camaralab / rayleighselection Goto Github PK

Hi,

I cloned the repo and tried to run the examples as they are without changing them, but they don't work.

1. In the mnist_example.Rmd for the following step

m2 <- mapper2D(distance_matrix = mnist_distances,
                filter_values = list(emb@data@data[,1], emb@data@data[,2]),
                num_intervals = c(30,30),
                percent_overlap = 35,
                num_bins_when_clustering = 10);

I get the following error:
Error in vertices_in_level[[k1]] : subscript out of bounds

2. Regarding the vr_cycle_example.Rmd in the last line of code

(scores[order(scores$R1, scores$R0),])[1:5,]

I get the following error
Error in order(scores$R1, scores$R0) : argument 1 is not a vector

In this case seems that scores doesn't have R1

> head(scores)
                     R0    p0        q0
0610007P14Rik 1.0076786 0.323 0.5204212
0610009O20Rik 0.9974801 0.201 0.3855278
0610010F05Rik 0.7698217 0.000 0.0000000
0610010K14Rik 0.9990372 0.203 0.3884544
0610011F06Rik 0.9924835 0.132 0.2933002
0610037L13Rik 0.9924345 0.130 0.2901680

OS: Ubuntu 20.04.2 LTS
R version 4.1.0 (2021-05-18)

Dear Developers,

I was attracted by your article in Plos One and wanted to try the approach on some proteomics data. However, I've got a problem when installing the package (s. the error message below). I am using R version 3.5.0 (2018-04-23) on platform: x86_64-w64-mingw32/x64 (64-bit) running under: Windows 10 x64 (build 17134).

Thank you for your help!

Best,
Ivan

`
devtools::install_github("CamaraLab/RayleighSelection")
Downloading GitHub repo CamaraLab/RayleighSelection@master
These packages have more recent versions available.
Which would you like to update?
1: All
2: CRAN packages only
3: None
4: igraph (1.2.4.1 -> 1.2.4.2) [CRAN]

Enter one or more numbers, or an empty line to skip updates:

√ checking for file 'C:\Users\IS\AppData\Local\Temp\RtmpENCvNJ\remotes19e88474a1a\CamaraLab-RayleighSelection-4d99000/DESCRIPTION' (516ms)

• preparing 'RayleighSelection':
  √ checking DESCRIPTION meta-information ...
• cleaning src
• checking for LF line-endings in source and make files and shell scripts (811ms)
• checking for empty or unneeded directories
• looking to see if a 'data/datalist' file should be added
• building 'RayleighSelection_0.0.0.9000.tar.gz' (708ms)

• installing source package 'RayleighSelection' ...
  ** libs

*** arch - i386
C:/Rtools/mingw_32/bin/g++ -I"C:/PROGRA1/R/R-351.0/include" -DNDEBUG -I"C:/Program Files/R/R-3.5.0/library/Rcpp/include" -I"C:/Program Files/R/R-3.5.0/library/RcppArmadillo/include" -fopenmp -O3 -Wno-unused-variable -Wno-unused-function -c RcppExports.cpp -o RcppExports.o
C:/Rtools/mingw_32/bin/g++ -I"C:/PROGRA1/R/R-351.0/include" -DNDEBUG -I"C:/Program Files/R/R-3.5.0/library/Rcpp/include" -I"C:/Program Files/R/R-3.5.0/library/RcppArmadillo/include" -fopenmp -O3 -Wno-unused-variable -Wno-unused-function -c adjacency.cpp -o adjacency.o
adjacency.cpp:9:28: error: '>>' should be '> >' within a nested template argument list
std::vector<std::vector> combo(int N, int K)
^
adjacency.cpp: In function 'std::vector<std::vector<int, std::allocator > > combo(int, int)':
adjacency.cpp:13:30: error: '>>' should be '> >' within a nested template argument list
std::vector<std::vector> combos;
^
adjacency.cpp: In function 'Rcpp::List adjacencyCpp(Rcpp::List, Rcpp::IntegerVector&)':
adjacency.cpp:86:36: error: '>>' should be '> >' within a nested template argument list
std::vector<std::pair<int, double>> feature_index_mean;
^
adjacency.cpp:99:65: error: 'get' is not a member of 'std'
(const int& ()(const std::pair<int, double>&))std::get<0>);
^
adjacency.cpp:99:76: error: expected primary-expression before ')' token
(const int& ()(const std::pair<int, double>&))std::get<0>);
^
adjacency.cpp:161:32: error: '>>' should be '> >' within a nested template argument list
std::vector<std::vector> edge_idxs = combo(idxs.size(), 2);
^
adjacency.cpp:163:13: error: expected unqualified-id before '&&' token
for(auto&& e : edge_idxs)
^
adjacency.cpp:163:13: error: expected ';' before '&&' token
adjacency.cpp:163:18: error: expected ';' before ':' token
for(auto&& e : edge_idxs)
^
adjacency.cpp:163:18: error: expected primary-expression before ':' token
adjacency.cpp:163:18: error: expected ')' before ':' token
adjacency.cpp:163:18: error: expected primary-expression before ':' token
adjacency.cpp:163:16: error: label 'e' used but not defined
for(auto&& e : edge_idxs)
^
make: *** [C:/PROGRA1/R/R-351.0/etc/i386/Makeconf:215: adjacency.o] Error 1
ERROR: compilation failed for package 'RayleighSelection'

• removing 'C:/Program Files/R/R-3.5.0/library/RayleighSelection'
  In R CMD INSTALL
  Error: Failed to install 'RayleighSelection' from GitHub:
  installation of package ‘C:/Users/IS/AppData/Local/Temp/RtmpENCvNJ/file19e8164e5246/RayleighSelection_0.0.0.9000.tar.gz’ had non-zero exit status
  `

For very large networks (with thousands of nodes), the directed force layouts implemented in the R package igraph are not efficient and the network visualizations produced by plot_skeleton() become messy. Is it possible to better represent very large networks in R using directed force layouts?

We should have the option to build weighted nerve complexes using Jaccard distances between open sets of the cover. To that end, we would include a Boolean option weight in the function nerve_complex() such that when weight=TRUE, instead of 1's in the entries of the adjacency matrix we use Jaccard distances (see https://en.wikipedia.org/wiki/Jaccard_index) between the open sets (nodes) connected by the edges. This should be implemented taking much care of the performance, so probably the best way to do it is at the level of the C++ code adjacencyCpp. To evaluate changes in performance please use the R package microbenchmark. By default, we should set weight=TRUE in nerve_complex().