# -*- coding: utf-8 -*-
"""
Module for map related plotting in ObsPy.
:copyright:
The ObsPy Development Team (devs@obspy.org)
:license:
GNU Lesser General Public License, Version 3
(https://www.gnu.org/copyleft/lesser.html)
"""
import datetime
import warnings
import numpy as np
import matplotlib
from matplotlib.colorbar import Colorbar
from matplotlib.dates import AutoDateFormatter, AutoDateLocator, date2num
from matplotlib import patheffects
from matplotlib.ticker import (FormatStrFormatter, Formatter, FuncFormatter,
MaxNLocator)
from obspy import UTCDateTime
from obspy.core.util import CARTOPY_VERSION
from obspy.core.util.decorator import deprecated_keywords
from obspy.geodetics.base import mean_longitude
if CARTOPY_VERSION and CARTOPY_VERSION >= [0, 12, 0]:
import cartopy
import cartopy.crs as ccrs
import cartopy.feature as cfeature
HAS_CARTOPY = True
else:
HAS_CARTOPY = False
if not HAS_CARTOPY:
msg = ("Cartopy not installed, map plots will not work.")
warnings.warn(msg)
_CARTOPY_RESOLUTIONS = {
'c': '110m',
'l': '110m',
'i': '50m',
'h': '50m',
'f': '10m',
'110m': '110m',
'50m': '50m',
'10m': '10m',
}
if HAS_CARTOPY:
_CARTOPY_FEATURES = {
'110m': (cfeature.BORDERS, cfeature.LAND, cfeature.OCEAN),
}
[docs]@deprecated_keywords({'bmap': None})
def _plot_cartopy_into_axes(
ax, lons, lats, size, color, bmap=None, labels=None,
projection='global', resolution='l', continent_fill_color='0.8',
water_fill_color='1.0', colormap=None, marker="o", title=None,
adjust_aspect_to_colorbar=False, **kwargs): # @UnusedVariable
"""
Creates a (or adds to existing) cartopy plot with a data point scatter
plot in given axes.
See :func:`plot_cartopy` for details on most args/kwargs.
:type ax: :class:`matplotlib.axes.Axes` or
:class:`cartopy.mpl.geoaxes.GeoAxes`
:param ax: Existing matplotlib axes instance, optionally with previous
cartopy plot. If a cartopy GeoAxes is provided, most setup steps will
be skipped.
:type bmap: :class:`matplotlib.axes.Axes`
:param bmap: Deprecated and unused. Whether `ax` is a plain matplotlib Axes
or a cartopy GeoAxes will determine if cartopy related setup on the
axis is skipped (setting up projection etc.).
:rtype: :class:`matplotlib.collections.PathCollection`
:returns: Matplotlib path collection (e.g. to reuse for colorbars).
"""
if not isinstance(ax, cartopy.mpl.geoaxes.GeoAxes):
if projection in ['global', 'ortho']:
pass
elif projection == 'local':
if min(lons) < -150 and max(lons) > 150:
max_lons = max(np.array(lons) % 360)
min_lons = min(np.array(lons) % 360)
else:
max_lons = max(lons)
min_lons = min(lons)
ax.set_extent([min_lons, max_lons, min(lats), max(lats)])
else:
msg = "Projection '%s' not supported." % projection
raise ValueError(msg)
# ax.gridlines()
# ax.coastlines()
# draw coast lines, country boundaries, fill continents.
# ax.set_facecolor(water_fill_color)
# newer matplotlib errors out if called with empty coastline data (no
# coast on map)
# if np.size(getattr(bmap, 'coastsegs', [])):
# bmap.drawcoastlines(color="0.4")
# bmap.drawcountries(color="0.75")
# bmap.fillcontinents(color=continent_fill_color,
# lake_color=water_fill_color)
# draw the edge of the bmap projection region (the projection limb)
# bmap.drawmapboundary(fill_color=water_fill_color)
# draw lat/lon grid lines every 30 degrees.
# bmap.drawmeridians(np.arange(-180, 180, 30))
# bmap.drawparallels(np.arange(-90, 90, 30))
ax.stock_img()
ax.gridlines()
ax.coastlines()
# compute the native bmap projection coordinates for events.
# x, y = bmap(lons, lats)
x, y = (lons, lats)
# plot labels
if labels:
if 100 > len(lons) > 1:
for name, xpt, ypt, _colorpt in zip(labels, x, y, color):
# Check if the point can actually be seen with the current bmap
# projection. The bmap object will set the coordinates to very
# large values if it cannot project a point.
if xpt > 1e25:
continue
ax.text(xpt, ypt, name, weight="heavy",
color="k", zorder=100,
path_effects=[
patheffects.withStroke(linewidth=3,
foreground="white")],
transform=ccrs.Geodetic())
elif len(lons) == 1:
ax.text(x[0], y[0], labels[0], weight="heavy", color="k",
path_effects=[
patheffects.withStroke(linewidth=3,
foreground="white")],
transform=ccrs.Geodetic())
# scatter plot is removing valid x/y points with invalid color value,
# so we plot those points separately.
try:
nan_points = np.isnan(np.array(color, dtype=float))
except ValueError:
# `color' was not a list of values, but a list of colors.
pass
else:
if nan_points.any():
x_ = np.array(x)[nan_points]
y_ = np.array(y)[nan_points]
size_ = np.array(size)[nan_points]
ax.scatter(x_, y_, marker=marker, s=size_, c="0.3",
zorder=10, cmap=None, transform=ccrs.Geodetic())
# Had to change transform to ccrs.PlateCarree, see:
# https://stackoverflow.com/a/13657749/3645626
scatter = ax.scatter(x, y, marker=marker, s=size, c=color, zorder=10,
cmap=colormap, transform=ccrs.PlateCarree(),)
if title:
ax.set_title(title)
return scatter
[docs]def plot_cartopy(lons, lats, size, color, labels=None, projection='global',
resolution='110m', continent_fill_color='0.8',
water_fill_color='1.0', colormap=None, colorbar=None,
marker="o", title=None, colorbar_ticklabel_format=None,
show=True, proj_kwargs=None, ax=None,
**kwargs): # @UnusedVariable
"""
Creates a Cartopy plot with a data point scatter plot.
:type lons: list[float] or tuple(float)
:param lons: Longitudes of the data points.
:type lats: list[float] or tuple(float)
:param lats: Latitudes of the data points.
:type size: float, list[float] or tuple(float)
:param size: Size of the individual points in the scatter plot.
:type color: list[float], tuple(float) or objects that can be
converted to floats, like e.g.
:class:`~obspy.core.utcdatetime.UTCDateTime`)
:param color: Color information of the individual data points to be
used in the specified color map (e.g. origin depths,
origin times).
:type labels: list[str] or tuple[float]
:param labels: Annotations for the individual data points.
:type projection: str, optional
:param projection: The map projection.
Currently supported are:
* ``"global"`` (Will plot the whole world using
:class:`~cartopy.crs.Mollweide`.)
* ``"ortho"`` (Will center around the mean lat/long using
:class:`~cartopy.crs.Orthographic`.)
* ``"local"`` (Will plot around local events using
:class:`~cartopy.crs.AlbersEqualArea`.)
* Any other Cartopy :class:`~cartopy.crs.Projection`. An instance
of this class will be created using the supplied ``proj_kwargs``.
Defaults to "global"
:type resolution: str, optional
:param resolution: Resolution of the boundary database to use. Will be
passed directly to the Cartopy module. Possible values are:
* ``"110m"``
* ``"50m"``
* ``"10m"``
Defaults to ``"110m"``. For compatibility, you may also specify any of
the cartopy resolutions defined in :func:`plot_cartopy`.
:type continent_fill_color: valid matplotlib color, optional
:param continent_fill_color: Color of the continents. Defaults to
``"0.9"`` which is a light gray.
:type water_fill_color: valid matplotlib color, optional
:param water_fill_color: Color of all water bodies.
Defaults to ``"white"``.
:type colormap: str, valid matplotlib colormap, optional
:param colormap: The colormap for color-coding the events as provided
in `color` kwarg.
The event with the smallest `color` property will have the
color of one end of the colormap and the event with the highest
`color` property the color of the other end with all other events
in between.
Defaults to None which will use the default matplotlib colormap.
:type colorbar: bool, optional
:param colorbar: When left `None`, a colorbar is plotted if more than one
object is plotted. Using `True`/`False` the colorbar can be forced
on/off.
:type title: str
:param title: Title above plot.
:type colorbar_ticklabel_format: str or function or
subclass of :class:`matplotlib.ticker.Formatter`
:param colorbar_ticklabel_format: Format string or Formatter used to format
colorbar tick labels.
:type show: bool
:param show: Whether to show the figure after plotting or not. Can be used
to do further customization of the plot before showing it.
:type proj_kwargs: dict
:param proj_kwargs: Keyword arguments to pass to the Cartopy
:class:`~cartopy.crs.Projection`. In this dictionary, you may specify
``central_longitude='auto'`` or ``central_latitude='auto'`` to have
this function calculate the latitude or longitude as it would for other
projections. Some arguments may be ignored if you choose one of the
built-in ``projection`` choices.
:type ax: :class:`matplotlib.axes.Axes` or
:class:`cartopy.mpl.geoaxes.GeoAxes`
:param ax: Existing matplotlib axes instance, optionally with previous
cartopy plot. If a cartopy GeoAxes is provided, most setup steps will
be skipped.
"""
import matplotlib.pyplot as plt
if isinstance(color[0], (datetime.datetime, UTCDateTime)):
datetimeplot = True
color = [date2num(getattr(t, 'datetime', t)) for t in color]
else:
datetimeplot = False
# If ax wasn't specified, look for fig in kwargs
if ax is None and kwargs.get("fig"):
ax = kwargs['fig'].axes[0]
if ax is None:
fig, map_ax, cm_ax, show_colorbar = _basic_setup(
lons=lons, lats=lats, size=size, color=color, labels=None,
projection='global', resolution='110m', continent_fill_color='0.8',
water_fill_color='1.0', colormap=None, colorbar=None, marker="o",
title=None, colorbar_ticklabel_format=None,
proj_kwargs=None)
else:
if isinstance(ax, matplotlib.figure.Figure):
fig = ax
map_ax = fig.axes[0]
else:
fig = ax.figure
map_ax = ax
cm_ax = None
show_colorbar = False
# Plot labels
if labels and len(lons) > 0:
with map_ax.hold_limits():
for name, xpt, ypt, _colorpt in zip(labels, lons, lats, color):
map_ax.text(xpt, ypt, name, weight="heavy", color="k",
zorder=100, transform=ccrs.PlateCarree(),
path_effects=[
patheffects.withStroke(linewidth=3,
foreground="white")])
scatter = map_ax.scatter(lons, lats, marker=marker, s=size, c=color,
zorder=10, cmap=colormap,
transform=ccrs.PlateCarree())
if title:
fig.suptitle(title)
# Only show the colorbar for more than one event.
if show_colorbar:
if colorbar_ticklabel_format is not None:
if isinstance(colorbar_ticklabel_format, str):
formatter = FormatStrFormatter(colorbar_ticklabel_format)
elif hasattr(colorbar_ticklabel_format, '__call__'):
formatter = FuncFormatter(colorbar_ticklabel_format)
elif isinstance(colorbar_ticklabel_format, Formatter):
formatter = colorbar_ticklabel_format
locator = MaxNLocator(5)
else:
if datetimeplot:
locator = AutoDateLocator()
formatter = AutoDateFormatter(locator)
# Compat with old matplotlib versions.
if hasattr(formatter, "scaled"):
formatter.scaled[1 / (24. * 60.)] = '%H:%M:%S'
else:
locator = None
formatter = None
cb = Colorbar(cm_ax, scatter,
orientation='horizontal',
ticks=locator,
format=formatter)
# Compat with old matplotlib versions.
if hasattr(cb, "update_ticks"):
cb.update_ticks()
if show:
plt.show()
return fig
[docs]def _basic_setup(
lons, lats, size, color, labels, projection, resolution,
continent_fill_color, water_fill_color, colormap, colorbar, marker,
title, colorbar_ticklabel_format, proj_kwargs):
import matplotlib.pyplot as plt
fig = plt.figure()
# The colorbar should only be plotted if more then one event is
# present.
if colorbar is not None:
show_colorbar = colorbar
else:
if len(lons) > 1 and hasattr(color, "__len__") and \
not isinstance(color, str):
show_colorbar = True
else:
show_colorbar = False
if projection == "local":
ax_x0, ax_width = 0.10, 0.80
elif projection == "global":
ax_x0, ax_width = 0.01, 0.98
else:
ax_x0, ax_width = 0.05, 0.90
proj_kwargs = proj_kwargs or {}
if projection == 'global':
proj_kwargs['central_longitude'] = np.mean(lons)
proj = ccrs.Mollweide(**proj_kwargs)
elif projection == 'ortho':
proj_kwargs['central_latitude'] = np.mean(lats)
proj_kwargs['central_longitude'] = mean_longitude(lons)
proj = ccrs.Orthographic(**proj_kwargs)
elif projection == 'local':
if min(lons) < -150 and max(lons) > 150:
max_lons = max(np.array(lons) % 360)
min_lons = min(np.array(lons) % 360)
else:
max_lons = max(lons)
min_lons = min(lons)
lat_0 = max(lats) / 2. + min(lats) / 2.
lon_0 = max_lons / 2. + min_lons / 2.
if lon_0 > 180:
lon_0 -= 360
deg2m_lat = 2 * np.pi * 6371 * 1000 / 360
deg2m_lon = deg2m_lat * np.cos(lat_0 / 180 * np.pi)
if len(lats) > 1:
height = (max(lats) - min(lats)) * deg2m_lat
width = (max_lons - min_lons) * deg2m_lon
margin = 0.2 * (width + height)
height += margin
width += margin
else:
height = 2.0 * deg2m_lat
width = 5.0 * deg2m_lon
# Do intelligent aspect calculation for local projection
# adjust to figure dimensions
w, h = fig.get_size_inches()
aspect = w / h
if show_colorbar:
aspect *= 1.2
if width / height < aspect:
width = height * aspect
else:
height = width / aspect
proj_kwargs['central_latitude'] = lat_0
proj_kwargs['central_longitude'] = lon_0
proj_kwargs['standard_parallels'] = [lat_0, lat_0]
proj = ccrs.AlbersEqualArea(**proj_kwargs)
# User-supplied projection.
elif isinstance(projection, type):
if 'central_longitude' in proj_kwargs:
if proj_kwargs['central_longitude'] == 'auto':
proj_kwargs['central_longitude'] = mean_longitude(lons)
if 'central_latitude' in proj_kwargs:
if proj_kwargs['central_latitude'] == 'auto':
proj_kwargs['central_latitude'] = np.mean(lats)
if 'pole_longitude' in proj_kwargs:
if proj_kwargs['pole_longitude'] == 'auto':
proj_kwargs['pole_longitude'] = np.mean(lons)
if 'pole_latitude' in proj_kwargs:
if proj_kwargs['pole_latitude'] == 'auto':
proj_kwargs['pole_latitude'] = np.mean(lats)
proj = projection(**proj_kwargs)
else:
msg = "Projection '%s' not supported." % projection
raise ValueError(msg)
if show_colorbar:
map_ax = fig.add_axes([ax_x0, 0.13, ax_width, 0.77], projection=proj)
cm_ax = fig.add_axes([ax_x0, 0.05, ax_width, 0.05])
plt.sca(map_ax)
else:
ax_y0, ax_height = 0.05, 0.85
if projection == "local":
ax_y0 += 0.05
ax_height -= 0.05
map_ax = fig.add_axes([ax_x0, ax_y0, ax_width, ax_height],
projection=proj)
cm_ax = None
if projection == 'local':
x0, y0 = proj.transform_point(lon_0, lat_0, proj.as_geodetic())
map_ax.set_xlim(x0 - width / 2, x0 + width / 2)
map_ax.set_ylim(y0 - height / 2, y0 + height / 2)
else:
map_ax.set_global()
# Pick features at specified resolution.
resolution = _CARTOPY_RESOLUTIONS[resolution]
try:
borders, land, ocean = _CARTOPY_FEATURES[resolution]
except KeyError:
borders = cfeature.NaturalEarthFeature(
cfeature.BORDERS.category, cfeature.BORDERS.name, resolution,
edgecolor='none', facecolor='none')
land = cfeature.NaturalEarthFeature(
cfeature.LAND.category, cfeature.LAND.name, resolution,
edgecolor='face', facecolor='none')
ocean = cfeature.NaturalEarthFeature(
cfeature.OCEAN.category, cfeature.OCEAN.name, resolution,
edgecolor='face', facecolor='none')
_CARTOPY_FEATURES[resolution] = (borders, land, ocean)
# Draw coast lines, country boundaries, fill continents.
map_ax.set_facecolor(water_fill_color)
map_ax.add_feature(ocean, facecolor=water_fill_color)
map_ax.add_feature(land, facecolor=continent_fill_color)
map_ax.add_feature(borders, edgecolor='0.75')
map_ax.coastlines(resolution=resolution, color='0.4')
# Draw grid lines - TODO: draw_labels=True doesn't work yet.
if projection == 'local':
map_ax.gridlines()
else:
# Draw lat/lon grid lines every 30 degrees.
map_ax.gridlines(xlocs=range(-180, 181, 30), ylocs=range(-90, 91, 30))
return fig, map_ax, cm_ax, show_colorbar
[docs]def plot_map(method, *args, **kwargs):
"""
Creates a map plot with a data point scatter plot.
:type method: str
:param method: Method to use for plotting. Possible values are:
* ``'cartopy'`` to use the Cartopy library. For other arguments, see
the :func:`plot_cartopy` function.
* ``None`` will use the Cartopy library since it is the only supported
method right now.
"""
if method is None:
if HAS_CARTOPY:
return plot_cartopy(*args, **kwargs)
else:
raise ImportError('Cartopy could not be imported.')
elif method == 'cartopy':
if not HAS_CARTOPY:
raise ImportError('Cartopy cannot be imported but was explicitly '
'requested.')
return plot_cartopy(*args, **kwargs)
else:
raise ValueError("The method argument must be either 'None' or "
"'cartopy', not '%s'." % (method, ))