scitools | Additional scientific computing functionality in Python | Performance Testing library

I have a cartopy GeoAxesSubplot with some points, and potentially lines or polygons. The projection could be any that is supported by cartopy, including orthographic.

I can plot using different transformations, as explained here:

If you download the data from: https://www.naturalearthdata.com/ then is there an option in cartopy.feature adds to check a local directory first before going to the webserver.

I think under windows there is some caching going on in appdata but could not find documentation to provide a path for this feature to look for the data in a directory. Nor how this would be standardized across OS. This could be applied to the feature request in this cartopy example:

https://scitools.org.uk/cartopy/docs/latest/gallery/lines_and_polygons/feature_creation.html#sphx-glr-gallery-lines-and-polygons-feature-creation-py

snippets:

For a project I need to create a visualization that draws a circle around some locations on a map. The visualization used Cartopy v.0.18.0 to render the map. It uses the GoogleTiles class to fetch and display the tiles in the relevant region, and the add_patch(Patch.Circle(..., transform=ccrs.PlateCarree())) method to draw the circle.

I create a Stamen terrain map with the country border from NaturalEarth. Now I want to remove all the data (terrain in this case) from outside the country border. How would I do that?

My example with the terrain visible inside and outside of Switzerland:

I have a task to analyze weather forecast data in Quicksight. The forecast data is held in NetCDF binary files in a public S3 bucket. The question is: how do you expose the contents of these binary files to Quicksight or even Athena?

There are python libraries that will decode the data from the binary files, such as Iris. They are used like this:

Quite regularly I find myself in the need of plotting (a lot of) maps of a variety of regions and region sizes. I would like these maps to have ticklabels indicating longitude and latitude (similar to this example: https://scitools.org.uk/cartopy/docs/v0.15/examples/tick_labels.html).

However, the solution suggested there does not work for me since it requires a priori knowledge about the region extend. I've written several way too complicated functions over the years in order to try and make this work in a flexible way. So what I'm wondering at this point: is there a simple solution to put latitude & longitude ticklabels to a map of variable extend?

This here comes somewhat close but is still quite unreliable:

The new capability in Cartopy 0.18.0 to add lat/lon labels for any map projection is excellent. It's a great addition to this package. For some maps, especially in polar regions, the lat/lon labels can be very crowded. Here is an example.

The cartopy.feature.NaturalEarthFeature class of cartopy looks like a very convenient way to add high quality map features, but I haven't been able to figure out what values are allowed for the name parameter at class initialization. The documentation indicates it needs to be a valid dataset name from www.naturalearthdata.com, but the dataset information there does not give clear indication of the datasets' names.

I have tried the obvious such as 'natural-earth-i-with-shaded-relief' (or variant 'natural_earth_i_with_shaded_relief') and other such guesses, but none of my guesses worked. The only names that don't drop a 404 on me are 'land' and 'ocean' under the 'physical' category -- but even then, although the code runs it doesn't render anything for those features. I am expecting some sort of basic land or ocean shading at the very least. Ideally I would like to add physical shaded relief as a backdrop to my data overlay.

I am playing with iris (really neat!) and I have a list of cities lat/lons I am interested to see average temperature over time. I have netcdf files with air temperatures covering entire country. I would like to tag data points in a cube with lat/lons closest to my cities so then I can easily get values I need just for these cities, or export data just for these cities somewhere.

I imagine I need to use add_categorised_coord somehow? https://scitools.org.uk/iris/docs/latest/iris/iris/coord_categorisation.html#iris.coord_categorisation.add_categorised_coord

I will appreciate an example. Thanks!