diff --git a/experiment/meteo_france_SCM_study/visualization/hypercube_visualization/abstract_hypercube_visualizer.py b/experiment/meteo_france_SCM_study/visualization/hypercube_visualization/abstract_hypercube_visualizer.py
new file mode 100644
index 0000000000000000000000000000000000000000..13524c335b8ce8a3001013423d340461b625dedc
--- /dev/null
+++ b/experiment/meteo_france_SCM_study/visualization/hypercube_visualization/abstract_hypercube_visualizer.py
@@ -0,0 +1,95 @@
+import os
+import os.path as op
+from typing import Dict, Tuple
+
+import matplotlib.pyplot as plt
+import pandas as pd
+
+from experiment.meteo_france_SCM_study.visualization.study_visualization.study_visualizer import StudyVisualizer
+from utils import cached_property, VERSION_TIME, get_display_name_from_object_type
+
+
+class AbstractHypercubeVisualizer(object):
+ """
+ A study visualizer contain some massifs and years. This forms the base DataFrame of the hypercube
+ Additional index will come from the tuple.
+ Tuple could contain altitudes, type of snow quantity
+ """
+
+ def __init__(self, tuple_to_study_visualizer: Dict[Tuple, StudyVisualizer],
+ trend_test_class,
+ fast=False,
+ save_to_file=False):
+ self.nb_data_for_fast_mode = 7 if fast else None
+ self.save_to_file = save_to_file
+ self.trend_test_class = trend_test_class
+ self.tuple_to_study_visualizer = tuple_to_study_visualizer # type: Dict[Tuple, StudyVisualizer]
+
+ # Main attributes defining the hypercube
+
+ @property
+ def trend_test_name(self):
+ return get_display_name_from_object_type(self.trend_test_class)
+
+ @cached_property
+ def starting_years(self):
+ starting_years = self.study_visualizer.starting_years
+ if self.nb_data_for_fast_mode is not None:
+ starting_years = starting_years[:self.nb_data_for_fast_mode]
+ return starting_years
+
+ def tuple_values(self, idx):
+ return sorted(set([t[idx] if isinstance(t, tuple) else t for t in self.tuple_to_study_visualizer.keys()]))
+
+ @cached_property
+ def df_hypercube_trend_type(self) -> pd.DataFrame:
+ df_spatio_temporal_trend_types = [
+ study_visualizer.df_trend_spatio_temporal(self.trend_test_class, self.starting_years,
+ self.nb_data_for_fast_mode)
+ for study_visualizer in self.tuple_to_study_visualizer.values()]
+ return pd.concat(df_spatio_temporal_trend_types, keys=list(self.tuple_to_study_visualizer.keys()), axis=0)
+
+ @cached_property
+ def df_hypercube_trend_strength(self) -> pd.DataFrame:
+ df_spatio_temporal_trend_types = [
+ study_visualizer.df_trend_spatio_temporal(self.trend_test_class, self.starting_years,
+ self.nb_data_for_fast_mode)
+ for study_visualizer in self.tuple_to_study_visualizer.values()]
+ return pd.concat(df_spatio_temporal_trend_types, keys=list(self.tuple_to_study_visualizer.keys()), axis=0)
+
+ # Some properties
+
+ @property
+ def study_title(self):
+ return self.study.title
+
+ def show_or_save_to_file(self, specific_title=''):
+ if self.save_to_file:
+ main_title, *_ = '_'.join(self.study_title.split()).split('/')
+ filename = "{}/{}/".format(VERSION_TIME, main_title)
+ filename += specific_title
+ filepath = op.join(self.study.result_full_path, filename + '.png')
+ dirname = op.dirname(filepath)
+ if not op.exists(dirname):
+ os.makedirs(dirname, exist_ok=True)
+ plt.savefig(filepath)
+ else:
+ plt.show()
+
+ @property
+ def study_visualizer(self) -> StudyVisualizer:
+ return list(self.tuple_to_study_visualizer.values())[0]
+
+ @property
+ def study(self):
+ return self.study_visualizer.study
+
+ @property
+ def starting_year_to_weights(self):
+ # Load uniform weights by default
+ uniform_weight = 1 / len(self.starting_years)
+ return {year: uniform_weight for year in self.starting_years}
+
+
+
+
diff --git a/experiment/meteo_france_SCM_study/visualization/hypercube_visualization/hypercube_visualizer.py b/experiment/meteo_france_SCM_study/visualization/hypercube_visualization/altitude_hypercube_visualizer.py
similarity index 58%
rename from experiment/meteo_france_SCM_study/visualization/hypercube_visualization/hypercube_visualizer.py
rename to experiment/meteo_france_SCM_study/visualization/hypercube_visualization/altitude_hypercube_visualizer.py
index c710200db79413babbaab7df2d85792bdcaf2dff..5c692a918bcfce40038e01e816c93a8408d87bb5 100644
--- a/experiment/meteo_france_SCM_study/visualization/hypercube_visualization/hypercube_visualizer.py
+++ b/experiment/meteo_france_SCM_study/visualization/hypercube_visualization/altitude_hypercube_visualizer.py
@@ -1,97 +1,14 @@
-import os
-import os.path as op
-from typing import Dict, Tuple
-
import matplotlib.pyplot as plt
import pandas as pd
+from experiment.meteo_france_SCM_study.visualization.hypercube_visualization.abstract_hypercube_visualizer import \
+ AbstractHypercubeVisualizer
from experiment.meteo_france_SCM_study.visualization.study_visualization.study_visualizer import StudyVisualizer
from experiment.trend_analysis.univariate_trend_test.abstract_trend_test import AbstractTrendTest
-from utils import cached_property, VERSION_TIME, get_display_name_from_object_type
-
-
-class HypercubeVisualizer(object):
- """
- A study visualizer contain some massifs and years. This forms the base DataFrame of the hypercube
- Additional index will come from the tuple.
- Tuple could contain altitudes, type of snow quantity
- """
-
- def __init__(self, tuple_to_study_visualizer: Dict[Tuple, StudyVisualizer],
- trend_test_class,
- fast=False,
- save_to_file=False):
- self.nb_data_for_fast_mode = 7 if fast else None
- self.save_to_file = save_to_file
- self.trend_test_class = trend_test_class
- self.tuple_to_study_visualizer = tuple_to_study_visualizer # type: Dict[Tuple, StudyVisualizer]
-
- # Main attributes defining the hypercube
-
- @property
- def trend_test_name(self):
- return get_display_name_from_object_type(self.trend_test_class)
-
- @cached_property
- def starting_years(self):
- starting_years = self.study_visualizer.starting_years
- if self.nb_data_for_fast_mode is not None:
- starting_years = starting_years[:self.nb_data_for_fast_mode]
- return starting_years
-
- @cached_property
- def tuple_to_df_trend_type(self):
- df_spatio_temporal_trend_types = [
- study_visualizer.df_trend_spatio_temporal(self.trend_test_class, self.starting_years,
- self.nb_data_for_fast_mode)
- for study_visualizer in self.tuple_to_study_visualizer.values()]
- return dict(zip(self.tuple_to_study_visualizer.keys(), df_spatio_temporal_trend_types))
-
- def tuple_values(self, idx):
- return sorted(set([t[idx] if isinstance(t, tuple) else t for t in self.tuple_to_study_visualizer.keys()]))
-
- @cached_property
- def df_hypercube(self) -> pd.DataFrame:
- keys = list(self.tuple_to_df_trend_type.keys())
- values = list(self.tuple_to_df_trend_type.values())
- df = pd.concat(values, keys=keys, axis=0)
- return df
+from utils import get_display_name_from_object_type
- # Some properties
- @property
- def study_title(self):
- return self.study.title
-
- def show_or_save_to_file(self, specific_title=''):
- if self.save_to_file:
- main_title, *_ = '_'.join(self.study_title.split()).split('/')
- filename = "{}/{}/".format(VERSION_TIME, main_title)
- filename += specific_title
- filepath = op.join(self.study.result_full_path, filename + '.png')
- dirname = op.dirname(filepath)
- if not op.exists(dirname):
- os.makedirs(dirname, exist_ok=True)
- plt.savefig(filepath)
- else:
- plt.show()
-
- @property
- def study_visualizer(self) -> StudyVisualizer:
- return list(self.tuple_to_study_visualizer.values())[0]
-
- @property
- def study(self):
- return self.study_visualizer.study
-
- @property
- def starting_year_to_weights(self):
- # Load uniform weights by default
- uniform_weight = 1 / len(self.starting_years)
- return {year: uniform_weight for year in self.starting_years}
-
-
-class AltitudeHypercubeVisualizer(HypercubeVisualizer):
+class AltitudeHypercubeVisualizer(AbstractHypercubeVisualizer):
@property
def altitudes(self):
@@ -109,7 +26,7 @@ class AltitudeHypercubeVisualizer(HypercubeVisualizer):
# Map each trend type to its serie with percentages
trend_type_to_s_percentages = {}
for trend_type in self.trend_types:
- df_bool = (self.df_hypercube == trend_type)
+ df_bool = (self.df_hypercube_trend_type == trend_type)
# Reduce the entire dataframe to a serie
s_percentages = reduction_function(df_bool)
assert isinstance(s_percentages, pd.Series)
@@ -125,10 +42,8 @@ class AltitudeHypercubeVisualizer(HypercubeVisualizer):
def subtitle_to_reduction_function(self, reduction_function, level=None, add_detailed_plot=False):
def reduction_function_with_level(df_bool):
- if level is None:
- return reduction_function(df_bool)
- else:
- return reduction_function(df_bool, level)
+ return reduction_function(df_bool) if level is None else reduction_function(df_bool, level)
+
return {'global': reduction_function_with_level}
def visualize_trend_test_evolution(self, reduction_function, xlabel, xlabel_values, ax=None, marker='o',
@@ -214,10 +129,10 @@ class AltitudeHypercubeVisualizer(HypercubeVisualizer):
# Take the mean with respect to the years
df_bool = df_bool.mean(axis=1)
# Take the mean with respect the massifs
- print(df_bool.head())
return df_bool.mean(level=level)
- for subtitle, reduction_function in self.subtitle_to_reduction_function(altitude_reduction, level=self.altitude_index_level,
+ for subtitle, reduction_function in self.subtitle_to_reduction_function(altitude_reduction,
+ level=self.altitude_index_level,
add_detailed_plot=add_detailed_plots).items():
self.visualize_trend_test_evolution(reduction_function=reduction_function, xlabel='altitude',
xlabel_values=self.altitudes, ax=ax, marker=marker,
@@ -230,51 +145,7 @@ class AltitudeHypercubeVisualizer(HypercubeVisualizer):
# Take the mean with respect the altitude
return df_bool.mean(level=level)
- for subtitle, reduction_function in self.subtitle_to_reduction_function(massif_reduction,level=self.massif_index_level,
+ for subtitle, reduction_function in self.subtitle_to_reduction_function(massif_reduction,
+ level=self.massif_index_level,
add_detailed_plot=add_detailed_plots).items():
self.visualize_trend_test_repartition(reduction_function, axes, subtitle=subtitle)
-
-
-class QuantityAltitudeHypercubeVisualizer(AltitudeHypercubeVisualizer):
-
- @property
- def study_title(self):
- return 'Quantity Altitude Study'
-
- def subtitle_to_reduction_function(self, reduction_function, level=None, add_detailed_plot=False):
- subtitle_to_reduction_function = super().subtitle_to_reduction_function(reduction_function, level, add_detailed_plot)
-
- def get_function_from_tuple(tuple_for_axis_0):
- def f(df_bool: pd.DataFrame):
- # Loc with a tuple with respect the axis 0
- df_bool = df_bool.loc[tuple_for_axis_0, :].copy()
- # Apply the reduction function
- if level is None:
- return reduction_function(df_bool)
- else:
- return reduction_function(df_bool, level-1)
-
- return f
-
- # Add the detailed plot, taken by loc with respect to the first index
- if add_detailed_plot:
- tuples_axis_0 = self.tuple_values(idx=0)
- for tuple_axis_0 in tuples_axis_0:
- subtitle_to_reduction_function[tuple_axis_0] = get_function_from_tuple(tuple_axis_0)
- return subtitle_to_reduction_function
-
- @property
- def quantities(self):
- return self.tuple_values(idx=0)
-
- @property
- def altitudes(self):
- return self.tuple_values(idx=1)
-
- @property
- def altitude_index_level(self):
- return 1
-
- @property
- def massif_index_level(self):
- return 2
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 987de94118d5dc42a6659f7cd671d9d9ae1d3d7a..28e8e3bcd9b5c17e2ce64850e6cdea144932d991 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
@@ -2,8 +2,10 @@ import time
from itertools import product
from collections import OrderedDict
-from experiment.meteo_france_SCM_study.visualization.hypercube_visualization.hypercube_visualizer import \
- AltitudeHypercubeVisualizer, QuantityAltitudeHypercubeVisualizer
+from experiment.meteo_france_SCM_study.visualization.hypercube_visualization.altitude_hypercube_visualizer import \
+ AltitudeHypercubeVisualizer
+from experiment.meteo_france_SCM_study.visualization.hypercube_visualization.quantity_altitude_visualizer import \
+ QuantityAltitudeHypercubeVisualizer
from experiment.meteo_france_SCM_study.visualization.study_visualization.main_study_visualizer import ALL_ALTITUDES, \
SCM_STUDIES, study_iterator, study_iterator_global
from experiment.meteo_france_SCM_study.visualization.study_visualization.study_visualizer import StudyVisualizer
@@ -90,9 +92,9 @@ 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/meteo_france_SCM_study/visualization/hypercube_visualization/quantity_altitude_visualizer.py b/experiment/meteo_france_SCM_study/visualization/hypercube_visualization/quantity_altitude_visualizer.py
new file mode 100644
index 0000000000000000000000000000000000000000..92d20988786352aefc381ea614068d7e638468ce
--- /dev/null
+++ b/experiment/meteo_france_SCM_study/visualization/hypercube_visualization/quantity_altitude_visualizer.py
@@ -0,0 +1,46 @@
+import pandas as pd
+
+from experiment.meteo_france_SCM_study.visualization.hypercube_visualization.altitude_hypercube_visualizer import \
+ AltitudeHypercubeVisualizer
+
+
+class QuantityAltitudeHypercubeVisualizer(AltitudeHypercubeVisualizer):
+
+ @property
+ def study_title(self):
+ return 'Quantity Altitude Study'
+
+ def subtitle_to_reduction_function(self, reduction_function, level=None, add_detailed_plot=False):
+ subtitle_to_reduction_function = super().subtitle_to_reduction_function(reduction_function,
+ level, add_detailed_plot)
+
+ def get_function_from_tuple(tuple_for_axis_0):
+ def f(df_bool: pd.DataFrame):
+ # Loc with a tuple with respect the axis 0
+ df_bool = df_bool.loc[tuple_for_axis_0, :].copy()
+ # Apply the reduction function
+ return reduction_function(df_bool) if level is None else reduction_function(df_bool, level-1)
+ return f
+
+ # Add the detailed plot, taken by loc with respect to the first index
+ if add_detailed_plot:
+ tuples_axis_0 = self.tuple_values(idx=0)
+ for tuple_axis_0 in tuples_axis_0:
+ subtitle_to_reduction_function[tuple_axis_0] = get_function_from_tuple(tuple_axis_0)
+ return subtitle_to_reduction_function
+
+ @property
+ def quantities(self):
+ return self.tuple_values(idx=0)
+
+ @property
+ def altitudes(self):
+ return self.tuple_values(idx=1)
+
+ @property
+ def altitude_index_level(self):
+ return 1
+
+ @property
+ def massif_index_level(self):
+ return 2
diff --git a/experiment/meteo_france_SCM_study/visualization/studies_visualization/main_studies_visualizer.py b/experiment/meteo_france_SCM_study/visualization/studies_visualization/main_studies_visualizer.py
index fc0f64a30d5d47444c0de4659f017c2c34217241..23c2c0fa56c95bd4594266c58cae4124d380145e 100644
--- a/experiment/meteo_france_SCM_study/visualization/studies_visualization/main_studies_visualizer.py
+++ b/experiment/meteo_france_SCM_study/visualization/studies_visualization/main_studies_visualizer.py
@@ -1,7 +1,4 @@
import time
-
-from experiment.meteo_france_SCM_study.visualization.hypercube_visualization.hypercube_visualizer import \
- AltitudeHypercubeVisualizer
from experiment.trend_analysis.abstract_score import MannKendall, WeigthedScore, MeanScore, MedianScore
from experiment.trend_analysis.univariate_trend_test.abstract_gev_trend_test import GevLocationTrendTest, \
GevScaleTrendTest, GevShapeTrendTest
@@ -11,7 +8,7 @@ from experiment.meteo_france_SCM_study.visualization.studies_visualization.studi
from experiment.meteo_france_SCM_study.visualization.studies_visualization.studies_visualizer import StudiesVisualizer, \
AltitudeVisualizer
from experiment.meteo_france_SCM_study.visualization.study_visualization.main_study_visualizer import ALL_ALTITUDES, \
- study_iterator_global, SCM_STUDIES, study_iterator
+ study_iterator_global, SCM_STUDIES
from experiment.meteo_france_SCM_study.visualization.study_visualization.study_visualizer import StudyVisualizer
from collections import OrderedDict