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Added updates to Matlab code to use anaconda 3 rather than standalone python. Allows for ease of updating packages instead of using older python Also requires update to DeBaCl which can be found here CoAxLab/DeBaCl#69
1 parent f36f6e9 commit bdeee6b

9 files changed

Lines changed: 282 additions & 224 deletions

‎Cluster analysis code/For PC/BeforeStartingAnalyses.m‎

Lines changed: 91 additions & 90 deletions
Original file line numberDiff line numberDiff line change
@@ -1,91 +1,92 @@
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%This function provides some preliminary information about the cluster analysis paramters and the dataset
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function [AxisLimits,pDeBaCl]=BeforeStartingAnalyses(DatasetName,MinClusterSizeHDBSCAN,MinSamplesHDBSCAN,hdbscanPersistencyThreshold,...
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hdbscanProbabilityThreshold,kDeBaCl,gammaDeBaCl,MassLengthDeBaClThreshold,...
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NNNforKNN,PrefactorDeBaClDensityThreshold,hdbscanAnalysisTwoTimes,PrefactForPersistancy,IgnorePersisInDeBaClanalysis,...
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IgnorehdbscanProbabilityThresholdAfterKNNrelabeling)
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X=importdata(DatasetName);
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g=figure(1);
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if size(X,2)==2
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plot(X(:,1),X(:,2),'k.','MarkerSize',2);
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pDeBaCl=2;%Dataset is 2D
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else
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plot3(X(:,1),X(:,2),X(:,3),'k.','MarkerSize',2);
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pDeBaCl=3;%Dataset is 3D
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end
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xlabel('X (nm)')
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ylabel('Y (nm)')
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zlabel('Z (nm)')
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AxisLimits=[min(X(:,1)) max(X(:,1));...
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min(X(:,2)) max(X(:,2));...
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min(X(:,3)) max(X(:,3))];
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xlim([AxisLimits(1,1) AxisLimits(1,2)])
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ylim([AxisLimits(2,1) AxisLimits(2,2)])
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zlim([AxisLimits(3,1) AxisLimits(3,2)])
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Title=({'Original Dataset';['Number of atoms in the dataset is ' num2str(size(X,1))]});
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title(Title)
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set(gcf,'Units','Normalized','OuterPosition',[0.25, 0.07, .65, .92])
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saveas(g,'1_OriginalDatat.tiff')
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%saveas(g,'1_OriginalDatat.fig')
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%close(g)
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fid1 = fopen('0_ParamtersUsedForClusterAnalyses.txt','wt');
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fprintf(fid1, '%s\t', ' DatasetName:');
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fprintf(fid1, '%s\n', DatasetName);
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fprintf(fid1, '%s', ' MinClusterSizeHDBSCAN=');
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fprintf(fid1, '%i\n', MinClusterSizeHDBSCAN);
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fprintf(fid1, '%s', ' MinSamplesHDBSCAN=');
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fprintf(fid1, '%i\n', MinSamplesHDBSCAN);
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fprintf(fid1, '%s', ' hdbscanAnalysisTwoTimes=');
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if hdbscanAnalysisTwoTimes
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fprintf(fid1, '%s\n', 'true');
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else
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fprintf(fid1, '%s\n', 'false');
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end
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fprintf(fid1, '%s', ' PrefactForPersistancy=');
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fprintf(fid1, '%i\n', PrefactForPersistancy);
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fprintf(fid1, '%s', ' hdbscanPersistencyThreshold=');
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fprintf(fid1, '%f\n', hdbscanPersistencyThreshold);
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fprintf(fid1, '%s', ' hdbscanProbabilityThreshold=');
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fprintf(fid1, '%f\n', hdbscanProbabilityThreshold);
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% fprintf(fid1, '%s', ' pDeBaCl=');
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% fprintf(fid1, '%i\n', pDeBaCl);
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fprintf(fid1, '%s', ' kDeBaCl=');
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fprintf(fid1, '%i\n', kDeBaCl);
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fprintf(fid1, '%s', ' gammaDeBaCl=');
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fprintf(fid1, '%i\n', gammaDeBaCl);
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fprintf(fid1, '%s', ' IgnorePersisInDeBaClanalysis=');
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if IgnorePersisInDeBaClanalysis
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fprintf(fid1, '%s\n', 'true');
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else
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fprintf(fid1, '%s\n', 'false');
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end
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fprintf(fid1, '%s', ' MassLengthDeBaClThreshold=');
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fprintf(fid1, '%f\n', MassLengthDeBaClThreshold);
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fprintf(fid1, '%s', ' NNNforKNN=');
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fprintf(fid1, '%i\n', NNNforKNN);
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fprintf(fid1, '%s', 'PrefactorDeBaClDensityThreshold=');
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fprintf(fid1, '%f', PrefactorDeBaClDensityThreshold);
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if IgnorehdbscanProbabilityThresholdAfterKNNrelabeling
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fprintf(fid1, '%s','IgnorehdbscanProbabilityThresholdAfterKNNrelabeling=true');
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else
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fprintf(fid1, '%s','IgnorehdbscanProbabilityThresholdAfterKNNrelabeling=false');
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end
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fclose(fid1);
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1+
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%This function provides some preliminary information about the cluster analysis paramters and the dataset
3+
function [AxisLimits,pDeBaCl]=BeforeStartingAnalyses(DatasetName,MinClusterSizeHDBSCAN,MinSamplesHDBSCAN,hdbscanPersistencyThreshold,...
4+
hdbscanProbabilityThreshold,kDeBaCl,gammaDeBaCl,MassLengthDeBaClThreshold,...
5+
NNNforKNN,PrefactorDeBaClDensityThreshold,hdbscanAnalysisTwoTimes,PrefactForPersistancy,IgnorePersisInDeBaClanalysis,...
6+
IgnorehdbscanProbabilityThresholdAfterKNNrelabeling)
7+
8+
X=importdata(DatasetName);
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g=figure(1);
10+
if size(X,2)==2
11+
plot(X(:,1),X(:,2),'k.','MarkerSize',2);
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pDeBaCl=2;%Dataset is 2D
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else
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plot3(X(:,1),X(:,2),X(:,3),'k.','MarkerSize',2);
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pDeBaCl=3;%Dataset is 3D
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end
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xlabel('X (nm)')
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ylabel('Y (nm)')
19+
zlabel('Z (nm)')
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AxisLimits=[min(X(:,1)) max(X(:,1));...
21+
min(X(:,2)) max(X(:,2));...
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min(X(:,3)) max(X(:,3))];
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xlim([AxisLimits(1,1) AxisLimits(1,2)])
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ylim([AxisLimits(2,1) AxisLimits(2,2)])
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zlim([AxisLimits(3,1) AxisLimits(3,2)])
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Title=({'Original Dataset';['Number of atoms in the dataset is ' num2str(size(X,1))]});
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title(Title)
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set(gcf,'Units','Normalized','OuterPosition',[0.25, 0.07, .65, .92])
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saveas(g,'1_OriginalDatat.tiff')
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%saveas(g,'1_OriginalDatat.fig')
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%close(g)
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fid1 = fopen('0_ParamtersUsedForClusterAnalyses.txt','wt');
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fprintf(fid1, '%s\t', ' DatasetName:');
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fprintf(fid1, '%s\n', DatasetName);
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fprintf(fid1, '%s', ' MinClusterSizeHDBSCAN=');
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fprintf(fid1, '%i\n', MinClusterSizeHDBSCAN);
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fprintf(fid1, '%s', ' MinSamplesHDBSCAN=');
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fprintf(fid1, '%i\n', MinSamplesHDBSCAN);
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fprintf(fid1, '%s', ' hdbscanAnalysisTwoTimes=');
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if hdbscanAnalysisTwoTimes
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fprintf(fid1, '%s\n', 'true');
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else
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fprintf(fid1, '%s\n', 'false');
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end
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51+
fprintf(fid1, '%s', ' PrefactForPersistancy=');
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fprintf(fid1, '%i\n', PrefactForPersistancy);
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54+
fprintf(fid1, '%s', ' hdbscanPersistencyThreshold=');
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fprintf(fid1, '%f\n', hdbscanPersistencyThreshold);
56+
57+
fprintf(fid1, '%s', ' hdbscanProbabilityThreshold=');
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fprintf(fid1, '%f\n', hdbscanProbabilityThreshold);
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60+
% fprintf(fid1, '%s', ' pDeBaCl=');
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% fprintf(fid1, '%i\n', pDeBaCl);
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fprintf(fid1, '%s', ' kDeBaCl=');
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fprintf(fid1, '%i\n', kDeBaCl);
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66+
fprintf(fid1, '%s', ' gammaDeBaCl=');
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fprintf(fid1, '%i\n', gammaDeBaCl);
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fprintf(fid1, '%s', ' IgnorePersisInDeBaClanalysis=');
70+
if IgnorePersisInDeBaClanalysis
71+
fprintf(fid1, '%s\n', 'true');
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else
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fprintf(fid1, '%s\n', 'false');
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end
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fprintf(fid1, '%s', ' MassLengthDeBaClThreshold=');
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fprintf(fid1, '%f\n', MassLengthDeBaClThreshold);
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79+
fprintf(fid1, '%s', ' NNNforKNN=');
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fprintf(fid1, '%i\n', NNNforKNN);
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fprintf(fid1, '%s', 'PrefactorDeBaClDensityThreshold=');
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fprintf(fid1, '%f', PrefactorDeBaClDensityThreshold);
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if IgnorehdbscanProbabilityThresholdAfterKNNrelabeling
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fprintf(fid1, '%s','IgnorehdbscanProbabilityThresholdAfterKNNrelabeling=true');
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else
88+
fprintf(fid1, '%s','IgnorehdbscanProbabilityThresholdAfterKNNrelabeling=false');
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end
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fclose(fid1);
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9192
end

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