def profilePlot(outpath, base_name, order_num, profile, peak, centroid,
ext_range, sky_range_top, sky_range_bot, top_bg_mean,
bot_bg_mean, gaussian, snr):
pl.figure('spatial profile', facecolor='white')
pl.cla()
pl.title('spatial profile, ' + base_name + ', order ' + str(order_num),
fontsize=14)
pl.xlabel('relative row (pixels)')
pl.ylabel('flux (counts)')
# set axes limits
yrange = profile.max() - profile.min()
ymin = profile.min() - (0.1 * yrange)
ymax = profile.max() + (0.1 * yrange)
pl.ylim(ymin, ymax)
# set ticks and grid
pl.minorticks_on()
pl.grid(False)
# plot profile
pl.plot(profile, "ko-", mfc='none', ms=3.0, linewidth=1)
# plot vertical line to indicate location of centroid
pl.plot([centroid, centroid], [ymin, profile.max()],
"g-",
linewidth=0.5,
label='peak')
# draw extraction window
wvlh = 0.01 * yrange
ewh = 0.05 * yrange
pl.plot((ext_range[0], ext_range[-1]), (profile.max(), profile.max()),
'r',
linewidth=0.5,
label='extraction window')
pl.plot((ext_range[0], ext_range[0]),
(profile.max() - wvlh, profile.max() + wvlh),
'r',
linewidth=1.5)
pl.plot((ext_range[-1], ext_range[-1]),
(profile.max() - wvlh, profile.max() + wvlh),
'r',
linewidth=1.5)
# draw annotation showing centroid, width and SNR
if gaussian is None:
width = 'unknown'
else:
width = '{:.1f}'.format(abs(gaussian[2]))
aStr = 'centroid = {:.1f} pixels'.format(centroid)
aStr = aStr + '\nwidth = {} pixels'.format(width)
if snr is not None:
aStr = aStr + '\nSNR = {:.1f}'.format(snr)
if peak > (len(profile) / 2):
pl.annotate(aStr, (peak - (len(ext_range) / 2) - 20,
((ymax - ymin) * 3 / 5) + ymin))
else:
pl.annotate(aStr, (peak + (len(ext_range) / 2) + 5,
((ymax - ymin) * 3 / 5) + ymin))
# draw sky windows
if sky_range_top is not None and len(sky_range_top) > 0:
pl.plot((sky_range_top[0], sky_range_top[-1]),
(top_bg_mean, top_bg_mean),
'b',
linewidth=0.5,
label='sky window')
pl.plot((sky_range_top[0], sky_range_top[0]),
(top_bg_mean - wvlh, top_bg_mean + wvlh),
'b',
linewidth=1.5)
pl.plot((sky_range_top[-1], sky_range_top[-1]),
(top_bg_mean - wvlh, top_bg_mean + wvlh),
'b',
linewidth=1.5)
if sky_range_bot is not None and len(sky_range_bot) > 0:
pl.plot((sky_range_bot[0], sky_range_bot[-1]),
(bot_bg_mean, bot_bg_mean),
'b',
linewidth=0.5)
pl.plot((sky_range_bot[0], sky_range_bot[0]),
(bot_bg_mean - wvlh, bot_bg_mean + wvlh),
'b',
linewidth=1.5)
pl.plot((sky_range_bot[-1], sky_range_bot[-1]),
(bot_bg_mean - wvlh, bot_bg_mean + wvlh),
'b',
linewidth=1.5)
# draw best fit Gaussian
if gaussian is not None:
min = np.amin(profile)
if min < 0:
offset = 0
else:
offset = min
pl.plot(image_lib.gaussian(range(len(profile)), gaussian[0],
gaussian[1], gaussian[2]) + offset,
'k--',
linewidth=0.5,
label='Gaussian fit')
pl.legend(loc='best', prop={'size': 8})
fn = constructFileName(outpath, base_name, order_num, 'profile.png')
savePreviewPlot(fn)
pl.close()
log_fn(fn)
return
def profilePlot(outpath, base_name, order_num, profile, peak, centroid,
ext_range, sky_range_top, sky_range_bot, top_bg_mean, bot_bg_mean, gaussian, snr):
pl.figure('spatial profile', facecolor='white')
pl.cla()
pl.title('spatial profile, ' + base_name + ', order ' + str(order_num), fontsize=14)
pl.xlabel('relative row (pixels)')
pl.ylabel('flux (counts)')
# set axes limits
#pl.xlim(0, profile.shape[0])
yrange = profile.max() - profile.min()
ymin = profile.min() - (0.1 * yrange)
ymax = profile.max() + (0.1 * yrange)
pl.ylim(ymin, ymax)
pl.minorticks_on()
pl.grid(False)
pl.plot(profile, "ko-", mfc='none', ms=3.0, linewidth=1)
# pl.plot([centroid, centroid], [ymin, profile[peak]], "g-", linewidth=0.5, label='peak')
pl.plot([centroid, centroid], [ymin, profile.max()], "g-", linewidth=0.5, label='peak')
# draw extraction window
wvlh = 0.01 * yrange;
ewh = 0.05 * yrange
pl.plot((ext_range[0], ext_range[-1]), (profile.max(), profile.max()),
'r', linewidth=0.5, label='extraction window')
pl.plot((ext_range[0], ext_range[0]),
(profile.max() - wvlh, profile.max() + wvlh),
'r', linewidth=1.5)
pl.plot((ext_range[-1], ext_range[-1]),
(profile.max() - wvlh, profile.max() + wvlh),
'r', linewidth=1.5)
if gaussian is None:
width = 'unknown'
else:
width = '{:.1f}'.format(abs(gaussian[2]))
if peak > (len(profile) / 2):
pl.annotate('centroid = {:.1f} pixels\nwidth = {} pixels\nSNR = {:.1f}'.format(
centroid, width, snr),
(peak - (len(ext_range) / 2) - 20, ((ymax - ymin) * 3 / 5) + ymin))
else:
pl.annotate('centroid = {:.1f} pixels\nwidth = {} pixels\nSNR = {:.1f}'.format(
centroid, width, snr),
(peak + (len(ext_range) / 2) + 5, ((ymax - ymin) * 3 / 5) + ymin))
# draw sky windows
if (sky_range_top):
pl.plot((sky_range_top[0], sky_range_top[-1]),
(top_bg_mean, top_bg_mean),
'b', linewidth=0.5, label='sky window')
pl.plot((sky_range_top[0], sky_range_top[0]),
(top_bg_mean - wvlh, top_bg_mean + wvlh),
'b', linewidth=1.5)
pl.plot((sky_range_top[-1], sky_range_top[-1]),
(top_bg_mean - wvlh, top_bg_mean + wvlh),
'b', linewidth=1.5)
if (sky_range_bot):
pl.plot((sky_range_bot[0], sky_range_bot[-1]),
(bot_bg_mean, bot_bg_mean),
'b', linewidth=0.5)
pl.plot((sky_range_bot[0], sky_range_bot[0]),
(bot_bg_mean - wvlh, bot_bg_mean + wvlh),
'b', linewidth=1.5)
pl.plot((sky_range_bot[-1], sky_range_bot[-1]),
(bot_bg_mean - wvlh, bot_bg_mean + wvlh),
'b', linewidth=1.5)
# draw best fit Gaussian
if gaussian is not None:
pl.plot(image_lib.gaussian(range(len(profile)), gaussian[0], gaussian[1], gaussian[2]) + np.amin(profile),
'k--', linewidth=0.5, label='Gaussian fit')
pl.legend(loc='best', prop={'size': 8})
fn = constructFileName(outpath, base_name, order_num, 'profile.png')
pl.savefig(fn)
pl.close()
log_fn(fn)
return