refactoring and renaming

extreme_estimator/R_model/gev/gev_mle_fit.py → extreme_estimator/gev/gev_mle_fit.py

@@ -4,8 +4,8 @@ import rpy2.robjects.numpy2ri as rpyn
 import os.path as op
 
 # Defining some constants
-from extreme_estimator.R_model.gev.gev_parameters import GevParams
-from extreme_estimator.R_model.utils import get_associated_r_file
+from extreme_estimator.gev_params import GevParams
+from extreme_estimator.extreme_models.utils import get_associated_r_file
 
 
 def gev_mle_fit(x_gev: np.ndarray, start_loc=0, start_scale=1, start_shape=0):

extreme_estimator/robustness_plot/msp_robustness.py

-from extreme_estimator.R_model.max_stable_model.abstract_max_stable_model import AbstractMaxStableModel, CovarianceFunction
-from extreme_estimator.R_model.max_stable_model.max_stable_models import Smith, BrownResnick, Schlather, ExtremalT
+from extreme_estimator.extreme_models.max_stable_model.abstract_max_stable_model import AbstractMaxStableModel, \
+    CovarianceFunction
+from extreme_estimator.extreme_models.max_stable_model.max_stable_models import Smith, BrownResnick, Schlather, \
+    ExtremalT
 from extreme_estimator.estimator.abstract_estimator import AbstractEstimator
 from extreme_estimator.estimator.max_stable_estimator import MaxStableEstimator
 from extreme_estimator.robustness_plot.multiple_plot import MultiplePlot
 from extreme_estimator.robustness_plot.single_plot import SinglePlot
-from spatio_temporal_dataset.dataset.simulation_dataset import SimulatedDataset
+from spatio_temporal_dataset.dataset.simulation_dataset import SimulatedDataset, MaxStableDataset
 from spatio_temporal_dataset.spatial_coordinates.abstract_spatial_coordinates import AbstractSpatialCoordinates
 from spatio_temporal_dataset.spatial_coordinates.alps_station_2D_coordinates import \
     AlpsStation2DCoordinatesBetweenZeroAndOne, AlpsStationCoordinatesBetweenZeroAndTwo
@@ -39,9 +41,9 @@ class MspSpatial(object):
         nb_station = self.NbStationItem.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)
-        dataset = SimulatedDataset.from_max_stable_sampling(nb_obs=nb_obs, max_stable_model=max_stable_model,
-                                                            spatial_coordinates=spatial_coordinate)
+        spatial_coordinates = spatial_coordinate_class.from_nb_points(nb_points=nb_station)
+        dataset = MaxStableDataset.from_sampling(nb_obs=nb_obs, max_stable_model=max_stable_model,
+                                                 spatial_coordinates=spatial_coordinates)
         estimator = MaxStableEstimator(dataset, max_stable_model)
         estimator.fit()
         return estimator.scalars(max_stable_model.params_sample)
@@ -88,7 +90,7 @@ def multiple_spatial_robustness_alps():
         nb_samples=nb_sample,
         main_title="Max stable analysis with {} years of observations".format(nb_observation),
         plot_png_filename=plot_name
-        )
+    )
     # Load all the models
     msp_models = [Smith(), BrownResnick()]
     # for covariance_function in CovarianceFunction:

spatio_temporal_dataset/dataset/simulation_dataset.py

-from extreme_estimator.R_model.margin_model.abstract_margin_model import AbstractMarginModel
-from extreme_estimator.R_model.max_stable_model.abstract_max_stable_model import AbstractMaxStableModel
+from extreme_estimator.extreme_models.margin_model.abstract_margin_model import AbstractMarginModel
+from extreme_estimator.extreme_models.max_stable_model.abstract_max_stable_model import AbstractMaxStableModel
 from spatio_temporal_dataset.dataset.abstract_dataset import AbstractDataset
 from spatio_temporal_dataset.spatial_coordinates.abstract_spatial_coordinates import AbstractSpatialCoordinates
 from spatio_temporal_dataset.temporal_observations.abstract_temporal_observations import AbstractTemporalObservations

spatio_temporal_dataset/spatial_coordinates/generated_coordinates.py

@@ -2,7 +2,7 @@ import math
 import numpy as np
 import pandas as pd
 
-from extreme_estimator.R_model.utils import get_loaded_r
+from extreme_estimator.extreme_models.utils import get_loaded_r
 from spatio_temporal_dataset.spatial_coordinates.abstract_spatial_coordinates import AbstractSpatialCoordinates
 import matplotlib.pyplot as plt
 

spatio_temporal_dataset/temporal_observations/annual_maxima_observations.py

 import pandas as pd
 
-from extreme_estimator.R_model.margin_model.abstract_margin_model import AbstractMarginModel
-from extreme_estimator.R_model.max_stable_model.abstract_max_stable_model import AbstractMaxStableModel
+from extreme_estimator.extreme_models.margin_model.abstract_margin_model import AbstractMarginModel
+from extreme_estimator.extreme_models.max_stable_model.abstract_max_stable_model import AbstractMaxStableModel
 from spatio_temporal_dataset.spatial_coordinates.abstract_spatial_coordinates import AbstractSpatialCoordinates
 from spatio_temporal_dataset.temporal_observations.abstract_temporal_observations import AbstractTemporalObservations
 

test/test_extreme_estimator/test_R_model/test_gev_mle_fit.py

@@ -2,8 +2,8 @@ import unittest
 
 import numpy as np
 
-from extreme_estimator.R_model.gev.gev_mle_fit import GevMleFit
-from extreme_estimator.R_model.utils import get_loaded_r
+from extreme_estimator.gev.gev_mle_fit import GevMleFit
+from extreme_estimator.extreme_models.utils import get_loaded_r
 
 
 class TestGevMleFit(unittest.TestCase):

test/test_extreme_estimator/test_R_model/test_margin_function.py

 import unittest
 
-from extreme_estimator.R_model.gev.gev_parameters import GevParams
-from extreme_estimator.R_model.margin_function.independent_margin_function import LinearMarginFunction
-from extreme_estimator.R_model.margin_model.smooth_margin_model import ConstantMarginModel, LinearShapeAxis0MarginModel
+from extreme_estimator.gev_params import GevParams
+from extreme_estimator.extreme_models.margin_model.smooth_margin_model import LinearShapeAxis0MarginModel
 from spatio_temporal_dataset.spatial_coordinates.generated_coordinates import CircleCoordinatesRadius1
 
 
 class TestLinearMarginModel(unittest.TestCase):
-    DISPLAY = True
+    DISPLAY = False
 
     def test_visualization_2D(self):
         spatial_coordinates = CircleCoordinatesRadius1.from_nb_points(nb_points=50)

test/test_extreme_estimator/test_estimator/test_margin_estimators.py

 import unittest
 
-from extreme_estimator.R_model.margin_model.abstract_margin_model import AbstractMarginModel
-from extreme_estimator.R_model.margin_model.smooth_margin_model import ConstantMarginModel
+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.estimator.margin_estimator import SmoothMarginEstimator
 from spatio_temporal_dataset.dataset.simulation_dataset import MarginDataset
 from spatio_temporal_dataset.spatial_coordinates.generated_coordinates import CircleCoordinatesRadius1

test/test_extreme_estimator/test_estimator/test_max_stable_estimators.py

 import unittest
 
-from extreme_estimator.R_model.max_stable_model.abstract_max_stable_model import \
+from extreme_estimator.extreme_models.max_stable_model.abstract_max_stable_model import \
     AbstractMaxStableModelWithCovarianceFunction, CovarianceFunction
-from extreme_estimator.R_model.max_stable_model.max_stable_models import Smith, BrownResnick, Schlather, \
+from extreme_estimator.extreme_models.max_stable_model.max_stable_models import Smith, BrownResnick, Schlather, \
     Geometric, ExtremalT, ISchlather
 from extreme_estimator.estimator.max_stable_estimator import MaxStableEstimator
 from spatio_temporal_dataset.dataset.simulation_dataset import MaxStableDataset