Nctoolkit

This release contains a new method for producing high quality static plots. Yuri Artioli of Plymouth Marine Laboratory contributed the core code to this new `pub_plot` method.

This is a quick release to make the package fully compatible with Pandas v2.0.0. Changes in the pandas api were causing some add/subtract etc. methods to fail for daily data. This is now fixed.

A couple of improvements have been made to internals.

This is a major(ish) release with some breaking changes related to plotting.

On pypi, cartopy has been switched to an optional dependency because it was causing installation difficulties for some users. You can now do a "complete" installation using pip to get all optional dependencies::

$ pip install nctoolkit[complete]

This does not impact the conda version, which will behave as before.

Support is now available for Python 3.11.

File paths with spaces are now supported.

This is a minor release that makes it easier to use nctoolkit on shared resources.

You can now specify who is using the imported version of nctoolkit using `options`.

So, if you did the following:

import nctoolkit as nc
nc.options(user = "george_costanza")

all temporary files generated will have "george_costanza" in the name. This makes it easier to identify files generated by you and others when you are sharing computational resources.

There are also some internal improvements in this release.

This is a minor releases that tidies up some issues and has some method enhancements.

The `regrid` and `to_latlon` methods can now be more efficient for multi-file datasets where all files have the same grid. Previously, the methods identified the grids for all methods, which is obviously inefficient if they are all the same. You can now set the `one_grid` argument to `True`, which will result in the methods assuming all files have the same grid, and only the first file being checked.

There was an issue with multi-file datasets in parallel in Python 3.8 and 3.9. A confusing `TypeError` was being thrown due to signalling issues by multiprocessing. This gave the impression there was a problem with processing when there wasn’t one. This problem is now fixed.

This is a minor release that deals with clean up issues on Jupyter notebooks. A change in a recent version of ipykernel was causing nctoolkit to not automatically remove temporary files on exit when using notebooks. This should now be fixed.

The `annual_anomaly` method now lets users temporally align the output, in the same way as other temporal methods such as `roll_mean`.

Some improvements have been made to internals for better warnings and errors.