Proposing to add Webviz to the list, along with Webviz-subsurface.

Project name:
Webviz+Webviz-subsurface

Project website/repository:
https://github.com/equinor/webviz-subsurface/

License:
MIT for webviz-config, GPLv3 for webviz-subsurface

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Description of the desired feature

matplotlib provides two methods, hlines and vlines, for plotting horizontal and vertical lines.

In PyGMT, we can plot any lines using the plot() method. However, for plotting horizontal and vertical lines,

we should add .ipynb to the gitignore - notebooks are out-of-scope for this repo. In the past we have had some notebooks be committed which adds a large volume of code to the log that is later removed

Description of the desired feature

The function uses np.min and np.max to get the bounding region of the given set of coordinates. This doesn't work if the coordinates are coming from xarray because the min

Description of the desired feature

On the last community call we decided to move all sample datasets in Fatiando to Rockhound.
Harmonica datasets are being moved to Rockhound on fatiando/rockhound#84.
After it is merged, we should remove the harmonica.datasets along with the data folder. Besides, all gallery examples should download their data from Rockhound, there

Incorporate simple melting and fractionation models into pyrolite.geochem.magma.

These can later be extended with more complicated models.

Relevant References

• Shaw D. M. (1970) Trace element fractionation during anatexis. Geochimica et Cosmochimica Acta 34, 237–243.

Is your feature request related to a problem? Please describe.
Would be interesting in trying Predictatops on this new dataset from Wyoming!
https://sites.google.com/a/wyo.gov/oil-and-gas/prb-study

Describe the solution you'd like
A tutorial that runs the prediction

Describe alternatives you've considered
A separate repo

About

Unidata is looking for Python programmers to contribute Jupyter Notebook dataset viewers to the TDS Jupyter Notebook service.
To contribute to this issue, create a Jupyter Notebook (or use a notebook or Python script you've already written! ) that does the following:

1. acc

Description of the desired feature

Would be nice if the gallery example corresponding to each dataset would explicit the license under it's released and a reference to its article (or doi). By facilitating this information we could encourage people to cite the models they use, and get to know under which license are they released.