def draw_limb(self, axes=None, **kwargs):
"""Draws a circle representing the solar limb
Parameters
----------
axes: matplotlib.axes object or None
Axes to plot limb on or None to use current axes.
Returns
-------
circ: list
A list containing the `matplotlib.patches.Circle` object that
has been added to the axes.
Notes
-----
keyword arguments are passed onto the Circle Patch, see:
http://matplotlib.org/api/artist_api.html#matplotlib.patches.Patch
http://matplotlib.org/api/artist_api.html#matplotlib.patches.Circle
"""
if not axes:
axes = wcsaxes_compat.gca_wcs(self.wcs)
transform = wcsaxes_compat.get_world_transform(axes)
if wcsaxes_compat.is_wcsaxes(axes):
radius = self.rsun_obs.to(u.deg).value
else:
radius = self.rsun_obs.value
c_kw = {'radius':radius,
'fill':False,
'color':'white',
'zorder':100,
'transform': transform
}
c_kw.update(kwargs)
circ = patches.Circle([0, 0], **c_kw)
axes.add_artist(circ)
return [circ]
def draw_grid(self, axes=None, grid_spacing=15*u.deg, **kwargs):
"""Draws a grid over the surface of the Sun
Parameters
----------
axes: matplotlib.axes object or None
Axes to plot limb on or None to use current axes.
grid_spacing: float
Spacing (in degrees) for longitude and latitude grid.
Returns
-------
lines: list
A list of `matplotlib.lines.Line2D` objects that have been plotted.
Notes
-----
keyword arguments are passed onto matplotlib.pyplot.plot
"""
if not axes:
axes = wcsaxes_compat.gca_wcs(self.wcs)
lines = []
# Do not automatically rescale axes when plotting the overlay
axes.set_autoscale_on(False)
transform = wcsaxes_compat.get_world_transform(axes)
XX, YY = np.meshgrid(np.arange(self.data.shape[0]),
np.arange(self.data.shape[1]))
x, y = self.pixel_to_data(XX*u.pix, YY*u.pix)
dsun = self.dsun
b0 = self.heliographic_latitude.to(u.deg).value
l0 = self.heliographic_longitude.to(u.deg).value
units = self.units
#Prep the plot kwargs
plot_kw = {'color':'white',
'linestyle':'dotted',
'zorder':100,
'transform':transform}
plot_kw.update(kwargs)
hg_longitude_deg = np.linspace(-180, 180, num=361) + l0
hg_latitude_deg = np.arange(-90, 90, grid_spacing.to(u.deg).value)
# draw the latitude lines
for lat in hg_latitude_deg:
x, y = wcs.convert_hg_hpc(hg_longitude_deg, lat * np.ones(361),
b0_deg=b0, l0_deg=l0, dsun_meters=dsun,
angle_units=units.x, occultation=True)
valid = np.logical_and(np.isfinite(x), np.isfinite(y))
x = x[valid]
y = y[valid]
if wcsaxes_compat.is_wcsaxes(axes):
x = (x*u.arcsec).to(u.deg).value
y = (y*u.arcsec).to(u.deg).value
lines += axes.plot(x, y, **plot_kw)
hg_longitude_deg = np.arange(-180, 180, grid_spacing.to(u.deg).value) + l0
hg_latitude_deg = np.linspace(-90, 90, num=181)
# draw the longitude lines
for lon in hg_longitude_deg:
x, y = wcs.convert_hg_hpc(lon * np.ones(181), hg_latitude_deg,
b0_deg=b0, l0_deg=l0, dsun_meters=dsun,
angle_units=units[0], occultation=True)
valid = np.logical_and(np.isfinite(x), np.isfinite(y))
x = x[valid]
y = y[valid]
if wcsaxes_compat.is_wcsaxes(axes):
x = (x*u.arcsec).to(u.deg).value
y = (y*u.arcsec).to(u.deg).value
lines += axes.plot(x, y, **plot_kw)
# Turn autoscaling back on.
axes.set_autoscale_on(True)
return lines
