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other:python:maps_by_jyp [2019/09/13 11:39]
jypeter
other:python:maps_by_jyp [2019/09/18 15:40]
jypeter [Megabiome maps]
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   * Summary: Plot two megabiome maps based on 2 versions of the IPSL model (CM5 and CM6), and compare them to a map with observations   * Summary: Plot two megabiome maps based on 2 versions of the IPSL model (CM5 and CM6), and compare them to a map with observations
-  * Authors: Raj Rani-Singh ​& Jean-Yves Peterschmitt+  * Authors: Raj Rani & Jean-Yves Peterschmitt
   * Date: September 2019   * Date: September 2019
   * Script: ''​~jypeter/​CDAT/​Progs/​Devel/​pasb/​PMIP4/​Press_Conference_1909/​mh_CM6_CM5_megabiome.py   * Script: ''​~jypeter/​CDAT/​Progs/​Devel/​pasb/​PMIP4/​Press_Conference_1909/​mh_CM6_CM5_megabiome.py
 ''​ ''​
  
- +{{:​other:​python:​mh_cm6_cm5_megabiome.png?​direct&​300 |}} 
-  * Load the NetCDF model data with ''​cdms2'',​ and the xlsx observations'​ data with ''​pandas''​+  * Load the NetCDF model data with ''​cdms2'',​ and the csv observations'​ data with ''​pandas''​
   * Use ''​matplotlib''​+''​cartopy''​ to create the plot   * Use ''​matplotlib''​+''​cartopy''​ to create the plot
     * Create three plots on a 2x2 layout with an //​Orthographic//​ projection (centered on Europe) and a common colorbar. Explicitly make the 4th plot //​invisible//​ in order to make space for plotting the colorbar (''​colorbar_plot.background_patch.set_visible(False)''​ and ''​colorbar_plot.outline_patch.set_visible(False)''​)     * Create three plots on a 2x2 layout with an //​Orthographic//​ projection (centered on Europe) and a common colorbar. Explicitly make the 4th plot //​invisible//​ in order to make space for plotting the colorbar (''​colorbar_plot.background_patch.set_visible(False)''​ and ''​colorbar_plot.outline_patch.set_visible(False)''​)
     * Use a square (''​figsize=(8,​ 8)''​) figure size in order to improve the page layout     * Use a square (''​figsize=(8,​ 8)''​) figure size in order to improve the page layout
     * Use the same color scale for both the model data (plotted with ''​pcolormesh''​) and the observation data (plotted with ''​scatter''​)     * Use the same color scale for both the model data (plotted with ''​pcolormesh''​) and the observation data (plotted with ''​scatter''​)
 +    * Use a //​dictionary trick// for easily using the same gridlines parameters for all the maps
     * Use a common //listed colormap// to plot the discrete megabiome values (with a //norm// associated with the megabiome values) and the observations (with a **different //norm//** associated with the observations)     * Use a common //listed colormap// to plot the discrete megabiome values (with a //norm// associated with the megabiome values) and the observations (with a **different //norm//** associated with the observations)
 +    * The three plots have the same colormap, but we create a standalone colormap (created with ''​mpl.colorbar.ColorbarBase''​) in the Bottom Left quadrant. We use ''​UR_plot.get_position().bounds''​ to determine the exact location of the Upper Right and Lower Left plots, and combine the coordinates to create the axis (with ''​my_page.add_axes''​) where the colorbar will be plotted
  
 /* standard page footer */ /* standard page footer */
other/python/maps_by_jyp.txt · Last modified: 2019/11/15 13:53 by jypeter