add source for user manual

doc/matStats-manual/matlab/anova-iris/anovaIris.m

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+%ANOVAIRIS  Performs sample Anova on Iris data set
+%
+%   output = anovaIris(input)
+%
+%   Example
+%   anovaIris
+%
+%   See also
+%
+
+% ------
+% Author: David Legland
+% e-mail: [email protected]
+% Created: 2017-07-19,    using Matlab 9.1.0.441655 (R2016b)
+% Copyright 2017 INRA - Cepia Software Platform.
+
+% Analysis of variance on Fisher's iris
+iris = Table.read('fisherIris');
+anovaPL = Anova(iris('PetalLength'), iris('Species'));
+
+%% display fitted coefficients
+coefficients(anovaPL, 'Species')
+% ans = 
+%                   PetalLength
+% Setosa                  1.462
+% Versicolor               4.26
+% Virginica               5.552
+
+
+%% Display residuals
+
+plotResiduals(anovaPL);
+print(gcf, 'anova-irisPL-resids.png', '-dpng');
+
+%% Display residual by factor level
+
+figure; set(gca, 'fontsize', 14);
+plot(iris('Species'), residuals(anovaPL), 'bs');
+hold on;
+plot([.5 3.5], [0 0], 'k-');
+print(gcf, 'anova-irisPL-residsBySpecies.png', '-dpng');

doc/matStats-manual/matlab/nmf/nmf_iris.m

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+%NMF_IRIS  One-line description here, please.
+%
+%   output = nmf_iris(input)
+%
+%   Example
+%   nmf_iris
+%
+%   See also
+%
+
+% ------
+% Author: David Legland
+% e-mail: [email protected]
+% INRAE - BIA Research Unit - BIBS Platform (Nantes)
+% Created: 2020-12-22,    using Matlab 9.8.0.1323502 (R2020a)
+% Copyright 2020 INRAE.
+
+iris = Table.read('fisherIris');
+[W, H] = nmf(iris(:,1:4), 2);
+% use Matlab 'biplot' function to represent the results
+biplot(H.Data', 'Scores', W.Data, 'varLabels', H.ColNames);
+axis equal; axis([0 1.2 0 1.0]);
+
+print(gcf, 'nmf_iris_biplot.png', '-dpng');

doc/matStats-manual/matlab/pca-cities/pcaCities.m

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+%PCACITIES  One-line description here, please.
+%
+%   output = pcaCities(input)
+%
+%   Example
+%   pcaCities
+%
+%   See also
+%
+
+% ------
+% Author: David Legland
+% e-mail: [email protected]
+% Created: 2017-06-16,    using Matlab 9.1.0.441655 (R2016b)
+% Copyright 2017 INRA - Cepia Software Platform.
+
+% load data
+load cities.mat
+
+% format to a data table
+colNames = strtrim(cellstr(categories))';
+rowNames = strtrim(cellstr(names));
+cities = Table(ratings, colNames, rowNames);
+
+resPca = Pca(cities, 'scale', true, 'display', 'off');
+
+

doc/matStats-manual/matlab/pca-iris/pcaIris.m

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+%PCAIRIS  One-line description here, please.
+%
+%   output = pcaIris(input)
+%
+%   Example
+%   pcaIris
+%
+%   See also
+%
+
+% ------
+% Author: David Legland
+% e-mail: [email protected]
+% Created: 2017-06-16,    using Matlab 9.1.0.441655 (R2016b)
+% Copyright 2017 INRA - Cepia Software Platform.
+

doc/matStats-manual/matlab/plots_basic/plotDemo.m

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+% Demonstration of plotting features of the MatStats library.
+%
+%   output = plotDemo(input)
+%
+%   Example
+%   plotDemo
+%
+%   See also
+%
+
+% ------
+% Author: David Legland
+% e-mail: [email protected]
+% INRAE - BIA Research Unit - BIBS Platform (Nantes)
+% Created: 2020-07-01,    using Matlab 9.8.0.1323502 (R2020a)
+% Copyright 2020 INRAE.
+
+
+%% Generate demo Table
+% Generate a data table containing three columns, corresponding to a dummy
+% parametrisation variable, and the result of two functions, here sine and
+% cosine functions. 
+
+% parametrisation (as vertical vector)
+t = linspace(0, 2*pi, 100)';
+
+% concatenate as a numerical array
+data = [t cos(t) sin(t)];
+
+% create the Data Table encapsulating the data. Also specifies the name to
+% populate the 'title' of the figures
+tab = Table(data, {'t', 'Cos(t)', 'Sin(t)'}, 'Name', 'Sine and Cosine');
+
+
+%% Line Plot
+
+figure; set(gca, 'FontSize', 14);
+linePlot(tab(:,1), tab(:, 2:3));
+
+
+%% Bar Plot
+
+figure; set(gca, 'FontSize', 14);
+barPlot(tab(:,1), tab(:, 2:3));
+
+
+%% Stair Steps Plot
+
+figure; set(gca, 'FontSize', 14);
+stairStepsPlot(tab(:,1), tab(:, 2:3));
+
+
+%% Line Plot
+
+figure; set(gca, 'FontSize', 14);
+stemPlot(tab(:,1), tab(:, 2:3));

doc/matStats-manual/matlab/plots_iris/demoPairPlot_iris.m

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+%DEMOPAIRPLOT_IRIS  One-line description here, please.
+%
+%   output = demoPairPlot_iris(input)
+%
+%   Example
+%   demoPairPlot_iris
+%
+%   See also
+%
+
+% ------
+% Author: David Legland
+% e-mail: [email protected]
+% INRAE - BIA Research Unit - BIBS Platform (Nantes)
+% Created: 2020-12-22,    using Matlab 9.8.0.1323502 (R2020a)
+% Copyright 2020 INRAE.
+
+iris = Table.read('fisherIris');
+figure; pairPlot(iris(:,1:4), iris(:,5));
+print(gcf, 'iris_pairPlot_bySpecies.png', '-dpng');

doc/matStats-manual/matlab/plots_iris/iris_histogram.m

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+%IRIS_HISTOGRAM  One-line description here, please.
+%
+%   output = iris_histogram(input)
+%
+%   Example
+%   iris_histogram
+%
+%   See also
+%
+
+% ------
+% Author: David Legland
+% e-mail: [email protected]
+% INRAE - BIA Research Unit - BIBS Platform (Nantes)
+% Created: 2020-12-22,    using Matlab 9.8.0.1323502 (R2020a)
+% Copyright 2020 INRAE.
+
+iris = Table.read('fisherIris');
+
+figure;
+histogram(iris('PetalLength'), 30);
+
+print(gcf, 'iris_histogram_n30.png', '-dpng');

doc/matStats-manual/matlab/plots_iris/makeIrisFigures.m

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+%% Generate figures for the Table class manual
+%
+%   Usage:
+%     demoTable
+%
+% started 2017-05-31
+
+%% Read and display data
+
+% Read data from a csv file (several options can be specified)
+tab = Table.read('fisherIris.txt');
+
+% display a part of the table on the console
+disp(tab(1:5, :));
+
+% Or display summary of the data, like in R
+summary(tab);
+
+% display the table in a frame
+show(tab);
+
+%% Histograms
+
+% histogram of petal length. Columns can be indexed by their name.
+figure;
+histogram(tab('PetalLength'), 30);
+print(gcf, 'iris_petalLength_hist.png', '-dpng');
+
+
+% plot values of petal length
+figure;
+plot(tab('PetalLength'), 'bs');
+print(gcf, 'iris_plotPetalLength_sq.png', '-dpng');
+
+% plot petal width against petal length
+figure;
+plot(tab('PetalLength'), tab('PetalWidth'), 'b*');
+print(gcf, 'iris_petalWidth_petalLength_star.png', '-dpng');
+
+
+%% Box and violin plots
+
+% box plot of the quantitative variables
+figure;
+boxplot(tab(:,1:4));
+print(gcf, 'iris_boxPlot.png', '-dpng');
+
+figure;
+violinPlot(tab(:,1:4));
+print(gcf, 'iris_violinPlot.png', '-dpng');
+
+
+%% Management of groups
+
+% scatter plot using groups
+figure;
+scatterGroup(tab('PetalLength'), tab('PetalWidth'), tab('Species'), ...
+    'Envelope', 'InertiaEllipse', ...
+    'LegendLocation', 'NorthWest');
+
+% Compute the mean of each group
+meanByGroup = aggregate(tab(:,1:4), tab('Species'), @mean);
+disp(meanByGroup);
+
+% display as bar plot
+figure;
+bar(meanByGroup');
+print(gcf, 'iris_meanByGroup_bar.png', '-dpng');
+
+
+%% Principal Component Analysis
+
+% Apply Principal Component Analysis on the quantitative variables
+irisPca = Pca(tab(:, 1:4), 'display', 'off');
+
+% The result is a Pca object, containing Table object for scores, loadings
+% and eigen values
+disp(irisPca);
+
+% Score plot can be displayed with automatic labeling of axes
+figure;
+scorePlot(irisPca, 1, 2);
+
+% Loadings can also be displayed with automatic labeling
+figure;
+loadingPlot(irisPca, 1, 2);
+
+% To display scores with group labelling, simply call the plot method on
+% the score object stored in Pca result
+figure;
+scatterGroup(irisPca.Scores(:, 1), irisPca.Scores(:, 2), tab('Species'), ...
+    'LegendLocation', 'NorthWest');