[quantile regression project] improve display for the quantile regression simulation framework

projects/quantile_regression_vs_evt/AbstractSimulation.py

@@ -32,6 +32,7 @@ class AbstractSimulation(object):
         self.quantile = quantile
         self.time_series_lengths = time_series_lengths
         self.nb_time_series = nb_time_series
+        self.uncertainty_interval_size = 0.5
 
     def generate_all_observation(self, nb_time_series, length) -> List[AbstractSpatioTemporalObservations]:
         raise NotImplementedError
@@ -83,7 +84,8 @@ class AbstractSimulation(object):
             length_to_error_values = OrderedDict()
             for length, estimators_fitted in d_sub.items():
                 errors = self.compute_errors(length, estimators_fitted)
-                error_values = [np.quantile(errors, q=0.025), np.mean(errors), np.quantile(errors, q=0.975)]
+                leftover = (1 - self.uncertainty_interval_size) / 2
+                error_values = [np.quantile(errors, q=leftover), np.mean(errors), np.quantile(errors, q=1-leftover)]
                 length_to_error_values[length] = error_values
             d[model_class] = length_to_error_values
         return d
@@ -92,15 +94,28 @@ class AbstractSimulation(object):
         raise NotImplementedError
 
     def plot_error_for_last_year_quantile(self, show=True):
+        # Display properties
+        alpha = 0.1
+        colors = ['green', 'orange', 'blue', 'red']
         ax = plt.gca()
-        for model_class, length_to_error_values in self.model_class_to_error_last_year_quantile.items():
+        for color, (model_class, length_to_error_values) in zip(colors, self.model_class_to_error_last_year_quantile.items()):
             lengths = list(length_to_error_values.keys())
             errors_values = np.array(list(length_to_error_values.values()))
             mean_error = errors_values[:, 1]
             label = get_display_name_from_object_type(model_class)
             ax.plot(lengths, mean_error, label=label)
             ax.set_xlabel('# Data')
-            ax.set_ylabel('Relative error for the {} quantile at the last coordinate'.format(self.quantile))
+            ax.set_ylabel('Average (out of {} samples) relative error\nfor the {} quantile at the last coordinate (%)'.format(self.nb_time_series,
+                                                                                                                              self.quantile))
+
+            lower_bound = errors_values[:, 0]
+            upper_bound = errors_values[:, 2]
+            # confidence_interval_str = '95 \% confidence interval'
+            ax.fill_between(lengths, lower_bound, upper_bound, color=color, alpha=alpha)
+            title = "{} + {}".format(get_display_name_from_object_type(type(self)),
+                                     get_display_name_from_object_type(self.transformation_class))
+            ax.set_title(title)
+
             ax.legend()
         if show:
             plt.show()

projects/quantile_regression_vs_evt/GevSimulation.py

@@ -59,7 +59,7 @@ class StationarySimulation(GevSimulation):
                                                       fit_method=TemporalMarginFitMethod.extremes_fevd_mle)
 
 
-class NonStationaryLocationSimulation(GevSimulation):
+class NonStationaryLocationGumbelSimulation(GevSimulation):
 
     def create_model(self, coordinates):
         gev_param_name_to_coef_list = {
@@ -69,3 +69,15 @@ class NonStationaryLocationSimulation(GevSimulation):
         }
         return NonStationaryLocationTemporalModel.from_coef_list(coordinates, gev_param_name_to_coef_list,
                                                                  fit_method=TemporalMarginFitMethod.extremes_fevd_mle)
+
+
+class NonStationaryLocationGevSimulation(GevSimulation):
+
+    def create_model(self, coordinates):
+        gev_param_name_to_coef_list = {
+            GevParams.LOC: [0, 1],
+            GevParams.SHAPE: [0.3],
+            GevParams.SCALE: [1],
+        }
+        return NonStationaryLocationTemporalModel.from_coef_list(coordinates, gev_param_name_to_coef_list,
+                                                                 fit_method=TemporalMarginFitMethod.extremes_fevd_mle)

projects/quantile_regression_vs_evt/main_quantile_regression.py

 from extreme_fit.model.margin_model.linear_margin_model.temporal_linear_margin_models import StationaryTemporalModel, \
-    NonStationaryLocationTemporalModel
+    NonStationaryLocationTemporalModel, NonStationaryLocationGumbelModel
 from extreme_fit.model.quantile_model.quantile_regression_model import ConstantQuantileRegressionModel, \
     TemporalCoordinatesQuantileRegressionModel
-from projects.quantile_regression_vs_evt.GevSimulation import StationarySimulation, NonStationaryLocationSimulation
+from projects.quantile_regression_vs_evt.GevSimulation import StationarySimulation, \
+    NonStationaryLocationGumbelSimulation, NonStationaryLocationGevSimulation
+from spatio_temporal_dataset.coordinates.transformed_coordinates.transformation.abstract_transformation import \
+    CenteredScaledNormalization, IdentityTransformation
+from spatio_temporal_dataset.coordinates.transformed_coordinates.transformation.uniform_normalization import \
+    BetweenZeroAndOneNormalization
 
 nb_time_series = 10
-quantile = 0.9
+quantile = 0.98
 time_series_lengths = [50, 100, 200]
+transformation_class = [IdentityTransformation, CenteredScaledNormalization][0]
+model_classes = [NonStationaryLocationTemporalModel, TemporalCoordinatesQuantileRegressionModel, NonStationaryLocationGumbelModel]
+simulation_class = [NonStationaryLocationGumbelSimulation, NonStationaryLocationGevSimulation][0]
 
-# simulation = StationarySimulation(nb_time_series=nb_time_series, quantile=quantile, time_series_lengths=time_series_lengths,
-#                                   model_classes=[StationaryTemporalModel, ConstantQuantileRegressionModel])
-# simulation.plot_error_for_last_year_quantile()
-
-simulation = NonStationaryLocationSimulation(nb_time_series=nb_time_series, quantile=quantile, time_series_lengths=time_series_lengths,
-                                  model_classes=[NonStationaryLocationTemporalModel, TemporalCoordinatesQuantileRegressionModel][:])
+simulation = NonStationaryLocationGumbelSimulation(nb_time_series=nb_time_series,
+                                                   quantile=quantile,
+                                                   time_series_lengths=time_series_lengths,
+                                                   model_classes=model_classes,
+                                                   transformation_class=transformation_class)
 simulation.plot_error_for_last_year_quantile()

test/test_projects/test_quantile_regression/test_gev_simulations.py

@@ -5,7 +5,7 @@ from extreme_fit.model.margin_model.linear_margin_model.temporal_linear_margin_m
 from extreme_fit.model.quantile_model.quantile_regression_model import ConstantQuantileRegressionModel, \
     TemporalCoordinatesQuantileRegressionModel
 from projects.quantile_regression_vs_evt.GevSimulation import GevSimulation, StationarySimulation, \
-    NonStationaryLocationSimulation
+    NonStationaryLocationGumbelSimulation
 
 
 class TestGevSimulations(unittest.TestCase):
@@ -17,8 +17,8 @@ class TestGevSimulations(unittest.TestCase):
         simulation.plot_error_for_last_year_quantile(self.DISPLAY)
 
     def test_non_stationary_run(self):
-        simulation = NonStationaryLocationSimulation(nb_time_series=1, quantile=0.5, time_series_lengths=[50, 60],
-                                                     model_classes=[NonStationaryLocationTemporalModel,
+        simulation = NonStationaryLocationGumbelSimulation(nb_time_series=1, quantile=0.5, time_series_lengths=[50, 60],
+                                                           model_classes=[NonStationaryLocationTemporalModel,
                                                                     TemporalCoordinatesQuantileRegressionModel])
         simulation.plot_error_for_last_year_quantile(self.DISPLAY)