From b3842718461a7361cc79c0b58039622920f0d8f6 Mon Sep 17 00:00:00 2001
From: leufen1 <l.leufen@fz-juelich.de>
Date: Tue, 26 Oct 2021 11:30:24 +0200
Subject: [PATCH] PlotBootstrapSkillScore is now called
PlotFeatureImportanceSkillScore
---
mlair/configuration/defaults.py | 2 +-
mlair/plotting/postprocessing_plotting.py | 12 ++++--------
mlair/run_modules/post_processing.py | 23 +++++++++++------------
3 files changed, 16 insertions(+), 21 deletions(-)
diff --git a/mlair/configuration/defaults.py b/mlair/configuration/defaults.py
index 9b79dc6a..ca569720 100644
--- a/mlair/configuration/defaults.py
+++ b/mlair/configuration/defaults.py
@@ -54,7 +54,7 @@ DEFAULT_FEATURE_IMPORTANCE_N_BOOTS = 20
DEFAULT_FEATURE_IMPORTANCE_BOOTSTRAP_TYPE = "singleinput"
DEFAULT_FEATURE_IMPORTANCE_BOOTSTRAP_METHOD = "shuffle"
DEFAULT_PLOT_LIST = ["PlotMonthlySummary", "PlotStationMap", "PlotClimatologicalSkillScore", "PlotTimeSeries",
- "PlotCompetitiveSkillScore", "PlotBootstrapSkillScore", "PlotConditionalQuantiles",
+ "PlotCompetitiveSkillScore", "PlotFeatureImportanceSkillScore", "PlotConditionalQuantiles",
"PlotAvailability", "PlotAvailabilityHistogram", "PlotDataHistogram", "PlotPeriodogram",
"PlotSampleUncertaintyFromBootstrap"]
DEFAULT_SAMPLING = "daily"
diff --git a/mlair/plotting/postprocessing_plotting.py b/mlair/plotting/postprocessing_plotting.py
index c95afea6..d9551815 100644
--- a/mlair/plotting/postprocessing_plotting.py
+++ b/mlair/plotting/postprocessing_plotting.py
@@ -591,14 +591,9 @@ class PlotCompetitiveSkillScore(AbstractPlotClass): # pragma: no cover
@TimeTrackingWrapper
-class PlotBootstrapSkillScore(AbstractPlotClass): # pragma: no cover
+class PlotFeatureImportanceSkillScore(AbstractPlotClass): # pragma: no cover
"""
- Create plot of climatological skill score after Murphy (1988) as box plot over all stations.
-
- A forecast time step (called "ahead") is separately shown to highlight the differences for each prediction time
- step. Either each single term is plotted (score_only=False) or only the resulting scores CASE I to IV are displayed
- (score_only=True, default). Y-axis is adjusted following the data and not hard coded. The plot is saved under
- plot_folder path with name skill_score_clim_{extra_name_tag}{model_setup}.pdf and resolution of 500dpi.
+ Create plot of feature importance analysis.
By passing a list `separate_vars` containing variable names, a second plot is created showing the `separate_vars`
and the remaining variables side by side with different scaling.
@@ -757,7 +752,8 @@ class PlotBootstrapSkillScore(AbstractPlotClass): # pragma: no cover
data_second = self._select_data(df=data, variables=remaining_vars, column_name=self._x_name)
fig, ax = plt.subplots(nrows=1, ncols=2, gridspec_kw={'width_ratios': [len(separate_vars),
- len(remaining_vars)]})
+ len(remaining_vars)]},
+ figsize=(len(remaining_vars),len(remaining_vars)/2.))
if len(separate_vars) > 1:
first_box_width = .8
else:
diff --git a/mlair/run_modules/post_processing.py b/mlair/run_modules/post_processing.py
index 0c516242..64ac9805 100644
--- a/mlair/run_modules/post_processing.py
+++ b/mlair/run_modules/post_processing.py
@@ -22,7 +22,7 @@ from mlair.helpers import TimeTracking, statistics, extract_value, remove_items,
from mlair.model_modules.linear_model import OrdinaryLeastSquaredModel
from mlair.model_modules import AbstractModelClass
from mlair.plotting.postprocessing_plotting import PlotMonthlySummary, PlotClimatologicalSkillScore, \
- PlotCompetitiveSkillScore, PlotTimeSeries, PlotBootstrapSkillScore, PlotConditionalQuantiles, \
+ PlotCompetitiveSkillScore, PlotTimeSeries, PlotFeatureImportanceSkillScore, PlotConditionalQuantiles, \
PlotSeparationOfScales, PlotSampleUncertaintyFromBootstrap
from mlair.plotting.data_insight_plotting import PlotStationMap, PlotAvailability, PlotAvailabilityHistogram, \
PlotPeriodogram, PlotDataHistogram
@@ -471,22 +471,21 @@ class PostProcessing(RunEnvironment):
f"\n{sys.exc_info()[0]}\n{sys.exc_info()[1]}\n{sys.exc_info()[2]}")
try:
- if (self.feature_importance_skill_scores is not None) and ("PlotBootstrapSkillScore" in plot_list):
+ if (self.feature_importance_skill_scores is not None) and ("PlotFeatureImportanceSkillScore" in plot_list):
for boot_type, boot_data in self.feature_importance_skill_scores.items():
for boot_method, boot_skill_score in boot_data.items():
try:
- #todo rename plot name
- #todo check if plot works properly
- PlotBootstrapSkillScore(boot_skill_score, plot_folder=self.plot_path,
- model_setup=self.forecast_indicator, sampling=self._sampling,
- ahead_dim=self.ahead_dim, separate_vars=to_list(self.target_var),
- bootstrap_type=boot_type, bootstrap_method=boot_method)
+ PlotFeatureImportanceSkillScore(
+ boot_skill_score, plot_folder=self.plot_path, model_setup=self.forecast_indicator,
+ sampling=self._sampling, ahead_dim=self.ahead_dim,
+ separate_vars=to_list(self.target_var), bootstrap_type=boot_type,
+ bootstrap_method=boot_method)
except Exception as e:
- logging.error(f"Could not create plot PlotBootstrapSkillScore ({boot_type}, {boot_method}) "
- f"due to the following error:\n{sys.exc_info()[0]}\n{sys.exc_info()[1]}\n"
- f"{sys.exc_info()[2]}")
+ logging.error(f"Could not create plot PlotFeatureImportanceSkillScore ({boot_type}, "
+ f"{boot_method}) due to the following error:\n{sys.exc_info()[0]}\n"
+ f"{sys.exc_info()[1]}\n{sys.exc_info()[2]}")
except Exception as e:
- logging.error(f"Could not create plot PlotBootstrapSkillScore due to the following error: {e}")
+ logging.error(f"Could not create plot PlotFeatureImportanceSkillScore due to the following error: {e}")
try:
if "PlotConditionalQuantiles" in plot_list:
--
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