context("hvq package") # require(plotly) ## Load data USArrests <- datasets::USArrests USArrests <- scale(USArrests,center = TRUE,scale = TRUE) set.seed(420) test_that("getCentroids give correct results for L1_Norm and mean",{ skip_on_cran() set.seed(420) hvt.results <- HVT::trainHVT(USArrests,n_cells = 3,depth = 1,quant.err = 0.2,distance_metric = "L1_Norm",error_metric = "mean", quant_method = "kmeans") expect_equal(length(hvt.results),7) expect_equal(hvt.results[[3]]$summary[,"Quant.Error"],c(0.5265759, 0.4197644, 0.4843762),1e-5) expect_equal(hvt.results[[3]]$compression_summary[["percentOfCellsBelowQuantizationErrorThreshold"]],0) }) test_that("getCentroids give correct results for L2_Norm and mean",{ skip_on_cran() set.seed(420) hvt.results <- HVT::trainHVT(USArrests,n_cells = 3,depth = 1,quant.err = 0.2,distance_metric = "L2_Norm",error_metric = "mean", quant_method = "kmeans") expect_equal(length(hvt.results),7) expect_equal(hvt.results[[3]]$summary[,"Quant.Error"],c(0.3141953, 0.2407124, 0.2885561),1e-5) expect_equal(hvt.results[[3]]$compression_summary[["percentOfCellsBelowQuantizationErrorThreshold"]],0) }) test_that("getCentroids give correct results for L1_Norm and max",{ skip_on_cran() set.seed(420) hvt.results <- HVT::trainHVT(USArrests,n_cells = 3,depth = 1,quant.err = 0.2,distance_metric = "L1_Norm",error_metric = "max", quant_method = "kmeans") expect_equal(length(hvt.results),7) expect_equal(hvt.results[[3]]$summary[,"Quant.Error"],c(1.0147530, 0.6268437, 0.8490633),1e-5) expect_equal(hvt.results[[3]]$compression_summary[["percentOfCellsBelowQuantizationErrorThreshold"]],0) }) test_that("getCentroids give correct results for L2_Norm and max",{ skip_on_cran() set.seed(420) hvt.results <- HVT::trainHVT(USArrests,n_cells = 3,depth = 1,quant.err = 0.2,distance_metric = "L2_Norm",error_metric = "max", quant_method = "kmeans") expect_equal(length(hvt.results),7) expect_equal(hvt.results[[3]]$summary[,"Quant.Error"],c(0.6168272, 0.3525659, 0.5722204),1e-5) expect_equal(hvt.results[[3]]$compression_summary[["percentOfCellsBelowQuantizationErrorThreshold"]],0) })