STARE_Overview

Basic tutorial for STARE

Tested Systems

MacOS

OS              : macOS 15.4 (24E248) Sequoia
    Kernel      : Darwin 24.4.0
    Architecture: arm64 (Little Endian)

    Model       : MacBook Pro (16-inch, 2021) (MacBookPro18,2)
    CPU         : Apple M1 Max @ 3.20GHz x 10 cores
    RAM         : 32GB LPDDR5-6400 MHz (unified memory, GPU can use)
    GPU         : Apple M1 Max 32 cores (4,096 Arithmetic Logic Units (ALUs))
    HD:         : 1 TB

    Shell       : bash 5.2.37
    clang       : 17.0.0 (clang-1700.0.13.3)
    XCode       : 16.3
    Homebrew    : Homebrew 4.4.27
    Conda       : conda 25.3.0
                    base                     /Users/mbauer/miniconda3                   Python 3.12.4
                    stare                 *  /Users/mbauer/miniconda3/envs/stare        Python 3.13.2

Linux

OS              : Ubuntu 24.04.2 LTS (Noble Numbat)
    Kernel      : 6.8.0-57-generic
    Architecture: x86_64 (Little Endian)

    Model       : HP OMEN by HP Obelisk Desktop 875-1xxx
    CPU         : Intel i7-9700K @ 3.60GHz x 8 cores (512 KB L1. 2 MB L2 and 12 MB L3 Caches)
    RAM         : 64 GB DDR4-2666 MHz (4 x 16 GB)
    GPU         : NVIDIA GeForce RTX 2080 SUPER
                    CUDA Cores           : 3072
                    Total Memory         : 8192 MB
                    CUDA Toolkit         : 12.0
    HD:         : 6.5 TB

    Shell       : bash 5.2.21
    gcc         : 13.3.0
    Conda       : conda 25.3.0
                    base                     /home/mbauer/miniconda3                   Python 3.12.7
                    stare                 *  /home/mbauer/miniconda3/envs/stare        Python 3.12.7

Windows

OS              : Windows 11 v24H2
    Model       : HP OMEN by HP Obelisk Desktop 875-1xxx

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Basic Requirements

• Python 3 (tested up to 3.13.2)
• CMake (tested with 4.0.0)
• C++ Compiler (tested with clang 17.0.0 and gcc 13.3.0)
• Conda (tested with 25.3.0)
  • Key packages
    • cartopy 0.24.0
    • cython 3.0.12
    • dask 2025.3.0
    • geopandas 1.0.1
    • matplotlib 3.10.1
    • netcdf4 1.7.2
    • numpy 2.2.4
    • pandas 2.2.3
    • pyshp 2.3.1
    • shapely 2.0.7
    • swig 4.3.0
    • xarray 2025.3.1
    • yaml 0.2.5
    • zarr 3.0.6

Install STARE, pySTARE and STAREPandas and Jupyter Lab:

We recommend installing using conda (or miniconda). Please see Conda installation instructions.

Below are the steps to install STARE, pySTARE, and STAREPandas with conda. We also recommend installing JupyterLab (or Jupyter Notebook). Then, set up this conda environment as a kernel for this notebook so that you can use all the libraries without any further installation.

1. STARE and pySTARE installation

2. STAREPandas installation

3. JupyterLab & Tmux & install STARE kernel:

Tmux:

    $ conda install -c conda-forge tmux

JupyterLab:

    $ conda install -c conda-forge jupyterlab

Setting up the stare kernel for jupyter lab

    $ conda create -n stare
    $ conda env list
    $ conda activate stare
    $ conda install -c conda-forge ipykernel
    $ python -m ipykernel install --user --name=stare
    $ conda deactivate stare

Run jupyter Lab

  $ tmux new -s stareLab
  (or if stareLab session if already exists) $ tmux a -t stareLab
  $ jupyter lab --ip 0.0.0.0 --no-browser --allow-root
  (Take the token from the console: e.g: 2ba47a5fb63ba45d442443db94b03d111e5cabcbb3cb3edc)
  
  (Log out from tmux session by:)
  $ Ctrl + B
  $ D

Connect to your localhost jupyter Lab

• From the web browser: [your-machine-public-ip-address]:8888
• E.g: http://127.0.0.1:8888 or localhost:8888
• Use the token above to login or set up a new password for your jupyter lab
• Download *.ipynb to your notebook
• Run the *.ipynb