Matlab Scripts

function [g6B,bin] = binData(g6C,binMax,bins)
% g6C:       Matrix containing the g6 values output from g6_struct
% binMax:    The maximum binning value
% bins:      The number of bins to take
%Returns
% g6B:       The binned g6 data
% bin:       The bin values of g6B

function [neighbours,locations] = findNN(pos,X,Y,radius)

function [ang] = getAngle(P1,P2)

function [EKc,EKi] = kinSpec(wfc_str,dimSize,dx,mass,qSpec,init,incr,fin)
%   wfc_str is the string of the wavefunction name. For time-ev this is
%       usually wfc_ev; wfc_0_const or wfc_0_ramp for ground-states
%   dimSize is a vector with the dimenion size, so that the wavefunctions
%       can be appropriately reshaped when loaded
%   dx is the increment along x. dx==dy
%   qSpec enables classical (0) or quantum (1) variant of energy spectra
%   init,incr,fin are the loop values for specifiying the range of the data

function [vorts] = loadVtx(start, step, fin, lostCheck)
%   start step and fin are the initial dataset, step size, and final
%   dataset to load for the vortex postions
%   lostCheck turns on the ability to test for vortex losses and ensure
%   that these vortices do not contribute to the dataset.
%   The Data should be in the format of [X Y Sign UID IsLost] 

[nn,idx] = findNN(pos,X,Y,radius); %find number of neighbours and indices of neighbours for (X,Y)
% pos:       Defines the location to calculate the orientational order parameter
% X,Y:       Vector of entire X,Y range of points
% radius:    Radius over which to determine neighbouring points
%Returns
% psi6_pos:  The value of orientational order psi_6 at position pos
% nn:        Number of nearest neighbours

function [S] = uniqPairIdx_precalc(R,psi6p)
% R:        Vectors of R=[X Y] values for points.
% psi6p:    Orientational order values defined over the range of points
%Return:
% S:        Struct of orientational corder values cor0,cor1 and distance
%            between elements

function [p6cp6, area, avg_area, num_edges, var]=voronoi2dCellColour(x,y,radius,edgeCol,dx,colScheme)
%vorCellColour 
%x,y: are the locations of the sites
%radius: is the area over which to perform the triangulation. This should
%     avoid too large values to ensure the traingulation does not run off to
%     infinity
%edgeCol: Defines the Voronoi diagram edge colours for edge indexed pair. edgeCol<0 is 
%     red, edgeCol==0 is black, edgeCol>0 is white
%dx: this is the increment size of the data
%colScheme: defines the colouring scheme, 1 for orientational correlations on the site 
%     with 6-fold symmetry, 0 for cell area 
% Returns:  p6cp6 = local values of correlations
%           area = cell areas
%           avg_area = average area of cells
%           num_edges = cell edges count
%           var = variance

x=linspace(-1,1,20); y=x;
 radius = 0.5; dx = 1; q = ones(length(x)*length(y),1);
 voronoi2dCellColour(kron(x',ones(length(y),1)),kron(ones(length(x),1),y'),0.75,zeros(length(x)^2,1),1,0);

function [vorts] = vtxTrajectory(start, step, fin, initial,threeD, dx, dimSize, dt)
%   Start step and fin are the initial, stepsize and final datasets
%   initial indicates if you wish to highlight the 
%   threeD also plots aspacetime (XYT) diagram in 3D.
%   dx is the stepsize along one dimension and assumes the same over x,y
%   dimSize is the length of the dimensions, and assumes x==y
%   dt is the time increment for the spacetime diagram.

function [h,DefCount] = defectTriangulation(x, y, dx, dimSize, plotit, radius)
%   radius defines the distance from 0,0, for which the defects will be
%considered. This can be used to avoid defects that arise naturally from
%the edge of the triangulation
%   h is a handle for generated plot
%   DefCount is a vector of the total number of defects counted for each
%   type with the index representing the number of connected edges

function [g6C] = g6_struct(X,Y,rad)
% X,Y:   Vectors of x,y values for points.
% rad:   Radius in which to examine for neighbouring points.
%Return:
% g6C:   Matrix of g6 values and parameters

function latexFig(gca, fontSize, cbar, xtick, ytick, xticklabels, yticklabels)
%   {x,y}tick can be used to overwrite the automatically defined tick
%   locations
%   {x,y}ticklabels overwrites the labels at the positions defined by
%   {x,y}tick values
%   This assumes that the Latin Modern fonts are installed
%   Fontsize sets the size of the text
%   cbar enables the colorbar if needed

pcolor(rand(10,10));
latexFig(gca, 30, 1, 2:2:10, 1:2:10, {'a1','b1','c1','d1','e1'}, {'a2','b2','c2','d2','e2'})

function [varargout] = quKineticSpec(Psir,m,dx,q,avg,iii)

% Ek = quKineticSpec(Psir,m,dx,q,avg,iii), 
% Psir N-dim wavefunction in r space with grid spacing dx and mass m
% q = include phase for quantum spectrum, 1=yes,0=no; 
% avg = perform angled average. Likely always want this to be yes, 1
% iii output index for naming the figure files. Useful when looped with
% kinSpec script

function [] = velField(wfc0,dx,m,incr,x,y,normed, lims)
% dx is the increment along x, and assumes dx==dy
% m is the mass of the atomic species
% incr is the increment over which to calculate field direction. Too low
%     and it may be very dense, too high and very sparse. Start at 1, and
%     increase until happy
% x,y are the grid spacings along the x and y axis
% normed specifies whether to normalise the vector directions. 1 if yes, 0 otherwise
% lims is [xMin xMax yMin yMax]. Hides the edge garbage. Otherwise, []

function [] = VtxCorr(dataSteps, dx, dimSize, radius, printIt, edgeCol)
%
%dataSteps: The range of values to be plotted (e.g. [1e3 1e4 5e6])
%dx:        this is the spatial increment size of the data
%dimSize:   The number of elements along one dimension. Used to calculate
%               max and min spatial values. Assumes x==y
%radius:    defines the bounded region to calculate the Voronoi diagram and all 
%               quantities. Useful to avoid cells tending to infinity.
%               Assumes a circularly symmetric dataset.
%printIt:   1 if plots are to be saved, 0 otherwise.
%edgeCol:   Defines the Voronoi diagram edge colours for edge indexed pair. 
%               edgeCol==0 is black, edgeCol>0 is white
% Returns
%%Testcase: Generate diagrams for data at steps 1e3 1e4 and 1e5
% dx=1e-4; dimSize=1024; radius = 200*dx; printIt = 0; edgeCol = 1;
% VtxCorr([1e3 1e4 1e5], dx, dimSize, radius, printIt, edgeCol)