plateform stringclasses 1
value | repo_name stringlengths 13 113 | name stringlengths 3 74 | ext stringclasses 1
value | path stringlengths 12 229 | size int64 23 843k | source_encoding stringclasses 9
values | md5 stringlengths 32 32 | text stringlengths 23 843k |
|---|---|---|---|---|---|---|---|---|
github | oiwic/QOS-master | tracking.m | .m | QOS-master/qos/+uix/tracking.m | 5,760 | utf_8 | 8b7417c20b8797c89c9253973d4c9f49 | function varargout = tracking( varargin )
%tracking Track anonymized usage data
%
% tracking(p,v,id) tracks usage to the property p for the product version
% v and identifier id. No personally identifiable information is tracked.
%
% r = tracking(...) returns the server response r, for debugging purposes.
%
% tra... |
github | oiwic/QOS-master | Text.m | .m | QOS-master/qos/+uix/Text.m | 14,906 | utf_8 | 76ee07c6fdddfe7c9dac8afc63ba2af5 | classdef Text < matlab.mixin.SetGet
%uix.Text Text control
%
% t = uix.Text(p1,v1,p2,v2,...) constructs a text control and sets
% parameter p1 to value v1, etc.
%
% A text control adds functionality to a uicontrol of Style text:
% * Set VerticalAlignment to 'top', 'middle' or 'bottom'
... |
github | oiwic/QOS-master | loadIcon.m | .m | QOS-master/qos/+uix/loadIcon.m | 3,127 | utf_8 | f8f5bf086b84150ff304ff497a22a246 | function cdata = loadIcon( filename, bgcol )
%loadIcon Load an icon and set the transparent color
%
% cdata = uix.loadIcon(filename) loads the icon from the specified
% filename. For PNG files with transparency, the transparent pixels are
% set to NaN. For other files, pixels that are pure green are set to
% ... |
github | oiwic/QOS-master | ChildObserver.m | .m | QOS-master/qos/+uix/ChildObserver.m | 8,831 | utf_8 | d8bd8928f6e84a50d8060fa72735e107 | classdef ( Hidden, Sealed ) ChildObserver < handle
%uix.ChildObserver Child observer
%
% co = uix.ChildObserver(o) creates a child observer for the graphics
% object o. A child observer raises events when objects are added to
% and removed from the property Children of o.
%
% See also:... |
github | oiwic/QOS-master | Empty.m | .m | QOS-master/qos/+uix/Empty.m | 2,628 | utf_8 | 3f36c752763a9a98d04ad7f56d5df829 | function obj = Empty( varargin )
%uix.Empty Create an empty space
%
% obj = uix.Empty() creates an empty space that can be used to add gaps
% between elements in layouts.
%
% obj = uix.Empty(param,value,...) also sets one or more property
% values.
%
% See the <a href="matlab:doc uix.Empty">documentation</a>... |
github | oiwic/QOS-master | resetQSettings.m | .m | QOS-master/qos/+sqc/+util/resetQSettings.m | 4,227 | utf_8 | 125a7f5a751a9af780ad012d7496cad6 | function resetQSettings()
% Copyright 2017 Yulin Wu, University of Science and Technology of China
% mail4ywu@gmail.com/mail4ywu@icloud.com
choice = questdlg('Reset all qubit settings?','Reset all qubit settings?',...
'Yes','No','No');
if isempty(choice) || strcmp(choice, 'No')
return;
... |
github | oiwic/QOS-master | PlotCPB.m | .m | QOS-master/qos/+sqc/+simulation/+ctx/PlotCPB.m | 6,347 | utf_8 | c889d2ae188b78ea47467f205c52eaf3 |
% plots the lowest energy levels and the
% average charge of a Cooper Pair Box (CPB), both single junction
% CPB and split CPB.
% A function call plots two figures, one is the energy levels and
% and the other is the average charge. The calculated data is
% saved to the current directory thus a later function call wi... |
github | oiwic/QOS-master | CPBEL.m | .m | QOS-master/qos/+sqc/+simulation/+ctx/CPBEL.m | 1,922 | utf_8 | 8ad0bebc3de4f2910f7077866e708cd5 |
% CPBEL calculats the lowest energy levels of a
% Cooper Pair Box (CPB), Transmon and Xmon. CPBEL returns the lowest M energy level
% values as an array EL and eigen vectors as an Matrix (the nth
% column is the eign vecotr of eign value EL(n)).
% EnergyLevel=CPBEL(Ec,Ej,Ng); EnergyLevel=CPBEL(Ec,Ej,Ng,phi);
% EnergyL... |
github | oiwic/QOS-master | PlotCPBEL.m | .m | QOS-master/qos/+sqc/+simulation/+ctx/PlotCPBEL.m | 5,014 | utf_8 | 67d7e6933fc8fceab84b9dd2e5162fde |
% This MATLAB function plots the lowest energy levels of a
% Cooper Pair Box (CPB), both single junction CPB and split CPB.
% A function call plots a figure of the energy levels and the
% calculated data is saved to the current directory (a later
% function call with the same parameters can thus skip the
% calculation... |
github | oiwic/QOS-master | TCPBEL4.m | .m | QOS-master/qos/+sqc/+simulation/+ctx/+twoBits/TCPBEL4.m | 899 | utf_8 | 62987cbd6351801cd9f92d478ac5f94d |
% TCPBEL4 calculates the eigen values and eigen states of two
% capacitively coupled charge qubits by expanding to the basis:
% { |00> |10> |01> |11> }.
% See TCPBEL for detailed description.
% Example:
% EnergyLevel=TCPBEL(1,1,0.2,0.2,0.3,0.5,0.01);
% Author: Yulin Wu
% Date: 2009/8/14
% Email: mail4ywu@gmail.com
f... |
github | oiwic/QOS-master | PlotTCPBELs.m | .m | QOS-master/qos/+sqc/+simulation/+ctx/+twoBits/PlotTCPBELs.m | 4,156 | utf_8 | 736aab4176f5dc5f2204ec8b4472f2a1 | % PlotTCPBELs is a slice-plot version of PlotTCPBEL.
% Author: Yulin Wu
% Date: 2009/8/13
% Email: mail4ywu@gmail.com
function PlotTCPBELs(Ec1,Ec2,Em,Ej1,Ej2,varargin)
NgLim=[0.25 0.8]; % Default ploting range: Ng, [-0.25 0.8],
nP=400; % 400 points for each energy level and
N=4; ... |
github | oiwic/QOS-master | PlotTCPBEL.m | .m | QOS-master/qos/+sqc/+simulation/+ctx/+twoBits/PlotTCPBEL.m | 4,016 | utf_8 | 533461691ff66e550d64e5afcbb86e82 |
% This MATLAB function plots the lowest energy levels of two
% capacitively coupled Cooper Pair Boxes (CPBs). A function call
% plots a figure of the energy levels. The calculated data is
% saved to the directory $/Output (a later function call with the
% same parameters can thus skip the calculation procedure).
% Fun... |
github | oiwic/QOS-master | PlotTCPBELsP.m | .m | QOS-master/qos/+sqc/+simulation/+ctx/+twoBits/PlotTCPBELsP.m | 3,675 | utf_8 | efa6473671483e49b50d1235e02dccfd | % PlotTCPBELsP is a parallel computing version of PlotTCPBELs.
% make sure parallel computing enabled.
% Author: Yulin Wu
% Date: 2009/8/13
% Email: mail4ywu@gmail.com
function PlotTCPBELsP(Ec1,Ec2,Em,Ej1,Ej2,varargin)
NgLim=[0.25 0.8]; % Default ploting range: Ng, [-0.25 0.8],
nP=400; % ... |
github | oiwic/QOS-master | PlotTCPBEL4s.m | .m | QOS-master/qos/+sqc/+simulation/+ctx/+twoBits/PlotTCPBEL4s.m | 2,077 | utf_8 | 0337e8ae09b6839f6d54847d6fa82518 | % PlotTCPBEL4s is a slice-plot version of PlotTCPBEL expand
% to the basis { |00> |10> |01> |11> }.
% Author: Yulin Wu
% Date: 2009/8/14
% Email: mail4ywu@gmail.com
function PlotTCPBEL4s(Ec1,Ec2,Em,Ej1,Ej2,varargin)
NgLim=[0.25 0.8]; % Default ploting range: Ng, [-0.25 0.8],
nP=400; % 400... |
github | oiwic/QOS-master | TCPBEL.m | .m | QOS-master/qos/+sqc/+simulation/+ctx/+twoBits/TCPBEL.m | 1,964 | utf_8 | 526a2eb30f37b91ac11654472ea07e45 |
% This MATLAB function calculats the lowest energy levels of two
% capacitively coupled Cooper Pair Boxes (CPBs). TCPBEL returns
% the lowest M energy level values as an array EL an eigen vectors
% as an Matrix (the nth column is the eign vecotr of eign value
% EL(n)).
% Function call and Meaning of arguments:
% Ener... |
github | oiwic/QOS-master | TriJFlxQbtdE.m | .m | QOS-master/qos/+sqc/+simulation/fluxQubit/3JJ/Fitting/TriJFlxQbtdE.m | 770 | utf_8 | e322b6267f212553e2c54421d78e3650 | function [E01,E02] = TriJFlxQbtdE(Jc,Cc,S,L,alpha,kappa,sigma,FluxBias,nk,nl,nm)
[Ej, Ec, beta] = EjEcBetaCalc(Jc,Cc,S,L,alpha);
EL = TriJFlxQbtEL(Ej,Ec,alpha,beta,kappa,sigma,FluxBias,nk,nl,nm,6);
E01 = (EL(3) + EL(4) - EL(1) - EL(2))/2;
E02 = (EL(5) + EL(6) - EL(1) - EL(2))/2;
end
function [Ej, Ec, b... |
github | oiwic/QOS-master | SpectrumLineErrorFcn_Jc_Cc_S_Alpaha_high.m | .m | QOS-master/qos/+sqc/+simulation/fluxQubit/3JJ/Fitting/SpectrumLineErrorFcn_Jc_Cc_S_Alpaha_high.m | 2,058 | utf_8 | 2d30be5f073da3099b6de0e619dde816 | function Err = SpectrumLineErrorFcn_Jc_Cc_S_Alpaha_high(p)
% x = [0 -3.0400 -6.0800 -9.1200 -12.1600 -15.2000];
% % y1 = [1.0712 5.2182 10.2069 15.1502 19.9511 24.2124];
% % y2 = [20.4903 22.3517 24.1392 25.7463 26.9363];
% x = [0 -3.0400 -6.0800 -9.1200 -12.1600 -15... |
github | oiwic/QOS-master | SpectrumLineErrorFcn_Jc_Cc_S_Alpaha_low.m | .m | QOS-master/qos/+sqc/+simulation/fluxQubit/3JJ/Fitting/SpectrumLineErrorFcn_Jc_Cc_S_Alpaha_low.m | 2,056 | utf_8 | 0c13251b4d4e82bb4853524e8c177ca6 | function Err = SpectrumLineErrorFcn_Jc_Cc_S_Alpaha_low(p)
% x = [0 -3.0400 -6.0800 -9.1200 -12.1600 -15.2000];
% % y1 = [1.0712 5.2182 10.2069 15.1502 19.9511 24.2124];
% % y2 = [20.4903 22.3517 24.1392 25.7463 26.9363];
% x = [0 -3.0400 -6.0800 -9.1200 -12.1600 -15.... |
github | oiwic/QOS-master | TriJFlxQbtEL.m | .m | QOS-master/qos/+sqc/+simulation/fluxQubit/3JJ/Fitting/TriJFlxQbtEL.m | 4,355 | utf_8 | eea0c43da523c4ca69b4dc8e04e4b756 | function EL = TriJFlxQbtEL(Ej,Ec,alpha,beta,kappa,sigma,FluxBias,nk,nl,nm,nlevels)
% 'TriJFlxQbtEL' calculates the three-junction flux qubit energy levels.
% Based on the papar: Robertson et al., Phys. Rev. Letts. B 73, 174526 (2006).
% Syntax
% Energy Level values = TriJFlxQbtEL(Ej,Ec,alpha,beta,kappa,sigma,FluxBias... |
github | oiwic/QOS-master | ThreeJJQbtES.m | .m | QOS-master/qos/+sqc/+simulation/fluxQubit/3JJ/GUIver/ThreeJJQbtES.m | 76,488 | utf_8 | 3510ee242c623625d8177c1ef818317e |
function varargout = ThreeJJQbtES(varargin)
% THREEJJQBTES M-file for ThreeJJQbtES.fig
% THREEJJQBTES, by itself, creates a new THREEJJQBTES or raises the existing
% singleton*.
%
% H = THREEJJQBTES returns the handle to a new THREEJJQBTES or the handle to
% the existing singleton*.
%
% THREEJ... |
github | oiwic/QOS-master | TriJFlxQbtEL.m | .m | QOS-master/qos/+sqc/+simulation/fluxQubit/3JJ/NonGUIver/TriJFlxQbtEL.m | 3,555 | utf_8 | efcd5ed209cbd8f77f6368b069b574e6 | function EL = TriJFlxQbtEL(Ej,Ec,alpha,beta,kappa,sigma,FluxBias,nk,nl,nm,nlevels)
% 'TriJFlxQbtEL' calculates the three-junction flux qubit energy levels.
% Based on the papar: Robertson et al., Phys. Rev. Letts. B 73, 174526 (2006).
% Syntax
% Energy Level values = TriJFlxQbtEL(Ej,Ec,alpha,beta,kappa,sigma,FluxBias... |
github | Jann5s/BasicGDIC-master | basicgdic.m | .m | BasicGDIC-master/basicgdic.m | 277,292 | utf_8 | 2047f1c1094adfb98912478c496ff353 | function varargout = basicgdic(varargin)
% BASICGDIC() is a program with a graphical user interface which can be
% used to perform Global Digital Image Correlation. Please see the help
% which is embedded in the user interface in the <Info> tab.
%
% Run this file to start the program, the help is also contained... |
github | Jann5s/BasicGDIC-master | quiverjn.m | .m | BasicGDIC-master/lib_bgdic/quiverjn.m | 9,790 | utf_8 | 1917f7f867d9e0c5d9134f4b0aa0059e | function hh = quiverjn(varargin)
%QUIVER Quiver plot.
% QUIVER(X,Y,U,V) plots velocity vectors as arrows with components (u,v)
% at the points (x,y). The matrices X,Y,U,V must all be the same size
% and contain corresponding position and velocity components (X and Y
% can also be vectors to specify a uniform g... |
github | Jann5s/BasicGDIC-master | rescompute.m | .m | BasicGDIC-master/lib_bgdic/rescompute.m | 5,171 | utf_8 | a56cc7d2f385f0c6e029915a8ecefb39 | % ==================================================
function [] = rescompute(varargin)
% compute result fields
H = varargin{3};
S = guihandles(H);
D = guidata(H);
% if D.usegpu
% D.gpu = gpuDevice;
% guidata(H,D);
% end
if ~isfield(D,'files')
return;
end
if ~isfield(D,'cor')
return;
end
% get the po... |
github | Jann5s/BasicGDIC-master | ginputjn.m | .m | BasicGDIC-master/lib_bgdic/ginputjn.m | 9,140 | utf_8 | c4d5714f00e7e828e17f2cd9602967ee | function [out1,out2,out3] = ginputjn(arg1)
%GINPUT Graphical input from mouse.
% [X,Y] = GINPUT(N) gets N points from the current axes and returns
% the X- and Y-coordinates in length N vectors X and Y. The cursor
% can be positioned using a mouse. Data points are entered by pressing
% a mouse button or any k... |
github | Jann5s/BasicGDIC-master | plotbasis.m | .m | BasicGDIC-master/lib_bgdic/plotbasis.m | 7,256 | utf_8 | 2fbccbed4c74578ab8112fdcaa2777b7 | % ==================================================
function [] = plotbasis(varargin)
% plot the current basis
H = varargin{3};
S = guihandles(H);
D = guidata(H);
if isfield(D,'outputfile')
% headless mode
return
end
% test if there are images
if ~isfield(D,'files')
return;
end
% Region of interest
if ~isf... |
github | Jann5s/BasicGDIC-master | bcwaitbar.m | .m | BasicGDIC-master/lib_bgdic/bcwaitbar.m | 1,348 | utf_8 | bd2b5f811191b0c8d3be69f2b75037da | % ==================================================
function [] = bcwaitbar(H,varargin)
% Button Callback: update the waitbar
% bcwaitbar(H,A)
% H = gui handle
% A = relative part of the waitbar which is full
S = guihandles(H);
D = guidata(H);
if isfield(D,'outputfile')
% headless mode, don't plot anything
re... |
github | Jann5s/BasicGDIC-master | pateval.m | .m | BasicGDIC-master/lib_bgdic/pateval.m | 4,783 | utf_8 | 0ebe529ab37f1b92d3b5e2da8779839a | % ==================================================
function [] = pateval(varargin)
% Button Callback: Evaluate the pattern
H = varargin{3};
S = guihandles(H);
D = guidata(H);
if ~isfield(D,'files')
msgstr = {'This action requires loaded images,';'load images in section 1'};
msgdlgjn(msgstr,dlgposition(H));
... |
github | Jann5s/BasicGDIC-master | inputdlgjn.m | .m | BasicGDIC-master/lib_bgdic/inputdlgjn.m | 3,028 | utf_8 | e01c55ac10d34f02181b98bcb50499f3 | function Answer=inputdlgjn(Prompt, Title, NumLines, DefAns, Position)
% function similar to inputdlg, except simpler and with the option to
% position it.
fontsize = 12;
N = length(Prompt);
M = max(cellfun('length',Prompt));
Figheight = N*2.0*fontsize + 6*fontsize + 2.5*fontsize;
Figwidth = M*1*fontsize + 10*1*fontsi... |
github | Jann5s/BasicGDIC-master | buildphi_legendre.m | .m | BasicGDIC-master/lib_bgdic/buildphi_legendre.m | 4,414 | utf_8 | 8a9ef7c76a829963ab23f166e409ff97 | function phi = buildphi_legendre(x,y,phi_list,roi,varargin)
%BUILDPHI_LEGENDRE creates the basis function matrix phi, which has one
% row for each pixel and one column for each basis function. The created
% 2D basis functions are based on the Legendre polynomials by
% Adrien-Marie Legendre.
%
% phi = build... |
github | Jann5s/BasicGDIC-master | plotimage.m | .m | BasicGDIC-master/lib_bgdic/plotimage.m | 1,340 | utf_8 | 64fab9dd9435e37bf42e2ca5c3c6ee18 | % ==================================================
function [] = plotimage(H)
% plot the current image to figpanel1
S = guihandles(H);
D = guidata(H);
if isfield(D,'outputfile')
% headless mode
return
end
% test if there are images
if ~isfield(D,'files')
return;
end
Nim = length(D.files);
% get current i... |
github | Jann5s/BasicGDIC-master | questdlgjn.m | .m | BasicGDIC-master/lib_bgdic/questdlgjn.m | 2,890 | utf_8 | 8636f53e071e35582654e368715ea7da | function Button=questdlgjn(Question,Title,Btn1,Btn2,Default,Position)
% function similar to questdlg, except simpler and with the option to
% position it.
if ~iscell(Question)
Question = {Question};
end
fontsize = 14;
N = length(Question);
M = max(cellfun('length',Question));
Figheight = N*2*fontsize + 2*fontsiz... |
github | Jann5s/BasicGDIC-master | jnmap.m | .m | BasicGDIC-master/lib_bgdic/jnmap.m | 2,969 | utf_8 | c9fcfad5111ee46345c8780e2368ef92 | function cmap = jnmap(varargin)
% Create Colormaps with monotomic change in Luminace and change in
% GrayValue (if converted).
%
% cmap = jnmap(N) : produces and Nx3 matrix as do the default matlab
% colormaps
%
% cmap = jnmap(N,colorname) : same but selects a color scheme with name
% ... |
github | Jann5s/BasicGDIC-master | plotiguess.m | .m | BasicGDIC-master/lib_bgdic/plotiguess.m | 6,535 | utf_8 | 7854d77a8c9160559cd34f3ac7adb6d8 | % ==================================================
function [] = plotiguess(H)
% plot the current image to figpanel1
S = guihandles(H);
D = guidata(H);
if isfield(D,'outputfile')
% headless mode
return
end
% test if there are images
if ~isfield(D,'files')
return;
end
% get current image (i.e. slider posi... |
github | Jann5s/BasicGDIC-master | buildphi_chebyshev.m | .m | BasicGDIC-master/lib_bgdic/buildphi_chebyshev.m | 4,453 | utf_8 | 5affe03bc22d62613537b2d203d68770 | function phi = buildphi_chebyshev(x,y,phi_list,roi,varargin)
%BUILDPHI_CHEBYSHEV creates the basis function matrix phi, which has one
% row for each pixel and one column for each basis function. The created
% 2D basis functions are based on the Chebyshev polynomials of the first
% kind by Pafnuty Chebyshev (a... |
github | Jann5s/BasicGDIC-master | plotroimask.m | .m | BasicGDIC-master/lib_bgdic/plotroimask.m | 2,619 | utf_8 | 1beb9f85fc948c232e153393a9bf8242 | % ==================================================
function [] = plotroimask(H)
% plot funtion for the evaluated pattern
S = guihandles(H);
D = guidata(H);
if isfield(D,'outputfile')
% headless mode
return
end
if ~isfield(D,'files')
return;
end
Nim = length(D.files);
id = str2double(get(S.roiid,'String'... |
github | Jann5s/BasicGDIC-master | correlate.m | .m | BasicGDIC-master/lib_bgdic/correlate.m | 26,394 | utf_8 | 6f3b921fd49ba1ae7149f491543f5835 | function dic = correlate(H,S,cg,phi12,phi34)
D = guidata(H);
usegpu = get(S.dicusegpu,'Value')-1;
if isfield(D,'outputfile')
headlessmode = true;
else
headlessmode = false;
end
% Prepare DIC
% ========================
dic = [];
% image space
f = cg.f;
g = cg.g;
x = cg.x;
y = cg.y;
[X, Y] = meshgrid(x,y);
i... |
github | Jann5s/BasicGDIC-master | dlgposition.m | .m | BasicGDIC-master/lib_bgdic/dlgposition.m | 285 | utf_8 | 7d1818cd97469cfdc8b55857acdcffa3 | % ==================================================
function dlgpos = dlgposition(H)
% helper function to get the center position for the dialog box, used for
% inputdlgjn
guipos = get(H,'Position');
xc = guipos(1) + 0.3*guipos(3);
yc = guipos(2) + 0.8*guipos(4);
dlgpos = [xc yc];
|
github | Jann5s/BasicGDIC-master | selectarea.m | .m | BasicGDIC-master/lib_bgdic/selectarea.m | 26,621 | utf_8 | 85e621954221c3a26ee5debe319d648b | function varargout = selectarea(varargin)
% A = selectarea, allows the user to interactively draw a shape in the
% current axes. The default shape is a rectangle. The shape control points
% are returned in matrix A, which for the case of the rectangle are the
% positions of two diagonally opposed corners, see more deta... |
github | Jann5s/BasicGDIC-master | listdlgjn.m | .m | BasicGDIC-master/lib_bgdic/listdlgjn.m | 3,399 | utf_8 | e49f003ed0221e6de496be1aafb9e7e4 | function [Selection, Ok] = listdlgjn(Prompt,Title,List,SelMode,Position)
% function similar to listdlg, except simpler and with the option to
% position it.
% [selection,ok] = listdlg(...
% 'Name','Select strain definition',...
% 'PromptString','Select strain definition',...
% 'SelectionMod... |
github | Jann5s/BasicGDIC-master | plotres.m | .m | BasicGDIC-master/lib_bgdic/plotres.m | 11,258 | utf_8 | 67c0af40cd9424e6f1508799401fd51a | % ==================================================
function [] = plotres(varargin)
% compute result figure
H = varargin{3};
S = guihandles(H);
D = guidata(H);
if isfield(D,'outputfile')
% headless mode
return
end
if ~isfield(D,'files')
return;
end
if ~isfield(D,'cor')
return;
end
if ~isfield(D.cor,'co... |
github | Jann5s/BasicGDIC-master | msgdlgjn.m | .m | BasicGDIC-master/lib_bgdic/msgdlgjn.m | 2,001 | utf_8 | 6d2d010713116624bb8bd97508c82699 | function msgdlgjn(Message,Position)
% function similar to msgbox, except simpler and with the option to
% position it.
if ~iscell(Message)
Message = {Message};
end
Title = 'basic gdic message';
fontsize = 12;
N = length(Message);
M = max(cellfun('length',Message));
Figheight = N*2.5*fontsize + 3.0*fontsize;
Fig... |
github | Jann5s/BasicGDIC-master | plotcor.m | .m | BasicGDIC-master/lib_bgdic/plotcor.m | 3,866 | utf_8 | 5a05dbac63927d0117d348f71264b1ce | % ==================================================
function [] = plotcor(H)
% plot the current image to figpanel7
S = guihandles(H);
D = guidata(H);
if isfield(D,'outputfile')
% headless mode
return
end
% test if there are images
if ~isfield(D,'files')
return;
end
n = D.files(1).size(1);
m = D.files(1).si... |
github | Jann5s/BasicGDIC-master | jncurvemap.m | .m | BasicGDIC-master/lib_bgdic/jncurvemap.m | 3,730 | utf_8 | 0d9e58bfff2c12eb9dcb21e6c94cb168 | function colors = jncurvemap(N,varargin)
% colors = jncurvemap(N)
%
% creates a cell-array of colors of length N. Note, this is not the same as
% the typical matrices obtained from a colormap type command (e.g. jet).
% the colors cell-array can be directly applied to a list of handles.
%
% example:
% x = linspace(0,1,1... |
github | Jann5s/BasicGDIC-master | plotpattern.m | .m | BasicGDIC-master/lib_bgdic/plotpattern.m | 4,157 | utf_8 | 637528aa28d3964a571b484d51abf745 | % ==================================================
function [] = plotpattern(H)
% plot funtion for the evaluated pattern
S = guihandles(H);
D = guidata(H);
if isfield(D,'outputfile')
% headless mode
return
end
if ~isfield(D,'files')
return;
end
% hide the ACF contour
delete(findobj(H,'Tag','pat_contour')... |
github | Jann5s/BasicGDIC-master | plotacf.m | .m | BasicGDIC-master/lib_bgdic/plotacf.m | 2,204 | utf_8 | 208c5e0b57d76dea733cba55213db15c | % ==================================================
function [] = plotacf(H)
% plot function for the evaluated autocorrelation function
D = guidata(H);
S = guihandles(H);
id = str2double(get(S.patid,'String'));
if isfield(D,'outputfile')
% headless mode
return
end
if ~isfield(D,'files')
return;
end
Nim = l... |
github | ganlubbq/matlab_beam_doa-master | beampattern.m | .m | matlab_beam_doa-master/Beam and Post/beampattern.m | 5,347 | utf_8 | b8dcfd082d676e6799f69fb494f49279 | function beampattern(beam_nr,phi_d,mue,mics,fs,varargin)
% beampattern(beam_nr,phi_d,mue,mics,fs,sim,phi_n)
% Plots the Beampattern of a 1-dimensional Array and the frequency response
% at a defined angle, as well as the frequncy response for small
% perturbations imposed to mic positions
% beam_nr
% phi_d
% mue
% mics... |
github | ganlubbq/matlab_beam_doa-master | istft.m | .m | matlab_beam_doa-master/STFT analysis - synthesis/istft.m | 1,814 | utf_8 | c64b6ca4cb5da6f329e8441ffea1f9c3 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Inverse Short-Time Fourier Transform %
% with MATLAB Implementation %
% %
% Author: M.Sc. Eng. Hristo Zhivomirov 12/26/13 %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
github | ganlubbq/matlab_beam_doa-master | stft.m | .m | matlab_beam_doa-master/STFT analysis - synthesis/stft.m | 1,547 | utf_8 | d38b73eee539e2f08c415ad0108eefd9 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Short-Time Fourier Transform %
% with MATLAB Implementation %
% %
% Author: M.Sc. Eng. Hristo Zhivomirov 12/21/13 %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
github | ganlubbq/matlab_beam_doa-master | RobustFSBdes.m | .m | matlab_beam_doa-master/Desktop/Matlab_Code_Angabe/RobustFSBdes.m | 14,966 | utf_8 | f8e2b60c21f75b32c814e27495821145 | % RobustFSB Designs the optimum filter weights of a robust least-squares
% frequency-invariant polynomial (RLSFIP) filter-and-sum beamformer.
%
function [fir_imp_resp, cfg, steerVector, realWNG_dB] = ...
RobustFSBdes(cfg)
local = [];
%------------------------------------------------------------------... |
github | ganlubbq/matlab_beam_doa-master | RobustFSBORG.m | .m | matlab_beam_doa-master/Desktop/Matlab_Code_Angabe/RobustFSBORG.m | 18,061 | iso_8859_13 | e19afddaa14b4622f7fb7ce34b9b560b | % RobustFSB Designs the optimum filter weights of a robust least-squares
% frequency-invariant polynomial (RLSFIP) filter-and-sum beamformer.
%
% Inputs:
% N: Number of sensors or actors
% spacing: spacing between micophones or radius of array [meters]
% 0 => no... |
github | ganlubbq/matlab_beam_doa-master | estimate_cdr_nodoa.m | .m | matlab_beam_doa-master/Desktop/Matlab_Code_Angabe/estimate_cdr_nodoa.m | 1,389 | utf_8 | b12850a707e91ffd8c8be07b04f04121 | %ESTIMATE_CDR_NODOA
% Blind (DOA-independent), unbiased estimation of the Coherent-to-Diffuse Ratio (CDR)
% from the complex coherence of a mixed (noisy) signal. Equivalent to CDRprop3 in [1].
%
% CDR = estimate_cdr_nodoa(Cxx, Cnn)
% Cxx: complex coherence of mixed (noisy) signal
% Cnn: coherence of noise ... |
github | ganlubbq/matlab_beam_doa-master | fft2melmx.m | .m | matlab_beam_doa-master/Desktop/Matlab_Code_Angabe/tools/fwsegsnr/fft2melmx.m | 6,437 | utf_8 | aed4ba527b0df617c06c56660cb6dd1c | function [wts,binfrqs] = fft2melmx(nfft, sr, nfilts, width, minfrq, maxfrq, htkmel, constamp)
% wts = fft2melmx(nfft, sr, nfilts, width, minfrq, maxfrq, htkmel, constamp)
% Generate a matrix of weights to combine FFT bins into Mel
% bins. nfft defines the source FFT size at sampling rate sr.
% Optional ... |
github | ganlubbq/matlab_beam_doa-master | get_asr_score_longsignal.m | .m | matlab_beam_doa-master/Desktop/Matlab_Code_Angabe/tools/sphinx_eval/get_asr_score_longsignal.m | 1,422 | utf_8 | a05565da96107aa0914c898c1ab421a3 | % get_asr_score_longsignal(long_signal, listname, endpoints)
%
% Andreas Schwarz (schwarz@lnt.de), 2013
%
% This function takes a concatenation of GRID utterances, splits it, calls the
% speech recognizer, and returns the keyword score (recognition rate for
% letter and number in the utterance, as in the CHIME challeng... |
github | ganlubbq/matlab_beam_doa-master | calc_grid_score.m | .m | matlab_beam_doa-master/Desktop/Matlab_Code_Angabe/tools/sphinx_eval/calc_grid_score.m | 784 | utf_8 | 931e917b36cbe9f487f30700f6731b05 | % unlike calc_chime_score, this function considers all words in the utterance
function [ relative_score ] = calc_grid_score( transcription )
correct = 0;
total = 0;
lines = regexp(strtrim(transcription),'\s*\n\s*','split');
for i=1:length(lines)
line = lines{i};
parts = regexp(line,'\(','split');
recognized_... |
github | ganlubbq/matlab_beam_doa-master | BF_Array_GeometryORG.m | .m | matlab_beam_doa-master/Desktop/Matlab_Code_Angabe/Generalized_RLSFI_BF/BF_Array_GeometryORG.m | 10,646 | utf_8 | c51be47f3a8f924a4a46500e6df9883e | %--------------------------------------------------------------------------
% Array Geometry
%--------------------------------------------------------------------------
function cfg = BF_Array_GeometryORG(cfg)
switch (cfg.geometry)
%-----------... |
github | ganlubbq/matlab_beam_doa-master | RobustFSB.m | .m | matlab_beam_doa-master/Desktop/Matlab_Code_Angabe/Generalized_RLSFI_BF/RobustFSB.m | 18,066 | iso_8859_13 | fde40277013097b05842c849828e06a1 | % RobustFSB Designs the optimum filter weights of a robust least-squares
% frequency-invariant polynomial (RLSFIP) filter-and-sum beamformer.
%
% Inputs:
% N: Number of sensors or actors
% spacing: spacing between micophones or radius of array [meters]
% 0 => no... |
github | ganlubbq/matlab_beam_doa-master | BF_Array_Geometry.m | .m | matlab_beam_doa-master/Desktop/Matlab_Code_Angabe/Generalized_RLSFI_BF/BF_Array_Geometry.m | 3,633 | utf_8 | 64c0c8b993e6f54de5c7e419e83a2021 | %--------------------------------------------------------------------------
% Array Geometry
%--------------------------------------------------------------------------
function cfg = BF_Array_Geometry(cfg)
switch (cfg.geometry)
%--------------... |
github | ganlubbq/matlab_beam_doa-master | InitLookDirVecORG.m | .m | matlab_beam_doa-master/Desktop/Matlab_Code_Angabe/Generalized_RLSFI_BF/InitLookDirVecORG.m | 1,981 | utf_8 | b0fc2f7e82155795dd8f7868654fc46f | %--------------------------------------------------------------------------
% Look Direction Vector
%--------------------------------------------------------------------------
function [cfg] = InitLookDirVecORG(cfg)
switch(cfg.int_choice)
%------... |
github | ganlubbq/matlab_beam_doa-master | InitLookDirVec.m | .m | matlab_beam_doa-master/Desktop/Matlab_Code_Angabe/Generalized_RLSFI_BF/InitLookDirVec.m | 1,369 | utf_8 | 490d36417fc2b1298fc7d601dad26910 | %--------------------------------------------------------------------------
% Look Direction Vector
%--------------------------------------------------------------------------
function [local] = InitLookDirVec(cfg,local)
% create vector d
%d includes all vec... |
github | ganlubbq/matlab_beam_doa-master | BF_Plot_BP.m | .m | matlab_beam_doa-master/Desktop/Matlab_Code_Angabe/Generalized_RLSFI_BF/BF_Plot_BP.m | 10,041 | ibm852 | 360548fdc8e8d33735fe0fef2134445a | %--------------------------------------------------------------------------
% Plotting PBF Array Beampattern %
%--------------------------------------------------------------------------
% This function plots the resulting beampattern of the polynomial
% beamformer as well as th... |
github | ganlubbq/matlab_beam_doa-master | estimate_cdr_nodiffuse.m | .m | matlab_beam_doa-master/cdr-demo/estimate_cdr_nodiffuse.m | 1,396 | utf_8 | 43c131381f4fd4e5b552a8f25639bc4e | %ESTIMATE_CDR_NODIFFUSE
% Unbiased estimation of the Coherent-to-Diffuse Ratio (CDR) from the complex
% coherence of a mixed (noisy) signal, without assuming knowledge of the noise
% coherence. Equivalent to CDRprop4 in [1].
%
% CDR = estimate_cdr_nodiffuse(X, NaN, S)
% X: complex coherence of mixed (noisy) signa... |
github | ganlubbq/matlab_beam_doa-master | estimate_cdr_robust_unbiased.m | .m | matlab_beam_doa-master/cdr-demo/estimate_cdr_robust_unbiased.m | 1,614 | utf_8 | cd460a3538aae3a4bcb2f0eb44bbe582 | %ESTIMATE_CDR_ROBUST_UNBIASED
% Unbiased estimation of the Coherent-to-Diffuse Ratio (CDR) from the complex
% coherence of a mixed (noisy) signal, using knowledge of both signal and noise
% coherence. This is a variation of estimate_cdr_unbiased which shows better
% performance in practice. Equivalent to CDRprop2 in [1... |
github | ganlubbq/matlab_beam_doa-master | estimate_cdr_nodoa.m | .m | matlab_beam_doa-master/cdr-demo/estimate_cdr_nodoa.m | 1,389 | utf_8 | b12850a707e91ffd8c8be07b04f04121 | %ESTIMATE_CDR_NODOA
% Blind (DOA-independent), unbiased estimation of the Coherent-to-Diffuse Ratio (CDR)
% from the complex coherence of a mixed (noisy) signal. Equivalent to CDRprop3 in [1].
%
% CDR = estimate_cdr_nodoa(Cxx, Cnn)
% Cxx: complex coherence of mixed (noisy) signal
% Cnn: coherence of noise ... |
github | ganlubbq/matlab_beam_doa-master | estimate_cdr_unbiased.m | .m | matlab_beam_doa-master/cdr-demo/estimate_cdr_unbiased.m | 1,446 | utf_8 | 0c57df9c844aec6695d9f99e28e8f4c2 | %ESTIMATE_CDR_UNBIASED
% Unbiased estimation of the Coherent-to-Diffuse Ratio (CDR) from the complex
% coherence of a mixed (noisy) signal, using knowledge of both signal and noise
% coherence. Equivalent to CDRprop1 in [1].
%
% CDR = estimate_cdr_nodiffuse(X, N, S)
% X: complex coherence of mixed (noisy) signal
... |
github | ganlubbq/matlab_beam_doa-master | estimate_delay_gcc_phat.m | .m | matlab_beam_doa-master/cdr-demo/lib/estimate_delay_gcc_phat.m | 787 | utf_8 | 2e7e08ecee1ab7c234ed1462ea89eab0 | %ESTIMATE_DELAY_GCC_PHAT Delay estimation using GCC-PHAT.
%
% Estimates the delay between two signals using the GCC-PHAT method.
% Returns the delay
% in samples.
%
% Andreas Schwarz (andreas.schwarz@fau.de), Dec. 2014
function shift = estimate_delay_gcc_phat(x1,x2)
factor = 20; % oversampling (padding) factor to inc... |
github | ganlubbq/matlab_beam_doa-master | spectral_subtraction.m | .m | matlab_beam_doa-master/cdr-demo/lib/spectral_subtraction.m | 867 | utf_8 | e1c1554ffadfa5ec0f73ab2c6b196574 | %SPECTRAL_SUBTRACTION Compute spectral subtraction weights.
%
% weights = spectral_subtraction(SNR,alpha,beta,mu,Gmin)
%
% alpha = 1; beta = 1; % power subtraction
% alpha = 2; beta = 0.5; % magnitude subtraction
% alpha = 2; beta = 1; % Wiener filter
% mu: noise overestimation
% Gmin: gain floor
%
% Andr... |
github | rushilanirudh/tsrvf-master | findP2_from_P1_A.m | .m | tsrvf-master/grassmann/GrassmannCodes/Grassmann_Projection/findP2_from_P1_A.m | 698 | utf_8 | 61a0e4fae53930bf5f4d76f94a18c24e | % Feb 21-10
% Given point P1 and velocity A, find point P2 reached in unit time by
% following a geodesic starting at P1 and having velocity A
% input: P1,A,U (can be tensors) where and Q is the identity component on
% Projection group
% P2 = findP2_from_P1_A(P1, A, U, t)
% inputs can be a batch of matrices in te... |
github | rushilanirudh/tsrvf-master | findVelocity_A_QtoP.m | .m | tsrvf-master/grassmann/GrassmannCodes/Grassmann_Projection/findVelocity_A_QtoP.m | 1,232 | utf_8 | 067b8876f6584a30de623c1d8b27cb2b | % Feb 24-10
% find velocity X, from Q to given P
function [A,X] = findVelocity_A_QtoP(Q,P)
B = Q - P;
[W,D] = eig(B);
W = real(W);
D = real(D);
eig_values = diag(D);
temp = abs(eig_values);
temp(temp<1e-5)=0;
eig_values(temp==0)=0;
% D must be in the format diag(a,-a,b,-b,.,0,0..);
[sEig,Ind]=sort(eig_values,'desc... |
github | rushilanirudh/tsrvf-master | extrinsicMean.m | .m | tsrvf-master/grassmann/GrassmannCodes/Grassmann_Projection/extrinsicMean.m | 291 | utf_8 | 65bf88621fcb646d72b0f0960bacbfc7 | % Feb 21-10
% compute the exterinsic mean of a set of projection matrix
function Pmean = extrinsicMean(Pt)
% Pt = tensor, each 2D matrix is a P
n = size(Pt,1);
Q = [eye(2) ,zeros(2,n-2);zeros(n-2,2) zeros(n-2)];
G = sum(Pt,3)/size(Pt,3);
[U,S,V] = svd(G);
Pmean = U * Q * U'; |
github | rushilanirudh/tsrvf-master | subspace2image.m | .m | tsrvf-master/grassmann/GrassmannCodes/Grassmann_Projection/subspace2image.m | 669 | utf_8 | 8ad9c171d0614298f5563d1d3ce97ac1 | % Feb 22-10
% map from subspace to landmark space by calculating the afffine matrix
function L = subspace2image(P, imgSpace)
% L = subspace2image(P, L_part, RigidIndex)
% P is the projection matrix which represents a subspace on Grassmann
% L_part is the landmarks we already have on the image (with RigidIndex a... |
github | rushilanirudh/tsrvf-master | grassmannRep.m | .m | tsrvf-master/grassmann/GrassmannCodes/Grassmann_Projection/grassmannRep.m | 328 | utf_8 | 78f0b2b39fdd798b9a06b23763e13be0 | % Feb 17-10
% find the procrustes representation for landmark matrix on Grassmann
% Manifold
%[out, Rot, trans] = grassmannRep(L)
% out*Rot+repmat(trans,size(out,1),1) = L;
function [out, Rot, trans] = grassmannRep(L)
L_mz = L - repmat(mean(L),length(L),1);
[U,S,V] = svd(L_mz,'econ');
out = U;
Rot = S*V';
trans = ... |
github | rushilanirudh/tsrvf-master | findVelocity_A_P1toP2.m | .m | tsrvf-master/grassmann/GrassmannCodes/Grassmann_Projection/findVelocity_A_P1toP2.m | 426 | utf_8 | 3f04e7c6dfe6fd698a7d6780c1cf5f34 | % Feb 23-10
% compute velocity matrix, A, between two subspace having projeciton
% matrices ans subspaces representation
% [A,X] = findVelocity_A_P1toP2(P1, P2, Q)
function [A,X] = findVelocity_A_P1toP2(P1, P2)
% P1 = U.Q.U'
n = size(P1,1);
Q = [eye(2), zeros(2,n-2);zeros(n-2,2) zeros(n-2)]; % Q is fixed for the enti... |
github | rushilanirudh/tsrvf-master | phi_inv.m | .m | tsrvf-master/grassmann/GrassmannCodes/Grassmann_Projection/phi_inv.m | 551 | utf_8 | bc4522aa49b585dd247618ef46542f49 | % Feb 24-10
% function phi: SO(3)-->P
% phi(U) = UQU'
% [U,Y] = phi_inv(P)
function [U,Y] = phi_inv(P)
% P = U.Q.U'
n = size(P,1);
if (0)
colSpc = rref(P);
tmp = eye(size(P));
flag = (colSpc == repmat(tmp(:,1),1,size(P,2)));
ind1 = find(sum(flag,1)==size(P,2));
flag = (colSpc == repmat(tmp(:,... |
github | jasnap/philogenetic_trees-master | tree_plot.m | .m | philogenetic_trees-master/tree_plot.m | 1,449 | utf_8 | f9d92d08126da9a08bd6ba451697a845 | %-------------- tree_plot -----------
% This function plots the phylogenetic tree calculated by BrB algorithm
%
% Input:
% optimal_model - Optimal model calculated by BrB
% u_model - Optimal model with negative internal nodes
%
function tree_plot(optimal_model, u_model, score, name_matrix)
optimal_model(1) = 1;
n = ... |
github | jasnap/philogenetic_trees-master | ExhaustiveSearch.m | .m | philogenetic_trees-master/ExhaustiveSearch.m | 1,007 | utf_8 | 3cf8a4af3bbbf983bfe41f9e3b293805 | %------------ ExhaustiveSearch -----------
% This function for searching trees with Exhaustive search method
%
% Input:
% set_of_seq - Matrix that contains all input sequences
% Output:
% optimal_score - Best score of all trees
% optimal_model - Tree model for the best score
function ... |
github | jasnap/philogenetic_trees-master | get_row_count.m | .m | philogenetic_trees-master/get_row_count.m | 375 | utf_8 | ae75b810d63d2fcfbf6f04ab242fa604 | %------- get_row_count --------
% This function calculates the number of all possible trees for a set of
% sequences
%
% Input:
% n - Number of input sequences
% Output:
% number - Number of possible trees
function number = get_row_count(n)
if(n > 2)
number = 1 + factd(2*(n-1)-5) + factd(2*... |
github | jasnap/philogenetic_trees-master | BrB.m | .m | philogenetic_trees-master/BrB.m | 1,472 | utf_8 | c1e27af46d4578537280d6cbf4b75483 | %----------------- BrB --------------------
% This function implements Branch and bound optimization of Maximum Parsimony
%
% Input:
% set_of_seq - Set of data with important information about sequences
% Output:
% optimal_score - Optimal score calculated
% optimal_model - Model with the optimal score
%
function [... |
github | jasnap/philogenetic_trees-master | get_row_odd.m | .m | philogenetic_trees-master/get_row_odd.m | 286 | utf_8 | 48629e52362a91d56b722393ce6f75a5 | %----------- get_row_odd-------------
% Function that calculates odd rows
%
% Input:
% n - Number of input sequences
% Output:
% odd - Number of odd sequences
function odd = get_row_odd(n)
n = n - 3;
odd = 1;
for i = 1:n
odd = odd + 2;
end
end
|
github | jasnap/philogenetic_trees-master | P_BrB.m | .m | philogenetic_trees-master/P_BrB.m | 2,028 | utf_8 | c89894b13c80b76fa5cae2cbadb0c56b | %---------------- P_BrB ------------------------
% This function implements parallel Branch and bound on CPU
%
% Input:
% set_of_seq - Set of sequences for calculating trees
% Output:
% optimal_score - Calculated optimal score
% optimal_model - Model with the calculated optimal score
%
function [optimal_score, opt... |
github | jasnap/philogenetic_trees-master | gen_complete_tree.m | .m | philogenetic_trees-master/gen_complete_tree.m | 606 | utf_8 | 4714861748185a1d891ee1ade3718036 | %------------ gen_complete_tree(previous, last)----------------------
%
% This function generates a complete tree based on inputs previous and
% last
%
% Input:
% previous - Previous complete tree that was scored
% last - Last possible complete tree that can be derived from given
% partial tree
% ... |
github | jasnap/philogenetic_trees-master | treeModelGen.m | .m | philogenetic_trees-master/treeModelGen.m | 634 | utf_8 | 74d424c7a9e1d7838a8a7fb47aa8d945 | %------------- treeModelGen ---------------
% This function generates a tree model based on the ID of the tree
%
% Input:
% id - Identification number of the tree
% Output:
% model - Generated model of the given tree id
function model = treeModelGen(id)
model(1, 1) = 1;
model(1, 2) = 2;
internal_node =... |
github | jasnap/philogenetic_trees-master | partial_treeID.m | .m | philogenetic_trees-master/partial_treeID.m | 1,250 | utf_8 | 2c82615bc9370b8988ea86488e1ff2fc | %------------ partial_treeID(n)--------------------------
%
% This function generates all partial trees for given number of sequences
%
% Input:
% n - Number of input sequences
% Output:
% matrix - Matrix containing all possible partial trees
function matrix = partial_treeID(n)
init_id = zeros(1, 2)... |
github | jasnap/philogenetic_trees-master | fasta_rd.m | .m | philogenetic_trees-master/fasta_rd.m | 738 | utf_8 | 3b24e4b98f2f7b53273b2e557af2ef30 | %------------- fasta_rd --------------
% This function preprocesses input fasta sequences
%
% Input:
% f - Read fasta file
% Output:
% data - Data readable for the BrB function
%
function data = fasta_rd(f)
SeqsMultiAligned = multialign(f);
[row, col] = size(SeqsMultiAligned);
for i = 1:row
te... |
github | jasnap/philogenetic_trees-master | FitchScoring.m | .m | philogenetic_trees-master/FitchScoring.m | 1,541 | utf_8 | 4cbf23b1022193d73d68742faf25bcb1 | % -------------- FitchScoring------------
% This function calculates score of a tree using Fitch scoring algorithm
%
% Input:
% id - Id of the tree it is scoring
% set_of_seq - Matrix of input sequences
% Output:
% out_model - Model of the output tree
% out_score - Calculated score
function [... |
github | jasnap/philogenetic_trees-master | treeID.m | .m | philogenetic_trees-master/treeID.m | 1,093 | utf_8 | cb43795b9ad99831e878df5c0e9a999a | %--------------- treeID ---------------
% This function generates all possible trees
%
% Input:
% n - Number of input sequences
% Output
% output - matrix with all possible trees and theis id numbers
function output = treeID(n)
row = get_row_count(n);
output = zeros(row, n);
% set 3rd column to 1
... |
github | jasnap/philogenetic_trees-master | tree_type.m | .m | philogenetic_trees-master/tree_type.m | 569 | utf_8 | a839cd73ba2c11c30f1a6c388df53de8 | %---------------- tree_type--------------
% This function finds if a tree is incomplete, partial or complete
%
% Input:
% tree - Id number of the tree
% Output:
% type - Type of the tree
%
% 0 - incomplete
% 1 - partial
% 2 - complete
function type = tree_type(tree)
num_of_zeros = sum(tree(:) == 0) - 2;
... |
github | jasnap/philogenetic_trees-master | non_inf_sites.m | .m | philogenetic_trees-master/non_inf_sites.m | 1,155 | utf_8 | 53c5b547770e3cb7e5707f484249c2d1 | %----------- non_inf_sites --------------
% This function removes all noninformative sites in a sequence
%
% Input:
% set_of_seq - Matrix of input sequences
% fact - Similarity factor
% Output:
% output - Matrix with all sequences where the non informative sites are removed
function output = non_inf_sites(set... |
github | jasnap/philogenetic_trees-master | Merge.m | .m | philogenetic_trees-master/Merge.m | 646 | utf_8 | 59a96d3097ae0682946b7bb184389b34 | %-------------- Merge -------------
% This function merges child nodes with parent nodes, and returns the parent
% node and the calculated score
%
% Input:
% seq1 - First child node sequence
% seq2 - Second child node sequence
% Output:
% score - Score of the merging
% out_seq - Merged parent sequence
function [s... |
github | jasnap/philogenetic_trees-master | nwk.m | .m | philogenetic_trees-master/nwk.m | 1,679 | utf_8 | 13c0c9ecbc7d66f3706e0a4234d1e365 | %------------- nwk(tree)---------
% This function returns a Newick file format of the tree, and draws a
% phylogenetic tree
%
% Input:
% s_model - Tree model that had been scored
% u_model - TreeID of the model that had been scored
% Output:
% tree_matrix - A matrix for generating phytree object... |
github | jasnap/philogenetic_trees-master | last_tree.m | .m | philogenetic_trees-master/last_tree.m | 299 | utf_8 | 6c8e36d8808d4d242467d1df7c013aa0 | %-------------- last_tree --------------
% This function calculates the last possible tree
%
% Input:
% n - Number of sequences
% Output:
% tree - Last possible tree
%
function tree = last_tree(n)
tree = [zeros(1, 2) 1];
for i = 3 : n - 1
tree(i + 1) = tree(i) + 2;
end
end
|
github | jasnap/philogenetic_trees-master | children.m | .m | philogenetic_trees-master/children.m | 411 | utf_8 | 619778fd59997345f2c3afac735fa25b | %---------------- children ----------
% Function for finding all children nodes
%
% Input:
% model - Tree model
% node - Parent node for which it's finding
% Output:
% child1 - First child node
% child2 - Second child node
function [child1, child2] = children(model,node)
o... |
github | kranthibalusu/Crystal-plasticity--master | distSet1Set2V2.m | .m | Crystal-plasticity--master/ProfileAnalysis/distSet1Set2V2.m | 1,430 | utf_8 | 3610325aa9f2a44d13bdf7758e8b8d1c | %function to determine the index of point in set 1
%closest to every point in set 2
%also compare one other parsameter
function [idSet, distSet] = distSet1Set2V2(set1,set2, set12, set22, par1by2)
% set1 and set12 are expected to be of the same size, describing the same thing
%par1by2 pareameter describes the ... |
github | kranthibalusu/Crystal-plasticity--master | distSet1Set2.m | .m | Crystal-plasticity--master/ProfileAnalysis/distSet1Set2.m | 1,039 | utf_8 | bae3b74d4651545121c99334db5b5786 | %function to determine the index of point in set 1
%closest to every point in set 2
function [idSet, distSet] = distSet1Set2(set1,set2)
%size of set1
set1S=size(set1,1);
%size of set2
set2S=size(set2,1);
idDiff = set1S - set2S;
%idSet allocatoipn
idSet = zeros(set2S,1);
distSet = zeros(set2S,1)... |
github | kranthibalusu/Crystal-plasticity--master | kraFilt.m | .m | Crystal-plasticity--master/ProfileAnalysis/kraFilt.m | 703 | utf_8 | b0c4a099dbb5ca3fc36db641b4747040 | % my own filter
%not implemented yet
%1) identify values lying outside a specif range
%2) replace them by a value average of its sorrounding.
function [imageFilt]=kraFilt(image,stds)
% image shoudl be having only one channel
%stds is the numbed of std deviations that have to be removed
%from image
[sizeC... |
github | kranthibalusu/Crystal-plasticity--master | IPFRDPlot.m | .m | Crystal-plasticity--master/ProfileAnalysis/IPFRDPlot.m | 2,906 | utf_8 | db565dd2b718e1a74d63a00d92b7f6c8 | % function to plot points on the IPF
function [plotnameFig] = IPFRDPlot(points,idx,labels)
%labels - array with labels for points
noPoints=size(points,1);
if ~exist('labels','var')
% third parameter does not exist, so default it to something
labels = [1:noPoints]';
end
%% RD location dete... |
github | lowrank/pat-master | lbfgsb_c.m | .m | pat-master/lbfgsc/Matlab/lbfgsb_c.m | 10,263 | utf_8 | a96e46dd0b500bad16bc460eed316eb1 | function [x,f,info] = lbfgsb_c( fcn, l, u, opts )
% x = lbfgsb( fcn, l, u )
% uses the lbfgsb v.3.0 library (fortran files must be installed;
% see compile_mex.m ) which is the L-BFGS-B algorithm.
% The algorithm is similar to the L-BFGS quasi-Newton algorithm,
% but also handles bound constraints via an ac... |
github | EvanMu96/nnPiCar-master | controlPad.m | .m | nnPiCar-master/server/controlPad.m | 5,614 | utf_8 | adadd6fc95f8d65c0c6dce342d9b689c | function varargout = controlPad(varargin)
% CONTROLPAD MATLAB code for controlPad.fig
% CONTROLPAD, by itself, creates a new CONTROLPAD or raises the existing
% singleton*.
%
% H = CONTROLPAD returns the handle to a new CONTROLPAD or the handle to
% the existing singleton*.
%
% CONTROLPAD('CALL... |
github | mszinte/pRF_gazeMod_testCode-master | kde2d.m | .m | pRF_gazeMod_testCode-master/stats/kde2d.m | 7,506 | utf_8 | 129d5d2a0461b7ae38b706c421cbb8a3 | function [bandwidth,density,X,Y]=kde2d(data,MIN_XY,MAX_XY,n)
% fast and accurate state-of-the-art
% bivariate kernel density estimator
% with diagonal bandwidth matrix.
% The kernel is assumed to be Gaussian.
% The two bandwidth parameters are
% chosen optimally without ever
% using/assuming a parametric model f... |
github | adeelz92/Machine-Learning-Coursera-master | submit.m | .m | Machine-Learning-Coursera-master/machine-learning-ex2/machine-learning-ex2/ex2/submit.m | 1,605 | utf_8 | 9b63d386e9bd7bcca66b1a3d2fa37579 | function submit()
addpath('./lib');
conf.assignmentSlug = 'logistic-regression';
conf.itemName = 'Logistic Regression';
conf.partArrays = { ...
{ ...
'1', ...
{ 'sigmoid.m' }, ...
'Sigmoid Function', ...
}, ...
{ ...
'2', ...
{ 'costFunction.m' }, ...
'Logistic R... |
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