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Various README suggestions #826

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72e88ec
README suggestions.
trexfeathers Jun 12, 2024
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README refactor pantry.
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More README suggestions.
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Revert "README refactor pantry."
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Better shop window.
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Even better shop window.
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84 changes: 45 additions & 39 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,26 @@
Cartographic rendering and mesh analytics powered by <a href="https://docs.pyvista.org/index.html">PyVista</a>
</h3>

<h3 align="center">
😍 <i>Bring your data to life!</i> 😍
</h3>

[🎥 WW3 SMC time-series](https://github.com/bjlittle/geovista/assets/2051656/876d877e-a6fa-42ff-8153-08c41ff8a19e)

<details><summary><i>What is this?</i></summary>

GeoVista is built on the shoulders of giants, namely [PyVista](https://docs.pyvista.org/version/stable/) and
[VTK](https://vtk.org/documentation/), thus allowing it to easily leverage the power of the GPU.

As a result, it offers a paradigm shift in rendering performance and interactive user experience, as demonstrated by
this realtime, time-series animation of WAVEWATCH III® third-generation wave model (**WAVE**-height, **WAT**er depth
and **C**urrent **H**indcasting), developed at [NOAA](https://www.noaa.gov/)/[NCEP](https://www.weather.gov/ncep/),
quasi-unstructured Spherical Multi-Cell (SMC) grid data of Sea Surface Wave Significant Height located on cell faces.

Like what you see? Loads more information is available below, so keep on scrolling! 🚀

</details>


| | |
|--------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
Expand All @@ -22,7 +42,6 @@
| 🛡️ Status | [![scitools](https://img.shields.io/badge/scitools-ownership%20pending-yellow)](https://github.com/bjlittle/geovista/issues/167) |
| | |


## Motivation

The goal of GeoVista is simple; to complement [PyVista](https://docs.pyvista.org/index.html) with a convenient
Expand All @@ -40,22 +59,21 @@ et al, which specialise in preparing your spatial data for visualisation. Rather
choice of tool to you the user, as we want GeoVista to remain as flexible and open-ended as possible to the entire
Scientific Python community.

Simply put, "*GeoVista is to PyVista*", as "*Cartopy is to Matplotlib*". Well, that's the aspiration.
Simply put, "*[GeoVista](https://geovista.readthedocs.io/) is to
[PyVista](https://docs.pyvista.org/)*", as
"*[Cartopy](https://scitools.org.uk/cartopy/docs/latest/) is to
[Matplotlib](https://matplotlib.org/)*". Well, that's the aspiration.

## Installation

GeoVista is available on both [conda-forge](https://anaconda.org/conda-forge/geovista) and [PyPI](https://pypi.org/project/geovista/).

We recommend using [mamba](https://github.com/mamba-org/mamba) to install GeoVista 👍
We recommend using [conda](https://docs.conda.io/projects/conda/en/latest/index.html) to install GeoVista 👍

### Mamba
### Conda

GeoVista is available on [conda-forge](https://anaconda.org/conda-forge/geovista), and can be easily installed with
[mamba](https://github.com/mamba-org/mamba):
```shell
mamba install -c conda-forge geovista
```
or alternatively with [conda](https://docs.conda.io/projects/conda/en/latest/index.html):
[conda](https://docs.conda.io/projects/conda/en/latest/index.html):
bjlittle marked this conversation as resolved.
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```shell
conda install -c conda-forge geovista
```
Expand Down Expand Up @@ -90,7 +108,7 @@ cd geovista
```
Create the `geovista-dev` conda development environment:
```shell
mamba env create --file requirements/geovista.yml
conda env create --file requirements/geovista.yml
```
Now activate the environment and install the `main` development branch of GeoVista:
```shell
Expand Down Expand Up @@ -142,7 +160,7 @@ base layer, and the gorgeous perceptually uniform [cmocean balance](https://matp
colormap.

<details>
<summary>🗒 </summary>
<summary>🗒 click for code</summary>
bjlittle marked this conversation as resolved.
Show resolved Hide resolved

```python
import geovista as gv
Expand Down Expand Up @@ -170,17 +188,17 @@ plotter.show()
```
</details>

![ww3-tri](https://raw.githubusercontent.com/bjlittle/geovista-media/2023.09.1/media/readme/ww3-tri.png)
<p align="center"><img src="https://raw.githubusercontent.com/bjlittle/geovista-media/2023.09.1/media/readme/ww3-tri.png" height="400"></p>

#### Finite Volume Community Ocean Model

Now, let's visualise the bathymetry of the
[Plymouth Sound and Tamar River](https://www.google.com/maps/place/Plymouth+Sound/@50.3337382,-4.2215988,12z/data=!4m5!3m4!1s0x486c93516bbce307:0xded7654eaf4f8f83!8m2!3d50.3638359!4d-4.1441365)
from an [FVCOM](http://fvcom.smast.umassd.edu/fvcom/) **unstructured** mesh, as kindly provided by the
from an [FVCOM](https://www.fvcom.org/) **unstructured** mesh, as kindly provided by the
[Plymouth Marine Laboratory](https://pml.ac.uk/) using the lush [cmocean deep](https://matplotlib.org/cmocean/#deep) colormap.

<details>
<summary>🗒 </summary>
<summary>🗒 click for code</summary>

```python
import geovista as gv
Expand Down Expand Up @@ -213,7 +231,7 @@ plotter.show()
```
</details>

![tamar](https://raw.githubusercontent.com/bjlittle/geovista-media/2023.09.1/media/readme/tamar.png)
<p align="center"><img src="https://raw.githubusercontent.com/bjlittle/geovista-media/2023.09.1/media/readme/tamar.png" height="400"></p>

#### CF UGRID

Expand All @@ -231,7 +249,7 @@ In the meantime, let's showcase our basic projection support with some high-reso
base layer.

<details>
<summary>🗒 </summary>
<summary>🗒 click for code</summary>

```python
import geovista as gv
Expand Down Expand Up @@ -262,7 +280,7 @@ plotter.show()
```
</details>

![lam-mollweide](https://raw.githubusercontent.com/bjlittle/geovista-media/2023.09.1/media/readme/lam-moll.png)
<p align="center"><img src="https://raw.githubusercontent.com/bjlittle/geovista-media/2023.09.1/media/readme/lam-moll.png" height="400"></p>

Using the same **unstructured** LAM data, reproject to
[Equidistant Cylindrical](https://proj.org/operations/projections/eqc.html) but this time using a
Expand All @@ -273,7 +291,7 @@ and a
base layer.

<details>
<summary>🗒 </summary>
<summary>🗒 click for code</summary>

```python
import cartopy.crs as ccrs
Expand Down Expand Up @@ -306,7 +324,7 @@ plotter.show()
```
</details>

![lam-mollweide](https://raw.githubusercontent.com/bjlittle/geovista-media/2023.09.1/media/readme/lam-eqc.png)
<p align="center"><img src="https://raw.githubusercontent.com/bjlittle/geovista-media/2023.09.1/media/readme/lam-eqc.png" height="400"></p>

#### LFRic Cube-Sphere

Expand All @@ -317,7 +335,7 @@ Now render a [Met Office LFRic](https://www.metoffice.gov.uk/research/approach/m
[cmocean thermal](https://matplotlib.org/cmocean/#thermal) colormap.

<details>
<summary>🗒 </summary>
<summary>🗒 click for code</summary>

```python
import geovista as gv
Expand Down Expand Up @@ -346,7 +364,7 @@ plotter.show()
```
</details>

![lam-mollweide](https://raw.githubusercontent.com/bjlittle/geovista-media/2023.09.1/media/readme/lfric-robin.png)
<p align="center"><img src="https://raw.githubusercontent.com/bjlittle/geovista-media/2023.09.1/media/readme/lfric-robin.png" height="400"></p>

#### UM ORCA2

Expand All @@ -356,7 +374,7 @@ using Met Office Unified Model (UM) ORCA2 Sea Water Potential Temperature data,
[1:50m Natural Earth I](https://www.naturalearthdata.com/downloads/50m-raster-data/50m-natural-earth-1/) base layer.

<details>
<summary>🗒 </summary>
<summary>🗒 click for code</summary>

```python
import geovista as gv
Expand Down Expand Up @@ -384,7 +402,7 @@ plotter.show()
```
</details>

![um-orca](https://raw.githubusercontent.com/bjlittle/geovista-media/2023.09.1/media/readme/um-orca.png)
<p align="center"><img src="https://raw.githubusercontent.com/bjlittle/geovista-media/2023.09.1/media/readme/um-orca.png" height="400"></p>

#### OISST AVHRR

Expand All @@ -394,7 +412,7 @@ Now let's render a [NOAA/NCEI Optimum Interpolation SST](https://www.ncei.noaa.g
[NASA Blue Marble](https://visibleearth.nasa.gov/collection/1484/blue-marble) base layer.

<details>
<summary>🗒 </summary>
<summary>🗒 click for code</summary>

```python
import geovista as gv
Expand Down Expand Up @@ -422,7 +440,7 @@ plotter.show()
```
</details>

![oisst-avhrr](https://raw.githubusercontent.com/bjlittle/geovista-media/2023.09.1/media/readme/oisst-avhrr.png)
<p align="center"><img src="https://raw.githubusercontent.com/bjlittle/geovista-media/2023.09.1/media/readme/oisst-avhrr.png" height="400"></p>

#### DYNAMICO

Expand All @@ -434,7 +452,7 @@ model uses hexagonal and pentagonal cells, and is a new dynamical core for
[10m Natural Earth coastlines](https://www.naturalearthdata.com/downloads/10m-physical-vectors/10m-coastline/).

<details>
<summary>🗒 </summary>
<summary>🗒 click for code</summary>

```python
import geovista as gv
Expand All @@ -457,19 +475,7 @@ plotter.show()
```
</details>

![dynamico-icosahedral](https://raw.githubusercontent.com/bjlittle/geovista-media/2023.09.1/media/readme/dynamico-icosahedral.png)

## Unreal Reels

GeoVista is built on the shoulders of giants, namely [PyVista](https://docs.pyvista.org/version/stable/) and
[VTK](https://vtk.org/documentation/), thus allowing it to easily leverage the power of the GPU.

As a result, it offers a paradigm shift in rendering performance and interactive user experience, as demonstrated by
this realtime, time-series animation of WAVEWATCH III® third-generation wave model (**WAVE**-height, **WAT**er depth
and **C**urrent **H**indcasting), developed at [NOAA](https://www.noaa.gov/)/[NCEP](https://www.weather.gov/ncep/),
quasi-unstructured Spherical Multi-Cell (SMC) grid data of Sea Surface Wave Significant Height located on cell faces.

[🎥 WW3 SMC time-series](https://github.com/bjlittle/geovista/assets/2051656/876d877e-a6fa-42ff-8153-08c41ff8a19e)
<p align="center"><img src="https://raw.githubusercontent.com/bjlittle/geovista-media/2023.09.1/media/readme/dynamico-icosahedral.png" height="400"></p>

## Further Examples

Expand Down
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