def make_waveform_realization_plot(ax, psr, real, sigma=0.68, *args, **kwargs):
"""
Make a waveform realization plot of signal vs time with
uncertantiy region.
:param ax: axes object instance
:param psr: Pulsar object instance
:param real: Nreal x ntoa array containing individual waveform realizations.
:param sigma: Uncertainty level on waveform
"""
nt = real.shape[1]
xmed, xlow, xhigh = np.zeros(nt), np.zeros(nt), np.zeros(nt)
for ii in range(nt):
rlind = np.flatnonzero(real[:, ii])
tmp, xmed[ii] = bu.confinterval(real[rlind, ii],
onesided=True,
sigma=0.5)
xlow[ii], xhigh[ii] = bu.confinterval(real[rlind, ii],
sigma=sigma,
type='minArea')
idx = np.argsort(psr.toas)
ax.fill_between(convert_mjd_to_greg(psr.toas[idx] / 86400),
xlow[idx] * 1e6, xhigh[idx] * 1e6, **kwargs)
ax.plot(convert_mjd_to_greg(psr.toas[idx] / 86400),
xmed[idx] * 1e6,
ls='--',
lw=1.5,
**kwargs)
def make_dm_waveform_realization_plot(ax,
psr,
qreal,
incDM=True,
*args,
**kwargs):
"""
Make a waveform realization plot of DM vs time with
uncertantiy region.
:param ax: axes object instance
:param psr: Pulsar object instance
:param qreal: Nreal x npar array containing individual quadratic posteriors
:param incDM: Boolean whether or not DM is in timing model or in noise model
"""
dmconst = 2.41e-4
#ntmpars = len(psr.ptmdescription)
ntmpars = psr.Mmat_reduced.shape[1]
nf = psr.Fmat.shape[1]
nfdm = len(psr.Fdmfreqs)
idd = np.arange(ntmpars + nf, ntmpars + nf + nfdm)
idx = np.argsort(psr.toas)
nt = len(idx)
dmsig = np.zeros((qreal.shape[0], nt))
for ii in range(qreal.shape[0]):
if incDM:
id1 = list(psr.newdes).index('DM1')
dmsig[ii, :] = psr.Ttmat[:,
id1] * qreal[ii,
id1] * dmconst * psr.freqs**2
id2 = list(psr.newdes).index('DM2')
dmsig[ii, :] += psr.Ttmat[:, id2] * qreal[
ii, id2] * dmconst * psr.freqs**2
dmsig[ii, :] += np.dot(psr.Fdmmat, qreal[ii, idd])
dmsig[ii, :] -= dmsig[ii, :].mean()
else:
idd = np.array([
ct for ct, pp in enumerate(psr.ptmdescription) if 'DMX' in pp
])
dmsig[ii, :] = np.dot(psr.Ttmat[:, idd],
qreal[ii, idd]) * dmconst * psr.freqs**2
xmed, xlow, xhigh = np.zeros(nt), np.zeros(nt), np.zeros(nt)
for ii in range(nt):
rlind = np.flatnonzero(dmsig[:, ii])
tmp, xmed[ii] = bu.confinterval(dmsig[rlind, ii],
onesided=True,
sigma=0.5)
xlow[ii], xhigh[ii] = bu.confinterval(dmsig[rlind, ii],
sigma=0.68,
type='minArea')
ax.fill_between(convert_mjd_to_greg(psr.toas[idx] / 86400),
xlow[idx] * 1e3, xhigh[idx] * 1e3, **kwargs)
ax.plot(convert_mjd_to_greg(psr.toas[idx] / 86400),
(xmed[idx] - xmed[idx].mean()) * 1e3,
ls='--',
lw=1.5,
color='k')
def make_spectrum_realization_plot(ax,
f,
psd,
sigma=0.68,
plot_median=True,
use_bars=False,
*args,
**kwargs):
"""
Make a waveform realization plot of signal vs time with
uncertantiy region.
:param ax: axes object instance
:param model: PAL2 Model class
:param real: Nreal x nf array containing individual spectrum realizations.
:param sigma: Uncertainty level on waveform
:param plot_median: Plot the median spectrum
:param use_bars: Use error bars instead of fill_between
"""
nt = len(f)
xmed, xlow, xhigh = np.zeros(nt), np.zeros(nt), np.zeros(nt)
for ii in range(nt):
tmp, xmed[ii] = bu.confinterval(psd[:, ii], onesided=True, sigma=0.5)
xlow[ii], xhigh[ii] = bu.confinterval(psd[:, ii],
sigma=sigma,
type='minArea')
#print xlow, xhigh
if use_bars:
ymean = psd.mean(axis=0)
ylow = np.log10(10**ymean - 10**xlow)
yhigh = np.log10(10**xhigh - 10**ymean)
yerr = np.vstack((ylow, yhigh))
ax.errorbar(f, 10**ymean, yerr=10**yerr, fmt='o', capsize=0, **kwargs)
else:
ax.fill_between(f, 10**xlow, 10**xhigh, **kwargs)
if plot_median:
ax.plot(f, 10**xmed, ls='--', lw=1.5, color='k')
ax.set_xscale('log')
ax.set_yscale('log')
ax.set_ylim(10**xlow.min() / 2, 10**xhigh.max() * 2)
df = f[1] - f[0]
ax.set_xlim(f.min() - df, f.max() + df)
ax.grid(which='both')
def make_dm_waveform_realization_plot(ax, psr, qreal, incDM=True, *args, **kwargs):
"""
Make a waveform realization plot of DM vs time with
uncertantiy region.
:param ax: axes object instance
:param psr: Pulsar object instance
:param qreal: Nreal x npar array containing individual quadratic posteriors
:param incDM: Boolean whether or not DM is in timing model or in noise model
"""
dmconst = 2.41e-4
# ntmpars = len(psr.ptmdescription)
ntmpars = psr.Mmat_reduced.shape[1]
nf = psr.Fmat.shape[1]
nfdm = len(psr.Fdmfreqs)
idd = np.arange(ntmpars + nf, ntmpars + nf + nfdm)
idx = np.argsort(psr.toas)
nt = len(idx)
dmsig = np.zeros((qreal.shape[0], nt))
for ii in range(qreal.shape[0]):
if incDM:
id1 = list(psr.newdes).index("DM1")
dmsig[ii, :] = psr.Ttmat[:, id1] * qreal[ii, id1] * dmconst * psr.freqs ** 2
id2 = list(psr.newdes).index("DM2")
dmsig[ii, :] += psr.Ttmat[:, id2] * qreal[ii, id2] * dmconst * psr.freqs ** 2
dmsig[ii, :] += np.dot(psr.Fdmmat, qreal[ii, idd])
dmsig[ii, :] -= dmsig[ii, :].mean()
else:
idd = np.array([ct for ct, pp in enumerate(psr.ptmdescription) if "DMX" in pp])
dmsig[ii, :] = np.dot(psr.Ttmat[:, idd], qreal[ii, idd]) * dmconst * psr.freqs ** 2
xmed, xlow, xhigh = np.zeros(nt), np.zeros(nt), np.zeros(nt)
for ii in range(nt):
rlind = np.flatnonzero(dmsig[:, ii])
tmp, xmed[ii] = bu.confinterval(dmsig[rlind, ii], onesided=True, sigma=0.5)
xlow[ii], xhigh[ii] = bu.confinterval(dmsig[rlind, ii], sigma=0.68, type="minArea")
ax.fill_between(convert_mjd_to_greg(psr.toas[idx] / 86400), xlow[idx] * 1e3, xhigh[idx] * 1e3, **kwargs)
ax.plot(
convert_mjd_to_greg(psr.toas[idx] / 86400), (xmed[idx] - xmed[idx].mean()) * 1e3, ls="--", lw=1.5, color="k"
)
def make_waveform_realization_plot(ax, psr, real, sigma=0.68, *args, **kwargs):
"""
Make a waveform realization plot of signal vs time with
uncertantiy region.
:param ax: axes object instance
:param psr: Pulsar object instance
:param real: Nreal x ntoa array containing individual waveform realizations.
:param sigma: Uncertainty level on waveform
"""
nt = real.shape[1]
xmed, xlow, xhigh = np.zeros(nt), np.zeros(nt), np.zeros(nt)
for ii in range(nt):
rlind = np.flatnonzero(real[:, ii])
tmp, xmed[ii] = bu.confinterval(real[rlind, ii], onesided=True, sigma=0.5)
xlow[ii], xhigh[ii] = bu.confinterval(real[rlind, ii], sigma=sigma, type="minArea")
idx = np.argsort(psr.toas)
ax.fill_between(convert_mjd_to_greg(psr.toas[idx] / 86400), xlow[idx] * 1e6, xhigh[idx] * 1e6, **kwargs)
ax.plot(convert_mjd_to_greg(psr.toas[idx] / 86400), xmed[idx] * 1e6, ls="--", lw=1.5, **kwargs)
def make_spectrum_realization_plot(ax, f, psd, sigma=0.68, plot_median=True, use_bars=False, *args, **kwargs):
"""
Make a waveform realization plot of signal vs time with
uncertantiy region.
:param ax: axes object instance
:param model: PAL2 Model class
:param real: Nreal x nf array containing individual spectrum realizations.
:param sigma: Uncertainty level on waveform
:param plot_median: Plot the median spectrum
:param use_bars: Use error bars instead of fill_between
"""
nt = len(f)
xmed, xlow, xhigh = np.zeros(nt), np.zeros(nt), np.zeros(nt)
for ii in range(nt):
tmp, xmed[ii] = bu.confinterval(psd[:, ii], onesided=True, sigma=0.5)
xlow[ii], xhigh[ii] = bu.confinterval(psd[:, ii], sigma=sigma, type="minArea")
# print xlow, xhigh
if use_bars:
ymean = psd.mean(axis=0)
ylow = np.log10(10 ** ymean - 10 ** xlow)
yhigh = np.log10(10 ** xhigh - 10 ** ymean)
yerr = np.vstack((ylow, yhigh))
ax.errorbar(f, 10 ** ymean, yerr=10 ** yerr, fmt="o", capsize=0, **kwargs)
else:
ax.fill_between(f, 10 ** xlow, 10 ** xhigh, **kwargs)
if plot_median:
ax.plot(f, 10 ** xmed, ls="--", lw=1.5, color="k")
ax.set_xscale("log")
ax.set_yscale("log")
ax.set_ylim(10 ** xlow.min() / 2, 10 ** xhigh.max() * 2)
df = f[1] - f[0]
ax.set_xlim(f.min() - df, f.max() + df)
ax.grid(which="both")
