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Inconsistent projection behavior between Matplotlib & Bokeh Backends #1410
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Thanks for reporting. Can you share as shapefile? import holoviews as hv
import cartopy.crs as ccrs
import xarray as xr
import hvplot
gdf = gpd.read_file("projected-data.csv")
gdf.set_geometry("geometry") Reading CSVs with geopandas doesn't seem to work very well Also, can you check whether removing geo=True/rasterize=True fixes it? If so, it's a datashader issue; if not it's a geoviews issue. |
Here's the shapefile: https://drive.google.com/file/d/1A4pecNOk0l6T40SXMi3d7Ht3ZwOQTxHQ/view?usp=sharing |
Thanks for confirming. Can you try reproducing it in geoviews without hvplot?
|
I posted an issue on GeoViews regarding something that may be related to this issue The common denominator is that it only occurs with the Bokeh backend. |
Depending on how deep you want to debug this, you can set up breakpoints and see what the call stack is. |
ALL software version info
(this library, plus any other relevant software, e.g. bokeh, python, notebook, OS, browser, etc)
Software Version Info
Description of expected behavior and the observed behavior
I am working with data that is projected to
InterruptedGoodeHomolosine
projection. Using matplotlib and bokeh prouce different results. The Matplotlib one below is what I expected, with anything outside of the bounds of the projecting being clipped out. However, the bokeh one produces different results. I'm not sure if this is intended or not.Complete, minimal, self-contained example code that reproduces the issue
Stack traceback and/or browser JavaScript console output
N/A
Screenshots or screencasts of the bug in action
Matplotlib
Bokeh
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