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Cartopy - a cartographic python library with matplotlib support
https://scitools.org.uk/cartopy/docs/latest
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Longitude overlap labels 180° when central_longitude is not 0 #1401

Open mickaellalande opened 4 years ago

mickaellalande commented 4 years ago

Description

I realized that when we shift the central_longitude in PlateCarree() projection the 180° overlap on global data set. Here I did format the longitude and latitude, but it happens also without the formatting (see code below):

longitude_overlap

Here is the data I am using:

snc_LImon_IPSL-CM6A-LR_historical_r1i1p1f1_gr_185001.zip

Code to reproduce

import xarray as xr
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER

da = xr.open_dataarray('snc_LImon_IPSL-CM6A-LR_historical_r1i1p1f1_gr_185001.nc')

plt.figure(figsize=(10,4))
ax = plt.axes(projection=ccrs.PlateCarree(180))
da.plot(ax=ax, transform=ccrs.PlateCarree())
ax.coastlines()
ax.set_global()
gl = ax.gridlines(crs=ccrs.PlateCarree(), draw_labels=True, linewidth=0.7, color='gray', alpha=0.5, linestyle='--')
gl.xlabels_top = False
gl.ylabels_right = False
gl.xformatter = LONGITUDE_FORMATTER
gl.yformatter = LATITUDE_FORMATTER

Thanks in advance for checking this. It is for sure possible to fix this by hand, but it is a lot of work, so it would be nice to have natively something that deals with this. I hope it is not overlapping another issue or that there is already an easy solution to fix this... but I didn't find so far.

Except:

Full environment definition ### Operating system Debian 10 ### Cartopy version cartopy 0.17.0 py37hbb7e04d_1 ### conda list ``` # packages in environment at /home/mlalande/miniconda3: # # Name Version Build Channel _libgcc_mutex 0.1 main asn1crypto 1.2.0 py37_0 atomicwrites 1.3.0 pypi_0 pypi attrs 19.3.0 py_0 backcall 0.1.0 py37_0 blas 1.0 mkl bleach 3.1.0 py37_0 bokeh 1.4.0 py37_0 bzip2 1.0.8 h7b6447c_0 ca-certificates 2019.10.16 0 cartopy 0.17.0 py37hbb7e04d_1 certifi 2019.9.11 py37_0 cffi 1.13.0 py37h2e261b9_0 cftime 1.0.3.4 py37hdd07704_1001 chardet 3.0.4 py37_1003 click 7.0 py37_0 cloudpickle 1.2.2 py_0 conda 4.7.12 py37_0 conda-package-handling 1.6.0 py37h7b6447c_0 cryptography 2.8 py37h1ba5d50_0 curl 7.65.3 hbc83047_0 cycler 0.10.0 py37_0 cytoolz 0.10.1 py37h7b6447c_0 dask 2.8.0 py_1 dask-core 2.8.0 py_0 dbus 1.13.12 h746ee38_0 decorator 4.4.0 py37_1 defusedxml 0.6.0 py_0 distributed 2.8.0 py_1 entrypoints 0.3 py37_0 esmf 8.0.0 ha4864fb_1 conda-forge esmpy 8.0.0 py37h5ca1d4c_0 conda-forge expat 2.2.6 he6710b0_0 fontconfig 2.13.0 h9420a91_0 freetype 2.9.1 h8a8886c_1 fsspec 0.6.0 py_0 geos 3.7.1 he6710b0_0 glib 2.56.2 hd408876_0 gmp 6.1.2 h6c8ec71_1 gst-plugins-base 1.14.0 hbbd80ab_1 gstreamer 1.14.0 hb453b48_1 hdf4 4.2.13 h3ca952b_2 hdf5 1.10.5 nompi_h3c11f04_1104 conda-forge heapdict 1.0.1 py_0 holoviews 1.12.6 py_0 pyviz icu 58.2 h9c2bf20_1 idna 2.8 py37_0 importlib_metadata 0.23 py37_0 intel-openmp 2019.4 243 ipykernel 5.1.2 py37h39e3cac_0 ipython 7.8.0 py37h39e3cac_0 ipython_genutils 0.2.0 py37_0 ipywidgets 7.5.1 py_0 jedi 0.15.1 py37_0 jinja2 2.10.3 py_0 jpeg 9c h14c3975_1001 conda-forge jsonschema 3.1.1 py37_0 jupyter 1.0.0 py37_7 jupyter_client 5.3.4 py37_0 jupyter_console 6.0.0 py37_0 jupyter_core 4.6.0 py37_0 kiwisolver 1.1.0 py37he6710b0_0 krb5 1.16.1 h173b8e3_7 libcurl 7.65.3 h20c2e04_0 libedit 3.1.20181209 hc058e9b_0 libffi 3.2.1 hd88cf55_4 libgcc-ng 9.1.0 hdf63c60_0 libgfortran-ng 7.3.0 hdf63c60_0 libnetcdf 4.7.1 nompi_h94020b1_101 conda-forge libpng 1.6.37 hbc83047_0 libsodium 1.0.16 h1bed415_0 libssh2 1.8.2 h1ba5d50_0 libstdcxx-ng 9.1.0 hdf63c60_0 libtiff 4.0.10 h2733197_2 libuuid 1.0.3 h1bed415_2 libxcb 1.13 h1bed415_1 libxml2 2.9.9 hea5a465_1 libxslt 1.1.33 h7d1a2b0_0 locket 0.2.0 py37_1 lxml 4.4.1 py37hefd8a0e_0 markdown 3.1.1 py37_0 markupsafe 1.1.1 py37h7b6447c_0 matplotlib 3.1.1 py37h5429711_0 mistune 0.8.4 py37h7b6447c_0 mkl 2019.4 243 mkl-service 2.3.0 py37he904b0f_0 mkl_fft 1.0.14 py37ha843d7b_0 mkl_random 1.1.0 py37hd6b4f25_0 more-itertools 7.2.0 py37_0 mpi 1.0 mpich conda-forge mpich 3.3.2 hc856adb_0 conda-forge msgpack-python 0.6.1 py37hfd86e86_1 nbconvert 5.6.0 py37_1 nbformat 4.4.0 py37_0 ncurses 6.1 he6710b0_1 netcdf-fortran 4.4.5 h55403cb_1003 conda-forge netcdf4 1.5.3 py37hf3213d6_0 conda-forge notebook 6.0.1 py37_0 numpy 1.17.2 py37haad9e8e_0 numpy-base 1.17.2 py37hde5b4d6_0 olefile 0.46 py37_0 openssl 1.1.1d h7b6447c_3 owslib 0.18.0 py_0 packaging 19.2 py_0 pandas 0.25.2 py37he6710b0_0 pandoc 2.2.3.2 0 pandocfilters 1.4.2 py37_1 panel 0.7.0 py_0 pyviz param 1.9.2 py_0 pyviz parso 0.5.1 py_0 partd 1.0.0 py_0 pcre 8.43 he6710b0_0 pexpect 4.7.0 py37_0 pickleshare 0.7.5 py37_0 pillow 6.2.0 py37h34e0f95_0 pip 19.3.1 py37_0 pluggy 0.13.0 pypi_0 pypi proj4 5.2.0 he6710b0_1 prometheus_client 0.7.1 py_0 prompt_toolkit 2.0.10 py_0 psutil 5.6.3 py37h7b6447c_0 ptyprocess 0.6.0 py37_0 py 1.8.0 pypi_0 pypi pycosat 0.6.3 py37h14c3975_0 pycparser 2.19 py37_0 pyct 0.4.6 py_0 pyviz pyct-core 0.4.6 py_0 pyviz pyepsg 0.4.0 py37_0 pygments 2.4.2 py_0 pykdtree 1.3.1 py37hdd07704_2 pyopenssl 19.0.0 py37_0 pyparsing 2.4.2 py_0 pyproj 1.9.6 py37h14380d9_0 pyqt 5.9.2 py37h05f1152_2 pyrsistent 0.15.4 py37h7b6447c_0 pyshp 2.1.0 py_0 pysocks 1.7.1 py37_0 pytest 5.2.4 pypi_0 pypi python 3.7.4 h265db76_1 python-dateutil 2.8.0 py37_0 pytz 2019.3 py_0 pyviz_comms 0.7.2 py_0 pyviz pyyaml 5.1.2 py37h7b6447c_0 pyzmq 18.1.0 py37he6710b0_0 qt 5.9.7 h5867ecd_1 qtconsole 4.5.5 py_0 readline 7.0 h7b6447c_5 requests 2.22.0 py37_0 ruamel_yaml 0.15.46 py37h14c3975_0 scipy 1.3.1 py37h7c811a0_0 send2trash 1.5.0 py37_0 setuptools 41.4.0 py37_0 shapely 1.6.4 py37h86c5351_0 sip 4.19.8 py37hf484d3e_0 six 1.12.0 py37_0 sortedcontainers 2.1.0 py37_0 sqlite 3.30.0 h7b6447c_0 tblib 1.5.0 py_0 terminado 0.8.2 py37_0 testpath 0.4.2 py37_0 tk 8.6.8 hbc83047_0 toolz 0.10.0 py_0 tornado 6.0.3 py37h7b6447c_0 tqdm 4.36.1 py_0 traitlets 4.3.3 py37_0 urllib3 1.24.2 py37_0 wcwidth 0.1.7 py37_0 webencodings 0.5.1 py37_1 wheel 0.33.6 py37_0 widgetsnbextension 3.5.1 py37_0 xarray 0.13.0 py_0 xesmf 0.2.1 py_0 conda-forge xz 5.2.4 h14c3975_4 yaml 0.1.7 had09818_2 zeromq 4.3.1 he6710b0_3 zict 1.0.0 py_0 zipp 0.6.0 py_0 zlib 1.2.11 h7b6447c_3 zstd 1.3.7 h0b5b093_0 ``` ### pip list ``` Package Version ---------------------- ----------- asn1crypto 1.2.0 atomicwrites 1.3.0 attrs 19.3.0 backcall 0.1.0 bleach 3.1.0 bokeh 1.4.0 Cartopy 0.17.0 certifi 2019.9.11 cffi 1.13.0 cftime 1.0.3.4 chardet 3.0.4 Click 7.0 cloudpickle 1.2.2 conda 4.7.12 conda-package-handling 1.6.0 cryptography 2.8 cycler 0.10.0 cytoolz 0.10.1 dask 2.8.0 decorator 4.4.0 defusedxml 0.6.0 distributed 2.8.0 entrypoints 0.3 ESMPy 8.0.0 fsspec 0.6.0 HeapDict 1.0.1 holoviews 1.12.6 idna 2.8 importlib-metadata 0.23 ipykernel 5.1.2 ipython 7.8.0 ipython-genutils 0.2.0 ipywidgets 7.5.1 jedi 0.15.1 Jinja2 2.10.3 jsonschema 3.1.1 jupyter 1.0.0 jupyter-client 5.3.4 jupyter-console 6.0.0 jupyter-core 4.6.0 kiwisolver 1.1.0 locket 0.2.0 lxml 4.4.1 Markdown 3.1.1 MarkupSafe 1.1.1 matplotlib 3.1.1 mistune 0.8.4 mkl-fft 1.0.14 mkl-random 1.1.0 mkl-service 2.3.0 more-itertools 7.2.0 msgpack 0.6.1 nbconvert 5.6.0 nbformat 4.4.0 netCDF4 1.5.3 notebook 6.0.1 numpy 1.17.2 olefile 0.46 OWSLib 0.18.0 packaging 19.2 pandas 0.25.2 pandocfilters 1.4.2 panel 0.7.0 param 1.9.2 parso 0.5.1 partd 1.0.0 pexpect 4.7.0 pickleshare 0.7.5 ```
dopplershift commented 4 years ago

Thanks for the report. Definitely not ideal behavior.

stefraynaud commented 4 years ago

The labelling system has recentrly changed in the master branch. It seems to fix this particular case.

The following code produces the following figure.

import xarray as xr
import matplotlib.pyplot as plt
import cartopy.crs as ccrs

da = xr.open_dataarray('snc_LImon_IPSL-CM6A-LR_historical_r1i1p1f1_gr_185001.nc')

plt.figure(figsize=(10,4))
ax = plt.axes(projection=ccrs.PlateCarree(180))
da.plot(ax=ax, transform=ccrs.PlateCarree())
ax.coastlines()
ax.set_global()
gl = ax.gridlines(crs=ccrs.PlateCarree(), draw_labels=True, linewidth=0.7, color='gray', alpha=0.5, linestyle='--', dms=True)
gl.top_labels = False
gl.right_labels = False

Figure

mickaellalande commented 4 years ago

Looks good, how is it possible to test that? Can I see this update with a conda update cartopy, or do we need to wait for a future update? Because for now, I don't see the dms option. Thanks for the reply, I am a bit new on GitHub, so I don't really know how do things work.