Using Gridliner with auto_update=True in Jupyter notebooks with %matplotlib ipympl results in a busy kernel #2247
Description
Description
Not exactly sure what words to use to describe this issue.
If I set up a Jupyter lab environment with the following code and generate a plot, the kernel flickers between Idle and Busy for as long as the plot is drawn as an output of a cell. For simple plots this just causes some unnecessary flickering, but for more complicated plots this can cause considerable slow down.
The flickering is noticeable in the top-right kernel indicator and in the status bar. I think the flickering is associated with redrawing the plot constantly. For more complicated plots, the plot becomes impossible to interact with because it spends much more time busy than it does idle, and a busy plot is not interactable.
Removing auto_update=True from the axes.gridlines() stops the flickering, but also stops the gridlines automatically updating.
Code to reproduce
Set up a conda environment and launch Jupyter lab. The emsarray dependency is for a later demonstration of a more complicated plot:
$ conda install -c conda-forge cartopy=0.22 matplotlib=3.8 python=3.11 jupyterlab=4.0 emsarray=0.5 ipympl=0.9
$ jupyter-labMake a new notebook and add the following code:
%matplotlib ipympl
import cartopy.crs
import numpy
from matplotlib import pyplot as plt
from matplotlib.collections import PolyCollection
figure = plt.figure(figsize=(6, 4), dpi=100)
axes = figure.add_subplot(projection=cartopy.crs.PlateCarree())
axes.set_aspect(aspect='equal', adjustable='datalim')
axes.set(title="botz")
collection = PolyCollection(
verts=[
[[151, -23], [152, -23], [151, -22], [150, -22]]
],
array=[0],
cmap='jet',
edgecolor='face',
)
axes.add_collection(collection)
gridlines = axes.gridlines(draw_labels=["bottom", "left"], auto_update=True)
axes.autoscale()To generate a more complicated plot to better show a busy plot being non-interactive, construct a more complicated PolyCollection:
import emsarray
ds = emsarray.tutorial.open_dataset('gbr4')
collection = ds.ems.make_poly_collection(ds['botz'])If auto_update=True is removed from axes.gridlines() the kernel is no longer permanently busy. The plot responds to mouse movements by updating the coordinates quickly. (If you drag the map the plot takes a while to rerender, but this is expected because the plot geometry is complicated)
Full environment definition
Operating system
Ubuntu 20.04
Cartopy version
0.22.0
conda list
# packages in environment at /home/hea211/hecking-around/emsarray/.conda:
#
# Name Version Build Channel
_libgcc_mutex 0.1 conda_forge conda-forge
_openmp_mutex 4.5 2_gnu conda-forge
alsa-lib 1.2.10 hd590300_0 conda-forge
anyio 4.0.0 pyhd8ed1ab_0 conda-forge
argon2-cffi 23.1.0 pyhd8ed1ab_0 conda-forge
argon2-cffi-bindings 21.2.0 py311hd4cff14_3 conda-forge
arrow 1.2.3 pyhd8ed1ab_0 conda-forge
asttokens 2.4.0 pyhd8ed1ab_0 conda-forge
async-lru 2.0.4 pyhd8ed1ab_0 conda-forge
attr 2.5.1 h166bdaf_1 conda-forge
attrs 23.1.0 pyh71513ae_1 conda-forge
aws-c-auth 0.7.3 he2921ad_3 conda-forge
aws-c-cal 0.6.2 hc309b26_1 conda-forge
aws-c-common 0.9.0 hd590300_0 conda-forge
aws-c-compression 0.2.17 h4d4d85c_2 conda-forge
aws-c-event-stream 0.3.2 h2e3709c_0 conda-forge
aws-c-http 0.7.12 hc865f51_1 conda-forge
aws-c-io 0.13.32 h1a03231_3 conda-forge
aws-c-mqtt 0.9.5 h3a0376c_1 conda-forge
aws-c-s3 0.3.17 h1678ad6_0 conda-forge
aws-c-sdkutils 0.1.12 h4d4d85c_1 conda-forge
aws-checksums 0.1.17 h4d4d85c_1 conda-forge
aws-crt-cpp 0.23.1 hffbee3f_1 conda-forge
aws-sdk-cpp 1.11.156 he6c2984_2 conda-forge
babel 2.12.1 pyhd8ed1ab_1 conda-forge
backcall 0.2.0 pyh9f0ad1d_0 conda-forge
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backports.functools_lru_cache 1.6.5 pyhd8ed1ab_0 conda-forge
beautifulsoup4 4.12.2 pyha770c72_0 conda-forge
bleach 6.0.0 pyhd8ed1ab_0 conda-forge
blosc 1.21.5 h0f2a231_0 conda-forge
bokeh 3.2.2 pyhd8ed1ab_0 conda-forge
bottleneck 1.3.7 py311hcb2cf0a_0 conda-forge
brotli 1.1.0 hd590300_0 conda-forge
brotli-bin 1.1.0 hd590300_0 conda-forge
brotli-python 1.1.0 py311hb755f60_0 conda-forge
bzip2 1.0.8 h7f98852_4 conda-forge
c-ares 1.19.1 hd590300_0 conda-forge
ca-certificates 2023.7.22 hbcca054_0 conda-forge
cached-property 1.5.2 hd8ed1ab_1 conda-forge
cached_property 1.5.2 pyha770c72_1 conda-forge
cairo 1.16.0 h0c91306_1017 conda-forge
cartopy 0.22.0 py311h320fe9a_0 conda-forge
certifi 2023.7.22 pyhd8ed1ab_0 conda-forge
cffi 1.15.1 py311h409f033_3 conda-forge
cftime 1.6.2 py311h4c7f6c3_1 conda-forge
charset-normalizer 3.2.0 pyhd8ed1ab_0 conda-forge
click 8.1.7 unix_pyh707e725_0 conda-forge
cloudpickle 2.2.1 pyhd8ed1ab_0 conda-forge
comm 0.1.4 pyhd8ed1ab_0 conda-forge
contourpy 1.1.1 py311h9547e67_0 conda-forge
cycler 0.11.0 pyhd8ed1ab_0 conda-forge
cytoolz 0.12.2 py311h459d7ec_0 conda-forge
dask 2023.9.2 pyhd8ed1ab_0 conda-forge
dask-core 2023.9.2 pyhd8ed1ab_0 conda-forge
dbus 1.13.6 h5008d03_3 conda-forge
debugpy 1.8.0 py311hb755f60_0 conda-forge
decorator 5.1.1 pyhd8ed1ab_0 conda-forge
defusedxml 0.7.1 pyhd8ed1ab_0 conda-forge
distributed 2023.9.2 pyhd8ed1ab_0 conda-forge
emsarray 0.5.0 0_fullpackage conda-forge
emsarray-core 0.5.0 pyhd8ed1ab_0 conda-forge
entrypoints 0.4 pyhd8ed1ab_0 conda-forge
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fontconfig 2.14.2 h14ed4e7_0 conda-forge
fonts-conda-ecosystem 1 0 conda-forge
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geos 3.12.0 h59595ed_0 conda-forge
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glib 2.78.0 hfc55251_0 conda-forge
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harfbuzz 8.2.1 h3d44ed6_0 conda-forge
hdf4 4.2.15 h501b40f_6 conda-forge
hdf5 1.14.2 nompi_h4f84152_100 conda-forge
icu 73.2 h59595ed_0 conda-forge
idna 3.4 pyhd8ed1ab_0 conda-forge
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jsonschema-specifications 2023.7.1 pyhd8ed1ab_0 conda-forge
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jupyter_events 0.7.0 pyhd8ed1ab_2 conda-forge
jupyter_server 2.7.3 pyhd8ed1ab_0 conda-forge
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lame 3.100 h166bdaf_1003 conda-forge
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lerc 4.0.0 h27087fc_0 conda-forge
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