"""
Extensions and helpers for tutorials.
"""
from __future__ import annotations
import numpy as np
import xarray as xr
from matplotlib import pyplot as plt
from numpy.typing import ArrayLike
from .config import settings
from .frame import AzimuthConvention
from .scenes.atmosphere import AbstractHeterogeneousAtmosphere
from .spectral import SpectralIndex
[docs]
def plot_polarfilm(
da: xr.DataArray,
levels: int | ArrayLike = 16,
show_contour: bool = True,
show_azimuth: bool = False,
figsize: tuple = (3, 3),
azimuth_convention: AzimuthConvention | str | None = None,
vmin: float | None = None,
vmax: float | None = None,
theta_max: float = 90.0,
):
"""
Plot film data generated by a hemispherical distant sensor as a polar
contour plot.
Parameters
----------
da : xarray.DataArray
Data array to be plotted.
levels : int or array-like, default: 16
Number of levels on the contour plot.
show_contour : bool, default: True
If ``True``, show contour outlines.
show_azimuth : bool, default: False
[Debug option] If ``True``, show azimuth values as points.
figsize : tuple, default: (3, 3)
Figure size.
azimuth_convention : .AzimuthConvention or str, optional
Azimuth convention of plotted data (will adjust the azimuth of the plot).
vmin, vmax : float, optional
Range of values to plot. If unset, automatically from the data.
theta_max : float, default: 90.0
Maximum value of the azimuth angle on plots.
Returns
-------
matplotlib.Figure
"""
import matplotlib.pyplot as plt
import matplotlib.tri as tri
# Filter grazing angles
da = (
da.where(da.vza <= theta_max)
.dropna("x_index", how="all")
.dropna("y_index", how="all")
)
theta_max = float(da.vza.max())
rscale = 90.0 / theta_max
# Prepare data for plotting
azimuth_convention = (
AzimuthConvention.convert(azimuth_convention)
if azimuth_convention is not None
else settings.AZIMUTH_CONVENTION
)
values = da.transpose("x_index", "y_index").values.ravel()
zeniths = da["vza"].values.ravel() # Degree
azimuths = np.deg2rad(da["vaa"].values).ravel() # Radian
# Create triangulation
x = zeniths * np.cos(azimuths) * rscale
y = zeniths * np.sin(azimuths) * rscale
triangles = tri.Triangulation(x, y)
# Make plot
fig = plt.figure(0, figsize=figsize)
rect = [0, 0, 1, 1]
# -- Main plot in Cartesian coordinates
ax_cartesian = fig.add_axes(rect, aspect="equal")
ax_cartesian.axis("off") # Hide axis
ctr = ax_cartesian.tricontourf(
triangles,
values,
levels=levels,
cmap="viridis",
vmin=vmin,
vmax=vmax,
)
if show_contour:
ax_cartesian.tricontour(
triangles,
values,
levels=levels,
linewidths=0.5,
colors="w",
alpha=0.5,
vmin=vmin,
vmax=vmax,
)
if show_azimuth:
ax_cartesian.scatter(x, y, c=azimuths, cmap="plasma", s=3)
ax_cartesian.set_xlim([-90, 90]) ## Match limits with the full zenith range
ax_cartesian.set_ylim([-90, 90])
## Polar axes
ax_polar = fig.add_axes(rect, polar=True, facecolor="none")
ax_polar.set_rlim([0, theta_max]) # Cover the full zenith value range
ax_polar.grid(False, axis="x")
ax_polar.grid(axis="y", alpha=0.25)
ax_polar.tick_params(axis="y", colors="white")
ax_polar.set_rlabel_position(120)
ax_polar.set_theta_offset(azimuth_convention.value[0])
ax_polar.set_theta_direction(azimuth_convention.value[1])
# Add the color bar (important: both axes must be adjusted)
fig.colorbar(ctr, ax=[ax_cartesian, ax_polar], shrink=0.75, pad=0.15)
return fig
[docs]
def plot_sigma_t(
*atmospheres: AbstractHeterogeneousAtmosphere,
labels: list[str] | None = None,
altitude_extent: tuple[float, float] | None = None,
si: SpectralIndex | None = None,
show: bool = True,
) -> tuple[plt.Figure, plt.Axes]:
"""
Display the extinction coefficient of one or several atmosphere objects for
a single spectral context.
Parameters
----------
*atmospheres : .AbstractHeterogeneousAtmosphere
One or several atmosphere objects for which to plot the extinction
coefficient.
labels : list of strings, optional
Labels associated with the passed atmosphere objects. If unset, no
legend will be added to the plot.
altitude_extent : tuple of float
A (min, max) altitude pair (in km) to which the plot is restricted.
si : .SpectralIndex, optional
The spectral index at which the extinction coefficient is evaluated.
If unset, a default spectral index is created using
:meth:`.SpectralIndex.new`.
show : bool, optional
If ``True``, return ``None`` and display the plot. Otherwise, return a
(``Figure``, ``Axes``) pair.
"""
from matplotlib.ticker import ScalarFormatter
from eradiate.units import to_quantity
if si is None: # If none is found, fall back to the default (550 nm)
si = SpectralIndex.new()
else: # Otherwise, apply conversion protocol
si = SpectralIndex.convert(si)
if labels is None:
label_iter = iter([None for _ in atmospheres])
else:
label_iter = iter(labels)
fig, ax = plt.subplots(1, 1)
with plt.rc_context({"lines.linestyle": ":", "lines.marker": "."}):
for atmosphere in atmospheres:
altitude = to_quantity(atmosphere.eval_radprops(si=si).z_layer).m_as("km")
sigma_t = to_quantity(atmosphere.eval_radprops(si=si).sigma_t).m_as("1/m")
ax.plot(altitude, sigma_t, label=next(label_iter))
formatter = ScalarFormatter(useMathText=True)
formatter.set_powerlimits((-3, 2))
ax.yaxis.set_major_formatter(formatter)
ax.set_ylabel("Extinction coefficient [1/m]")
if labels is not None:
fig.legend(
bbox_to_anchor=(1.0, 0.5),
loc="center left",
borderaxespad=0.0,
)
if altitude_extent is not None:
ax.set_xlim(altitude_extent)
ax.set_xlabel("Altitude [km]")
plt.tight_layout()
if show:
plt.show()
else:
return fig, ax
[docs]
def load_ipython_extension(ipython):
"""
IPython extension for Eradiate tutorials. Should be loaded at the top of the
tutorial notebook.
It sets the Matplotlib style and prints the current date and Eradiate
version as markdown.
See Also
--------
:func:`eradiate.plot.set_style`
Notes
-----
This extension should be loaded using the IPython magic:
.. code::
%load_ext eradiate.tutorials
"""
import datetime
from IPython.display import Markdown, display
from . import __version__
from .plot import set_style
set_style()
xr.set_options(display_expand_data=False)
display(
Markdown(
f"*Last updated: {datetime.datetime.now():%Y-%m-%d %H:%M} "
f"(eradiate v{__version__})*"
)
)
Eradiate