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# SPDX-FileCopyrightText: Copyright (c) 2025 The torch-harmonics Authors. All rights reserved.
# SPDX-License-Identifier: BSD-3-Clause
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice, this
# list of conditions and the following disclaimer.
#
# 2. Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
#
# 3. Neither the name of the copyright holder nor the names of its
# contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#
import numpy as np
import os
# guarded imports
try:
import matplotlib.pyplot as plt
except ImportError as err:
plt = None
try:
import cartopy
import cartopy.crs as ccrs
except ImportError as err:
cartopy = None
ccrs = None
def check_plotting_dependencies():
if plt is None:
raise ImportError("matplotlib is required for plotting functions. Install it with 'pip install matplotlib'")
if cartopy is None:
raise ImportError("cartopy is required for map plotting. Install it with 'pip install cartopy'")
def get_projection(
projection,
central_latitude=0,
central_longitude=0,
):
"""
Get a cartopy projection object for map plotting.
Parameters
-----------
projection : str
Projection type ("orthographic", "robinson", "platecarree", "mollweide")
central_latitude : float, optional
Central latitude for the projection, by default 0
central_longitude : float, optional
Central longitude for the projection, by default 0
Returns
-------
cartopy.crs.Projection
Cartopy projection object
Raises
------
ValueError
If projection type is not supported
"""
if projection == "orthographic":
proj = ccrs.Orthographic(central_latitude=central_latitude, central_longitude=central_longitude)
elif projection == "robinson":
proj = ccrs.Robinson(central_longitude=central_longitude)
elif projection == "platecarree":
proj = ccrs.PlateCarree(central_longitude=central_longitude)
elif projection == "mollweide":
proj = ccrs.Mollweide(central_longitude=central_longitude)
else:
raise ValueError(f"Unknown projection mode {projection}")
return proj
def plot_sphere(
data, fig=None, projection="robinson", cmap="RdBu", title=None, colorbar=False, coastlines=False, gridlines=False, central_latitude=0, central_longitude=0, lon=None, lat=None, **kwargs
):
"""
Plots a function defined on the sphere using pcolormesh
Parameters
-----------
data : numpy.ndarray or torch.Tensor
Data to plot with shape (nlat, nlon)
fig : matplotlib.figure.Figure, optional
Figure to plot on, by default None (creates new figure)
projection : str, optional
Map projection type, by default "robinson"
cmap : str, optional
Colormap name, by default "RdBu"
title : str, optional
Plot title, by default None
colorbar : bool, optional
Whether to add a colorbar, by default False
coastlines : bool, optional
Whether to add coastlines, by default False
gridlines : bool, optional
Whether to add gridlines, by default False
central_latitude : float, optional
Central latitude for projection, by default 0
central_longitude : float, optional
Central longitude for projection, by default 0
lon : numpy.ndarray, optional
Longitude coordinates, by default None (auto-generated)
lat : numpy.ndarray, optional
Latitude coordinates, by default None (auto-generated)
**kwargs
Additional arguments passed to pcolormesh
Returns
-------
matplotlib.collections.QuadMesh
The plotted image object
"""
# make sure cartopy exist
check_plotting_dependencies()
if fig == None:
fig = plt.figure()
nlat = data.shape[-2]
nlon = data.shape[-1]
if lon is None:
lon = np.linspace(0, 2 * np.pi, nlon + 1)[:-1]
if lat is None:
lat = np.linspace(np.pi / 2.0, -np.pi / 2.0, nlat)
Lon, Lat = np.meshgrid(lon, lat)
# convert radians to degrees
Lon = Lon * 180 / np.pi
Lat = Lat * 180 / np.pi
# get the projection. Latitude is shifted to match plot_sphere
proj = get_projection(projection, central_latitude=central_latitude, central_longitude=central_longitude)
ax = fig.add_subplot(projection=proj)
# contour data over the map.
im = ax.pcolormesh(Lon, Lat, data, cmap=cmap, transform=ccrs.PlateCarree(), antialiased=False, **kwargs)
# add features if requested
if coastlines:
ax.add_feature(cartopy.feature.COASTLINE, edgecolor="white", facecolor="none", linewidth=1.5)
# add colorbar if requested
if colorbar:
plt.colorbar(im)
# add gridlines
if gridlines:
gl = ax.gridlines(crs=ccrs.PlateCarree(), draw_labels=False, linewidth=1, color="gray", alpha=0.6, linestyle="--")
# add title with smaller font
plt.title(title, y=1.05, fontsize=8)
return im
def imshow_sphere(data, fig=None, projection="robinson", title=None, central_latitude=0, central_longitude=0, **kwargs):
"""
Displays an image on the sphere
Parameters
-----------
data : numpy.ndarray or torch.Tensor
Data to display with shape (nlat, nlon)
fig : matplotlib.figure.Figure, optional
Figure to plot on, by default None (creates new figure)
projection : str, optional
Map projection type, by default "robinson"
title : str, optional
Plot title, by default None
central_latitude : float, optional
Central latitude for projection, by default 0
central_longitude : float, optional
Central longitude for projection, by default 0
**kwargs
Additional arguments passed to imshow
Returns
-------
matplotlib.image.AxesImage
The displayed image object
"""
# make sure cartopy exist
check_plotting_dependencies()
if fig == None:
fig = plt.figure()
# get the projection. Latitude is shifted to match plot_sphere
proj = get_projection(projection, central_latitude=central_latitude, central_longitude=central_longitude + 180)
ax = fig.add_subplot(projection=proj)
# contour data over the map.
im = ax.imshow(data, transform=ccrs.PlateCarree(), **kwargs)
# add title
plt.title(title, y=1.05)
return im
# def plot_data(data,
# fig=None,
# cmap="RdBu",
# title=None,
# colorbar=False,
# coastlines=False,
# central_longitude=0,
# lon=None,
# lat=None,
# **kwargs):
# if fig == None:
# fig = plt.figure()
# nlat = data.shape[-2]
# nlon = data.shape[-1]
# if lon is None:
# lon = np.linspace(0, 2*np.pi, nlon+1)[:-1]
# if lat is None:
# lat = np.linspace(np.pi/2., -np.pi/2., nlat)
# Lon, Lat = np.meshgrid(lon, lat)
# proj = ccrs.Robinson(central_longitude=central_longitude)
# # proj = ccrs.Mollweide(central_longitude=central_longitude)
# ax = fig.add_subplot(projection=proj)
# Lon = Lon*180/np.pi
# Lat = Lat*180/np.pi
# # contour data over the map.
# im = ax.pcolormesh(Lon, Lat, data, cmap=cmap, transform=ccrs.PlateCarree(), antialiased=False, **kwargs)
# if coastlines:
# ax.add_feature(cartopy.feature.COASTLINE, edgecolor='white', facecolor='none', linewidth=1.5)
# if colorbar:
# plt.colorbar(im)
# plt.title(title, y=1.05)
# return im
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