def main(args):
logger.info('Loading data from %s', args.filename)
with fits.open(args.filename) as infile:
flux = infile['flux'].data
detflux = infile['casudet'].data
logger.debug('Computing statistics')
# Remember detflux is in magnitudes
med_mags = np.median(detflux, axis=1)
med_flux = np.median(flux, axis=1)
undetrended_frms = flux.std(axis=1) / med_flux
detrended_frms = detflux.std(axis=1)
logger.info('Plotting to %s', args.output)
with subplots(xlabels=['Magnitude'], ylabels=['Fractional rms']) as (fig, axes):
axes[0].semilogy(med_mags, undetrended_frms, '.', alpha=0.3, label='Raw')
axes[0].semilogy(med_mags, detrended_frms, '.', alpha=0.3, label='CASU')
axes[0].set_xlim(10, 18)
axes[0].set_ylim(1E-3, 1E-1)
axes[0].legend(loc='best')
axes[0].grid(True, which='both')
fig.savefig(args.output, bbox_inches='tight')
def main(args):
if args.verbose:
logger.setLevel('DEBUG')
logger.debug(args)
with fits.open(args.filename) as infile:
imagelist = infile['imagelist'].data
imag = -2.5 * np.log10(infile['flux'].data)
detflux = infile['casudet'].data
mjd = imagelist['tmid']
mjd0 = int(mjd.min())
mjd -= mjd0
normalised_flux = detflux - np.median(detflux, axis=1)[:, np.newaxis]
normalised_raw = imag - np.median(imag, axis=1)[:, np.newaxis]
with subplots() as (fig, axes):
l, med, u = compute_stats(normalised_flux)
err = (u - l) / np.sqrt(normalised_flux.shape[0])
errorbar(axes[0], mjd, med, err, zorder=10)
axes[0].plot(mjd, med, '.r', zorder=11)
ylims = axes[0].get_ylim()
med_detrended = np.median(med)
axes[0].axhline(med_detrended, color='k', ls='--', zorder=50)
axes[0].axhline(med_detrended + 1E-3, color='k', ls=':', zorder=50)
axes[0].axhline(med_detrended - 1E-3, color='k', ls=':', zorder=50)
l, med, u = compute_stats(normalised_raw)
err = (u - l) / np.sqrt(normalised_raw.shape[0])
errorbar(axes[0], mjd, med, err, zorder=5)
axes[0].plot(mjd, med, '.k', zorder=6)
axes[0].set_ylim(*ylims)
for ax in axes:
ax.invert_yaxis()
axes[0].set_ylabel(r'Raw')
axes[0].set_ylabel(r'Post-CASU')
axes[-1].set_xlabel(r'MJD - {}'.format(mjd0))
fig.savefig(args.output)
def main(args):
if args.verbose:
logger.setLevel('DEBUG')
logger.debug(args)
logger.info('Reading autoguider stats from %s', args.filename)
imagelist = fits.getdata(args.filename)
colours = ['#d95f02', '#1b9e77']
mjd = imagelist['tmid']
mjd0 = int(mjd.min())
mjd -= mjd0
keys = ['ag_err', 'ag_corr', 'ag_delt']
axes_labels = ['x', 'y']
full_keys = (a + b for (a, b) in product(keys, axes_labels))
with subplots(6, 1, sharex=True, figsize=(11, 11)) as (fig, axes):
for (key, ax, colour) in zip(full_keys, axes, cycle(colours)):
logger.debug('Plotting %s', key)
ax.plot(mjd, imagelist[key], '.', color=colour)
ax.set_ylabel(key)
axes[-1].set_xlabel(r'MJD - {}'.format(mjd0))
logger.info('Rendering to %s', args.output)
fig.savefig(args.output, bbox_inches='tight')