Skip to main content

Map with R



How it really works in R ggplot2 


http://eriqande.github.io/rep-res-web/lectures/making-maps-with-R.html

You need to create data in following format:

                long      lat        group order region subregion
#> 1 -101.4078 29.74224     1     1   main      
#> 2 -101.3906 29.74224     1     2   main      
#> 3 -101.3620 29.65056     1     3   main      
#> 4 -101.3505 29.63911     1     4   main      
#> 5 -101.3219 29.63338     1     5   main      
#> 6 -101.3047 29.64484     1     6   main      


Some useful packages


  • ggmap
  • googleVis







Comments

Popular posts from this blog

MATLAB cross validation

// use built-in function samplesize = size( matrix , 1); c = cvpartition(samplesize,  'kfold' , k); % return the indexes on each fold ///// output in matlab console K-fold cross validation partition              N: 10    NumTestSets: 4      TrainSize: 8  7  7  8       TestSize: 2  3  3  2 ////////////////////// for i=1 : k    trainIdxs = find(training(c,i) ); %training(c,i);  // 1 means in train , 0 means in test    testInxs  = find(test(c,i)       ); % test(c,i);       // 1 means in test , 0 means in train    trainMatrix = matrix (  matrix(trainIdxs ), : );    testMatrix  = matrix (  matrix(testIdxs  ), : ); end //// now calculate performance %%  calculate performance of a partiti...

MATLAB optimization toolbox usage with genetic algorithm

Useful tutorial http://www.mathworks.com/products/global-optimization/description3.html Best example of implementatoin with Constraint, objective function http://www.mathworks.com/help/gads/examples/constrained-minimization-using-the-genetic-algorithm.html More about how to use multi-objective http://www.mathworks.com/discovery/multiobjective-optimization.html http://www.mathworks.com/help/gads/examples/performing-a-multiobjective-optimization-using-the-genetic-algorithm.html http://www.mathworks.com/help/gads/examples/multiobjective-genetic-algorithm-options.html Example GAMULTOBJ (can handle Multiple Objective)  GA(can handle 1 objective) Constrained Minimization Problem We want to minimize a simple fitness function of two variables x1 and x2 min f(x) = 100 * (x1^2 - x2) ^2 + (1 - x1)^2; x min f(x) = 100 * (x1^2 + x2) ^2 + (1 + x1)^2; x such that the following two nonlinear constraints and bounds are satisfied x1*x2 + x1 - x2 + 1.5 <...

MATLAB confusion matrix

%  test_class  & predicted_class must be same dimension % 'order' - describes the order of label. Here labels are 'g' as positive and 'h' as negative [C,order] = confusionmat( test_class(1: noSampleTest), predicted_class, 'order', ['g' ;'h'] ) tp = C(1,1); fn = C(1,2); fp = C(2,1); tn = C(2,2); sensitivity = tp /( tp + fn ) specificity = tn /( fp + tn ) accuracy = (tp+tn) / (tp+fn+fp+tn) tpr = sensitivity fpr = 1-specificity precision = tp /( tp + fp ) fVal = (2*tpr*precision)/(tpr+precision)