diff --git a/extreme_estimator/estimator/margin_estimator.py b/extreme_estimator/estimator/margin_estimator.py
index 30bb6836f6494ab6dc5fabe4077ae0d026d2b8fe..82fdc39fbdf040d24a41d22cf992e4d294acf3f0 100644
--- a/extreme_estimator/estimator/margin_estimator.py
+++ b/extreme_estimator/estimator/margin_estimator.py
@@ -1,5 +1,8 @@
from extreme_estimator.extreme_models.margin_model.abstract_margin_model import AbstractMarginModel
from extreme_estimator.estimator.abstract_estimator import AbstractEstimator
+from extreme_estimator.extreme_models.margin_model.margin_function.abstract_margin_function import \
+ AbstractMarginFunction
+from extreme_estimator.extreme_models.margin_model.smooth_margin_model import LinearMarginModel
from spatio_temporal_dataset.dataset.abstract_dataset import AbstractDataset
@@ -11,8 +14,8 @@ class AbstractMarginEstimator(AbstractEstimator):
self._margin_function_fitted = None
@property
- def margin_function_fitted(self):
- assert self._margin_function_fitted is not None, 'Error: estimator has not been not fitted yet'
+ def margin_function_fitted(self) -> AbstractMarginFunction:
+ assert self._margin_function_fitted is not None, 'Error: estimator has not been fitted'
return self._margin_function_fitted
@@ -23,9 +26,9 @@ class PointWiseMarginEstimator(AbstractMarginEstimator):
class SmoothMarginEstimator(AbstractMarginEstimator):
"""# with different type of marginals: cosntant, linear...."""
- def __init__(self, dataset: AbstractDataset, margin_model: AbstractMarginModel):
+ def __init__(self, dataset: AbstractDataset, margin_model: LinearMarginModel):
super().__init__(dataset)
- assert isinstance(margin_model, AbstractMarginModel)
+ assert isinstance(margin_model, LinearMarginModel)
self.margin_model = margin_model
def _fit(self):
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 6db453091f16ea9c8890c8ba1fac0bc1641d6f29..e5a593b45c1f1241c22fd4e1f075a2dd0c05e33f 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
@@ -18,16 +18,23 @@ class AbstractMarginFunction(object):
def get_gev_params(self, coordinate: np.ndarray) -> GevParams:
pass
- def visualize_2D(self, gev_param_name=GevParams.GEV_LOC, show=False):
+ def visualize_2D(self, gev_param_name=GevParams.GEV_LOC, ax=None, show=False):
x = self.spatial_coordinates.x_coordinates
y = self.spatial_coordinates.y_coordinates
+ grid = self.get_grid_2D(x, y)
+ gev_param_idx = GevParams.GEV_PARAM_NAMES.index(gev_param_name)
+ if ax is None:
+ ax = plt.gca()
+ imshow_method = ax.imshow
+ imshow_method(grid[..., gev_param_idx], extent=(x.min(), x.max(), y.min(), y.max()),
+ interpolation='nearest', cmap=cm.gist_rainbow)
+ if show:
+ plt.show()
+
+ def get_grid_2D(self, x, y):
resolution = 100
grid = np.zeros([resolution, resolution, 3])
for i, xi in enumerate(np.linspace(x.min(), x.max(), resolution)):
for j, yj in enumerate(np.linspace(y.min(), y.max(), resolution)):
grid[i, j] = self.get_gev_params(np.array([xi, yj])).to_array()
- gev_param_idx = GevParams.GEV_PARAM_NAMES.index(gev_param_name)
- plt.imshow(grid[..., gev_param_idx], extent=(x.min(), x.max(), y.min(), y.max()),
- interpolation='nearest', cmap=cm.gist_rainbow)
- if show:
- plt.show()
+ return grid
diff --git a/extreme_estimator/extreme_models/margin_model/smooth_margin_model.py b/extreme_estimator/extreme_models/margin_model/smooth_margin_model.py
index 8d9febabb2a1d9bee04fb38a1e70af3e9daedca2..6a33d939a567af114610bfc45b2fba0653d5c9ff 100644
--- a/extreme_estimator/extreme_models/margin_model/smooth_margin_model.py
+++ b/extreme_estimator/extreme_models/margin_model/smooth_margin_model.py
@@ -33,8 +33,8 @@ class LinearShapeAxis0MarginModel(LinearMarginModel):
def load_margin_functions(self, margin_function_class: type = None, gev_param_name_to_linear_axis=None):
super().load_margin_functions({GevParams.GEV_SHAPE: 0})
- # def fitmargin_from_maxima_gev(self, maxima_gev: np.ndarray, coordinates: np.ndarray) -> AbstractMarginFunction:
- # return self.margin_function_start_fit
+ def fitmargin_from_maxima_gev(self, maxima_gev: np.ndarray, coordinates: np.ndarray) -> AbstractMarginFunction:
+ return self.margin_function_start_fit
if __name__ == '__main__':
diff --git a/extreme_estimator/return_level_plot/spatial_2D_plot.py b/extreme_estimator/return_level_plot/spatial_2D_plot.py
new file mode 100644
index 0000000000000000000000000000000000000000..8347b0e90cf475097612577e6dc9296a8d698542
--- /dev/null
+++ b/extreme_estimator/return_level_plot/spatial_2D_plot.py
@@ -0,0 +1,30 @@
+from itertools import product
+from typing import List, Dict
+
+import matplotlib.pyplot as plt
+
+from extreme_estimator.extreme_models.margin_model.margin_function.abstract_margin_function import \
+ AbstractMarginFunction
+from extreme_estimator.gev_params import GevParams
+
+plt.style.use('seaborn-white')
+
+
+class Spatial2DPlot(object):
+
+ def __init__(self, name_to_margin_function: Dict[str, AbstractMarginFunction]):
+ self.name_to_margin_function = name_to_margin_function # type: Dict[str, AbstractMarginFunction]
+ self.grid_columns = GevParams.GEV_PARAM_NAMES
+
+ def plot(self):
+ nb_grid_rows, nb_grid_columns = len(self.name_to_margin_function), len(self.grid_columns)
+ fig, axes = plt.subplots(nb_grid_rows, nb_grid_columns, sharex='col', sharey='row')
+ fig.subplots_adjust(hspace=0.4, wspace=0.4)
+ margin_function: AbstractMarginFunction
+ for i, (name, margin_function) in enumerate(self.name_to_margin_function.items()):
+ for j, param_name in enumerate(self.grid_columns):
+ ax = axes[i, j] if nb_grid_rows > 1 else axes[j]
+ margin_function.visualize_2D(gev_param_name=param_name, ax=ax)
+ ax.set_title("{} for {}".format(param_name, name))
+ fig.suptitle('Spatial2DPlot')
+ plt.show()
diff --git a/test/test_extreme_estimator/test_estimator/test_full_estimators.py b/test/test_extreme_estimator/test_estimator/test_full_estimators.py
index 5e03f8fd0d6a070d239cba3705fab66c00d271ba..49df744f0ded4bbefef5f84e2825a2e02bf2e4d4 100644
--- a/test/test_extreme_estimator/test_estimator/test_full_estimators.py
+++ b/test/test_extreme_estimator/test_estimator/test_full_estimators.py
@@ -4,7 +4,7 @@ from itertools import product
from extreme_estimator.estimator.full_estimator import SmoothMarginalsThenUnitaryMsp
from spatio_temporal_dataset.dataset.simulation_dataset import FullSimulatedDataset
from spatio_temporal_dataset.spatial_coordinates.generated_coordinates import CircleCoordinatesRadius1
-from test.test_extreme_estimator.test_estimator.test_margin_estimators import TestMarginEstimators
+from test.test_extreme_estimator.test_estimator.test_margin_estimators import TestSmoothMarginEstimator
from test.test_extreme_estimator.test_estimator.test_max_stable_estimators import TestMaxStableEstimators
@@ -16,7 +16,7 @@ class TestFullEstimators(unittest.TestCase):
super().setUp()
self.spatial_coordinates = CircleCoordinatesRadius1.from_nb_points(nb_points=5, max_radius=1)
self.max_stable_models = TestMaxStableEstimators.load_max_stable_models()
- self.margin_models = TestMarginEstimators.load_margin_models(spatial_coordinates=self.spatial_coordinates)
+ self.margin_models = TestSmoothMarginEstimator.load_margin_models(spatial_coordinates=self.spatial_coordinates)
def test_full_estimators(self):
for margin_model, max_stable_model in product(self.margin_models, self.max_stable_models):
diff --git a/test/test_extreme_estimator/test_estimator/test_margin_estimators.py b/test/test_extreme_estimator/test_estimator/test_margin_estimators.py
index 480ebba2df2b33ad4a51c4d51fe9b073946b5d11..9dcea3dcaef2861970b3cf0e4244f8bc0f70b94c 100644
--- a/test/test_extreme_estimator/test_estimator/test_margin_estimators.py
+++ b/test/test_extreme_estimator/test_estimator/test_margin_estimators.py
@@ -1,15 +1,17 @@
import unittest
from extreme_estimator.extreme_models.margin_model.abstract_margin_model import AbstractMarginModel
-from extreme_estimator.extreme_models.margin_model.smooth_margin_model import ConstantMarginModel
+from extreme_estimator.extreme_models.margin_model.smooth_margin_model import ConstantMarginModel, \
+ LinearShapeAxis0MarginModel
from extreme_estimator.estimator.margin_estimator import SmoothMarginEstimator
+from extreme_estimator.return_level_plot.spatial_2D_plot import Spatial2DPlot
from spatio_temporal_dataset.dataset.simulation_dataset import MarginDataset
from spatio_temporal_dataset.spatial_coordinates.generated_coordinates import CircleCoordinatesRadius1
-class TestMarginEstimators(unittest.TestCase):
+class TestSmoothMarginEstimator(unittest.TestCase):
DISPLAY = False
- MARGIN_TYPES = [ConstantMarginModel]
+ MARGIN_TYPES = [ConstantMarginModel, LinearShapeAxis0MarginModel][1:]
MARGIN_ESTIMATORS = [SmoothMarginEstimator]
def setUp(self):
@@ -25,14 +27,17 @@ class TestMarginEstimators(unittest.TestCase):
for margin_model in self.margin_models:
dataset = MarginDataset.from_sampling(nb_obs=10, margin_model=margin_model,
spatial_coordinates=self.spatial_coordinates)
-
- for estimator_class in self.MARGIN_ESTIMATORS:
- estimator = estimator_class(dataset=dataset, margin_model=margin_model)
- estimator.fit()
- if self.DISPLAY:
- print(type(margin_model))
- print(dataset.df_dataset.head())
- print(estimator.additional_information)
+ # Fit estimator
+ estimator = SmoothMarginEstimator(dataset=dataset, margin_model=margin_model)
+ estimator.fit()
+ # Map name to their margin functions
+ name_to_margin_function = {
+ 'Ground truth margin function': dataset.margin_model.margin_function_sample,
+ # 'Estimated margin function': estimator.margin_function_fitted,
+ }
+ # Spatial Plot
+ if self.DISPLAY:
+ Spatial2DPlot(name_to_margin_function=name_to_margin_function).plot()
self.assertTrue(True)