def plotresults(img,
ch0_image=True,
rms_image=True,
mean_image=True,
ch0_islands=True,
gresid_image=True,
sresid_image=False,
gmodel_image=True,
smodel_image=False,
pyramid_srcs=False,
source_seds=False,
ch0_flagged=False,
pi_image=False,
psf_major=False,
psf_minor=False,
psf_pa=False,
broadcast=False):
"""Show the results of a fit."""
global img_ch0, img_rms, img_mean, img_gaus_mod, img_shap_mod
global img_gaus_resid, img_shap_resid, pixels_per_beam, pix2sky
global vmin, vmax, vmin_cur, vmax_cur, ch0min, ch0max, img_pi
global low, fig, images, src_list, srcid_cur, sky2pix, markers
global img_psf_maj, img_psf_min, img_psf_pa, do_broadcast, samp_client
global samp_key, samp_gaul_table_url, samp_srl_table_url
if not has_pl:
print "\033[31;1mWARNING\033[0m: Matplotlib not found. Plotting is disabled."
return
if hasattr(img, 'samp_client'):
samp_client = img.samp_client
samp_key = img.samp_key
if hasattr(img, 'samp_srl_table_url'):
samp_srl_table_url = img.samp_srl_table_url
else:
samp_srl_table_url = None
if hasattr(img, 'samp_gaul_table_url'):
samp_gaul_table_url = img.samp_gaul_table_url
else:
samp_gaul_table_url = None
else:
samp_clent = None
samp_key = None
samp_srl_table_url = None
samp_gaul_table_url = None
do_broadcast = broadcast
# Define the images. The images are used both by imshow and by the
# on_press() and coord_format event handlers
pix2sky = img.pix2sky
sky2pix = img.sky2pix
gfactor = 2.0 * N.sqrt(2.0 * N.log(2.0))
pixels_per_beam = 2.0 * N.pi * (img.beam2pix(img.beam)[0] *
img.beam2pix(img.beam)[1]) / gfactor**2
# Construct lists of images, titles, etc.
images = []
titles = []
names = []
markers = []
img_gaus_mod = None # default needed for key press event
img_shap_mod = None # default needed for key press event
if ch0_image:
img_ch0 = img.ch0_arr
images.append(img_ch0)
titles.append('Original (ch0) Image\n(arbitrary logarithmic scale)')
names.append('ch0')
if ch0_islands:
img_ch0 = img.ch0_arr
images.append(img_ch0)
if hasattr(img, 'ngaus'):
if hasattr(img, 'ch0_pi_arr'):
ch0_str = 'Islands (hatched boundaries; red = PI only) and\nGaussians'
else:
ch0_str = 'Islands (hatched boundaries) and\nGaussians'
if hasattr(img, 'atrous_gaussians'):
ch0_str += ' (red = wavelet)'
titles.append(ch0_str)
else:
titles.append('Islands (hatched boundaries)')
names.append('ch0')
if ch0_flagged:
if not hasattr(img, 'ngaus'):
print 'Image was not fit with Gaussians. Skipping display of flagged Gaussians.'
else:
img_ch0 = img.ch0_arr
images.append(img_ch0)
titles.append('Flagged Gaussians')
names.append('ch0')
if pi_image:
if not hasattr(img, 'ch0_pi_arr'):
print 'Polarization module not run. Skipping PI image.'
else:
img_pi = img.ch0_pi_arr
images.append(img_pi)
titles.append('Polarized Intensity Image')
names.append('ch0_pi')
if rms_image:
img_rms = img.rms_arr
images.append(img_rms)
titles.append('Background rms Image')
names.append('rms')
if gresid_image:
if not hasattr(img, 'ngaus'):
print 'Image was not fit with Gaussians. Skipping residual Gaussian image.'
else:
img_gaus_resid = img.resid_gaus_arr
images.append(img_gaus_resid)
titles.append('Gaussian Residual Image')
names.append('gaus_resid')
if gmodel_image:
if not hasattr(img, 'ngaus'):
print 'Image was not fit with Gaussians. Skipping model Gaussian image.'
else:
img_gaus_mod = img.model_gaus_arr
images.append(img_gaus_mod)
titles.append('Gaussian Model Image')
names.append('gaus_mod')
if mean_image:
img_mean = img.mean_arr
images.append(img_mean)
titles.append('Background mean Image')
names.append('mean')
if sresid_image:
if img.opts.shapelet_do == False:
print 'Image was not decomposed into shapelets. Skipping residual shapelet image.'
else:
img_shap_resid = img.ch0_arr - img.model_shap_arr
images.append(img_shap_resid)
titles.append('Shapelet Residual Image')
names.append('shap_resid')
if smodel_image:
if img.opts.shapelet_do == False:
print 'Image was not decomposed into shapelets. Skipping model shapelet image.'
else:
img_shap_mod = img.model_shap_arr
images.append(img_shap_mod)
titles.append('Shapelet Model Image')
names.append('shap_mod')
if source_seds:
if img.opts.spectralindex_do == False:
print 'Source SEDs were not fit. Skipping source SED plots.'
else:
src_list = img.sources
sed_src = get_src(src_list, 0)
if sed_src == None:
print 'No sources found. Skipping source SED plots.'
else:
images.append('seds')
titles.append('')
names.append('seds')
srcid_cur = 0
if pyramid_srcs:
if img.opts.atrous_do == False:
print 'Image was not decomposed into wavelets. Skipping wavelet images.'
else:
# Get the unique j levels and store them. Only make subplots for
# occupied j levels
print 'Pyramidal source plots not yet supported.'
# j_list = []
# for p in img.pyrsrcs:
# for l in p.jlevels:
# j_list.append(l)
# j_set = set(j_list)
# j_with_gaus = list(j_set)
# index_first_waveplot = len(images)
# for i in range(len(j_with_gaus)):
# images.append('wavelets')
# names.append('pyrsrc'+str(i))
if psf_major or psf_minor or psf_pa:
if img.opts.psf_vary_do == False:
print 'PSF variation not calculated. Skipping PSF variation images.'
else:
if psf_major:
img_psf_maj = img.psf_vary_maj_arr * fwsig
images.append(img_psf_maj)
titles.append('PSF Major Axis FWHM (pixels)')
names.append('psf_maj')
if psf_minor:
img_psf_min = img.psf_vary_min_arr * fwsig
images.append(img_psf_min)
titles.append('PSF Minor Axis FWHM (pixels)')
names.append('psf_min')
if psf_pa:
img_psf_pa = img.psf_vary_pa_arr
images.append(img_psf_pa)
titles.append('PSF Pos. Angle FWhM (degrees)')
names.append('psf_pa')
if images == []:
print 'No images to display.'
return
im_mean = img.clipped_mean
im_rms = img.clipped_rms
if img.resid_gaus == None:
low = 1.1 * abs(img.min_value)
else:
low = N.max(
[1.1 * abs(img.min_value), 1.1 * abs(N.nanmin(img.resid_gaus))])
if low <= 0.0:
low = 1E-6
vmin_est = im_mean - im_rms * 5.0 + low
if vmin_est <= 0.0:
vmin = N.log10(low)
else:
vmin = N.log10(vmin_est)
vmax = N.log10(im_mean + im_rms * 30.0 + low)
ch0min = vmin
ch0max = N.log10(img.max_value + low)
vmin_cur = vmin
vmax_cur = vmax
origin = 'lower'
colours = ['m', 'b', 'c', 'g', 'y', 'k'] # reserve red ('r') for wavelets
styles = ['-', '-.', '--']
print '=' * 72
print 'NOTE -- With the mouse pointer in plot window:'
print ' Press "i" ........ : Get integrated flux densities and mean rms'
print ' values for the visible portion of the image'
print ' Press "m" ........ : Change min and max scaling values'
print ' Press "n" ........ : Show / hide island IDs'
print ' Press "0" ........ : Reset scaling to default'
if 'seds' in images:
print ' Press "c" ........ : Change source for SED plot'
if ch0_islands and hasattr(img, 'ngaus'):
print ' Click Gaussian ... : Print Gaussian and source IDs (zoom_rect mode, '
print ' toggled with the "zoom" button and indicated in '
print ' the lower right corner, must be off)'
if 'seds' in images:
print ' The SED plot will also show the chosen source.'
print '_' * 72
if len(images) > 1:
numx = 2
else:
numx = 1
numy = int(N.ceil(float(len(images)) / float(numx)))
fig = pl.figure(figsize=(max(15, 10.0 * float(numy) / float(numx)), 10.0))
fig.canvas.set_window_title('PyBDSM Fit Results for ' + img.filename)
gray_palette = cm.gray
gray_palette.set_bad('k')
for i, image in enumerate(images):
if image != 'wavelets' and image != 'seds':
if i == 0:
cmd = 'ax' + str(i+1) + ' = pl.subplot(' + str(numx) + \
', ' + str(numy) + ', ' + str(i+1) + ')'
else:
cmd = 'ax' + str(i+1) + ' = pl.subplot(' + str(numx) + \
', ' + str(numy) + ', ' + str(i+1) + ', sharex=ax1' + \
', sharey=ax1)'
exec cmd
if 'PSF' in titles[i]:
im = image
else:
im = N.log10(image + low)
if 'Islands' in titles[i]:
island_offsets_x = []
island_offsets_y = []
border_color = []
ax = pl.gca()
for iisl, isl in enumerate(img.islands):
xb, yb = isl.border
if hasattr(isl, '_pi'):
for c in range(len(xb)):
border_color.append('r')
else:
for c in range(len(xb)):
border_color.append('#afeeee')
island_offsets_x += xb.tolist()
island_offsets_y += yb.tolist()
marker = ax.text(N.max(xb) + 2,
N.max(yb),
str(isl.island_id),
color='#afeeee',
clip_on=True)
marker.set_visible(not marker.get_visible())
markers.append(marker)
# draw the gaussians with one colour per source or island
# (if gaul2srl was not run)
if hasattr(img, 'nsrc'):
nsrc = len(isl.sources)
for isrc in range(nsrc):
col = colours[isrc % 6]
style = styles[isrc / 6 % 3]
src = isl.sources[isrc]
for g in src.gaussians:
if hasattr(g, 'valid'):
valid = g.valid
else:
valid = True
if g.jlevel == 0 and valid and g.gaus_num >= 0:
gidx = g.gaus_num
e = Ellipse(xy=g.centre_pix,
width=g.size_pix[0],
height=g.size_pix[1],
angle=g.size_pix[2] + 90.0)
ax.add_artist(e)
e.set_picker(3)
e.set_clip_box(ax.bbox)
e.set_facecolor(col)
e.set_alpha(0.5)
e.gaus_id = gidx
e.src_id = src.source_id
e.jlevel = g.jlevel
e.isl_id = g.island_id
e.tflux = g.total_flux
e.pflux = g.peak_flux
e.centre_sky = g.centre_sky
if len(img.islands) > 0:
island_offsets = zip(N.array(island_offsets_x),
N.array(island_offsets_y))
isl_borders = collections.AsteriskPolygonCollection(
4,
offsets=island_offsets,
color=border_color,
transOffset=ax.transData,
sizes=(10.0, ))
ax.add_collection(isl_borders)
if hasattr(img, 'gaussians'):
for atrg in img.gaussians:
if atrg.jlevel > 0 and atrg.gaus_num >= 0:
col = 'r'
style = '-'
gidx = atrg.gaus_num
e = Ellipse(xy=atrg.centre_pix,
width=atrg.size_pix[0],
height=atrg.size_pix[1],
angle=atrg.size_pix[2] + 90.0)
ax.add_artist(e)
e.set_picker(3)
e.set_clip_box(ax.bbox)
e.set_edgecolor(col)
e.set_facecolor('none')
e.set_alpha(0.8)
e.gaus_id = gidx
e.src_id = atrg.source_id
e.jlevel = atrg.jlevel
e.isl_id = atrg.island_id
e.tflux = atrg.total_flux
e.pflux = atrg.peak_flux
e.centre_sky = atrg.centre_sky
if 'Flagged' in titles[i]:
for iisl, isl in enumerate(img.islands):
ax = pl.gca()
style = '-'
for ig, g in enumerate(isl.fgaul):
col = colours[ig % 6]
ellx, elly = func.drawellipse(g)
gline, = ax.plot(ellx,
elly,
color=col,
linestyle=style,
picker=3)
gline.flag = g.flag
if 'PSF' in titles[i]:
cmd = 'ax' + str(i+1) + ".imshow(N.transpose(im), origin=origin, "\
"interpolation='nearest', cmap=gray_palette)"
else:
cmd = 'ax' + str(i+1) + ".imshow(N.transpose(im), origin=origin, "\
"interpolation='nearest',vmin=vmin, vmax=vmax, cmap=gray_palette)"
exec cmd
cmd = 'ax' + str(i +
1) + '.format_coord = format_coord_' + names[i]
exec cmd
pl.title(titles[i])
elif image == 'seds':
cmd = 'ax' + str(i+1) + ' = pl.subplot(' + str(numx) + \
', ' + str(numy) + ', ' + str(i+1) + ')'
exec cmd
ax = pl.gca()
plot_sed(sed_src, ax)
elif image == 'wavelets':
if i == index_first_waveplot:
for j in range(len(j_with_gaus)):
cmd = 'ax' + str(j+i+1) + ' = pl.subplot(' + str(numx) + \
', ' + str(numy) + ', ' + str(j+i+1) + ', sharex=ax1, '+\
'sharey=ax1)'
exec cmd
pl.title('Pyramidal Sources for\nWavelet Scale J = ' +
str(j_with_gaus[j]))
for pyr in img.pyrsrcs:
for iisl, isl in enumerate(pyr.islands):
jj = pyr.jlevels[iisl]
jindx = j_with_gaus.index(jj)
col = colours[pyr.pyr_id % 6]
ind = N.where(~isl.mask_active)
cmd = "ax" + str(jindx + index_first_waveplot + 1) + \
".plot(ind[0]+isl.origin[0], "\
"ind[1]+isl.origin[1], '.', color=col)"
exec cmd
fig.canvas.mpl_connect('key_press_event', on_press)
fig.canvas.mpl_connect('pick_event', on_pick)
pl.show()
pl.close('all')
def plotresults(img, ch0_image=True, rms_image=True, mean_image=True,
ch0_islands=True, gresid_image=True, sresid_image=False,
gmodel_image=True, smodel_image=False, pyramid_srcs=False,
source_seds=False, ch0_flagged=False, pi_image=False,
psf_major=False, psf_minor=False, psf_pa=False, broadcast=False):
"""Show the results of a fit."""
global img_ch0, img_rms, img_mean, img_gaus_mod, img_shap_mod
global img_gaus_resid, img_shap_resid, pixels_per_beam, pix2sky
global vmin, vmax, vmin_cur, vmax_cur, ch0min, ch0max, img_pi
global low, fig, images, src_list, srcid_cur, sky2pix, markers
global img_psf_maj, img_psf_min, img_psf_pa, do_broadcast, samp_client
global samp_key, samp_gaul_table_url, samp_srl_table_url
if not has_pl:
print "\033[31;1mWARNING\033[0m: Matplotlib not found. Plotting is disabled."
return
if hasattr(img, 'samp_client'):
samp_client = img.samp_client
samp_key = img.samp_key
if hasattr(img, 'samp_srl_table_url'):
samp_srl_table_url = img.samp_srl_table_url
else:
samp_srl_table_url = None
if hasattr(img, 'samp_gaul_table_url'):
samp_gaul_table_url = img.samp_gaul_table_url
else:
samp_gaul_table_url = None
else:
samp_clent = None
samp_key = None
samp_srl_table_url = None
samp_gaul_table_url = None
do_broadcast = broadcast
# Define the images. The images are used both by imshow and by the
# on_press() and coord_format event handlers
pix2sky = img.pix2sky
sky2pix = img.sky2pix
gfactor = 2.0 * N.sqrt(2.0 * N.log(2.0))
pixels_per_beam = 2.0 * N.pi * (img.beam2pix(img.beam)[0]
* img.beam2pix(img.beam)[1]) / gfactor**2
# Construct lists of images, titles, etc.
images = []
titles = []
names = []
markers = []
img_gaus_mod = None # default needed for key press event
img_shap_mod = None # default needed for key press event
if ch0_image:
img_ch0 = img.ch0_arr
images.append(img_ch0)
titles.append('Original (ch0) Image\n(arbitrary logarithmic scale)')
names.append('ch0')
if ch0_islands:
img_ch0 = img.ch0_arr
images.append(img_ch0)
if hasattr(img, 'ngaus'):
if hasattr(img, 'ch0_pi_arr'):
ch0_str = 'Islands (hatched boundaries; red = PI only) and\nGaussians'
else:
ch0_str = 'Islands (hatched boundaries) and\nGaussians'
if hasattr(img, 'atrous_gaussians'):
ch0_str += ' (red = wavelet)'
titles.append(ch0_str)
else:
titles.append('Islands (hatched boundaries)')
names.append('ch0')
if ch0_flagged:
if not hasattr(img, 'ngaus'):
print 'Image was not fit with Gaussians. Skipping display of flagged Gaussians.'
else:
img_ch0 = img.ch0_arr
images.append(img_ch0)
titles.append('Flagged Gaussians')
names.append('ch0')
if pi_image:
if not hasattr(img, 'ch0_pi_arr'):
print 'Polarization module not run. Skipping PI image.'
else:
img_pi = img.ch0_pi_arr
images.append(img_pi)
titles.append('Polarized Intensity Image')
names.append('ch0_pi')
if rms_image:
img_rms = img.rms_arr
images.append(img_rms)
titles.append('Background rms Image')
names.append('rms')
if gresid_image:
if not hasattr(img, 'ngaus'):
print 'Image was not fit with Gaussians. Skipping residual Gaussian image.'
else:
img_gaus_resid = img.resid_gaus_arr
images.append(img_gaus_resid)
titles.append('Gaussian Residual Image')
names.append('gaus_resid')
if gmodel_image:
if not hasattr(img, 'ngaus'):
print 'Image was not fit with Gaussians. Skipping model Gaussian image.'
else:
img_gaus_mod = img.model_gaus_arr
images.append(img_gaus_mod)
titles.append('Gaussian Model Image')
names.append('gaus_mod')
if mean_image:
img_mean = img.mean_arr
images.append(img_mean)
titles.append('Background mean Image')
names.append('mean')
if sresid_image:
if img.opts.shapelet_do == False:
print 'Image was not decomposed into shapelets. Skipping residual shapelet image.'
else:
img_shap_resid = img.ch0_arr - img.model_shap_arr
images.append(img_shap_resid)
titles.append('Shapelet Residual Image')
names.append('shap_resid')
if smodel_image:
if img.opts.shapelet_do == False:
print 'Image was not decomposed into shapelets. Skipping model shapelet image.'
else:
img_shap_mod = img.model_shap_arr
images.append(img_shap_mod)
titles.append('Shapelet Model Image')
names.append('shap_mod')
if source_seds:
if img.opts.spectralindex_do == False:
print 'Source SEDs were not fit. Skipping source SED plots.'
else:
src_list = img.sources
sed_src = get_src(src_list, 0)
if sed_src is None:
print 'No sources found. Skipping source SED plots.'
else:
images.append('seds')
titles.append('')
names.append('seds')
srcid_cur = 0
if pyramid_srcs:
if img.opts.atrous_do == False:
print 'Image was not decomposed into wavelets. Skipping wavelet images.'
else:
# Get the unique j levels and store them. Only make subplots for
# occupied j levels
print 'Pyramidal source plots not yet supported.'
# j_list = []
# for p in img.pyrsrcs:
# for l in p.jlevels:
# j_list.append(l)
# j_set = set(j_list)
# j_with_gaus = list(j_set)
# index_first_waveplot = len(images)
# for i in range(len(j_with_gaus)):
# images.append('wavelets')
# names.append('pyrsrc'+str(i))
if psf_major or psf_minor or psf_pa:
if img.opts.psf_vary_do == False:
print 'PSF variation not calculated. Skipping PSF variation images.'
else:
if psf_major:
img_psf_maj = img.psf_vary_maj_arr*fwsig
images.append(img_psf_maj)
titles.append('PSF Major Axis FWHM (pixels)')
names.append('psf_maj')
if psf_minor:
img_psf_min = img.psf_vary_min_arr*fwsig
images.append(img_psf_min)
titles.append('PSF Minor Axis FWHM (pixels)')
names.append('psf_min')
if psf_pa:
img_psf_pa = img.psf_vary_pa_arr
images.append(img_psf_pa)
titles.append('PSF Pos. Angle FWhM (degrees)')
names.append('psf_pa')
if images == []:
print 'No images to display.'
return
im_mean = img.clipped_mean
im_rms = img.clipped_rms
if img.resid_gaus is None:
low = 1.1*abs(img.min_value)
else:
low = N.max([1.1*abs(img.min_value),1.1*abs(N.nanmin(img.resid_gaus))])
if low <= 0.0:
low = 1E-6
vmin_est = im_mean - im_rms*5.0 + low
if vmin_est <= 0.0:
vmin = N.log10(low)
else:
vmin = N.log10(vmin_est)
vmax = N.log10(im_mean + im_rms*30.0 + low)
ch0min = vmin
ch0max = N.log10(img.max_value + low)
vmin_cur = vmin
vmax_cur = vmax
origin = 'lower'
colours = ['m', 'b', 'c', 'g', 'y', 'k'] # reserve red ('r') for wavelets
styles = ['-', '-.', '--']
print '=' * 72
print 'NOTE -- With the mouse pointer in plot window:'
print ' Press "i" ........ : Get integrated flux densities and mean rms'
print ' values for the visible portion of the image'
print ' Press "m" ........ : Change min and max scaling values'
print ' Press "n" ........ : Show / hide island IDs'
print ' Press "0" ........ : Reset scaling to default'
if 'seds' in images:
print ' Press "c" ........ : Change source for SED plot'
if ch0_islands and hasattr(img, 'ngaus'):
print ' Click Gaussian ... : Print Gaussian and source IDs (zoom_rect mode, '
print ' toggled with the "zoom" button and indicated in '
print ' the lower right corner, must be off)'
if 'seds' in images:
print ' The SED plot will also show the chosen source.'
print '_' * 72
if len(images) > 1:
numx = 2
else:
numx = 1
numy = int(N.ceil(float(len(images))/float(numx)))
fig = pl.figure(figsize=(max(15, 10.0*float(numy)/float(numx)), 10.0))
fig.canvas.set_window_title('PyBDSM Fit Results for '+ img.filename)
gray_palette = cm.gray
gray_palette.set_bad('k')
for i, image in enumerate(images):
if image != 'wavelets' and image != 'seds':
if i == 0:
cmd = 'ax' + str(i+1) + ' = pl.subplot(' + str(numx) + \
', ' + str(numy) + ', ' + str(i+1) + ')'
else:
cmd = 'ax' + str(i+1) + ' = pl.subplot(' + str(numx) + \
', ' + str(numy) + ', ' + str(i+1) + ', sharex=ax1' + \
', sharey=ax1)'
exec cmd
if 'PSF' in titles[i]:
im = image
else:
im = N.log10(image + low)
if 'Islands' in titles[i]:
island_offsets_x = []
island_offsets_y = []
border_color = []
ax = pl.gca()
for iisl, isl in enumerate(img.islands):
xb, yb = isl.border
if hasattr(isl, '_pi'):
for c in range(len(xb)):
border_color.append('r')
else:
for c in range(len(xb)):
border_color.append('#afeeee')
island_offsets_x += xb.tolist()
island_offsets_y += yb.tolist()
marker = ax.text(N.max(xb)+2, N.max(yb), str(isl.island_id),
color='#afeeee', clip_on=True)
marker.set_visible(not marker.get_visible())
markers.append(marker)
# draw the gaussians with one colour per source or island
# (if gaul2srl was not run)
if hasattr(img, 'nsrc'):
nsrc = len(isl.sources)
for isrc in range(nsrc):
col = colours[isrc % 6]
style = styles[isrc/6 % 3]
src = isl.sources[isrc]
for g in src.gaussians:
if hasattr(g, 'valid'):
valid = g.valid
else:
valid = True
if g.jlevel == 0 and valid and g.gaus_num >= 0:
gidx = g.gaus_num
e = Ellipse(xy=g.centre_pix, width=g.size_pix[0],
height=g.size_pix[1], angle=g.size_pix[2]+90.0)
ax.add_artist(e)
e.set_picker(3)
e.set_clip_box(ax.bbox)
e.set_facecolor(col)
e.set_alpha(0.5)
e.gaus_id = gidx
e.src_id = src.source_id
e.jlevel = g.jlevel
e.isl_id = g.island_id
e.tflux = g.total_flux
e.pflux = g.peak_flux
e.centre_sky = g.centre_sky
if len(img.islands) > 0:
island_offsets = zip(N.array(island_offsets_x), N.array(island_offsets_y))
isl_borders = collections.AsteriskPolygonCollection(4, offsets=island_offsets, color=border_color,
transOffset=ax.transData, sizes=(10.0,))
ax.add_collection(isl_borders)
if hasattr(img, 'gaussians'):
for atrg in img.gaussians:
if atrg.jlevel > 0 and atrg.gaus_num >= 0:
col = 'r'
style = '-'
gidx = atrg.gaus_num
e = Ellipse(xy=atrg.centre_pix, width=atrg.size_pix[0], height=atrg.size_pix[1], angle=atrg.size_pix[2]+90.0)
ax.add_artist(e)
e.set_picker(3)
e.set_clip_box(ax.bbox)
e.set_edgecolor(col)
e.set_facecolor('none')
e.set_alpha(0.8)
e.gaus_id = gidx
e.src_id = atrg.source_id
e.jlevel = atrg.jlevel
e.isl_id = atrg.island_id
e.tflux = atrg.total_flux
e.pflux = atrg.peak_flux
e.centre_sky = atrg.centre_sky
if 'Flagged' in titles[i]:
for iisl, isl in enumerate(img.islands):
ax = pl.gca()
style = '-'
for ig, g in enumerate(isl.fgaul):
col = colours[ig % 6]
ellx, elly = func.drawellipse(g)
gline, = ax.plot(ellx, elly, color = col,
linestyle = style, picker=3)
gline.flag = g.flag
if 'PSF' in titles[i]:
cmd = 'ax' + str(i+1) + ".imshow(N.transpose(im), origin=origin, "\
"interpolation='nearest', cmap=gray_palette)"
else:
cmd = 'ax' + str(i+1) + ".imshow(N.transpose(im), origin=origin, "\
"interpolation='nearest',vmin=vmin, vmax=vmax, cmap=gray_palette)"
exec cmd
cmd = 'ax' + str(i+1) + '.format_coord = format_coord_'+names[i]
exec cmd
pl.title(titles[i])
elif image == 'seds':
cmd = 'ax' + str(i+1) + ' = pl.subplot(' + str(numx) + \
', ' + str(numy) + ', ' + str(i+1) + ')'
exec cmd
ax = pl.gca()
plot_sed(sed_src, ax)
elif image == 'wavelets':
if i == index_first_waveplot:
for j in range(len(j_with_gaus)):
cmd = 'ax' + str(j+i+1) + ' = pl.subplot(' + str(numx) + \
', ' + str(numy) + ', ' + str(j+i+1) + ', sharex=ax1, '+\
'sharey=ax1)'
exec cmd
pl.title('Pyramidal Sources for\nWavelet Scale J = ' +
str(j_with_gaus[j]))
for pyr in img.pyrsrcs:
for iisl, isl in enumerate(pyr.islands):
jj = pyr.jlevels[iisl]
jindx = j_with_gaus.index(jj)
col = colours[pyr.pyr_id % 6]
ind = N.where(~isl.mask_active)
cmd = "ax" + str(jindx + index_first_waveplot + 1) + \
".plot(ind[0]+isl.origin[0], "\
"ind[1]+isl.origin[1], '.', color=col)"
exec cmd
fig.canvas.mpl_connect('key_press_event', on_press)
fig.canvas.mpl_connect('pick_event', on_pick)
pl.show()
pl.close('all')
