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Minimum version of Scikit-learn dependencies are listed below along with itsįor installing on PyPy, PyP圓-v5.10+, Numpy 1.14.0+, and scipy 1.1.0+Īre required. Matplotlib and some examples require scikit-image, pandas, or seaborn. Scikit-learn plotting capabilities (i.e., functions start with “plot_”Īnd classes end with “Display”) require Matplotlib. Particular configurations of operating system and hardware (such as Linux on When using pip, please ensure that binary wheels are used,Īnd NumPy and SciPy are not recompiled from source, which can happen when using If you have not installed NumPy or SciPy yet, you can also install these usingĬonda or pip. Prior to running any Python command whenever you start a new terminal session.
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Note that you should always remember to activate the environment of your choice Package manager of the distribution (apt, dnf, pacman…). In particular under Linux is itĭiscouraged to install pip packages alongside the packages managed by the Version of scikit-learn with pip or conda and its dependencies independently ofĪny previously installed Python packages. Using such an isolated environment makes it possible to install a specific Strongly recommended to use a virtual environment (venv) or a conda environment. Note that in order to avoid potential conflicts with other packages it is This tutorial has been successfully tested in Safari, Google Chrome and Mozilla Firefox.Python3 -m pip show scikit-learn # to see which version and where scikit-learn is installed python3 -m pip freeze # to see all packages installed in the active virtualenv python3 -c "import sklearn sklearn.show_versions()" python -m pip show scikit-learn # to see which version and where scikit-learn is installed python -m pip freeze # to see all packages installed in the active virtualenv python -c "import sklearn sklearn.show_versions()" python -m pip show scikit-learn # to see which version and where scikit-learn is installed python -m pip freeze # to see all packages installed in the active virtualenv python -c "import sklearn sklearn.show_versions()" python -m pip show scikit-learn # to see which version and where scikit-learn is installed python -m pip freeze # to see all packages installed in the active virtualenv python -c "import sklearn sklearn.show_versions()" conda list scikit-learn # to see which scikit-learn version is installed conda list # to see all packages installed in the active conda environment python -c "import sklearn sklearn.show_versions()".To access the notebook, open this file in a browser:įile:///home/USER/.local/share/jupyter/runtime/nbserver-29420-open.html Use Control-C to stop this server and shut down all kernels (twice to skip confirmation). Serving notebooks from local directory: /home/USER/projects/BioBB/tutorials If this is not the case, copy all the address provided by Jupyter Notebook (with the long token included) and copy it to your browser: When launching the above instruction the default browser is automatically launched. Jupyter Notebook is a web-based interactive computational environment.Jupyter-notebook biobb_wf_md_setup/notebooks/biobb_MDsetup_tutorial.ipynb Jupyter-nbextension enable -py -user nglview Jupyter-nbextension enable -py -user widgetsnbextension In some distributions, conda activate instruction doesn't work. Once it's done, let's activate the environment: The creation of the environment will take some minutes.
#MAC INSTALL JUPYTER DOWNLOAD#
First off, download the tutorial cloning the project in your computer:Ĭonda env create -f conda_env/environment.yml.As an exemple we have taken the Protein MD Setup tutorial: Go to the tutorial and follow the instructions. If not, go to the next link and install it: If you have Git installed (to test it, just type git in your terminal), please skip this step.
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If it doesn't work, the path must be exported:Įxport PATH=/home/USER/anaconda3/bin:$PATH