def updatefig(i, im, annotate, ani_data, removes):
while removes:
removes.pop(0).remove()
im.set_array(ani_data[i].data)
im.set_cmap(ani_data[i].plot_settings['cmap'])
norm = deepcopy(ani_data[i].plot_settings['norm'])
# The following explicit call is for bugged versions of Astropy's
# ImageNormalize
norm.autoscale_None(ani_data[i].data)
im.set_norm(norm)
if wcsaxes_compat.is_wcsaxes(axes):
im.axes.reset_wcs(ani_data[i].wcs)
wcsaxes_compat.default_wcs_grid(axes)
else:
bl = ani_data[i]._get_lon_lat(ani_data[i].bottom_left_coord)
tr = ani_data[i]._get_lon_lat(ani_data[i].top_right_coord)
x_range = list(
u.Quantity([bl[0],
tr[0]]).to(ani_data[i].spatial_units[0]).value)
y_range = list(
u.Quantity([bl[1],
tr[1]]).to(ani_data[i].spatial_units[1]).value)
im.set_extent(np.concatenate((x_range.value, y_range.value)))
if annotate:
annotate_frame(i)
removes += list(plot_function(fig, axes, ani_data[i]))
def updatefig(self, val, im, slider):
# Remove all the objects that need to be removed from the
# plot
while self.remove_obj:
self.remove_obj.pop(0).remove()
i = int(val)
im.set_array(self.data[i].data)
im.set_cmap(self.mapcube[i].plot_settings['cmap'])
norm = deepcopy(self.mapcube[i].plot_settings['norm'])
# The following explicit call is for bugged versions of Astropy's ImageNormalize
norm.autoscale_None(self.data[i].data)
im.set_norm(norm)
if wcsaxes_compat.is_wcsaxes(im.axes):
im.axes.reset_wcs(self.mapcube[i].wcs)
wcsaxes_compat.default_wcs_grid(im.axes)
# Having this line in means the plot will resize for non-homogenous
# maps. However it also means that if you zoom in on the plot bad
# things happen.
# im.set_extent(self.mapcube[i].xrange + self.mapcube[i].yrange)
if self.annotate:
self._annotate_plot(i)
self.remove_obj += list(self.user_plot_function(self.fig, self.axes, self.mapcube[i]))
def _drawFallback(self, model):
self.figure.clear()
try:
s_map = model.map
plot_preferences = model.plot_preferences
ax = self.figure.add_subplot(111, projection=s_map)
image = ax.imshow(model.data,
cmap=model.cmap,
norm=model.norm,
interpolation=model.interpolation,
origin=model.origin)
if plot_preferences["show_colorbar"]:
self.figure.colorbar(image)
if plot_preferences["show_limb"]:
s_map.draw_limb(axes=ax)
if plot_preferences["contours"]:
levels = sorted(plot_preferences["contours"])
s_map.draw_contours(levels * u.percent, axes=ax)
if plot_preferences["draw_grid"]:
s_map.draw_grid(grid_spacing=10 * u.deg, axes=ax)
if plot_preferences["wcs_grid"] and wcsaxes_compat.is_wcsaxes(ax):
wcsaxes_compat.default_wcs_grid(ax,
units=s_map.spatial_units,
ctypes=s_map.wcs.wcs.ctype)
except Exception as ex:
self.figure.clear()
self.figure.text(0.5,
0.5,
s="Error during rendering data: " + str(ex),
ha="center",
va="center")
def updatefig(i, im, annotate, ani_data, removes):
while removes:
removes.pop(0).remove()
im.set_array(ani_data[i].data)
im.set_cmap(ani_data[i].plot_settings['cmap'])
norm = deepcopy(ani_data[i].plot_settings['norm'])
# The following explicit call is for bugged versions of Astropy's
# ImageNormalize
norm.autoscale_None(ani_data[i].data)
im.set_norm(norm)
if wcsaxes_compat.is_wcsaxes(axes):
im.axes.reset_wcs(ani_data[i].wcs)
wcsaxes_compat.default_wcs_grid(axes)
else:
bl = ani_data[i]._get_lon_lat(ani_data[i].bottom_left_coord)
tr = ani_data[i]._get_lon_lat(ani_data[i].top_right_coord)
x_range = list(u.Quantity([bl[0], tr[0]]).to(ani_data[i].spatial_units[0]).value)
y_range = list(u.Quantity([bl[1], tr[1]]).to(ani_data[i].spatial_units[1]).value)
im.set_extent(np.concatenate((x_range.value, y_range.value)))
if annotate:
annotate_frame(i)
removes += list(plot_function(fig, axes, ani_data[i]))
def updatefig(self, val, im, slider):
# Remove all the objects that need to be removed from the
# plot
while self.remove_obj:
self.remove_obj.pop(0).remove()
i = int(val)
im.set_array(self.data[i].data)
im.set_cmap(self.mapcube[i].plot_settings['cmap'])
norm = deepcopy(self.mapcube[i].plot_settings['norm'])
# The following explicit call is for bugged versions of Astropy's ImageNormalize
norm.autoscale_None(self.data[i].data)
im.set_norm(norm)
if wcsaxes_compat.is_wcsaxes(im.axes):
im.axes.reset_wcs(self.mapcube[i].wcs)
wcsaxes_compat.default_wcs_grid(im.axes)
# Having this line in means the plot will resize for non-homogenous
# maps. However it also means that if you zoom in on the plot bad
# things happen.
# im.set_extent(self.mapcube[i].xrange + self.mapcube[i].yrange)
if self.annotate:
self._annotate_plot(i)
self.remove_obj += list(
self.user_plot_function(self.fig, self.axes, self.mapcube[i]))
def updatefig(i, im, annotate, ani_data, removes):
while removes:
removes.pop(0).remove()
im.set_array(ani_data[i].data)
im.set_cmap(ani_data[i].plot_settings['cmap'])
norm = deepcopy(ani_data[i].plot_settings['norm'])
# The following explicit call is for bugged versions of Astropy's
# ImageNormalize
norm.autoscale_None(ani_data[i].data)
im.set_norm(norm)
if wcsaxes_compat.is_wcsaxes(axes):
im.axes.reset_wcs(ani_data[i].wcs)
wcsaxes_compat.default_wcs_grid(axes,
ani_data[i].spatial_units,
ani_data[i].coordinate_system)
else:
im.set_extent(
np.concatenate(
(ani_data[i].xrange.value, ani_data[i].yrange.value)))
if annotate:
annotate_frame(i)
removes += list(plot_function(fig, axes, ani_data[i]))
def updatefig(i, im, annotate, ani_data, removes):
while removes:
removes.pop(0).remove()
im.set_array(ani_data[i].data)
im.set_cmap(self.maps[i].plot_settings['cmap'])
norm = deepcopy(self.maps[i].plot_settings['norm'])
# The following explicit call is for bugged versions of Astropy's ImageNormalize
norm.autoscale_None(ani_data[i].data)
im.set_norm(norm)
if wcsaxes_compat.is_wcsaxes(axes):
im.axes.reset_wcs(self.maps[i].wcs)
wcsaxes_compat.default_wcs_grid(axes)
else:
im.set_extent(np.concatenate((self.maps[i].xrange.value,
self.maps[i].yrange.value)))
if annotate:
annotate_frame(i)
removes += list(plot_function(fig, axes, self.maps[i]))
def updatefig(self, val, im, slider):
"""
?
Parameters
----------
val : ?
?
im : ?
?
Returns
-------
.. todo::
improve documentation
"""
# Remove all the objects that need to be removed from the
# plot
while self.remove_obj:
self.remove_obj.pop(0).remove()
i = int(val)
im.set_array(self.data[i].data)
im.set_cmap(self.mapcube[i].plot_settings['cmap'])
im.set_norm(self.mapcube[i].plot_settings['norm'])
if wcsaxes_compat.is_wcsaxes(im.axes):
im.axes.reset_wcs(self.mapcube[i].wcs)
wcsaxes_compat.default_wcs_grid(im.axes)
# Having this line in means the plot will resize for non-homogenous
# maps. However it also means that if you zoom in on the plot bad
# things happen.
# im.set_extent(self.mapcube[i].xrange + self.mapcube[i].yrange)
if self.annotate:
self._annotate_plot(i)
self.remove_obj += list(self.user_plot_function(self.fig, self.axes, self.mapcube[i]))
def plot(self, gamma=None, annotate=True, axes=None, **imshow_args):
""" Plots the map object using matplotlib, in a method equivalent
to plt.imshow() using nearest neighbour interpolation.
Parameters
----------
gamma : float
Gamma value to use for the color map
annotate : bool
If true, the data is plotted at it's natural scale; with
title and axis labels.
axes: matplotlib.axes object or None
If provided the image will be plotted on the given axes. Else the
current matplotlib axes will be used.
**imshow_args : dict
Any additional imshow arguments that should be used
when plotting the image.
Examples
--------
#Simple Plot with color bar
>>> aiamap.plot()
>>> plt.colorbar()
#Add a limb line and grid
>>> aia.plot()
>>> aia.draw_limb()
>>> aia.draw_grid()
"""
#Get current axes
if not axes:
axes = wcsaxes_compat.gca_wcs(self.wcs)
# Check that the image is properly oriented
if (not wcsaxes_compat.is_wcsaxes(axes) and
not np.array_equal(self.rotation_matrix, np.matrix(np.identity(2)))):
warnings.warn("This map is not properly oriented. Plot axes may be incorrect",
Warning)
# Normal plot
if annotate:
axes.set_title("{name} {date:{tmf}}".format(name=self.name,
date=parse_time(self.date),
tmf=TIME_FORMAT))
# x-axis label
if self.coordinate_system.x == 'HG':
xlabel = 'Longitude [{lon}]'.format(lon=self.units.x)
else:
xlabel = 'X-position [{xpos}]'.format(xpos=self.units.x)
# y-axis label
if self.coordinate_system.y == 'HG':
ylabel = 'Latitude [{lat}]'.format(lat=self.units.y)
else:
ylabel = 'Y-position [{ypos}]'.format(ypos=self.units.y)
axes.set_xlabel(xlabel)
axes.set_ylabel(ylabel)
cmap = deepcopy(self.cmap)
if gamma is not None:
cmap.set_gamma(gamma)
kwargs = self._mpl_imshow_kwargs(axes, cmap)
kwargs.update(imshow_args)
if self.mask is None:
ret = axes.imshow(self.data, **kwargs)
else:
ret = axes.imshow(np.ma.array(np.asarray(self.data), mask=self.mask), **kwargs)
if wcsaxes_compat.is_wcsaxes(axes):
wcsaxes_compat.default_wcs_grid(axes)
#Set current image (makes colorbar work)
plt.sca(axes)
plt.sci(ret)
return ret
def plot(self, annotate=True, axes=None, title=True, **imshow_kwargs):
""" Plots the map object using matplotlib, in a method equivalent
to plt.imshow() using nearest neighbour interpolation.
Parameters
----------
annotate : bool
If True, the data is plotted at it's natural scale; with
title and axis labels.
axes: `~matplotlib.axes` or None
If provided the image will be plotted on the given axes. Else the
current matplotlib axes will be used.
**imshow_kwargs : dict
Any additional imshow arguments that should be used
when plotting.
Examples
--------
#Simple Plot with color bar
>>> aiamap.plot() # doctest: +SKIP
>>> plt.colorbar() # doctest: +SKIP
#Add a limb line and grid
>>> aia.plot() # doctest: +SKIP
>>> aia.draw_limb() # doctest: +SKIP
>>> aia.draw_grid() # doctest: +SKIP
"""
# Get current axes
if not axes:
axes = wcsaxes_compat.gca_wcs(self.wcs)
# Check that the image is properly oriented
if not wcsaxes_compat.is_wcsaxes(axes) and not np.array_equal(self.rotation_matrix, np.matrix(np.identity(2))):
warnings.warn("This map is not properly oriented. Plot axes may be incorrect", Warning)
# Normal plot
imshow_args = deepcopy(self.plot_settings)
if imshow_args.has_key("title"):
plot_settings_title = imshow_args.pop("title")
else:
plot_settings_title = self.name
if annotate:
if title is True:
title = plot_settings_title
if title:
axes.set_title(title)
# x-axis label
if self.coordinate_system.x == "HG":
xlabel = "Longitude [{lon}]".format(lon=self.units.x)
else:
xlabel = "X-position [{xpos}]".format(xpos=self.units.x)
# y-axis label
if self.coordinate_system.y == "HG":
ylabel = "Latitude [{lat}]".format(lat=self.units.y)
else:
ylabel = "Y-position [{ypos}]".format(ypos=self.units.y)
axes.set_xlabel(xlabel)
axes.set_ylabel(ylabel)
if not wcsaxes_compat.is_wcsaxes(axes):
imshow_args.update({"extent": list(self.xrange.value) + list(self.yrange.value)})
imshow_args.update(imshow_kwargs)
if self.mask is None:
ret = axes.imshow(self.data, **imshow_args)
else:
ret = axes.imshow(np.ma.array(np.asarray(self.data), mask=self.mask), **imshow_args)
if wcsaxes_compat.is_wcsaxes(axes):
wcsaxes_compat.default_wcs_grid(axes)
# Set current image (makes colorbar work)
plt.sca(axes)
plt.sci(ret)
return ret
