@mark-wieczorek:matrix.org, waiting for the docs to be merged on another repo still. Here is a link to the doc build from CI that shows the What's New https://2550-5282596-gh.circle-artifacts.com/0/docs/build/html/whats_new.html
CHANNELS="-c conda-forge/label/testing -c conda-forge -c defaults"
PACKAGES_COMMON="flufl.lock owslib pep8 pillow pyepsg pyshp pytest"
PACKAGES_COMMON="$PACKAGES_COMMON pytest-xdist requests setuptools_scm"
PACKAGES_COMMON="$PACKAGES_COMMON setuptools_scm_git_archive shapely"
PACKAGES_LATEST="python=3.8 cython fiona matplotlib-base numpy proj<8 pykdtree scipy pytest-cov coveralls spyder=4"
:( Bummer... The CI systems list out what packages they installed and where they got them from
conda list at the end of the "Install Dependencies" step. You can try to see if there is a difference between your local versions and those I guess? Here is the most recent one: https://github.com/SciTools/cartopy/runs/2413220331
reading the Cartopy documentation I found the solution. (https://scitools.org.uk/cartopy/docs/latest/gallery/gridlines_and_labels/tick_labels.html?highlight=set_xticks)
Thank you very much @stefraynaud, I would like, although it seems that with the use of the code of (https://scitools.org.uk/cartopy/docs/latest/gallery/gridlines_and_labels/tick_labels.html?highlight=set_xticks), the plot of SST values are more accurate. Could you help me understand?
Hello! I want to use cartopy but it keeps asking for Proj 4.9.0. I installed it using the indications on https://proj.org/install.html, it is on my harddisk but it isnt connected to my python apparently
I use windows
@stefraynaud, Better to draw with ax.gridlines (draw_labels = True)
When I use this code, I am introducing a tracing error. Because this code is for the Mercator projection. I hope to help fix this issue.
"# Label axes of a Mercator projection without degree symbols in the labels
and formatting labels to include 1 decimal place: "
@rcsmit, Is PROJ in your library path on Windows? It may be due to virtual environments not having access to where you installed PROJ... There are some Windows binaries available here: https://www.lfd.uci.edu/~gohlke/pythonlibs/#cartopy or conda-forge is another good place to look for easier installation as well.
This might point you in the right direction: https://scitools.org.uk/cartopy/docs/latest/gallery/lines_and_polygons/hurricane_katrina.html#sphx-glr-gallery-lines-and-polygons-hurricane-katrina-py
You can usually search for X shapefile and find something that'd work for that, e.g., plate tectonic shapefiles like https://github.com/fraxen/tectonicplates
Hi! Is this project open to adding more/unconventional projections? I'd be interested in adding support for the Dymaxion projection (e.g. https://github.com/Teque5/pydymax) if that's something that'd be interesting for the maintainers. If not then I can just hack together what I'm looking for
Hi all, in case anbody here has experience with cProfile, would you mind having a look at a Matplotlib Discourse issue of mine? It's part of an MSc thesis project. Much appreciated: https://discourse.matplotlib.org/t/cprofiling-cartopys-vs-geopandass-interface-with-matplotlib-puzzling-results/22255
Thanks, @greglucas. That did help a bit! For both options, the cartopy average goes up to around 13.5 seconds (vs GeoPandas' 59 seconds) - still the general behaviour persists though that the cProfiles are dumped to file (one after the other since I'm running the function through a for loop n-times) before each of the figures is rendered n-times afterwards. Hmm....
You need to make a blocking call in your loop then I think.
fig.savefig('/tmp/data.png') I think blocks until the buffer is fully written to disk. To compare all of these cases you'll really need to read up a lot more about profiling all of these various libraries because all of them do different things under the hood that may be beneficial in certain ways, like blitting or re-using the same canvas. If you're writing to disk or just showing an in-memory representation.
*than
Testing with the upcoming MPL v3.5 is going to break quite a few people using coastlines due to the ordering of patches being different. We discussed this at length yesterday on the MPL side and think it is best to try and push a release for Cartopy with a fix for this out before the MPL release. That means in the next ~2-3 weeks we should be cutting a v0.20 release.
I think that some of the failures are pretty minor tolerance increases that have just pushed them over the edge of tolerance. i.e., the clipping/boundary was already wrong in the previous MPL version and we just bumped the tolerance. For instance, I think the "bleeding" of pcolor over into the spine and anti-aliasing with the colors was present before as well? I'm pretty sure these boil down to some MPL issues you've opened up previously: matplotlib/matplotlib#15952 and matplotlib/matplotlib#15946
