def sampling_figure(prefix="plots"):
matplotlib.rcParams["axes.labelsize"] = 40
matplotlib.rcParams["xtick.labelsize"] = 26
xmin = 0.
radecs = []
level = 0.
fig = plt.figure(figsize=(15, 15))
ax = fig.add_subplot(111)
for ii in range(100):
lightCurves = session.query(LightCurve).filter(
func.array_length(LightCurve.mjd, 1) > 100).limit(100).all()
if level >= 10: break
for lc in lightCurves:
if (max(lc.mjd) - min(lc.mjd)) > 365:
next_lc = False
for radec in radecs:
try:
sep = g.subtends(lc.ra,
lc.dec,
radec[0],
radec[1],
units="degrees")
except ValueError:
next_lc = True
if sep < 5.:
next_lc = True
if next_lc: continue
else: radecs.append((lc.ra, lc.dec))
#ax.errorbar(lc.Rmjd, lc.Rmag, lc.Rerror, ls='none', marker='o', c='k', ecolor='0.7', capsize=0)
ax.plot(lc.Rmjd, [level] * len(lc.Rmjd),
marker='o',
ms=20.0,
c='k',
ls='none',
alpha=0.3)
if xmin == 0:
xmin = min(lc.Rmjd)
ax.set_xlim(xmin, xmin + 365)
level += 1
ymin, ymax = ax.get_ylim()
ydel = ymax - ymin
ax.set_ylim(ymin - ydel / 10., ymax + ydel / 10.)
ax.set_xlabel("MJD")
ax.set_yticklabels([])
plt.savefig(os.path.join(prefix, "ptf_sampling_figure.pdf"))
def sampling_figure(prefix="plots"):
matplotlib.rcParams["axes.labelsize"] = 40
matplotlib.rcParams["xtick.labelsize"] = 26
xmin = 0.
radecs = []
level = 0.
fig = plt.figure(figsize=(15,15))
ax = fig.add_subplot(111)
for ii in range(100):
lightCurves = session.query(LightCurve).filter(func.array_length(LightCurve.mjd, 1) > 100).limit(100).all()
if level >= 10: break
for lc in lightCurves:
if (max(lc.mjd) - min(lc.mjd)) > 365:
next_lc = False
for radec in radecs:
try:
sep = g.subtends(lc.ra, lc.dec, radec[0], radec[1], units="degrees")
except ValueError:
next_lc = True
if sep < 5.:
next_lc = True
if next_lc: continue
else: radecs.append((lc.ra, lc.dec))
#ax.errorbar(lc.Rmjd, lc.Rmag, lc.Rerror, ls='none', marker='o', c='k', ecolor='0.7', capsize=0)
ax.plot(lc.Rmjd, [level]*len(lc.Rmjd), marker='o', ms=20.0, c='k', ls='none', alpha=0.3)
if xmin == 0:
xmin = min(lc.Rmjd)
ax.set_xlim(xmin, xmin+365)
level += 1
ymin, ymax = ax.get_ylim()
ydel = ymax-ymin
ax.set_ylim(ymin-ydel/10., ymax+ydel/10.)
ax.set_xlabel("MJD")
ax.set_yticklabels([])
plt.savefig(os.path.join(prefix, "ptf_sampling_figure.pdf"))
def bad_data_figure(prefix="plots"):
matplotlib.rcParams["axes.titlesize"] = 40
matplotlib.rcParams["axes.labelsize"] = 40
matplotlib.rcParams["xtick.labelsize"] = 20
matplotlib.rcParams["ytick.labelsize"] = 20
lightCurve1 = session.query(LightCurve).filter(LightCurve.objid == 14688560553413090141).one()
lightCurve2 = session.query(LightCurve).filter(LightCurve.objid == 14688560553413090134).one()
print "Distance between objects: {0}\"".format(g.subtends(lightCurve1.ra, lightCurve1.dec, lightCurve2.ra, lightCurve2.dec, units="degrees")*3600.)
medMag1 = np.median(lightCurve1.mag)
medMag2 = np.median(lightCurve2.mag)
fig = plt.figure(figsize=(20,25))
fig.subplots_adjust(hspace=0.2, left=0.1)
ax1 = fig.add_subplot(211)
ax1.errorbar(lightCurve1.mjd, lightCurve1.mag, lightCurve1.error, ls='none', marker='o', ecolor='0.7', capsize=0)
ax2 = fig.add_subplot(212)
ax2.errorbar(lightCurve2.mjd, lightCurve2.mag, lightCurve2.error, ls='none', marker='o', ecolor='0.7', capsize=0)
ax1.set_ylim(medMag1-0.5,medMag1+0.5)
ax1.set_ylim(ax1.get_ylim()[::-1])
ax1.set_xlim(55000, 56000)
ax1.set_ylabel(r"$R$")
ax1.set_xticklabels([])
ax1.set_title("objid: {0}".format(lightCurve1.objid))
ax2.set_ylim(medMag2-0.5,medMag2+0.5)
ax2.set_ylim(ax2.get_ylim()[::-1])
ax2.set_xlim(55000, 56000)
ax2.set_ylabel(r"$R$")
ax2.set_xlabel("MJD")
ax2.set_title("objid: {0}".format(lightCurve2.objid))
plt.savefig(os.path.join(prefix, "bad_data_figure.pdf"))
return
# Code below is to search for light curves that are similar
while True:
lightCurve1 = session.query(LightCurve).filter(func.array_length(LightCurve.mjd, 1) > 200).order_by(func.random()).limit(1).one()
lightCurve2 = session.query(LightCurve).filter(func.array_length(LightCurve.mjd, 1) > 200).\
filter(func.q3c_radial_query(LightCurve.ra, LightCurve.dec, lightCurve1.ra, lightCurve1.dec, 60./3600.)).\
order_by(func.random()).limit(1).one()
medMag1 = np.median(lightCurve1.mag)
medMag2 = np.median(lightCurve2.mag)
if medMag1 > 17 or medMag2 > 17: continue
fig = plt.figure(figsize=(20,25))
fig.subplots_adjust(hspace=0.3, left=0.1)
ax1 = fig.add_subplot(211)
ax1.errorbar(lightCurve1.mjd, lightCurve1.mag, lightCurve1.error, ls='none', marker='o', ecolor='0.7', capsize=0)
ax2 = fig.add_subplot(212)
ax2.errorbar(lightCurve2.mjd, lightCurve2.mag, lightCurve2.error, ls='none', marker='o', ecolor='0.7', capsize=0)
ax1.set_ylim(medMag1-0.5,medMag1+0.5)
ax1.set_ylim(ax1.get_ylim()[::-1])
ax1.set_xlim(55000, 56000)
ax1.set_ylabel(r"$R$")
ax1.set_xticklabels([])
ax1.set_title("objid: {0}".format(lightCurve1.objid))
ax2.set_ylim(medMag2-0.5,medMag2+0.5)
ax2.set_ylim(ax2.get_ylim()[::-1])
ax2.set_xlim(55000, 56000)
ax2.set_ylabel(r"$R$")
ax2.set_xlabel("MJD")
ax2.set_title("objid: {0}".format(lightCurve2.objid))
plt.show()
def bad_data_figure(prefix="plots"):
matplotlib.rcParams["axes.titlesize"] = 40
matplotlib.rcParams["axes.labelsize"] = 40
matplotlib.rcParams["xtick.labelsize"] = 20
matplotlib.rcParams["ytick.labelsize"] = 20
lightCurve1 = session.query(LightCurve).filter(
LightCurve.objid == 14688560553413090141).one()
lightCurve2 = session.query(LightCurve).filter(
LightCurve.objid == 14688560553413090134).one()
print "Distance between objects: {0}\"".format(
g.subtends(lightCurve1.ra,
lightCurve1.dec,
lightCurve2.ra,
lightCurve2.dec,
units="degrees") * 3600.)
medMag1 = np.median(lightCurve1.mag)
medMag2 = np.median(lightCurve2.mag)
fig = plt.figure(figsize=(20, 25))
fig.subplots_adjust(hspace=0.2, left=0.1)
ax1 = fig.add_subplot(211)
ax1.errorbar(lightCurve1.mjd,
lightCurve1.mag,
lightCurve1.error,
ls='none',
marker='o',
ecolor='0.7',
capsize=0)
ax2 = fig.add_subplot(212)
ax2.errorbar(lightCurve2.mjd,
lightCurve2.mag,
lightCurve2.error,
ls='none',
marker='o',
ecolor='0.7',
capsize=0)
ax1.set_ylim(medMag1 - 0.5, medMag1 + 0.5)
ax1.set_ylim(ax1.get_ylim()[::-1])
ax1.set_xlim(55000, 56000)
ax1.set_ylabel(r"$R$")
ax1.set_xticklabels([])
ax1.set_title("objid: {0}".format(lightCurve1.objid))
ax2.set_ylim(medMag2 - 0.5, medMag2 + 0.5)
ax2.set_ylim(ax2.get_ylim()[::-1])
ax2.set_xlim(55000, 56000)
ax2.set_ylabel(r"$R$")
ax2.set_xlabel("MJD")
ax2.set_title("objid: {0}".format(lightCurve2.objid))
plt.savefig(os.path.join(prefix, "bad_data_figure.pdf"))
return
# Code below is to search for light curves that are similar
while True:
lightCurve1 = session.query(LightCurve).filter(
func.array_length(LightCurve.mjd, 1) > 200).order_by(
func.random()).limit(1).one()
lightCurve2 = session.query(LightCurve).filter(func.array_length(LightCurve.mjd, 1) > 200).\
filter(func.q3c_radial_query(LightCurve.ra, LightCurve.dec, lightCurve1.ra, lightCurve1.dec, 60./3600.)).\
order_by(func.random()).limit(1).one()
medMag1 = np.median(lightCurve1.mag)
medMag2 = np.median(lightCurve2.mag)
if medMag1 > 17 or medMag2 > 17: continue
fig = plt.figure(figsize=(20, 25))
fig.subplots_adjust(hspace=0.3, left=0.1)
ax1 = fig.add_subplot(211)
ax1.errorbar(lightCurve1.mjd,
lightCurve1.mag,
lightCurve1.error,
ls='none',
marker='o',
ecolor='0.7',
capsize=0)
ax2 = fig.add_subplot(212)
ax2.errorbar(lightCurve2.mjd,
lightCurve2.mag,
lightCurve2.error,
ls='none',
marker='o',
ecolor='0.7',
capsize=0)
ax1.set_ylim(medMag1 - 0.5, medMag1 + 0.5)
ax1.set_ylim(ax1.get_ylim()[::-1])
ax1.set_xlim(55000, 56000)
ax1.set_ylabel(r"$R$")
ax1.set_xticklabels([])
ax1.set_title("objid: {0}".format(lightCurve1.objid))
ax2.set_ylim(medMag2 - 0.5, medMag2 + 0.5)
ax2.set_ylim(ax2.get_ylim()[::-1])
ax2.set_xlim(55000, 56000)
ax2.set_ylabel(r"$R$")
ax2.set_xlabel("MJD")
ax2.set_title("objid: {0}".format(lightCurve2.objid))
plt.show()