From: emilie Date: Wed, 12 Apr 2017 10:54:11 +0000 (+0200) Subject: update the output to have the classification X-Git-Url: https://git.auder.net/variants/Chakart/pieces/img/css/current/git-favicon.png?a=commitdiff_plain;h=9fadef2bff80d4b0371962dea4b6de24086f230b;p=valse.git update the output to have the classification --- diff --git a/pkg/R/main.R b/pkg/R/main.R index 695a23f..89c4bcd 100644 --- a/pkg/R/main.R +++ b/pkg/R/main.R @@ -131,9 +131,23 @@ print(tableauRecap) mod = as.character(tableauRecap[indModSel,1]) listMod = as.integer(unlist(strsplit(mod, "[.]"))) - if (plot){ - print(plot_valse(models_list[[listMod[1]]][[listMod[2]]],n)) + modelSel = models_list[[listMod[1]]][[listMod[2]]] + + ##Affectations + Gam = matrix(0, ncol = length(modelSel$pi), nrow = n) + for (i in 1:n){ + for (r in 1:length(modelSel$pi)){ + sqNorm2 = sum( (Y[i,]%*%modelSel$rho[,,r]-X[i,]%*%modelSel$phi[,,r])^2 ) + Gam[i,r] = modelSel$pi[r] * exp(-0.5*sqNorm2)* det(modelSel$rho[,,r]) + } + } + Gam = Gam/rowSums(Gam) + modelSel$affec = apply(Gam, 1,which.max) + modelSel$proba = Gam + + if (plot){ + print(plot_valse(modelSel,n)) } - models_list[[listMod[1]]][[listMod[2]]] + return(modelSel) } diff --git a/pkg/R/plot_valse.R b/pkg/R/plot_valse.R index 2c74554..120196d 100644 --- a/pkg/R/plot_valse.R +++ b/pkg/R/plot_valse.R @@ -48,20 +48,11 @@ plot_valse = function(model,n){ print(gCov ) ### proportions - Gam = matrix(0, ncol = K, nrow = n) - gam = Gam - for (i in 1:n){ - for (r in 1:K){ - sqNorm2 = sum( (Y[i,]%*%model$rho[,,r]-X[i,]%*%model$phi[,,r])^2 ) - Gam[i,r] = model$pi[r] * exp(-0.5*sqNorm2)* det(model$rho[,,r]) - } - gam[i,] = Gam[i,] / sum(Gam[i,]) - } - affec = apply(gam, 1,which.max) gam2 = matrix(NA, ncol = K, nrow = n) for (i in 1:n){ - gam2[i, ] = c(gam[i, affec[i]], affec[i]) + gam2[i, ] = c(model$Gam[i, model$affec[i]], model$affec[i]) } + bp <- ggplot(data.frame(gam2), aes(x=X2, y=X1, color=X2, group = X2)) + geom_boxplot() + theme(legend.position = "none")+ background_grid(major = "xy", minor = "none") print(bp )