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Thibault Hallouin authoredInternally, rather than using the multi-dimensional character of tensors to compute all sites and all lead times at once, loops are performed for each site and each lead time, in turn, in order to minimise memory imprint. Although at the moment, the input tensors are expected to feature the sites and lead times dimensions. If memory is an issue, the user can still send smaller tensors with size 1 for those dimensions and recompose multi-sites/multi-lead times output arrays externally.
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from typing import Dict
import matplotlib as mpl
import matplotlib.cm as cm
import matplotlib.colorbar as cbar
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from mpl_toolkits.axes_grid1 import make_axes_locatable
from extreme_estimator.margin_fits.plot.shifted_color_map import shiftedColorMap
from extreme_estimator.margin_fits.extreme_params import ExtremeParams
from extreme_estimator.margin_fits.gev.gev_params import GevParams
from spatio_temporal_dataset.coordinates.abstract_coordinates import AbstractCoordinates
from spatio_temporal_dataset.slicer.split import Split
def plot_extreme_param(ax, gev_param_name, values):
# Load the shifted cmap to center on a middle point
vmin, vmax = np.min(values), np.max(values)
cmap = [plt.cm.coolwarm, plt.cm.bwr, plt.cm.seismic][1]
if gev_param_name == ExtremeParams.SHAPE and vmin < 0:
midpoint = 1 - vmax / (vmax + abs(vmin))
shifted_cmap = shiftedColorMap(cmap, midpoint=midpoint, name='shifted')
else:
shifted_cmap = shiftedColorMap(cmap, midpoint=0.0, name='shifted')
norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax)
divider = make_axes_locatable(ax)
cax = divider.append_axes('right', size='5%', pad=0.05)
cb = cbar.ColorbarBase(cax, cmap=shifted_cmap, norm=norm)
cb.set_label(gev_param_name)
return norm, shifted_cmap
def get_color_rbga(ax, gev_param_name, values):
"""
For some display it was necessary to transform dark blue values into white values
"""
norm, shifted_cmap = plot_extreme_param(ax, gev_param_name, values)
m = cm.ScalarMappable(norm=norm, cmap=shifted_cmap)
colors = [m.to_rgba(value) for value in values]
if gev_param_name != ExtremeParams.SHAPE:
colors = [color if color != (0, 0, 1, 1) else (1, 1, 1, 1) for color in colors]
return colors