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| <?xml version="1.0" encoding="UTF-8"?> | ||
| <!-- | ||
| Copyright (c) 2017, RTE (http://www.rte-france.com) | ||
| This Source Code Form is subject to the terms of the Mozilla Public | ||
| License, v. 2.0. If a copy of the MPL was not distributed with this | ||
| file, You can obtain one at http://mozilla.org/MPL/2.0/. | ||
| --> | ||
| <project xmlns="http://maven.apache.org/POM/4.0.0" | ||
| xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" | ||
| xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"> | ||
| <modelVersion>4.0.0</modelVersion> | ||
|
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| <parent> | ||
| <groupId>eu.itesla_project</groupId> | ||
| <artifactId>itesla-parent</artifactId> | ||
| <version>0.1-SNAPSHOT</version> | ||
| </parent> | ||
|
|
||
| <artifactId>uncertainties-analysis</artifactId> | ||
|
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| <name>Uncertainties analysis</name> | ||
|
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| <dependencies> | ||
| <!-- Compilation dependencies --> | ||
| <dependency> | ||
| <groupId>com.google.auto.service</groupId> | ||
| <artifactId>auto-service</artifactId> | ||
| </dependency> | ||
| <dependency> | ||
| <groupId>com.google.guava</groupId> | ||
| <artifactId>guava</artifactId> | ||
| </dependency> | ||
| <dependency> | ||
| <groupId>com.powsybl</groupId> | ||
| <artifactId>powsybl-commons</artifactId> | ||
| </dependency> | ||
| <dependency> | ||
| <groupId>com.powsybl</groupId> | ||
| <artifactId>powsybl-computation</artifactId> | ||
| </dependency> | ||
| <dependency> | ||
| <groupId>com.powsybl</groupId> | ||
| <artifactId>powsybl-iidm-api</artifactId> | ||
| </dependency> | ||
| <dependency> | ||
| <groupId>com.powsybl</groupId> | ||
| <artifactId>powsybl-iidm-converter-api</artifactId> | ||
| </dependency> | ||
| <dependency> | ||
| <groupId>commons-cli</groupId> | ||
| <artifactId>commons-cli</artifactId> | ||
| </dependency> | ||
| <dependency> | ||
| <groupId>joda-time</groupId> | ||
| <artifactId>joda-time</artifactId> | ||
| </dependency> | ||
| <dependency> | ||
| <groupId>org.slf4j</groupId> | ||
| <artifactId>slf4j-api</artifactId> | ||
| </dependency> | ||
|
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| <dependency> | ||
| <groupId>${project.groupId}</groupId> | ||
| <artifactId>ampl-export</artifactId> | ||
| <version>${project.version}</version> | ||
| </dependency> | ||
| <dependency> | ||
| <groupId>${project.groupId}</groupId> | ||
| <artifactId>histodb-client</artifactId> | ||
| <version>${project.version}</version> | ||
| </dependency> | ||
| <dependency> | ||
| <groupId>${project.groupId}</groupId> | ||
| <artifactId>modules</artifactId> | ||
| <version>${project.version}</version> | ||
| </dependency> | ||
| <dependency> | ||
| <groupId>${project.groupId}</groupId> | ||
| <artifactId>wca-integration</artifactId> | ||
| <version>${project.version}</version> | ||
| </dependency> | ||
|
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| <!-- Test dependencies --> | ||
| <dependency> | ||
| <groupId>com.google.jimfs</groupId> | ||
| <artifactId>jimfs</artifactId> | ||
| <scope>test</scope> | ||
| </dependency> | ||
| <dependency> | ||
| <groupId>junit</groupId> | ||
| <artifactId>junit</artifactId> | ||
| <scope>test</scope> | ||
| </dependency> | ||
| </dependencies> | ||
| </project> |
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uncertainties-analysis/resources/R/bluestone/error_box_v1.1.R
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| ############################################################################################## | ||
| ### Copyright (c) 2017, RTE (http://www.rte-france.com) | ||
| ### This Source Code Form is subject to the terms of the Mozilla Public | ||
| ### License, v. 2.0. If a copy of the MPL was not distributed with this | ||
| ### file, You can obtain one at http://mozilla.org/MPL/2.0/. | ||
| ### | ||
| ### Program name : error_box.R | ||
| ### Author : Cedric Faucheux (Bluestone) | ||
| ### Project : RTE prototype for the iTesla online module | ||
| ### Function : Compute error box with the error_box function | ||
| ### Parameters : dataset= the dataset on which the error box is calculated | ||
| ### the dataset is in the equipment base | ||
| ### prct= the percentage of observations in the error box | ||
| ### epsilon= the precision for z, the box main parameter | ||
| ### Outputs : z= the box parameter | ||
| ### inf= the lower bounds of the box | ||
| ### sup= the upper bounds of the box | ||
| ### loadings= the transition matrix from equipments to principal components | ||
| ### structure: rows= equipments, columns= principal components | ||
| ### Version : 1.1 | ||
| ### Modification : "comp.XX" names changed to "DimXX" | ||
| ### Date : 14/10/2014 | ||
| ### Comments : This file also contains four other functions: | ||
| ### plot_error_box function plots the error box, given two principal components | ||
| ### nb_inbounds function calculates which principal components have observations out of the box | ||
| ### find_z function calculates the box parameter, called by error_box. | ||
| ### nb_inbox function calculates the number of observations in the box, called by error_box. | ||
| ############################################################################################## | ||
| ### Example: | ||
| ### box=error_box(errors_P,0.95,0.00001) | ||
| ### data_PC=as.matrix(errors_P)%*%box[[4]] | ||
| ### PC_inbound=nb_inbounds(data_PC,error_box = box) | ||
| ### plot_error_box(data_PC,error_box = box,comp1 = PC_inbound[1,1],comp2 = PC_inbound[2,1]) | ||
| ############################################################################################## | ||
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| #Function which computes the error boxes | ||
| error_box<-function(dataset,prct,epsilon){ | ||
| # dataset: the dataset on which the error box is calculated, the dataset is in the equipment base | ||
| # prct: the percentage of observations in the error box | ||
| # epsilon: the precision on z | ||
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| #PCA: error boxes are calculated on PCA axes | ||
| acp=princomp(dataset,cor=F) | ||
| data_PC=acp$scores | ||
| #Compute mu and sigma for each column | ||
| mu=apply(data_PC,2,mean) | ||
| sigma=apply(data_PC,2,sd) | ||
| #Find z | ||
| z=find_z(data_PC,prct,epsilon,mu,sigma) | ||
| #Lower bound | ||
| inf=mu-z*sigma | ||
| #Upper bound | ||
| sup=mu+z*sigma | ||
| res=list(z,inf,sup,acp$loadings) | ||
| names(res)=c("z","inf","sup","loadings") | ||
| names(res$inf)=paste("Dim",substr(names(res$inf),6,nchar(names(res$inf))),sep="") | ||
| names(res$sup)=paste("Dim",substr(names(res$sup),6,nchar(names(res$sup))),sep="") | ||
| colnames(res$loadings)=paste("Dim",substr(colnames(res$loadings),6,nchar(colnames(res$loadings))),sep="") | ||
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| # z: the box parameter | ||
| # inf: the lower bound of the box | ||
| # sup: the upper bound of the box | ||
| # loadings: the matrix to go from equipments to principal components | ||
| # loadings structure: rows= equipments, columns= principal components | ||
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| return(res) | ||
| } | ||
|
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| #Function which find z | ||
| find_z<-function(data_PC,prct,epsilon,mu,sigma){ | ||
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| #find extrema of z | ||
| val=matrix(0,nrow=nrow(data_PC),ncol=ncol(data_PC)) | ||
| for(k in 1:ncol(data_PC)){ | ||
| if(sigma[k]!=0){ | ||
| val[,k]=data_PC[,k]/sigma[k] | ||
| }else{ | ||
| val[,k]=0 | ||
| } | ||
| } | ||
| zmax<-max(na.omit(val)) | ||
| zmin=0 | ||
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| #initialisation | ||
| zd=(zmax+zmin)/2 | ||
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| #Required number of observations in the box | ||
| ndata=prct*nrow(data_PC) | ||
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| #### Find zd by dichotomy | ||
| #Stop iterations when zd change less than Epsilon from one iteration to the other | ||
| nbox=nb_inbox(zd,data_PC,mu,sigma) | ||
| nb_iter=0 | ||
| while(nb_iter!=-1){ | ||
| nb_iter=nb_iter+1 | ||
| old_zd=zd | ||
| if(nbox<ndata){ | ||
| zmin=zd | ||
| zd=(zmax+zmin)/2 | ||
| }else{ | ||
| zmax=zd | ||
| zd=(zmax+zmin)/2 | ||
| } | ||
| if(abs(zd-old_zd)<epsilon){ | ||
| z=c(zd,old_zd) | ||
| zd=z[which.min(c(abs(nb_inbox(zd,data_PC,mu,sigma)-ndata),abs( | ||
| nb_inbox(old_zd,data_PC,mu,sigma)-ndata)))] | ||
| nb_iter=-1 | ||
| } | ||
| nbox=nb_inbox(zd,data_PC,mu,sigma) | ||
| print(c(zmin,zmax,zd,nbox,nbox/ndata*prct*100,nb_iter)) | ||
| } | ||
| return(zd) | ||
| } | ||
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| ##Function which calculates the number of observation in the box | ||
| nb_inbox<-function(z,data_PC,mu,sigma){ | ||
| if (z!=0){ | ||
| inf=mu-z*sigma | ||
| sup=mu+z*sigma | ||
| data_inf<-sweep(data_PC,2,inf) | ||
| data_sup<-sweep(data_PC,2,sup) | ||
| nobs_line=length(which(apply((data_inf>=0)&(data_sup<=0),1,sum)==ncol(data_PC))) | ||
| }else {nobs_line=0} | ||
| return(nobs_line) | ||
| } | ||
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| ##Function which calculates the number of observation in the box for each principal component | ||
| nb_inbounds<-function(data_PC,error_box){ | ||
| inf=error_box[[2]] | ||
| sup=error_box[[3]] | ||
| nobs_pc<-as.data.frame(matrix(0,ncol(data_PC),0)) | ||
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| for (col in 1:ncol(data_PC)){ | ||
| nobs_pc[col,1]<-colnames(data_PC)[col] | ||
| nobs_pc[col,2]<-length(data_PC[,col][which((data_PC[,col]>=inf[col])&(data_PC[,col]<=sup[col]))]) | ||
| } | ||
| nobs_pc[,3]=nobs_pc[,2]/nrow(data_PC)*100 | ||
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| #Sort according to the number of observations in the box | ||
| nobs_pc=nobs_pc[order(nobs_pc[,2]),] | ||
| colnames(nobs_pc)<-c("Principal Component","Observations_in_box","%Observations_in_box") | ||
| return(nobs_pc) | ||
| } | ||
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| ##Function to plot error box | ||
| plot_error_box<-function(data_PC,error_box,comp1,comp2){ | ||
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| data=data_PC[,c(comp1,comp2)] | ||
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| inf=error_box[[2]] | ||
| sup=error_box[[3]] | ||
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| abs1<-as.numeric(inf[comp1]) | ||
| abs2<-as.numeric(sup[comp1]) | ||
| ord1<-as.numeric(inf[comp2]) | ||
| ord2<-as.numeric(sup[comp2]) | ||
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| a1=min(abs1,min(data[,1])) | ||
| a2=max(abs2,max(data[,1])) | ||
| o1=min(ord1,min(data[,2])) | ||
| o2=max(ord2,max(data[,2])) | ||
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| smoothScatter(data[,1],data[,2],main=paste("Error box for ",colnames(data)[1]," and ",colnames(data)[2],sep=""),xlab=colnames(data)[1],ylab=colnames(data)[2],xlim=c(a1-1,a2+1),ylim= c(o1-1,o2+1)) | ||
| rect(abs1,ord1,abs2,ord2,border='red',xpd=T) | ||
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| } | ||
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