lapack | Wrappers for LAPACK | Wrapper library

I actually attempted this earlier today and these are the steps I used:

• In the site.cfg file, put

This is an open issue with dplyr: https://github.com/tidyverse/dplyr/issues/6138

To paraphrase the discussion in the GitHub issue: The problem is caused by cur_data() including the previously summarised column (in this case, mean), without it having been recycled to match the number of rows in the data frame. That makes cur_data() essentially a malfromed data frame.

In your case, using as.data.frame() solves the problem because it does the recycling to make mean match the rest of the columns in length, and having the statements in a different order solves the problem because at that point cur_data() doesn’t include any new columns yet.

Perhaps my failed attempts will help someone else solve this problem; my approach:

• boot up a clean CentOS 7 vm
• install R and some dependencies

Currently (2022-02-05), CRAN builds R binaries for Apple silicon using Apple clang (from Command Line Tools for Xcode 12.4) and an experimental build of gfortran.

If you obtain R from CRAN (i.e., here), then you need to replicate CRAN's compiler setup on your system before building R packages that contain C/C++/Fortran code from their sources (and before using Rcpp, etc.). This requirement ensures that your package builds are compatible with R itself.

A further complication is the fact that Apple clang doesn't support OpenMP, so you need to do even more work to compile programs that make use of multithreading. You could circumvent the issue by building R itself and all R packages from sources with LLVM clang, which does support OpenMP, but this approach is onerous and "for experts only". There is another approach that has been tested by a few people, including Simon Urbanek, the maintainer of R for macOS. It is experimental and also "for experts only", but seems to work on my machine and is simpler than trying to build R yourself.

Warning: These instructions come with no warranty and could break at any time. They assume some level of familiarity with C/C++/Fortran program compilation, Makefile syntax, and Unix shells. As usual, sudo at your own risk.

I will try to address compilers and OpenMP support at the same time. I am going to assume that you are starting from nothing. Feel free to skip steps you've already taken, though you might find a fresh start helpful.

I've tested these instructions on a machine running Big Sur, and at least one person has tested them on a machine running Monterey. I would be glad to hear from others.

1. Download an R binary from CRAN here and install. Be sure to select the binary built for Apple silicon.

2. Run

I think you might be slightly overcomplicating things. Ideally, you'd just want a single key drawing method for the whole layer. However, because you're using a Stat to do the majority of calculations, this becomes hairy to implement. In my answer, I'm avoiding this.

Let's say I'd want to use a geom-only implementation of such a layer. I can make the following (simplified) class/constructor pair. Below, I haven't bothered width_scale or height_scale parameters, just for simplicity.

Finally I found the solution:

Since both system has the arch and OS. I cross copied the R compiled installations between them. The R which was compiled on the problematic system, but was run on the correct one gave the warnings below after the calling of the install.packages("renv", repos="https://cran.wu.ac.at/")

As has been commented, There seems to be an issue with flexdashboard in R 4.1. It does work (on MacOS) with R 3.6. I'd suggest filing an issue on their GitHub repo.

Besides downgrading R, you could also "automatically" zoom in at the beginning and use flyTo() instead of setView().

Both solutions are rather hot fixes but I am afraid that the core problem must be fixed by flexdashboard itself.

As others have stated, Python 3.10 is not currently compatible with Matplotlib. You need to install and use Python 3.9 until it is supported. Until then you have a few options:

You can use the Python Launcher for Windows (py.exe) script to choose which Python version to run like so:

py.exe script help: py -h

List all installed versions py -0

Use a specified version py -3.9

e.g. 1 Create a virtual environment using python 3.9 py -3.9 venv .venv

e.g. 2 install matplotlib with pip using python 3.9 py -3.9 -m pip install matplotlib

On Linux you can run whatever Python version you like like so:

python3.9

You can set up a local (your working directory and all sub-directories) virtual environment that will use your specified version like so:

python3.9 -m venv .venv

Which will set the version of python used to 3.9 while in the local directory, and allow you to type python instead of python3.9 each time you need it.

Another relevant and helpful post by Rotareti here.

Please note that I have not described how to activate and use Python Virtual Environments here in detail, for more information on using them read the python docs.

Reference this answer if you're interested in installing a matplotlib release candidate.

In scipy's PyPI page, it looks like scipy doesn't support 3.10 as the meta says