diff --git a/mlair/plotting/data_insight_plotting.py b/mlair/plotting/data_insight_plotting.py
index 3440321a8708ee905c5c991c4c8c5a1870719e63..aff3b4c73fa90ac10325b025eb39116f95af9a58 100644
--- a/mlair/plotting/data_insight_plotting.py
+++ b/mlair/plotting/data_insight_plotting.py
@@ -20,70 +20,50 @@ from mlair.helpers import TimeTrackingWrapper, to_list
from mlair.plotting.abstract_plot_class import AbstractPlotClass
@TimeTrackingWrapper
-class PlotOversamplingHistogram(AbstractPlotClass):
+class PlotOversampling(AbstractPlotClass):
- def __init__(self, Y, Y_extreme, bin_edges, plot_folder: str = ".",
- plot_name="oversampling_histogram"):
+ def __init__(self, Y, Y_extreme, bin_edges, oversampling_rates, plot_folder: str = ".",
+ plot_names=["oversampling_histogram", "oversampling_density_histogram", "oversampling_rates",
+ "oversampling_rates_deviation"]):
- super().__init__(plot_folder, plot_name)
- self._plot(Y, Y_extreme, bin_edges)
+ super().__init__(plot_folder, plot_names[0])
+ Y_hist, Y_extreme_hist = self._plot_oversampling_histogram(Y, Y_extreme, bin_edges)
+ real_oversampling = Y_extreme_hist / Y_hist
+ self._save()
+ self.plot_name = plot_names[1]
+ self._plot_oversampling_density_histogram(Y, Y_extreme, bin_edges)
+ self._save()
+ self.plot_name = plot_names[2]
+ self._plot_oversampling_rates(oversampling_rates, real_oversampling)
+ self._save()
+ self.plot_name = plot_names[3]
+ self._plot_oversampling_rates_deviation(oversampling_rates, real_oversampling)
self._save()
- def _plot(self, Y, Y_extreme, bin_edges):
+ def _plot_oversampling_histogram(self, Y, Y_extreme, bin_edges):
fig, ax = plt.subplots(1, 1)
- Y.plot.hist(bins=bin_edges, histtype="step", label="Before", ax=ax)[0]
- Y_extreme.plot.hist(bins=bin_edges, histtype="step", label="After", ax=ax)[0]
+ Y_hist = Y.plot.hist(bins=bin_edges, histtype="step", label="Before", ax=ax)[0]
+ Y_extreme_hist = Y_extreme.plot.hist(bins=bin_edges, histtype="step", label="After", ax=ax)[0]
ax.set_title(f"Histogram before-after oversampling")
ax.legend()
+ return Y_hist, Y_extreme_hist
-
-@TimeTrackingWrapper
-class PlotOversamplingDensityHistogram(AbstractPlotClass):
-
- def __init__(self, Y, Y_extreme, bin_edges, plot_folder: str = ".",
- plot_name="oversampling_density_histogram"):
- super().__init__(plot_folder, plot_name)
- self._plot(Y, Y_extreme, bin_edges)
- self._save()
-
- def _plot(self, Y, Y_extreme, bin_edges):
+ def _plot_oversampling_density_histogram(self, Y, Y_extreme, bin_edges):
fig, ax = plt.subplots(1, 1)
Y.plot.hist(bins=bin_edges, density=True, histtype="step", label="Before", ax=ax)[0]
Y_extreme.plot.hist(bins=bin_edges, density=True, histtype="step", label="After", ax=ax)[0]
ax.set_title(f"Density Histogram before-after oversampling")
ax.legend()
-
-@TimeTrackingWrapper
-class PlotOversamplingRates(AbstractPlotClass):
-
- def __init__(self, Y, Y_extreme, bin_edges, oversampling_rates, Y_hist, Y_extreme_hist, plot_folder: str = ".",
- plot_name="oversampling_rates"):
- super().__init__(plot_folder, plot_name)
- self._plot(Y, Y_extreme, bin_edges, oversampling_rates, Y_hist, Y_extreme_hist)
- self._save()
-
- def _plot(self, Y, Y_extreme, bin_edges, oversampling_rates, Y_hist, Y_extreme_hist):
+ def _plot_oversampling_rates(self, oversampling_rates, real_oversampling):
fig, ax = plt.subplots(1, 1)
- real_oversampling = Y_extreme_hist[0] / Y_hist[0]
ax.plot(range(len(real_oversampling)), oversampling_rates, label="Desired oversampling_rates")
ax.plot(range(len(real_oversampling)), real_oversampling, label="Actual Oversampling Rates")
ax.set_title(f"Oversampling rates")
ax.legend()
-
-@TimeTrackingWrapper
-class PlotOversamplingRatesDeviation(AbstractPlotClass):
-
- def __init__(self, Y, Y_extreme, bin_edges, oversampling_rates, Y_hist, Y_extreme_hist, plot_folder: str = ".",
- plot_name="oversampling_rates_deviation"):
- super().__init__(plot_folder, plot_name)
- self._plot(Y, Y_extreme, bin_edges, oversampling_rates, Y_hist, Y_extreme_hist)
- self._save()
-
- def _plot(self, Y, Y_extreme, bin_edges, oversampling_rates, Y_hist, Y_extreme_hist):
+ def _plot_oversampling_rates_deviation(self, oversampling_rates, real_oversampling):
fig, ax = plt.subplots(1, 1)
- real_oversampling = Y_extreme_hist[0] / Y_hist[0]
ax.plot(range(len(real_oversampling)), real_oversampling / oversampling_rates,
label="Actual/Desired Rate")
ax.set_title(f"Deviation from desired oversampling rates")
diff --git a/mlair/run_modules/post_processing.py b/mlair/run_modules/post_processing.py
index 742acf2f772abded667bff3a54b17064f5901c4b..74e786a6b994c4082c70949621b8584e8bf0018e 100644
--- a/mlair/run_modules/post_processing.py
+++ b/mlair/run_modules/post_processing.py
@@ -22,8 +22,7 @@ from mlair.model_modules import AbstractModelClass
from mlair.plotting.postprocessing_plotting import PlotMonthlySummary, PlotClimatologicalSkillScore, \
PlotCompetitiveSkillScore, PlotTimeSeries, PlotBootstrapSkillScore, PlotConditionalQuantiles, PlotSeparationOfScales
from mlair.plotting.data_insight_plotting import PlotStationMap, PlotAvailability, PlotAvailabilityHistogram, \
- PlotPeriodogram, PlotDataHistogram, PlotOversamplingHistogram, PlotOversamplingDensityHistogram, \
- PlotOversamplingRates, PlotOversamplingRatesDeviation
+ PlotPeriodogram, PlotDataHistogram, PlotOversampling
from mlair.run_modules.run_environment import RunEnvironment
@@ -313,14 +312,7 @@ class PostProcessing(RunEnvironment):
oversampling_rates = self.data_store.get('oversampling_rates_capped','train')
Y = self.data_store.get('Oversampling_Y')
Y_extreme = self.data_store.get('Oversampling_Y_extreme')
- Y_hist = Y.plot.hist(bins=bin_edges, histtype="step")
- Y_extreme_hist = Y_extreme.plot.hist(bins=bin_edges, histtype="step")
- PlotOversamplingHistogram(Y, Y_extreme, bin_edges, plot_folder=self.plot_path)
- PlotOversamplingDensityHistogram(Y, Y_extreme, bin_edges, plot_folder=self.plot_path)
- PlotOversamplingRates(Y, Y_extreme, bin_edges, oversampling_rates, Y_hist, Y_extreme_hist,
- plot_folder=self.plot_path)
- PlotOversamplingRatesDeviation(Y, Y_extreme, bin_edges, oversampling_rates, Y_hist,
- Y_extreme_hist, plot_folder=self.plot_path)
+ PlotOversampling(Y, Y_extreme, bin_edges, oversampling_rates, plot_folder=self.plot_path)
except Exception as e:
logging.error(f"Could not create plot OversamplingPlots due to the following error: {e}")