diff --git a/experiment/meteo_france_data/plot/mask_poly.py b/experiment/meteo_france_data/plot/mask_poly.py
deleted file mode 100644
index d7a478680b54176a7444f73bae5455140eb196ae..0000000000000000000000000000000000000000
--- a/experiment/meteo_france_data/plot/mask_poly.py
+++ /dev/null
@@ -1,44 +0,0 @@
-import matplotlib.pyplot as plt
-import matplotlib.patches as mpatches
-import matplotlib.path as mpath
-
-
-# from: https://stackoverflow.com/questions/3320311/fill-outside-of-polygon-mask-array-where-indicies-are-beyond-a-circular-bounda
-def mask_outside_polygon(poly_verts, ax=None):
- """
- Plots a mask on the specified axis ("ax", defaults to plt.gca()) such that
- all areas outside of the polygon specified by "poly_verts" are masked.
-
- "poly_verts" must be a list of tuples of the verticies in the polygon in
- counter-clockwise order.
-
- Returns the matplotlib.patches.PathPatch instance plotted on the figure.
- """
-
- if ax is None:
- ax = plt.gca()
-
- # Get current plot limits
- xlim = ax.get_xlim()
- ylim = ax.get_ylim()
-
- # Verticies of the plot boundaries in clockwise order
- bound_verts = [(xlim[0], ylim[0]), (xlim[0], ylim[1]),
- (xlim[1], ylim[1]), (xlim[1], ylim[0]),
- (xlim[0], ylim[0])]
-
- # A series of codes (1 and 2) to tell matplotlib whether to draw a line or
- # move the "pen" (So that there's no connecting line)
- bound_codes = [mpath.Path.MOVETO] + (len(bound_verts) - 1) * [mpath.Path.LINETO]
- poly_codes = [mpath.Path.MOVETO] + (len(poly_verts) - 1) * [mpath.Path.LINETO]
-
- # Plot the masking patch
- path = mpath.Path(bound_verts + poly_verts, bound_codes + poly_codes)
- patch = mpatches.PathPatch(path, facecolor='white', edgecolor='none')
- patch = ax.add_patch(patch)
-
- # Reset the plot limits to their original extents
- ax.set_xlim(xlim)
- ax.set_ylim(ylim)
-
- return patch
diff --git a/experiment/meteo_france_data/plot/shifted_color_map.py b/experiment/meteo_france_data/plot/shifted_color_map.py
deleted file mode 100644
index dd4ac7d627b5eba0ef982e271a1780955c8f5533..0000000000000000000000000000000000000000
--- a/experiment/meteo_france_data/plot/shifted_color_map.py
+++ /dev/null
@@ -1,56 +0,0 @@
-import numpy as np
-import matplotlib
-import matplotlib.pyplot as plt
-from mpl_toolkits.axes_grid1 import AxesGrid
-
-# from: https://stackoverflow.com/questions/7404116/defining-the-midpoint-of-a-colormap-in-matplotlib/20528097
-def shiftedColorMap(cmap, start=0, midpoint=0.5, stop=1.0, name='shiftedcmap'):
- '''
- Function to offset the "center" of a colormap. Useful for
- data with a negative min and positive max and you want the
- middle of the colormap's dynamic range to be at zero.
-
- Input
- -----
- cmap : The matplotlib colormap to be altered
- start : Offset from lowest point in the colormap's range.
- Defaults to 0.0 (no lower offset). Should be between
- 0.0 and `midpoint`.
- midpoint : The new center of the colormap. Defaults to
- 0.5 (no shift). Should be between 0.0 and 1.0. In
- general, this should be 1 - vmax / (vmax + abs(vmin))
- For example if your data range from -15.0 to +5.0 and
- you want the center of the colormap at 0.0, `midpoint`
- should be set to 1 - 5/(5 + 15)) or 0.75
- stop : Offset from highest point in the colormap's range.
- Defaults to 1.0 (no upper offset). Should be between
- `midpoint` and 1.0.
- '''
- cdict = {
- 'red': [],
- 'green': [],
- 'blue': [],
- 'alpha': []
- }
-
- # regular index to compute the colors
- reg_index = np.linspace(start, stop, 257)
-
- # shifted index to match the data
- shift_index = np.hstack([
- np.linspace(0.0, midpoint, 128, endpoint=False),
- np.linspace(midpoint, 1.0, 129, endpoint=True)
- ])
-
- for ri, si in zip(reg_index, shift_index):
- r, g, b, a = cmap(ri)
-
- cdict['red'].append((si, r, r))
- cdict['green'].append((si, g, g))
- cdict['blue'].append((si, b, b))
- cdict['alpha'].append((si, a, a))
-
- newcmap = matplotlib.colors.LinearSegmentedColormap(name, cdict)
- plt.register_cmap(cmap=newcmap)
-
- return newcmap
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 23a7a7ec934799fefdc352bec6b7e81cdf94660e..b60f72a660299fc636d843842d08669b9e7b9f09 100644
--- a/experiment/meteo_france_data/scm_models_data/abstract_study.py
+++ b/experiment/meteo_france_data/scm_models_data/abstract_study.py
@@ -25,7 +25,7 @@ from experiment.meteo_france_data.scm_models_data.scm_constants import ALTITUDES
from experiment.meteo_france_data.scm_models_data.visualization.utils import get_km_formatter
from extreme_fit.function.margin_function.abstract_margin_function import \
AbstractMarginFunction
-from experiment.meteo_france_data.plot.create_shifted_cmap import create_colorbase_axis, \
+from experiment.meteo_france_data.scm_models_data.visualization.create_shifted_cmap import create_colorbase_axis, \
get_shifted_map, get_colors
from spatio_temporal_dataset.coordinates.abstract_coordinates import AbstractCoordinates
from spatio_temporal_dataset.coordinates.spatial_coordinates.abstract_spatial_coordinates import \
@@ -369,11 +369,7 @@ class AbstractStudy(object):
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:
- # mask_outside_polygon(poly_verts=l, ax=ax)
# Plot the contour of the massif
-
coords_list = list(zip(*coords_list))
ax.plot(*coords_list, color='black')
diff --git a/experiment/meteo_france_data/scm_models_data/cumulated_study.py b/experiment/meteo_france_data/scm_models_data/safran/cumulated_study.py
similarity index 100%
rename from experiment/meteo_france_data/scm_models_data/cumulated_study.py
rename to experiment/meteo_france_data/scm_models_data/safran/cumulated_study.py
diff --git a/experiment/meteo_france_data/scm_models_data/safran/safran.py b/experiment/meteo_france_data/scm_models_data/safran/safran.py
index a19b8207edaa24f9a603febf0e323cd395aacded..f2fe8f75f0505aa895fb0e517656dd469ab66989 100644
--- a/experiment/meteo_france_data/scm_models_data/safran/safran.py
+++ b/experiment/meteo_france_data/scm_models_data/safran/safran.py
@@ -3,7 +3,7 @@ import numpy as np
from experiment.meteo_france_data.scm_models_data.abstract_extended_study import AbstractExtendedStudy
from experiment.meteo_france_data.scm_models_data.abstract_study import AbstractStudy
from experiment.meteo_france_data.scm_models_data.abstract_variable import AbstractVariable
-from experiment.meteo_france_data.scm_models_data.cumulated_study import CumulatedStudy
+from experiment.meteo_france_data.scm_models_data.safran.cumulated_study import CumulatedStudy
from experiment.meteo_france_data.scm_models_data.safran.safran_variable import SafranSnowfallVariable, \
SafranRainfallVariable, SafranTemperatureVariable, SafranTotalPrecipVariable
diff --git a/experiment/meteo_france_data/plot/create_shifted_cmap.py b/experiment/meteo_france_data/scm_models_data/visualization/create_shifted_cmap.py
similarity index 58%
rename from experiment/meteo_france_data/plot/create_shifted_cmap.py
rename to experiment/meteo_france_data/scm_models_data/visualization/create_shifted_cmap.py
index 7f6fc9706d61b705c20c0833ddf5a1c723667ea2..9534f0fcaa92bfa419bc6bf530881fc0f83b719f 100644
--- a/experiment/meteo_france_data/plot/create_shifted_cmap.py
+++ b/experiment/meteo_france_data/scm_models_data/visualization/create_shifted_cmap.py
@@ -1,3 +1,4 @@
+import matplotlib
import matplotlib as mpl
import matplotlib.cm as cm
import matplotlib.colorbar as cbar
@@ -5,7 +6,6 @@ import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.axes_grid1 import make_axes_locatable
-from experiment.meteo_france_data.plot.shifted_color_map import shiftedColorMap
from extreme_fit.distribution.abstract_params import AbstractParams
@@ -66,3 +66,57 @@ def imshow_shifted(ax, gev_param_name, values, visualization_extend, mask_2D=Non
masked_array[-1, -1] = value - epsilon
# IMPORTANT: Origin for all the plots is at the bottom left corner
ax.imshow(masked_array, extent=visualization_extend, cmap=shifted_cmap, origin='lower')
+
+
+
+# from: https://stackoverflow.com/questions/7404116/defining-the-midpoint-of-a-colormap-in-matplotlib/20528097
+def shiftedColorMap(cmap, start=0, midpoint=0.5, stop=1.0, name='shiftedcmap'):
+ '''
+ Function to offset the "center" of a colormap. Useful for
+ data with a negative min and positive max and you want the
+ middle of the colormap's dynamic range to be at zero.
+
+ Input
+ -----
+ cmap : The matplotlib colormap to be altered
+ start : Offset from lowest point in the colormap's range.
+ Defaults to 0.0 (no lower offset). Should be between
+ 0.0 and `midpoint`.
+ midpoint : The new center of the colormap. Defaults to
+ 0.5 (no shift). Should be between 0.0 and 1.0. In
+ general, this should be 1 - vmax / (vmax + abs(vmin))
+ For example if your data range from -15.0 to +5.0 and
+ you want the center of the colormap at 0.0, `midpoint`
+ should be set to 1 - 5/(5 + 15)) or 0.75
+ stop : Offset from highest point in the colormap's range.
+ Defaults to 1.0 (no upper offset). Should be between
+ `midpoint` and 1.0.
+ '''
+ cdict = {
+ 'red': [],
+ 'green': [],
+ 'blue': [],
+ 'alpha': []
+ }
+
+ # regular index to compute the colors
+ reg_index = np.linspace(start, stop, 257)
+
+ # shifted index to match the data
+ shift_index = np.hstack([
+ np.linspace(0.0, midpoint, 128, endpoint=False),
+ np.linspace(midpoint, 1.0, 129, endpoint=True)
+ ])
+
+ for ri, si in zip(reg_index, shift_index):
+ r, g, b, a = cmap(ri)
+
+ cdict['red'].append((si, r, r))
+ cdict['green'].append((si, g, g))
+ cdict['blue'].append((si, b, b))
+ cdict['alpha'].append((si, a, a))
+
+ newcmap = matplotlib.colors.LinearSegmentedColormap(name, cdict)
+ plt.register_cmap(cmap=newcmap)
+
+ return newcmap
diff --git a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/__init__.py b/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/abstract_hypercube_visualizer.py b/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/abstract_hypercube_visualizer.py
deleted file mode 100644
index 30b3417d1ea334048bac50cb326bea55f8f832e3..0000000000000000000000000000000000000000
--- a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/abstract_hypercube_visualizer.py
+++ /dev/null
@@ -1,144 +0,0 @@
-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_data.scm_models_data.visualization.study_visualization.study_visualizer import \
- StudyVisualizer
-from root_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,
- nb_data_reduced_for_speed=False,
- reduce_strength_array=False,
- save_to_file=False,
- first_starting_year=None,
- last_starting_year=None,
- exact_starting_year=None,
- verbose=True,
- sigma_for_best_year=0.0):
- assert sigma_for_best_year >= 0.0
- self.sigma_for_best_year = sigma_for_best_year
- self.reduce_strength_array = reduce_strength_array
- self.verbose = verbose
- 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]
-
- if isinstance(nb_data_reduced_for_speed, bool):
- self.nb_data_for_fast_mode = 7 if nb_data_reduced_for_speed else None
- else:
- assert isinstance(nb_data_reduced_for_speed, int)
- self.nb_data_for_fast_mode = nb_data_reduced_for_speed
-
- if exact_starting_year is not None:
- assert first_starting_year is None and last_starting_year is None
- self.first_starting_year, self.last_starting_year = exact_starting_year, exact_starting_year
- else:
- default_first_starting_year, *_, default_last_starting_year = self.all_potential_starting_years
- self.first_starting_year = first_starting_year if first_starting_year is not None else default_first_starting_year
- self.last_starting_year = last_starting_year if last_starting_year is not None else default_last_starting_year
- # Load starting year
- self.starting_years = [year for year in self.all_potential_starting_years
- if self.first_starting_year <= year <= self.last_starting_year]
- if self.nb_data_for_fast_mode is not None:
- self.starting_years = self.starting_years[:self.nb_data_for_fast_mode]
- self.last_starting_year = self.starting_years[-1]
-
- if self.verbose:
- print('Hypercube with parameters:')
- print('First starting year: {}, Last starting year: {}'.format(self.first_starting_year,
- self.last_starting_year))
- print('Starting years:', self.starting_years)
- print('Trend test class:', get_display_name_from_object_type(self.trend_test_class))
-
- # Main attributes defining the hypercube
-
- @property
- def trend_test_name(self):
- return get_display_name_from_object_type(self.trend_test_class)
-
- @property
- def all_potential_starting_years(self):
- return self.study_visualizer.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_trends_spatio_temporal(self):
- return [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()]
-
- def _df_hypercube_trend_meta(self, idx) -> pd.DataFrame:
- df_spatio_temporal_trend_strength = [e[idx] for e in self.df_trends_spatio_temporal]
- return pd.concat(df_spatio_temporal_trend_strength, keys=list(self.tuple_to_study_visualizer.keys()), axis=0)
-
- @cached_property
- def df_hypercube_trend_type(self) -> pd.DataFrame:
- return self._df_hypercube_trend_meta(idx=0
- )
-
- @cached_property
- def df_hypercube_trend_slope_relative_strength(self) -> pd.DataFrame:
- return self._df_hypercube_trend_meta(idx=1)
-
- @cached_property
- def df_hypercube_trend_nllh(self) -> pd.DataFrame:
- return self._df_hypercube_trend_meta(idx=2)
-
- @cached_property
- def df_hypercube_trend_constant_quantile(self) -> pd.DataFrame:
- return self._df_hypercube_trend_meta(idx=3)
-
- @cached_property
- def df_hypercube_trend_mean_same_sign(self) -> pd.DataFrame:
- return self._df_hypercube_trend_meta(idx=4)
-
- @cached_property
- def df_hypercube_trend_variance_same_sign(self) -> pd.DataFrame:
- return self._df_hypercube_trend_meta(idx=5)
-
- # Some properties
-
- @property
- def study_title(self):
- return self.study.title
-
- def show_or_save_to_file(self, specific_title='', tight=False, dpi=None):
- 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)
- if tight:
- plt.savefig(filepath, bbox_inches='tight', pad_inches=+0.03, dpi=1000)
- elif dpi is not None:
- plt.savefig(filepath, dpi=dpi)
- else:
- plt.savefig(filepath)
- else:
- plt.show()
- plt.close()
-
- @property
- def study_visualizer(self) -> StudyVisualizer:
- return list(self.tuple_to_study_visualizer.values())[0]
-
- @property
- def study(self):
- return self.study_visualizer.study
diff --git a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/altitude_hypercube_visualizer.py b/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/altitude_hypercube_visualizer.py
deleted file mode 100644
index 52c60ce4e55feafb5f4023f0ab8eadddccb2a46d..0000000000000000000000000000000000000000
--- a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/altitude_hypercube_visualizer.py
+++ /dev/null
@@ -1,528 +0,0 @@
-import numpy as np
-import pandas as pd
-import matplotlib.pyplot as plt
-from matplotlib.ticker import ScalarFormatter
-from scipy.ndimage import gaussian_filter
-
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.abstract_hypercube_visualizer import \
- AbstractHypercubeVisualizer
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.main_study_visualizer import \
- SCM_STUDY_NAME_TO_COLOR, SCM_STUDY_NAME_TO_ABBREVIATION, SCM_STUDY_CLASS_TO_ABBREVIATION
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.study_visualizer import \
- StudyVisualizer
-from experiment.trend_analysis.univariate_test.extreme_trend_test.abstract_gev_trend_test import AbstractGevTrendTest
-from experiment.trend_analysis.univariate_test.abstract_univariate_test import AbstractUnivariateTest
-from root_utils import get_display_name_from_object_type
-
-ALTITUDES_XLABEL = 'altitudes'
-
-STARTING_YEARS_XLABEL = 'starting years'
-
-from math import log10, floor
-
-
-def round_sig(x, sig=2):
- return round(x, sig - int(floor(log10(abs(x)))) - 1)
-
-
-def make_patch_spines_invisible(ax):
- ax.set_frame_on(True)
- ax.patch.set_visible(False)
- for sp in ax.spines.values():
- sp.set_visible(False)
-
-
-class AltitudeHypercubeVisualizer(AbstractHypercubeVisualizer):
-
- @property
- def altitudes(self):
- return self.tuple_values(idx=0)
-
- @property
- def display_trend_type_to_style(self):
- return self.trend_test_class.display_trend_type_to_style()
-
- @property
- def display_trend_types(self):
- return self.display_trend_type_to_style.keys()
-
- @property
- def nb_rows(self):
- return 1
-
- def ylabel_to_series(self, reduction_function, isin_parameters=None):
- return {}
-
- def trend_type_to_series(self, reduction_function, isin_parameters=None):
- # Map each trend type to its serie with percentages
- # Define here all the trend type we might need in the results/displays
- return {trend_type: self.trend_type_reduction_series(reduction_function=reduction_function,
- df_bool=self.df_bool(trend_type, isin_parameters).copy())
- for trend_type in self.trend_types_to_process}
-
- @property
- def trend_types_to_process(self):
- return list(self.display_trend_types) + [AbstractUnivariateTest.SIGNIFICATIVE_ALL_TREND]
-
- def df_bool(self, display_trend_type, isin_parameters=None):
- return self.df_hypercube_trend_type.isin(AbstractUnivariateTest.get_real_trend_types(display_trend_type))
-
- def trend_type_reduction_series(self, reduction_function, df_bool):
- # Reduce df_bool df to a serie s_trend_type_percentage
- s_trend_type_percentage = reduction_function(df_bool)
- assert isinstance(s_trend_type_percentage, pd.Series)
- assert not isinstance(s_trend_type_percentage.index, pd.MultiIndex)
- s_trend_type_percentage *= 100
- series = [s_trend_type_percentage]
- if self.reduce_strength_array:
- # Reduce df_strength to a serie s_trend_strength
- df_strength = self.df_hypercube_trend_slope_relative_strength[df_bool]
- s_trend_strength = reduction_function(df_strength)
- df_constant = self.df_hypercube_trend_constant_quantile[df_bool]
- s_trend_constant = reduction_function(df_constant)
- series.extend([s_trend_strength, s_trend_constant])
- # Add the mean and the variance anyway
- s_trend_mean_sign = reduction_function(self.df_hypercube_trend_mean_same_sign[df_bool])
- s_trend_variance_sign = reduction_function(self.df_hypercube_trend_variance_same_sign[df_bool])
- series.extend([s_trend_mean_sign, s_trend_variance_sign])
- return series
-
- def subtitle_to_reduction_function(self, reduction_function, level=None, add_detailed_plot=False, subtitle=None):
- def reduction_function_with_level(df_bool, **kwargs):
- return reduction_function(df_bool, **kwargs) if level is None else reduction_function(df_bool, level,
- **kwargs)
-
- if subtitle is None:
- # subtitle = self.study.variable_name[:6]
- subtitle = SCM_STUDY_CLASS_TO_ABBREVIATION[type(self.study)]
- # Ensure that subtitle does not belong to this dictionary so that the plot will be normal
- assert subtitle not in SCM_STUDY_NAME_TO_COLOR
-
- return {subtitle: reduction_function_with_level}
-
- def get_title_plot(self, xlabel, ax_idx=None):
- labels = ['altitudes', 'starting years', 'massifs']
- assert xlabel in labels, xlabel
- if ax_idx == 1:
- return '% of change per year for the parameter value'
- elif ax_idx == 0:
- return '% of trend type'
- else:
- labels.remove(xlabel)
- if xlabel != 'starting years':
- labels.remove('starting years')
- common_txt = 'averaged on {}'.format(' & '.join(labels))
- common_txt += ' with any starting year between {} and {}'.format(self.first_starting_year,
- self.last_starting_year)
- return common_txt
-
- def visualize_trend_test_evolution(self, reduction_function, xlabel, xlabel_values, axes=None, marker='o',
- subtitle='', isin_parameters=None,
- plot_title=None, idx_reduction=None,
- poster_plot=False):
-
- # Plot in one graph several graph that correspond to the same trend_type
- trend_type_to_series = self.trend_type_to_series(reduction_function, isin_parameters)
- end_idx = len(list(trend_type_to_series.values())[0])
- axes_for_trend_type = axes[:end_idx]
- for ax_idx, ax in enumerate(axes_for_trend_type):
- for display_trend_type in self.display_trend_types:
- style = self.display_trend_type_to_style[display_trend_type]
- values = trend_type_to_series[display_trend_type][ax_idx]
- xlabel_values = list(values.index)
- values = list(values.values)
- ax.plot(xlabel_values, values, style + marker, label=display_trend_type)
-
- if ax_idx == 0:
- # Global information
- ax.set_ylabel(self.get_title_plot(xlabel, ax_idx=0))
- if xlabel != STARTING_YEARS_XLABEL:
- ax.set_yticks(list(range(0, 101, 20)))
- else:
- ax.set_ylabel(self.get_title_plot(xlabel, ax_idx=ax_idx))
-
- # Common function functions
- if xlabel == STARTING_YEARS_XLABEL:
- ax.set_xticks(xlabel_values[::3])
- else:
- ax.set_xticks(xlabel_values)
- ax.set_xlabel(xlabel)
- ax.grid()
- ax.legend()
- if plot_title is not None:
- ax.set_title(plot_title)
-
- # Plot other graphs where there is a single line that do not correspond to trend types
- axes_remaining = axes[end_idx:]
- ylabel_to_series = self.ylabel_to_series(reduction_function, isin_parameters)
- assert len(axes_remaining) == len(ylabel_to_series), '{}, {}'.format(len(axes_remaining), len(ylabel_to_series))
- best_year = np.nan
- for ax_idx, (ax, (ylabel, serie)) in enumerate(zip(axes_remaining, ylabel_to_series.items())):
- assert isinstance(serie, pd.Series)
- xlabel_values = list(serie.index)
- values = list(serie.values)
- smooth_values = gaussian_filter(values, self.sigma_for_best_year)
- argmax_idx = np.argmax(smooth_values)
- best_year = xlabel_values[argmax_idx]
- if plot_title is not None:
- plot_title += ' (max reached in {})'.format(best_year)
-
- if subtitle in SCM_STUDY_NAME_TO_COLOR:
- ax_reversed, color = ax.twinx(), SCM_STUDY_NAME_TO_COLOR[subtitle]
- ylabel = 'mean logLik for ' + SCM_STUDY_NAME_TO_ABBREVIATION[subtitle]
- ax.plot([], [], label=ylabel, color=color)
- linewidth = 10 if poster_plot else None
- ax_reversed.plot(xlabel_values, values, label=ylabel, color=color, linewidth=linewidth)
- if self.sigma_for_best_year > 0:
- ax_reversed.plot(xlabel_values, smooth_values, label=ylabel + ' smooth', color=color, linestyle=':',
- linewidth=linewidth)
- fontsize = 30 if poster_plot else None
- ax_reversed.set_ylabel(ylabel, color=color, fontsize=fontsize, labelpad=-20)
- ax_reversed.axvline(x=best_year, color=color, linestyle='--', linewidth=linewidth)
-
- # Offset the right spine of par2. The ticks and label have already been
- # placed on the right by twinx above.
- position = 1 + idx_reduction * 0.08
- if idx_reduction > 0:
- ax_reversed.spines["right"].set_position(("axes", position))
- # Having been created by twinx, par2 has its frame off, so the line of its
- # detached spine is invisible. First, activate the frame but make the patch
- # and spines invisible.
- make_patch_spines_invisible(ax_reversed)
- # Second, show the right spine.
- ax_reversed.spines["right"].set_visible(True)
- if poster_plot:
- # ax_reversed.yaxis.set_major_formatter(FormatStrFormatter('%.1f'))
- ax_reversed.yaxis.set_major_formatter(ScalarFormatter(useMathText=True))
- # ax_reversed.tick_params(axis='both', which='major', labelsize=15)
- ax_reversed.tick_params(axis='y', which='major', labelsize=25)
- # ax.tick_params(axis='x', which='major', labelsize=20)
- ax.tick_params(axis='x', which='major', labelsize=25)
-
- ax_reversed.yaxis.set_ticks([np.round(min(values), 1), np.round(max(values), 1)])
- else:
- ax.set_title(plot_title)
- # ax.legend()
- # Common things to all the graph
- if not poster_plot:
- ax.set_xlabel(xlabel)
- plt.setp(ax.get_yticklabels(), visible=False)
-
- specific_title = self.specific_title_trend_evolution(subtitle, xlabel, loglik_title=len(axes_remaining) > 0)
-
- # Figure title
- # specific_title += '\n'
- #
- # trend_types = [AbstractUnivariateTest.ALL_TREND,
- # AbstractUnivariateTest.SIGNIFICATIVE_ALL_TREND,
- # AbstractUnivariateTest.SIGNIFICATIVE_POSITIVE_TREND,
- # AbstractUnivariateTest.SIGNIFICATIVE_NEGATIVE_TREND]
- # series = [trend_type_to_series[trend_type][0] for trend_type in trend_types]
- # percents = [serie.sum() if xlabel == STARTING_YEARS_XLABEL else serie.mean() for serie in series]
- # percents = [np.round(p) for p in percents]
- # specific_title += 'Total ' if xlabel == STARTING_YEARS_XLABEL else 'Mean '
- # specific_title += 'all trend {}, all significative trends: {} (+:{} -{})'.format(*percents)
- if not poster_plot:
- plt.suptitle(specific_title)
-
- return specific_title, best_year
-
- def specific_title_trend_evolution(self, subtitle, xlabel, loglik_title=False):
- if loglik_title:
- specific_title = 'Mean LogLik of the non stationary model'
- else:
- specific_title = 'Evolution of {} trends'.format(subtitle)
- specific_title += ' wrt to the {}'.format(xlabel)
- if len(self.altitudes) == 1:
- specific_title += ' at altitude={}m'.format(self.altitudes[0])
- return specific_title
-
- def load_trend_test_evolution_axes(self, nb_rows):
- fig, axes = plt.subplots(nb_rows, 1, figsize=self.study_visualizer.figsize, constrained_layout=True)
- if not isinstance(axes, np.ndarray):
- axes = [axes]
- return axes
-
- def load_trend_test_evolution_axes_with_columns(self, nb_rows, nb_columns):
- fig, axes = plt.subplots(nb_rows, nb_columns, figsize=self.study_visualizer.figsize, constrained_layout=True)
- if not isinstance(axes, np.ndarray):
- axes = [axes]
- else:
- axes = axes.reshape((nb_rows * nb_columns))
- return axes
-
- def visualize_trend_test_repartition(self, reduction_function, axes=None, subtitle='', isin_parameters=None,
- plot_title=None):
-
- for i, axes_row in enumerate(axes):
- trend_type_to_serie = {k: v[i].replace(0.0, np.nan) for k, v in
- self.trend_type_to_series(reduction_function, isin_parameters).items()}
- vmax = max([s.max() for s in trend_type_to_serie.values()])
- vmin = min([s.min() for s in trend_type_to_serie.values()])
- vmax = max(vmax, 0.01)
- if vmin == vmax:
- epislon = 0.001 * vmax
- vmin -= epislon
- vmax += epislon
-
- if i == 0:
- vmin, vmax = 0, 100
- for ax, display_trend_type in zip(axes_row, self.display_trend_types):
- serie = trend_type_to_serie[display_trend_type]
- massif_to_value = dict(serie)
- cmap = self.trend_test_class.get_cmap_from_trend_type(display_trend_type)
- self.study.visualize_study(ax, massif_to_value, show=False, cmap=cmap, label=display_trend_type,
- vmax=vmax, vmin=vmin)
- if plot_title is not None:
- ax.set_title(plot_title)
- row_title = self.get_title_plot(xlabel='massifs', ax_idx=i)
- StudyVisualizer.clean_axes_write_title_on_the_left(axes_row, row_title, left_border=None)
-
- # Global information
- title = 'Repartition of {} trends (significative or not) with {}'.format(subtitle, self.trend_test_name)
- title += '\n ' + self.get_title_plot('massifs')
- plt.suptitle(title)
-
- return title
-
- def visualize_trend_test_repartition_poster(self, reduction_function, axes=None, subtitle='', isin_parameters=None,
- plot_title=None,
- poster_plot=False,
- write_text_on_massif=True,
- display_trend_color=True):
- trend_type_to_serie = {k: v[0].replace(0.0, np.nan) for k, v in
- self.trend_type_to_series(reduction_function, isin_parameters).items()}
-
- massif_to_color = {}
- add_text = self.nb_rows > 1
- massif_to_year = {}
- massif_to_strength = {}
- massif_to_constant = {}
- massif_to_mean_difference_same_sign = {}
- massif_to_variance_difference_same_sign = {}
- poster_trend_types = [AbstractUnivariateTest.SIGNIFICATIVE_POSITIVE_TREND,
- AbstractUnivariateTest.SIGNIFICATIVE_NEGATIVE_TREND,
- AbstractUnivariateTest.NEGATIVE_TREND,
- AbstractUnivariateTest.POSITIVE_TREND,
- ][:]
- for display_trend_type, style in self.display_trend_type_to_style.items():
- if display_trend_type in poster_trend_types:
- color = style[:-1]
- serie = trend_type_to_serie[display_trend_type]
- massif_to_color_for_trend_type = {k: color for k, v in dict(serie).items() if not np.isnan(v)}
- massif_to_color.update(massif_to_color_for_trend_type)
- if add_text:
- if self.reduce_strength_array:
- massif_to_value_for_trend_type = [{k: v for k, v in
- self.trend_type_to_series(reduction_function,
- isin_parameters)[
- display_trend_type][i].items()
- if k in massif_to_color_for_trend_type} for i in [1, 2]]
- massif_to_strength.update(massif_to_value_for_trend_type[0])
- massif_to_constant.update(massif_to_value_for_trend_type[1])
- mean_idx, variance_idx = 3, 4
- else:
- mean_idx, variance_idx = 1, 2
-
- massif_to_value_for_trend_type = {k: int(v) for k, v in
- self.trend_type_to_series(reduction_function,
- isin_parameters)[
- display_trend_type][3].items()
- if k in massif_to_color_for_trend_type}
- massif_to_year.update(massif_to_value_for_trend_type)
-
- # Add the mean and variance sign anyway
- massif_to_value_for_trend_type = [{k: v for k, v in
- self.trend_type_to_series(reduction_function,
- isin_parameters)[
- display_trend_type][i].items()
- if k in massif_to_color_for_trend_type} for i in
- [mean_idx, variance_idx]]
- massif_to_mean_difference_same_sign.update(massif_to_value_for_trend_type[0])
- massif_to_variance_difference_same_sign.update(massif_to_value_for_trend_type[1])
- # Compute massif to hatch boolean
- massif_name_to_hatch_boolean_list = {
- massif: [massif_to_mean_difference_same_sign[massif] == 1.0,
- massif_to_variance_difference_same_sign[massif] == 1.0]
- for massif in massif_to_color.keys()
- }
-
- # Compute massif_to_value
- if self.reduce_strength_array:
- massif_name_to_value = {m: "{} {}{}".format(
- int(massif_to_constant[m]),
- "+" if massif_to_strength[m] > 0 else "",
- round(massif_to_strength[m], 1),
- AbstractGevTrendTest.nb_years_for_quantile_evolution)
- for m in massif_to_strength}
- else:
- massif_name_to_value = {k: "$t_0=$" + str(int(v)) if display_trend_color else v for k, v in massif_to_year.items()}
-
- title = self.set_trend_test_reparition_title(subtitle, set=not poster_plot, first_title=display_trend_color)
-
- if display_trend_color:
- self.study.visualize_study(None, massif_name_to_color=massif_to_color, show=False,
- show_label=False, scaled=True, add_text=write_text_on_massif,
- massif_name_to_value=massif_name_to_value,
- fontsize=4,
- axis_off=True,
- massif_name_to_hatch_boolean_list=massif_name_to_hatch_boolean_list,
- )
- else:
- VMIN = 1957
- VMAX = 1998
- assert VMIN < self.first_starting_year
- assert VMAX > self.last_starting_year
- self.study.visualize_study(None, show=False,
- show_label=False, scaled=True, add_text=False,
- massif_name_to_value=massif_name_to_value,
- cmap=plt.cm.GnBu,
- add_colorbar=True,
- vmin=VMIN,
- vmax=VMAX)
-
-
-
-
- return title
-
- def set_trend_test_reparition_title(self, subtitle, set=True, first_title=True):
- # Global information
- title = 'Repartition of {} trends'.format(subtitle)
- if self.study.has_orientation:
- title += ' orientation {} degrees'.format(int(self.study.orientation))
- title += ' at altitude={}m \nfor the starting_year={}'.format(self.altitudes[0], self.first_starting_year)
- if len(self.starting_years) > 1:
- title += ' until starting_year={}'.format(self.last_starting_year)
- title += ' with {} test'.format(get_display_name_from_object_type(self.trend_test_class))
- if first_title:
- title += '\nEvolution of the Eurocode quantile every {} years'.format(
- AbstractGevTrendTest.nb_years_for_quantile_evolution)
- else:
- title += '\nStarting years'
- if set:
- plt.suptitle(title)
- return title
-
- def load_axes_for_trend_test_repartition(self, nb_rows, nb_columns=None):
- if nb_columns is None:
- nb_columns = len(self.display_trend_type_to_style)
- fig, axes = plt.subplots(nb_rows, nb_columns, figsize=self.study_visualizer.figsize)
- if isinstance(axes, np.ndarray):
- axes = axes.reshape((nb_rows, nb_columns))
- return axes
-
- @property
- def altitude_index_level(self):
- return 0
-
- @property
- def massif_index_level(self):
- return 1
-
- @staticmethod
- def year_reduction(df, **kwargs):
- # Take the mean with respect to all the first axis indices
- return df.mean(axis=0)
-
- def visualize_year_trend_test(self, axes=None, marker='o', add_detailed_plots=False, plot_title=None,
- isin_parameters=None,
- show_or_save_to_file=True,
- subtitle_specified=None,
- poster_plot=False):
- if axes is None:
- axes = self.load_trend_test_evolution_axes(self.nb_rows)
- else:
- assert len(axes) == self.nb_rows
-
- results = []
- for idx_reduction, (subtitle, reduction_function) in enumerate(
- self.subtitle_to_reduction_function(self.year_reduction,
- add_detailed_plot=add_detailed_plots,
- subtitle=subtitle_specified).items()):
- specific_title, best_year = self.visualize_trend_test_evolution(
- reduction_function=reduction_function,
- xlabel=STARTING_YEARS_XLABEL,
- xlabel_values=self.starting_years, axes=axes,
- marker=marker,
- subtitle=subtitle,
- isin_parameters=isin_parameters,
- plot_title=plot_title,
- idx_reduction=idx_reduction,
- poster_plot=poster_plot
- )
- results.append((specific_title, best_year, subtitle))
- if show_or_save_to_file:
- last_specific_title = results[-1][0]
- self.show_or_save_to_file(specific_title=last_specific_title,
- )
- return results
-
- @staticmethod
- def index_reduction(df, level):
- # Take the sum with respect to the years, replace any missing data with np.nan
- df = df.any(axis=1)
- # Take the mean with respect to the level of interest
- return df.mean(level=level)
-
- def visualize_altitude_trend_test(self, axes=None, marker='o', add_detailed_plots=False, plot_title=None,
- isin_parameters=None,
- show_or_save_to_file=True):
- if axes is None:
- axes = self.load_trend_test_evolution_axes(self.nb_rows)
- else:
- assert len(axes) == self.nb_rows
-
- last_title = ''
- for subtitle, reduction_function in self.subtitle_to_reduction_function(self.index_reduction,
- level=self.altitude_index_level,
- add_detailed_plot=add_detailed_plots).items():
- last_title = self.visualize_trend_test_evolution(reduction_function=reduction_function,
- xlabel=ALTITUDES_XLABEL,
- xlabel_values=self.altitudes, axes=axes, marker=marker,
- subtitle=subtitle, isin_parameters=isin_parameters,
- plot_title=plot_title)
- if show_or_save_to_file:
- self.show_or_save_to_file(specific_title=last_title)
- return last_title
-
- def visualize_massif_trend_test(self, axes=None, add_detailed_plots=False, plot_title=None,
- isin_parameters=None,
- show_or_save_to_file=True):
- if axes is None:
- axes = self.load_axes_for_trend_test_repartition(self.nb_rows)
- else:
- assert len(axes) == self.nb_rows
-
- last_title = ''
- for subtitle, reduction_function in self.subtitle_to_reduction_function(self.index_reduction,
- level=self.massif_index_level,
- add_detailed_plot=add_detailed_plots).items():
- last_title = self.visualize_trend_test_repartition(reduction_function, axes, subtitle=subtitle,
- isin_parameters=isin_parameters,
- plot_title=plot_title)
- if show_or_save_to_file:
- self.show_or_save_to_file(specific_title=last_title)
-
- return last_title
-
- def visualize_massif_trend_test_one_altitude(self, axes=None, add_detailed_plots=False, plot_title=None,
- isin_parameters=None,
- show_or_save_to_file=True,
- poster_plot=False,
- write_text_on_massif=True,
- display_trend_color=True):
- last_title = ''
- for subtitle, reduction_function in self.subtitle_to_reduction_function(self.index_reduction,
- level=self.massif_index_level,
- add_detailed_plot=add_detailed_plots).items():
- last_title = self.visualize_trend_test_repartition_poster(reduction_function, axes, subtitle=subtitle,
- isin_parameters=isin_parameters,
- plot_title=plot_title,
- poster_plot=poster_plot,
- write_text_on_massif=write_text_on_massif,
- display_trend_color=display_trend_color)
- if show_or_save_to_file:
- self.show_or_save_to_file(specific_title=last_title, dpi=1000, tight=poster_plot)
-
- return last_title
diff --git a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/altitude_hypercube_visualizer_extended.py b/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/altitude_hypercube_visualizer_extended.py
deleted file mode 100644
index 3e1607a4e43bd4e7b68cbd527704213ef6858c6f..0000000000000000000000000000000000000000
--- a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/altitude_hypercube_visualizer_extended.py
+++ /dev/null
@@ -1,148 +0,0 @@
-from experiment.meteo_france_data.scm_models_data.abstract_extended_study import AbstractExtendedStudy
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.abstract_hypercube_visualizer import \
- AbstractHypercubeVisualizer
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.altitude_hypercube_visualizer import \
- AltitudeHypercubeVisualizer
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.altitude_year_hypercube_visualizer import \
- Altitude_Hypercube_Year_Visualizer, AltitudeHypercubeVisualizerBis, AltitudeHypercubeVisualizerWithoutTrendType
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.quantity_altitude_visualizer import \
- QuantityAltitudeHypercubeVisualizer
-
-
-class AltitudeHypercubeVisualizerExtended(AltitudeHypercubeVisualizer):
-
- def df_bool(self, display_trend_type, isin_parameters=None):
- df_bool = super().df_bool(display_trend_type)
- # Slice a part of the array
- df_bool = self.isin_slicing(df_bool, isin_parameters)
- return df_bool
-
- def isin_slicing(self, df, isin_parameters):
- if isin_parameters is not None:
- assert isinstance(isin_parameters, list)
- for isin_parameter in isin_parameters:
- transpose, values, level = isin_parameter
- if transpose:
- df = df.transpose()
- ind = df.index.isin(values=values, level=level)
- res = df.loc[ind].copy()
- df = res.transpose() if transpose else res
- return df
-
- def _visualize_meta(self, visualization_function, loading_function, name_to_isin_parameters=None,
- multiplication_factor_column=None, add_detailed_plot=False):
- assert name_to_isin_parameters is not None, 'this method should not be called directly'
-
- if multiplication_factor_column is None:
- multiplication_factor_row = len(name_to_isin_parameters)
- all_axes = loading_function(self.nb_rows * multiplication_factor_row)
- multiplication_factor = multiplication_factor_row
- else:
- multiplication_factor_row = len(name_to_isin_parameters) // multiplication_factor_column
- multiplication_factor = multiplication_factor_row * multiplication_factor_column
- all_axes = loading_function(self.nb_rows * multiplication_factor_row, multiplication_factor_column)
- specific_title = ''
- for j, (name, isin_parameters) in enumerate(name_to_isin_parameters.items()):
- axes = all_axes[j::multiplication_factor]
- specific_title = visualization_function(axes, plot_title=name,
- isin_parameters=isin_parameters,
- show_or_save_to_file=False,
- add_detailed_plots=add_detailed_plot)
- self.show_or_save_to_file(specific_title=specific_title)
-
- # Altitude trends
-
- def _visualize_altitude_trend_test(self, name_to_isin_parameters=None):
- return self._visualize_meta(visualization_function=self.visualize_altitude_trend_test,
- loading_function=self.load_trend_test_evolution_axes,
- name_to_isin_parameters=name_to_isin_parameters)
-
- def visualize_altitute_trend_test_by_regions(self):
- return self._visualize_altitude_trend_test(name_to_isin_parameters=self.region_name_to_isin_parameters)
-
- @property
- def region_name_to_isin_parameters(self):
- return {region_name: [(False, values, self.massif_index_level)]
- for region_name, values in AbstractExtendedStudy.region_name_to_massif_names.items()}
-
- # Massif trends
-
- def _visualize_massif_trend_test(self, name_to_isin_parameters=None):
- return self._visualize_meta(visualization_function=self.visualize_massif_trend_test,
- loading_function=self.load_axes_for_trend_test_repartition,
- name_to_isin_parameters=name_to_isin_parameters)
-
- def visualize_massif_trend_test_by_altitudes(self):
- return self._visualize_massif_trend_test(name_to_isin_parameters=self.altitude_band_name_to_isin_parameters)
-
- @property
- def altitude_band_name_to_values(self):
- return {
- '900m <= alti <= 3000m': self.altitudes,
- '900m <= alti <= 1800m': [900, 1200, 1500, 1800],
- '2100m <= alti <= 3000m': [2100, 2400, 2700, 3000],
- }
-
- # altitude_band = 1000
- # group_idxs = [a // altitude_band for a in self.altitudes]
- # altitude_band_name_to_values = {'All altitudes': self.altitudes}
- # for group_idx in set(group_idxs):
- # values = [a for a, i in zip(self.altitudes, group_idxs) if i == group_idx]
- # altitude_band_name = '{}m <= altitude <={}m'.format(group_idx * altitude_band,
- # (group_idx + 1) * altitude_band)
- # altitude_band_name_to_values[altitude_band_name] = values
- # return altitude_band_name_to_values
-
- @property
- def altitude_band_name_to_isin_parameters(self):
- return {altitude_band_name: [(False, values, self.altitude_index_level)]
- for altitude_band_name, values in self.altitude_band_name_to_values.items()}
-
- # Year trends
-
- @property
- def massif_name_and_altitude_band_name_to_isin_parameters(self):
- d = {}
- for massif_name, isin_parameters1 in self.region_name_to_isin_parameters.items():
- for altitude_band_name, isin_parameters2 in self.altitude_band_name_to_isin_parameters.items():
- name = massif_name + ' ' + altitude_band_name
- isin_parameters = isin_parameters1 + isin_parameters2
- d[name] = isin_parameters
- return d
-
- def vsualize_year_trend_by_regions_and_altitudes(self, add_detailed_plot=False):
- return self._visualize_meta(visualization_function=self.visualize_year_trend_test,
- loading_function=self.load_trend_test_evolution_axes_with_columns,
- name_to_isin_parameters=self.massif_name_and_altitude_band_name_to_isin_parameters,
- multiplication_factor_column=len(self.altitude_band_name_to_isin_parameters),
- add_detailed_plot=add_detailed_plot)
-
-
-class AltitudeHypercubeVisualizerWithoutTrendExtended(AltitudeHypercubeVisualizerExtended,
- AltitudeHypercubeVisualizerWithoutTrendType):
-
- def df_loglikelihood(self, isin_parameters=None):
- df = super().df_loglikelihood()
- df = self.isin_slicing(df=df, isin_parameters=isin_parameters)
- return df
-
-
-# Extension
-
-class AltitudeHypercubeVisualizerBisExtended(AltitudeHypercubeVisualizerExtended, AltitudeHypercubeVisualizerBis):
- pass
-
-
-class AltitudeYearHypercubeVisualizerExtended(AltitudeHypercubeVisualizerExtended, Altitude_Hypercube_Year_Visualizer):
- pass
-
-
-# Quantity hypercube
-
-class QuantityHypercubeWithoutTrend(AltitudeHypercubeVisualizerWithoutTrendType, QuantityAltitudeHypercubeVisualizer):
- pass
-
-
-class QuantityHypercubeWithoutTrendExtended(AltitudeHypercubeVisualizerWithoutTrendExtended,
- QuantityHypercubeWithoutTrend):
- pass
diff --git a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/altitude_year_hypercube_visualizer.py b/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/altitude_year_hypercube_visualizer.py
deleted file mode 100644
index 8b0ed5161c57826f40c923127f1ce067e717710d..0000000000000000000000000000000000000000
--- a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/altitude_year_hypercube_visualizer.py
+++ /dev/null
@@ -1,52 +0,0 @@
-import numpy as np
-
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.altitude_hypercube_visualizer import \
- AltitudeHypercubeVisualizer
-
-
-class AltitudeHypercubeVisualizerWithoutTrendType(AltitudeHypercubeVisualizer):
-
- def trend_type_to_series(self, reduction_function, isin_parameters=None):
- return {trend_type: [] for trend_type in self.trend_types_to_process}
-
- def df_loglikelihood(self, isin_parameters=None):
- return -self.df_hypercube_trend_nllh
-
- def ylabel_to_series(self, reduction_function, isin_parameters=None):
- return {'mean LogLik': reduction_function(self.df_loglikelihood(isin_parameters=isin_parameters))}
-
-
-class AltitudeHypercubeVisualizerBis(AltitudeHypercubeVisualizer):
-
- @staticmethod
- def index_reduction(df, level, **kwargs):
- replace_zero_with_nan = kwargs.get('year_visualization') is not None
- # Take the sum with respect to the years, replace any missing data with np.nan
- if replace_zero_with_nan:
- df = df.sum(axis=1).replace(0.0, np.nan)
- else:
- df = df.sum(axis=1)
- # Take the mean with respect to the level of interest
- return df.mean(level=level)
-
-
-class Altitude_Hypercube_Year_Visualizer(AltitudeHypercubeVisualizerBis):
-
- def get_title_plot(self, xlabel, ax_idx=None):
- if ax_idx == self.nb_rows - 1:
- return 'mean starting year'
- return super().get_title_plot(xlabel, ax_idx)
-
- @property
- def nb_rows(self):
- return super().nb_rows + 1
-
- def trend_type_reduction_series(self, reduction_function, df_bool):
- series = super().trend_type_reduction_series(reduction_function, df_bool)
- # Create df argmax
- df = df_bool.copy()
- df = (df * df.columns)[df_bool]
- # Reduce and append
- serie = reduction_function(df, year_visualization=True)
- series.append(serie)
- return series
diff --git a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/main_files/__init__.py b/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/main_files/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/main_files/main_fast_hypercube_one_altitudes.py b/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/main_files/main_fast_hypercube_one_altitudes.py
deleted file mode 100644
index bd461db47012ab2142b0147e853e20e732674e6f..0000000000000000000000000000000000000000
--- a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/main_files/main_fast_hypercube_one_altitudes.py
+++ /dev/null
@@ -1,65 +0,0 @@
-import time
-
-from experiment.meteo_france_data.scm_models_data.safran.safran import SafranSnowfall
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.altitude_hypercube_visualizer_extended import \
- AltitudeHypercubeVisualizerBisExtended, QuantityHypercubeWithoutTrend
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.utils_hypercube import \
- load_altitude_visualizer, load_quantity_visualizer
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.main_study_visualizer import \
- SCM_STUDIES
-from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_one_parameter import GevLocationTrendTest
-
-
-def get_fast_parameters(altitude=1800):
- save_to_file = False
- only_first_one = False
- nb_data_reduced_for_speed = 4
- altitudes = [altitude]
- last_starting_year = None
- trend_test_class = GevLocationTrendTest
- return altitudes, last_starting_year, nb_data_reduced_for_speed, only_first_one, save_to_file, trend_test_class
-
-
-def get_fast_altitude_visualizer(altitude_hypercube_class, altitude=1800, study_class=SafranSnowfall, exact_year=None):
- altitudes, last_starting_year, nb_data_reduced_for_speed, only_first_one, save_to_file, trend_test_class = get_fast_parameters(altitude=altitude)
- visualizer = load_altitude_visualizer(altitude_hypercube_class, altitudes, last_starting_year,
- nb_data_reduced_for_speed, only_first_one, save_to_file, [study_class],
- trend_test_class, exact_starting_year=exact_year)
- return visualizer
-
-
-def get_fast_quantity_visualizer(quantity_hypercube_class, altitude=1800, study_classes=None):
- altitudes, last_starting_year, nb_data_reduced_for_speed, only_first_one, save_to_file, trend_test_class = get_fast_parameters(altitude=altitude)
- if study_classes is None:
- study_classes = SCM_STUDIES[:2]
- visualizer = load_quantity_visualizer(quantity_hypercube_class, altitudes, last_starting_year, nb_data_reduced_for_speed, only_first_one,
- save_to_file, study_classes, trend_test_class)
- return visualizer
-
-
-def main_mean_log_likelihood_poster_1():
- # Simply the main graph
- res = get_fast_quantity_visualizer(QuantityHypercubeWithoutTrend).visualize_year_trend_test(add_detailed_plots=True, poster_plot=True)
- # get_fast_quantity_visualizer(QuantityHypercubeWithoutTrendExtended).vsualize_year_trend_by_regions_and_altitudes(
- # add_detailed_plot=True)
- # get_fast_altitude_visualizer(AltitudeHypercubeVisualizerWithoutTrendExtended).vsualize_year_trend_by_regions_and_altitudes()
-
-
-def main_percentage_trend_poster_2():
- visualizer = get_fast_altitude_visualizer(AltitudeHypercubeVisualizerBisExtended, exact_year=1958)
- # visualizer.vsualize_year_trend_by_regions_and_altitudes()
- # visualizer.visualize_massif_trend_test_by_altitudes()
- visualizer.visualize_massif_trend_test_one_altitude()
- # visualizer.visualize_altitute_trend_test_by_regions()
-
-
-def main_run():
- main_mean_log_likelihood_poster_1()
- # main_percentage_trend_poster_2()
-
-
-if __name__ == '__main__':
- start = time.time()
- main_run()
- duration = time.time() - start
- print('Full run took {}s'.format(round(duration, 1)))
diff --git a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/main_files/main_fast_hypercube_several_altitudes.py b/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/main_files/main_fast_hypercube_several_altitudes.py
deleted file mode 100644
index d29f20a20128453559ecd5f71e822dd59050c2cd..0000000000000000000000000000000000000000
--- a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/main_files/main_fast_hypercube_several_altitudes.py
+++ /dev/null
@@ -1,66 +0,0 @@
-import time
-
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.altitude_hypercube_visualizer_extended import \
- AltitudeHypercubeVisualizerBisExtended, QuantityHypercubeWithoutTrend
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.utils_hypercube import \
- load_altitude_visualizer, load_quantity_visualizer
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.main_study_visualizer import \
- ALL_ALTITUDES, SCM_STUDIES
-from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_one_parameter import GevLocationTrendTest
-
-
-def get_fast_parameters(altitude=None):
- save_to_file = False
- only_first_one = False
- nb_data_reduced_for_speed = 4
- if altitude is not None:
- altitudes = [altitude]
- else:
- altitudes = [ALL_ALTITUDES[3], ALL_ALTITUDES[-7]]
- last_starting_year = None
- trend_test_class = GevLocationTrendTest
- return altitudes, last_starting_year, nb_data_reduced_for_speed, only_first_one, save_to_file, trend_test_class
-
-
-def get_fast_altitude_visualizer(altitude_hypercube_class):
- altitudes, last_starting_year, nb_data_reduced_for_speed, only_first_one, save_to_file, trend_test_class = get_fast_parameters()
- study_classes = SCM_STUDIES[:1]
- visualizer = load_altitude_visualizer(altitude_hypercube_class, altitudes, last_starting_year,
- nb_data_reduced_for_speed, only_first_one, save_to_file, study_classes,
- trend_test_class)
- return visualizer
-
-
-def get_fast_quantity_visualizer(quantity_hypercube_class):
- altitudes, last_starting_year, nb_data_reduced_for_speed, only_first_one, save_to_file, trend_test_class = get_fast_parameters()
- study_classes = SCM_STUDIES[:2]
- visualizer = load_quantity_visualizer(quantity_hypercube_class, altitudes, last_starting_year, nb_data_reduced_for_speed, only_first_one,
- save_to_file, study_classes, trend_test_class)
- return visualizer
-
-
-def main_mean_log_likelihood():
- # Simply the main graph
- get_fast_quantity_visualizer(QuantityHypercubeWithoutTrend).visualize_year_trend_test(add_detailed_plots=True)
- # get_fast_quantity_visualizer(QuantityHypercubeWithoutTrendExtended).vsualize_year_trend_by_regions_and_altitudes(
- # add_detailed_plot=True)
- # get_fast_altitude_visualizer(AltitudeHypercubeVisualizerWithoutTrendExtended).vsualize_year_trend_by_regions_and_altitudes()
-
-
-def main_percentage_trend():
- visualizer = get_fast_altitude_visualizer(AltitudeHypercubeVisualizerBisExtended)
- visualizer.vsualize_year_trend_by_regions_and_altitudes()
- visualizer.visualize_massif_trend_test_by_altitudes()
- visualizer.visualize_altitute_trend_test_by_regions()
-
-
-def main_run():
- main_mean_log_likelihood()
- # main_percentage_trend()
-
-
-if __name__ == '__main__':
- start = time.time()
- main_run()
- duration = time.time() - start
- print('Full run took {}s'.format(round(duration, 1)))
diff --git a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/main_files/main_full_hypercube.py b/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/main_files/main_full_hypercube.py
deleted file mode 100644
index 679e5d751a241d6be7683653683b8cb5c090cc99..0000000000000000000000000000000000000000
--- a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/main_files/main_full_hypercube.py
+++ /dev/null
@@ -1,75 +0,0 @@
-import time
-
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.altitude_hypercube_visualizer_extended import \
- AltitudeHypercubeVisualizerBisExtended, QuantityHypercubeWithoutTrend
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.utils_hypercube import \
- load_altitude_visualizer, load_quantity_visualizer
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.main_study_visualizer import \
- ALL_ALTITUDES, SCM_STUDIES
-from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_one_parameter import GevLocationTrendTest
-
-
-def get_full_parameters(altitude=None, offset_starting_year=10):
- save_to_file = True
- only_first_one = False
- nb_data_reduced_for_speed = False
- if altitude is not None:
- altitudes = [altitude]
- else:
- altitudes = ALL_ALTITUDES[3:-6]
- first_starting_year = 1959
- last_starting_year = 2019 - offset_starting_year
- trend_test_class = GevLocationTrendTest
- return altitudes, first_starting_year, last_starting_year, nb_data_reduced_for_speed, only_first_one, save_to_file, trend_test_class
-
-
-def get_full_altitude_visualizer(altitude_hypercube_class, study_classes, exact_starting_year=None, altitude=None):
- altitudes, first_starting_year, last_starting_year, nb_data_reduced_for_speed, only_first_one, save_to_file, trend_test_class = get_full_parameters(altitude=altitude)
- if exact_starting_year is not None:
- last_starting_year = None
- visualizer = load_altitude_visualizer(altitude_hypercube_class, altitudes, last_starting_year,
- nb_data_reduced_for_speed, only_first_one, save_to_file, study_classes,
- trend_test_class, exact_starting_year=exact_starting_year, first_starting_year=first_starting_year)
- return visualizer
-
-
-def get_full_quantity_visualizer(quantity_hypercube_class, altitude=None, study_classes=None):
- altitudes, first_starting_year, last_starting_year, nb_data_reduced_for_speed, only_first_one, save_to_file, trend_test_class = get_full_parameters(altitude=altitude)
- if study_classes is None:
- study_classes = SCM_STUDIES[:3]
- visualizer = load_quantity_visualizer(quantity_hypercube_class, altitudes, last_starting_year,
- nb_data_reduced_for_speed, only_first_one,
- save_to_file, study_classes, trend_test_class)
- return visualizer
-
-
-def main_mean_log_likelihood():
- # Main plot
- get_full_quantity_visualizer(QuantityHypercubeWithoutTrend).visualize_year_trend_test(add_detailed_plots=True)
- # Detailed plot
- # get_full_quantity_visualizer(QuantityHypercubeWithoutTrendExtended).vsualize_year_trend_by_regions_and_altitudes(
- # add_detailed_plot=True)
-
-
- # get_full_altitude_visualizer(AltitudeHypercubeVisualizerWithoutTrendExtended).vsualize_year_trend_by_regions_and_altitudes()
-
-
-def main_percentage_trend():
- for study_class in SCM_STUDIES:
- study_classees = [study_class]
- visualizer = get_full_altitude_visualizer(AltitudeHypercubeVisualizerBisExtended, exact_starting_year=1981,
- study_classes=study_classees)
- visualizer.visualize_massif_trend_test_by_altitudes()
- visualizer.visualize_altitute_trend_test_by_regions()
-
-
-def main_run():
- main_mean_log_likelihood()
- # main_percentage_trend()
-
-
-if __name__ == '__main__':
- start = time.time()
- main_run()
- duration = time.time() - start
- print('Full run took {}s'.format(round(duration, 1)))
diff --git a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/main_files/main_poster_IMSC2019.py b/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/main_files/main_poster_IMSC2019.py
deleted file mode 100644
index 011477f7efff572b3f60859ccaf1f8158e33d272..0000000000000000000000000000000000000000
--- a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/main_files/main_poster_IMSC2019.py
+++ /dev/null
@@ -1,65 +0,0 @@
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.altitude_hypercube_visualizer_extended import \
- QuantityHypercubeWithoutTrend, AltitudeHypercubeVisualizerBisExtended, \
- AltitudeHypercubeVisualizerWithoutTrendExtended
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.main_files.main_fast_hypercube_one_altitudes import \
- get_fast_parameters, get_fast_quantity_visualizer, get_fast_altitude_visualizer
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.main_files.main_full_hypercube import \
- get_full_quantity_visualizer, get_full_altitude_visualizer
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.utils_hypercube import \
- load_altitude_visualizer
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.main_study_visualizer import \
- SCM_STUDIES, altitude_massif_name_and_study_class_for_poster, SCM_STUDIES_NAMES, SCM_STUDY_NAME_TO_SCM_STUDY
-from root_utils import get_display_name_from_object_type
-
-POSTER_ALTITUDES = [900, 1800, 2700]
-
-
-def fast_poster():
- for altitude in POSTER_ALTITUDES[:1]:
- study_classes = SCM_STUDIES[:2]
- # The QuantityHypercubeWithoutTrend object is used to have one single plot with all the results
- results = get_fast_quantity_visualizer(QuantityHypercubeWithoutTrend,
- altitude=altitude,
- study_classes=study_classes).visualize_year_trend_test(
- add_detailed_plots=True)
- study_class_to_year = dict(zip(study_classes, [t[1] for t in results]))
- for study_class, exact_year in study_class_to_year.items():
- altitudes, last_starting_year, nb_data_reduced_for_speed, only_first_one, save_to_file, trend_test_class = get_fast_parameters(
- altitude=altitude)
- spatial_visualizer = load_altitude_visualizer(AltitudeHypercubeVisualizerBisExtended, altitudes,
- last_starting_year,
- nb_data_reduced_for_speed, only_first_one, save_to_file,
- [study_class],
- trend_test_class,
- exact_starting_year=exact_year)
- spatial_visualizer.visualize_massif_trend_test_one_altitude()
-
-
-def full_poster():
- for altitude in POSTER_ALTITUDES[:]:
- study_classes = SCM_STUDIES[:]
- visualizer = get_full_quantity_visualizer(QuantityHypercubeWithoutTrend, altitude=altitude,
- study_classes=study_classes)
- results = visualizer.visualize_year_trend_test(
- add_detailed_plots=True)
- study_name_to_year = dict(zip(visualizer.quantities, [t[1] for t in results]))
- for study_name, exact_year in study_name_to_year.items():
- print(study_name, exact_year)
- study_class = SCM_STUDY_NAME_TO_SCM_STUDY[study_name]
- spatial_visualizer = get_full_altitude_visualizer(AltitudeHypercubeVisualizerBisExtended, [study_class],
- exact_starting_year=exact_year, altitude=altitude)
- spatial_visualizer.visualize_massif_trend_test_one_altitude()
-
-
-def example_for_the_starting_years():
- for altitude, massif_name, study_class in altitude_massif_name_and_study_class_for_poster[:]:
- visualizer = get_full_altitude_visualizer(AltitudeHypercubeVisualizerWithoutTrendExtended, altitude=altitude,
- study_classes=[study_class])
- isin_parameters = [(False, [massif_name], visualizer.massif_index_level)]
- visualizer.visualize_year_trend_test(isin_parameters=isin_parameters,
- subtitle_specified=get_display_name_from_object_type(study_class))
-
-
-if __name__ == '__main__':
- # full_poster()
- example_for_the_starting_years()
diff --git a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/quantity_altitude_visualizer.py b/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/quantity_altitude_visualizer.py
deleted file mode 100644
index d668b5c551e55cbad7ebc102949234e1ffbee3e0..0000000000000000000000000000000000000000
--- a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/quantity_altitude_visualizer.py
+++ /dev/null
@@ -1,52 +0,0 @@
-from collections import OrderedDict
-
-import pandas as pd
-
-from experiment.meteo_france_data.scm_models_data.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=None):
- def get_function_from_tuple(tuple_for_axis_0):
- def f(df: pd.DataFrame):
- # Loc with a tuple with respect the axis 0
- df = df.loc[tuple_for_axis_0, :].copy()
- # Apply the reduction function
- s = reduction_function(df) if level is None else reduction_function(df, level - 1)
- return s
- return f
-
- # Add the detailed plot, taken by loc with respect to the first index
- subtitle_to_reduction_function = OrderedDict()
- 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)
- # Add the super plot at the last rank
- subtitle_to_reduction_function.update(super().subtitle_to_reduction_function(reduction_function,
- level, add_detailed_plot,
- 'global'))
-
- 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_data/scm_models_data/visualization/hypercube_visualization/utils_hypercube.py b/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/utils_hypercube.py
deleted file mode 100644
index 5b7fbcb94e2986f316f81c40743ee36570f67099..0000000000000000000000000000000000000000
--- a/experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/utils_hypercube.py
+++ /dev/null
@@ -1,54 +0,0 @@
-from collections import OrderedDict
-from itertools import product
-
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.altitude_hypercube_visualizer import \
- AltitudeHypercubeVisualizer
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.quantity_altitude_visualizer import \
- QuantityAltitudeHypercubeVisualizer
-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 root_utils import get_display_name_from_object_type
-
-
-def load_quantity_visualizer(quantity_hypercube_class, altitudes, last_starting_year, nb_data_reduced_for_speed,
- only_first_one,
- save_to_file, study_classes, trend_test_class):
- visualizers = [StudyVisualizer(study, temporal_non_stationarity=True, verbose=False, multiprocessing=True)
- for study in study_iterator_global(study_classes=study_classes, only_first_one=only_first_one,
- altitudes=altitudes)]
- study_classes_str = [get_display_name_from_object_type(c) for c in study_classes]
- quantity_altitude_tuples = list(product(study_classes_str, altitudes))
- quantity_altitude_to_visualizer = OrderedDict(zip(quantity_altitude_tuples, visualizers))
- visualizer = quantity_hypercube_class(quantity_altitude_to_visualizer,
- save_to_file=save_to_file,
- trend_test_class=trend_test_class,
- nb_data_reduced_for_speed=nb_data_reduced_for_speed,
- last_starting_year=last_starting_year)
- assert isinstance(visualizer, QuantityAltitudeHypercubeVisualizer)
- return visualizer
-
-
-def load_altitude_visualizer(altitude_hypercube_class, altitudes, last_starting_year, nb_data_reduced_for_speed,
- only_first_one, save_to_file, study_classes, trend_test_class
- , exact_starting_year=None, first_starting_year=1958,
- orientations=None,
- verbose=True):
- visualizers = [StudyVisualizer(study, temporal_non_stationarity=True, verbose=False, multiprocessing=True)
- for study in study_iterator_global(study_classes=study_classes, only_first_one=only_first_one,
- altitudes=altitudes,
- orientations=orientations,
- verbose=verbose)]
- altitude_to_visualizer = OrderedDict(zip(altitudes, visualizers))
- visualizer = altitude_hypercube_class(altitude_to_visualizer,
- save_to_file=save_to_file,
- trend_test_class=trend_test_class,
- nb_data_reduced_for_speed=nb_data_reduced_for_speed,
- last_starting_year=last_starting_year,
- first_starting_year=first_starting_year,
- exact_starting_year=exact_starting_year,
- verbose=verbose,
- )
- assert isinstance(visualizer, AltitudeHypercubeVisualizer)
- return visualizer
diff --git a/experiment/meteo_france_data/scm_models_data/visualization/study_visualization/main_study_visualizer.py b/experiment/meteo_france_data/scm_models_data/visualization/main_study_visualizer.py
similarity index 99%
rename from experiment/meteo_france_data/scm_models_data/visualization/study_visualization/main_study_visualizer.py
rename to experiment/meteo_france_data/scm_models_data/visualization/main_study_visualizer.py
index 2629457be4eebffa0d47b39b49d9f7ff03ccc613..b8d9cc8ba70a90df8d363c7ef7a1112a99c7178b 100644
--- a/experiment/meteo_france_data/scm_models_data/visualization/study_visualization/main_study_visualizer.py
+++ b/experiment/meteo_france_data/scm_models_data/visualization/main_study_visualizer.py
@@ -2,7 +2,7 @@ import time
from typing import List
from experiment.meteo_france_data.scm_models_data.crocus.crocus_variables import CrocusDensityVariable
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.study_visualizer import \
+from experiment.meteo_france_data.scm_models_data.visualization.study_visualizer import \
StudyVisualizer
from papers.exceeding_snow_loads.discussion_data_comparison_with_eurocode.crocus_study_comparison_with_eurocode import \
CrocusDifferenceSnowLoad, \
diff --git a/experiment/meteo_france_data/scm_models_data/visualization/studies_visualization/__init__.py b/experiment/meteo_france_data/scm_models_data/visualization/studies_visualization/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/experiment/meteo_france_data/scm_models_data/visualization/studies_visualization/main_studies_visualizer.py b/experiment/meteo_france_data/scm_models_data/visualization/studies_visualization/main_studies_visualizer.py
deleted file mode 100644
index 4b6eb7e46ea88f12f26901c47435a0f277844d1d..0000000000000000000000000000000000000000
--- a/experiment/meteo_france_data/scm_models_data/visualization/studies_visualization/main_studies_visualizer.py
+++ /dev/null
@@ -1,68 +0,0 @@
-import time
-from experiment.trend_analysis.abstract_score import MannKendall, WeigthedScore, MeanScore, MedianScore
-from experiment.trend_analysis.univariate_test.extreme_trend_test.abstract_gev_trend_test import GevLocationChangePointTest, \
- GevScaleChangePointTest, GevShapeChangePointTest
-from experiment.trend_analysis.univariate_test.abstract_univariate_test import MannKendallTrendTest
-from experiment.meteo_france_data.scm_models_data.safran.safran import ExtendedSafranPrecipitation
-from experiment.meteo_france_data.scm_models_data.visualization import Studies
-from experiment.meteo_france_data.scm_models_data.visualization import StudiesVisualizer, \
- AltitudeVisualizer
-from experiment.meteo_france_data.scm_models_data.visualization import ALL_ALTITUDES, \
- study_iterator_global, SCM_STUDIES
-
-from experiment.meteo_france_data.scm_models_data.visualization import StudyVisualizer
-from collections import OrderedDict
-
-
-def normal_visualization():
- for study_type in [ExtendedSafranPrecipitation]:
- extended_studies = Studies(study_type)
- studies_visualizer = StudiesVisualizer(extended_studies)
- studies_visualizer.mean_as_a_function_of_altitude(region_only=True)
-
-
-def altitude_trends():
- save_to_file = True
- only_first_one = False
- # altitudes that have 20 massifs at least
- altitudes = ALL_ALTITUDES[3:-6]
- # altitudes = ALL_ALTITUDES[:2]
- for study_class in SCM_STUDIES[:]:
- for score_class in [MedianScore, MeanScore, MannKendall, WeigthedScore]:
- visualizers = [StudyVisualizer(study, temporal_non_stationarity=True, verbose=True,
- score_class=score_class)
- for study in
- study_iterator_global(study_classes=[study_class], only_first_one=only_first_one,
- altitudes=altitudes)]
- altitude_to_visualizer = OrderedDict(zip(altitudes, visualizers))
- visualizer = AltitudeVisualizer(altitude_to_visualizer, multiprocessing=False, save_to_file=save_to_file)
- visualizer.negative_trend_percentages_evolution(reverse=True)
-
-
-def altitude_trends_significant():
- save_to_file = False
- only_first_one = False
- # altitudes that have 20 massifs at least
- altitudes = ALL_ALTITUDES[3:-6]
- # altitudes = ALL_ALTITUDES[3:5]
- altitudes = ALL_ALTITUDES[2:4]
- for study_class in SCM_STUDIES[:1]:
- trend_test_classes = [MannKendallTrendTest, GevLocationChangePointTest, GevScaleChangePointTest, GevShapeChangePointTest][:1]
- visualizers = [StudyVisualizer(study, temporal_non_stationarity=True, verbose=False)
- for study in study_iterator_global(study_classes=[study_class], only_first_one=only_first_one,
- altitudes=altitudes)]
- altitude_to_visualizer = OrderedDict(zip(altitudes, visualizers))
- visualizer = AltitudeVisualizer(altitude_to_visualizer, multiprocessing=False, save_to_file=save_to_file)
- visualizer.trend_tests_percentage_evolution_with_altitude(trend_test_classes, starting_year_to_weights=None)
-
-
-def main_run():
- # altitude_trends()
- altitude_trends_significant()
-
-
-if __name__ == '__main__':
- start = time.time()
- main_run()
- duration = time.time() - start
- print('Full run took {}s'.format(round(duration, 1)))
diff --git a/experiment/meteo_france_data/scm_models_data/visualization/studies_visualization/studies.py b/experiment/meteo_france_data/scm_models_data/visualization/studies_visualization/studies.py
deleted file mode 100644
index d956246d1ba7b431ac082493fd77afdcdbaa5f01..0000000000000000000000000000000000000000
--- a/experiment/meteo_france_data/scm_models_data/visualization/studies_visualization/studies.py
+++ /dev/null
@@ -1,29 +0,0 @@
-from collections import OrderedDict
-from typing import Dict
-
-from experiment.meteo_france_data.scm_models_data.abstract_study import AbstractStudy
-from experiment.meteo_france_data.scm_models_data.scm_constants import ALTITUDES
-
-
-class Studies(object):
- """Object that will handle studies of the same study type (it could be Safran for instance)
- at several altitudes"""
-
- def __init__(self, study_type, altitude_list=None) -> None:
- # Load altitude_list attribute
- if altitude_list is None:
- altitude_list = ALTITUDES
- else:
- assert isinstance(altitude_list, list)
- assert len(altitude_list) > 0
- assert all([altitudes in ALTITUDES for altitudes in altitude_list])
- altitude_list = sorted(altitude_list)
- self.altitude_list = altitude_list
- # Load altitude_to_study attribute
- self.altitude_to_study = OrderedDict() # type: Dict[int, AbstractStudy]
- for altitude in self.altitude_list:
- self.altitude_to_study[altitude] = study_type(altitude=altitude)
-
- @property
- def first_study(self):
- return self.altitude_to_study[self.altitude_list[0]]
diff --git a/experiment/meteo_france_data/scm_models_data/visualization/studies_visualization/studies_visualizer.py b/experiment/meteo_france_data/scm_models_data/visualization/studies_visualization/studies_visualizer.py
deleted file mode 100644
index f553d1ac624b5194fe5b6424b1acf76e3cb47510..0000000000000000000000000000000000000000
--- a/experiment/meteo_france_data/scm_models_data/visualization/studies_visualization/studies_visualizer.py
+++ /dev/null
@@ -1,250 +0,0 @@
-from collections import OrderedDict, Counter
-import os
-import os.path as op
-from multiprocessing.dummy import Pool
-from typing import Dict
-
-import numpy as np
-import pandas as pd
-import matplotlib.pyplot as plt
-from matplotlib.lines import Line2D
-
-from experiment.meteo_france_data.scm_models_data.abstract_extended_study import AbstractExtendedStudy
-from experiment.meteo_france_data.scm_models_data.visualization.studies_visualization.studies import Studies
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.study_visualizer import \
- StudyVisualizer
-from experiment.trend_analysis.univariate_test.abstract_univariate_test import AbstractUnivariateTest
-from experiment.meteo_france_data.scm_models_data.visualization.utils import plot_df
-from root_utils import cached_property, get_display_name_from_object_type, VERSION_TIME
-
-
-class StudiesVisualizer(object):
-
- def __init__(self, studies: Studies) -> None:
- self.studies = studies
-
- @property
- def first_study(self):
- return self.studies.first_study
-
- def mean_as_a_function_of_altitude(self, region_only=False):
- # Load the massif names to display
- if region_only:
- assert isinstance(self.first_study, AbstractExtendedStudy)
- massif_names = self.first_study.region_names
- else:
- massif_names = self.first_study.study_massif_names
- # Load the dictionary that maps each massif_name to its corresponding time series
- mean_series = []
- for study in self.studies.altitude_to_study.values():
- mean_serie = study.df_annual_total.loc[:, massif_names].mean(axis=0)
- mean_series.append(mean_serie)
- df_mean = pd.concat(mean_series, axis=1) # type: pd.DataFrame
- df_mean.columns = self.studies.altitude_list
- plot_df(df_mean)
-
-
-def get_percentages(v):
- return v.percentages_of_negative_trends()[0]
-
-
-class AltitudeVisualizer(object):
-
- def __init__(self, altitude_to_study_visualizer: Dict[int, StudyVisualizer], multiprocessing=False,
- save_to_file=False):
- self.save_to_file = save_to_file
- self.multiprocessing = multiprocessing
- assert isinstance(altitude_to_study_visualizer, OrderedDict)
- self.altitude_to_study_visualizer = altitude_to_study_visualizer # type: Dict[int, StudyVisualizer]
-
- @property
- def altitudes(self):
- return list(self.altitude_to_study_visualizer.keys())
-
- @cached_property
- def all_percentages(self):
- if self.multiprocessing:
- with Pool(4) as p:
- l = p.map(get_percentages, list(self.altitude_to_study_visualizer.values()))
- else:
- l = [get_percentages(v) for v in self.altitude_to_study_visualizer.values()]
- return l
-
- @property
- def any_study_visualizer(self) -> StudyVisualizer:
- return list(self.altitude_to_study_visualizer.values())[0]
-
- @property
- def study(self):
- return self.any_study_visualizer.study
-
- def get_item_fct(self, year):
- idx = self.any_study_visualizer.starting_years.index(year)
- f = lambda s: s[idx]
- return f
-
- @cached_property
- def starting_year(self):
- return self.any_study_visualizer.starting_years[0]
-
- def get_top_potential_years(self, reverse=False):
- top_n = 5
- top_top = 3
- # keep the top_n for each altitude
- all_years = [[year for year, _ in sorted(enumerate(p), key=lambda s: s[1], reverse=reverse)[-top_n:]] for p in
- self.all_percentages]
- from itertools import chain
- all_years = list(chain(*all_years))
- years = [y for y, _ in sorted(Counter(all_years).items(), key=lambda s: s[1])[-top_top:]]
- years = [y + self.starting_year for y in years]
- return years
-
- 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()
-
- def negative_trend_percentages_evolution(self, reverse=True):
- curve_name__metric_and_color = [
- ('max', np.max, 'g'),
- ('mean', np.mean, 'b'),
- ('median', np.median, 'c'),
- ('min', np.min, 'r'),
- ]
- # Add some years
- # spotted_years = [1963, 1976]
- # years_to_display = spotted_years
- str_markers = ['o'] + [m for m in Line2D.markers if isinstance(m, str)][3:]
- # for year, marker in zip(years_to_display, str_markers):
- # new = (str(year), self.get_item_fct(year), 'y', marker + ':')
- # curve_name__metric_and_color.append(new)
-
- for year, marker in zip(self.get_top_potential_years(), str_markers):
- new = (str(year), self.get_item_fct(year), 'y', marker + ':')
- curve_name__metric_and_color.append(new)
- for year, marker in zip(self.get_top_potential_years(reverse=True), str_markers):
- new = (str(year), self.get_item_fct(year), 'm', marker + ':')
- curve_name__metric_and_color.append(new)
-
- fig, ax = plt.subplots(1, 1, figsize=self.any_study_visualizer.figsize)
- for curve_name, metric, color, *marker in curve_name__metric_and_color[:]:
- marker, curve_name = (marker[0], curve_name + ' starting year') if marker \
- else ('-', curve_name + ' over the starting years')
- values = [metric(p) for p in self.all_percentages]
- if reverse:
- values = [100 - v for v in values]
- k = ['max', 'min']
- for before, new in zip(k, k[::-1]):
- if before in curve_name:
- curve_name = curve_name.replace(before, new)
- break
- ax.plot(self.altitudes, values, color + marker, label=curve_name)
- ax.legend()
- ax.set_xticks(self.altitudes)
- ax.set_yticks(list(range(0, 101, 10)))
- ax.grid()
-
- ax.axhline(y=50, color='k')
- word = 'positive' if reverse else 'negative'
- ax.set_ylabel('% of massifs with {} trends'.format(word))
- ax.set_xlabel('altitude')
- variable_name = self.study.variable_class.NAME
- score_name = get_display_name_from_object_type(self.any_study_visualizer.score_class)
- title = 'Evolution of {} trends wrt to the altitude with {}'.format(variable_name, score_name)
- ax.set_title(title)
- self.show_or_save_to_file(specific_title=title)
-
- """
- Trends tests
-
- In all the cases, I use all the massifs and I use all the altitude
-
- The only thing that can change, is that I use a different starting year distribution
- (specified with starting_year_to_weights) dict
- """
-
- # Trend tests repartition
-
- def trend_tests_percentage_repartition_spatially(self, trend_test_classes, starting_year_to_weights: None):
- pass
-
-
- # Trend tests evolution
-
- def trend_tests_percentage_evolution_with_altitude(self, trend_test_classes, starting_year_to_weights: None):
- # Load uniform weights by default
- if starting_year_to_weights is None:
- startings_years = self.any_study_visualizer.starting_years
- uniform_weight = 1 / len(startings_years)
- starting_year_to_weights = {year: uniform_weight for year in startings_years}
-
- # To get a single year, I could do:
- # starting_year_to_weights = {1980: 1.0}
- else:
- uniform_weight = 0.0
-
- fig, ax = plt.subplots(1, 1, figsize=self.any_study_visualizer.figsize)
-
- # Create one display for each trend test class
- markers = ['o', 's', 'D', '*']
- assert len(markers) >= len(trend_test_classes)
- # Add a second legend for the color and to explain the line
- for marker, trend_test_class in zip(markers, trend_test_classes):
- self.trend_test_class_weighted_percentages(ax, marker, trend_test_class, starting_year_to_weights)
-
- # Add the color legend
- handles, labels = ax.get_legend_handles_labels()
- unique_labels = set(labels)
- idx_labels = sorted([labels.index(label) for label in unique_labels])
- handles_ax, labels_ax = [handles[i] for i in idx_labels], [labels[i] for i in idx_labels]
- ax.legend(handles_ax, labels_ax, markerscale=0.0, loc=1)
- ax.set_xticks(self.altitudes)
- ax.set_yticks(list(range(0, 101, 10)))
- ax.grid()
-
- # Add the marker legend
- names = [get_display_name_from_object_type(c) for c in trend_test_classes]
- idx_for_positive_trend = [i for i, label in enumerate(labels) if label == AbstractUnivariateTest.POSITIVE_TREND]
- handles_ax2, labels_ax2 = [handles[i] for i in idx_for_positive_trend], names
- ax2 = ax.twinx()
- ax2.legend(handles_ax2, labels_ax2, loc=2)
- ax2.set_yticks([])
-
- # Global information
- added_str = '' if uniform_weight > 0.0 else 'weighted '
- ylabel = '% averaged on massifs & {}averaged on starting years'.format(added_str)
- ylabel += ' (with uniform weights)'
- ax.set_ylabel(ylabel)
- ax.set_xlabel('altitude')
- variable_name = self.study.variable_class.NAME
- title = 'Evolution of {} trends (significative or not) wrt to the altitude with {}'.format(variable_name,
- ', '.join(names))
- ax.set_title(title)
- self.show_or_save_to_file(specific_title=title)
-
- def trend_test_class_weighted_percentages(self, ax, marker, trend_test_class, starting_year_to_weights):
- # Build OrderedDict mapping altitude to a mean serie
- altitude_to_serie_with_mean_percentages = OrderedDict()
- for altitude, study_visualizer in self.altitude_to_study_visualizer.items():
- s = study_visualizer.df_trend_test_count(trend_test_class, starting_year_to_weights).mean(axis=1)
- altitude_to_serie_with_mean_percentages[altitude] = s
- # Plot weighted percentages over the years
- for trend_type, style in trend_test_class.display_trend_type_to_style().items():
-
- weighted_percentages = [v.loc[trend_type] if trend_type in v.index else 0.0
- for v in altitude_to_serie_with_mean_percentages.values()]
- if set(weighted_percentages) == {0.0}:
- ax.plot([], [], style + marker, label=trend_type)
- else:
- ax.plot(self.altitudes, weighted_percentages, style + marker, label=trend_type
- )
- # todo: If I wanted I could display here with a degradé, all the year composing the keys of starting_year_to_weights dictionary
- # maybe I could do that only when the dictionary is small for instance
diff --git a/experiment/meteo_france_data/scm_models_data/visualization/study_visualization/__init__.py b/experiment/meteo_france_data/scm_models_data/visualization/study_visualization/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/experiment/meteo_france_data/scm_models_data/visualization/study_visualization/study_visualizer.py b/experiment/meteo_france_data/scm_models_data/visualization/study_visualizer.py
similarity index 100%
rename from experiment/meteo_france_data/scm_models_data/visualization/study_visualization/study_visualizer.py
rename to experiment/meteo_france_data/scm_models_data/visualization/study_visualizer.py
diff --git a/experiment/meteo_france_data/stations_data/comparison_analysis.py b/experiment/meteo_france_data/stations_data/comparison_analysis.py
index 9b1a9d802742171f38058449f03533ee4a869078..0eb48e2a5203eb37800363d3af53e6e278cb90af 100644
--- a/experiment/meteo_france_data/stations_data/comparison_analysis.py
+++ b/experiment/meteo_france_data/stations_data/comparison_analysis.py
@@ -5,7 +5,7 @@ from typing import List
from cached_property import cached_property
from experiment.meteo_france_data.scm_models_data.safran.safran import SafranSnowfall
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.main_study_visualizer import \
+from experiment.meteo_france_data.scm_models_data.visualization.main_study_visualizer import \
ALL_ALTITUDES
from extreme_fit.estimator.full_estimator.abstract_full_estimator import \
FullEstimatorInASingleStepWithSmoothMargin
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 fa5cf0d0a2ded453510dee0674aeb95cd8b241d6..03f44f67073394fe68e5ca3cbac3f7d2c850c48a 100644
--- a/experiment/meteo_france_data/stations_data/main_station_comparison.py
+++ b/experiment/meteo_france_data/stations_data/main_station_comparison.py
@@ -1,4 +1,4 @@
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.main_study_visualizer import \
+from experiment.meteo_france_data.scm_models_data.visualization.main_study_visualizer import \
ALL_ALTITUDES_WITH_20_STATIONS_AT_LEAST
from experiment.meteo_france_data.stations_data.visualization.comparisons_visualization.comparisons_visualization import \
ComparisonsVisualization, path_backup_csv_file
diff --git a/experiment/meteo_france_data/stations_data/main_station_comparison_all_altitudes.py b/experiment/meteo_france_data/stations_data/main_station_comparison_all_altitudes.py
index 1d5f2e995bdb1efb1948f8b800a5ddc022088f77..d9469c794b2c13593d8be85ac75606d6e321aa28 100644
--- a/experiment/meteo_france_data/stations_data/main_station_comparison_all_altitudes.py
+++ b/experiment/meteo_france_data/stations_data/main_station_comparison_all_altitudes.py
@@ -1,4 +1,4 @@
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.main_study_visualizer import \
+from experiment.meteo_france_data.scm_models_data.visualization.main_study_visualizer import \
ALL_ALTITUDES
from experiment.meteo_france_data.stations_data.visualization.comparisons_visualization.comparisons_visualization import \
ComparisonsVisualization
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 7be7297adac50bdefe23884753541c8b43e7faf5..ed4e689d7d37666f42894c0b6b000739c040a06f 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
@@ -10,7 +10,7 @@ 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 \
+from experiment.meteo_france_data.scm_models_data.visualization.study_visualizer import \
VisualizationParameters
from experiment.meteo_france_data.stations_data.comparison_analysis import ComparisonAnalysis, MASSIF_COLUMN_NAME, \
REANALYSE_STR, ALTITUDE_COLUMN_NAME, STATION_COLUMN_NAME
diff --git a/experiment/regression_margin/__init__.py b/experiment/regression_margin/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/experiment/regression_margin/regression_margin.py b/experiment/regression_margin/regression_margin.py
deleted file mode 100644
index 33b67924c6eba9e4bdd09609154fa872dea70ee6..0000000000000000000000000000000000000000
--- a/experiment/regression_margin/regression_margin.py
+++ /dev/null
@@ -1,66 +0,0 @@
-import numpy as np
-
-from extreme_fit.estimator.full_estimator.abstract_full_estimator import FullEstimatorInASingleStepWithSmoothMargin
-from extreme_fit.function.margin_function.linear_margin_function import LinearMarginFunction
-from extreme_fit.model.margin_model.linear_margin_model.linear_margin_model import LinearAllParametersAllDimsMarginModel, \
- ConstantMarginModel
-from extreme_fit.model.max_stable_model.max_stable_models import Smith
-from extreme_fit.distribution.gev.gev_params import GevParams
-from spatio_temporal_dataset.coordinates.spatial_coordinates.coordinates_1D import LinSpaceSpatialCoordinates
-import matplotlib.pyplot as plt
-
-from spatio_temporal_dataset.dataset.simulation_dataset import FullSimulatedDataset
-
-nb_points = 50
-nb_obs = 60
-nb_estimator = 2
-show = False
-
-coordinates = LinSpaceSpatialCoordinates.from_nb_points(nb_points=nb_points)
-
-########## GENERATING THE DATA #####################
-
-# MarginModel Linear with respect to the shape (from 0.01 to 0.02)
-params_sample = {
- # (GevParams.GEV_SHAPE, 0): 0.2,
- (GevParams.LOC, 0): 10,
- (GevParams.SHAPE, 0): 1.0,
- (GevParams.SCALE, 0): 1.0,
-}
-margin_model = ConstantMarginModel(coordinates=coordinates, params_sample=params_sample)
-margin_model_for_estimator_class = [LinearAllParametersAllDimsMarginModel, ConstantMarginModel][-1]
-max_stable_model = Smith()
-
-
-######### FITTING A MODEL #################
-
-
-axes = None
-for i in range(nb_estimator):
- print("{}/{}".format(i+1, nb_estimator))
- # Data part
- dataset = FullSimulatedDataset.from_double_sampling(nb_obs=nb_obs, margin_model=margin_model,
- coordinates=coordinates,
- max_stable_model=max_stable_model)
-
- if show and i == 0:
- # Plot a realization from the maxima distribution (i.e the maxima obtained just by simulating the marginal law)
- for maxima in np.transpose(dataset.maxima_frech()):
- plt.plot(coordinates.coordinates_values(), maxima, 'o')
- plt.show()
-
- margin_function_sample = dataset.margin_model.margin_function_sample # type: LinearMarginFunction
- margin_function_sample.visualize_function(show=False, axes=axes, dot_display=True)
- axes = margin_function_sample.visualization_axes
-
- # Estimation part
- margin_model_for_estimator = margin_model_for_estimator_class(coordinates)
- full_estimator = FullEstimatorInASingleStepWithSmoothMargin(dataset, margin_model_for_estimator, max_stable_model)
- full_estimator.fit()
- full_estimator.function_from_fit.visualize_function(axes=axes, show=False)
-plt.show()
-
-# Display all the margin on the same graph for comparison
-
-# Plot the margin functions
-# margin_model.margin_function_sample.visualize_2D()
diff --git a/extreme_fit/function/margin_function/abstract_margin_function.py b/extreme_fit/function/margin_function/abstract_margin_function.py
index 994e7ebc9ba57afb8c3905a75b9d23c09bc50d68..981a25aa47d62995661c8b877579d46cde07f765 100644
--- a/extreme_fit/function/margin_function/abstract_margin_function.py
+++ b/extreme_fit/function/margin_function/abstract_margin_function.py
@@ -6,7 +6,7 @@ import pandas as pd
from experiment.meteo_france_data.scm_models_data.visualization.utils import create_adjusted_axes
from extreme_fit.distribution.gev.gev_params import GevParams
-from experiment.meteo_france_data.plot.create_shifted_cmap import imshow_shifted
+from experiment.meteo_france_data.scm_models_data.visualization.create_shifted_cmap import imshow_shifted
from extreme_fit.function.abstract_function import AbstractFunction
from spatio_temporal_dataset.coordinates.abstract_coordinates import AbstractCoordinates
from spatio_temporal_dataset.slicer.split import Split
diff --git a/papers/contrasting_snow_loads/main_spatial_relative_change_in_maxima_at_fixed_altitude.py b/papers/contrasting_snow_loads/main_spatial_relative_change_in_maxima_at_fixed_altitude.py
index 17d48f3fc1c0a1f5fb2f5066f3e5c570d9b94812..881ac233d0fa1f63ad391bff7c324f21d4de5c7c 100644
--- a/papers/contrasting_snow_loads/main_spatial_relative_change_in_maxima_at_fixed_altitude.py
+++ b/papers/contrasting_snow_loads/main_spatial_relative_change_in_maxima_at_fixed_altitude.py
@@ -1,20 +1,10 @@
-from experiment.meteo_france_data.scm_models_data.crocus.crocus import CrocusDepth, CrocusSnowLoad3Days, \
+from experiment.meteo_france_data.scm_models_data.crocus.crocus import CrocusSnowLoad3Days, \
CrocusSnowLoadTotal
-from experiment.meteo_france_data.scm_models_data.crocus.crocus_variables import CrocusDepthVariable
from experiment.meteo_france_data.scm_models_data.safran.safran import SafranSnowfall, SafranRainfall, SafranPrecipitation
-from experiment.meteo_france_data.scm_models_data.safran.safran_variable import SafranTotalPrecipVariable
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.main_study_visualizer import \
- study_iterator_global, SCM_STUDY_CLASS_TO_ABBREVIATION, snow_density_str, ALL_ALTITUDES_WITHOUT_NAN
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.study_visualizer import \
+from experiment.meteo_france_data.scm_models_data.visualization.study_visualizer import \
StudyVisualizer
import matplotlib.pyplot as plt
-from papers.exceeding_snow_loads.discussion_data_comparison_with_eurocode.crocus_study_comparison_with_eurocode import \
- CrocusDifferenceSnowLoad, \
- CrocusSnowDensityAtMaxofSwe, CrocusDifferenceSnowLoadRescaledAndEurocodeToSeeSynchronization, \
- CrocusSnowDepthAtMaxofSwe, CrocusSnowDepthDifference
-from papers.exceeding_snow_loads.paper_utils import dpi_paper1_figure
-
def test():
study = CrocusSnowLoad3Days(altitude=1200)
diff --git a/papers/exceeding_snow_loads/check_mle_convergence_for_trends/mixed_distribution/mixed_distribution_impact.py b/papers/exceeding_snow_loads/check_mle_convergence_for_trends/mixed_distribution/mixed_distribution_impact.py
index 0bea22245ebef006d9988cebe558b706c0d23a3b..e713a8277d1429b7d18f1df048b06df23e7c1934 100644
--- a/papers/exceeding_snow_loads/check_mle_convergence_for_trends/mixed_distribution/mixed_distribution_impact.py
+++ b/papers/exceeding_snow_loads/check_mle_convergence_for_trends/mixed_distribution/mixed_distribution_impact.py
@@ -1,10 +1,6 @@
import pandas as pd
from experiment.meteo_france_data.scm_models_data.crocus.crocus import CrocusSnowLoadTotal
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.main_study_visualizer import \
- ALL_ALTITUDES_WITHOUT_NAN
-from extreme_fit.model.result_from_model_fit.result_from_extremes.confidence_interval_method import \
- ConfidenceIntervalMethodFromExtremes
from papers.exceeding_snow_loads.study_visualizer_for_non_stationary_trends import StudyVisualizerForNonStationaryTrends
diff --git a/papers/exceeding_snow_loads/check_mle_convergence_for_trends/qqplot/main_qqplot_for_big_shapes.py b/papers/exceeding_snow_loads/check_mle_convergence_for_trends/qqplot/main_qqplot_for_big_shapes.py
index 3109e7ea594c265c373534f755701b17aeb230d0..5b66afc5453ba871efcb4e50118dc86c30f7363e 100644
--- a/papers/exceeding_snow_loads/check_mle_convergence_for_trends/qqplot/main_qqplot_for_big_shapes.py
+++ b/papers/exceeding_snow_loads/check_mle_convergence_for_trends/qqplot/main_qqplot_for_big_shapes.py
@@ -1,8 +1,7 @@
-from typing import Dict
import matplotlib.pyplot as plt
from experiment.meteo_france_data.scm_models_data.crocus.crocus import CrocusSnowLoadTotal
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.main_study_visualizer import \
+from experiment.meteo_france_data.scm_models_data.visualization.main_study_visualizer import \
ALL_ALTITUDES_WITHOUT_NAN
from papers.exceeding_snow_loads.study_visualizer_for_non_stationary_trends import \
StudyVisualizerForNonStationaryTrends
diff --git a/papers/exceeding_snow_loads/check_mle_convergence_for_trends/qqplot/plot_qqplot.py b/papers/exceeding_snow_loads/check_mle_convergence_for_trends/qqplot/plot_qqplot.py
index 1aaa9a01722cc5dc392c104ee70e3155202fb5b9..f3de8750233168d81c024d394b95a8f1ebda0e7f 100644
--- a/papers/exceeding_snow_loads/check_mle_convergence_for_trends/qqplot/plot_qqplot.py
+++ b/papers/exceeding_snow_loads/check_mle_convergence_for_trends/qqplot/plot_qqplot.py
@@ -7,8 +7,6 @@ import pandas as pd
from matplotlib.ticker import PercentFormatter
from experiment.meteo_france_data.scm_models_data.crocus.crocus import CrocusSnowLoadTotal
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.main_study_visualizer import \
- ALL_ALTITUDES_WITHOUT_NAN
from extreme_fit.model.margin_model.linear_margin_model.abstract_temporal_linear_margin_model import \
TemporalMarginFitMethod
from extreme_fit.model.result_from_model_fit.result_from_extremes.abstract_extract_eurocode_return_level import \
diff --git a/papers/exceeding_snow_loads/check_mle_convergence_for_trends/shape/study_visualizer_for_shape_repartition.py b/papers/exceeding_snow_loads/check_mle_convergence_for_trends/shape/study_visualizer_for_shape_repartition.py
index 59d377f79f48fad285074cda3de9b5731e66f176..241c8508bdc0cfc61091134fc3c050cd7a932cca 100644
--- a/papers/exceeding_snow_loads/check_mle_convergence_for_trends/shape/study_visualizer_for_shape_repartition.py
+++ b/papers/exceeding_snow_loads/check_mle_convergence_for_trends/shape/study_visualizer_for_shape_repartition.py
@@ -1,11 +1,10 @@
import matplotlib
from cached_property import cached_property
-from experiment.meteo_france_data.plot.create_shifted_cmap import get_shifted_map
+from experiment.meteo_france_data.scm_models_data.visualization.create_shifted_cmap import get_shifted_map
from experiment.meteo_france_data.scm_models_data.abstract_study import AbstractStudy
from papers.exceeding_snow_loads.study_visualizer_for_non_stationary_trends import \
StudyVisualizerForNonStationaryTrends
-from experiment.trend_analysis.abstract_score import MeanScore
class StudyVisualizerForShape(StudyVisualizerForNonStationaryTrends):
diff --git a/papers/exceeding_snow_loads/check_mle_convergence_for_trends/without_maximum/main_fit_without_maximum.py b/papers/exceeding_snow_loads/check_mle_convergence_for_trends/without_maximum/main_fit_without_maximum.py
index 22faaf45b72933fea0c3460a10f72d557ef17980..834198ee6096972f0d81e2821f453e52f1ea1076 100644
--- a/papers/exceeding_snow_loads/check_mle_convergence_for_trends/without_maximum/main_fit_without_maximum.py
+++ b/papers/exceeding_snow_loads/check_mle_convergence_for_trends/without_maximum/main_fit_without_maximum.py
@@ -1,7 +1,7 @@
from typing import Dict
from experiment.meteo_france_data.scm_models_data.crocus.crocus import CrocusSnowLoadTotal
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.main_study_visualizer import \
+from experiment.meteo_france_data.scm_models_data.visualization.main_study_visualizer import \
ALL_ALTITUDES_WITHOUT_NAN
from papers.exceeding_snow_loads.check_mle_convergence_for_trends.without_maximum.study_visualizer_for_fit_witout_maximum import \
StudyVisualizerForFitWithoutMaximum
diff --git a/papers/exceeding_snow_loads/check_mle_convergence_for_trends/without_maximum/study_visualizer_for_fit_witout_maximum.py b/papers/exceeding_snow_loads/check_mle_convergence_for_trends/without_maximum/study_visualizer_for_fit_witout_maximum.py
index 2ce354fc7a4baa4118cedfc0b0b43c201f6c7ae7..e1f62b2d01d6c4085463be2d21b37426a77b8083 100644
--- a/papers/exceeding_snow_loads/check_mle_convergence_for_trends/without_maximum/study_visualizer_for_fit_witout_maximum.py
+++ b/papers/exceeding_snow_loads/check_mle_convergence_for_trends/without_maximum/study_visualizer_for_fit_witout_maximum.py
@@ -1,14 +1,11 @@
from typing import Dict, Tuple
-import matplotlib
import numpy as np
from cached_property import cached_property
-from experiment.meteo_france_data.plot.create_shifted_cmap import get_shifted_map
from experiment.meteo_france_data.scm_models_data.abstract_study import AbstractStudy
from papers.exceeding_snow_loads.study_visualizer_for_non_stationary_trends import \
StudyVisualizerForNonStationaryTrends
-from experiment.trend_analysis.abstract_score import MeanScore
class StudyVisualizerForFitWithoutMaximum(StudyVisualizerForNonStationaryTrends):
diff --git a/papers/exceeding_snow_loads/data/main_example_swe_total_plot.py b/papers/exceeding_snow_loads/data/main_example_swe_total_plot.py
index c96cc96b86c2d4c935a321c8a80f644c36250020..efdd80b09e6df9f72b46326207080f5cde672d7b 100644
--- a/papers/exceeding_snow_loads/data/main_example_swe_total_plot.py
+++ b/papers/exceeding_snow_loads/data/main_example_swe_total_plot.py
@@ -1,9 +1,9 @@
import matplotlib.pyplot as plt
from experiment.meteo_france_data.scm_models_data.crocus.crocus import CrocusSnowLoadTotal
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.main_study_visualizer import \
+from experiment.meteo_france_data.scm_models_data.visualization.main_study_visualizer import \
study_iterator_global, SCM_STUDY_CLASS_TO_ABBREVIATION
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.study_visualizer import \
+from experiment.meteo_france_data.scm_models_data.visualization.study_visualizer import \
StudyVisualizer
from papers.exceeding_snow_loads.paper_utils import dpi_paper1_figure
diff --git a/papers/exceeding_snow_loads/discussion_data_comparison_with_eurocode/main_comparison_with_eurocode_examples.py b/papers/exceeding_snow_loads/discussion_data_comparison_with_eurocode/main_comparison_with_eurocode_examples.py
index a7026f8fd0ced96524fd4dac08de80c5b234c798..0017f555101e1ba37fb5f5fe14649161123eb85c 100644
--- a/papers/exceeding_snow_loads/discussion_data_comparison_with_eurocode/main_comparison_with_eurocode_examples.py
+++ b/papers/exceeding_snow_loads/discussion_data_comparison_with_eurocode/main_comparison_with_eurocode_examples.py
@@ -1,19 +1,15 @@
-import matplotlib as mpl
# mpl.rcParams['text.usetex'] = True
# mpl.rcParams['text.latex.preamble'] = [r'\usepackage{amsmath}']
-from experiment.meteo_france_data.scm_models_data.crocus.crocus import CrocusDepth
-from experiment.meteo_france_data.scm_models_data.crocus.crocus_variables import CrocusDepthVariable
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.main_study_visualizer import \
+from experiment.meteo_france_data.scm_models_data.visualization.main_study_visualizer import \
study_iterator_global, SCM_STUDY_CLASS_TO_ABBREVIATION, snow_density_str
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.study_visualizer import \
+from experiment.meteo_france_data.scm_models_data.visualization.study_visualizer import \
StudyVisualizer
import matplotlib.pyplot as plt
from papers.exceeding_snow_loads.discussion_data_comparison_with_eurocode.crocus_study_comparison_with_eurocode import \
CrocusDifferenceSnowLoad, \
- CrocusSnowDensityAtMaxofSwe, CrocusDifferenceSnowLoadRescaledAndEurocodeToSeeSynchronization, \
- CrocusSnowDepthAtMaxofSwe, CrocusSnowDepthDifference
+ CrocusSnowDensityAtMaxofSwe, CrocusSnowDepthDifference
from papers.exceeding_snow_loads.paper_utils import dpi_paper1_figure
diff --git a/papers/exceeding_snow_loads/discussion_data_comparison_with_eurocode/main_comparison_with_eurocode_global.py b/papers/exceeding_snow_loads/discussion_data_comparison_with_eurocode/main_comparison_with_eurocode_global.py
index 6a8342040ca621b4d712610dc1187fa500f7799e..07069c5f7c52b257ed6b4a2d31b5a9dc53b57567 100644
--- a/papers/exceeding_snow_loads/discussion_data_comparison_with_eurocode/main_comparison_with_eurocode_global.py
+++ b/papers/exceeding_snow_loads/discussion_data_comparison_with_eurocode/main_comparison_with_eurocode_global.py
@@ -1,15 +1,12 @@
-from experiment.meteo_france_data.scm_models_data.crocus.crocus import CrocusDepth
-from experiment.meteo_france_data.scm_models_data.crocus.crocus_variables import CrocusDepthVariable
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.main_study_visualizer import \
- study_iterator_global, SCM_STUDY_CLASS_TO_ABBREVIATION, snow_density_str
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.study_visualizer import \
+from experiment.meteo_france_data.scm_models_data.visualization.main_study_visualizer import \
+ study_iterator_global, SCM_STUDY_CLASS_TO_ABBREVIATION
+from experiment.meteo_france_data.scm_models_data.visualization.study_visualizer import \
StudyVisualizer
import matplotlib.pyplot as plt
from experiment.exceeding_snow_loads.discussion_data_comparison_with_eurocode.crocus_study_comparison_with_eurocode import \
CrocusDifferenceSnowLoad, \
- CrocusSnowDensityAtMaxofSwe, CrocusDifferenceSnowLoadRescaledAndEurocodeToSeeSynchronization, \
- CrocusSnowDepthAtMaxofSwe, CrocusSnowDepthDifference
+ CrocusSnowDensityAtMaxofSwe, CrocusSnowDepthDifference
from experiment.exceeding_snow_loads.paper_utils import dpi_paper1_figure
diff --git a/papers/exceeding_snow_loads/discussion_data_comparison_with_eurocode/main_spatio_temporal_density_wrt_altitude.py b/papers/exceeding_snow_loads/discussion_data_comparison_with_eurocode/main_spatio_temporal_density_wrt_altitude.py
index 0c4dfadc594de7726a985a726f74cb17e5ae573b..96c796f251b2fef49c17c5d5651b973702e6a57e 100644
--- a/papers/exceeding_snow_loads/discussion_data_comparison_with_eurocode/main_spatio_temporal_density_wrt_altitude.py
+++ b/papers/exceeding_snow_loads/discussion_data_comparison_with_eurocode/main_spatio_temporal_density_wrt_altitude.py
@@ -1,15 +1,11 @@
-from experiment.meteo_france_data.scm_models_data.crocus.crocus import CrocusDepth
-from experiment.meteo_france_data.scm_models_data.crocus.crocus_variables import CrocusDepthVariable
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.main_study_visualizer import \
- study_iterator_global, SCM_STUDY_CLASS_TO_ABBREVIATION, snow_density_str
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.study_visualizer import \
+from experiment.meteo_france_data.scm_models_data.visualization.main_study_visualizer import \
+ study_iterator_global, SCM_STUDY_CLASS_TO_ABBREVIATION
+from experiment.meteo_france_data.scm_models_data.visualization.study_visualizer import \
StudyVisualizer
import matplotlib.pyplot as plt
from experiment.exceeding_snow_loads.discussion_data_comparison_with_eurocode.crocus_study_comparison_with_eurocode import \
- CrocusDifferenceSnowLoad, \
- CrocusSnowDensityAtMaxofSwe, CrocusDifferenceSnowLoadRescaledAndEurocodeToSeeSynchronization, \
- CrocusSnowDepthAtMaxofSwe, CrocusSnowDepthDifference
+ CrocusSnowDensityAtMaxofSwe
from experiment.exceeding_snow_loads.paper_utils import dpi_paper1_figure
diff --git a/papers/exceeding_snow_loads/paper1_old/1 - non stationary model choice/__init__.py b/papers/exceeding_snow_loads/paper1_old/1 - non stationary model choice/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/papers/exceeding_snow_loads/paper1_old/1 - non stationary model choice/main2_choice_to_not_use_starting_years.py b/papers/exceeding_snow_loads/paper1_old/1 - non stationary model choice/main2_choice_to_not_use_starting_years.py
deleted file mode 100644
index d6fc5ab39673686501ecc3bad9e777c18d08a207..0000000000000000000000000000000000000000
--- a/papers/exceeding_snow_loads/paper1_old/1 - non stationary model choice/main2_choice_to_not_use_starting_years.py
+++ /dev/null
@@ -1,36 +0,0 @@
-import time
-
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.altitude_year_hypercube_visualizer import \
- Altitude_Hypercube_Year_Visualizer
-from experiment.exceeding_snow_loads.paper1_old import get_full_altitude_visualizer, FULL_ALTITUDES
-
-
-def main_fast_spatial_repartition():
- for altitude in FULL_ALTITUDES[-1:]:
- vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
- exact_starting_year=1958)
- vizualiser.save_to_file = False
- vizualiser.visualize_massif_trend_test_one_altitude()
-
-
-def main_full_spatial_repartition():
- for altitude in FULL_ALTITUDES[:]:
- # Compute for the most likely starting year
- # vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude)
- # vizualiser.visualize_massif_trend_test_one_altitude()
- # Compute the trend for a linear trend
- vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
- exact_starting_year=1958)
- vizualiser.visualize_massif_trend_test_one_altitude()
-
-
-def main_run():
- # main_full_spatial_repartition()
- main_fast_spatial_repartition()
-
-
-if __name__ == '__main__':
- start = time.time()
- main_run()
- duration = time.time() - start
- print('Full run took {}s'.format(round(duration, 1)))
diff --git a/papers/exceeding_snow_loads/paper1_old/1 - non stationary model choice/main3_non_stationary_strength_evolution.py b/papers/exceeding_snow_loads/paper1_old/1 - non stationary model choice/main3_non_stationary_strength_evolution.py
deleted file mode 100644
index 368008f2611ab0341bdc4508d802efc5a553837c..0000000000000000000000000000000000000000
--- a/papers/exceeding_snow_loads/paper1_old/1 - non stationary model choice/main3_non_stationary_strength_evolution.py
+++ /dev/null
@@ -1,42 +0,0 @@
-import time
-
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.altitude_year_hypercube_visualizer import \
- Altitude_Hypercube_Year_Visualizer
-from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_one_parameter import GevScaleTrendTest, \
- GevLocationTrendTest
-from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_two_parameters.gev_trend_test_two_parameters import GevLocationAndScaleTrendTest
-
-"""
-Visualize the 0.99 quantile initial value and its evolution
-"""
-from experiment.exceeding_snow_loads.paper1_old import get_full_altitude_visualizer, FULL_ALTITUDES
-
-
-def main_fast_spatial_risk_evolution():
- for altitude in [1800]:
- vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
- exact_starting_year=1958, reduce_strength_array=True,
- trend_test_class=GevLocationAndScaleTrendTest)
- vizualiser.save_to_file = False
- vizualiser.visualize_massif_trend_test_one_altitude()
-
-
-def main_full_spatial_risk_evolution():
- for altitude in FULL_ALTITUDES[:]:
- for trend_test_class in [GevLocationTrendTest, GevScaleTrendTest, GevLocationAndScaleTrendTest][-1:]:
- vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
- exact_starting_year=1958, reduce_strength_array=True,
- trend_test_class=trend_test_class)
- vizualiser.visualize_massif_trend_test_one_altitude()
-
-
-def main_run():
- # main_full_spatial_risk_evolution()
- main_fast_spatial_risk_evolution()
-
-
-if __name__ == '__main__':
- start = time.time()
- main_run()
- duration = time.time() - start
- print('Full run took {}s'.format(round(duration, 1)))
diff --git a/papers/exceeding_snow_loads/paper1_old/1 - non stationary model choice/main4_common_spatial_altitude_starting_years_impact.py b/papers/exceeding_snow_loads/paper1_old/1 - non stationary model choice/main4_common_spatial_altitude_starting_years_impact.py
deleted file mode 100644
index 443a0c6a5eab74ae8c86620377911ef8a442c7af..0000000000000000000000000000000000000000
--- a/papers/exceeding_snow_loads/paper1_old/1 - non stationary model choice/main4_common_spatial_altitude_starting_years_impact.py
+++ /dev/null
@@ -1,56 +0,0 @@
-import time
-
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.altitude_year_hypercube_visualizer import \
- Altitude_Hypercube_Year_Visualizer, AltitudeHypercubeVisualizerWithoutTrendType
-from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_two_parameters.gev_trend_test_two_parameters import GevLocationAndScaleTrendTest
-
-"""
-Visualize the 0.99 quantile initial value and its evolution
-"""
-from experiment.exceeding_snow_loads.paper1_old import get_full_altitude_visualizer, FULL_ALTITUDES
-
-
-def main_fast_spatial_risk_evolution():
- vizualiser = get_full_altitude_visualizer(AltitudeHypercubeVisualizerWithoutTrendType, altitude=None,
- reduce_strength_array=True,
- trend_test_class=GevLocationAndScaleTrendTest,
- offset_starting_year=28)
- vizualiser.save_to_file = False
- vizualiser.sigma_for_best_year = 1.0
- res = vizualiser.visualize_year_trend_test(subtitle_specified='CrocusSwe3Days')
- print(res)
-
-
-def main_full_spatial_risk_evolution():
- for trend_test_class in [GevLocationAndScaleTrendTest]:
- # Compare the risk with and without taking into account the starting year
- vizualiser = get_full_altitude_visualizer(AltitudeHypercubeVisualizerWithoutTrendType, altitude=None,
- reduce_strength_array=True,
- trend_test_class=trend_test_class,
- offset_starting_year=20)
- vizualiser.sigma_for_best_year = 1.0
- res = vizualiser.visualize_year_trend_test(subtitle_specified='CrocusSwe3Days')
- best_year = res[0][1]
- for altitude in FULL_ALTITUDES[:]:
- # Starting Year=1958
- vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
- exact_starting_year=1958, reduce_strength_array=True,
- trend_test_class=trend_test_class)
- vizualiser.visualize_massif_trend_test_one_altitude()
- # Optimal common starting year
- vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
- exact_starting_year=best_year, reduce_strength_array=True,
- trend_test_class=trend_test_class)
- vizualiser.visualize_massif_trend_test_one_altitude()
-
-
-def main_run():
- main_full_spatial_risk_evolution()
- # main_fast_spatial_risk_evolution()
-
-
-if __name__ == '__main__':
- start = time.time()
- main_run()
- duration = time.time() - start
- print('Full run took {}s'.format(round(duration, 1)))
diff --git a/papers/exceeding_snow_loads/paper1_old/1 - non stationary model choice/main4_common_spatial_starting_years_impact.py b/papers/exceeding_snow_loads/paper1_old/1 - non stationary model choice/main4_common_spatial_starting_years_impact.py
deleted file mode 100644
index 3ad25abdd3c1433a2a7dbacc1e1dd5c56cd683e0..0000000000000000000000000000000000000000
--- a/papers/exceeding_snow_loads/paper1_old/1 - non stationary model choice/main4_common_spatial_starting_years_impact.py
+++ /dev/null
@@ -1,58 +0,0 @@
-import time
-
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.altitude_year_hypercube_visualizer import \
- Altitude_Hypercube_Year_Visualizer, AltitudeHypercubeVisualizerWithoutTrendType
-from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_two_parameters.gev_trend_test_two_parameters import GevLocationAndScaleTrendTest
-
-"""
-Visualize the 0.99 quantile initial value and its evolution
-"""
-from experiment.exceeding_snow_loads.paper1_old import get_full_altitude_visualizer, FULL_ALTITUDES
-
-
-def main_fast_spatial_risk_evolution():
- for altitude in [1800]:
- vizualiser = get_full_altitude_visualizer(AltitudeHypercubeVisualizerWithoutTrendType, altitude=altitude,
- reduce_strength_array=True,
- trend_test_class=GevLocationAndScaleTrendTest,
- offset_starting_year=20)
- vizualiser.save_to_file = False
- res = vizualiser.visualize_year_trend_test(subtitle_specified='CrocusSwe3Days')
- print(res)
- vizualiser.visualize_massif_trend_test_one_altitude()
- vizualiser.reduce_strength_array = True
- vizualiser.visualize_massif_trend_test_one_altitude()
-
-
-def main_full_spatial_risk_evolution():
- # Compare the risk with and without taking into account the starting year
- for altitude in FULL_ALTITUDES[-1:]:
- for trend_test_class in [GevLocationAndScaleTrendTest]:
- # Starting Year=1958
- # vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
- # exact_starting_year=1958, reduce_strength_array=True,
- # trend_test_class=trend_test_class)
- # vizualiser.visualize_massif_trend_test_one_altitude()
- # Optimal common starting year
- vizualiser = get_full_altitude_visualizer(AltitudeHypercubeVisualizerWithoutTrendType, altitude=altitude,
- reduce_strength_array=True,
- trend_test_class=trend_test_class,
- offset_starting_year=20)
- res = vizualiser.visualize_year_trend_test(subtitle_specified='CrocusSwe3Days')
- best_year = res[0][1]
- vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
- exact_starting_year=best_year, reduce_strength_array=True,
- trend_test_class=trend_test_class)
- vizualiser.visualize_massif_trend_test_one_altitude()
-
-
-def main_run():
- main_full_spatial_risk_evolution()
- # main_fast_spatial_risk_evolution()
-
-
-if __name__ == '__main__':
- start = time.time()
- main_run()
- duration = time.time() - start
- print('Full run took {}s'.format(round(duration, 1)))
diff --git a/papers/exceeding_snow_loads/paper1_old/1 - non stationary model choice/main4_individual_starting_years_impact.py b/papers/exceeding_snow_loads/paper1_old/1 - non stationary model choice/main4_individual_starting_years_impact.py
deleted file mode 100644
index 9a38884fb86b7dc7c8668ca5aab79db8efdb7752..0000000000000000000000000000000000000000
--- a/papers/exceeding_snow_loads/paper1_old/1 - non stationary model choice/main4_individual_starting_years_impact.py
+++ /dev/null
@@ -1,51 +0,0 @@
-import time
-
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.altitude_year_hypercube_visualizer import \
- Altitude_Hypercube_Year_Visualizer
-from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_two_parameters.gev_trend_test_two_parameters import GevLocationAndScaleTrendTest
-
-"""
-Visualize the 0.99 quantile initial value and its evolution
-"""
-from experiment.exceeding_snow_loads.paper1_old import get_full_altitude_visualizer, FULL_ALTITUDES
-
-
-def main_fast_spatial_risk_evolution():
- for altitude in [1800]:
- vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
- reduce_strength_array=False,
- trend_test_class=GevLocationAndScaleTrendTest,
- offset_starting_year=20)
- vizualiser.save_to_file = False
- vizualiser.visualize_massif_trend_test_one_altitude()
- vizualiser.reduce_strength_array = True
- vizualiser.visualize_massif_trend_test_one_altitude()
-
-
-def main_full_spatial_risk_evolution():
- # Compare the risk with and without taking into account the starting year
- for altitude in FULL_ALTITUDES[-2:-1]:
- for trend_test_class in [GevLocationAndScaleTrendTest]:
- # vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
- # exact_starting_year=1958, reduce_strength_array=True,
- # trend_test_class=trend_test_class)
- # vizualiser.visualize_massif_trend_test_one_altitude()
- vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
- reduce_strength_array=True,
- trend_test_class=trend_test_class,
- offset_starting_year=20)
- vizualiser.visualize_massif_trend_test_one_altitude()
- vizualiser.reduce_strength_array = False
- vizualiser.visualize_massif_trend_test_one_altitude()
-
-
-def main_run():
- main_full_spatial_risk_evolution()
- # main_fast_spatial_risk_evolution()
-
-
-if __name__ == '__main__':
- start = time.time()
- main_run()
- duration = time.time() - start
- print('Full run took {}s'.format(round(duration, 1)))
diff --git a/papers/exceeding_snow_loads/paper1_old/__init__.py b/papers/exceeding_snow_loads/paper1_old/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/papers/exceeding_snow_loads/paper1_old/poster_EVAN2019/__init__.py b/papers/exceeding_snow_loads/paper1_old/poster_EVAN2019/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/papers/exceeding_snow_loads/paper1_old/poster_EVAN2019/main_poster_EVAN2019.py b/papers/exceeding_snow_loads/paper1_old/poster_EVAN2019/main_poster_EVAN2019.py
deleted file mode 100644
index df96d6bddc37d9210db063b91cd71b77cbec2e38..0000000000000000000000000000000000000000
--- a/papers/exceeding_snow_loads/paper1_old/poster_EVAN2019/main_poster_EVAN2019.py
+++ /dev/null
@@ -1,138 +0,0 @@
-from experiment.meteo_france_data.scm_models_data.crocus.crocus import CrocusSwe3Days
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.altitude_year_hypercube_visualizer import \
- Altitude_Hypercube_Year_Visualizer, AltitudeHypercubeVisualizerWithoutTrendType
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.main_study_visualizer import \
- SCM_STUDIES
-from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_one_parameter import GevScaleTrendTest, \
- GevLocationTrendTest
-from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_two_parameters.gev_trend_test_two_parameters import GevLocationAndScaleTrendTest
-from experiment.exceeding_snow_loads.paper1_old import get_full_altitude_visualizer
-
-POSTER_ALTITUDES = [900, 1800, 2700]
-import matplotlib as mpl
-
-mpl.rcParams['hatch.linewidth'] = 0.3
-
-
-def main_poster_A_non_stationary_model_choice():
- nb = 1
- for altitude in POSTER_ALTITUDES[:]:
- for trend_test_class in [GevLocationTrendTest, GevScaleTrendTest, GevLocationAndScaleTrendTest][-nb:]:
- vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
- exact_starting_year=1958, reduce_strength_array=False,
- trend_test_class=trend_test_class,
- )
- # vizualiser.save_to_file = False
- vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=False)
-
-
-def main_poster_B_starting_years_analysis():
- nb = 3
- for altitude in POSTER_ALTITUDES[:nb]:
- for trend_test_class in [GevLocationAndScaleTrendTest]:
- # 1958 as starting year
- vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
- exact_starting_year=1958, reduce_strength_array=False,
- trend_test_class=trend_test_class,
- )
- for d in [True, False]:
- vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=False,
- display_trend_color=d)
- # vizualiser.save_to_file = False
-
- vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=False)
- # Optimal common starting year
- vizualiser = get_full_altitude_visualizer(AltitudeHypercubeVisualizerWithoutTrendType, altitude=altitude,
- reduce_strength_array=True,
- trend_test_class=trend_test_class,
- offset_starting_year=20)
- res = vizualiser.visualize_year_trend_test(subtitle_specified='CrocusSwe3Days')
- best_year = res[0][1]
- vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
- exact_starting_year=best_year, reduce_strength_array=False,
- trend_test_class=trend_test_class)
- for d in [True, False]:
- vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=False,
- display_trend_color=d)
- # Individual most likely starting year for each massif
- vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
- reduce_strength_array=False,
- trend_test_class=trend_test_class,
- offset_starting_year=20)
- for d in [True, False]:
- vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=False,
- display_trend_color=d)
-
-# def main_poster_B_test():
-# nb = 3
-# for altitude in POSTER_ALTITUDES[:1]:
-# for trend_test_class in [GevLocationAndScaleTrendTest]:
-# # # 1958 as starting year
-# vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
-# exact_starting_year=1958, reduce_strength_array=False,
-# trend_test_class=trend_test_class,
-# )
-# # vizualiser.save_to_file = False
-# vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=False,
-# display_trend_color=False)
-# vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=False,
-# display_trend_color=True)
-# # # Optimal common starting year
-# vizualiser = get_full_altitude_visualizer(AltitudeHypercubeVisualizerWithoutTrendType, altitude=altitude,
-# reduce_strength_array=True,
-# trend_test_class=trend_test_class,
-# offset_starting_year=20)
-# res = vizualiser.visualize_year_trend_test(subtitle_specified='CrocusSwe3Days')
-# best_year = res[0][1]
-# vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
-# exact_starting_year=best_year, reduce_strength_array=False,
-# trend_test_class=trend_test_class)
-# vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=False,
-# display_trend_color=False)
-# vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=False,
-# display_trend_color=True)
-# # vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=False)
-# # Individual most likely starting year for each massif
-# # vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
-# # reduce_strength_array=False,
-# # trend_test_class=trend_test_class,
-# # offset_starting_year=50)
-# # # vizualiser.save_to_file = False
-# # vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=True,
-# # display_trend_color=False)
-
-
-
-def main_poster_C_orientation_analysis():
- """By default the slope is equal to 20"""
- nb = 0
- cardinal_orientations = [0.0, 90.0, 180.0, 270.0]
- trend_test_class = GevLocationAndScaleTrendTest
- for altitude in POSTER_ALTITUDES[nb:]:
- study_class = CrocusSwe3Days
- for orientation in cardinal_orientations[nb:]:
- vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
- exact_starting_year=1958, reduce_strength_array=False,
- trend_test_class=trend_test_class,
- study_class=study_class,
- orientation=orientation)
- vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=False)
-
-
-def main_poster_D_other_quantities_analysis():
- nb = 3
- trend_test_class = GevLocationAndScaleTrendTest
- for altitude in POSTER_ALTITUDES[:nb]:
- for study_class in SCM_STUDIES[:nb]:
- vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
- exact_starting_year=1958, reduce_strength_array=False,
- trend_test_class=trend_test_class,
- study_class=study_class)
- vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=False)
-
-
-if __name__ == '__main__':
- main_poster_A_non_stationary_model_choice()
- # main_poster_B_starting_years_analysis()
- # main_poster_C_orientation_analysis()
- # main_poster_D_other_quantities_analysis()
diff --git a/papers/exceeding_snow_loads/paper1_old/poster_EVAN2019/shape_prior_check/__init__.py b/papers/exceeding_snow_loads/paper1_old/poster_EVAN2019/shape_prior_check/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/papers/exceeding_snow_loads/paper1_old/poster_EVAN2019/shape_prior_check/analyse_shape_from_some_experiment.py b/papers/exceeding_snow_loads/paper1_old/poster_EVAN2019/shape_prior_check/analyse_shape_from_some_experiment.py
deleted file mode 100644
index 97c42f9a441b8b3abc1ee698ba13a6acee69f81b..0000000000000000000000000000000000000000
--- a/papers/exceeding_snow_loads/paper1_old/poster_EVAN2019/shape_prior_check/analyse_shape_from_some_experiment.py
+++ /dev/null
@@ -1,10 +0,0 @@
-import matplotlib.pyplot as plt
-
-# Load shapes
-lines = []
-with open('shape_from_some_experiment.txt') as f:
- for l in f:
- lines.append(float(l.split('\n')[0]))
-# Build his
-plt.hist(lines, bins=50, histtype='step')
-plt.show()
\ No newline at end of file
diff --git a/papers/exceeding_snow_loads/paper1_old/poster_EVAN2019/shape_prior_check/hist_values_shape.png b/papers/exceeding_snow_loads/paper1_old/poster_EVAN2019/shape_prior_check/hist_values_shape.png
deleted file mode 100644
index 2aa54e3a4c6b777ae861ae7a2195f278cd138626..0000000000000000000000000000000000000000
Binary files a/papers/exceeding_snow_loads/paper1_old/poster_EVAN2019/shape_prior_check/hist_values_shape.png and /dev/null differ
diff --git a/papers/exceeding_snow_loads/paper1_old/poster_EVAN2019/shape_prior_check/shape_from_some_experiment.txt b/papers/exceeding_snow_loads/paper1_old/poster_EVAN2019/shape_prior_check/shape_from_some_experiment.txt
deleted file mode 100644
index 813b089896d72ada17f7dff66af0991fc9151383..0000000000000000000000000000000000000000
--- a/papers/exceeding_snow_loads/paper1_old/poster_EVAN2019/shape_prior_check/shape_from_some_experiment.txt
+++ /dev/null
@@ -1,396 +0,0 @@
--0.17986546997305747
--0.21512821907488117
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--0.04716342309438759
--0.036858800462481356
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--0.00035516640950627006
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--0.09443055073415636
--0.12516161155424058
--0.017603453383083965
--0.03341544379480277
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--0.17175820929152086
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--0.029649574367349434
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--0.044957908239197805
--0.007512152372008501
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--0.012661463769511036
--0.012099524333183728
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--0.023541225896109897
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--0.008410124971168734
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--0.09443055073415636
--0.12436056994005414
--0.017603453383083965
--0.03351139880158266
\ No newline at end of file
diff --git a/papers/exceeding_snow_loads/paper1_old/poster_EVAN2019/shape_prior_check/some_experiment_EVAN.py b/papers/exceeding_snow_loads/paper1_old/poster_EVAN2019/shape_prior_check/some_experiment_EVAN.py
deleted file mode 100644
index a6a982c37fde9c7c568c48417c4825ba7a5e21b0..0000000000000000000000000000000000000000
--- a/papers/exceeding_snow_loads/paper1_old/poster_EVAN2019/shape_prior_check/some_experiment_EVAN.py
+++ /dev/null
@@ -1,32 +0,0 @@
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.altitude_year_hypercube_visualizer import \
- Altitude_Hypercube_Year_Visualizer
-from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_one_parameter.abstract_comparison_non_stationary_model import ComparisonAgainstMu, \
- ComparisonAgainstSigma
-from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_one_parameter import GevScaleTrendTest, \
- GevLocationTrendTest
-from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_two_parameters.gev_trend_test_two_parameters import GevLocationAndScaleTrendTest
-from experiment.exceeding_snow_loads.paper1_old import get_full_altitude_visualizer
-
-POSTER_ALTITUDES = [900, 1800, 2700]
-import matplotlib as mpl
-
-mpl.rcParams['hatch.linewidth'] = 0.3
-
-
-def main_non_stationary_model_comparison():
- stop_loop = False
- for altitude in POSTER_ALTITUDES[:]:
- for trend_test_class in [GevLocationTrendTest, GevScaleTrendTest, GevLocationAndScaleTrendTest,
- ComparisonAgainstMu, ComparisonAgainstSigma][:]:
- vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
- exact_starting_year=1958, reduce_strength_array=False,
- trend_test_class=trend_test_class,
- verbose=False)
- # vizualiser.save_to_file = False
- vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=False)
- if stop_loop:
- return
-
-
-if __name__ == '__main__':
- main_non_stationary_model_comparison()
diff --git a/papers/exceeding_snow_loads/paper1_old/utils.py b/papers/exceeding_snow_loads/paper1_old/utils.py
deleted file mode 100644
index 55caf1fee2060ab9f5a45bb8d183e00ac818e96b..0000000000000000000000000000000000000000
--- a/papers/exceeding_snow_loads/paper1_old/utils.py
+++ /dev/null
@@ -1,30 +0,0 @@
-from experiment.meteo_france_data.scm_models_data.crocus.crocus import CrocusSwe3Days
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.main_files.main_full_hypercube import \
- get_full_parameters
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.utils_hypercube import \
- load_altitude_visualizer
-from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_one_parameter import GevLocationTrendTest
-
-FULL_ALTITUDES = [900, 1200, 1500, 1800, 2100, 2400, 2700, 3000]
-
-
-def get_full_altitude_visualizer(altitude_hypercube_class, exact_starting_year=None, altitude=900,
- reduce_strength_array=False,
- trend_test_class = GevLocationTrendTest,
- offset_starting_year=10,
- study_class=CrocusSwe3Days,
- orientation=None,
- verbose=True):
- altitudes, first_starting_year, last_starting_year, nb_data_reduced_for_speed, only_first_one, save_to_file, _ = get_full_parameters(
- altitude=altitude, offset_starting_year=offset_starting_year)
- if exact_starting_year is not None:
- first_starting_year, last_starting_year = None, None
- study_classes = [study_class]
- visualizer = load_altitude_visualizer(altitude_hypercube_class, altitudes, last_starting_year,
- nb_data_reduced_for_speed, only_first_one, save_to_file, study_classes,
- trend_test_class, first_starting_year=first_starting_year,
- exact_starting_year=exact_starting_year,
- orientations=[orientation],
- verbose=verbose)
- visualizer.reduce_strength_array = reduce_strength_array
- return visualizer
diff --git a/papers/exceeding_snow_loads/paper1_old/validations/__init__.py b/papers/exceeding_snow_loads/paper1_old/validations/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/papers/exceeding_snow_loads/paper1_old/validations/main0_comparison_with_observations.py b/papers/exceeding_snow_loads/paper1_old/validations/main0_comparison_with_observations.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/papers/exceeding_snow_loads/paper1_old/validations/main1_good_stationary_gev_fit.py b/papers/exceeding_snow_loads/paper1_old/validations/main1_good_stationary_gev_fit.py
deleted file mode 100644
index f7b764b96784c6241079b5b43a695d6b12bce4ef..0000000000000000000000000000000000000000
--- a/papers/exceeding_snow_loads/paper1_old/validations/main1_good_stationary_gev_fit.py
+++ /dev/null
@@ -1,23 +0,0 @@
-from experiment.meteo_france_data.scm_models_data.crocus.crocus import CrocusSwe3Days
-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
-
-
-def maxima_analysis():
- save_to_file = False
- only_first_one = False
- durand_altitude = [900, 1500, 1800, 2100, 2700][2:-2]
- altitudes = durand_altitude
- study_classes = [CrocusSwe3Days][:]
- for study in study_iterator_global(study_classes, only_first_one=only_first_one, altitudes=altitudes):
- study_visualizer = StudyVisualizer(study, save_to_file=save_to_file,
- verbose=True,
- multiprocessing=True)
- # study_visualizer.visualize_summary_of_annual_values_and_stationary_gev_fit()
- study_visualizer.visualize_all_mean_and_max_graphs()
-
-
-if __name__ == '__main__':
- maxima_analysis()
diff --git a/papers/exceeding_snow_loads/paper_utils.py b/papers/exceeding_snow_loads/paper_utils.py
index 35e2c51921deab72ebb18c4d2cc303e409994f2e..d3c419e5208144cfed9f27e701cf55c2f200b719 100644
--- a/papers/exceeding_snow_loads/paper_utils.py
+++ b/papers/exceeding_snow_loads/paper_utils.py
@@ -2,7 +2,7 @@ from enum import Enum
from experiment.meteo_france_data.scm_models_data.crocus.crocus import CrocusSnowLoadTotal, CrocusSnowLoadEurocode, \
CrocusSnowLoad3Days
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.main_study_visualizer import \
+from experiment.meteo_france_data.scm_models_data.visualization.main_study_visualizer import \
ALL_ALTITUDES_WITHOUT_NAN
from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_one_parameter.gumbel_trend_test_one_parameter import \
GumbelVersusGumbel, GumbelLocationTrendTest, GumbelScaleTrendTest, GevStationaryVersusGumbel
@@ -12,7 +12,6 @@ from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_two
GevLocationAgainstGumbel, GevScaleAgainstGumbel
from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_two_parameters.gumbel_test_two_parameters import \
GumbelLocationAndScaleTrendTest
-from root_utils import get_display_name_from_object_type
paper_altitudes = ALL_ALTITUDES_WITHOUT_NAN
paper_study_classes = [CrocusSnowLoadTotal, CrocusSnowLoadEurocode, CrocusSnowLoad3Days][:2]
diff --git a/papers/exceeding_snow_loads/result_trends_and_return_levels/plot_uncertainty_curves.py b/papers/exceeding_snow_loads/result_trends_and_return_levels/plot_uncertainty_curves.py
index 87b8325e4e9938244c3a5816594802150f54e04e..e68a89384931514b7532b5711c0d4bd74320f9a2 100644
--- a/papers/exceeding_snow_loads/result_trends_and_return_levels/plot_uncertainty_curves.py
+++ b/papers/exceeding_snow_loads/result_trends_and_return_levels/plot_uncertainty_curves.py
@@ -5,10 +5,7 @@ import numpy as np
from experiment.eurocode_data.utils import EUROCODE_RETURN_LEVEL_STR, EUROCODE_ALTITUDES, \
YEAR_OF_INTEREST_FOR_RETURN_LEVEL
-from experiment.meteo_france_data.scm_models_data.abstract_study import AbstractStudy, filled_marker_legend_list, \
- filled_marker_legend_list2
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.main_study_visualizer import \
- SCM_STUDY_CLASS_TO_ABBREVIATION
+from experiment.meteo_france_data.scm_models_data.abstract_study import AbstractStudy, filled_marker_legend_list2
from papers.exceeding_snow_loads.paper_utils import dpi_paper1_figure, ModelSubsetForUncertainty
from papers.exceeding_snow_loads.study_visualizer_for_non_stationary_trends import \
StudyVisualizerForNonStationaryTrends
@@ -16,8 +13,7 @@ from extreme_fit.model.result_from_model_fit.result_from_extremes.abstract_extra
AbstractExtractEurocodeReturnLevel
from experiment.eurocode_data.massif_name_to_departement import massif_name_to_eurocode_region
from experiment.meteo_france_data.scm_models_data.visualization.utils import create_adjusted_axes
-from extreme_fit.model.result_from_model_fit.result_from_extremes.confidence_interval_method import ci_method_to_color, \
- ConfidenceIntervalMethodFromExtremes
+from extreme_fit.model.result_from_model_fit.result_from_extremes.confidence_interval_method import ci_method_to_color
from root_utils import get_display_name_from_object_type
diff --git a/papers/exceeding_snow_loads/study_visualizer_for_non_stationary_trends.py b/papers/exceeding_snow_loads/study_visualizer_for_non_stationary_trends.py
index 68b8b75c67c6255d376c8f0b10d3b0262b11ed00..0bd3c014d3198c7b8ac0e8d5e731e63d37b6b3df 100644
--- a/papers/exceeding_snow_loads/study_visualizer_for_non_stationary_trends.py
+++ b/papers/exceeding_snow_loads/study_visualizer_for_non_stationary_trends.py
@@ -10,10 +10,10 @@ from experiment.eurocode_data.eurocode_region import C2, C1, E
from experiment.eurocode_data.massif_name_to_departement import massif_name_to_eurocode_region
from experiment.eurocode_data.utils import EUROCODE_QUANTILE, EUROCODE_RETURN_LEVEL_STR, \
YEAR_OF_INTEREST_FOR_RETURN_LEVEL
-from experiment.meteo_france_data.plot.create_shifted_cmap import get_shifted_map, get_colors
+from experiment.meteo_france_data.scm_models_data.visualization.create_shifted_cmap import get_shifted_map, get_colors
from experiment.meteo_france_data.scm_models_data.abstract_extended_study import AbstractExtendedStudy
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 \
+from experiment.meteo_france_data.scm_models_data.visualization.study_visualizer import \
StudyVisualizer
from papers.exceeding_snow_loads.check_mcmc_convergence_for_return_levels.gelman_convergence_test import \
compute_gelman_convergence_value
@@ -22,10 +22,6 @@ from experiment.trend_analysis.abstract_score import MeanScore
from experiment.trend_analysis.univariate_test.extreme_trend_test.abstract_gev_trend_test import AbstractGevTrendTest
from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_one_parameter.gumbel_trend_test_one_parameter import \
GumbelLocationTrendTest, GevStationaryVersusGumbel, GumbelScaleTrendTest, GumbelVersusGumbel
-from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_three_parameters.gev_trend_test_three_parameters import \
- GevLocationAndScaleTrendTestAgainstGumbel
-from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_two_parameters.gev_trend_test_two_parameters import \
- GevLocationAgainstGumbel, GevScaleAgainstGumbel
from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_two_parameters.gumbel_test_two_parameters import \
GumbelLocationAndScaleTrendTest
from extreme_fit.model.margin_model.linear_margin_model.abstract_temporal_linear_margin_model import \
diff --git a/papers/projection_snow_load/main_difference_between_reanalysis_and_simulations.py b/papers/projection_snow_load/main_difference_between_reanalysis_and_simulations.py
index 220143476743f42d53f3659ed7625d00db779a2f..6acff7cecf4608cc6d65e2ad0c350414f4fa715a 100644
--- a/papers/projection_snow_load/main_difference_between_reanalysis_and_simulations.py
+++ b/papers/projection_snow_load/main_difference_between_reanalysis_and_simulations.py
@@ -1,7 +1,7 @@
from experiment.meteo_france_data.adamont_data.ensemble_simulation import EnsembleSimulation
from experiment.meteo_france_data.scm_models_data.crocus.crocus import CrocusSnowLoad3Days, \
CrocusSweTotal
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.study_visualizer import \
+from experiment.meteo_france_data.scm_models_data.visualization.study_visualizer import \
StudyVisualizer
import matplotlib.pyplot as plt
diff --git a/test/test_experiment/test_SCM_study.py b/test/test_experiment/test_SCM_study.py
index e7c14277054d7e926c18caa18a15c58061878c0d..c17c2e6ebe0c0456592d9b40dd48528941bf15fd 100644
--- a/test/test_experiment/test_SCM_study.py
+++ b/test/test_experiment/test_SCM_study.py
@@ -4,13 +4,13 @@ from random import sample
import pandas as pd
-from experiment.meteo_france_data.scm_models_data.cumulated_study import NB_DAYS
+from experiment.meteo_france_data.scm_models_data.safran.cumulated_study import NB_DAYS
from experiment.meteo_france_data.scm_models_data.safran.safran import SafranSnowfall, ExtendedSafranSnowfall, \
SafranTemperature, \
SafranPrecipitation
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.main_study_visualizer import \
+from experiment.meteo_france_data.scm_models_data.visualization.main_study_visualizer import \
study_iterator, study_iterator_global, SCM_STUDIES, ALL_ALTITUDES
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.study_visualizer import \
+from experiment.meteo_france_data.scm_models_data.visualization.study_visualizer import \
StudyVisualizer
from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_one_parameter.gev_trend_test_one_parameter import \
GevLocationTrendTest
diff --git a/test/test_experiment/test_coordinate_sensitivity.py b/test/test_experiment/test_coordinate_sensitivity.py
index f0eb3a4b1856510e7ba81ac1068c39ae6eb6fafd..d66c1713d80119bb07e83e4f4dfbdd118c5ed5d3 100644
--- a/test/test_experiment/test_coordinate_sensitivity.py
+++ b/test/test_experiment/test_coordinate_sensitivity.py
@@ -1,9 +1,9 @@
import unittest
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 \
+from experiment.meteo_france_data.scm_models_data.visualization.main_study_visualizer import \
study_iterator_global
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.study_visualizer import \
+from experiment.meteo_france_data.scm_models_data.visualization.study_visualizer import \
StudyVisualizer
from experiment.trend_analysis.non_stationary_trends import \
ConditionalIndedendenceLocationTrendTest
diff --git a/test/test_experiment/test_hypercube.py b/test/test_experiment/test_hypercube.py
deleted file mode 100644
index 80446d443f02fb818671d13305bda286aa26361e..0000000000000000000000000000000000000000
--- a/test/test_experiment/test_hypercube.py
+++ /dev/null
@@ -1,56 +0,0 @@
-import unittest
-from collections import OrderedDict
-
-import numpy as np
-
-from experiment.meteo_france_data.scm_models_data.safran.safran import SafranSnowfall
-from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.altitude_year_hypercube_visualizer import \
- Altitude_Hypercube_Year_Visualizer
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.main_study_visualizer import \
- study_iterator
-from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.study_visualizer import \
- StudyVisualizer
-from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_one_parameter.gev_trend_test_one_parameter import \
- GevLocationTrendTest
-from extreme_fit.model.utils import set_seed_for_test
-
-
-class TestHypercube(unittest.TestCase):
- DISPLAY = False
-
- def setUp(self) -> None:
- set_seed_for_test(42)
- altitudes = [900, 3000]
-
- visualizers = [StudyVisualizer(study, temporal_non_stationarity=True, verbose=False, multiprocessing=True)
- for study in study_iterator(study_class=SafranSnowfall, only_first_one=False,
- altitudes=altitudes, verbose=self.DISPLAY)]
- self.altitude_to_visualizer = OrderedDict(zip(altitudes, visualizers))
- self.trend_test_class = GevLocationTrendTest
- self.nb_data_reduced_for_speed = 4
-
- # def test_altitude_hypercube_visualizer(self):
- # visualizer = AltitudeHypercubeVisualizer(self.altitude_to_visualizer, save_to_file=False,
- # trend_test_class=self.trend_test_class,
- # nb_data_reduced_for_speed=self.nb_data_reduced_for_speed,
- # verbose=self.DISPLAY)
- # self.df = visualizer.df_hypercube_trend_type
-
- def test_year_altitude_hypercube_visualizer(self):
- visualizer = Altitude_Hypercube_Year_Visualizer(self.altitude_to_visualizer, save_to_file=False,
- trend_test_class=self.trend_test_class,
- nb_data_reduced_for_speed=self.nb_data_reduced_for_speed,
- verbose=self.DISPLAY)
- self.df = visualizer.df_hypercube_trend_type
-
- def tearDown(self) -> None:
- if self.DISPLAY:
- print(self.df)
- # Check that all the rows contain
- nb_non_nan_values_per_row = (~self.df.isnull()).sum(axis=1)
- equality = nb_non_nan_values_per_row.values == np.ones(len(self.df))
- self.assertTrue(equality.all())
-
-
-if __name__ == '__main__':
- unittest.main()
diff --git a/experiment/meteo_france_data/plot/__init__.py b/test/test_extreme_fit/test_function/__init__.py
similarity index 100%
rename from experiment/meteo_france_data/plot/__init__.py
rename to test/test_extreme_fit/test_function/__init__.py
diff --git a/test/test_extreme_fit/test_model/test_margin_function.py b/test/test_extreme_fit/test_function/test_margin_function.py
similarity index 100%
rename from test/test_extreme_fit/test_model/test_margin_function.py
rename to test/test_extreme_fit/test_function/test_margin_function.py
diff --git a/thesis_report/slides.py b/thesis_report/slides.py
deleted file mode 100644
index f6aed506e251817bf36e4f28cc63e1d494e6b5d0..0000000000000000000000000000000000000000
--- a/thesis_report/slides.py
+++ /dev/null
@@ -1,41 +0,0 @@
-import numpy as np
-import matplotlib.pyplot as plt
-
-from extreme_fit.model.utils import r, set_seed_r
-
-
-def snowfall_plot(flip=False):
- set_seed_r(seed=21)
- mean, sd = 200, 50
- lim = 200
- x = np.linspace(max(0, mean-lim), mean+lim, 1000)
- y = r.dnorm(x, mean=mean, sd=sd)
-
- if flip:
- plt.plot(y, x)
- else:
- plt.plot(x, y)
- plt.legend()
- plt.xlabel('snowfall S in mm')
- plt.ylabel('P(S)')
-
- level_to_color = {0.99: 'r',
- 0.5: 'g'}
- for level, color in level_to_color.items():
- quantile = r.qnorm(p=level, mean=mean, sd=sd)
- print(level, color, quantile)
- if flip:
- plt.plot(r.dnorm(quantile, mean=mean, sd=sd), quantile, color + 'o')
- else:
- plt.plot(quantile, r.dnorm(quantile, mean=mean, sd=sd), color + 'o')
-
- # Place the sample
- if not flip:
- n = 50
- plt.plot(r.rnorm(n=n, mean=mean, sd=sd), np.zeros(n), 'ko')
-
- plt.show()
-
-
-if __name__ == '__main__':
- snowfall_plot(flip=True)