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* first part * added instructions to contributing * add build and deploy badge to readme * auto-alphebetize * ncl applications * move around applications structure
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# Contributor's Guide | ||
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`conda env update -f environment.yml` | ||
## Create the docs locally | ||
``` python | ||
conda env update -f environment.yml | ||
conda activate geocat-applications | ||
make clean html | ||
open _build/html/index.html | ||
``` | ||
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`conda activate geocat-applications` | ||
## How to add entries or pages | ||
### Applications | ||
TO DO | ||
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`make clean html` | ||
### NCL Index | ||
There are two paths to adding something to the NCL index: | ||
1. After creating a new applications entry | ||
2. Adding an entry that does not have a corresponding applications entry | ||
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`open _build/html/index.html` | ||
#### After creating a new applications entry | ||
To add a new entry to the NCL Index after creating a new geocat-applications entry: | ||
1. Add a new line to the `ncl/ncl_index/ncl-index-table.csv` file | ||
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#### Adding an entry that does not have a corresponding applications entry | ||
We include entries in the NCL Index that do not have corresponding geocat-applications entries for the purpose of | ||
including functions that are too small to warrant their own entry and to give users verified recommendations before | ||
an applications entry is completed. | ||
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To add an entry that does not have a corresponding geocat-applications entry: | ||
1. Create a "receipt" file in the `ncl/receipts` directory following the naming convention | ||
`ncl/receipts/<ncl-function-or-category-name>.rst` | ||
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2. Add a new line to the `ncl/ncl_index/ncl-index-table.csv` file |
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# geocat-applications | ||
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# [GeoCAT Applications](https://ncar.github.io/geocat-applications/) | ||
[](https://github.com/NCAR/geocat-applications/actions/workflows/deploy.yml) | ||
This is the source repository for GeoCAT-applications. |
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.. _applications: | ||
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.. grid:: 4 | ||
:gutter: 2 | ||
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.. grid-item:: | ||
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.. grid:: 1 | ||
:gutter: 1 | ||
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.. card:: `Plot Types <applications/plot_types/plot_types.rst>`_ | ||
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- `Contour <applications/plot_types/contour.ipynb>`_ | ||
- Plot type 2 | ||
- Plot type 3 | ||
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.. grid-item:: | ||
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.. grid:: 1 | ||
:gutter: 1 | ||
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.. card:: `Data Analysis <applications/data_analysis/data_analysis.rst>`_ | ||
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- `Data Analysis 1 <applications/data_analysis/sample.ipynb>`_ | ||
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.. grid-item:: | ||
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.. grid:: 1 | ||
:gutter: 1 | ||
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.. card:: `File I/O <applications/file_io/file_io.rst>`_ | ||
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- `File I/O 1 <applications/file_io/sample.ipynb>`_ | ||
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.. card:: Date Time Routines | ||
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.. grid-item:: | ||
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.. grid:: 1 | ||
:gutter: 1 | ||
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.. card:: Regridding | ||
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.. card:: Interpolation |
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.. _ncl_applications: | ||
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NCL Applications | ||
================ |
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NCL Function,Description,Python Equivalent,Notes | ||
`example <https://www.ncl.ucar.edu/>`__,example,example,example | ||
a,a,a,a |
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.. _ncl_index: | ||
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NCL Index | ||
========= | ||
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.. Link to temp file with alphabetized version of csv file (see conf.py) | ||
.. csv-table:: | ||
:file: ../../tmp/ncl-index-table.csv | ||
:width: 100% | ||
:header-rows: 1 | ||
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.. note:: | ||
For more information on how we verify these recommendations, see the :ref:`receipts`. |
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.. This keeps the page from being included in the TOC, but allows it to be included in the build. | ||
:orphan: | ||
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.. _receipts: | ||
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Receipts List | ||
============= | ||
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.. warning:: | ||
**This page is not meant to be useful to the typical user.** It is meant to be a reference for developers working on | ||
the NCL Index or users interested in the "behind the curtain" details of how we verify entries to the NCL Index. | ||
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.. This will automatically generates a list of all the files in the ncl/receipts directory. | ||
.. toctree:: | ||
:glob: | ||
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* |
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{ | ||
"cells": [ | ||
{ | ||
"metadata": {}, | ||
"cell_type": "markdown", | ||
"source": "# Something else", | ||
"id": "cc283431cbdce854" | ||
}, | ||
{ | ||
"metadata": {}, | ||
"cell_type": "code", | ||
"outputs": [], | ||
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"source": "", | ||
"id": "194f11e89c01919d" | ||
} | ||
], | ||
"metadata": { | ||
"kernelspec": { | ||
"display_name": "Python 3", | ||
"language": "python", | ||
"name": "python3" | ||
}, | ||
"language_info": { | ||
"codemirror_mode": { | ||
"name": "ipython", | ||
"version": 2 | ||
}, | ||
"file_extension": ".py", | ||
"mimetype": "text/x-python", | ||
"name": "python", | ||
"nbconvert_exporter": "python", | ||
"pygments_lexer": "ipython2", | ||
"version": "2.7.6" | ||
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"nbformat": 4, | ||
"nbformat_minor": 5 | ||
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{ | ||
"cells": [ | ||
{ | ||
"metadata": {}, | ||
"cell_type": "markdown", | ||
"source": "# Hello", | ||
"id": "cc553ef27145b766" | ||
}, | ||
{ | ||
"metadata": {}, | ||
"cell_type": "code", | ||
"outputs": [], | ||
"execution_count": null, | ||
"source": "", | ||
"id": "c60e3d9f10a815a4" | ||
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"metadata": { | ||
"kernelspec": { | ||
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"language": "python", | ||
"name": "python3" | ||
}, | ||
"language_info": { | ||
"codemirror_mode": { | ||
"name": "ipython", | ||
"version": 2 | ||
}, | ||
"file_extension": ".py", | ||
"mimetype": "text/x-python", | ||
"name": "python", | ||
"nbconvert_exporter": "python", | ||
"pygments_lexer": "ipython2", | ||
"version": "2.7.6" | ||
} | ||
}, | ||
"nbformat": 4, | ||
"nbformat_minor": 5 | ||
} |
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