From 54462cff0e20727c449b27cf550df6540f67d392 Mon Sep 17 00:00:00 2001
From: Le Roux Erwan <erwan.le-roux@irstea.fr>
Date: Fri, 22 Mar 2019 11:40:13 +0100
Subject: [PATCH] [SCM] add smooth spatio_temporal margin fit
---
.../meteo_france_SCM_study/abstract_study.py | 2 +-
.../meteo_france_SCM_study/safran/safran.py | 2 +-
.../study_visualization/study_visualizer.py | 29 ++++++++-----------
.../abstract_margin_estimator.py | 3 +-
.../abstract_margin_function.py | 24 ++++++++-------
.../coordinates/abstract_coordinates.py | 4 +--
6 files changed, 32 insertions(+), 32 deletions(-)
diff --git a/experiment/meteo_france_SCM_study/abstract_study.py b/experiment/meteo_france_SCM_study/abstract_study.py
index 89a3b59e..b0beb53d 100644
--- a/experiment/meteo_france_SCM_study/abstract_study.py
+++ b/experiment/meteo_france_SCM_study/abstract_study.py
@@ -72,7 +72,7 @@ class AbstractStudy(object):
return year_to_dataset
@property
- def start_year_and_end_year(self) -> Tuple[int, int]:
+ def start_year_and_stop_year(self) -> Tuple[int, int]:
ordered_years = list(self.year_to_dataset_ordered_dict.keys())
return ordered_years[0], ordered_years[-1]
diff --git a/experiment/meteo_france_SCM_study/safran/safran.py b/experiment/meteo_france_SCM_study/safran/safran.py
index 5b8e19bc..98147a32 100644
--- a/experiment/meteo_france_SCM_study/safran/safran.py
+++ b/experiment/meteo_france_SCM_study/safran/safran.py
@@ -28,7 +28,7 @@ class SafranFrequency(Safran):
@property
def variable_name(self):
- return super().variable_name + ' cumulated over {} days'.format(self.nb_consecutive_days)
+ return super().variable_name + ' cumulated over {} day(s)'.format(self.nb_consecutive_days)
def annual_aggregation_function(self, *args, **kwargs):
return np.sum(*args, **kwargs)
diff --git a/experiment/meteo_france_SCM_study/visualization/study_visualization/study_visualizer.py b/experiment/meteo_france_SCM_study/visualization/study_visualization/study_visualizer.py
index d767bc56..67f11692 100644
--- a/experiment/meteo_france_SCM_study/visualization/study_visualization/study_visualizer.py
+++ b/experiment/meteo_france_SCM_study/visualization/study_visualization/study_visualizer.py
@@ -14,12 +14,11 @@ from experiment.utils import average_smoothing_with_sliding_window
from extreme_estimator.estimator.full_estimator.abstract_full_estimator import \
FullEstimatorInASingleStepWithSmoothMargin
from extreme_estimator.estimator.margin_estimator.abstract_margin_estimator import SmoothMarginEstimator
+from extreme_estimator.extreme_models.margin_model.linear_margin_model import LinearAllParametersAllDimsMarginModel
from extreme_estimator.extreme_models.margin_model.margin_function.abstract_margin_function import \
AbstractMarginFunction
from extreme_estimator.extreme_models.margin_model.param_function.param_function import AbstractParamFunction
-from extreme_estimator.extreme_models.margin_model.linear_margin_model import LinearAllParametersAllDimsMarginModel
from extreme_estimator.extreme_models.max_stable_model.abstract_max_stable_model import CovarianceFunction
-from extreme_estimator.extreme_models.max_stable_model.max_stable_models import BrownResnick
from extreme_estimator.margin_fits.abstract_params import AbstractParams
from extreme_estimator.margin_fits.gev.gev_params import GevParams
from extreme_estimator.margin_fits.gev.gevmle_fit import GevMleFit
@@ -69,8 +68,11 @@ class StudyVisualizer(object):
self.subplot_space = 0.5
self.coef_zoom_map = 1
+ # Modify some class attributes
# Remove some assert
AbstractParamFunction.OUT_OF_BOUNDS_ASSERT = False
+ # INCREASE THE TEMPORAL STEPS FOR VISUALIZATION
+ AbstractMarginFunction.VISUALIZATION_TEMPORAL_STEPS = 5
@property
def dataset(self):
@@ -85,8 +87,8 @@ class StudyVisualizer(object):
if self.temporal_non_stationarity:
# Build spatio temporal dataset from a temporal dataset
df_spatial = coordinates.df_spatial_coordinates()
- start, end = self.study.start_year_and_end_year
- nb_steps = end - start + 1
+ start, stop = self.study.start_year_and_stop_year
+ nb_steps = stop - start + 1
coordinates = AbstractSpatioTemporalCoordinates.from_df_spatial_and_nb_steps(df_spatial=df_spatial,
nb_steps=nb_steps,
start=start)
@@ -246,6 +248,7 @@ class StudyVisualizer(object):
def visualize_linear_margin_fit(self, only_first_max_stable=False):
default_covariance_function = CovarianceFunction.powexp
+ margin_class = LinearAllParametersAllDimsMarginModel
plot_name = 'Full Likelihood with Linear marginals and max stable dependency structure'
plot_name += '\n(with {} covariance structure when a covariance is needed)'.format(
str(default_covariance_function).split('.')[-1])
@@ -277,7 +280,6 @@ class StudyVisualizer(object):
# Plot the margin fit independently on the additional row
self.visualize_independent_margin_fits(threshold=None, axes=axes[-1], show=False)
- margin_class = LinearAllParametersAllDimsMarginModel
# Plot the smooth margin only
margin_model = margin_class(coordinates=self.coordinates)
estimator = SmoothMarginEstimator(dataset=self.dataset, margin_model=margin_model)
@@ -300,30 +302,23 @@ class StudyVisualizer(object):
margin_fct._visualization_x_limits = self.study.visualization_x_limits
margin_fct._visualization_y_limits = self.study.visualization_y_limits
margin_fct.mask_2D = self.study.mask_french_alps
+ if self.temporal_non_stationarity:
+ margin_fct.add_future_temporal_steps = True
- axes = margin_fct.visualize_function(show=False, axes=axes, title='') # type: np.ndarray
+ axes = margin_fct.visualize_function(show=False, axes=axes, title='') # type: np.ndarray
if axes.ndim == 1:
self.visualize_contour_and_move_axes_limits(axes)
self.clean_axes_write_title_on_the_left(axes, title)
else:
axes = np.transpose(axes)
- for axes_line in axes:
+ for temporal_step, axes_line in zip(margin_fct.temporal_steps, axes):
self.visualize_contour_and_move_axes_limits(axes_line)
- self.clean_axes_write_title_on_the_left(axes_line, title, left_border=False)
+ self.clean_axes_write_title_on_the_left(axes_line, str(temporal_step) + title, left_border=False)
def visualize_contour_and_move_axes_limits(self, axes):
- def get_lim_array(ax_with_lim_to_measure):
- return np.array([np.array(ax_with_lim_to_measure.get_xlim()), np.array(ax_with_lim_to_measure.get_ylim())])
-
for ax in axes:
- # old_lim = get_lim_array(ax)
self.study.visualize_study(ax, fill=False, show=False)
- # new_lim = get_lim_array(ax)
- # assert 0 <= self.coef_zoom_map <= 1
- # updated_lim = new_lim * self.coef_zoom_map + (1 - self.coef_zoom_map) * old_lim
- # for i, method in enumerate([ax.set_xlim, ax.set_ylim]):
- # method(updated_lim[i, 0], updated_lim[i, 1])
@staticmethod
def clean_axes_write_title_on_the_left(axes, title, left_border=True):
diff --git a/extreme_estimator/estimator/margin_estimator/abstract_margin_estimator.py b/extreme_estimator/estimator/margin_estimator/abstract_margin_estimator.py
index 8ffb8bf2..ab686e12 100644
--- a/extreme_estimator/estimator/margin_estimator/abstract_margin_estimator.py
+++ b/extreme_estimator/estimator/margin_estimator/abstract_margin_estimator.py
@@ -18,6 +18,7 @@ class AbstractMarginEstimator(AbstractEstimator, ABC):
@property
def margin_function_fitted(self) -> AbstractMarginFunction:
assert self._margin_function_fitted is not None, 'Error: estimator has not been fitted'
+ assert isinstance(self._margin_function_fitted, AbstractMarginFunction)
return self._margin_function_fitted
@@ -44,4 +45,4 @@ class SmoothMarginEstimator(AbstractMarginEstimator):
df_coordinates_spat=df_coordinates_spat,
df_coordinates_temp=df_coordinates_temp)
self.extract_fitted_models_from_fitted_params(self.margin_model.margin_function_start_fit, self.fitted_values)
- assert isinstance(self.margin_function_fitted, AbstractMarginFunction)
+
diff --git a/extreme_estimator/extreme_models/margin_model/margin_function/abstract_margin_function.py b/extreme_estimator/extreme_models/margin_model/margin_function/abstract_margin_function.py
index 2428f5fd..a2b5b3d0 100644
--- a/extreme_estimator/extreme_models/margin_model/margin_function/abstract_margin_function.py
+++ b/extreme_estimator/extreme_models/margin_model/margin_function/abstract_margin_function.py
@@ -1,4 +1,4 @@
-from typing import Dict
+from typing import Dict, List
import matplotlib.cm as cm
import matplotlib.pyplot as plt
@@ -37,6 +37,7 @@ class AbstractMarginFunction(object):
self.temporal_step_to_grid_2D = {}
self._grid_1D = None
self.title = None
+ self.add_future_temporal_steps = False
# Visualization limits
self._visualization_x_limits = None
@@ -220,22 +221,25 @@ class AbstractMarginFunction(object):
# Visualization 3D
- def visualize_2D_spatial_1D_temporal(self, gev_param_name=GevParams.LOC, axes=None, show=True,
- add_future_temporal_steps=False):
+ def visualize_2D_spatial_1D_temporal(self, gev_param_name=GevParams.LOC, axes=None, show=True):
if axes is None:
axes = create_adjusted_axes(self.VISUALIZATION_TEMPORAL_STEPS, 1)
assert len(axes) == self.VISUALIZATION_TEMPORAL_STEPS
# Build temporal_steps a list of time steps
- future_temporal_steps = [10, 100] if add_future_temporal_steps else []
- nb_past_temporal_step = self.VISUALIZATION_TEMPORAL_STEPS - len(future_temporal_steps)
- start, stop = self.coordinates.df_temporal_range()
- temporal_steps = list(np.linspace(start, stop, num=nb_past_temporal_step)) + future_temporal_steps
- assert len(temporal_steps) == self.VISUALIZATION_TEMPORAL_STEPS
-
- for ax, temporal_step in zip(axes, temporal_steps):
+ assert len(self.temporal_steps) == self.VISUALIZATION_TEMPORAL_STEPS
+ for ax, temporal_step in zip(axes, self.temporal_steps):
self.visualize_2D(gev_param_name, ax, show=False, temporal_step=temporal_step)
self.set_title(ax, gev_param_name)
if show:
plt.show()
+
+ @cached_property
+ def temporal_steps(self) -> List[int]:
+ future_temporal_steps = [10, 100] if self.add_future_temporal_steps else []
+ nb_past_temporal_step = self.VISUALIZATION_TEMPORAL_STEPS - len(future_temporal_steps)
+ start, stop = self.coordinates.df_temporal_range()
+ temporal_steps = [int(step) for step in np.linspace(start, stop, num=nb_past_temporal_step)]
+ temporal_steps += [stop + step for step in future_temporal_steps]
+ return temporal_steps
diff --git a/spatio_temporal_dataset/coordinates/abstract_coordinates.py b/spatio_temporal_dataset/coordinates/abstract_coordinates.py
index 3d259a95..5b1a0ea1 100644
--- a/spatio_temporal_dataset/coordinates/abstract_coordinates.py
+++ b/spatio_temporal_dataset/coordinates/abstract_coordinates.py
@@ -202,9 +202,9 @@ class AbstractCoordinates(object):
else:
return self.df_coordinates(split).loc[:, self.coordinates_temporal_names].drop_duplicates()
- def df_temporal_range(self, split: Split = Split.all) -> Tuple[float, float]:
+ def df_temporal_range(self, split: Split = Split.all) -> Tuple[int, int]:
df_temporal_coordinates = self.df_temporal_coordinates(split)
- return float(df_temporal_coordinates.min()), float(df_temporal_coordinates.max()),
+ return int(df_temporal_coordinates.min()), int(df_temporal_coordinates.max()),
# Visualization
--
GitLab