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| other:uvcdat:cdat_conda:cdat_2024_03 [2024/03/13 17:00] – created jypeter | other:uvcdat:cdat_conda:cdat_2024_03 [2025/04/09 16:48] (current) – [Extra packages list] Added NumExpr jypeter |
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| Read the next sections of this web page | Read the next sections of this web page |
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| There are some slight differences if you want to install this distribution: | There are some slight differences depending on how and where you want to install this distribution: |
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| * Only for you. This is the usual case. Well, if you break something you can always remove everything and start from scratch | * **Only for you**\\ This is the common case. Well, if you break something you can always remove everything and start from scratch |
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| * For sharing a stable version with several other people. You should be careful not to break the installion! | * For **sharing a stable version with several other people**\\ You should be careful not to break a shared installation! |
| | * Be extremely careful with packages that require downgrading other packages/dependencies (especially downgrading key packages like ''numpy'' and ''matplotlib''). |
| | * Try to avoid packages only based on ''pip'' |
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| The notes at the beginning of each section will tell you if you can skip the section if you are just installing for you | The notes at the beginning of each section will tell you if you can skip the section if you are just installing for you |
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| ===== What's New in CDAT 8.2.1? ===== | ===== What's New in JYP's 2024-03 distribution? ===== |
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| * [[https://github.com/CDAT/cdat/releases/tag/v8.2.1|8.2.1 announcement]] and features summary ([[https://github.com/UV-CDAT/uvcdat/releases|all versions]]) | * This is the first distribution not //tied// to CDAT packages |
| * Full [[https://uvcdat.llnl.gov/changelog.html#8.2.1|Change log]] | |
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| Note: this particular CDAT installation at LSCE (and on other machines/servers) provides **many extra (non-CDAT) packages**. You can jump directly to the [[#extra_packages_list|Extra package list]] at the bottom of this page, if you want to see what is available | * There are lots (and lots) of extra packages that all have their own history. You can always visit the [[#extra_packages_list|Extra package list]] on this page, to get news from individual packages |
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| ===== Installation with Miniconda3 ===== | ===== Installation with Miniconda3 ===== |
| ==== Installing Miniconda3 ==== | ==== Installing Miniconda3 ==== |
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| If //Miniconda3// is not already installed, or if you want to start over with a brand new version, read [[other:uvcdat:cdat_conda:miniconda3_install|JYP steps for installing Miniconda3]]. | If //Miniconda3// is not already installed, or if you want to start over with a brand new (or clean) version of //Miniconda3//, read [[other:uvcdat:cdat_conda:miniconda3_install|JYP steps for installing Miniconda3]]. |
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| ===== Extra packages list ===== | ===== Extra packages list ===== |
| | |
| | <note important> |
| | Do not forget to add the following packages to the future environments\\ \\ |
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| | |
| | * [[https://anaconda.org/conda-forge/cxx-compiler/|cxx-compiler]]: a metapackage to obtain a C++ compiler |
| | * [[https://f90nml.readthedocs.io/|f90nml]]: a Fortran namelist parser, generator, and editor |
| | * [[https://flake8.pycqa.org/en/stable/|flake8]]: your Tool For Style Guide Enforcement |
| | * [[https://loguru.readthedocs.io/|Loguru]]: a library which aims to bring enjoyable logging in Python |
| | * [[https://pythonot.github.io/|pot]]: Python Optimal Transport\\ This open source Python library provides several solvers for optimization problems related to Optimal Transport for signal, image processing and machine learning |
| | * [[https://pybind11.readthedocs.io/|pybind11]]: a lightweight header-only library that exposes C++ types in Python and vice versa |
| | * [[https://docs.astral.sh/ruff/|ruff]]: An extremely fast Python linter and code formatter, written in Rust |
| | * [[https://xrft.readthedocs.io/|xrft]]: Fourier transforms for xarray data |
| | * [[https://zarr.readthedocs.io/|zarr]]: a file storage format for chunked, compressed, N-dimensional arrays based on an open-source specification |
| | </note> |
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| FIXME: need to clean the list below, and move the packages to the ordered list further down | FIXME: need to clean the list below, and move the packages to the ordered list further down |
| * [[https://gitlab.com/remikz/nccmp|nccmp]]: compare two NetCDF files bitwise, semantically or with a user defined tolerance (absolute or relative percentage) | * [[https://gitlab.com/remikz/nccmp|nccmp]]: compare two NetCDF files bitwise, semantically or with a user defined tolerance (absolute or relative percentage) |
| * can probably also be done with [[https://code.mpimet.mpg.de/projects/cdo/embedded/index.html#x1-580002.1.3|cdo -v diffn file1.nc file2.nc]] | * can probably also be done with [[https://code.mpimet.mpg.de/projects/cdo/embedded/index.html#x1-580002.1.3|cdo -v diffn file1.nc file2.nc]] |
| | * [[https://github.com/pydata/numexpr|NumExpr]]: Fast numerical expression evaluator for NumPy |
| * [[https://opencv.org/|OpenCV]]: OpenCV (Open Source Computer Vision Library) is an open-source library that includes several hundreds of computer vision algorithms. See also [[https://www.geeksforgeeks.org/opencv-python-tutorial/|OpenCV Python Tutorial]] and **scikit-image** | * [[https://opencv.org/|OpenCV]]: OpenCV (Open Source Computer Vision Library) is an open-source library that includes several hundreds of computer vision algorithms. See also [[https://www.geeksforgeeks.org/opencv-python-tutorial/|OpenCV Python Tutorial]] and **scikit-image** |
| * [[https://openpyxl.readthedocs.io/|openpyxl]]: a Python library to read/write Excel 2010 ''xlsx''/''xlsm'' files | * [[https://openpyxl.readthedocs.io/|openpyxl]]: a Python library to read/write Excel 2010 ''xlsx''/''xlsm'' files |
| * see also ''python-kaleido'' and ''dash'' | * see also ''python-kaleido'' and ''dash'' |
| * [[https://www.fatiando.org/pooch/|pooch]]: a friend to fetch your data files (makes it easy to download a file, without messing with ''requests'' and ''urllib'') | * [[https://www.fatiando.org/pooch/|pooch]]: a friend to fetch your data files (makes it easy to download a file, without messing with ''requests'' and ''urllib'') |
| * [[https://proplot.readthedocs.io/en/latest/|proplot]]: a lightweight **matplotlib wrapper** for making beautiful, publication-quality graphics | * //proplot//: a lightweight matplotlib wrapper for making beautiful, publication-quality graphics |
| | * **Replaced by ''ultraplot''** |
| * [[https://psyplot.github.io/|psyplot]]: Interactive Data Visualization from Python and GUIs | * [[https://psyplot.github.io/|psyplot]]: Interactive Data Visualization from Python and GUIs |
| | * [[https://www.pygmt.org/latest/|PyGMT]]: a Python interface for the [[https://www.generic-mapping-tools.org/|Generic Mapping Tools]] |
| * [[https://github.com/jswhit/pygrib|pygrib]]: high-level interface to the ECWMF ECCODES C library for reading GRIB files | * [[https://github.com/jswhit/pygrib|pygrib]]: high-level interface to the ECWMF ECCODES C library for reading GRIB files |
| * see also ''eccodes'' and ''cfgrib'' | * see also ''eccodes'' and ''cfgrib'' |
| * [[https://anaconda.org/anaconda/tensorflow-mkl|tensorflow-mkl]] will install the **CPU**-based (**not GPU**) version | * [[https://anaconda.org/anaconda/tensorflow-mkl|tensorflow-mkl]] will install the **CPU**-based (**not GPU**) version |
| * [[https://github.com/tqdm|tqdm]]: make your loops show a smart progress meter | * [[https://github.com/tqdm|tqdm]]: make your loops show a smart progress meter |
| | * [[https://ultraplot.readthedocs.io/en/latest/|UltraPlot]]: a succinct matplotlib wrapper for making beautiful, publication-quality graphics |
| * [[https://uxarray.readthedocs.io/|uxarray]]: provide xarray styled functionality for unstructured grid datasets following [[https://ugrid-conventions.github.io/ugrid-conventions/|UGRID Conventions]] | * [[https://uxarray.readthedocs.io/|uxarray]]: provide xarray styled functionality for unstructured grid datasets following [[https://ugrid-conventions.github.io/ugrid-conventions/|UGRID Conventions]] |
| * [[https://docs.xarray.dev/en/stable/|xarray]]: Xarray makes working with labelled multi-dimensional arrays in Python simple, efficient, and fun! | * [[https://docs.xarray.dev/en/stable/|xarray]]: Xarray makes working with labelled multi-dimensional arrays in Python simple, efficient, and fun! |
