diff --git a/extreme_estimator/estimator/abstract_estimator.py b/extreme_estimator/estimator/abstract_estimator.py
index 40ca905b2e3ab6dc131a99edde8bf636e396a56c..6aa9063d736057ce77030946bd46fa5055f10eea 100644
--- a/extreme_estimator/estimator/abstract_estimator.py
+++ b/extreme_estimator/estimator/abstract_estimator.py
@@ -1,12 +1,21 @@
+import time
class AbstractEstimator(object):
def __init__(self):
- pass
+ self.fit_duration = None
+
+ def timed_fit(self):
+ ts = time.time()
+ result = self.fit()
+ te = time.time()
+ log_time = int((te - ts) * 1000)
+ self.fit_duration = log_time
+ return result
def fit(self):
pass
- def error(self):
+ def error(self, true_max_stable_params: dict):
pass
\ No newline at end of file
diff --git a/extreme_estimator/estimator/msp_estimator.py b/extreme_estimator/estimator/msp_estimator.py
index bb467d09985dc2d850480cc0e9990dcef47d7686..9b141d70292fa0fa38c44b18ec481bd42f30c01f 100644
--- a/extreme_estimator/estimator/msp_estimator.py
+++ b/extreme_estimator/estimator/msp_estimator.py
@@ -5,18 +5,20 @@ import numpy as np
class MaxStableEstimator(AbstractEstimator):
+ MAE_ERROR = 'mae'
def __init__(self, dataset: AbstractDataset, max_stable_model: AbstractMaxStableModel):
self.dataset = dataset
self.max_stable_model = max_stable_model
+ # Fit parameters
self.max_stable_params_fitted = None
def fit(self):
- self.max_stable_params_fitted = self.max_stable_model.fitmaxstab(maxima=self.dataset.maxima, coord=self.dataset.coord)
+ self.max_stable_params_fitted = self.max_stable_model.fitmaxstab(maxima=self.dataset.maxima,
+ coord=self.dataset.coord)
def error(self, true_max_stable_params: dict):
absolute_errors = {param_name: np.abs(param_true_value - self.max_stable_params_fitted[param_name])
for param_name, param_true_value in true_max_stable_params.items()}
mean_absolute_error = np.mean(np.array(list(absolute_errors.values())))
- # return {**absolute_errors, **{'mae': mean_absolute_error}}
- return mean_absolute_error
+ return {**absolute_errors, **{self.MAE_ERROR: mean_absolute_error}}
diff --git a/extreme_estimator/robustness_plot/abstract_robustness.py b/extreme_estimator/robustness_plot/abstract_robustness.py
deleted file mode 100644
index 4925440748052f919a3268c57ecbc822bd3f090b..0000000000000000000000000000000000000000
--- a/extreme_estimator/robustness_plot/abstract_robustness.py
+++ /dev/null
@@ -1,97 +0,0 @@
-from typing import List
-
-from extreme_estimator.estimator.msp_estimator import MaxStableEstimator
-from extreme_estimator.R_fit.max_stable_fit.abstract_max_stable_model import GaussianMSP, AbstractMaxStableModel
-from itertools import product
-
-from spatio_temporal_dataset.dataset.simulation_dataset import SimulatedDataset
-from spatio_temporal_dataset.spatial_coordinates.generated_coordinates import CircleCoordinates
-import matplotlib.pyplot as plt
-
-plt.style.use('seaborn-white')
-
-
-class DisplayItem(object):
-
- def __init__(self, argument_name, default_value, dislay_name=None):
- self.argument_name = argument_name
- self.default_value = default_value
- self.dislay_name = dislay_name if dislay_name is not None else self.argument_name
-
- def values_from_kwargs(self, **kwargs):
- return kwargs.get(self.argument_name, [self.default_value])
-
- def value_from_kwargs(self, **kwargs):
- return kwargs.get(self.argument_name, self.default_value)
-
-
-MaxStableModelItem = DisplayItem('max_stable_model', GaussianMSP)
-SpatialCoordinateClassItem = DisplayItem('spatial_coordinate_class', CircleCoordinates)
-SpatialParamsItem = DisplayItem('spatial_params', {"r": 1})
-NbStationItem = DisplayItem('nb_station', None)
-NbObservationItem = DisplayItem('nb_obs', 50)
-
-
-class AbstractRobustnessPlot(object):
-
- def __init__(self, grid_row_item, grid_column_item, plot_row_item, plot_label_item):
- self.grid_row_item = grid_row_item # type: DisplayItem
- self.grid_column_item = grid_column_item # type: DisplayItem
- self.plot_row_item = plot_row_item # type: DisplayItem
- self.plot_label_item = plot_label_item # type: DisplayItem
-
- self.estimation_error = self.estimation_error_max_stable_unitary_frechet
-
- def robustness_grid_plot(self, **kwargs):
- grid_row_values = self.grid_row_item.values_from_kwargs(**kwargs)
- grid_column_values = self.grid_column_item.values_from_kwargs(**kwargs)
- nb_grid_rows, nb_grid_columns = len(grid_row_values), len(grid_column_values)
- fig = plt.figure()
- fig.subplots_adjust(hspace=0.4, wspace=0.4)
- for i, (grid_row_value, grid_column_value) in enumerate(product(grid_row_values, grid_column_values), 1):
- print('Grid plot: {}={} {}={}'.format(self.grid_row_item.dislay_name, grid_row_value,
- self.grid_column_item.dislay_name, grid_column_value))
- ax = fig.add_subplot(nb_grid_rows, nb_grid_columns, i)
- kwargs_single_plot = kwargs.copy()
- kwargs_single_plot.update({self.grid_row_item.argument_name: grid_row_value,
- self.grid_column_item.argument_name: grid_column_value})
- self.robustness_single_plot(ax, **kwargs_single_plot)
- plt.show()
-
- def robustness_single_plot(self, ax, **kwargs_single_plot):
- plot_row_values = self.plot_row_item.values_from_kwargs(**kwargs_single_plot)
- plot_label_values = self.plot_label_item.values_from_kwargs(**kwargs_single_plot)
- colors = ['blue', 'red', 'green', 'black']
- assert isinstance(plot_label_values, list), plot_label_values
- assert isinstance(plot_row_values, list), plot_row_values
- for j, plot_label_value in enumerate(plot_label_values):
- plot_row_value_to_error = {}
- # todo: do some parallzlization here
- for plot_row_value in plot_row_values:
- kwargs_single_point = kwargs_single_plot.copy()
- kwargs_single_point.update({self.plot_row_item.argument_name: plot_row_value,
- self.plot_label_item.argument_name: plot_label_value})
- plot_row_value_to_error[plot_row_value] = self.estimation_error(**kwargs_single_point)
- plot_column_values = [plot_row_value_to_error[plot_row_value] for plot_row_value in plot_row_values]
- ax.plot(plot_row_values, plot_column_values, color=colors[j % len(colors)], label=str(j))
- ax.legend()
- ax.set_xlabel(self.plot_row_item.dislay_name)
- ax.set_ylabel('Absolute error')
- ax.set_title('Title (display all the other parameters)')
-
- @staticmethod
- def estimation_error_max_stable_unitary_frechet(**kwargs_single_points):
- # Get the argument from kwargs
- max_stable_model = MaxStableModelItem.value_from_kwargs(**kwargs_single_points)
- spatial_coordinate_class = SpatialCoordinateClassItem.value_from_kwargs(**kwargs_single_points)
- nb_station = NbStationItem.value_from_kwargs(**kwargs_single_points)
- spatial_params = SpatialParamsItem.value_from_kwargs(**kwargs_single_points)
- nb_obs = NbObservationItem.value_from_kwargs(**kwargs_single_points)
- # Run the estimation
- spatial_coordinate = spatial_coordinate_class.from_nb_points(nb_points=nb_station, **spatial_params)
- dataset = SimulatedDataset.from_max_stable_sampling(nb_obs=nb_obs, max_stable_model=max_stable_model,
- spatial_coordinates=spatial_coordinate)
- estimator = MaxStableEstimator(dataset, max_stable_model)
- estimator.fit()
- errors = estimator.error(max_stable_model.params_sample)
- return errors
diff --git a/extreme_estimator/robustness_plot/abstract_robustness_plot.py b/extreme_estimator/robustness_plot/abstract_robustness_plot.py
new file mode 100644
index 0000000000000000000000000000000000000000..c9b4837fb1bcfa40cd4566f9aeefaedfc1f50779
--- /dev/null
+++ b/extreme_estimator/robustness_plot/abstract_robustness_plot.py
@@ -0,0 +1,35 @@
+import matplotlib.pyplot as plt
+
+plt.style.use('seaborn-white')
+
+
+class DisplayItem(object):
+
+ def __init__(self, argument_name, default_value, dislay_name=None):
+ self.argument_name = argument_name
+ self.default_value = default_value
+ self.dislay_name = dislay_name if dislay_name is not None else self.argument_name
+
+ def values_from_kwargs(self, **kwargs):
+ values = kwargs.get(self.argument_name, [self.default_value])
+ assert isinstance(values, list)
+ return values
+
+ def value_from_kwargs(self, **kwargs):
+ return kwargs.get(self.argument_name, self.default_value)
+
+ def update_kwargs_value(self, value, **kwargs):
+ updated_kwargs = kwargs.copy()
+ updated_kwargs.update({self.argument_name: value})
+ return updated_kwargs
+
+
+
+class AbstractPlot(object):
+ COLORS = ['blue', 'red', 'green', 'black', 'magenta', 'cyan']
+
+ def __init__(self, grid_row_item, grid_column_item, plot_row_item, plot_label_item):
+ self.grid_row_item = grid_row_item # type: DisplayItem
+ self.grid_column_item = grid_column_item # type: DisplayItem
+ self.plot_row_item = plot_row_item # type: DisplayItem
+ self.plot_label_item = plot_label_item # type: DisplayItem
diff --git a/extreme_estimator/robustness_plot/max_stable_robustness/single_spatial_robustness.py b/extreme_estimator/robustness_plot/max_stable_robustness/single_spatial_robustness.py
new file mode 100644
index 0000000000000000000000000000000000000000..4a406c1bd852e65aa9b1ca465d01d870c383a41f
--- /dev/null
+++ b/extreme_estimator/robustness_plot/max_stable_robustness/single_spatial_robustness.py
@@ -0,0 +1,52 @@
+from extreme_estimator.R_fit.max_stable_fit.abstract_max_stable_model import AbstractMaxStableModel
+from extreme_estimator.R_fit.max_stable_fit.max_stable_models import Smith, BrownResnick
+from extreme_estimator.estimator.msp_estimator import MaxStableEstimator
+from extreme_estimator.robustness_plot.abstract_robustness_plot import DisplayItem
+from extreme_estimator.robustness_plot.single_scalar_plot import SingleScalarPlot
+from spatio_temporal_dataset.dataset.simulation_dataset import SimulatedDataset
+from spatio_temporal_dataset.spatial_coordinates.alps_station_coordinates import AlpsStationCoordinates, \
+ AlpsStationCoordinatesBetweenZeroAndOne
+from spatio_temporal_dataset.spatial_coordinates.generated_coordinates import CircleCoordinates
+
+
+class MspSpatial(SingleScalarPlot):
+ MaxStableModelItem = DisplayItem('max_stable_model', Smith)
+ SpatialCoordinateClassItem = DisplayItem('spatial_coordinate_class', CircleCoordinates)
+ SpatialParamsItem = DisplayItem('spatial_params', {"r": 1})
+ NbStationItem = DisplayItem('nb_station', 50)
+ NbObservationItem = DisplayItem('nb_obs', 60)
+
+ def single_scalar_from_all_params(self, **kwargs_single_point) -> float:
+ # Get the argument from kwargs
+ max_stable_model = self.MaxStableModelItem.value_from_kwargs(**kwargs_single_point) # type: AbstractMaxStableModel
+ spatial_coordinate_class = self.SpatialCoordinateClassItem.value_from_kwargs(**kwargs_single_point)
+ nb_station = self.NbStationItem.value_from_kwargs(**kwargs_single_point)
+ spatial_params = self.SpatialParamsItem.value_from_kwargs(**kwargs_single_point)
+ nb_obs = self.NbObservationItem.value_from_kwargs(**kwargs_single_point)
+ # Run the estimation
+ spatial_coordinate = spatial_coordinate_class.from_nb_points(nb_points=nb_station, **spatial_params)
+ dataset = SimulatedDataset.from_max_stable_sampling(nb_obs=nb_obs, max_stable_model=max_stable_model,
+ spatial_coordinates=spatial_coordinate)
+ estimator = MaxStableEstimator(dataset, max_stable_model)
+ estimator.timed_fit()
+ errors = estimator.error(max_stable_model.params_sample)
+ mae_error = errors[MaxStableEstimator.MAE_ERROR]
+ return mae_error
+
+
+def spatial_robustness_alps():
+ spatial_robustness = MspSpatial(grid_row_item=MspSpatial.NbObservationItem,
+ grid_column_item=MspSpatial.SpatialCoordinateClassItem,
+ plot_row_item=MspSpatial.NbStationItem,
+ plot_label_item=MspSpatial.MaxStableModelItem)
+ # Put only the parameter that will vary
+ spatial_robustness.robustness_grid_plot(**{
+ MspSpatial.NbStationItem.argument_name: [10, 30, 50, 70, 86][:],
+ MspSpatial.NbObservationItem.argument_name: [10],
+ MspSpatial.MaxStableModelItem.argument_name: [Smith(), BrownResnick()][:],
+ MspSpatial.SpatialCoordinateClassItem.argument_name: [CircleCoordinates, AlpsStationCoordinatesBetweenZeroAndOne][:],
+ })
+
+
+if __name__ == '__main__':
+ spatial_robustness_alps()
diff --git a/extreme_estimator/robustness_plot/multiple_scalar_plot.py b/extreme_estimator/robustness_plot/multiple_scalar_plot.py
new file mode 100644
index 0000000000000000000000000000000000000000..e13f64db396f13cd2902d444c89b17259dc89293
--- /dev/null
+++ b/extreme_estimator/robustness_plot/multiple_scalar_plot.py
@@ -0,0 +1,14 @@
+from extreme_estimator.robustness_plot.abstract_robustness_plot import AbstractPlot
+
+
+class MultipleScalarPlot(AbstractPlot):
+ """
+ In a Multiple Scalar plot, for each
+
+ Each scalar, will be display on a grid row (to ease visual comparison)
+ """
+
+ def __init__(self, grid_column_item, plot_row_item, plot_label_item):
+ super().__init__(grid_row_item=None, grid_column_item=grid_column_item,
+ plot_row_item=plot_row_item, plot_label_item=plot_label_item)
+
diff --git a/extreme_estimator/robustness_plot/single_scalar_plot.py b/extreme_estimator/robustness_plot/single_scalar_plot.py
new file mode 100644
index 0000000000000000000000000000000000000000..30eb8aed8751a8939757fd4630f7438128253335
--- /dev/null
+++ b/extreme_estimator/robustness_plot/single_scalar_plot.py
@@ -0,0 +1,52 @@
+from extreme_estimator.robustness_plot.abstract_robustness_plot import AbstractPlot
+import matplotlib.pyplot as plt
+from itertools import product
+
+
+class SingleScalarPlot(AbstractPlot):
+ """
+ For a single scalar plot, for the combination of all the parameters of interest,
+ then the function
+ """
+
+ def single_scalar_from_all_params(self, **kwargs_single_point) -> float:
+ pass
+
+ def robustness_grid_plot(self, **kwargs):
+ # Extract Grid row and columns values
+ grid_row_values = self.grid_row_item.values_from_kwargs(**kwargs)
+ grid_column_values = self.grid_column_item.values_from_kwargs(**kwargs)
+ nb_grid_rows, nb_grid_columns = len(grid_row_values), len(grid_column_values)
+ # Start the overall plot
+ fig = plt.figure()
+ fig.subplots_adjust(hspace=0.4, wspace=0.4)
+ for i, (grid_row_value, grid_column_value) in enumerate(product(grid_row_values, grid_column_values), 1):
+ print('Grid plot: {}={} {}={}'.format(self.grid_row_item.dislay_name, grid_row_value,
+ self.grid_column_item.dislay_name, grid_column_value))
+ ax = fig.add_subplot(nb_grid_rows, nb_grid_columns, i)
+ # Adapt the kwargs for the single plot
+ kwargs_single_plot = kwargs.copy()
+ kwargs_single_plot.update({self.grid_row_item.argument_name: grid_row_value,
+ self.grid_column_item.argument_name: grid_column_value})
+ self.robustness_single_plot(ax, **kwargs_single_plot)
+ plt.show()
+
+ def robustness_single_plot(self, ax, **kwargs_single_plot):
+ plot_row_values = self.plot_row_item.values_from_kwargs(**kwargs_single_plot)
+ plot_label_values = self.plot_label_item.values_from_kwargs(**kwargs_single_plot)
+ for j, plot_label_value in enumerate(plot_label_values):
+ # Compute
+ plot_row_value_to_error = {}
+ # todo: do some parallzlization here (do the parallelization in the Asbtract class if possible)
+ for plot_row_value in plot_row_values:
+ # Adapt the kwargs for the single value
+ kwargs_single_point = kwargs_single_plot.copy()
+ kwargs_single_point.update({self.plot_row_item.argument_name: plot_row_value,
+ self.plot_label_item.argument_name: plot_label_value})
+ plot_row_value_to_error[plot_row_value] = self.single_scalar_from_all_params(**kwargs_single_point)
+ plot_column_values = [plot_row_value_to_error[plot_row_value] for plot_row_value in plot_row_values]
+ ax.plot(plot_row_values, plot_column_values, color=self.COLORS[j % len(self.COLORS)], label=str(j))
+ ax.legend()
+ ax.set_xlabel(self.plot_row_item.dislay_name)
+ ax.set_ylabel('Absolute error')
+ ax.set_title('Title (display all the other parameters)')
diff --git a/extreme_estimator/robustness_plot/spatial_robustness.py b/extreme_estimator/robustness_plot/spatial_robustness.py
deleted file mode 100644
index 937a66b7c51d500a495c0614ea9c09519a60b516..0000000000000000000000000000000000000000
--- a/extreme_estimator/robustness_plot/spatial_robustness.py
+++ /dev/null
@@ -1,15 +0,0 @@
-from extreme_estimator.robustness_plot.abstract_robustness import DisplayItem, AbstractRobustnessPlot, \
- SpatialCoordinateClassItem, NbObservationItem, NbStationItem, MaxStableModelItem, SpatialParamsItem
-from spatio_temporal_dataset.spatial_coordinates.generated_coordinates import CircleCoordinates
-
-spatial_robustness = AbstractRobustnessPlot(grid_row_item=SpatialCoordinateClassItem,
- grid_column_item=NbObservationItem,
- plot_row_item=NbStationItem,
- plot_label_item=MaxStableModelItem)
-
-# Put only the parameter that will vary
-spatial_robustness.robustness_grid_plot(**{
- NbStationItem.argument_name: [10, 30, 50, 100],
- MaxStableModelItem.argument_name: [GaussianMSP(), BrownResick()][:],
- NbObservationItem.argument_name: [10, 50, 100]
-})