[DATA EXTRACTION] add all_days & all_daily_series property, that was useful to...

[DATA EXTRACTION] add all_days & all_daily_series property, that was useful to extract some data of snow depth for taline

experiment/meteo_france_data/scm_models_data/abstract_study.py

+import datetime
 import io
 import os
 import os.path as op
 from collections import OrderedDict
 from contextlib import redirect_stdout
+from itertools import chain
 from multiprocessing.pool import Pool
 from typing import List, Dict, Tuple, Union
 
@@ -41,8 +43,11 @@ class AbstractStudy(object):
         - a start and a end year
 
     Les fichiers netcdf de SAFRAN et CROCUS sont autodocumentés (on peut les comprendre avec ncdump -h notamment).
+
+    The year 2017 represents the nc file that correspond to the winter between the year 2017 and 2018.
     """
     REANALYSIS_FOLDER = 'SAFRAN_montagne-CROCUS_2019/alp_flat/reanalysis'
+    # REANALYSIS_FOLDER = 'SAFRAN_montagne-CROCUS_2019/alp_allslopes/reanalysis'
     # REANALYSIS_FOLDER = 'SAFRAN_montagne-CROCUS_2019/postes/reanalysis'
 
     def __init__(self, variable_class: type, altitude: int = 1800, year_min=1000, year_max=3000,
@@ -56,6 +61,33 @@ class AbstractStudy(object):
         self.year_max = year_max
         self.multiprocessing = multiprocessing
 
+    """ Time """
+
+    @cached_property
+    def year_to_days(self) -> OrderedDict:
+        # Map each year to the 'days since year-08-01 06:00:00'
+        year_to_days = OrderedDict()
+        for year in self.ordered_years:
+            date = datetime.datetime(year=year, month=8, day=1, hour=6, minute=0, second=0)
+            days = []
+            for i in range(366):
+                days.append(str(date).split()[0])
+                date += datetime.timedelta(days=1)
+                if date.month == 8 and date.day == 1:
+                    break
+            year_to_days[year] = days
+        return year_to_days
+
+    @property
+    def all_days(self):
+        return list(chain(*list(self.year_to_days.values())))
+
+    @property
+    def all_daily_series(self):
+        all_daily_series = np.concatenate(list(self.year_to_daily_time_serie_array.values()))
+        assert len(all_daily_series) == len(self.all_days)
+        return all_daily_series
+
     """ Annual maxima """
 
     @property

experiment/meteo_france_data/scm_models_data/crocus/taline_data.py

+from collections import OrderedDict
+
+import numpy as np
+import pandas as pd
+
+from experiment.meteo_france_data.scm_models_data.crocus.crocus import CrocusDepth
+from experiment.meteo_france_data.scm_models_data.scm_constants import ALTITUDES
+from utils import get_display_name_from_object_type
+
+massif_name = 'Queyras'
+study_class = CrocusDepth
+all_days = study_class(altitude=0).all_days
+altitude_to_queyras_depth = OrderedDict()
+for altitude in ALTITUDES[:]:
+    study = study_class(altitude=altitude)
+    if massif_name in study.study_massif_names:
+        idx_queyras = study.study_massif_names.index(massif_name)
+        queyras_all_daily_series = study.all_daily_series[:, idx_queyras]
+        altitude_to_queyras_depth[altitude] = queyras_all_daily_series
+df = pd.DataFrame.from_dict(altitude_to_queyras_depth)
+df.index = all_days
+df.to_csv('{}_{}.csv'.format(massif_name, get_display_name_from_object_type(study_class)))
\ No newline at end of file

test/test_experiment/test_region_eurocode.py

@@ -3,16 +3,6 @@ from collections import OrderedDict
 
 from experiment.eurocode_data.eurocode_visualizer import display_region_limit
 from experiment.eurocode_data.region_eurocode import C1, E
-from experiment.meteo_france_data.scm_models_data.crocus.crocus import CrocusSweTotal
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.main_study_visualizer import \
-    study_iterator_global
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.study_visualizer import \
-    StudyVisualizer
-from experiment.trend_analysis.non_stationary_trends import \
-    ConditionalIndedendenceLocationTrendTest
-from spatio_temporal_dataset.coordinates.transformed_coordinates.transformation.uniform_normalization import \
-    BetweenZeroAndOneNormalization, BetweenZeroAndOneNormalizationMinEpsilon, BetweenZeroAndOneNormalizationMaxEpsilon
-from utils import get_display_name_from_object_type
 
 
 class TestCoordinateSensitivity(unittest.TestCase):