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    greglucas commented #1992
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    greglucas opened #1998
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    greglucas commented #1994
Stephane Raynaud
@stefraynaud
Yep. I juste use python 3.8 because my old compiler fails with 3.9.
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"
Greg Lucas
@greglucas
:( 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
Stephane Raynaud
@stefraynaud
Good idea
Leonardo
@leonardojimenez1990
Hello I would like to know how I can correctly plot the longitude on the map.
errorTrazarLongitudMap.png
errorTrazarLongitud.png
Leonardo
@leonardojimenez1990
correctoTrazarCoordenadasMap.png
codeCorrectoTrazarCoordenadasMap.png
Stephane Raynaud
@stefraynaud
hi @leonardojimenez1990 you should probably use ax.gridlines(draw_labels=True)
Leonardo
@leonardojimenez1990
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?
correctoTrazadoax.gridlines.png
Stephane Raynaud
@stefraynaud
What do you mean by "more accurate" ?
Leonardo
@leonardojimenez1990
In my appreciation, when you plot SST values on the map, you use more and smaller scale intervals. example [-2.0, -1.5, -1.0, -0.5, 0, 0.5, 1.0, 1.5, 2.0] while ax.gridlines (draw_labels = True) uses [-1.0, -0.5, 0, 0.5, 1.0]
Stephane Raynaud
@stefraynaud
I have no idea by the colorbar is changed when adding gridlines
Leonardo
@leonardojimenez1990
Thank you very much @stefraynaud , it seems like an interesting topic. Know the differences of these two plotting methods.
Rene Smit
@rcsmit
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
Leonardo
@leonardojimenez1990

@stefraynaud, Better to draw with ax.gridlines (draw_labels = True)

codeCorrectoTrazarCoordenadasMap.png

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: "

Greg Lucas
@greglucas
@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.
Rene Smit
@rcsmit
thank you so much, I'll try.
Rene Smit
@rcsmit
It worked from that uci.edu site! thanks again
eocene
@eocene
Hi! How can I plot different continents with Cartopy? I.e. paleo continents...
Ryan May
@dopplershift
You’ll need some data (e.g. shapefiles) that you can use to plot or turn into some kind of Shapely feature
Elliott Sales de Andrade
@QuLogic
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
eocene
@eocene
ok - thank you!
Stefan
@Stimj
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
Elliott Sales de Andrade
@QuLogic
usually we defer the actual calculation to proj
Stefan
@Stimj
That makes more sense - I was getting pretty confused about where the actual work was done after looking through crs.py
I'll have a look at OSGeo, thank you!
Gregor Herda
@gregorhd
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
Greg Lucas
@greglucas
@gregorhd, you may need to put fig.savefig() inside your function (or fig.canvas.draw()). A lot of rendering functions are lazily executed and don't happen until a draw is explicitly requested.
Gregor Herda
@gregorhd
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....
Greg Lucas
@greglucas
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.
Gregor Herda
@gregorhd
Ah I see! Thanks a mil. Clearly more complicated then I thought.
*than
Greg Lucas
@greglucas
Don't be discouraged by what I said either, just know it will take some thought and time to try and get right :) I'm guessing people will be interested in your findings!
Gregor Herda
@gregorhd
Thanks! I appreciate the encouragement :)
Greg Lucas
@greglucas
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.
Elliott Sales de Andrade
@QuLogic
Fixing the zorder goes from 23 down to 8 failures; those remaining seem to be some sort of clipping/boundary changes
Greg Lucas
@greglucas
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
Elliott Sales de Andrade
@QuLogic
Oh, it's possible they're old things like that, I hadn't looked too closely at the remaining ones yet
anuappu
@anuappu
Hi, I am encountering an issue while running cartopy. This is the error: TopologyException: side location conflict at -5505010.9196614036 8482555.2457595281. Please advise
Greg Lucas
@greglucas
@QuLogic, do you know when we should be aiming for the v0.20 release? I think we mentioned mid-september, so about this weekend.
Elliott Sales de Andrade
@QuLogic
Yea, that sounds good
Around now or so
Greg Lucas
@greglucas
:( We need to get a release out ASAP to fix the download issue... I can't believe how many duplicate issues we are getting.
Elliott Sales de Andrade
@QuLogic
On the up side, it means we're actually getting used