Made HopTestPts and HopTests user adjustable parameters.

Author: MJWester1

MATLAB/+smi_cluster/@ClusterInterface/ClusterInterface.m

@@ -43,7 +43,7 @@
    % Called by singleConditionDriver.
    singleCondition(pathname, files, algorithm_range, E_range, ...
                    minPts_range, Pixel2nm, base_name, A_ROI,  ...
-                   doHopkins, doSigmaActual, Alpha)
+                   doHopkins, doSigmaActual, Alpha, SC)
 
    % Called by Example_plotROIDriver.
    plotROIDriver(PixelSize, options, start_datadir, SaveDir, IncludeCell)

MATLAB/+smi_cluster/@ClusterInterface/singleCondition.m

@@ -1,6 +1,6 @@
 function singleCondition(pathname, files, algorithm_range, E_range, ...
                          minPts_range, Pixel2nm, base_name, A_ROI,  ...
-                         doHopkins, doSigmaActual, Alpha)
+                         doHopkins, doSigmaActual, Alpha, SC)
 % ---------- Statistics for a single condition
 % Perform cluster analysis for comparison of experimental conditions.  This is
 % useful for performing parameter studies, especially over a range of E's
@@ -23,7 +23,8 @@ function singleCondition(pathname, files, algorithm_range, E_range, ...
 %                      avoid crashes due to lack of memory
 %    Alpha             [DEFAULT = 2] ratio of local density / overall density
 %                      for Voronoi clustering
-%                     
+%    SC                StatisticsClustering object containing certain
+%                      parameters such as HopTestPts and HopTests
 %
 % OUTPUTS:
 %    A variety of plots are produced and are placed in a subdirectory of
@@ -52,8 +53,10 @@ function singleCondition(pathname, files, algorithm_range, E_range, ...
    end
 
    c  = smi_cluster.Clustering();
-   SC = smi_cluster.StatisticsClustering();
    PC = smi_cluster.PairCorrelation();
+   if ~exist('SC', 'var')
+      SC = smi_cluster.StatisticsClustering();
+   end
 
    base_name_save = base_name;
    if ~startsWith(base_name, 'ALL')

MATLAB/+smi_cluster/@StatisticsClustering/StatisticsClustering.m

@@ -57,6 +57,8 @@
    CSV = false;           % If true, produce a CSV file of the data
 
    % Properties below are used by various routines.
+   HopTestPts    =  10;   % Number of test points to compute Hopkins' statistic
+   HopTests      =1000;   % Number of tests to run to produce a Hopkins' stat.
    Rate          =  20;   % Sampling rate for statistical functions
    Dendro_cutoff =  50;   % Cluster cutoff for Dendrogram analysis (nm)
    Ripley_cutoff = 200;   % Ripley distance cutoff (nm)

MATLAB/+smi_cluster/@StatisticsClustering/hopkins.m

@@ -10,6 +10,8 @@
 %       BaseName        name to identify saved plots, which will have various
 %                       descriptive suffixes attached
 %       Rate            [ 20]    sampling rate for statistical functions
+%       HopTestPts      number of Hopkins' statistic test points
+%       HopTests        number of tests to run to produce a Hopkins' statistic
 %    particle_types   cell array of particle types (names)
 %                     e.g., particle_types = {'5', '10'};
 %                         are of the form {[n1 x 1], [n2 x 1]}
@@ -76,8 +78,10 @@
    D_nm = -1;
 end
 
-test = 5;        % The number of test points.
-ntests = 1000;   % The number of Hopkins statistics to use.
+%test = 5;        % The number of test points.
+%ntests = 1000;   % The number of Hopkins statistics to use.
+test = obj.HopTestPts;   % The number of test points.
+ntests = obj.HopTests;   % The number of Hopkins statistics to use.
 bins = 100;      % The number of bins for the probability graphs.
 fitting = false; % Gaussian fitting of the data.
 

MATLAB/+smi_cluster/@StatisticsClustering/hopkins_ROIcombined.m

@@ -10,6 +10,8 @@
 %                       descriptive suffixes attached
 %       Xlim            []       x-axis limits if defined
 %       Ylim            []       y-axis limits if defined
+%       HopTestPts      number of Hopkins' statistic test points
+%       HopTests        number of tests to run to produce a Hopkins' statistic
 %    n_ROIs      number of ROIs to combine
 %    ROIs        n_ROIs cell array containing the following fields (nm):
 %       ROI      ROI limits in the form
@@ -24,8 +26,10 @@
 
 base_name = obj.BaseName;
 
-test = 5;        % The number of test points.
-ntests = 1000;   % The number of Hopkins statistics to use.
+%test = 5;        % The number of test points.
+%ntests = 1000;   % The number of Hopkins statistics to use.
+test = obj.HopTestPts;   % The number of test points.
+ntests = obj.HopTests;   % The number of Hopkins statistics to use.
 
 % Dimension (2D or 3D)
 dim = 2;

MATLAB/examples/singleConditionDriver.m

@@ -132,9 +132,14 @@
 Alpha = 2;
 
 CI = smi_cluster.ClusterInterface();
-%Alpha = 3;
+SC = smi_cluster.StatisticsClustering();
+C.HopTestPts = 10;
+C.HopTests = 1000;
+
+%Alpha = 2;
 CI.singleCondition(pathname, files, algorithm_range, E_range, minPts_range,...
-                   Pixel2nm, base_name, A_ROI, doHopkins, doSigmaActual, Alpha);
+                   Pixel2nm, base_name, A_ROI, doHopkins, doSigmaActual,   ...
+                   Alpha, SC);
 
 %Alpha = 3;
 %CI.singleCondition(pathname, files, algorithm_range, E_range, minPts_range,...