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 a88c4beb20ec5bd06ea82e5bd26f76a436308775..3ae470f8a597fc6868d57d890e027c61edd42d5e 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
@@ -9,13 +9,15 @@ from extreme_estimator.margin_fits.gev.gev_params import GevParams
from extreme_estimator.margin_fits.plot.create_shifted_cmap import plot_extreme_param, imshow_shifted
from spatio_temporal_dataset.coordinates.abstract_coordinates import AbstractCoordinates
from spatio_temporal_dataset.slicer.split import Split
+from utils import cached_property
class AbstractMarginFunction(object):
""" Class of function mapping points from a space S (could be 1D, 2D,...) to R^3 (the 3 parameters of the GEV)"""
- def __init__(self, coordinates: AbstractCoordinates):
+ def __init__(self, coordinates: AbstractCoordinates, resolution=100):
self.coordinates = coordinates
+ self.resolution = resolution
# Visualization parameters
self.visualization_axes = None
@@ -29,6 +31,14 @@ class AbstractMarginFunction(object):
self._grid_2D = None
self._grid_1D = None
+ @property
+ def x(self):
+ return self.coordinates.x_coordinates
+
+ @property
+ def y(self):
+ return self.coordinates.y_coordinates
+
def get_gev_params(self, coordinate: np.ndarray) -> GevParams:
"""Main method that maps each coordinate to its GEV parameters"""
pass
@@ -131,14 +141,11 @@ class AbstractMarginFunction(object):
# Visualization 2D
def visualize_2D(self, gev_param_name=GevParams.LOC, ax=None, show=True):
- x = self.coordinates.x_coordinates
- y = self.coordinates.y_coordinates
- grid = self.grid_2D(x, y)
if ax is None:
ax = plt.gca()
# Special display
- imshow_shifted(ax, gev_param_name, grid[gev_param_name], x, y)
+ imshow_shifted(ax, gev_param_name, self.grid_2D[gev_param_name], self.x, self.y)
# X axis
ax.set_xlabel('coordinate X')
@@ -152,13 +159,15 @@ class AbstractMarginFunction(object):
if show:
plt.show()
- def grid_2D(self, x, y):
- resolution = 100
+ @cached_property
+ def grid_2D(self):
+ x = self.x
+ y = self.y
grid = []
- for i, xi in enumerate(np.linspace(x.min(), x.max(), resolution)):
- for j, yj in enumerate(np.linspace(y.min(), y.max(), resolution)):
+ for i, xi in enumerate(np.linspace(x.min(), x.max(), self.resolution)):
+ for j, yj in enumerate(np.linspace(y.min(), y.max(), self.resolution)):
grid.append(self.get_gev_params(np.array([xi, yj])).summary_dict)
- grid = {value_name: np.array([g[value_name] for g in grid]).reshape([resolution, resolution])
+ grid = {value_name: np.array([g[value_name] for g in grid]).reshape([self.resolution, self.resolution])
for value_name in GevParams.SUMMARY_NAMES}
return grid
diff --git a/extreme_estimator/margin_fits/plot/create_shifted_cmap.py b/extreme_estimator/margin_fits/plot/create_shifted_cmap.py
index f176a58587b9fb78a56e4a66bb0e310fb5294449..128954fa47485c779a0a4c730fb28ddee43836ff 100644
--- a/extreme_estimator/margin_fits/plot/create_shifted_cmap.py
+++ b/extreme_estimator/margin_fits/plot/create_shifted_cmap.py
@@ -53,5 +53,6 @@ def imshow_shifted(ax, gev_param_name, values, x, y):
value = np.min(values)
# The right blue corner will be blue (but most of the time, another display will be on top)
masked_array[-1, -1] = value - epsilon
- ax.imshow(masked_array, extent=(x.min(), x.max(), y.min(), y.max()), cmap=shifted_cmap)
+ # IMPORTANT: Origin for all the plots is at the bottom left corner
+ ax.imshow(masked_array, extent=(x.min(), x.max(), y.min(), y.max()), cmap=shifted_cmap, origin='lower')
diff --git a/spatio_temporal_dataset/coordinates/spatial_coordinates/coordinates_2D.py b/spatio_temporal_dataset/coordinates/spatial_coordinates/coordinates_2D.py
new file mode 100644
index 0000000000000000000000000000000000000000..3c845c9e5e656ee56b4779be95a7172c154480c4
--- /dev/null
+++ b/spatio_temporal_dataset/coordinates/spatial_coordinates/coordinates_2D.py
@@ -0,0 +1,21 @@
+import numpy as np
+import pandas as pd
+from rpy2.robjects import r
+
+from spatio_temporal_dataset.coordinates.spatial_coordinates.abstract_spatial_coordinates import \
+ AbstractSpatialCoordinates
+from spatio_temporal_dataset.coordinates.spatial_coordinates.coordinates_1D import LinSpaceSpatialCoordinates
+
+
+class AbstractBiDimensionalSpatialCoordinates(AbstractSpatialCoordinates):
+ pass
+
+
+class LinSpaceSpatial2DCoordinates(AbstractBiDimensionalSpatialCoordinates):
+
+ @classmethod
+ def from_nb_points(cls, nb_points, train_split_ratio: float = None, start=-1.0, end=1.0):
+ axis_coordinates = np.linspace(start, end, nb_points)
+ df = pd.DataFrame.from_dict({cls.COORDINATE_X: axis_coordinates,
+ cls.COORDINATE_Y: axis_coordinates})
+ return cls.from_df(df, train_split_ratio)
diff --git a/spatio_temporal_dataset/coordinates/spatial_coordinates/generated_spatial_coordinates.py b/spatio_temporal_dataset/coordinates/spatial_coordinates/generated_spatial_coordinates.py
index f2716fbb8107a6ea48a2eca62625c79235238a7c..cb48486ab6d9d98b990e2460e19912abed9c5115 100644
--- a/spatio_temporal_dataset/coordinates/spatial_coordinates/generated_spatial_coordinates.py
+++ b/spatio_temporal_dataset/coordinates/spatial_coordinates/generated_spatial_coordinates.py
@@ -12,17 +12,17 @@ from spatio_temporal_dataset.coordinates.spatial_coordinates.abstract_spatial_co
class CircleSpatialCoordinates(AbstractSpatialCoordinates):
@classmethod
- def df_spatial(cls, nb_points, max_radius=1.0):
+ def df_spatial(cls, nb_points, max_radius=1.0, random=True):
# Sample uniformly inside the circle
- angles = np.array(r.runif(nb_points, max=2 * math.pi))
- radius = np.sqrt(np.array(r.runif(nb_points, max=max_radius)))
+ angles = np.array(r.runif(nb_points, max=2 * math.pi)) if random else np.linspace(0.0, 2 * math.pi, nb_points+1)[:-1]
+ radius = np.sqrt(np.array(r.runif(nb_points, max=max_radius))) if random else np.ones(nb_points) * max_radius
df = pd.DataFrame.from_dict({cls.COORDINATE_X: radius * np.cos(angles),
cls.COORDINATE_Y: radius * np.sin(angles)})
return df
@classmethod
- def from_nb_points(cls, nb_points, train_split_ratio: float = None, max_radius=1.0):
- return cls.from_df(cls.df_spatial(nb_points, max_radius), train_split_ratio)
+ def from_nb_points(cls, nb_points, train_split_ratio: float = None, max_radius=1.0, random=True):
+ return cls.from_df(cls.df_spatial(nb_points, max_radius, random), train_split_ratio)
def visualization_2D(self):
radius = 1.0
@@ -36,5 +36,5 @@ class CircleSpatialCoordinates(AbstractSpatialCoordinates):
class CircleSpatialCoordinatesRadius2(CircleSpatialCoordinates):
@classmethod
- def from_nb_points(cls, nb_points, train_split_ratio: float = None, max_radius=1.0):
- return 2 * super().from_nb_points(nb_points, train_split_ratio, max_radius)
+ def from_nb_points(cls, nb_points, train_split_ratio: float = None, max_radius=1.0, random=True):
+ return 2 * super().from_nb_points(nb_points, train_split_ratio, max_radius, random)
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 1be2e00e012a4c7dc3c6ccd854648c79eb3a3546..5f60a476fc9573134678682d3928774f1355cc39 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
@@ -1,16 +1,18 @@
+import numpy as np
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.coordinates_2D import LinSpaceSpatial2DCoordinates
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):
+class TestVisualizationMarginModel(unittest.TestCase):
DISPLAY = False
nb_points = 2
margin_model_class = [LinearShapeDim1MarginModel, LinearAllParametersAllDimsMarginModel][-1]
@@ -24,8 +26,13 @@ class VisualizationMarginModel(unittest.TestCase):
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)
+ spatial_coordinates = LinSpaceSpatial2DCoordinates.from_nb_points(nb_points=self.nb_points)
self.margin_model = self.margin_model_class(coordinates=spatial_coordinates)
+ # Assert that the grid correspond to what we expect in a simple case
+ self.margin_model.margin_function_sample.resolution = 2
+ grid = self.margin_model.margin_function_sample.grid_2D['loc']
+ true_grid = np.array([[0.98, 1.0], [1.0, 1.02]])
+ self.assertTrue((grid == true_grid).all(), msg="\nexpected:\n{}, \nfound:\n{}".format(true_grid, grid))
# def test_example_visualization_2D_spatio_temporal(self):
# self.nb_steps = 2
@@ -49,5 +56,6 @@ class VisualizationMarginModel(unittest.TestCase):
if __name__ == '__main__':
unittest.main()
- # v = VisualizationMarginModel()
- # v.test_example_visualization_2D_spatio_temporal()
+ # v = TestVisualizationMarginModel()
+ # v.test_example_visualization_2D_spatial()
+ # v.tearDown()