From bee5048c0b2065dc2f5f1c9f0819bcc97b25fe18 Mon Sep 17 00:00:00 2001
From: Le Roux Erwan <erwan.le-roux@irstea.fr>
Date: Mon, 18 Mar 2019 18:59:48 +0100
Subject: [PATCH] [SCM] improve visualization of the margin. add a 2D optional
mask & visualization bounds to visualize a 2D margin
---
.../meteo_france_SCM_study/abstract_study.py | 32 +++++++++++++----
.../main_study_visualizer.py | 2 +-
.../study_visualization/study_visualizer.py | 35 ++++++++++++++-----
.../abstract_margin_function.py | 35 +++++++++++++++----
.../param_function/param_function.py | 4 ++-
.../margin_fits/plot/create_shifted_cmap.py | 9 +++--
6 files changed, 91 insertions(+), 26 deletions(-)
diff --git a/experiment/meteo_france_SCM_study/abstract_study.py b/experiment/meteo_france_SCM_study/abstract_study.py
index e46e3f62..927bce4a 100644
--- a/experiment/meteo_france_SCM_study/abstract_study.py
+++ b/experiment/meteo_france_SCM_study/abstract_study.py
@@ -158,14 +158,10 @@ class AbstractStudy(object):
if ax is None:
ax = plt.gca()
- df_massif = pd.read_csv(op.join(self.map_full_path, 'massifsalpes.csv'))
- coord_tuples = [(row_massif['idx'], row_massif[AbstractCoordinates.COORDINATE_X],
- row_massif[AbstractCoordinates.COORDINATE_Y])
- for _, row_massif in df_massif.iterrows()]
- for _, coordinate_id in enumerate(set([t[0] for t in coord_tuples])):
+ for coordinate_id, coords_list in self.idx_to_coords_list.items():
# Retrieve the list of coords (x,y) that define the contour of the massif of id coordinate_id
- coords_list = [coords for idx, *coords in coord_tuples if idx == coordinate_id]
+
# if j == 0:
# mask_outside_polygon(poly_verts=l, ax=ax)
# Plot the contour of the massif
@@ -200,6 +196,30 @@ class AbstractStudy(object):
if show:
plt.show()
+ @property
+ def idx_to_coords_list(self):
+ df_massif = pd.read_csv(op.join(self.map_full_path, 'massifsalpes.csv'))
+ coord_tuples = [(row_massif['idx'], row_massif[AbstractCoordinates.COORDINATE_X],
+ row_massif[AbstractCoordinates.COORDINATE_Y])
+ for _, row_massif in df_massif.iterrows()]
+ all_idxs = set([t[0] for t in coord_tuples])
+ return {idx: [coords for idx_loop, *coords in coord_tuples if idx == idx_loop] for idx in all_idxs}
+
+ @property
+ def all_coords_list(self):
+ all_values = []
+ for e in self.idx_to_coords_list.values():
+ all_values.extend(e)
+ return list(zip(*all_values))
+
+ @property
+ def visualization_x_limits(self):
+ return min(self.all_coords_list[0]), max(self.all_coords_list[0])
+
+ @property
+ def visualization_y_limits(self):
+ return min(self.all_coords_list[1]), max(self.all_coords_list[1])
+
""" Some properties """
@property
diff --git a/experiment/meteo_france_SCM_study/visualization/study_visualization/main_study_visualizer.py b/experiment/meteo_france_SCM_study/visualization/study_visualization/main_study_visualizer.py
index d03ff3df..5b9dbe4f 100644
--- a/experiment/meteo_france_SCM_study/visualization/study_visualization/main_study_visualizer.py
+++ b/experiment/meteo_france_SCM_study/visualization/study_visualization/main_study_visualizer.py
@@ -71,7 +71,7 @@ def normal_visualization():
study_visualizer = StudyVisualizer(study, save_to_file=save_to_file)
# study_visualizer.visualize_independent_margin_fits(threshold=[None, 20, 40, 60][0])
# study_visualizer.visualize_annual_mean_values()
- study_visualizer.visualize_linear_margin_fit(only_first_max_stable=only_first_one)
+ study_visualizer.visualize_linear_margin_fit(only_first_max_stable=None)
def complete_analysis(only_first_one=False):
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 d39d41ab..b6f093e3 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
@@ -13,6 +13,7 @@ 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.param_function.param_function import ParamFunction
from extreme_estimator.extreme_models.margin_model.smooth_margin_model import LinearAllParametersAllDimsMarginModel
from extreme_estimator.extreme_models.max_stable_model.abstract_max_stable_model import CovarianceFunction
from extreme_estimator.margin_fits.abstract_params import AbstractParams
@@ -52,7 +53,10 @@ class StudyVisualizer(object):
else:
self.figsize = (16.0, 10.0)
self.subplot_space = 0.5
- self.coef_zoom_map = 0
+ self.coef_zoom_map = 1
+
+ # Remove some assert
+ ParamFunction.OUT_OF_BOUNDS_ASSERT = False
@property
def observations(self):
@@ -214,6 +218,8 @@ class StudyVisualizer(object):
max_stable_models = load_test_max_stable_models(default_covariance_function=default_covariance_function)
if only_first_max_stable:
max_stable_models = max_stable_models[:1]
+ if only_first_max_stable is None:
+ max_stable_models = []
fig, axes = plt.subplots(len(max_stable_models) + 2, len(GevParams.SUMMARY_NAMES), figsize=self.figsize)
fig.subplots_adjust(hspace=self.subplot_space, wspace=self.subplot_space)
margin_class = LinearAllParametersAllDimsMarginModel
@@ -238,20 +244,33 @@ class StudyVisualizer(object):
estimator.fit()
margin_fct = estimator.margin_function_fitted
+
+ # margin_fct.visualization_x_limits = self.study.
+ margin_fct._visualization_x_limits = self.study.visualization_x_limits
+ margin_fct._visualization_y_limits = self.study.visualization_y_limits
+ # Example of mask 2D
+ mask_2D = np.zeros([margin_fct.resolution, margin_fct.resolution], dtype=bool)
+ lim = 5
+ mask_2D[lim:-lim, lim:-lim] = True
+
+ margin_fct.mask_2D = mask_2D
axes = margin_fct.visualize_function(show=False, axes=axes, title='')
+ self.visualize_contour_and_move_axes_limits(axes)
+ self.clean_axes_write_title_on_the_left(axes, title)
+
+ 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)
+ # 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])
- self.clean_axes_write_title_on_the_left(axes, title)
+ # 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):
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 3ae470f8..166e87b9 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
@@ -15,9 +15,10 @@ from utils import cached_property
class AbstractMarginFunction(object):
""" Class of function mapping points from a space S (could be 1D, 2D,...) to R^3 (the 3 parameters of the GEV)"""
- def __init__(self, coordinates: AbstractCoordinates, resolution=100):
+ def __init__(self, coordinates: AbstractCoordinates):
self.coordinates = coordinates
- self.resolution = resolution
+ self.resolution = 100
+ self.mask_2D = None
# Visualization parameters
self.visualization_axes = None
@@ -31,6 +32,10 @@ class AbstractMarginFunction(object):
self._grid_2D = None
self._grid_1D = None
+ # Visualization limits
+ self._visualization_x_limits = None
+ self._visualization_y_limits = None
+
@property
def x(self):
return self.coordinates.x_coordinates
@@ -145,7 +150,7 @@ class AbstractMarginFunction(object):
ax = plt.gca()
# Special display
- imshow_shifted(ax, gev_param_name, self.grid_2D[gev_param_name], self.x, self.y)
+ imshow_shifted(ax, gev_param_name, self.grid_2D[gev_param_name], self.visualization_extend, self.mask_2D)
# X axis
ax.set_xlabel('coordinate X')
@@ -159,13 +164,29 @@ class AbstractMarginFunction(object):
if show:
plt.show()
+ @property
+ def visualization_x_limits(self):
+ if self._visualization_x_limits is None:
+ return self.x.min(), self.x.max()
+ else:
+ return self._visualization_x_limits
+
+ @property
+ def visualization_y_limits(self):
+ if self._visualization_y_limits is None:
+ return self.y.min(), self.y.max()
+ else:
+ return self._visualization_y_limits
+
+ @property
+ def visualization_extend(self):
+ return self.visualization_x_limits + self.visualization_y_limits
+
@cached_property
def grid_2D(self):
- x = self.x
- y = self.y
grid = []
- for i, xi in enumerate(np.linspace(x.min(), x.max(), self.resolution)):
- for j, yj in enumerate(np.linspace(y.min(), y.max(), self.resolution)):
+ for xi in np.linspace(*self.visualization_x_limits, self.resolution):
+ for yj in np.linspace(*self.visualization_y_limits, self.resolution):
grid.append(self.get_gev_params(np.array([xi, yj])).summary_dict)
grid = {value_name: np.array([g[value_name] for g in grid]).reshape([self.resolution, self.resolution])
for value_name in GevParams.SUMMARY_NAMES}
diff --git a/extreme_estimator/extreme_models/margin_model/param_function/param_function.py b/extreme_estimator/extreme_models/margin_model/param_function/param_function.py
index ad8555ef..f8b882d6 100644
--- a/extreme_estimator/extreme_models/margin_model/param_function/param_function.py
+++ b/extreme_estimator/extreme_models/margin_model/param_function/param_function.py
@@ -4,6 +4,7 @@ from extreme_estimator.extreme_models.margin_model.param_function.linear_coef im
class ParamFunction(object):
+ OUT_OF_BOUNDS_ASSERT = True
def get_gev_param_value(self, coordinate: np.ndarray) -> float:
pass
@@ -31,7 +32,8 @@ class LinearOneAxisParamFunction(ParamFunction):
def get_gev_param_value(self, coordinate: np.ndarray) -> float:
t = coordinate[self.linear_axis]
- assert self.t_min <= t <= self.t_max, 'Out of bounds'
+ if self.OUT_OF_BOUNDS_ASSERT:
+ assert self.t_min <= t <= self.t_max, 'Out of bounds'
return t * self.coef
diff --git a/extreme_estimator/margin_fits/plot/create_shifted_cmap.py b/extreme_estimator/margin_fits/plot/create_shifted_cmap.py
index 128954fa..194466ec 100644
--- a/extreme_estimator/margin_fits/plot/create_shifted_cmap.py
+++ b/extreme_estimator/margin_fits/plot/create_shifted_cmap.py
@@ -44,8 +44,11 @@ def get_color_rbga_shifted(ax, replace_blue_by_white: bool, values: np.ndarray,
return colors
-def imshow_shifted(ax, gev_param_name, values, x, y):
- masked_array = np.ma.masked_where(np.isnan(values), values)
+def imshow_shifted(ax, gev_param_name, values, visualization_extend, mask_2D=None):
+ condition = np.isnan(values)
+ if mask_2D is not None:
+ condition |= mask_2D
+ masked_array = np.ma.masked_where(condition, values)
norm, shifted_cmap = plot_extreme_param(ax, gev_param_name, masked_array)
shifted_cmap.set_bad(color='white')
if gev_param_name != ExtremeParams.SHAPE:
@@ -54,5 +57,5 @@ def imshow_shifted(ax, gev_param_name, values, x, y):
# The right blue corner will be blue (but most of the time, another display will be on top)
masked_array[-1, -1] = value - epsilon
# IMPORTANT: Origin for all the plots is at the bottom left corner
- ax.imshow(masked_array, extent=(x.min(), x.max(), y.min(), y.max()), cmap=shifted_cmap, origin='lower')
+ ax.imshow(masked_array, extent=visualization_extend, cmap=shifted_cmap, origin='lower')
--
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