From b2947f4665d4c5e498e96e58454b1c57f4e35d84 Mon Sep 17 00:00:00 2001
From: Le Roux Erwan <erwan.le-roux@irstea.fr>
Date: Tue, 31 Mar 2020 15:00:38 +0200
Subject: [PATCH] [contrasting project] add test for study loader. refactor
their init function to have a better error message.
---
.../scm_models_data/safran/safran.py | 73 ++++++++++---------
.../estimator/margin_estimator/utils.py | 4 +-
.../presentation/statistical_model.py | 7 +-
.../test_meteo_france_data/test_SCM_study.py | 14 +++-
4 files changed, 56 insertions(+), 42 deletions(-)
diff --git a/extreme_data/meteo_france_data/scm_models_data/safran/safran.py b/extreme_data/meteo_france_data/scm_models_data/safran/safran.py
index 1d1a9d46..8eecfc81 100644
--- a/extreme_data/meteo_france_data/scm_models_data/safran/safran.py
+++ b/extreme_data/meteo_france_data/scm_models_data/safran/safran.py
@@ -22,33 +22,32 @@ class Safran(AbstractStudy):
class SafranSnowfall(Safran, CumulatedStudy):
- def __init__(self, *args, **kwargs):
- CumulatedStudy.__init__(self, SafranSnowfallVariable, *args, **kwargs)
- Safran.__init__(self, SafranSnowfallVariable, *args, **kwargs)
+ def __init__(self, **kwargs):
+ super().__init__(SafranSnowfallVariable, **kwargs)
class SafranSnowfall1Day(SafranSnowfall):
- def __init__(self, *args, **kwargs):
- super().__init__(nb_consecutive_days=1, *args, **kwargs)
+ def __init__(self, **kwargs):
+ super().__init__(nb_consecutive_days=1, **kwargs)
class SafranSnowfall3Days(SafranSnowfall):
- def __init__(self, *args, **kwargs):
- super().__init__(nb_consecutive_days=3, *args, **kwargs)
+ def __init__(self, **kwargs):
+ super().__init__(nb_consecutive_days=3, **kwargs)
class SafranSnowfall5Days(SafranSnowfall):
- def __init__(self, *args, **kwargs):
- super().__init__(nb_consecutive_days=5, *args, **kwargs)
+ def __init__(self, **kwargs):
+ super().__init__(nb_consecutive_days=5, **kwargs)
class SafranSnowfall7Days(SafranSnowfall):
- def __init__(self, *args, **kwargs):
- super().__init__(nb_consecutive_days=7, *args, **kwargs)
+ def __init__(self, **kwargs):
+ super().__init__(nb_consecutive_days=7, **kwargs)
class ExtendedSafranSnowfall(AbstractExtendedStudy, SafranSnowfall):
@@ -57,38 +56,38 @@ class ExtendedSafranSnowfall(AbstractExtendedStudy, SafranSnowfall):
class SafranRainfall(CumulatedStudy, Safran):
- def __init__(self, *args, **kwargs):
- super().__init__(SafranRainfallVariable, *args, **kwargs)
+ def __init__(self, **kwargs):
+ super().__init__(SafranRainfallVariable, **kwargs)
class SafranRainfall1Day(SafranRainfall):
- def __init__(self, *args, **kwargs):
- super().__init__(nb_consecutive_days=1, *args, **kwargs)
+ def __init__(self, **kwargs):
+ super().__init__(nb_consecutive_days=1, **kwargs)
class SafranRainfall3Days(SafranRainfall):
- def __init__(self, *args, **kwargs):
- super().__init__(nb_consecutive_days=3, *args, **kwargs)
+ def __init__(self, **kwargs):
+ super().__init__(nb_consecutive_days=3, **kwargs)
class SafranRainfall5Days(SafranRainfall):
- def __init__(self, *args, **kwargs):
- super().__init__(nb_consecutive_days=5, *args, **kwargs)
+ def __init__(self, **kwargs):
+ super().__init__(nb_consecutive_days=5, **kwargs)
class SafranRainfall7Days(SafranRainfall):
- def __init__(self, *args, **kwargs):
- super().__init__(nb_consecutive_days=7, *args, **kwargs)
+ def __init__(self, **kwargs):
+ super().__init__(nb_consecutive_days=7, **kwargs)
class SafranPrecipitation(CumulatedStudy, Safran):
- def __init__(self, *args, **kwargs):
- super().__init__(SafranTotalPrecipVariable, *args, **kwargs)
+ def __init__(self, **kwargs):
+ super().__init__(SafranTotalPrecipVariable, **kwargs)
def load_variable_array(self, dataset):
return [np.array(dataset.variables[k]) for k in self.load_keyword()]
@@ -100,26 +99,26 @@ class SafranPrecipitation(CumulatedStudy, Safran):
class SafranPrecipitation1Day(SafranPrecipitation):
- def __init__(self, *args, **kwargs):
- super().__init__(nb_consecutive_days=1, *args, **kwargs)
+ def __init__(self, **kwargs):
+ super().__init__(nb_consecutive_days=1, **kwargs)
class SafranPrecipitation3Days(SafranPrecipitation):
- def __init__(self, *args, **kwargs):
- super().__init__(nb_consecutive_days=3, *args, **kwargs)
+ def __init__(self, **kwargs):
+ super().__init__(nb_consecutive_days=3, **kwargs)
class SafranPrecipitation5Days(SafranPrecipitation):
- def __init__(self, *args, **kwargs):
- super().__init__(nb_consecutive_days=5, *args, **kwargs)
+ def __init__(self, **kwargs):
+ super().__init__(nb_consecutive_days=5, **kwargs)
class SafranPrecipitation7Days(SafranPrecipitation):
- def __init__(self, *args, **kwargs):
- super().__init__(nb_consecutive_days=7, *args, **kwargs)
+ def __init__(self, **kwargs):
+ super().__init__(nb_consecutive_days=7, **kwargs)
class ExtendedSafranPrecipitation(AbstractExtendedStudy, SafranPrecipitation):
@@ -128,14 +127,20 @@ class ExtendedSafranPrecipitation(AbstractExtendedStudy, SafranPrecipitation):
class SafranTemperature(Safran):
- def __init__(self, *args, **kwargs):
- super().__init__(SafranTemperatureVariable, *args, **kwargs)
+ def __init__(self, **kwargs):
+ super().__init__(SafranTemperatureVariable, **kwargs)
def annual_aggregation_function(self, *args, **kwargs):
return np.mean(*args, **kwargs)
if __name__ == '__main__':
- study = SafranRainfall1Day()
+ altitude = 900
+ year_min = 1959
+ year_max = 2000
+ study = SafranRainfall1Day(altitude, year_min=year_min, year_max=year_max)
+ d = study.year_to_dataset_ordered_dict[1959]
+ print(d.keywords)
+ print(d.variables.keys())
print(study.year_to_annual_maxima[1959])
print(study.ordered_years)
diff --git a/extreme_fit/estimator/margin_estimator/utils.py b/extreme_fit/estimator/margin_estimator/utils.py
index 95dc74d0..df580526 100644
--- a/extreme_fit/estimator/margin_estimator/utils.py
+++ b/extreme_fit/estimator/margin_estimator/utils.py
@@ -2,6 +2,8 @@ import pandas as pd
from extreme_fit.distribution.gev.gev_params import GevParams
from extreme_fit.estimator.margin_estimator.abstract_margin_estimator import LinearMarginEstimator
+from extreme_fit.model.margin_model.linear_margin_model.abstract_temporal_linear_margin_model import \
+ TemporalMarginFitMethod
from extreme_fit.model.margin_model.linear_margin_model.temporal_linear_margin_models import StationaryTemporalModel
from spatio_temporal_dataset.coordinates.temporal_coordinates.generated_temporal_coordinates import \
ConsecutiveTemporalCoordinates
@@ -20,7 +22,7 @@ def fitted_linear_margin_estimator(model_class, coordinates, dataset, starting_y
return estimator
-def fitted_stationary_gev(x_gev, fit_method, model_class=StationaryTemporalModel, starting_year=None,
+def fitted_stationary_gev(x_gev, fit_method=TemporalMarginFitMethod.is_mev_gev_fit, model_class=StationaryTemporalModel, starting_year=None,
transformation_class=CenteredScaledNormalization) -> GevParams:
coordinates = ConsecutiveTemporalCoordinates.from_nb_temporal_steps(nb_temporal_steps=len(x_gev),
transformation_class=CenteredScaledNormalization)
diff --git a/projects/exceeding_snow_loads/presentation/statistical_model.py b/projects/exceeding_snow_loads/presentation/statistical_model.py
index 1a5e8dcd..72bdf968 100644
--- a/projects/exceeding_snow_loads/presentation/statistical_model.py
+++ b/projects/exceeding_snow_loads/presentation/statistical_model.py
@@ -25,6 +25,7 @@ def binomial_observation():
plt.yticks([0.0, 1.0], ['Heads', 'Tails'])
ax.plot(time, data, color=color, label=label, linewidth=4)
+
def histogram_for_gev():
import matplotlib.pyplot as plt
from extreme_data.meteo_france_data.scm_models_data.crocus.crocus import CrocusSnowLoadTotal
@@ -53,9 +54,6 @@ def histogram_for_gev():
ax.set_ylim([0, 0.3])
-
-
-
def histogram_for_normal():
ax = plt.gca()
linewidth = 5
@@ -71,9 +69,8 @@ def histogram_for_normal():
ax.set_ylim([0, 0.6])
-
if __name__ == '__main__':
# binomial_observation()
# histogram_for_gev()
histogram_for_normal()
- plt.show()
\ No newline at end of file
+ plt.show()
diff --git a/test/test_extreme_data/test_meteo_france_data/test_SCM_study.py b/test/test_extreme_data/test_meteo_france_data/test_SCM_study.py
index 9c829c99..56ab48da 100644
--- a/test/test_extreme_data/test_meteo_france_data/test_SCM_study.py
+++ b/test/test_extreme_data/test_meteo_france_data/test_SCM_study.py
@@ -4,9 +4,10 @@ from random import sample
import pandas as pd
+from extreme_data.meteo_france_data.scm_models_data.crocus.crocus import CrocusSnowLoad3Days
from extreme_data.meteo_france_data.scm_models_data.safran.cumulated_study import NB_DAYS
from extreme_data.meteo_france_data.scm_models_data.safran.safran import SafranSnowfall, SafranTemperature, \
- SafranPrecipitation
+ SafranPrecipitation, SafranSnowfall3Days, SafranRainfall3Days
from extreme_data.meteo_france_data.scm_models_data.utils import SeasonForTheMaxima
from extreme_data.meteo_france_data.scm_models_data.visualization.main_study_visualizer import \
study_iterator_global, SCM_STUDIES, ALL_ALTITUDES
@@ -33,9 +34,10 @@ class TestSCMAllStudy(unittest.TestCase):
self.assertEqual(len(days), len(daily_time_series))
def test_instantiate_studies(self):
+ study_classes = SCM_STUDIES
nb_sample = 2
for nb_days in sample(set(NB_DAYS), k=nb_sample):
- for study in study_iterator_global(study_classes=SCM_STUDIES,
+ for study in study_iterator_global(study_classes=study_classes,
only_first_one=False, verbose=False,
altitudes=sample(set(ALL_ALTITUDES), k=nb_sample), nb_days=nb_days):
first_path_file = study.ordered_years_and_path_files[0][0]
@@ -44,6 +46,14 @@ class TestSCMAllStudy(unittest.TestCase):
msg='{} days for type {}'.format(nb_days, get_display_name_from_object_type(
type(variable_object))))
+ def test_instantiate_studies_with_number_of_days(self):
+ altitude = 900
+ year_min = 1959
+ year_max = 2000
+ study_classes = [SafranSnowfall3Days, SafranRainfall3Days, CrocusSnowLoad3Days]
+ for study_class in study_classes:
+ study_class(altitude=altitude, year_min=year_min, year_max=year_max)
+
class TestSCMStudy(unittest.TestCase):
--
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