# all python tests are skipped to avoid build errors, even though they succeed locally # to run the tests the reticulate package must be installed, correctly hooked up to # python, and the ripser module must be downloaded. test_that("ripser can be imported and verified.",{ skip_if(T) ripser <- import_ripser() expect_invisible(check_ripser(ripser)) expect_error(check_ripser(2),"ripser object") expect_error(check_ripser(NULL),"ripser object") np <- reticulate::import("numpy") expect_error(check_ripser(np),"ripser object") }) test_that("PyH can detect bad input parameters.",{ skip_if(T) ripser <- import_ripser() expect_error(PyH(X = data.frame(),maxdim = 1,thresh = 1,distance_mat = F,ripser = ripser),"two rows") expect_error(PyH(X = NULL,maxdim = 1,thresh = 1,distance_mat = F,ripser = ripser),"dataframe") expect_error(PyH(X = data.frame(x = 1:2,y = c("1","2")),maxdim = 1,thresh = 1,distance_mat = F,ripser = ripser),"numeric") expect_error(PyH(X = data.frame(x = c(1,NA,2)),maxdim = 1,thresh = 1,distance_mat = F,ripser = ripser),"missing") expect_error(PyH(X = data.frame(x = 1:3),maxdim = 1,thresh = 1,distance_mat = T,ripser = ripser),"square") expect_error(PyH(X = data.frame(x = 1:3,y = 1:3,z = 1:3),maxdim = 1,thresh = 1,distance_mat = T,ripser = ripser),"matrix") expect_error(PyH(X = data.frame(x = 1:3,y = 1:3,z = 1:3),maxdim = NA,thresh = 1,distance_mat = T,ripser = ripser),"maxdim") expect_error(PyH(X = data.frame(x = 1:3,y = 1:3,z = 1:3),maxdim = -1,thresh = 1,distance_mat = T,ripser = ripser),"maxdim") expect_error(PyH(X = data.frame(x = 1:3,y = 1:3,z = 1:3),maxdim = 1,thresh = 1,distance_mat = NULL,ripser = ripser),"NULL") expect_error(PyH(X = data.frame(x = 1:3,y = 1:3,z = 1:3),maxdim = 1,thresh = 1,distance_mat = NA,ripser = ripser),"NA") expect_error(PyH(X = data.frame(x = 1:3,y = 1:3,z = 1:3),maxdim = 1,thresh = 1,distance_mat = c(T,F),ripser = ripser),"logical") expect_error(PyH(X = data.frame(x = 1:3,y = 1:3,z = 1:3),maxdim = 1,thresh = 1,distance_mat = T,ripser = ripser,ignore_infinite_cluster = NULL),"NULL") expect_error(PyH(X = data.frame(x = 1:3,y = 1:3,z = 1:3),maxdim = 1,thresh = 1,distance_mat = T,ripser = ripser,ignore_infinite_cluster = c(T,F)),"single") expect_error(PyH(X = data.frame(x = 1:3,y = 1:3,z = 1:3),maxdim = 1,thresh = 1,distance_mat = T,ripser = ripser,ignore_infinite_cluster = NA),"NA") expect_error(PyH(X = data.frame(x = 1:3,y = 1:3,z = 1:3),maxdim = 1,thresh = 1,distance_mat = T,ripser = ripser,calculate_representatives = NULL),"NULL") expect_error(PyH(X = data.frame(x = 1:3,y = 1:3,z = 1:3),maxdim = 1,thresh = 1,distance_mat = T,ripser = ripser,calculate_representatives = c(T,F)),"single") expect_error(PyH(X = data.frame(x = 1:3,y = 1:3,z = 1:3),maxdim = 1,thresh = 1,distance_mat = T,ripser = ripser,calculate_representatives = NA),"NA") }) test_that("PyH is computing correctly.",{ skip_if(T) D1 <- data.frame(x = stats::rnorm(20),y = stats::rnorm(20)) D2 <- data.frame(x = stats::rnorm(20),y = stats::rnorm(20)) D3 <- data.frame(x = stats::rnorm(20),y = stats::rnorm(20)) phom_TDA_1 <- diagram_to_df(TDAstats::calculate_homology(D1,threshold = 5)) phom_TDA_2 <- diagram_to_df(TDAstats::calculate_homology(D2,threshold = 5)) phom_TDA_3 <- diagram_to_df(TDAstats::calculate_homology(D3,threshold = 5)) ripser <- import_ripser() phom_py_1 <- PyH(D1,thresh = 5,ripser = ripser) phom_py_2 <- PyH(D2,thresh = 5,ripser = ripser) phom_py_3 <- PyH(D3,thresh = 5,ripser = ripser) expect_equal(phom_TDA_1,phom_py_1,tolerance = 0.00001) expect_equal(phom_TDA_2,phom_py_2,tolerance = 0.00001) expect_equal(phom_TDA_3,phom_py_3,tolerance = 0.000001) phom_with_extra_cluster <- PyH(D1,thresh = 5,ripser = ripser,ignore_infinite_cluster = F) expect_length(which(phom_with_extra_cluster$dimension == 0),20) phom_with_reps <- PyH(D1,thresh = 5,ripser = ripser,calculate_representatives = T) expect_type(phom_with_reps,"list") circ <- TDA::circleUnif(n = 10,r = 1) phom_with_empty_dim <- PyH(circ,thresh = 2,ripser = ripser,maxdim = 2) expect_s3_class(phom_with_empty_dim,"data.frame") }) test_that("bootstrap function can detect PyH errors correctly.",{ skip_if(T) ripser = import_ripser() D <- TDA::circleUnif(n = 50,r = 1) expect_error(bootstrap_persistence_thresholds(X = D,FUN_diag = "PyH",maxdim = 1,thresh = 2,calculate_representatives = T,return_diag = T,ripser = ripser,num_workers = 2,num_samples = 3,return_subsetted = T,ignore_infinite_cluster = NULL),"NULL") expect_error(bootstrap_persistence_thresholds(X = D,FUN_diag = "PyH",maxdim = 1,thresh = 2,calculate_representatives = T,return_diag = T,ripser = ripser,num_workers = 2,num_samples = 3,return_subsetted = T,ignore_infinite_cluster = 2),"logical") expect_error(bootstrap_persistence_thresholds(X = D,FUN_boot = "PyH",maxdim = 1,thresh = 2,calculate_representatives = T,return_diag = T,ripser = ripser,num_workers = 2,num_samples = 3,return_subsetted = T,ignore_infinite_cluster = NA),"NA") }) test_that("PyH functionality works in bootstrap function.",{ skip_if(T) ripser = import_ripser() D <- TDA::circleUnif(n = 50,r = 1) # PyH with multiple thresholds bs <- bootstrap_persistence_thresholds(X = D,FUN_diag = "PyH",FUN_boot = "PyH",maxdim = 1,thresh = 2,calculate_representatives = T,return_diag = T,ripser = ripser,num_workers = 2,num_samples = 3,return_subsetted = T,ignore_infinite_cluster = F) expect_length(bs$representatives[[2]],length(which(bs$diag$dimension == 1))) expect_length(bs$thresholds,2) expect_gt(bs$thresholds[[1]],0) expect_gt(bs$thresholds[[2]],0) expect_lte(length(bs$subsetted_representatives),nrow(bs$subsetted_diag) + 1) if(length(which(bs$subsetted_diag$dimension == 0)) > 0) { expect_true(min(bs$subsetted_diag[which(bs$subsetted_diag$dimension == 0),]$death - bs$subsetted_diag[which(bs$subsetted_diag$dimension == 0),]$birth) >= bs$thresholds[[1]]) } expect_true(min(bs$subsetted_diag[which(bs$subsetted_diag$dimension == 1),]$death - bs$subsetted_diag[which(bs$subsetted_diag$dimension == 1),]$birth) > bs$thresholds[[2]]) # check on circle bs <- bootstrap_persistence_thresholds(X = D,FUN_diag = "PyH",maxdim = 1,thresh = 2,return_diag = T,ripser = ripser,num_workers = 2,num_samples = 3) expect_lte(length(bs$subsetted_diag$dimension),1) bs <- bootstrap_persistence_thresholds(X = D,FUN_diag = "PyH",maxdim = 1,thresh = 2,return_diag = T,ripser = ripser,ignore_infinite_cluster = F,num_workers = 2,num_samples = 3) expect_lte(length(bs$subsetted_diag$dimension),2) })