd1945385d80ed3dc5ff483dd9ed | MATLAB | 29,976 | 401 | % ---------------------------------------------------------------------------- %
% RELAX-Jr EEG CLEANING PIPELINE, Copyright (C) (2024) Aron Hill & Neil Bailey
% ---------------------------------------------------------------------------- %
% This program is free software: you can redistribute it and/or modify it
... |
7540978240184ca5fe61d3c1b84ab393b42262b9ced9ad6f412d1790fd471e54 | MATLAB | 29,980 | 630 | function [selectedVars,Wlsq,varargout] = bolasso(X,y,varargin)
% Use the Bolasso (bootstrap-enhanced least absolute shrinkage operator) to
% perform model selection, i.e. to select relevant variables. Once
% selected, fit a model using unregularized least squares regression
% using only the selected variables.
%
% Th... |
fca3fbbbd22d16ebbae4c2465d45cb281fabdf49dd58659e8415089a05e0bf5a | MATLAB | 30,015 | 666 | function plot_ground_truth_compare_test(folders,option,method)
total_number(1:3) = 0;
for nfolder = 1:length(folders)
cd(folders{nfolder})
load decoded_replay_events
[~,time_range]=sort_replay_events([],'wcorr');
for event = 1:length(decoded_replay_events(1).replay_events)
event_time = deco... |
2022ce112e81c731876f0852251711e89d31806b3f7f21514ae3434e290445cf | MATLAB | 30,037 | 506 | function R = weightedcorrs(Y, w)
%
% WEIGHTEDCORRS returns a symmetric matrix R of weighted correlation
% coefficients calculated from an input T-by-N matrix Y whose rows are
% observations and whose columns are variables and an input T-by-1 vector
% w of weights for the observations. This function may be ... |
2b54cdd71e46c4240c622f2aee19e4d09727f40849beb4de24ac2873dbf2a968 | MATLAB | 30,122 | 743 | function chantype = ft_chantype(input, desired)
% FT_CHANTYPE determines for each individual channel what chantype of data it
% represents, e.g. a planar gradiometer, axial gradiometer, magnetometer,
% trigger channel, etc. If you want to know what the acquisition system is
% (e.g. ctf151 or neuromag306), you should n... |
b5f362dff1c8ca0a0bababb561a58ec93831a5b7c7bfe8616eac99d569a3194b | MATLAB | 30,161 | 1,116 |
%% load aligment directories
cd ..\
load('anatomicalDistance_2.mat');
cd('NNNearNeighbor_uni_uniqueCells')
%% CELL ANATOMY - AO1 vs VS1
folders = folders_audio_vs_visual;
%
% distancesInfos = nan( length(folders), 3 ); % AO1 vs VS1
% AOtoAO
% AOtoVS
% VStoAO
% VStoVS
% allROIs = cell( leng... |
843b15397a5b383469652adbbcbf489fb75616907caf459a2fdc84e757262cf1 | MATLAB | 30,175 | 661 | function [FitDetails]=Multi_3D_Fitting(TempXData,TempYData,TempZData,XLabel,YLabel,ZLabel,Title,FigSaveDir,ScratchDir,...
Azimuth,Elevation,Save3DFitFigs,FigurePosition_3D,AxesPosition_3D,AxesStandardFontSizes,SilentColor,UpperLimitBuffer,AdjustRatio,MovieFits,SubPlotSize,FigurePosition_AllFits,SurfaceFitAlpha)
... |
58b4effe408644adc6b3cb52d359404d2cd760d761cc94870b9055390d381c24 | MATLAB | 30,294 | 718 | function behaviorAnnotator( fName, aName, tName )
% Caltech Behavior Annotator.
%
% Can only be used to annotated seq files. To annotate other types of video
% files, they need to be converted to seq files first. For example, to
% convert an avi file into an seq file, use the following command:
% seqIo([seqName],'frIm... |
09c4a73ec55a1327ba1b89affb6386ab10654f8af9ca127e0fe832904228d87d | MATLAB | 30,319 | 666 | function [cfg] = ft_multiplotER(cfg, varargin)
% FT_MULTIPLOTER plots the event-related potentials or event-related fields verus
% time, or the oscillatory activity (power or coherence) versus frequency. Multiple
% datasets can be overlayed. The plots are arranged according to their location
% specified in the layout.... |
8ec0138496123853cfc8126b02d26c030132c1ef2a519d74e7658eb265740ac3 | MATLAB | 30,377 | 683 | function [] = plot_ground_truth_compare_spearman(folders,option,method)
% spearman_analysis(folders);
total_number(1:3) = 0;
for nfolder = 1:length(folders)
cd(folders{nfolder})
load decoded_replay_events
[~,time_range]=sort_replay_events([],'wcorr');
for event = 1:length(decoded_replay_events(1).r... |
044e7ecfd78c43392a5e7058907c675872682fd1c941b2df033439255232098d | MATLAB | 30,468 | 592 | function [frac_sig_bothtuned,...
dT_bin_labels,...
ratio_conTOdiv,...
ratio_conTOdiv_CI,...
dPOsig_perint_binned,...
dPOall_perint_binned,...
output] = ...
eval_PO_stability(data,varargin)
p = inputParser();
p.KeepUnmatched = false;
p.CaseSensitive = false;
p.StructExpand = fal... |
b3ee4cbff4615822671f35a0610a588bcec440d577f19570a2a22e71ffab35dc | MATLAB | 30,478 | 829 | function TrioEEGAnalyseByTrials(timelock);
% Analyse EEG data that can be split by the result.data trial information.
% This requires that the same number of trials are found in the EEG
% recordings and in the result.data structure, which may not be the case
% due to missing triggers or aborted trials (use TrioEEGAnaly... |
cd727a5d001b56d2f738957957c43d646d80aeb82238700612f061db9c27f006 | MATLAB | 30,483 | 640 | % pipeline_fluorescence_analysis.m
%% Initial Setup
% Put all needed paramters in a structure called "parameters", which you
% can then easily feed into your functions.
clear all;
% Create the experiment name.
parameters.experiment_name='Random Motorized Treadmill';
% Output directory name bases
parameters.dir_b... |
a848763114ed07d0fa0b6d87b4071753fd25cc1956671668aedb0f05d6b21655 | MATLAB | 30,522 | 902 | % NOTE: there is no Fig. 1 ver. 6
% Changes: log-scale plots for B and D
% Waveforms for example cells
% Box-and-arrows diagram for Fig. 1A
% Changes/removal of tagging panel
% Avg rate/CV bars for D (labeled rate-CV plot)
%% Load Unit Data
datRoot = '/Volumes/LaCie/Farries recordings/';
load([datRoot 'unitDat_fina... |
cca0be7f87625043acab74a3c6abff6708af1948e009499f9c6123070a959ba0 | MATLAB | 30,529 | 413 | function significant_replay_events = number_of_significant_replays(p_value_threshold,ripple_zscore_threshold, method, rexposure_option)
% Establish significance for the replay events that are above a set ripple power threshold.
% The output will therefore have less replay events than the structures that have been load... |
428a357d539ae69c6739dbb1c9b45708aa95d3b6295681efa3b6afa16425b234 | MATLAB | 30,543 | 886 | % AUTHORSHIP
% Primary Developer: Stephen Meehan <swmeehan@stanford.edu>
% Math Lead & Secondary Developer: Connor Meehan <connor.gw.meehan@gmail.com>
% Bioinformatics Lead: Wayne Moore <wmoore@stanford.edu>
% Provided by the Herzenberg Lab at Stanford University
% License: BSD 3 clause
%
classdef PopU... |
c67f3fac01f737f1dfe57e6ec524090fb33efe589eb1d84246a9ac5686e655c7 | MATLAB | 30,563 | 652 | %% Supervised learning using non-parametric discriminative models in pmtk3
%
%
%% Kernel functions
%
% One common form of basis function expansion
% is to define a new feature vector $\phi(x)$ by comparing the input
% $x$ to a set of prototypes or examplars $\mu_k$ as follows:
%%
% $$\phi(x) = (K(x,\mu_1), ...... |
49e18ea14b36b97df6ae266edff5b6531ae5584652e23282831e5a0f7157ac8c | MATLAB | 30,595 | 928 |
%% load aligment directories: contact lead author for data
%% CELL ANATOMY - AO1 vs VS1
% folders = folders_audio_vs_visual;
%
% distancesInfos = nan( length(folders), 3 ); % AO1 vs VS1
% AOtoAO
% AOtoVS
% VStoAO
% VStoVS
% allROIs = cell( length(folders), 2 );
if 0
ntry = 100;
for f... |
07c28a94310eb24830b5998af9a97e3d99a1e07552931c4e3c0240177c18c200 | MATLAB | 30,602 | 814 | % AUTHORSHIP
% Primary Developer: Stephen Meehan <swmeehan@stanford.edu>
% Math Lead & Secondary Developer: Connor Meehan <connor.gw.meehan@gmail.com>
% Bioinformatics Lead: Wayne Moore <wmoore@stanford.edu>
% Provided by the Herzenberg Lab at Stanford University
% License: BSD 3 clause
%
classdef Plot... |
4a383a714bbdae0b54d583011e79a61501101121f3c60d720e73ab4b0fe5907f | MATLAB | 30,604 | 1,064 | %%
stl_file = './functions/Intermediate Assembly 231108.stl';
tr = stlread(stl_file);
stlverts = tr.Points*10;
stlfaces = tr.ConnectivityList;
stlverts2 = stlverts;
stlverts2(stlverts2(:,2)>-55,:) = NaN;
stlverts2(stlverts2(:,2)<-90,:) = NaN;
stlverts2(stlverts2(:,1)>120,:) = NaN;
stlverts2(stlverts2(:,1)<80... |
7cde52b2217da3570d8942dfd5774ef90b5c21a3612a303a06902c74f80d7e72 | MATLAB | 30,972 | 1,041 | function mwizard(file)
%MWIZARD - M2HTML Graphical User Interface
% MWIZARD launches a Matlab GUI front-end to edit parameters
% that are then used by M2HTML to generate HTML documentation.
% MWIZARD(FILE) allows to specify a mat-file FILE from which
% default parameters are extracted and can be updated.
%
% For... |
347de4493b2bac3456637d788d9475394e610b511c9a3806dd63069b2d07c7e3 | MATLAB | 31,001 | 1,139 | function [] = VBA_spm_dcm_explore(P)
% build GUI for DCM results reviewing
if ~nargin
[P, sts] = VBA_spm_select(Inf,'^DCM.*\.mat$','select DCM_???.mat');
if ~sts, return; end
nf = size(P,1);
P0 = P;
P = cell(nf,1);
for i=1:nf
[pathstr,name,ext] = fileparts(P0(i,:));
P{i} = [pat... |
35792791059a5f746abb4e504359731a5fc6f3367d1427ad37b2d1f2d7888ec4 | MATLAB | 31,047 | 762 | % Author: Birgit Nierula
% nierula@cbs.mpg.de
function ga_amplitudeAndLatency_allSubjects(subjects, condition, srmr_nr)
savepath_ga = getenv('GADIR'); if ~exist(savepath_ga,'dir'), mkdir(savepath_ga); end
% get condition info
[cond_info] = get_conditionInfo(condition, srmr_nr);
cond_name1 = cond_info.cond_name;
nerv... |
aceb43006ec16f97c042fade733cbbdf581e6d205d8bca4cc215ba686c210790 | MATLAB | 31,094 | 708 | function [cfg] = ft_multiplotTFR(cfg, data)
% FT_MULTIPLOTTFR plots the time-frequency representations of power or coherence
% in a topographical layout. The plots of the indivual sensors are arranged
% according to their location specified in the layout.
%
% Use as
% ft_multiplotTFR(cfg, data)
%
% The data can be a... |
919a0a217c68e5759281f6961f910dca34ae5350417cd2cfeb0e522a68e2c83b | MATLAB | 31,102 | 806 | classdef MovieManagerController < handle
properties (SetAccess=private)
parent_ % scalar LabelerController that created this object
hFig % scalar handle to MovieManager fig
labeler % scalar labeler Obj
mmm_ % scalar MovieManagerModel ref; weak by convention (Labeler owns it)
listeners % cell arr... |
e4bc0c7f85b9be79b05e6e09e97d35439d576b1d49fe140a0363d73415cff4e9 | MATLAB | 31,117 | 927 | classdef LabelCoreSeqMAController < LabelCoreController
% Multi-animal sequential labeling controller
%
% Owns all graphics for multi-animal sequential labeling mode. Receives GUI
% callbacks, extracts GUI state (mouse position, modifiers), delegates data
% logic to LabelCoreSeqMAModel, and syncs graphics in response t... |
33231ff20c7035621df7a79e71f9d90d4130075fef76c34a0924d85a0d61ea05 | MATLAB | 31,325 | 648 | classdef BioSigKit < handle
%% ============== BioSigKit ==================
% BioSigKit is a set of useful signal processing tools that are either
% developed by me personally or others in different fields of biosignal
% processing. BioSigKit is a wrapper with a simple visual interface that
% gathers this tools under... |
d02573b93caf43f4189aa11e812d30f3e879c2d3c56d7e47bf199296dbdea180 | MATLAB | 31,336 | 755 | function ft_plot_cloud(pos, val, varargin)
% FT_PLOT_CLOUD visualizes spatially sparse scalar data as spheres or
% spherical clouds of points and optionally 2D slices through those clouds
%
% Use as
% ft_plot_cloud(pos, val, ...)
% where the first argument are the positions and the second argument are the values
% f... |
fbb8ba3fab7de0b9d9a009eaf2b818df8263c74619990cb6f1cfca7df9103287 | MATLAB | 31,414 | 766 | classdef CellsReader < SurpassObjectReader
% CellsReader Read Imaris ims file Cells object data
%
% © 2015–2016, Peter Beemiller (pbeemiller@gmail.com)
%
% See also ImarisReader | SurpassObjectReader
properties (SetAccess = 'immutable', GetAccess = 'public', Transient = true)
... |
f650e0f4d0b5a97285bb1d6382d39d045840c4c2979704c7d1897f1aa1fb927b | MATLAB | 31,458 | 628 | function [] = plot_ground_truth_compare_jump_distance_backup(folders,option,method)
total_number{1}(1:3) = 0;
total_number{2}(1:3) = 0;
for nfolder = 1:length(folders) % Get total number of replay events
for nshuffle = 1:2 % 1 is original and 2 is global remapped
session_total_number{nshuffle}(nfolder,1:3)... |
1485e0a17d7952ac4df72508ced457ce00ed203c917a467ba3d9f4efdaf239f7 | MATLAB | 31,534 | 1,227 | function GLAN = erp_stata(GLAN,cfg)
% <*LAN)<]
% v.0.1.1.2
%
%ERP_STATA REALIZA ESTADISTICA NOPARAMETRICA A ERP
%
% cfg.
% subject = {[{}{}{}]},{....}
% comp = [n1 n2]; % INDEX OF THE CONDITION TO COMPARED
% matdif = [-1 1 -2 2] % MATRIZ DE DIFERENCIAS, DEL MISMO TAMAGNO QUE cfg.comp.
%... |
8532b2d918861462fe9c0698653466dcab42aeb93e0c6aa3d22c1947deffe887 | MATLAB | 31,577 | 692 | % TSMATCH Searches TSdata for matches to matchcode combinations.
% TSMATCH (TSDATA, MATCHCODES) searches the TSDATA for matches to
% matchcode combinations specified in matchcodes. Works like a search
% engine or a regular expression engine. Match codes are row vectors of
% TS event codes which represent a ... |
3c877b8aa1a1c073c40ea68643dd217eec922fdc9cbba695563795b4b67a562f | MATLAB | 31,608 | 414 | % Analysis of individual questions instead of whole runs
%% Starting brainvoyager from Matlab
bvqx = actxserver('BrainVoyager.BrainVoyagerScriptAccess.1');
%% Defining working directories and general parameters
subjects_analysis_dir = 'E:\Social_networks_analysis\Analysis_2mm_smoothing\'; % A directo... |
0da31201031205a458a5885d2a5389ed02e77cc1c720d38079ab65c451c7210c | MATLAB | 31,620 | 760 | function ft_plot_cloud(pos, val, varargin)
% FT_PLOT_CLOUD visualizes spatially sparse scalar data as points, spheres, or
% spherical clouds of points and optionally 2D slices through the spherical
% clouds. This is for example useful for spectral power on depth (sEEG) electrodes.
%
% Use as
% ft_plot_cloud(pos, v... |
6d9c17b8c8052d57c262a9daa0a28f51f435870ac11d71d7fd32f0a0686f3cc1 | MATLAB | 31,818 | 742 | function varargout = VBA_spm_XYZreg(varargin)
% Registry for GUI XYZ locations, and point list utility functions
%
% ----------------
%
% PointList & voxel centre utilities...
%
% FORMAT [xyz,d] = spm_XYZreg('RoundCoords',xyz,M,D)
% FORMAT [xyz,d] = spm_XYZreg('RoundCoords',xyz,V)
% Round spe... |
8212078b31f8de4434641e93c8d710ddf6c815a77f6aabee24b1a0b64be394c5 | MATLAB | 31,931 | 1,108 | %% GUI for supervising vesicles segmentation
% Author: Antonio Martinez-Sanchez
function varargout = vesseg(varargin)
% VESSEG MATLAB code for vesseg.fig
% VESSEG, by itself, creates a new VESSEG or raises the existing
% singleton*.
%
% H = VESSEG returns the handle to a new VESSEG or the handle to
% ... |
c94da14da5f9973119b3aa4f7857a470316ac3643891feaed954d227e711ae11 | MATLAB | 31,951 | 601 | function estimated_position = log_odd_bayesian_decoding(place_fields_BAYESIAN,bayesian_spike_count,place_field_index,timebin,posbin,option,modify,save_option)
% INPUTS:
% place fields: matrix or []. Place fields to use as a template in the decoding. If empty, it will load place fields for the whole session (extracted_p... |
45f70cbc0704cd5c5687093cda73c27ba3f8a238f9d2f00c6d4de02f690cfa2b | MATLAB | 31,967 | 1,139 | clear
clc
NineMuscleMorphParaInitial = load('NineMuscleMorphParaInitial.mat');
NineMuscleMorphParaInitial = NineMuscleMorphParaInitial.NineMuscleMorphParaInitial;
G = 4; % Muscle Group Number (G = 1 to 9)
x0(1) = NineMuscleMorphParaInitial{G, 1}.MorphologicalParameters.a1;
x0(2) = NineMuscleMorphParaInitial{G, 1}.M... |
24282f0e08c64e852a7fbaae7e14e1a952daac6f72087f44965e9040847cace1 | MATLAB | 31,990 | 938 | function bnd = prepare_mesh_manual(cfg, mri)
% PREPARE_MESH_MANUAL is called by PREPARE_MESH and opens a GUI to manually
% select points/polygons in an mri dataset.
%
% It allows:
% Visualization of 3d data in 3 different projections
% Adjustment of brightness for every slice
% Storage of the data points in an e... |
219a8d9d06b626a2dc7935a2b42ebe0020dc32bdf788b4d21d76676a7f86ca69 | MATLAB | 32,003 | 1,136 | clear
clc
NineMuscleMorphParaInitial = load('NineMuscleMorphParaInitial.mat');
NineMuscleMorphParaInitial = NineMuscleMorphParaInitial.NineMuscleMorphParaInitial;
G = 8; % Muscle Group Number (G = 1 to 9)
x0(1) = NineMuscleMorphParaInitial{G, 1}.MorphologicalParameters.a1;
x0(2) = NineMuscleMorphParaInitial{G, 1}.M... |
b765f1c3760987c27d52b7a57fbcae51871f39030bb5648d0bf8227c90ab6066 | MATLAB | 32,007 | 1,135 | clear
clc
NineMuscleMorphParaInitial = load('NineMuscleMorphParaInitial.mat');
NineMuscleMorphParaInitial = NineMuscleMorphParaInitial.NineMuscleMorphParaInitial;
G = 1; % Muscle Group Number (G = 1 to 9)
x0(1) = NineMuscleMorphParaInitial{G, 1}.MorphologicalParameters.a1;
x0(2) = NineMuscleMorphParaInitial{G, 1}.M... |
0c659f9cc5658f242e304862fb4afabbb9cc9b65acc5581248100d3437cb450a | MATLAB | 32,035 | 1,140 | clear
clc
NineMuscleMorphParaInitial = load('NineMuscleMorphParaInitial.mat');
NineMuscleMorphParaInitial = NineMuscleMorphParaInitial.NineMuscleMorphParaInitial;
G = 2; % Muscle Group Number (G = 1 to 9)
x0(1) = NineMuscleMorphParaInitial{G, 1}.MorphologicalParameters.a1;
x0(2) = NineMuscleMorphParaInitial{G, 1}.M... |
35773d201b682f20264ee3cf60d64a83237a1f7496cc1c60fd1ab58754b1d17f | MATLAB | 32,291 | 411 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
f8c6a3008a03514a10fda52ec1af18c5992fc24c395bb7ac6d7576657963cd6c | MATLAB | 32,295 | 954 | %% Load Unit Data
datRoot = '/Volumes/LaCie/Farries recordings/';
load([datRoot 'unitDat_final_culled.mat'])
uName = arrayfun(@(u) strsplit(u.name), unit, 'UniformOutput', false);
uRat = cellfun(@(u) u{1}, uName, 'UniformOutput', false);
uSes = cellfun(@(u) u{2}, uName, 'UniformOutput', false);
uTrode = cellfun(@(u) ... |
c77920a4c608f7e7ffa8ad53228c37801dc05d7b3227285e80adbff8ba1d504a | MATLAB | 32,300 | 825 | function [x,fval,exitflag,output,grad]=fminlbfgs(funfcn,x_init,optim)
%FMINLBFGS finds a local minimum of a function of several variables.
% This optimizer is developed for image registration methods with large
% amounts of unknown variables.
%
% Optimization methods supported:
% - Quasi Newton Broyden–Flet... |
575044a0db6841ff2c8353ad22ab37bc6804670578ef1e40eb5036c3ac47412f | MATLAB | 32,331 | 733 | function [elec_realigned] = ft_electroderealign(cfg, elec_original)
% FT_ELECTRODEREALIGN rotates, translates, scales and warps electrode positions. The
% default is to only rotate and translate, i.e. to do a rigid body transformation in
% which only the coordinate system is changed. With the right settings if can app... |
861baa1c27347e768d9d371203ced73ff7ad1ec7740aaa72e6bf902b355b7508 | MATLAB | 32,354 | 660 | function plot_ground_truth_compare_normalisation(folders,option,method)
total_number{1}(1:3) = 0;
total_number{2}(1:3) = 0;
for nfolder = 1:length(folders) % Get total number of replay events
for nshuffle = 1:2 % 1 is original and 2 is global remapped
session_total_number{nshuffle}(nfolder,1:3) = 0;
en... |
e6cb3d0db16eaff0ced72a3aadaf30daabd4f9bc867181b14b27cab61803775f | MATLAB | 32,437 | 741 | function [elec_realigned] = ft_electroderealign(cfg, elec_original)
% FT_ELECTRODEREALIGN rotates, translates, scales and warps electrode positions. The
% default is to only rotate and translate, i.e. to do a rigid body transformation in
% which only the coordinate system is changed. With the right settings if can app... |
fbc58cf4694ef8d4b23a0161caf2c5f96c3c225c85dfe98ee5535d890a44e74e | MATLAB | 32,481 | 1,020 | % clear
% clc
NineMuscleMorphParaInitial = load('NineMuscleMorphParaInitial.mat');
NineMuscleMorphParaInitial = NineMuscleMorphParaInitial.NineMuscleMorphParaInitial;
G = 5; % Muscle Group Number (G = 1 to 9)
x0(1) = NineMuscleMorphParaInitial{G, 1}.MorphologicalParameters.OW.a1OW;
x0(2) = NineMuscleMorphParaInitia... |
bc8636b5e2a3f35624fcc611ee3f0806986e2e6de458f3c8c7e66460ea63459a | MATLAB | 32,523 | 838 | function AnalyzeFaceScratch()
Convert();
% Possible args: {'SUA','Pop','ERA','Decode'};
BodySpec();
BodySpecC();
ActionType();
end
function Convert()
%% Body spec
fn ={};
tl = {};
filename = {'20170222-120530-120650-TextTraining',...
'20170222-120530-121309-TextTraining',...
'20170315-10461... |
f46446e3e11773aa8815246a0a85bc3efdb0bc61c52d94e3b173144300ddd78e | MATLAB | 32,539 | 718 | function [] = plot_replay_score_vs_log_odds_difference(folders,option,method)
total_number{1}(1:3) = 0;
total_number{2}(1:3) = 0;
for nfolder = 1:length(folders) % Get total number of replay events
for nshuffle = 1:2 % 1 is original and 2 is global remapped
session_total_number{nshuffle}(nfolder,1:3) = 0;... |
782ea9d4e08fd93e454808e0850482fb9da735510e2198ad502d14724ca71f1b | MATLAB | 32,589 | 904 | function [comp] = ft_componentanalysis(cfg, data)
% FT_COMPONENTANALYSIS performs independent component analysis or other
% spatio-temporal decompositions of EEG or MEG data. This function computes
% the topography and timecourses of the components. The output of this
% function can be further analyzed with FT_TIMELOC... |
be19aec23ca9768c12a524b8ec6a0a1532e747f2ecebc4a4611333cf300be9ee | MATLAB | 32,590 | 904 | function [comp] = ft_componentanalysis(cfg, data)
% FT_COMPONENTANALYSIS performs independent component analysis or other
% spatio-temporal decompositions of EEG or MEG data. This function computes
% the topography and timecourses of the components. The output of this
% function can be further analyzed with FT_TIMELOC... |
ba7d5d2ce161f6a7198ae066c7dadaaccab3cfc7a631ea5fcd605ad856cac08f | MATLAB | 32,638 | 803 | function chantype = ft_chantype(input, desired)
% FT_CHANTYPE determines for each individual channel what chantype of data it
% represents, e.g. a planar gradiometer, axial gradiometer, magnetometer,
% trigger channel, etc. If you want to know what the acquisition system is
% (e.g. ctf151 or neuromag306), you should n... |
56358ab9bd9781050fb87be76241bf8555cbf88ad50375d9fac0228a74707b50 | MATLAB | 32,658 | 1,041 | % clear
% clc
NineMuscleMorphParaInitial = load('NineMuscleMorphParaInitial.mat');
NineMuscleMorphParaInitial = NineMuscleMorphParaInitial.NineMuscleMorphParaInitial;
G = 5; % Muscle Group Number (G = 1 to 9)
x0(1) = NineMuscleMorphParaInitial{G, 1}.MorphologicalParameters.OW.a1OW;
x0(2) = NineMuscleMorphParaInitia... |
8faa4a5429e1fac6af14ac824186bc80499dce67eab7af81a7dda460f2654cfd | MATLAB | 32,700 | 523 |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
fprintf('Merging All Episode QuaSOR Coordinates...')
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
for EpisodeNumbe... |
6c6c1baaa1f089f8f395466d55d6cd5012be267afb856b138d81e5f5ed5424ce | MATLAB | 32,736 | 941 | function stack = tiffread(file_name, indices, varargin)
% tiffread, version 3.32 - November 23, 2018
%
% stack = tiffread;
% stack = tiffread(filename);
% stack = tiffread(filename, indices);
%
% Two options can be specified: 'ReadUnknownTags' and 'DistributeMetaData', eg:
% stack = tiffread(filename, [], 'ReadUnknown... |
2227d9a8abf06fad62c5973c1cd8b6e6f2a4627ec04910f9dbd0d281ce1958f8 | MATLAB | 32,778 | 415 | %%
%# Citation for DISCOVER-EEG-2.0.0
%# If this code contributes to a project that leads to a scientific publication, please acknowledge this work by citing the following paper:
%# Gil Ávila C, Bott FS, Tiemann L, Hohn VD, May ES, Nickel MM, Zebhauser PT, Gross J, Ploner P. DISCOVER-EEG: an open, fully automated EEG p... |
c210e8268bbc433074cdf4ec56acc5fa69446e37daf98b7295fd6aa4e5adb8da | MATLAB | 32,794 | 961 | function bnd = prepare_mesh_manual(cfg, mri)
% PREPARE_MESH_MANUAL is called by PREPARE_MESH and opens a GUI to manually
% select points/polygons in an mri dataset.
%
% It allows:
% Visualization of 3d data in 3 different projections
% Adjustment of brightness for every slice
% Storage of the data points in an e... |
7bce9ad9dfc8d1112238b938f8089b981a25cfb6c1cc471cc4841887f0d90ac3 | MATLAB | 32,819 | 740 | % encoderFindBehaviorPeriods.m
% Sarah West
% 10/11/21
function [parameters] = encoderFindBehaviorPeriods(parameters)
% Inputs
fps = parameters.fps;
frames = parameters.frames;
periods_long_threshold = parameters.periods_long_threshold;
periods_long = parameters.periods_long;
pe... |
12b2a275aa5ba1477efd223221bbae0d44036dbc9a55509d11a186f0c3023d25 | MATLAB | 32,823 | 1,073 | %% Diffraction crosstalk from a point source through a Gaussian aperture
% analytical solution
% single source through two pinholes - coherent vs incoherent summation
lambda = 520e-9;
k = 2*pi/lambda;
sp = 7.4250e-5; % spacing between weights
pds = 2.5e-3; % spacing between pds
x_grid = 2e-5;
x = -5e-3:x... |
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