DiceR::ivi_table returns wrong format

[mattpaletta]

This code fixes the issue (as.dataframe + transpose), change as you see fit in diceR.

ivi_table <- function(cl.df, data) {
  ndata <- apply(data, 2, function(x) as.numeric(as.character(x)))
  data.frame(
    Algorithms = colnames(cl.df),
    cl.df %>% purrr::map_df(
      clusterCrit::intCriteria,
      traj = ndata,
      crit = c("Calinski_Harabasz", "Dunn", "PBM", "Tau", "Gamma", "C_index",
               "Davies_Bouldin", "McClain_Rao", "SD_Dis", "Ray_Turi", "G_plus",
               "Silhouette", "S_Dbw")) %>% as.data.frame %>% t(.),
    Compactness = cl.df %>% purrr::map_dbl(compactness, data = data),
    Connectivity = cl.df %>% purrr::map_dbl(
      ~ clValid::connectivity(Data = ndata, clusters = .))
  ) %>%
    dplyr::mutate_all(dplyr::funs(structure(., names = colnames(cl.df))))

[dchiu911]

I'm not sure what the issue is, did you come across an error using the current diceR:::ivi_table()?

library(diceR)
library(magrittr)

# Consensus clustering for multiple algorithms
set.seed(911)
data <- matrix(rnorm(500), ncol = 10)
CC <- consensus_cluster(data, nk = 3:4, reps = 10, algorithms = c("ap", "km"),
progress = FALSE)

E <- abind::abind(list(CC), along = 3)
cl.mat <- consensus_combine(E, element = "class") %>%
  purrr::map(as.data.frame)

# Internal indices
ii <- cl.mat %>% purrr::map(diceR:::ivi_table, data = data)
ii
#> $`3`
#>     Algorithms calinski_harabasz      dunn       pbm       tau     gamma
#> 1 KM_Euclidean          6.045309 0.3600191 1.3893937 0.3577857 0.5190154
#> 2           AP          5.696644 0.3457346 0.8813185 0.2159109 0.3268007
#>     c_index davies_bouldin mcclain_rao    sd_dis ray_turi    g_plus
#> 1 0.2266867       2.228815   0.8216877 0.7217225 1.304566 0.1141910
#> 2 0.3184778       2.494521   0.8770018 0.6898195 1.560352 0.1468054
#>   silhouette s_dbw Compactness Connectivity
#> 1 0.07426715   NaN    4.004848     52.72937
#> 2 0.09232744   NaN    3.997723     48.54167
#> 
#> $`4`
#>     Algorithms calinski_harabasz      dunn       pbm       tau     gamma
#> 1 KM_Euclidean          6.357976 0.3471004 1.2763344 0.3269021 0.5134915
#> 2           AP          5.037927 0.3240620 0.8629581 0.2023128 0.3197935
#>     c_index davies_bouldin mcclain_rao    sd_dis  ray_turi     g_plus
#> 1 0.2274210       1.903901   0.8153465 0.6498983 0.9936387 0.09850874
#> 2 0.3280725       2.082346   0.8817180 0.6522639 1.2652438 0.13600773
#>   silhouette s_dbw Compactness Connectivity
#> 1 0.09587392   NaN    3.796956     47.43214
#> 2 0.09311465   NaN    3.869159     56.45198

ivi_table2 <- function(cl.df, data) {
  ndata <- apply(data, 2, function(x) as.numeric(as.character(x)))
  data.frame(
    Algorithms = colnames(cl.df),
    cl.df %>% purrr::map_df(
      clusterCrit::intCriteria,
      traj = ndata,
      crit = c("Calinski_Harabasz", "Dunn", "PBM", "Tau", "Gamma", "C_index",
               "Davies_Bouldin", "McClain_Rao", "SD_Dis", "Ray_Turi", "G_plus",
               "Silhouette", "S_Dbw")) %>% as.data.frame %>% t(.),
    Compactness = cl.df %>% purrr::map_dbl(compactness, data = data),
    Connectivity = cl.df %>% purrr::map_dbl(
      ~ clValid::connectivity(Data = ndata, clusters = .))
  ) %>%
    dplyr::mutate_all(dplyr::funs(structure(., names = colnames(cl.df))))
}

# Modified version
ii2 <- cl.mat %>% purrr::map(ivi_table2, data = data)
#> Error in data.frame(Algorithms = colnames(cl.df), cl.df %>% purrr::map_df(clusterCrit::intCriteria, : arguments imply differing number of rows: 2, 13

Created on 2018-05-23 by the reprex package (v0.2.0).