From: Benjamin Auder Date: Tue, 21 Feb 2017 11:42:54 +0000 (+0100) Subject: set-up tests X-Git-Url: https://git.auder.net/images/doc/html/current/pieces/img/cross.svg?a=commitdiff_plain;h=a65907cc939a5fe419613d3ba555b1d1c1af97d3;p=talweg.git set-up tests --- diff --git a/pkg/tests/testthat/test.computeFilaments.R b/pkg/tests/testthat/test.computeFilaments.R index 9de6274..46f2e3f 100644 --- a/pkg/tests/testthat/test.computeFilaments.R +++ b/pkg/tests/testthat/test.computeFilaments.R @@ -1,36 +1,51 @@ -#TODO: toy dataset, check that indices returned are correct + colors +context("Check that computeFilaments behaves as expected") -context("Check that getParamsDirs behaves as expected") - -test_that("on input of sufficient size, beta is estimated accurately enough", { - n = 100000 - d = 2 - K = 2 - Pr = c(0.5, 0.5) - - betas_ref = array( c(1,0,0,1 , 1,-2,3,1), dim=c(2,2,2) ) - for (i in 1:(dim(betas_ref)[3])) +test_that("output is as expected on simulated series", +{ + x = seq(0,10,0.1) + L = length(x) + s1 = cos(x) + s2 = sin(x) + s3 = c( s1[1:(L%/%2)] , s2[(L%/%2+1):L] ) + #sum((s1-s2)^2) == 97.59381 + #sum((s1-s3)^2) == 57.03051 + #sum((s2-s3)^2) == 40.5633 + s = list( s1, s2, s3 ) + n = 150 + series = list() + for (i in seq_len(n)) { - beta_ref = betas_ref[,,i] - #all parameters are supposed to be of norm 1: thus, normalize beta_ref - norm2 = sqrt(colSums(beta_ref^2)) - beta_ref = beta_ref / norm2[col(beta_ref)] - - io = generateSampleIO(n, d, K, Pr, beta_ref) - beta = getParamsDirs(io$X, io$Y, K) - betas = .labelSwitchingAlign( - array( c(beta_ref,beta), dim=c(d,K,2) ), compare_to="first", ls_mode="exact") - - #Some traces: 0 is not well estimated, but others are OK - cat("\n\nReference parameter matrix:\n") - print(beta_ref) - cat("Estimated parameter matrix:\n") - print(betas[,,2]) - cat("Difference norm (Matrix norm ||.||_1, max. abs. sum on a column)\n") - diff_norm = norm(beta_ref - betas[,,2]) - cat(diff_norm,"\n") - - #NOTE: 0.5 is loose threshold, but values around 0.3 are expected... - expect_that( diff_norm, is_less_than(0.5) ) + index = (i%%3) + 1 + level = mean(s[[index]]) + serie = s[[index]] - level + rnorm(L,sd=0.05) + # 10 series with NAs for index 2 + if (index == 2 && i >= 60 && i<= 90) + serie[sample(seq_len(L),1)] = NA + series[[i]] = list("level"=level,"serie"=serie) #no need for more } + data = new("Data", data=series) + + # index 142 : serie type 2 + f2 = computeFilaments(data, 142, limit=60, plot=FALSE) + # Expected output: 22 series of type 3 (closer), then 50-2-10 series of type 2 + # + # + # + # + # + # + # Simulate shift at origin when predict_at > 0 + series[2:(n+1)] = series[1:n] + series[[1]] = list("level"=0, "serie"=s[[1]][1:(L%/%2)]) + # index 143 : serie type 3 + f3 = computeFilaments(data, 143, limit=70, plot=FALSE) + # Expected output: 22 series of type 2 (closer) then 50-2 series of type 3 + # ATTENTION au shift + # + # + # index 144 : serie type 1 + f1 = computeFilaments(data, 144, limit=50, plot=FALSE) + # Expected output: 2 series of type 3 (closer), then 50-2 series of type 1 + # + expect_that( diff_norm, is_less_than(0.5) ) }) diff --git a/pkg/tests/testthat/test.dateIndexToInteger.R b/pkg/tests/testthat/test.dateIndexToInteger.R index fb4c8e4..9786097 100644 --- a/pkg/tests/testthat/test.dateIndexToInteger.R +++ b/pkg/tests/testthat/test.dateIndexToInteger.R @@ -1,69 +1,26 @@ -context("Check that getParamsDirs behaves as expected") +context("Check that dateIndexToInteger behaves as expected") -test_that("on input of sufficient size, beta is estimated accurately enough", { - n = 100000 - d = 2 - K = 2 - Pr = c(0.5, 0.5) +test_that("integer index matches date in data", +{ - betas_ref = array( c(1,0,0,1 , 1,-2,3,1), dim=c(2,2,2) ) - for (i in 1:(dim(betas_ref)[3])) - { - beta_ref = betas_ref[,,i] - #all parameters are supposed to be of norm 1: thus, normalize beta_ref - norm2 = sqrt(colSums(beta_ref^2)) - beta_ref = beta_ref / norm2[col(beta_ref)] - io = generateSampleIO(n, d, K, Pr, beta_ref) - beta = getParamsDirs(io$X, io$Y, K) - betas = .labelSwitchingAlign( - array( c(beta_ref,beta), dim=c(d,K,2) ), compare_to="first", ls_mode="exact") - #Some traces: 0 is not well estimated, but others are OK - cat("\n\nReference parameter matrix:\n") - print(beta_ref) - cat("Estimated parameter matrix:\n") - print(betas[,,2]) - cat("Difference norm (Matrix norm ||.||_1, max. abs. sum on a column)\n") - diff_norm = norm(beta_ref - betas[,,2]) - cat(diff_norm,"\n") +#TODO: with and without shift at origin (so series values at least forst ones are required) - #NOTE: 0.5 is loose threshold, but values around 0.3 are expected... - expect_that( diff_norm, is_less_than(0.5) ) - } -}) -dateIndexToInteger = function(index, data) -{ - index = index[1] - if (is.numeric(index)) - index = as.integer(index) - if (is.integer(index)) - return (index) - if (inherits(index, "Date") || is.character(index)) + + n = 1500 + series = list() + for (i in seq_len(n)) { - tryCatch(dt <- as.POSIXct(index), error=function(e) stop("Unrecognized index format")) - #TODO: tz arg to difftime ? - integerIndex <- round( (as.numeric( difftime(dt, data$getTime(1)) ))[1] ) + 1 - if (integerIndex > 0 && integerIndex <= data$getSize()) - { - #WARNING: if series start at date >0h, result must be shifted - date1 = as.POSIXlt(data$getTime(1)[1]) - date2 = as.POSIXlt(data$getTime(2)[1]) - shift = (date1$year==date2$year && date1$mon==date2$mon && date1$mday==date2$mday) - return (integerIndex + ifelse(shift,1,0)) - } - stop("Date outside data range") + index = (i%%3) + 1 + level = mean(s[[index]]) + serie = s[[index]] - level + rnorm(L,sd=0.05) + # 10 series with NAs for index 2 + if (index == 2 && i >= 60 && i<= 90) + serie[sample(seq_len(L),1)] = NA + series[[i]] = list("level"=level,"serie"=serie) #no need for more :: si : time !!! } - stop("Unrecognized index format") -} - -#' @title integerIndexToDate -#' -#' @description Transform an integer index to date index (relative to data) -#' -#' @param index Date (or integer) index -#' @param data Object of class \code{Data} -#' -#' @export -integerIndexToDate = function(index, data) + data = new("Data", data=series) + dateIndexToInteger = function(index, data) +}) diff --git a/pkg/tests/testthat/test.integerIndexToDate.R b/pkg/tests/testthat/test.integerIndexToDate.R index 5f0008f..31cd740 100644 --- a/pkg/tests/testthat/test.integerIndexToDate.R +++ b/pkg/tests/testthat/test.integerIndexToDate.R @@ -1,34 +1,22 @@ -context("Check that getParamsDirs behaves as expected") +context("Check that integerIndexToDate behaves as expected") -test_that("on input of sufficient size, beta is estimated accurately enough", { - n = 100000 - d = 2 - K = 2 - Pr = c(0.5, 0.5) +test_that("date matches index in data", +{ + #TODO: with and without shift at origin (so series values at least forst ones are required) - betas_ref = array( c(1,0,0,1 , 1,-2,3,1), dim=c(2,2,2) ) - for (i in 1:(dim(betas_ref)[3])) + n = 1500 + series = list() + for (i in seq_len(n)) { - beta_ref = betas_ref[,,i] - #all parameters are supposed to be of norm 1: thus, normalize beta_ref - norm2 = sqrt(colSums(beta_ref^2)) - beta_ref = beta_ref / norm2[col(beta_ref)] - - io = generateSampleIO(n, d, K, Pr, beta_ref) - beta = getParamsDirs(io$X, io$Y, K) - betas = .labelSwitchingAlign( - array( c(beta_ref,beta), dim=c(d,K,2) ), compare_to="first", ls_mode="exact") - - #Some traces: 0 is not well estimated, but others are OK - cat("\n\nReference parameter matrix:\n") - print(beta_ref) - cat("Estimated parameter matrix:\n") - print(betas[,,2]) - cat("Difference norm (Matrix norm ||.||_1, max. abs. sum on a column)\n") - diff_norm = norm(beta_ref - betas[,,2]) - cat(diff_norm,"\n") - - #NOTE: 0.5 is loose threshold, but values around 0.3 are expected... - expect_that( diff_norm, is_less_than(0.5) ) + index = (i%%3) + 1 + level = mean(s[[index]]) + serie = s[[index]] - level + rnorm(L,sd=0.05) + # 10 series with NAs for index 2 + if (index == 2 && i >= 60 && i<= 90) + serie[sample(seq_len(L),1)] = NA + series[[i]] = list("level"=level,"serie"=serie) #no need for more :: si : time !!! } + data = new("Data", data=series) + + integerIndexToDate = function(index, data) })