def plot_compsite_map(vlafile,
aiafile,
outfile='',
label='',
pol=0,
chans=[],
chan_mask=None,
x_range=[],
y_range=[],
levels=[0.9],
plotstyle='centroid',
figsize=(10, 8),
figdpi=100,
width=[5, 5],
zorder=1,
maponly=False,
vlaonly=False,
dspecdata={},
thrshd=None,
cmap='jet',
plt_clbar=True,
aiaplt_args={
'axes': None,
'cmap': None,
'vmax': None,
'vmin': None
},
**kwargs):
cmap = cm.get_cmap(cmap)
if aiaplt_args['cmap'] is None:
aiaplt_args.pop('cmap', None)
if outfile:
plt.ioff()
if not vlaonly:
if type(aiafile) != sunpy.map.sources.sdo.AIAMap and type(
aiafile) != sunpy.map.compositemap.CompositeMap:
aiamap = sunpy.map.Map(aiafile)
else:
aiamap = aiafile
if x_range and y_range:
try:
aiamap = aiamap.submap(u.Quantity(x_range * u.arcsec),
u.Quantity(y_range * u.arcsec))
except:
from astropy.coordinates import SkyCoord
bl = SkyCoord(x_range[0] * u.arcsec,
y_range[0] * u.arcsec,
frame=aiamap.coordinate_frame)
tr = SkyCoord(x_range[1] * u.arcsec,
y_range[1] * u.arcsec,
frame=aiamap.coordinate_frame)
aiamap = aiamap.submap(bl, tr)
if type(vlafile) == dict:
if dspecdata:
if dspecdata['stack'] == 'Vstack':
fig = plt.figure(figsize=(9, 12))
plt.subplot(2, 1, 1)
elif dspecdata['stack'] == 'Hstack':
fig = plt.figure(figsize=(20, 8))
plt.subplot(1, 2, 1)
else:
if aiaplt_args['axes'] is None:
fig = plt.figure(figsize=figsize)
plt.subplot()
else:
fig = plt.gcf()
if not vlaonly:
aiamap.plot(**aiaplt_args)
ax1 = plt.gca()
ax1.set_autoscale_on(False)
else:
ax1 = aiaplt_args['axes']
ax1.set_autoscale_on(False)
if label:
ax1.text(0.98,
0.98,
label,
horizontalalignment='right',
verticalalignment='top',
color='white',
transform=ax1.transAxes,
fontsize=14)
clrange = vlafile['ColorMapper']['crange']
if not maponly:
cargsort = np.argsort(np.array(vlafile['ColorMapper']['c']))
cargsort = cargsort[::zorder]
vlafile['x'] = np.array(vlafile['x'])[cargsort]
vlafile['y'] = np.array(vlafile['y'])[cargsort]
vlafile['ColorMapper']['c'] = np.array(
vlafile['ColorMapper']['c'])[cargsort]
vlafile['s'] = np.array(vlafile['s'])[cargsort]
im1 = ax1.scatter(vlafile['x'],
vlafile['y'],
c=vlafile['ColorMapper']['c'],
s=vlafile['s'],
vmin=clrange[0],
vmax=clrange[-1],
cmap=cmap,
**kwargs)
else:
im1 = ax1.scatter([], [],
c=[],
s=[],
vmin=clrange[0],
vmax=clrange[-1],
cmap=cmap,
**kwargs)
if not dspecdata:
if plt_clbar:
cb1 = plt.colorbar(im1, orientation='vertical', ax=ax1)
if type(vlafile) == dict:
if 'title' in vlafile['ColorMapper'].keys():
cb1.set_label(vlafile['ColorMapper']['title'])
else:
cb1.set_label('Frequency [GHz]')
else:
cb1.set_label('Frequency [GHz]')
else:
tim = dspecdata['time']
dt = np.mean(np.diff(tim))
cmapspec = cmap
cmapspec.set_bad('white', 1.0)
normspec = colors.Normalize(vmin=dspecdata['drange'][0],
vmax=dspecdata['drange'][1])
if dspecdata['stack'] == 'Vstack':
plt.subplot(2, 1, 2)
elif dspecdata['stack'] == 'Hstack':
plt.subplot(1, 2, 2)
ax2 = plt.gca()
im2 = plt.pcolormesh(tim,
dspecdata['freq'],
dspecdata['peak'],
cmap=cmapspec,
norm=normspec)
ax2.add_patch(
patches.Rectangle((vlafile['t'], dspecdata['freq'][0]),
dt,
dspecdata['freq'][-1] - dspecdata['freq'][0],
facecolor='black',
edgecolor='white',
alpha=0.3))
ax2.set_xlim(tim[0], tim[-1])
ax2.set_ylim(dspecdata['freq'][0], dspecdata['freq'][-1])
ax2.set_title('Vector Dynamic spectrum')
labels = ax2.get_xticks().tolist()
newlabels = [
Time(lb / 24. / 3600., format='jd').iso.split(' ')[1]
for lb in labels
]
ax2.set_xticklabels(newlabels, rotation=45)
if plt_clbar:
cb1 = plt.colorbar(im1, orientation='vertical', ax=ax1)
if type(vlafile) == dict:
if 'title' in vlafile['ColorMapper'].keys():
cb1.set_label(vlafile['ColorMapper']['title'])
else:
cb1.set_label('Frequency [GHz]')
else:
cb1.set_label('Frequency [GHz]')
cb2 = plt.colorbar(im2, orientation='vertical', ax=ax2)
cb2.set_label('Max intensity [Jy/beam]')
else:
if aiaplt_args['axes'] is None:
fig = plt.figure(figsize=figsize)
plt.subplot()
else:
fig = plt.gcf()
if not vlaonly:
aiamap.plot(**aiaplt_args)
ax1 = plt.gca()
ax1.set_autoscale_on(False)
else:
ax1 = aiaplt_args['axes']
ax1.set_autoscale_on(False)
# ax1.xaxis.set_ticks_position('top')
# ax1.yaxis.set_ticks_position('right')
if label:
ax1.text(0.98,
0.98,
label,
horizontalalignment='right',
verticalalignment='top',
color='white',
transform=ax1.transAxes,
fontsize=14)
# # Prevent the image from being re-scaled while overplotting.
hdulist = fits.open(vlafile)
hdu = hdulist[0]
nfreq = hdu.data.shape[1]
if not maponly:
vladata = hdu.data[pol, 0, :, :]
vlamap = sunpy.map.Map((vladata, hdu.header))
XX, YY = np.meshgrid(np.arange(vlamap.data.shape[1]),
np.arange(vlamap.data.shape[0]))
mapxy = vlamap.pixel_to_data(XX * u.pix, YY * u.pix)
mapx, mapy = mapxy.Tx.value, mapxy.Ty.value
clrange = (hdu.header['CRVAL3'] +
np.arange(nfreq) * hdu.header['CDELT3']) / 1e9
if len(chans) == 0:
chans = range(0, nfreq)
if plotstyle == 'centroid':
pltdata = {'x': [], 'y': [], 's': [], 'c': []}
for idx, chan in enumerate(chans):
vladata = hdu.data[pol, chan, :, :]
if np.nanmax(vladata):
vlamap.data = vladata
maxxy = maxfit(vlamap, mapxy=[mapx, mapy], width=width)
if maxxy:
x, y = maxxy
pltdata['x'].append(x)
pltdata['y'].append(y)
pltdata['c'].append(
(hdu.header['CRVAL3'] +
chan * hdu.header['CDELT3']) / 1e9)
pltdata['s'].append(np.nanmax(vladata))
cargsort = np.argsort(np.array(pltdata['c']))
cargsort = cargsort[::zorder]
pltdata['x'] = np.array(pltdata['x'])[cargsort]
pltdata['y'] = np.array(pltdata['y'])[cargsort]
pltdata['c'] = np.array(pltdata['c'])[cargsort]
pltdata['s'] = np.array(pltdata['s'])[cargsort]
im1 = ax1.scatter(pltdata['x'],
pltdata['y'],
c=pltdata['c'],
s=pltdata['s'],
vmin=clrange[0],
vmax=clrange[-1],
cmap=cmap,
**kwargs)
if plt_clbar:
cb1 = plt.colorbar(im1, orientation='vertical', ax=ax1)
cb1.set_label('Frequency [GHz]')
elif plotstyle == 'contour':
nchan = len(chans)
for idx, chan in enumerate(chans):
if chan_mask is not None:
freq = (hdu.header['CRVAL3'] +
chan * hdu.header['CDELT3']) / 1e9
if freq not in chan_mask:
continue
vladata = hdu.data[pol, chan, :, :]
vlamap = sunpy.map.Map((vladata, hdu.header))
SRC_vlamap_contour = DButil.get_contour_data(mapx,
mapy,
vlamap.data,
levels=levels)
if SRC_vlamap_contour.data['xs']:
for ii, xs in enumerate(SRC_vlamap_contour.data['xs']):
x, y = xs, SRC_vlamap_contour.data['ys'][ii]
if not thrshd or np.nanmax(vladata) >= thrshd:
plt.plot(x,
y,
color=cmap(
int(float(chan) / nfreq * 255)),
zorder=nchan + zorder * idx,
**kwargs)
if plt_clbar:
fig.subplots_adjust(right=0.8)
cax1 = fig.add_axes([0.85, 0.1, 0.01, 0.8])
norm = colors.Normalize(vmin=clrange[0], vmax=clrange[-1])
cb1 = colorbar.ColorbarBase(cax1,
cmap=cmap,
norm=norm,
orientation='vertical')
cb1.set_label('Frequency [GHz]')
try:
cb1.ax.set_aspect(40)
cb1.ax.tick_params(direction='in')
except:
pass
try:
cb2.ax.set_aspect(40)
cb2.ax.tick_params(direction='in')
except:
pass
if aiaplt_args['axes'] is None:
fig.tight_layout(pad=3)
if outfile:
if outfile.endswith('.eps'):
fig.savefig(outfile, format='eps', dpi=int(figdpi))
elif outfile.endswith('.pdf'):
fig.savefig(outfile, format='pdf', dpi=int(figdpi))
elif outfile.endswith('.png'):
fig.savefig(outfile, format='png', dpi=int(figdpi))
elif outfile.endswith('.jpeg'):
fig.savefig(outfile, format='jpeg', dpi=int(figdpi))
elif outfile.endswith('.jpg'):
fig.savefig(outfile, format='jpg', dpi=int(figdpi))
else:
raise ValueError(
'Can not save {}. Provide a filename with extension of eps, pdf, png or jpeg.'
.format(outfile))
def plotmap(vlafile,
aiafile,
outfile='',
label='',
pol=0,
chans=[],
x_range=[],
y_range=[],
levels=[0.9],
plotstyle='centroid',
figsize=(10, 8),
figdpi=100,
zorder=-1,
maponly=False,
dspecdata={},
**kwargs):
import matplotlib.gridspec as gridspec
if outfile:
plt.ioff()
if type(aiafile) != sunpy.map.sources.sdo.AIAMap:
aiamap = sunpy.map.Map(aiafile)
else:
aiamap = aiafile
if x_range and y_range:
aiamap = aiamap.submap(u.Quantity(x_range * u.arcsec),
u.Quantity(y_range * u.arcsec))
if type(vlafile) == dict:
if dspecdata:
if dspecdata['stack'] == 'Vstack':
gs = gridspec.GridSpec(2,
2,
width_ratios=[1, 0.02],
height_ratios=[1, 0.5])
fig = plt.figure(figsize=(9, 12))
elif dspecdata['stack'] == 'Hstack':
gs = gridspec.GridSpec(1,
4,
width_ratios=[1, 0.02, 1.5, 0.02],
height_ratios=[1])
fig = plt.figure(figsize=(18, 8))
ax1 = plt.subplot(gs[0], projection=aiamap)
ax2 = plt.subplot(gs[1])
ax3 = plt.subplot(gs[2])
ax4 = plt.subplot(gs[3])
else:
gs = gridspec.GridSpec(1,
2,
width_ratios=[1, 0.05],
height_ratios=[1])
fig = plt.figure(figsize=figsize)
ax1 = plt.subplot(gs[0], projection=aiamap)
ax2 = plt.subplot(gs[1])
aiamap.plot(axes=ax1)
ax1.set_autoscale_on(False)
if label:
ax1.text(0.98,
0.98,
label,
horizontalalignment='right',
verticalalignment='top',
color='white',
transform=ax1.transAxes,
fontsize=14)
freqs = vlafile['ColorMapper']['crange']
if not maponly:
nchan = len(vlafile['ColorMapper']['c'])
for idx, chan in enumerate(vlafile['ColorMapper']['c']):
x, y = [vlafile['x'][idx], vlafile['y'][idx]] * u.arcsec
s = vlafile['s'][idx]
ax1.scatter(x.to(u.deg),
y.to(u.deg),
transform=ax1.get_transform('world'),
facecolor=cm.jet(
int((chan - freqs[0]) /
(freqs[-1] - freqs[0]) * 255)),
edgecolor='black',
s=s,
zorder=nchan + zorder * idx,
**kwargs)
if not dspecdata:
cmap = cm.jet
norm = colors.Normalize(vmin=freqs[0], vmax=freqs[-1])
cb1 = colorbar.ColorbarBase(ax2,
cmap=cmap,
norm=norm,
orientation='vertical')
if type(vlafile) == dict:
cb1.set_label(vlafile['ColorMapper']['title'])
else:
cb1.set_label('Frequency [GHz]')
else:
tim = dspecdata['time']
dt = np.mean(np.diff(tim))
cmapspec = cm.jet
cmapspec.set_bad('white', 1.0)
normspec = colors.Normalize(vmin=dspecdata['drange'][0],
vmax=dspecdata['drange'][1])
ax3.pcolormesh(tim,
dspecdata['freq'],
dspecdata['peak'],
cmap=cmapspec,
norm=normspec)
ax3.add_patch(
patches.Rectangle((vlafile['t'], dspecdata['freq'][0]),
dt,
dspecdata['freq'][-1] - dspecdata['freq'][0],
facecolor='black',
edgecolor='white',
alpha=0.3))
ax3.set_xlim(tim[0], tim[-1] + dt)
ax3.set_ylim(dspecdata['freq'][0], dspecdata['freq'][-1])
ax3.set_title('Vector Dynamic spectrum')
labels = ax3.get_xticks().tolist()
newlabels = [
Time(lb / 24. / 3600., format='jd').iso.split(' ')[1]
for lb in labels
]
ax3.set_xticklabels(newlabels, rotation=45)
if dspecdata['stack'] == 'Vstack':
fig.tight_layout(h_pad=3, pad=3)
ax3.set_ylabel('Frequency [GHz]')
pos1 = ax1.get_position()
pos2 = ax2.get_position()
pos4 = ax4.get_position()
pos2new = [
pos2.x0 - (1.0 - pos1.x1) / 2, pos2.y0, pos2.width,
pos2.height
]
ax2.set_position(pos2new)
pos4new = [
pos4.x0 - (1.0 - pos1.x1) / 2, pos4.y0, pos4.width,
pos4.height
]
ax4.set_position(pos4new)
elif dspecdata['stack'] == 'Hstack':
fig.tight_layout(w_pad=0, pad=5)
ax3.set_yticklabels([])
pos2 = ax2.get_position()
pos4 = ax4.get_position()
pos2new = [pos2.x0 - 0.03, pos2.y0, pos2.width, pos2.height]
ax2.set_position(pos2new)
pos4new = [pos4.x0 - 0.01, pos4.y0, pos4.width, pos4.height]
ax4.set_position(pos4new)
cmap = cm.jet
norm = colors.Normalize(vmin=freqs[0], vmax=freqs[-1])
cb1 = colorbar.ColorbarBase(ax2,
cmap=cmap,
norm=norm,
orientation='vertical')
cb2 = colorbar.ColorbarBase(ax4,
cmap=cmapspec,
norm=normspec,
orientation='vertical')
if type(vlafile) == dict:
cb1.set_label(vlafile['ColorMapper']['title'])
else:
cb1.set_label('Frequency [GHz]')
cb2.set_label('Max intensity [Jy/beam]')
else:
fig = plt.figure(figsize=figsize)
ax1 = plt.subplot(projection=aiamap)
aiamap.plot()
if label:
ax1.text(0.98,
0.98,
label,
horizontalalignment='right',
verticalalignment='top',
color='white',
transform=ax1.transAxes,
fontsize=14)
# # Prevent the image from being re-scaled while overplotting.
ax1.set_autoscale_on(False)
hdulist = fits.open(vlafile)
hdu = hdulist[0]
if not maponly:
vladata = hdu.data[pol, 0, :, :]
vlamap = sunpy.map.Map((vladata, hdu.header))
XX, YY = np.meshgrid(np.arange(vlamap.data.shape[1]),
np.arange(vlamap.data.shape[0]))
mapx, mapy = vlamap.pixel_to_data(XX * u.pix, YY * u.pix)
mapx, mapy = mapx.value, mapy.value
nfreq = hdu.data[pol, :, :, :].shape[1]
if len(chans) == 0:
chans = range(0, nfreq)
nchan = len(chans)
if plotstyle == 'centroid':
for idx, chan in enumerate(chans):
vladata = hdu.data[pol, chan, :, :]
if np.nanmax(vladata):
vlamap.data = vladata
maxxy = maxfit(vlamap, mapxy=[mapx, mapy])
if maxxy:
x, y = maxxy * u.arcsec
plt.scatter(x.to(u.deg),
y.to(u.deg),
transform=ax1.get_transform('world'),
facecolor=cm.jet(
int(float(chan) / nfreq * 255)),
edgecolor='black',
s=np.nanmax(vladata),
zorder=nchan + zorder * idx,
**kwargs)
elif plotstyle == 'contour':
for idx, chan in enumerate(chans):
vladata = hdu.data[pol, chan, :, :]
vlamap = sunpy.map.Map((vladata, hdu.header))
SRC_vlamap_contour = DButil.get_contour_data(mapx,
mapy,
vlamap.data,
levels=levels)
if SRC_vlamap_contour.data['xs']:
xs = SRC_vlamap_contour.data['xs'][0] * u.arcsec
ys = SRC_vlamap_contour.data['ys'][0] * u.arcsec
plt.plot(xs.to(u.deg),
ys.to(u.deg),
transform=ax1.get_transform('world'),
color=cm.jet(int(float(chan) / nfreq * 255)),
zorder=nchan + zorder * idx,
**kwargs)
freqs = (hdu.header['CRVAL3'] +
np.arange(nfreq) * hdu.header['CDELT3']) / 1e9
fig.subplots_adjust(right=0.8)
cax1 = fig.add_axes([0.85, 0.1, 0.05, 0.8])
cmap = cm.jet
norm = colors.Normalize(vmin=freqs[0], vmax=freqs[-1])
cb1 = colorbar.ColorbarBase(cax1,
cmap=cmap,
norm=norm,
orientation='vertical')
cb1.set_label('Frequency [GHz]')
if outfile:
if outfile.endswith('.eps'):
fig.savefig(outfile, format='eps', dpi=int(figdpi))
elif outfile.endswith('.pdf'):
fig.savefig(outfile, format='pdf', dpi=int(figdpi))
elif outfile.endswith('.png'):
fig.savefig(outfile, format='png', dpi=int(figdpi))
elif outfile.endswith('.jpeg'):
fig.savefig(outfile, format='jpeg', dpi=int(figdpi))
elif outfile.endswith('.jpg'):
fig.savefig(outfile, format='jpg', dpi=int(figdpi))
else:
raise ValueError(
'Can not save {}. Provide a filename with extension of eps, pdf, png or jpeg.'
.format(outfile))
