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Updates to recipe_seaborn.yml and seaborn diagnostic #3808

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Updates to recipe_seaborn.yml and seaborn diagnostic #3808

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f02e295
Update seaborn diagnostics for scatter plot
aytacpacal Nov 5, 2024
d51c422
Add ORCID link for author Pacal, Aytac in config-references.yml
aytacpacal Nov 7, 2024
d8de7fd
fix reset_true and diagnostic comment
debe-kevin Nov 18, 2024
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5 changes: 5 additions & 0 deletions esmvaltool/config-references.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -311,6 +311,11 @@ authors:
institute: DLR, Germany
orcid:
github: jeremykraftdlr
pacal_aytac:
name: Pacal, Aytac
institute: DLR, Germany
orcid: https://orcid.org/0000-0002-1324-2389
github: aytacpacal
krasting_john:
name: Krasting, John
institute: NOAA, USA
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11 changes: 10 additions & 1 deletion esmvaltool/diag_scripts/seaborn_diag.py
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Expand Up @@ -148,6 +148,7 @@ def _create_plot(
plot_func_str,
_get_str_from_kwargs(plot_kwargs),
)

plot_obj = plot_func(data=data_frame, **plot_kwargs)

# Adjust plot appearance
Expand All @@ -171,7 +172,10 @@ def _create_plot(
getattr(plot_obj, func_name)(func_args)
if cfg['suptitle'] is not None:
logger.debug("Setting `suptitle='%s'`", cfg['suptitle'])
plt.suptitle(cfg['suptitle'], y=1.05)
if plot_func_str in ['jointplot']:
plt.suptitle(cfg['suptitle'].format(data_frame["shape_id"].unique()[0]), y=1.05)
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This will cause the diagnostic to fail if no shape_id is present. Is this change necessary because you created a multi-panel plot (as far as I understand, this is not possible with jointplot)? If you need such a change, it would be better to hardcode the format string into the recipe Like Plot of {shape_id} and then let the diagnostic fill this. This will be much more general.

else:
plt.suptitle(cfg['suptitle'], y=1.05)
if cfg['legend_title'] is not None:
_set_legend_title(plot_obj, cfg['legend_title'])

Expand Down Expand Up @@ -443,6 +447,11 @@ def _set_legend_title(plot_obj, legend_title: str) -> None:
legend = plot_obj.get_legend()
elif hasattr(plot_obj, 'legend'): # FacetGrid, PairGrid
legend = plot_obj.legend
elif isinstance(plot_obj, sns.axisgrid.JointGrid): # JointGrid
# Manually create a legend if needed in JointGrid
handles, labels = plot_obj.ax_joint.get_legend_handles_labels()
if handles and labels:
legend = plot_obj.ax_joint.legend(handles=handles, labels=labels, title=legend_title)
else:
raise ValueError(
f"Cannot set legend title, `{type(plot_obj).__name__}` does not "
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215 changes: 210 additions & 5 deletions esmvaltool/recipes/recipe_seaborn.yml
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Expand Up @@ -13,6 +13,9 @@ documentation:

authors:
- schlund_manuel
- debeire_kevin
- kraft_jeremy
- pacal_aytac

maintainer:
- schlund_manuel
Expand All @@ -26,13 +29,10 @@ documentation:
- isenes3
- usmile


preprocessors:

zonal_mean:
zonal_statistics:
operator: mean

zonal_statistics:
operator: mean
extract_ar6_regions:
regrid:
target_grid: 5x5
Expand All @@ -51,10 +51,215 @@ preprocessors:
- Equatorial.Indic-Ocean
convert_units:
units: mm day-1

extract_regions_pr:
regrid_time: &regrid_time
calendar: standard
frequency: mon
regrid:
target_grid: 5x5
scheme: linear
extract_shape:
shapefile: ar6
crop: true
decomposed: true
ids:
Name: &regions_to_regrid
- N.Europe
- West&Central-Europe
- Mediterranean
- E.Europe
- Caribbean
- E.Antarctica
convert_units:
units: mm day-1

extract_regions_clivi:
regrid_time: *regrid_time
regrid:
target_grid: 5x5
scheme: linear
extract_shape:
shapefile: ar6
crop: true
decomposed: true
ids:
Name: *regions_to_regrid
convert_units:
units: g m-2

extract_region_pr_jointplot:
regrid_time: *regrid_time
regrid:
target_grid: 5x5
scheme: linear
extract_shape:
shapefile: ar6
crop: true
decomposed: true
ids:
Name: &region_to_regrid
- N.Europe
convert_units:
units: mm day-1

extract_region_clivi_jointplot:
regrid_time: *regrid_time
regrid:
target_grid: 5x5
scheme: linear
extract_shape:
shapefile: ar6
crop: true
decomposed: true
ids:
Name: *region_to_regrid
convert_units:
units: g m-2

extract_region_clt_jointplot:
regrid_time: *regrid_time
regrid:
target_grid: 5x5
scheme: linear
extract_shape:
shapefile: ar6
crop: true
decomposed: true
ids:
Name: *region_to_regrid

diagnostics:
plot_precipitation_vs_clivi_jointplot:
description: Scatter plot and histograms of precipitation vs. clivi in grid cells for a single region.
variables:
pr:
mip: Amon
preprocessor: extract_region_pr_jointplot
exp: historical
timerange: '1991/2014'
clivi:
mip: Amon
preprocessor: extract_region_clivi_jointplot
exp: historical
timerange: '1991/2014'
additional_datasets:
- {project: CMIP6, dataset: CESM2-WACCM, grid: gn, ensemble: r1i1p1f1}
- {project: CMIP6, dataset: GFDL-ESM4, grid: gr1, ensemble: r1i1p1f1}
- {project: CMIP6, dataset: ACCESS-CM2, grid: gn, ensemble: r1i1p1f1}
- {project: native6, dataset: ERA5, type: reanaly, version: v1, tier: 3}

scripts:
plot:
script: seaborn_diag.py
seaborn_func: jointplot
groupby_facet: dataset
seaborn_kwargs:
x: pr
y: clivi
marker: .
hue: dataset
add_aux_coords: true
reset_index: true
legend_title: Model
plot_object_methods:
set_axis_labels:
xlabel: 'Precipitation [mm/day]'
ylabel: 'Cloud Ice Water Path [g/m^2]'
suptitle: 'Simulated Precipitation vs. Cloud Ice Water Path (1991-2014) in {}'

plot_precipitation_vs_clt_jointplot:
description: Scatter plot and histograms of precipitation vs. cloud area fraction in grid cells for a single region.
variables:
pr:
mip: Amon
preprocessor: extract_region_pr_jointplot
exp: historical
timerange: '1991/2014'
clt:
mip: Amon
preprocessor: extract_region_clt_jointplot
exp: historical
timerange: '1991/2014'
additional_datasets:
- {project: CMIP6, dataset: CESM2-WACCM, grid: gn, ensemble: r1i1p1f1}
- {project: CMIP6, dataset: GFDL-ESM4, grid: gr1, ensemble: r1i1p1f1}
- {project: CMIP6, dataset: ACCESS-CM2, grid: gn, ensemble: r1i1p1f1}
- {project: native6, dataset: ERA5, type: reanaly, version: v1, tier: 3}

scripts:
plot:
script: seaborn_diag.py
seaborn_func: jointplot
groupby_facet: dataset
seaborn_kwargs:
x: pr
y: clt
marker: .
hue: dataset
add_aux_coords: true
reset_index: true
legend_title: Model
plot_object_methods:
set_axis_labels:
xlabel: 'Precipitation [mm/day]'
ylabel: 'Cloud Area fraction [%]'
suptitle: 'Simulated Precipitation vs. Cloud Area fraction (1991-2014) in {}'

plot_precipitation_vs_clivi:
description: Scatter plots precipitation vs. clivi in grid cells
variables:
pr:
mip: Amon
preprocessor: extract_regions_pr
project: CMIP6
exp: historical
timerange: '1991/2014'
clivi:
mip: Amon
preprocessor: extract_regions_clivi
project: CMIP6
exp: historical
timerange: '1991/2014'
additional_datasets:
- {dataset: CESM2-WACCM, grid: gn, ensemble: r1i1p1f1}
- {dataset: GFDL-ESM4, grid: gr1, ensemble: r1i1p1f1}
- {dataset: ACCESS-CM2, grid: gn, ensemble: r1i1p1f1}
- {dataset: ERA5, project: native6, type: reanaly, version: v1, tier: 3}
scripts:
plot:
script: seaborn_diag.py
seaborn_func: relplot
groupby_facet: dataset
seaborn_kwargs:
x: pr
y: clivi
col: shape_id
col_order: *regions_to_regrid
col_wrap: 3
hue: dataset
marker: .
s: 5
facet_kws:
sharey: false
sharex: false
add_aux_coords: true
dropna_kwargs:
axis: 0
how: any
legend_title: Model
plot_object_methods:
set:
xlabel: 'Precipitation [mm/day]'
ylabel: 'Cloud Ice Water Path [g/m^2]'
set_titles: '{col_name}'
seaborn_settings:
style: ticks
rc:
axes.titlepad: 15.0
suptitle: Simulated Precipitation vs. Cloud Ice Water Path (1991-2014)


plot_temperature_vs_lat:
description: Plot air temperature vs. latitude (pressure levels = colors).
variables:
Expand Down