In Atom Platformio-IDE-Terminal I'm trying to set the environment but it shows this error
> `ERROR: The install method you used for conda--probably either `pip
> install conda` or `easy_install conda`--is not compatible with using
> conda as an application. If your intention is to install conda as a
> standalone application, currently supported install methods include
> the Anaconda installer and the miniconda installer. You can download
> the miniconda installer from https://conda.io/miniconda.html.`
Usual terminal working perfectly, what is the problem?
Related
I used to work in R 3.4.0 version. Hovewer, this version doesn't support such packages as keras and tensorflow.
I was adviced to upgrade my R version to the newest one.
I downloaded the most recent R version 4.0.2 from the official site, then ran the following code:
install.packages("keras")
library(keras)
install_keras()
And got the following error:
Error in install_keras() :
You should call install_keras() only in a fresh R session that has not yet initialized Keras and TensorFlow (this is to avoid DLL in use errors during installation)
After this, when I tried to quit R session by q() , I faced the following error:
Error: option error has NULL value
Error: no more error handlers available (recursive errors?); invoking 'abort' restart
Error: option error has NULL value
I've never faced such an error before. When I used old R version, I typed q() and then had to choose between y and n. No errors appeared.
I'm asking you to help to to solve this problem.
You need to create a new environment and then you can install R 4.+ in Anaconda. Follow these steps.
conda create --name r4-base
After activating r4-base run these commands
conda activate r4-base
conda install -c conda-forge r-base
conda install -c conda-forge/label/gcc7 r-base
Finally, you will notice r-basa version 4 will be installed.
Thereafter, you can install any supported packages. But with this only, you won't have the ability to use it in the Jupyter notebook. You need to install install.packages('IRkernel') and Jupyter notebook as well if you want to use it. Otherwise you are good to go with R-Studio.
For Jupyter Installation and RKernel.
conda install jupyter
Then open the R console. Write in R console
install.packages('IRkernel')
IRkernel::installspec()
Congrats! You can use Notebook for Python and R.
Find the location of R.exe on your computer. In my computer, this executable is at
C:\Program Files\R\R-3.4.3\bin
Open another Anaconda Prompt as Administrator and change directories to wherever R.exe is on your computer with cd file path. On my computer, it’s cd C:\Program Files\R\R-3.4.3\bin, but it might be different for you.
Then run R from within Anaconda Prompt in Admin mode with R.exe
You’ll notice that you’re in an R session. From here, run the following three commands into the terminal.
install.packages("devtools")
devtools::install_github("IRkernel/IRkernel")
IRkernel::installspec()
In order, they (1) install the devtools package which gets you the install_github() function, (2) install the IR Kernel from GitHub, and (3) tell Jupyter where to find the IR Kernel.
Open Jupyter notebook and enjoy your new R kernel!
Get more information here
#Rheatey Bash works perfectly. but i was facing python.exe this program cant start because api-ms-win-core-path-l1-1-0.dll python system error. this is a problem running on windows 7 but i resolved this issue by installing the kernel following https://richpauloo.github.io/2018-05-16-Installing-the-R-kernel-in-Jupyter-Lab/ and it works fine
I'm facing difficulties downloading the r package rsvg. I created first an environment with conda for the latest R version 4.0.2 following these instructions. I was able to download many other R packages & bioconductor packages without problem, however, this one produces huge pile of lines while configuring it and ends with errors downloadind its dependencies (systemfonts, stringi, stringr, gdtools, magick, svglite, knitr). My exact command is install.packages("rsvg", dependencies =T). Trying to download each of those packages produced also a tree of required dependencies (with configuration fail at the end of each).
Among the lines I noticed this error /user/include/freetype2/freetype/config/ftheader.h:3:12: fatal error x86_64-linux-gnu/freetype2/config/fthreader.h no such file or directory which make me suspect that my R installation is incopmlete or corrupted. I tested it with other R versions (e.g. R 3.6.0) yet the same error appear. Installing it on windows (Rstudio 3.6.2) also didn't work, and now I'm wondering if this package needs to be installed differently or it is system related problem? Any help would be highly appreciated
You need to create a new environment and then you can install R 4.+ in Anaconda. Follow these steps.
conda create --name r4-base
After activating r4-base run these commands
conda install -c conda-forge r-base
conda install -c conda-forge/label/gcc7 r-base
Finally, you will notice r-basa version 4 will be installed.
Thereafter, you can install any supported packages. But with this only, you won't have the ability to use it in the Jupyter notebook. You need to install install.packages('IRkernel') and Jupyter notebook as well if you want to use it. Otherwise you are good to go with R-Studio.
For Jupyter Installation and RKernel.
conda install jupyter
Then open the R console. Write in R console
install.packages('IRkernel')
IRkernel::installspec()
Congrats! You can use Notebook for Python and R.
I first encountered the error referenced here:
Installing rpy2 on windows
which is that I couldn't install rpy2 because '.sh' isn't recognized by the default windows terminal as a command. To get around that, I'm using a Git Bash terminal, but then I get the error mentioned here:
Installing the R interpeter and R as a shared library uder the same tree
However, the solution in that post is for a Linux install only (I think).
As I understood that post, I should navigate to the bin/ directory in R and run ./configure (which doesn't exist in my directory). Any thoughts on how to fix this error for a Windows install?
I am trying to create a deb package for my qt project to install on my sama5d3. I am using Ubuntu 14.04 64bit. have managed to create it for armhf. but when I try to install it on the board it fail with "incompatible architecture".
so I search for the architecture and find it is armv7ahf-vfp. how can I build a package for that architecture?
ok I found how to build for armv7ahf-vfp.. just run the poky environment setup script :
source /environment-setup-cortexa5t2hf-vfp-neon-poky-linux-gnueabi
I had Tensorflow installed with Anaconda. Now I want use it in R and I need to reinstall Tensorflow, because the note here
NOTE: You should NOT install TensorFlow with Anaconda as there are
issues with the way Anaconda builds the python shared library that
prevent dynamic linking from R.
I already tried to uninstall from Anaconda and install with pip but its came to the same place in anaconda directory. Tesorflow is working from terminal but in R shows Error: Command failed (1)
Anybody can help me to how I can solve the problem? Should I uninstall anaconda and install Tensorflow using pip?
You have several options on what to do. Probably the cleanest one is to install a system-wide python (if not installed yet) and then create a virtual environment. This basically takes your system python binaries and moves them to its own compartment where everythign is isolated from the rest, incl. anaconda. Once you are inside an activated virtual environment you can install all the necessary Python appendages for TensorFlow. Once that is done, make sure you set up a correct environmental PATH for TensorFlow from where R can reach it:
Sys.setenv(TENSORFLOW_PYTHON="/path/to/virtualenv/python/binary")
devtools::install_github("rstudio/tensorflow")
Example of the path to where you installed the virtual environment project would be, I think, something like ~/minion/medvedi/venv_medvedi/bin/python.
This is no longer an issue, the documentation was updated too.
See here:
https://github.com/rstudio/tensorflow/commit/4e1e11d6ba2fe7efe1a03356f96172dbf8db365e
With the help of Keras, we can install the TensorFlow package in R.
install_keras()
library(keras)
devtools::install_github("rstudio/keras")
install_tensorflow(package_url = "https://pypi.python.org/packages/b8/d6/af3d52dd52150ec4a6ceb7788bfeb2f62ecb6aa2d1172211c4db39b349a2/tensorflow-1.3.0rc0-cp27-cp27mu-manylinux1_x86_64.whl#md5=1cf77a2360ae2e38dd3578618eacc03b")
library(tensorflow)
Keras is a high-level neural network API for deep learning from TensorFlow Google.
my suggestion is to install anaconda and create an environment called "r-reticulate".
you can do it using anaconda navigator or
reticulate::conda_create(envname = "r-reticulate")
then to check that env detected by reticulate, use reticulate::conda_python().it must return directory of python.exe for your env.
after that you can install tensorflow by install_tensorflow(). [not working in my case]
so I install the tesnorflow from CMD.
follow these steps:
open the cmd :]
activate the r-reticulate env using conda activate r-reticulate (you may need your directory to conda directory if you did not add conda to your PATH)
use : conda install -c anaconda tensorflow
now in R, you can use TensorFlow.
for installing Keras, you can use pip install Keras. [i tried install_keras() function after the installation of tensorflow, but it ruined my TensorFlow installation also]
Eventually I found the best and fast method to do it in R:
devtools::install_github("rstudio/keras")
library(keras)
install_keras(method = "conda")
install_keras(tensorflow = "gpu")
tensorflow::install_tensorflow()