From ef98837860cf795aec2be3d1baf138700dc11ad5 Mon Sep 17 00:00:00 2001
From: Le Roux Erwan <erwan.le-roux@irstea.fr>
Date: Tue, 26 Feb 2019 11:17:53 +0100
Subject: [PATCH] [SCM] improve empirical distribution visualization for
slides. add single_massif_graph visualization
---
.../meteo_france_SCM_study/main_visualize.py | 6 +--
.../safran/safran_visualizer.py | 45 +++++++++++--------
.../abstract_margin_function.py | 11 ++++-
.../margin_fits/abstract_params.py | 7 +--
.../test_extreme_models/test_margin_model.py | 44 +++++++++++++-----
5 files changed, 77 insertions(+), 36 deletions(-)
diff --git a/experiment/meteo_france_SCM_study/main_visualize.py b/experiment/meteo_france_SCM_study/main_visualize.py
index 2cf6622d..180ea81b 100644
--- a/experiment/meteo_france_SCM_study/main_visualize.py
+++ b/experiment/meteo_france_SCM_study/main_visualize.py
@@ -33,9 +33,9 @@ def study_iterator(study_class, only_first_one=False, both_altitude=False, verbo
def extended_visualization():
- for study_class in SCM_EXTENDED_STUDIES[-1:]:
- for study in study_iterator(study_class, only_first_one=True):
- study_visualizer = StudyVisualizer(study)
+ for study_class in SCM_EXTENDED_STUDIES[:]:
+ for study in study_iterator(study_class, only_first_one=False):
+ study_visualizer = StudyVisualizer(study, single_massif_graph=True, save_to_file=True)
# study_visualizer.visualize_all_kde_graphs()
study_visualizer.visualize_all_experimental_law()
diff --git a/experiment/meteo_france_SCM_study/safran/safran_visualizer.py b/experiment/meteo_france_SCM_study/safran/safran_visualizer.py
index 90ac03a8..8e3b0f91 100644
--- a/experiment/meteo_france_SCM_study/safran/safran_visualizer.py
+++ b/experiment/meteo_france_SCM_study/safran/safran_visualizer.py
@@ -28,7 +28,8 @@ from utils import get_display_name_from_object_type, VERSION_TIME, float_to_str_
class StudyVisualizer(object):
- def __init__(self, study: AbstractStudy, show=True, save_to_file=False):
+ def __init__(self, study: AbstractStudy, show=True, save_to_file=False, single_massif_graph=False):
+ self.single_massif_graph = single_massif_graph
self.save_to_file = save_to_file
self.study = study
self.show = False if self.save_to_file else show
@@ -50,18 +51,22 @@ class StudyVisualizer(object):
# Graph for each massif / or groups of massifs
def visualize_massif_graphs(self, visualize_function):
- nb_columns = 5
- nb_rows = math.ceil(len(self.study.safran_massif_names) / nb_columns)
- fig, axes = plt.subplots(nb_rows, nb_columns, figsize=self.figsize)
- fig.subplots_adjust(hspace=1.0, wspace=1.0)
- for massif_id, massif_name in enumerate(self.study.safran_massif_names):
- row_id, column_id = massif_id // nb_columns, massif_id % nb_columns
- ax = axes[row_id, column_id]
- visualize_function(ax, massif_id)
+ if self.single_massif_graph:
+ fig, ax = plt.subplots(1, 1, figsize=self.figsize)
+ visualize_function(ax, 0)
+ else:
+ nb_columns = 5
+ nb_rows = math.ceil(len(self.study.safran_massif_names) / nb_columns)
+ fig, axes = plt.subplots(nb_rows, nb_columns, figsize=self.figsize)
+ fig.subplots_adjust(hspace=1.0, wspace=1.0)
+ for massif_id, massif_name in enumerate(self.study.safran_massif_names):
+ row_id, column_id = massif_id // nb_columns, massif_id % nb_columns
+ ax = axes[row_id, column_id]
+ visualize_function(ax, massif_id)
def visualize_all_experimental_law(self):
self.visualize_massif_graphs(self.visualize_experimental_law)
- plot_name = ' Experimental law with all the data'
+ plot_name = ' Empirical distribution with all available data'
self.show_or_save_to_file(plot_name)
def visualize_experimental_law(self, ax, massif_id):
@@ -76,24 +81,26 @@ class StudyVisualizer(object):
# Plot the mean point in green
x_level_to_color = {
- np.mean(all_massif_data): 'g',
+ np.mean(all_massif_data): ('g', 'mean'),
}
- # Plot some specific quantiles in red
- for p in AbstractParams.QUANTILE_P_VALUES:
+ # Plot some specific quantiles in their color
+ for p, color, name in zip(AbstractParams.QUANTILE_P_VALUES, AbstractParams.QUANTILE_COLORS, AbstractParams.QUANTILE_NAMES):
x_level = all_massif_data[int(p * len(all_massif_data))]
- x_level_to_color[x_level] = 'r'
+ x_level_to_color[x_level] = (color, name)
- for xi, color in x_level_to_color.items():
+ for xi, (color, name) in x_level_to_color.items():
yi = np.interp(xi, data_x, data_y)
- ax.plot([xi], [yi], color=color, marker="o")
+ ax.scatter([xi], [yi], color=color, marker="o", label=name)
- ax.set_ylabel('Density', color=color_kde)
- ax.set_xlabel(self.study.title)
+ ax.set_ylabel('Probability Density function f(x)', color=color_kde)
+ ax.set_xlabel('x = {}'.format(self.study.title))
extraticks = [float(float_to_str_with_only_some_significant_digits(x, nb_digits=2))
for x in sorted(list(x_level_to_color.keys()))]
- extraticks = [extraticks[0], extraticks[-1]]
+ if not self.single_massif_graph:
+ extraticks = [extraticks[0], extraticks[-1]]
ax.set_xticks(extraticks)
ax.set_title(self.study.safran_massif_names[massif_id])
+ ax.legend()
def visualize_all_mean_and_max_graphs(self):
self.visualize_massif_graphs(self.visualize_mean_and_max_graph)
diff --git a/extreme_estimator/extreme_models/margin_model/margin_function/abstract_margin_function.py b/extreme_estimator/extreme_models/margin_model/margin_function/abstract_margin_function.py
index cc1ac24b..a88c4beb 100644
--- a/extreme_estimator/extreme_models/margin_model/margin_function/abstract_margin_function.py
+++ b/extreme_estimator/extreme_models/margin_model/margin_function/abstract_margin_function.py
@@ -78,8 +78,10 @@ class AbstractMarginFunction(object):
self.visualize_1D(gev_value_name, ax, show)
elif self.coordinates.nb_coordinates_spatial == 2:
self.visualize_2D(gev_value_name, ax, show)
+ elif self.coordinates.nb_coordinates_spatial == 3:
+ self.visualize_3D(gev_value_name, ax, show)
else:
- raise NotImplementedError('3D Margin visualization not yet implemented')
+ raise NotImplementedError('Other visualization not yet implemented')
# Visualization 1D
@@ -159,3 +161,10 @@ class AbstractMarginFunction(object):
grid = {value_name: np.array([g[value_name] for g in grid]).reshape([resolution, resolution])
for value_name in GevParams.SUMMARY_NAMES}
return grid
+
+ # Visualization 3D
+
+ def visualize_3D(self, gev_param_name=GevParams.LOC, ax=None, show=True):
+ # Make the first/the last time step 2D visualization side by side
+ # self.visualize_2D(gev_param_name=gev_param_name, ax=ax, show=show)
+ pass
diff --git a/extreme_estimator/margin_fits/abstract_params.py b/extreme_estimator/margin_fits/abstract_params.py
index 659aa06d..338b4b8d 100644
--- a/extreme_estimator/margin_fits/abstract_params.py
+++ b/extreme_estimator/margin_fits/abstract_params.py
@@ -8,11 +8,12 @@ class AbstractParams(object):
# Parameters
PARAM_NAMES = []
# Quantile
- QUANTILE_10 = 'quantile 10'
- QUANTILE_100 = 'quantile 100'
- QUANTILE_1000 = 'quantile 1000'
+ QUANTILE_10 = 'quantile 0.9'
+ QUANTILE_100 = 'quantile 0.99'
+ QUANTILE_1000 = 'quantile 0.999'
QUANTILE_NAMES = [QUANTILE_10, QUANTILE_100, QUANTILE_1000][:-1]
QUANTILE_P_VALUES = [0.9, 0.99, 0.999][:-1]
+ QUANTILE_COLORS = ['orange', 'red', 'darkviolet']
# Summary
SUMMARY_NAMES = PARAM_NAMES + QUANTILE_NAMES
diff --git a/test/test_extreme_estimator/test_extreme_models/test_margin_model.py b/test/test_extreme_estimator/test_extreme_models/test_margin_model.py
index 7611f024..1be2e00e 100644
--- a/test/test_extreme_estimator/test_extreme_models/test_margin_model.py
+++ b/test/test_extreme_estimator/test_extreme_models/test_margin_model.py
@@ -1,29 +1,53 @@
import unittest
+from extreme_estimator.extreme_models.margin_model.margin_function.linear_margin_function import LinearMarginFunction
from extreme_estimator.margin_fits.gev.gev_params import GevParams
from extreme_estimator.extreme_models.margin_model.smooth_margin_model import LinearShapeDim1MarginModel, \
LinearAllParametersAllDimsMarginModel
-from spatio_temporal_dataset.coordinates.spatial_coordinates.generated_spatial_coordinates import CircleSpatialCoordinates
+from spatio_temporal_dataset.coordinates.spatial_coordinates.generated_spatial_coordinates import \
+ CircleSpatialCoordinates
from spatio_temporal_dataset.coordinates.spatial_coordinates.coordinates_1D import LinSpaceSpatialCoordinates
+from test.test_utils import load_test_spatiotemporal_coordinates
class VisualizationMarginModel(unittest.TestCase):
DISPLAY = False
nb_points = 2
- margin_model = [LinearShapeDim1MarginModel, LinearAllParametersAllDimsMarginModel][-1]
+ margin_model_class = [LinearShapeDim1MarginModel, LinearAllParametersAllDimsMarginModel][-1]
- def test_example_visualization_2D(self):
- spatial_coordinates = CircleSpatialCoordinates.from_nb_points(nb_points=self.nb_points)
- margin_model = self.margin_model(coordinates=spatial_coordinates)
- if self.DISPLAY:
- margin_model.margin_function_sample.visualize_function()
+ def tearDown(self) -> None:
+ self.margin_model.margin_function_sample.visualize_function(show=self.DISPLAY)
+ self.assertTrue(True)
def test_example_visualization_1D(self):
coordinates = LinSpaceSpatialCoordinates.from_nb_points(nb_points=self.nb_points)
- margin_model = self.margin_model(coordinates=coordinates, params_sample={(GevParams.SHAPE, 1): 0.02})
- margin_model.margin_function_sample.visualize_function(show=self.DISPLAY)
- self.assertTrue(True)
+ self.margin_model = self.margin_model_class(coordinates=coordinates, params_sample={(GevParams.SHAPE, 1): 0.02})
+
+ def test_example_visualization_2D_spatial(self):
+ spatial_coordinates = CircleSpatialCoordinates.from_nb_points(nb_points=self.nb_points)
+ self.margin_model = self.margin_model_class(coordinates=spatial_coordinates)
+
+ # def test_example_visualization_2D_spatio_temporal(self):
+ # self.nb_steps = 2
+ # coordinates = load_test_spatiotemporal_coordinates(nb_steps=self.nb_steps, nb_points=self.nb_points)[0]
+ # self.margin_model = self.margin_model_class(coordinates)
+ #
+ # # Load margin function from coef dict
+ # coef_dict = {'locCoeff1': 0, 'locCoeff2': 1, 'scaleCoeff1': 0,
+ # 'scaleCoeff2': 1, 'shapeCoeff1': 0,
+ # 'shapeCoeff2': 1,
+ # 'tempCoeffLoc1': 1, 'tempCoeffScale1': 1,
+ # 'tempCoeffShape1': 1}
+ # margin_function = LinearMarginFunction.from_coef_dict(coordinates,
+ # self.margin_model.margin_function_sample.gev_param_name_to_linear_dims,
+ # coef_dict)
+ # self.margin_model.margin_function_sample = margin_function
+ # self.margin_model.margin_function_sample.visualize_2D(show=True)
+ #
+ # # Load
if __name__ == '__main__':
unittest.main()
+ # v = VisualizationMarginModel()
+ # v.test_example_visualization_2D_spatio_temporal()
--
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