Open karthikgou opened 1 year ago
Steps to reproduce:
1 Run the evaluation code with rds dataset 2 You will encounter the error below Error: Quitting from lines 177-207 [Results] (evaluation.Rmd) oscb_worker2 | oscb_worker2 | Error in dplyr::select(): oscb_worker2 | ! Can't subset columns that don't exist. oscb_worker2 | ✖ Column trueclass doesn't exist. oscb_worker2 | Backtrace: oscb_worker2 | 1. ... %>% ... oscb_worker2 | 6. dplyr:::select.data.frame(., dataset, method, cell, run, k, resolution, cluster, trueclass)
dplyr::select()
trueclass
Error occurred in the below code
assignments <- do.call(rbind, lapply(L, function(w) w$assignments)) timings <- do.call(rbind, lapply(L, function(w) w$timings)) k_estimates <- do.call(rbind, lapply(L, function(w) w$k_estimates))
assignments$trueclass <- sce_data$Tru_lab$majorType[match(assignments$cell, sce_data$Tru_lab$X)]
res <- list(assignments = assignments, timings = timings, k_estimates = k_estimates)
df <- dplyr::full_join(res$assignments %>% dplyr::select(dataset, method, cell, run, k, resolution, cluster, trueclass), res$k_estimates %>% dplyr::select(dataset, method, run, k, resolution, est_k) ) %>% dplyr::full_join(res$timings %>% dplyr::select(dataset, method, run, k, resolution, elapsed))
Dataset used to run the evaluation code: tung (1).zip
Steps to reproduce:
1 Run the evaluation code with rds dataset 2 You will encounter the error below Error: Quitting from lines 177-207 [Results] (evaluation.Rmd) oscb_worker2 | oscb_worker2 | Error in
dplyr::select()
: oscb_worker2 | ! Can't subset columns that don't exist. oscb_worker2 | ✖ Columntrueclass
doesn't exist. oscb_worker2 | Backtrace: oscb_worker2 | 1. ... %>% ... oscb_worker2 | 6. dplyr:::select.data.frame(., dataset, method, cell, run, k, resolution, cluster, trueclass)Error occurred in the below code
assignments <- do.call(rbind, lapply(L, function(w) w$assignments)) timings <- do.call(rbind, lapply(L, function(w) w$timings)) k_estimates <- do.call(rbind, lapply(L, function(w) w$k_estimates))
assignments$trueclass <- sce_data$Tru_lab$majorType[match(assignments$cell, sce_data$Tru_lab$X)]
res <- list(assignments = assignments, timings = timings, k_estimates = k_estimates)
df <- dplyr::full_join(res$assignments %>% dplyr::select(dataset, method, cell, run, k, resolution, cluster, trueclass), res$k_estimates %>% dplyr::select(dataset, method, run, k, resolution, est_k) ) %>% dplyr::full_join(res$timings %>% dplyr::select(dataset, method, run, k, resolution, elapsed))