Hi,

the documentation of hopach says that the result of the distancevector and distancematrix functions should be "identical". However, that is not the case.

This is the example in the documentation:

mydata<-matrix(rnorm(50),nrow=10)
deuclid<-distancematrix(mydata,d="euclid")
# old method vdeuclid<-dissvector(deuclid)
vdeuclid<-deuclid@Data
ddaisy<-daisy(mydata)
vdeuclid ddaisy/sqrt(length(mydata[1,]))

d1<-distancematrix(mydata,d="abscosangle")
d2<-distancevector(mydata,mydata[1,],d="abscosangle")
d1[1,] d2 #equal to d1[1,]

However, at least since hopach-2.50, the results of distancevector apply also the extra step used in "ddaisy/sqrt(length(mydata[1,]))"

> mydata<-matrix(rnorm(50),nrow=10)
> deuclid<-distancematrix(mydata,d="euclid")
> vdeuclid<-deuclid@Data
> ddaisy<-daisy(mydata)
> vdeuclid[1:10]
 [1] 3.534428 2.764194 4.274093 4.037899 1.942037 5.592038 2.539513 1.451171 4.565247 1.354340
> ddaisy/sqrt(length(mydata[1,]))[1]
Dissimilarities :
           1         2         3         4         5         6         7         8         9
2  1.5806443                                                                                
3  1.2361851 0.6056791                                                                      
4  1.9114325 0.7752572 0.9199244                                                            
5  1.8058033 1.3887343 1.4681481 1.3347749                                                  
6  0.8685054 1.2025777 0.9410266 1.7518570 1.6624963                                        
7  2.5008355 2.0364315 2.2338201 2.4665746 1.8328549 1.8465481                              
8  1.1357047 0.9515974 0.8468085 1.1752720 0.8702290 0.9018104 1.7221714                    
9  0.6489835 1.4214805 0.9261624 1.6151358 1.7102315 0.8523305 2.4401483 0.9605887          
10 2.0416405 2.1729064 2.0948553 2.2511179 1.4792959 1.8247131 1.5366251 1.3427259 1.8488145

Metric :  euclidean 
Number of objects : 10
> d1<-distancematrix(mydata,d="euclid")
> d2<-distancevector(mydata,mydata[1,],d="euclid")
> d1[1,]
  1        2        3        4        5        6        7        8        9       10
1 0 3.534428 2.764194 4.274093 4.037899 1.942037 5.592038 2.539513 1.451171 4.565247
> d2
 [1] 0.0000000 1.5806443 1.2361851 1.9114325 1.8058033 0.8685054 2.5008355 1.1357047 0.6489835 2.0416405
> d1[1,]/sqrt(length(mydata[1,]))
  1        2        3        4        5         6        7        8         9       10
1 0 1.580644 1.236185 1.911433 1.805803 0.8685054 2.500836 1.135705 0.6489835 2.041641

Is this the intended behavior? Shouldn't both distancevector and distancematrix return the same without adding an extra step?? Since when is this happening?

Thanks,

Txema

> sessionInfo()
R version 4.1.2 (2021-11-01)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Mojave 10.14.6

Matrix products: default
BLAS:   /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRlapack.dylib

Random number generation:
 RNG:     Mersenne-Twister 
 Normal:  Inversion 
 Sample:  Rounding 

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] hopach_2.54.0       Biobase_2.54.0      BiocGenerics_0.40.0 cluster_2.1.2       sfsmisc_1.1-12     
 [6] pheatmap_1.0.12     gridExtra_2.3       ggplot2_3.3.5       SeuratObject_4.0.4  Seurat_4.1.0       
[11] MASS_7.3-55         Matrix_1.4-0       

loaded via a namespace (and not attached):
 [1] nlme_3.1-155          spatstat.sparse_2.1-0 matrixStats_0.61.0    RcppAnnoy_0.0.19      RColorBrewer_1.1-2   
 [6] httr_1.4.2            sctransform_0.3.3     tools_4.1.2           utf8_1.2.2            R6_2.5.1             
[11] irlba_2.3.5           rpart_4.1.16          KernSmooth_2.23-20    uwot_0.1.11           mgcv_1.8-38          
[16] lazyeval_0.2.2        colorspace_2.0-2      withr_2.4.3           tidyselect_1.1.1      compiler_4.1.2       
[21] cli_3.2.0             plotly_4.10.0         scales_1.1.1          spatstat.data_2.1-2   lmtest_0.9-39        
[26] ggridges_0.5.3        pbapply_1.5-0         goftest_1.2-3         stringr_1.4.0         digest_0.6.29        
[31] spatstat.utils_2.3-0  pkgconfig_2.0.3       htmltools_0.5.2       parallelly_1.30.0     fastmap_1.1.0        
[36] htmlwidgets_1.5.4     rlang_1.0.1           shiny_1.7.1           generics_0.1.2        zoo_1.8-9            
[41] jsonlite_1.7.3        spatstat.random_2.1-0 ica_1.0-2             dplyr_1.0.8           magrittr_2.0.2       
[46] patchwork_1.1.1       Rcpp_1.0.8            munsell_0.5.0         fansi_1.0.2           abind_1.4-5          
[51] reticulate_1.24       lifecycle_1.0.1       stringi_1.7.6         Rtsne_0.15            plyr_1.8.6           
[56] grid_4.1.2            parallel_4.1.2        listenv_0.8.0         promises_1.2.0.1      ggrepel_0.9.1        
[61] crayon_1.5.0          deldir_1.0-6          miniUI_0.1.1.1        lattice_0.20-45       cowplot_1.1.1        
[66] splines_4.1.2         tensor_1.5            pillar_1.7.0          igraph_1.2.11         spatstat.geom_2.3-2  
[71] future.apply_1.8.1    reshape2_1.4.4        codetools_0.2-18      leiden_0.3.9          glue_1.6.1           
[76] data.table_1.14.2     BiocManager_1.30.16   png_0.1-7             vctrs_0.3.8           httpuv_1.6.5         
[81] polyclip_1.10-0       gtable_0.3.0          RANN_2.6.1            purrr_0.3.4           spatstat.core_2.4-0  
[86] tidyr_1.2.0           scattermore_0.8       future_1.23.0         mime_0.12             xtable_1.8-4         
[91] later_1.3.0           survival_3.2-13       viridisLite_0.4.0     tibble_3.1.6          globals_0.14.0       
[96] fitdistrplus_1.1-6    ellipsis_0.3.2        ROCR_1.0-11