diff --git a/experiment/meteo_france_data/scm_models_data/abstract_study.py b/experiment/meteo_france_data/scm_models_data/abstract_study.py
index 0a18ad1fe19d8aa86e6f76c62313076facffb8d8..6fe1e078b5d19065ec5def8cca49ae2196954ad5 100644
--- a/experiment/meteo_france_data/scm_models_data/abstract_study.py
+++ b/experiment/meteo_france_data/scm_models_data/abstract_study.py
@@ -4,7 +4,7 @@ import os.path as op
from collections import OrderedDict
from contextlib import redirect_stdout
from multiprocessing.pool import Pool
-from typing import List, Dict, Tuple
+from typing import List, Dict, Tuple, Union
import matplotlib.pyplot as plt
import numpy as np
@@ -26,7 +26,7 @@ from spatio_temporal_dataset.coordinates.abstract_coordinates import AbstractCoo
from spatio_temporal_dataset.coordinates.spatial_coordinates.abstract_spatial_coordinates import \
AbstractSpatialCoordinates
from spatio_temporal_dataset.spatio_temporal_observations.annual_maxima_observations import AnnualMaxima
-from utils import get_full_path, cached_property, NB_CORES
+from utils import get_full_path, cached_property, NB_CORES, classproperty
f = io.StringIO()
with redirect_stdout(f):
@@ -112,8 +112,6 @@ class AbstractStudy(object):
year_to_daily_time_serie_array[year] = daily_time_serie
return year_to_daily_time_serie_array
-
-
""" Load Variables and Datasets """
@cached_property
@@ -215,20 +213,29 @@ class AbstractStudy(object):
""" Visualization methods """
- @cached_property
- def massifs_coordinates_for_display(self) -> AbstractSpatialCoordinates:
+ @classmethod
+ def massifs_coordinates_for_display(cls, massif_names) -> AbstractSpatialCoordinates:
# Coordinate object that represents the massif coordinates in Lambert extended
# extracted for a csv file, and used only for display purposes
- df = self.load_df_centroid()
+ df = cls.load_df_centroid()
# Filter, keep massifs present at the altitude of interest
- df = df.loc[self.study_massif_names]
+ df = df.loc[massif_names, :]
# Build coordinate object from df_centroid
return AbstractSpatialCoordinates.from_df(df)
- def visualize_study(self, ax=None, massif_name_to_value=None, show=True, fill=True, replace_blue_by_white=True,
- label=None, add_text=False, cmap=None, vmax=100, vmin=0):
+ @classmethod
+ def visualize_study(cls, ax=None, massif_name_to_value: Union[None, Dict[str, float]] = None, show=True, fill=True,
+ replace_blue_by_white=True,
+ label=None, add_text=False, cmap=None, vmax=100, vmin=0,
+ default_color_for_missing_massif='w',
+ default_color_for_nan_values='w',
+ ):
+ if ax is None:
+ ax = plt.gca()
+
if massif_name_to_value is None:
massif_name_to_fill_kwargs = None
+ massif_names, values = None, None
else:
massif_names, values = list(zip(*massif_name_to_value.items()))
if cmap is None:
@@ -237,14 +244,11 @@ class AbstractStudy(object):
norm = Normalize(vmin, vmax)
create_colorbase_axis(ax, label, cmap, norm)
m = cm.ScalarMappable(norm=norm, cmap=cmap)
- colors = [m.to_rgba(value) if not np.isnan(value) else 'w' for value in values]
+ colors = [m.to_rgba(value) if not np.isnan(value) else default_color_for_nan_values for value in values]
massif_name_to_fill_kwargs = {massif_name: {'color': color} for massif_name, color in
zip(massif_names, colors)}
- if ax is None:
- ax = plt.gca()
-
- for coordinate_id, coords_list in self.idx_to_coords_list.items():
+ for coordinate_id, coords_list in cls.idx_to_coords_list.items():
# Retrieve the list of coords (x,y) that define the contour of the massif of id coordinate_id
# if j == 0:
@@ -253,11 +257,14 @@ class AbstractStudy(object):
coords_list = list(zip(*coords_list))
ax.plot(*coords_list, color='black')
# Potentially, fill the inside of the polygon with some color
- if fill and coordinate_id in self.coordinate_id_to_massif_name:
- massif_name = self.coordinate_id_to_massif_name[coordinate_id]
+ if fill and coordinate_id in cls.coordinate_id_to_massif_name:
+ massif_name = cls.coordinate_id_to_massif_name[coordinate_id]
if massif_name_to_fill_kwargs is not None and massif_name in massif_name_to_fill_kwargs:
fill_kwargs = massif_name_to_fill_kwargs[massif_name]
ax.fill(*coords_list, **fill_kwargs)
+ else:
+ ax.fill(*coords_list, **{'color': default_color_for_missing_massif})
+
# else:
# fill_kwargs = {}
@@ -268,8 +275,11 @@ class AbstractStudy(object):
# ax.scatter(x, y)
# ax.text(x, y, massif_name)
# Display the center of the massif
- ax.scatter(self.massifs_coordinates_for_display.x_coordinates,
- self.massifs_coordinates_for_display.y_coordinates, s=1)
+ print(massif_names)
+ masssif_coordinate_for_display = cls.massifs_coordinates_for_display(massif_names)
+
+ ax.scatter(masssif_coordinate_for_display.x_coordinates,
+ masssif_coordinate_for_display.y_coordinates, s=1)
# Improve some explanation on the X axis and on the Y axis
ax.set_xlabel('Longitude (km)')
ax.xaxis.set_major_formatter(get_km_formatter())
@@ -277,7 +287,7 @@ class AbstractStudy(object):
ax.yaxis.set_major_formatter(get_km_formatter())
# Display the name or value of the massif
if add_text:
- for _, row in self.massifs_coordinates_for_display.df_all_coordinates.iterrows():
+ for _, row in masssif_coordinate_for_display.df_all_coordinates.iterrows():
x, y = list(row)
massif_name = row.name
value = massif_name_to_value[massif_name]
@@ -293,15 +303,15 @@ class AbstractStudy(object):
""" Path properties """
- @property
+ @classproperty
def relative_path(self) -> str:
return r'local/spatio_temporal_datasets'
- @property
+ @classproperty
def full_path(self) -> str:
return get_full_path(relative_path=self.relative_path)
- @property
+ @classproperty
def map_full_path(self) -> str:
return op.join(self.full_path, 'map')
@@ -321,12 +331,13 @@ class AbstractStudy(object):
def original_safran_massif_id_to_massif_name(self) -> Dict[int, str]:
return {massif_id: massif_name for massif_id, massif_name in enumerate(self.all_massif_names)}
- @cached_property
- def all_massif_names(self) -> List[str]:
+ # @cached_property
+ @classproperty
+ def all_massif_names(cls) -> List[str]:
"""
Pour l'identification des massifs, le numéro de la variable massif_num correspond à celui de l'attribut num_opp
"""
- metadata_path = op.join(self.full_path, self.REANALYSIS_FOLDER, 'metadata')
+ metadata_path = op.join(cls.full_path, cls.REANALYSIS_FOLDER, 'metadata')
dbf = Dbf5(op.join(metadata_path, 'massifs_alpes.dbf'))
df = dbf.to_dataframe().copy() # type: pd.DataFrame
dbf.f.close()
@@ -336,15 +347,16 @@ class AbstractStudy(object):
all_massif_names[all_massif_names.index('Beaufortin')] = 'Beaufortain'
return all_massif_names
- def load_df_centroid(self) -> pd.DataFrame:
+ @classmethod
+ def load_df_centroid(cls) -> pd.DataFrame:
# Load df_centroid containing all the massif names
- df_centroid = pd.read_csv(op.join(self.map_full_path, 'coordonnees_massifs_alpes.csv'))
+ df_centroid = pd.read_csv(op.join(cls.map_full_path, 'coordonnees_massifs_alpes.csv'))
df_centroid.set_index('NOM', inplace=True)
# Check that the names of massifs are the same
- symmetric_difference = set(df_centroid.index).symmetric_difference(self.all_massif_names)
+ symmetric_difference = set(df_centroid.index).symmetric_difference(cls.all_massif_names)
assert len(symmetric_difference) == 0, symmetric_difference
# Sort the column in the order of the SAFRAN dataset
- df_centroid = df_centroid.reindex(self.all_massif_names, axis=0)
+ df_centroid = df_centroid.reindex(cls.all_massif_names, axis=0)
for coord_column in [AbstractCoordinates.COORDINATE_X, AbstractCoordinates.COORDINATE_Y]:
df_centroid.loc[:, coord_column] = df_centroid[coord_column].str.replace(',', '.').astype(float)
return df_centroid
@@ -371,12 +383,12 @@ class AbstractStudy(object):
""" Visualization methods """
- @property
- def coordinate_id_to_massif_name(self) -> Dict[int, str]:
- df_centroid = self.load_df_centroid()
+ @classproperty
+ def coordinate_id_to_massif_name(cls) -> Dict[int, str]:
+ df_centroid = cls.load_df_centroid()
return dict(zip(df_centroid['id'], df_centroid.index))
- @property
+ @classproperty
def idx_to_coords_list(self):
df_massif = pd.read_csv(op.join(self.map_full_path, 'massifsalpes.csv'))
coord_tuples = [(row_massif['idx'], row_massif[AbstractCoordinates.COORDINATE_X],
diff --git a/experiment/meteo_france_data/stations_data/main_station_comparison.py b/experiment/meteo_france_data/stations_data/main_station_comparison.py
index 4a62e8d0c59a378f3b29d1d401d508487d29f22b..e8dd8bb4544f93101dcfc73e243fc0e58de727dd 100644
--- a/experiment/meteo_france_data/stations_data/main_station_comparison.py
+++ b/experiment/meteo_france_data/stations_data/main_station_comparison.py
@@ -7,7 +7,7 @@ from experiment.meteo_france_data.stations_data.visualization.comparisons_visual
def visualize_all_stations():
vizu = ComparisonsVisualization(altitudes=ALL_ALTITUDES_WITH_20_STATIONS_AT_LEAST, margin=150)
- vizu.visualize_maximum()
+ vizu.visualize_maximum(visualize_metric_only=False)
def visualize_non_nan_station():
@@ -53,9 +53,9 @@ def quick_metric_analysis():
if __name__ == '__main__':
# wrong_example3()
# visualize_fast_comparison()
- # visualize_all_stations()
+ visualize_all_stations()
+ # quick_metric_analysis()
# wrong_example2()
# visualize_non_nan_station()
- quick_metric_analysis()
# example()
diff --git a/experiment/meteo_france_data/stations_data/visualization/comparisons_visualization/comparisons_visualization.py b/experiment/meteo_france_data/stations_data/visualization/comparisons_visualization/comparisons_visualization.py
index 60ed00648c1131596d7e4febd726f987a30527bd..0e5a4914b26e4139e3a3f13fdc2a4fa0e149c0ce 100644
--- a/experiment/meteo_france_data/stations_data/visualization/comparisons_visualization/comparisons_visualization.py
+++ b/experiment/meteo_france_data/stations_data/visualization/comparisons_visualization/comparisons_visualization.py
@@ -7,6 +7,7 @@ import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
+from experiment.meteo_france_data.scm_models_data.abstract_study import AbstractStudy
from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.study_visualizer import \
VisualizationParameters
from experiment.meteo_france_data.stations_data.comparison_analysis import ComparisonAnalysis, MASSIF_COLUMN_NAME, \
@@ -17,6 +18,9 @@ from experiment.trend_analysis.univariate_test.utils import compute_gev_change_p
from extreme_estimator.extreme_models.result_from_fit import ResultFromIsmev
from extreme_estimator.extreme_models.utils import r, safe_run_r_estimator, ro
from spatio_temporal_dataset.coordinates.abstract_coordinates import AbstractCoordinates
+from utils import classproperty
+
+MAE_COLUMN_NAME = 'mean absolute difference'
DISTANCE_COLUMN_NAME = 'distance'
path_df_location_to_value_csv_example = r'/home/erwan/Documents/projects/spatiotemporalextremes/experiment/meteo_france_data/stations_data/csv/example.csv'
@@ -47,6 +51,14 @@ class ComparisonsVisualization(VisualizationParameters):
def comparisons(self) -> List[ComparisonAnalysis]:
return list(self.altitude_to_comparison.values())
+ @property
+ def comparison(self):
+ return self.comparisons[0]
+
+ @property
+ def study(self):
+ return self.comparison.study
+
@property
def nb_plot(self):
return sum([c.nb_massifs for c in self.comparisons])
@@ -78,6 +90,8 @@ class ComparisonsVisualization(VisualizationParameters):
plt.suptitle(title)
if show:
plt.show()
+ else:
+ plt.clf()
# Build dataframe from the dictionary
df = pd.DataFrame(tuple_location_to_values, index=index).transpose()
@@ -85,18 +99,24 @@ class ComparisonsVisualization(VisualizationParameters):
return df
@classmethod
- def visualize_metric(cls, df_location_to_value=None):
+ def visualize_metric(cls, df=None):
# Load or update df value from example file
- if df_location_to_value is None:
- df_location_to_value = pd.read_csv(path_df_location_to_value_csv_example, index_col=[0, 1, 2])
+ if df is None:
+ df = pd.read_csv(path_df_location_to_value_csv_example, index_col=[0, 1, 2])
else:
- df_location_to_value.to_csv(path_df_location_to_value_csv_example)
+ df.to_csv(path_df_location_to_value_csv_example)
- print(df_location_to_value)
- print(df_location_to_value.index)
- print(df_location_to_value.columns)
+ # Compute some column like a classication boolean
# Display some score spatially
+ df_score = df.groupby([MASSIF_COLUMN_NAME]).mean()
+ s_mae = df_score[MAE_COLUMN_NAME]
+ massif_name_to_value = s_mae.to_dict()
+ AbstractStudy.visualize_study(massif_name_to_value=massif_name_to_value,
+ default_color_for_missing_massif='b',
+ cmap=plt.cm.Reds,
+ vmin=s_mae.min(),
+ vmax=s_mae.max())
def _visualize_ax_main(self, plot_function, comparison: ComparisonAnalysis, massif, ax=None, show=False):
if ax is None:
@@ -126,21 +146,19 @@ class ComparisonsVisualization(VisualizationParameters):
ordered_value_dict = OrderedDict()
label = i
- label += ' ({}m)'.format(s[ALTITUDE_COLUMN_NAME])
- label += ' ({}km)'.format(s[DISTANCE_COLUMN_NAME])
+
maxima, years = self.get_maxima_and_year(s)
# Compute the distance between maxima and maxima_center
# In percent the number of times the observations is stricty higher than the reanalysis
mask = ~np.isnan(maxima_center) & ~np.isnan(maxima)
mean_absolute_difference = np.round(np.mean(np.abs(maxima[mask] - maxima_center[mask])), 0)
- label += 'Mean absolute diff {}mm'.format(mean_absolute_difference)
- ordered_value_dict['mean absolute difference'] = mean_absolute_difference
- # metric = np.mean(np.sign(maxima[mask] - maxima_center[mask]) == 1)
- # metric = np.round(metric * 100, 0)
- # label += '{}% strictly above'.format(metric)
+ ordered_value_dict[MAE_COLUMN_NAME] = mean_absolute_difference
+ label += ' ({}m)'.format(s[ALTITUDE_COLUMN_NAME])
+ label += ' ({}km)'.format(s[DISTANCE_COLUMN_NAME])
+ label += '({}mm)'.format(mean_absolute_difference)
plot_color = color if REANALYSE_STR not in label else 'g'
plot_ordered_value_dict = plot_function(ax, ax2, years, maxima, label, plot_color)
diff --git a/utils.py b/utils.py
index 37d72bb945e22206b596a7b12962a0d8fc726a40..f43fe09f504956b9e7a0a31c52e02aeac3a95646 100644
--- a/utils.py
+++ b/utils.py
@@ -44,6 +44,38 @@ class Example(object):
return 2
+# https://stackoverflow.com/questions/5189699/how-to-make-a-class-property
+# does not enable setter, but follow the link to activate setter option
+
+class ClassPropertyDescriptor(object):
+
+ def __init__(self, fget, fset=None):
+ self.fget = fget
+ self.fset = fset
+
+ def __get__(self, obj, klass=None):
+ if klass is None:
+ klass = type(obj)
+ return self.fget.__get__(obj, klass)()
+
+ def __set__(self, obj, value):
+ if not self.fset:
+ raise AttributeError("can't set attribute")
+ type_ = type(obj)
+ return self.fset.__get__(obj, type_)(value)
+
+ def setter(self, func):
+ if not isinstance(func, (classmethod, staticmethod)):
+ func = classmethod(func)
+ self.fset = func
+ return self
+
+def classproperty(func):
+ if not isinstance(func, (classmethod, staticmethod)):
+ func = classmethod(func)
+
+ return ClassPropertyDescriptor(func)
+
if __name__ == '__main__':
e = Example()
print(e.big_attribute)