From 661bfe2903dcb24ad6485213bdf09c66cf67ab15 Mon Sep 17 00:00:00 2001
From: Le Roux Erwan <erwan.le-roux@irstea.fr>
Date: Wed, 22 May 2019 16:45:13 +0200
Subject: [PATCH] [SCM][HYPERCUBE] normalize gev trend_strength with distance
between years. update test to check this distance.
---
.../main_hypercube_visualization.py | 4 ++--
.../univariate_trend_test/abstract_gev_trend_test.py | 11 +++++++++--
.../coordinates/abstract_coordinates.py | 4 ++--
.../abstract_temporal_coordinates.py | 6 +++++-
.../test_transformation.py | 9 +++++----
5 files changed, 23 insertions(+), 11 deletions(-)
diff --git a/experiment/meteo_france_SCM_study/visualization/hypercube_visualization/main_hypercube_visualization.py b/experiment/meteo_france_SCM_study/visualization/hypercube_visualization/main_hypercube_visualization.py
index 534541c8..dce9a699 100644
--- a/experiment/meteo_france_SCM_study/visualization/hypercube_visualization/main_hypercube_visualization.py
+++ b/experiment/meteo_france_SCM_study/visualization/hypercube_visualization/main_hypercube_visualization.py
@@ -93,9 +93,9 @@ def fast_trends_with_quantity_altitude_hypercube():
def main_run():
- # fast_trends_with_altitude_hypercube()
+ fast_trends_with_altitude_hypercube()
# fast_trends_with_quantity_altitude_hypercube()
- full_trends_with_quantity_altitude_hypercube()
+ # full_trends_with_quantity_altitude_hypercube()
if __name__ == '__main__':
diff --git a/experiment/trend_analysis/univariate_trend_test/abstract_gev_trend_test.py b/experiment/trend_analysis/univariate_trend_test/abstract_gev_trend_test.py
index c9811d9e..1b734763 100644
--- a/experiment/trend_analysis/univariate_trend_test/abstract_gev_trend_test.py
+++ b/experiment/trend_analysis/univariate_trend_test/abstract_gev_trend_test.py
@@ -28,7 +28,7 @@ class AbstractGevTrendTest(AbstractTrendTest):
df = pd.DataFrame({AbstractCoordinates.COORDINATE_T: years_after_change_point})
df_maxima_gev = pd.DataFrame(maxima_after_change_point, index=df.index)
observations = AbstractSpatioTemporalObservations(df_maxima_gev=df_maxima_gev)
- self.coordinates = AbstractTemporalCoordinates.from_df(df, transformation_class=CenteredScaledNormalization)
+ self.coordinates = AbstractTemporalCoordinates.from_df(df, transformation_class=CenteredScaledNormalization) # type: AbstractTemporalCoordinates
self.dataset = AbstractDataset(observations=observations, coordinates=self.coordinates)
try:
@@ -81,7 +81,14 @@ class AbstractGevTrendTest(AbstractTrendTest):
@property
def test_trend_strength(self):
- return 100 * np.abs(self.non_stationary_linear_coef) / np.abs(self.non_stationary_intercept_coef)
+ return self.percentage_of_change_per_year
+
+ @property
+ def percentage_of_change_per_year(self):
+ ratio = np.abs(self.non_stationary_linear_coef) / np.abs(self.non_stationary_intercept_coef)
+ scaled_ratio = ratio * self.coordinates.transformed_distance_between_two_successive_years
+ percentage_of_change_per_year = 100 * scaled_ratio
+ return percentage_of_change_per_year
@property
def test_sign(self) -> int:
diff --git a/spatio_temporal_dataset/coordinates/abstract_coordinates.py b/spatio_temporal_dataset/coordinates/abstract_coordinates.py
index 523d5131..9a8f63de 100644
--- a/spatio_temporal_dataset/coordinates/abstract_coordinates.py
+++ b/spatio_temporal_dataset/coordinates/abstract_coordinates.py
@@ -133,8 +133,8 @@ class AbstractCoordinates(object):
# Normalize
def transform(self, coordinate: np.ndarray) -> np.ndarray:
- coordinate_float = coordinate.astype(self.COORDINATE_TYPE)
- return self.transformation.transform_array(coordinate=coordinate_float)
+ coordinate_array_as_float = coordinate.astype(self.COORDINATE_TYPE)
+ return self.transformation.transform_array(coordinate=coordinate_array_as_float)
# Split
diff --git a/spatio_temporal_dataset/coordinates/temporal_coordinates/abstract_temporal_coordinates.py b/spatio_temporal_dataset/coordinates/temporal_coordinates/abstract_temporal_coordinates.py
index 8084820e..8edda847 100644
--- a/spatio_temporal_dataset/coordinates/temporal_coordinates/abstract_temporal_coordinates.py
+++ b/spatio_temporal_dataset/coordinates/temporal_coordinates/abstract_temporal_coordinates.py
@@ -1,5 +1,5 @@
import pandas as pd
-
+import numpy as np
from spatio_temporal_dataset.coordinates.abstract_coordinates import AbstractCoordinates
from spatio_temporal_dataset.slicer.temporal_slicer import TemporalSlicer
@@ -10,6 +10,10 @@ class AbstractTemporalCoordinates(AbstractCoordinates):
def temporal_coordinates(self):
return self
+ @property
+ def transformed_distance_between_two_successive_years(self):
+ return self.transform(np.ones([1])) - self.transform(np.zeros([1]))
+
@classmethod
def from_df(cls, df: pd.DataFrame, train_split_ratio: float = None, transformation_class: type = None):
assert cls.COORDINATE_T in df.columns
diff --git a/test/test_spatio_temporal_dataset/test_transformation.py b/test/test_spatio_temporal_dataset/test_transformation.py
index bbce7051..e03b0eb5 100644
--- a/test/test_spatio_temporal_dataset/test_transformation.py
+++ b/test/test_spatio_temporal_dataset/test_transformation.py
@@ -18,14 +18,15 @@ class TestTransformation(unittest.TestCase):
nb_steps = 3
start = 1950
transformation_class_to_expected = {
- BetweenZeroAndOneNormalization: [0.0, 0.5, 1.0],
- BetweenMinusOneAndOneNormalization: [-1.0, 0.0, 1.0],
- CenteredScaledNormalization: [-1.22474487, 0., 1.22474487],
+ BetweenZeroAndOneNormalization: (0.5, [0.0, 0.5, 1.0]),
+ BetweenMinusOneAndOneNormalization: (1.0, [-1.0, 0.0, 1.0]),
+ CenteredScaledNormalization: (1.22474487, [-1.22474487, 0., 1.22474487]),
}
- for transformation_class, expected in transformation_class_to_expected.items():
+ for transformation_class, (expected_distance, expected) in transformation_class_to_expected.items():
temporal_coordinates = ConsecutiveTemporalCoordinates.from_nb_temporal_steps(nb_temporal_steps=nb_steps,
start=start,
transformation_class=transformation_class)
+ self.assertTrue(np.allclose(temporal_coordinates.transformed_distance_between_two_successive_years, expected_distance))
normalized_coordinates = temporal_coordinates.df_coordinates().iloc[:, 0].values
expected_coordinates = np.array(expected)
equal = np.allclose(normalized_coordinates , expected_coordinates)
--
GitLab