def sanity_compAirmasses(self):
"""
Compare different airmass calculations
"""
from PyAstronomy import pyasl
for za in range(0,70,10):
ampp = pyasl.airmassPP(za)
amsp = pyasl.airmassSpherical(za, 0.0)
self.assertAlmostEqual(ampp/amsp, 1.0, delta=0.01)
def sanity_airmassPPExample(self):
"""
Example for plane-parallel airmass
"""
from PyAstronomy import pyasl
print "Airmass for plane-parallel atmosphere"
for za in range(0,70,10):
print "Zenith angle: %2d deg, airmass = %7.2f" % \
(za, pyasl.airmassPP(za))
def StarObsPlot(year=None,
targets=None,
observatory=None,
period=None,
hover=False,
sunless_hours=None,
remove_watermark=False):
"""
Plot the visibility of target.
Parameters
----------
year: int
The year for which to calculate the visibility.
targets: list
List of targets.
Each target should be a dictionary with keys 'name' and 'coord'.
The key 'name' is a string, 'coord' is a SkyCoord object.
observatory: string
Name of the observatory that pyasl.observatory can resolve.
Basically, any of pyasl.listObservatories().keys()
period: string, optional
ESO period for which to calculate the visibility. Overrides `year`.
hover: boolean, optional
If True, color visibility lines when mouse over.
sunless_hours: float, optional
If not None, plot sunless hours above this airmass
"""
from mpl_toolkits.axes_grid1 import host_subplot
from matplotlib.ticker import MultipleLocator
from matplotlib.font_manager import FontProperties
from matplotlib import rcParams
rcParams['xtick.major.pad'] = 12
font0 = FontProperties()
font1 = font0.copy()
font0.set_family('sans-serif')
font0.set_weight('light')
font1.set_family('sans-serif')
font1.set_weight('medium')
# set the observatory
if isinstance(observatory, dict):
obs = observatory
else:
obs = pyasl.observatory(observatory)
fig = plt.figure(figsize=(15, 10))
fig.subplots_adjust(left=0.07, right=0.8, bottom=0.15, top=0.88)
# watermak
if not remove_watermark:
fig.text(0.99,
0.99,
'Created with\ngithub.com/iastro-pt/ObservationTools',
fontsize=10,
color='gray',
ha='right',
va='top',
alpha=0.5)
# plotting sunless hours?
shmode = False
if sunless_hours is not None:
shmode = True
# limit in airmass (assumed plane-parallel atm)
shairmass = sunless_hours
# correspoing limit in altitude
from scipy.optimize import bisect
shalt = 90 - bisect(lambda alt: pyasl.airmassPP(alt) - shairmass, 0,
89)
if shmode:
fig.subplots_adjust(hspace=0.35)
ax = host_subplot(211)
axsh = host_subplot(212)
plt.text(0.5,
0.47,
"- sunless hours above airmass {:.1f} - \n".format(shairmass),
transform=fig.transFigure,
ha='center',
va='bottom',
fontsize=12)
plt.text(0.5, 0.465,
"the thick line above the curves represents the total sunless hours "\
"for each day of the year",
transform=fig.transFigure, ha='center', va='bottom', fontsize=10)
else:
ax = host_subplot(111)
for n, target in enumerate(targets):
target_coord = target['coord']
target_ra = target_coord.ra.deg
target_dec = target_coord.dec.deg
if period is not None:
jd_start, jd_end = get_ESO_period(period)
else:
jd_start = pyasl.jdcnv(dt.datetime(year, 1, 1))
jd_end = pyasl.jdcnv(dt.datetime(year, 12, 31))
jdbinsize = 1 # every day
each_day = np.arange(jd_start, jd_end, jdbinsize)
jds = []
## calculate the mid-dark times
sun = ephem.Sun()
for day in each_day:
date_formatted = '/'.join([str(i) for i in pyasl.daycnv(day)[:-1]])
s = ephem.Observer()
s.date = date_formatted
s.lat = ':'.join([str(i) for i in decdeg2dms(obs['latitude'])])
s.lon = ':'.join([str(i) for i in decdeg2dms(obs['longitude'])])
jds.append(ephem.julian_date(s.next_antitransit(sun)))
jds = np.array(jds)
# Get JD floating point
jdsub = jds - np.floor(jds[0])
# Get alt/az of object
altaz = pyasl.eq2hor(jds, np.ones_like(jds)*target_ra, np.ones_like(jds)*target_dec, \
lon=obs['longitude'], lat=obs['latitude'], alt=obs['altitude'])
ax.plot(jdsub, altaz[0], '-', color='k')
# label for each target
plabel = "[{0:2d}] {1!s}".format(n + 1, target['name'])
# number of target at the top of the curve
ind_label = np.argmax(altaz[0])
# or at the bottom if the top is too close to the corners
# if jdsub[ind_label] < 5 or jdsub[ind_label] > jdsub.max()-5:
# ind_label = np.argmin(altaz[0])
ax.text( jdsub[ind_label], altaz[0][ind_label], str(n+1), color="b", fontsize=14, \
fontproperties=font1, va="bottom", ha="center")
if n + 1 == 29:
# too many?
ax.text(1.1, 1.0-float(n+1)*0.04, "too many targets", ha="left", va="top", transform=ax.transAxes, \
fontsize=10, fontproperties=font0, color="r")
else:
ax.text(1.1, 1.0-float(n+1)*0.04, plabel, ha="left", va="top", transform=ax.transAxes, \
fontsize=12, fontproperties=font0, color="b")
if shmode:
sunless_hours = []
for day in each_day:
date_formatted = '/'.join([str(i) for i in pyasl.daycnv(day)[:-1]])
s = ephem.Observer()
s.date = date_formatted
s.lat = ':'.join([str(i) for i in decdeg2dms(obs['latitude'])])
s.lon = ':'.join([str(i) for i in decdeg2dms(obs['longitude'])])
# hours from sunrise to sunset
td = pyasl.daycnv(ephem.julian_date(s.next_setting(sun)), mode='dt') \
- pyasl.daycnv(ephem.julian_date(s.next_rising(sun)), mode='dt')
sunless_hours.append(24 - td.total_seconds() / 3600)
days = each_day - np.floor(each_day[0])
axsh.plot(days, sunless_hours, '-', color='k', lw=2)
axsh.set(
ylim=(0, 15),
yticks=range(1, 15),
ylabel='Useful hours',
yticklabels=[r'${}^{{\rm h}}$'.format(n) for n in range(1, 15)])
ax.text(1.1, 1.03, "List of targets", ha="left", va="top", transform=ax.transAxes, \
fontsize=12, fontproperties=font0, color="b")
axrange = ax.get_xlim()
if period is None:
months = range(1, 13)
ndays = [0] + [calendar.monthrange(date, m)[1] for m in months]
ax.set_xlim([0, 366])
ax.set_xticks(np.cumsum(ndays)[:-1] + (np.array(ndays) / 2.)[1:])
ax.set_xticklabels(map(calendar.month_abbr.__getitem__, months),
fontsize=10)
if shmode:
axsh.set_xlim([0, 366])
axsh.set_xticks(np.cumsum(ndays)[:-1] + (np.array(ndays) / 2.)[1:])
axsh.set_xticklabels(map(calendar.month_abbr.__getitem__, months),
fontsize=10)
else:
if int(period) % 2 == 0:
# even ESO period, Oct -> Mar
months = [10, 11, 12, 1, 2, 3]
ndays = [0] + [calendar.monthrange(date, m)[1] for m in months]
ax.set_xlim([0, 181])
ax.set_xticks(np.cumsum(ndays)[:-1] + (np.array(ndays) / 2.)[1:])
ax.set_xticklabels(map(calendar.month_abbr.__getitem__, months),
fontsize=10)
if shmode:
axsh.set_xlim([0, 181])
axsh.set_xticks(
np.cumsum(ndays)[:-1] + (np.array(ndays) / 2.)[1:])
axsh.set_xticklabels(map(calendar.month_abbr.__getitem__,
months),
fontsize=10)
else:
# odd ESO period, Apr -> Sep
months = range(4, 10)
ndays = [0] + [calendar.monthrange(date, m)[1] for m in months]
ax.set_xlim([0, 182])
ax.set_xticks(np.cumsum(ndays)[:-1] + (np.array(ndays) / 2.)[1:])
ax.set_xticklabels(map(calendar.month_abbr.__getitem__, months),
fontsize=10)
if shmode:
axsh.set_xlim([0, 182])
axsh.set_xticks(
np.cumsum(ndays)[:-1] + (np.array(ndays) / 2.)[1:])
axsh.set_xticklabels(map(calendar.month_abbr.__getitem__,
months),
fontsize=10)
if axrange[1] - axrange[0] <= 1.0:
jdhours = np.arange(0, 3, 1.0 / 24.)
utchours = (np.arange(0, 72, dtype=int) + 12) % 24
else:
jdhours = np.arange(0, 3, 1.0 / 12.)
utchours = (np.arange(0, 72, 2, dtype=int) + 12) % 24
# Make ax2 responsible for "top" axis and "right" axis
ax2 = ax.twin()
# Set upper x ticks
ax2.set_xticks(np.cumsum(ndays))
ax2.set_xlabel("Day")
# plane-parallel airmass
airmass_ang = np.arange(10, 81, 5)
geo_airmass = pyasl.airmass.airmassPP(airmass_ang)[::-1]
ax2.set_yticks(airmass_ang)
airmassformat = []
for t in range(geo_airmass.size):
airmassformat.append("{0:2.2f}".format(geo_airmass[t]))
ax2.set_yticklabels(airmassformat) #, rotation=90)
ax2.set_ylabel("Relative airmass", labelpad=32)
ax2.tick_params(axis="y", pad=6, labelsize=8)
plt.text(1.02,-0.04, "Plane-parallel", transform=ax.transAxes, ha='left', \
va='top', fontsize=10, rotation=90)
ax22 = ax.twin()
ax22.set_xticklabels([])
ax22.set_frame_on(True)
ax22.patch.set_visible(False)
ax22.yaxis.set_ticks_position('right')
ax22.yaxis.set_label_position('right')
ax22.spines['right'].set_position(('outward', 30))
ax22.spines['right'].set_color('k')
ax22.spines['right'].set_visible(True)
airmass2 = list(
map(
lambda ang: pyasl.airmass.airmassSpherical(90. - ang, obs[
'altitude']), airmass_ang))
ax22.set_yticks(airmass_ang)
airmassformat = []
for t in range(len(airmass2)):
airmassformat.append(" {0:2.2f}".format(airmass2[t]))
ax22.set_yticklabels(airmassformat, rotation=90)
ax22.tick_params(axis="y", pad=8, labelsize=8)
plt.text(1.05,-0.04, "Spherical+Alt", transform=ax.transAxes, ha='left', va='top', \
fontsize=10, rotation=90)
ax.set_ylim([0, 91])
ax.yaxis.set_major_locator(MultipleLocator(15))
ax.yaxis.set_minor_locator(MultipleLocator(5))
yticks = ax.get_yticks()
ytickformat = []
for t in range(yticks.size):
ytickformat.append(str(int(yticks[t])) + r"$^\circ$")
ax.set_yticklabels(ytickformat, fontsize=16)
ax.set_ylabel("Altitude", fontsize=18)
yticksminor = ax.get_yticks(minor=True)
ymind = np.where(yticksminor % 15. != 0.)[0]
yticksminor = yticksminor[ymind]
ax.set_yticks(yticksminor, minor=True)
m_ytickformat = []
for t in range(yticksminor.size):
m_ytickformat.append(str(int(yticksminor[t])) + r"$^\circ$")
ax.set_yticklabels(m_ytickformat, minor=True)
ax.set_ylim([0, 91])
ax.yaxis.grid(color='gray', linestyle='dashed')
ax.yaxis.grid(color='gray', which="minor", linestyle='dotted')
ax2.xaxis.grid(color='gray', linestyle='dotted')
if period is not None:
plt.text(
0.5,
0.95,
"Visibility over P{0!s}\n - altitudes at mid-dark time -".format(
period),
transform=fig.transFigure,
ha='center',
va='bottom',
fontsize=12)
else:
plt.text(
0.5,
0.95,
"Visibility over {0!s}\n - altitudes at mid-dark time -".format(
date),
transform=fig.transFigure,
ha='center',
va='bottom',
fontsize=12)
obsco = "Obs coord.: {0:8.4f}$^\circ$, {1:8.4f}$^\circ$, {2:4f} m".format(
obs['longitude'], obs['latitude'], obs['altitude'])
plt.text(0.01,
0.97,
obsco,
transform=fig.transFigure,
ha='left',
va='center',
fontsize=10)
plt.text(0.01,
0.95,
obs['name'],
transform=fig.transFigure,
ha='left',
va='center',
fontsize=10)
# interactive!
if hover:
main_axis = fig.axes[0]
all_lines = set(main_axis.get_lines())
def on_plot_hover(event):
for line in main_axis.get_lines():
if line.contains(event)[0]:
line.set_color('red') # make this line red
# and all others black
all_other_lines = all_lines - set([line])
for other_line in all_other_lines:
other_line.set_color('black')
fig.canvas.draw_idle()
fig.canvas.mpl_connect('motion_notify_event', on_plot_hover)
return fig
def JupiterPlotEW(DateUT, BandID, Grating, FluxType='Albedo'):
#JupiterPlotEW("20150123UT","619CH4","100lpm-550CLR")
import sys
sys.path.append('f:\Astronomy\Projects\Jupiter\Spectral Data')
sys.path.append('f:\\Astronomy\Python Play')
sys.path.append('f:\\Astronomy\Python Play\Utils')
sys.path.append('f:\\Astronomy\Python Play\Spectrophotometry\Spectroscopy')
import astropy.units as u
from astropy.time import Time
from astropy.coordinates import SkyCoord, EarthLocation, AltAz
import numpy as np
import ephem
import EquivWidthUtils as EWU
from PyAstronomy import pyasl
import matplotlib.pyplot as pl
import PlotUtils as PU
import ConfigFiles as CF
from scipy import interpolate
TimePlot = PU.PlotSetup("JupiterEWSpecPlotConfig.txt")
TimePlot.loadplotparams("f:", "Jupiter_" + BandID, "Time")
AirmassPlot = PU.PlotSetup("JupiterEWSpecPlotConfig.txt")
AirmassPlot.loadplotparams("f:", "Jupiter_" + BandID, "Airmass")
CMIIPlot = PU.PlotSetup("JupiterEWSpecPlotConfig.txt")
CMIIPlot.loadplotparams("f:", "Jupiter_" + BandID, "CMII")
PWVPlot = PU.PlotSetup("JupiterEWSpecPlotConfig.txt")
PWVPlot.loadplotparams("f:", "Earth_PWV", "Time")
PressPlot = PU.PlotSetup("JupiterEWSpecPlotConfig.txt")
PressPlot.loadplotparams("f:", "Earth_Press", "Time")
TempFPlot = PU.PlotSetup("JupiterEWSpecPlotConfig.txt")
TempFPlot.loadplotparams("f:", "Earth_TempF", "Time")
Earth_Airmass = PU.PlotSetup("JupiterEWSpecPlotConfig.txt")
Earth_Airmass.loadplotparams("f:", "Earth_Airmass", "Time")
CalibrationStars = {
'20150123UT': "Pollux",
'20150209UT': "Pollux",
'20150210UT': "Pollux",
'20150318UT': "Pollux",
'20150322UT': "Pollux",
'20150331UT': "Pollux"
}
CalibrationDates = {
'20150123UT': '2015-01-23 05:54:00',
'20150209UT': '2015-02-10 05:54:00',
'20150210UT': '2015-02-10 05:54:00',
'20150318UT': '2015-03-18 05:54:00',
'20150322UT': '2015-03-22 05:54:00',
'20150331UT': '2015-03-22 05:54:00'
}
ResponseFile = {
'20150123UT': 'PolluxResponse20150123UT.txt',
'20150209UT': 'PolluxResponse20150210UT.txt',
'20150210UT': 'PolluxResponse20150210UT.txt',
'20150318UT': 'PolluxResponse20150318UT.txt',
'20150322UT': 'PolluxResponse20150322UT.txt',
'20150331UT': 'PolluxResponse20150322UT.txt'
}
Pollux = SkyCoord.from_name('Pollux')
observer = ephem.Observer()
#Location from Google Maps at 483 S Oneida Way, Denver 80224
observer.lon = ephem.degrees('-104.907985')
observer.lat = ephem.degrees('39.708200')
print float(observer.lat) * 180 / np.pi
Oneida = EarthLocation(lat=float(observer.lat) * u.rad,
lon=float(observer.lon) * u.rad,
height=1500 * u.m)
utcoffset = 0 * u.hour # Universal Time
time = Time(CalibrationDates[DateUT]) - utcoffset
Polluxaltaz = Pollux.transform_to(AltAz(obstime=time, location=Oneida))
print Polluxaltaz.alt.deg
print("Pollux's Altitude = {0.alt:.2}".format(Polluxaltaz))
print Polluxaltaz.secz
AEWs = EWU.EWObservations("../EWs/" + DateUT + "-" + Grating +
"-Albedo-EW.txt")
AEWs.load_records("Jupiter", BandID)
REWs = EWU.EWObservations("../EWs/" + DateUT + "-" + Grating +
"-RawFlux-EW.txt")
REWs.load_records("Jupiter", BandID)
#print EWs.DateTimeUTObs
#print EWs.EW
########################################################
TimePlot.Setup_PlotDate(min(AEWs.DateTimeUTObs),
max(AEWs.DateTimeUTObs),
1,
canvas_size=[8.0, 6.0],
subplot=[4, 1, 1])
lbl = BandID + " REW " + str(round(np.mean(REWs.EW), 3)) + "$\pm$" + str(
round(np.std(REWs.EW), 3))
pl.plot_date(REWs.DateTimeUTObs, REWs.EW, label=lbl)
lbl = BandID + " AEW " + str(round(np.mean(AEWs.EW), 3)) + "$\pm$" + str(
round(np.std(AEWs.EW), 3))
pl.plot_date(AEWs.DateTimeUTObs, AEWs.EW, label=lbl)
pl.ylabel("Equiv. Width (nm)", fontsize=7)
pl.legend(loc=2, ncol=3, fontsize=6, scatterpoints=1)
pl.title("Jupiter " + DateUT + " " + BandID)
print "Average AEW, Std. Dev., 95% Conf.= ",np.mean(AEWs.EW),np.std(AEWs.EW),\
1.96*np.std(AEWs.EW)/np.sqrt(len(AEWs.EW))
print "Average REW, Std. Dev., 95% Conf.= ",np.mean(REWs.EW),np.std(REWs.EW),\
1.96*np.std(REWs.EW)/np.sqrt(len(REWs.EW))
########################################################
print PWVPlot.DataFile
Earth_atmo = CF.Observing_Conditions(PWVPlot.DataFile)
print DateUT[0:4] + '-' + DateUT[4:6] + '-' + DateUT[6:8]
Earth_atmo.load_records(DateUT[0:4] + '-' + DateUT[4:6] + '-' +
DateUT[6:8])
AX = PWVPlot.Setup_PlotDate(min(AEWs.DateTimeUTObs),
max(AEWs.DateTimeUTObs),
1,
new_canvas=False,
subplot=[4, 1, 2])
DTarray = []
DT1array = []
for DT in Earth_atmo.ObsDateUT:
TmpDT = Time(DT[0:19], format='isot', scale='utc')
DTarray.append(float(TmpDT.jd))
for DT1 in AEWs.DateTimeUTObs:
TmpDT1 = Time(DT1, format='iso', scale='utc')
DT1array.append(float(TmpDT1.jd))
InterpPWV = interpolate.interp1d(DTarray,
Earth_atmo.PWV,
kind='linear',
copy=True,
bounds_error=False,
fill_value=np.NaN,
axis=0)
PWVonGrid = InterpPWV(np.array(DT1array))
AX.plot_date(AEWs.DateTimeUTObs, PWVonGrid, label="PWV [mm]")
AX.set_ylabel("PWV (mm)", fontsize=7)
########################################################
InterpPress = interpolate.interp1d(DTarray,
Earth_atmo.Press,
kind='linear',
copy=True,
bounds_error=False,
fill_value=np.NaN,
axis=0)
PressonGrid = InterpPress(np.array(DT1array))
ax1 = AX.twinx()
#ax1.set_xlim(x0,x1)
#ax1.set_xticks(np.linspace(x0,x1,xtks, endpoint=True))
ax1.set_ylim(800., 850.)
ax1.set_yticks(np.linspace(800., 850., 11, endpoint=True))
ax1.tick_params(axis='y', which='major', labelsize=7)
ax1.set_ylabel("Pressure (mb)", fontsize=7)
#PressPlot.Setup_PlotDate(min(EWs.DateTimeUTObs),max(EWs.DateTimeUTObs),1)
ax1.plot_date(AEWs.DateTimeUTObs,
PressonGrid,
'C1',
markerfacecolor='C1',
marker="o",
linewidth=0.0,
label="Pressure")
AX.legend(loc=2, ncol=3, fontsize=6, scatterpoints=1)
ax1.legend(loc=1, ncol=3, fontsize=6, scatterpoints=1)
########################################################
InterpTempC = interpolate.interp1d(DTarray,
Earth_atmo.TempC,
kind='linear',
copy=True,
bounds_error=False,
fill_value=np.NaN,
axis=0)
TempConGrid = InterpTempC(np.array(DT1array))
InterpRelHum = interpolate.interp1d(DTarray,
Earth_atmo.RelHum,
kind='linear',
copy=True,
bounds_error=False,
fill_value=np.NaN,
axis=0)
RelHumonGrid = InterpRelHum(np.array(DT1array))
az = TempFPlot.Setup_PlotDate(min(AEWs.DateTimeUTObs),
max(AEWs.DateTimeUTObs),
1,
new_canvas=False,
subplot=[4, 1, 3])
az.plot_date(AEWs.DateTimeUTObs,
TempConGrid * 9.0 / 5.0 + 32.0,
label="Temp.[F]")
az.plot_date(AEWs.DateTimeUTObs, RelHumonGrid, label="Rel. Hum. [%]")
pl.legend(loc=2, ncol=3, fontsize=6, scatterpoints=1)
########################################################
airmass = []
CMII = []
for d in AEWs.DateTimeUTObs:
observer.date = d
Planet = ephem.Jupiter(d)
Planet.compute(observer)
airmass.extend([pyasl.airmassPP(90. - Planet.alt * 180. / np.pi)])
CMII.append(Planet.cmlII * 180. / np.pi)
########################################################
EAM = Earth_Airmass.Setup_PlotDate(min(AEWs.DateTimeUTObs),
max(AEWs.DateTimeUTObs),
1,
new_canvas=False,
subplot=[4, 1, 4])
#lbl=BandID+" AEW "+str(round(np.mean(AEWs.EW),3))+"$\pm$"+str(round(np.std(AEWs.EW),3))
EAM.plot_date(AEWs.DateTimeUTObs, np.array(airmass), label=lbl)
ref_airmass = np.full(len(airmass), Polluxaltaz.secz)
EAM.plot_date(AEWs.DateTimeUTObs,
ref_airmass,
linestyle='solid',
marker='None',
color='C0')
#PLOT HORIZONTAL LINE WITH REFERENCE AIR MASS HERE
EAM.set_ylabel("Air Mass", fontsize=7)
EAM.text(
sorted(AEWs.DateTimeUTObs)[0],
2.9,
CalibrationStars[DateUT],
color='#000000',
fontsize=8,
verticalalignment='top',
horizontalalignment='left',
)
EAM.text(
sorted(AEWs.DateTimeUTObs)[0],
2.7,
CalibrationDates[DateUT],
color='#000000',
fontsize=8,
verticalalignment='top',
horizontalalignment='left',
)
EAM.text(
sorted(AEWs.DateTimeUTObs)[0],
2.5,
"Air Mass=" + str(round(Polluxaltaz.secz, 3)),
color='#000000',
fontsize=8,
verticalalignment='top',
horizontalalignment='left',
)
print ' '
print sorted(AEWs.DateTimeUTObs)[0]
pl.subplots_adjust(left=0.08, right=0.92, top=0.95, bottom=0.05)
pl.savefig("Jupiter EW Plot" + DateUT + " " + BandID + ".png", dpi=300)
########################################################
########################################################
AirmassPlot.Setup_Plot()
pl.scatter(np.array(airmass), AEWs.EW)
Coefs = np.polyfit(np.array(airmass), AEWs.EW, 1)
EWFit = Coefs[1] + Coefs[0] * np.array(airmass)
pl.plot(np.array(airmass), EWFit)
corr = np.corrcoef([np.array(airmass), AEWs.EW])
print "Coefs= ", Coefs
print "Correlation Coef.= ", corr[0, 1]
#CoefsUT=np.polyfit(np.array(EWs.DateTimeUTObs), EWs.EW, 1)
########################################################
CMIIPlot.Setup_Plot()
pl.scatter(np.array(CMII), AEWs.EW)
pl.text(
10.,
20.,
'GOES-16/SUVI Fe195 YYYY-MM-DD HH:MM:SS',
color='#000000',
fontsize=8,
verticalalignment='bottom',
horizontalalignment='left',
)
def StarObsPlot(year=None, targets=None, observatory=None, period=None,
hover=False, sunless_hours=None, remove_watermark=False):
"""
Plot the visibility of target.
Parameters
----------
year: int
The year for which to calculate the visibility.
targets: list
List of targets.
Each target should be a dictionary with keys 'name' and 'coord'.
The key 'name' is a string, 'coord' is a SkyCoord object.
observatory: string
Name of the observatory that pyasl.observatory can resolve.
Basically, any of pyasl.listObservatories().keys()
period: string, optional
ESO period for which to calculate the visibility. Overrides `year`.
hover: boolean, optional
If True, color visibility lines when mouse over.
sunless_hours: float, optional
If not None, plot sunless hours above this airmass
"""
from mpl_toolkits.axes_grid1 import host_subplot
from matplotlib.ticker import MultipleLocator
from matplotlib.font_manager import FontProperties
from matplotlib import rcParams
rcParams['xtick.major.pad'] = 12
font0 = FontProperties()
font1 = font0.copy()
font0.set_family('sans-serif')
font0.set_weight('light')
font1.set_family('sans-serif')
font1.set_weight('medium')
# set the observatory
if isinstance(observatory, dict):
obs = observatory
else:
obs = pyasl.observatory(observatory)
fig = plt.figure(figsize=(15,10))
fig.subplots_adjust(left=0.07, right=0.8, bottom=0.15, top=0.88)
# watermak
if not remove_watermark:
fig.text(0.99, 0.99, 'Created with\ngithub.com/iastro-pt/ObservationTools',
fontsize=10, color='gray',
ha='right', va='top', alpha=0.5)
# plotting sunless hours?
shmode = False
if sunless_hours is not None:
shmode = True
# limit in airmass (assumed plane-parallel atm)
shairmass = sunless_hours
# correspoing limit in altitude
from scipy.optimize import bisect
shalt = 90 - bisect(lambda alt: pyasl.airmassPP(alt) - shairmass, 0, 89)
if shmode:
fig.subplots_adjust(hspace=0.35)
ax = host_subplot(211)
axsh = host_subplot(212)
plt.text(0.5, 0.47,
"- sunless hours above airmass {:.1f} - \n".format(shairmass),
transform=fig.transFigure, ha='center', va='bottom', fontsize=12)
plt.text(0.5, 0.465,
"the thick line above the curves represents the total sunless hours "\
"for each day of the year",
transform=fig.transFigure, ha='center', va='bottom', fontsize=10)
else:
ax = host_subplot(111)
for n, target in enumerate(targets):
target_coord = target['coord']
target_ra = target_coord.ra.deg
target_dec = target_coord.dec.deg
if period is not None:
jd_start, jd_end = get_ESO_period(period)
else:
jd_start = pyasl.jdcnv(dt.datetime(year, 1, 1))
jd_end = pyasl.jdcnv(dt.datetime(year, 12, 31))
jdbinsize = 1 # every day
each_day = np.arange(jd_start, jd_end, jdbinsize)
jds = []
## calculate the mid-dark times
sun = ephem.Sun()
for day in each_day:
date_formatted = '/'.join([str(i) for i in pyasl.daycnv(day)[:-1]])
s = ephem.Observer();
s.date = date_formatted;
s.lat = ':'.join([str(i) for i in decdeg2dms(obs['latitude'])])
s.lon = ':'.join([str(i) for i in decdeg2dms(obs['longitude'])])
jds.append(ephem.julian_date(s.next_antitransit(sun)))
jds = np.array(jds)
# Get JD floating point
jdsub = jds - np.floor(jds[0])
# Get alt/az of object
altaz = pyasl.eq2hor(jds, np.ones_like(jds)*target_ra, np.ones_like(jds)*target_dec, \
lon=obs['longitude'], lat=obs['latitude'], alt=obs['altitude'])
ax.plot( jdsub, altaz[0], '-', color='k')
# label for each target
plabel = "[{0:2d}] {1!s}".format(n+1, target['name'])
# number of target at the top of the curve
ind_label = np.argmax(altaz[0])
# or at the bottom if the top is too close to the corners
# if jdsub[ind_label] < 5 or jdsub[ind_label] > jdsub.max()-5:
# ind_label = np.argmin(altaz[0])
ax.text( jdsub[ind_label], altaz[0][ind_label], str(n+1), color="b", fontsize=14, \
fontproperties=font1, va="bottom", ha="center")
if n+1 == 29:
# too many?
ax.text(1.1, 1.0-float(n+1)*0.04, "too many targets", ha="left", va="top", transform=ax.transAxes, \
fontsize=10, fontproperties=font0, color="r")
else:
ax.text(1.1, 1.0-float(n+1)*0.04, plabel, ha="left", va="top", transform=ax.transAxes, \
fontsize=12, fontproperties=font0, color="b")
if shmode:
sunless_hours = []
for day in each_day:
date_formatted = '/'.join([str(i) for i in pyasl.daycnv(day)[:-1]])
s = ephem.Observer();
s.date = date_formatted;
s.lat = ':'.join([str(i) for i in decdeg2dms(obs['latitude'])])
s.lon = ':'.join([str(i) for i in decdeg2dms(obs['longitude'])])
# hours from sunrise to sunset
td = pyasl.daycnv(ephem.julian_date(s.next_setting(sun)), mode='dt') \
- pyasl.daycnv(ephem.julian_date(s.next_rising(sun)), mode='dt')
sunless_hours.append(24 - td.total_seconds() / 3600)
days = each_day - np.floor(each_day[0])
axsh.plot(days, sunless_hours, '-', color='k', lw=2)
axsh.set(ylim=(0, 15), yticks=range(1,15), ylabel='Useful hours',
yticklabels=[r'${}^{{\rm h}}$'.format(n) for n in range(1,15)])
ax.text(1.1, 1.03, "List of targets", ha="left", va="top", transform=ax.transAxes, \
fontsize=12, fontproperties=font0, color="b")
axrange = ax.get_xlim()
if period is None:
months = range(1, 13)
ndays = [0] + [calendar.monthrange(date, m)[1] for m in months]
ax.set_xlim([0, 366])
ax.set_xticks(np.cumsum(ndays)[:-1] + (np.array(ndays)/2.)[1:])
ax.set_xticklabels(map(calendar.month_abbr.__getitem__, months), fontsize=10)
if shmode:
axsh.set_xlim([0, 366])
axsh.set_xticks(np.cumsum(ndays)[:-1] + (np.array(ndays)/2.)[1:])
axsh.set_xticklabels(map(calendar.month_abbr.__getitem__, months), fontsize=10)
else:
if int(period) % 2 == 0:
# even ESO period, Oct -> Mar
months = [10, 11, 12, 1, 2, 3]
ndays = [0] + [calendar.monthrange(date, m)[1] for m in months]
ax.set_xlim([0, 181])
ax.set_xticks(np.cumsum(ndays)[:-1] + (np.array(ndays)/2.)[1:])
ax.set_xticklabels(map(calendar.month_abbr.__getitem__, months), fontsize=10)
if shmode:
axsh.set_xlim([0, 181])
axsh.set_xticks(np.cumsum(ndays)[:-1] + (np.array(ndays)/2.)[1:])
axsh.set_xticklabels(map(calendar.month_abbr.__getitem__, months), fontsize=10)
else:
# odd ESO period, Apr -> Sep
months = range(4, 10)
ndays = [0] + [calendar.monthrange(date, m)[1] for m in months]
ax.set_xlim([0, 182])
ax.set_xticks(np.cumsum(ndays)[:-1] + (np.array(ndays)/2.)[1:])
ax.set_xticklabels(map(calendar.month_abbr.__getitem__, months), fontsize=10)
if shmode:
axsh.set_xlim([0, 182])
axsh.set_xticks(np.cumsum(ndays)[:-1] + (np.array(ndays)/2.)[1:])
axsh.set_xticklabels(map(calendar.month_abbr.__getitem__, months), fontsize=10)
if axrange[1]-axrange[0] <= 1.0:
jdhours = np.arange(0,3,1.0/24.)
utchours = (np.arange(0,72,dtype=int)+12)%24
else:
jdhours = np.arange(0,3,1.0/12.)
utchours = (np.arange(0,72, 2, dtype=int)+12)%24
# Make ax2 responsible for "top" axis and "right" axis
ax2 = ax.twin()
# Set upper x ticks
ax2.set_xticks(np.cumsum(ndays))
ax2.set_xlabel("Day")
# plane-parallel airmass
airmass_ang = np.arange(10, 81, 5)
geo_airmass = pyasl.airmass.airmassPP(airmass_ang)[::-1]
ax2.set_yticks(airmass_ang)
airmassformat = []
for t in range(geo_airmass.size):
airmassformat.append("{0:2.2f}".format(geo_airmass[t]))
ax2.set_yticklabels(airmassformat)#, rotation=90)
ax2.set_ylabel("Relative airmass", labelpad=32)
ax2.tick_params(axis="y", pad=6, labelsize=8)
plt.text(1.02,-0.04, "Plane-parallel", transform=ax.transAxes, ha='left', \
va='top', fontsize=10, rotation=90)
ax22 = ax.twin()
ax22.set_xticklabels([])
ax22.set_frame_on(True)
ax22.patch.set_visible(False)
ax22.yaxis.set_ticks_position('right')
ax22.yaxis.set_label_position('right')
ax22.spines['right'].set_position(('outward', 30))
ax22.spines['right'].set_color('k')
ax22.spines['right'].set_visible(True)
airmass2 = list(map(lambda ang: pyasl.airmass.airmassSpherical(90. - ang, obs['altitude']), airmass_ang))
ax22.set_yticks(airmass_ang)
airmassformat = []
for t in range(len(airmass2)):
airmassformat.append(" {0:2.2f}".format(airmass2[t]))
ax22.set_yticklabels(airmassformat, rotation=90)
ax22.tick_params(axis="y", pad=8, labelsize=8)
plt.text(1.05,-0.04, "Spherical+Alt", transform=ax.transAxes, ha='left', va='top', \
fontsize=10, rotation=90)
ax.set_ylim([0, 91])
ax.yaxis.set_major_locator(MultipleLocator(15))
ax.yaxis.set_minor_locator(MultipleLocator(5))
yticks = ax.get_yticks()
ytickformat = []
for t in range(yticks.size):
ytickformat.append(str(int(yticks[t]))+r"$^\circ$")
ax.set_yticklabels(ytickformat, fontsize=16)
ax.set_ylabel("Altitude", fontsize=18)
yticksminor = ax.get_yticks(minor=True)
ymind = np.where( yticksminor % 15. != 0. )[0]
yticksminor = yticksminor[ymind]
ax.set_yticks(yticksminor, minor=True)
m_ytickformat = []
for t in range(yticksminor.size):
m_ytickformat.append(str(int(yticksminor[t]))+r"$^\circ$")
ax.set_yticklabels(m_ytickformat, minor=True)
ax.set_ylim([0, 91])
ax.yaxis.grid(color='gray', linestyle='dashed')
ax.yaxis.grid(color='gray', which="minor", linestyle='dotted')
ax2.xaxis.grid(color='gray', linestyle='dotted')
if period is not None:
plt.text(0.5, 0.95,
"Visibility over P{0!s}\n - altitudes at mid-dark time -".format(period),
transform=fig.transFigure, ha='center', va='bottom', fontsize=12)
else:
plt.text(0.5, 0.95,
"Visibility over {0!s}\n - altitudes at mid-dark time -".format(date),
transform=fig.transFigure, ha='center', va='bottom', fontsize=12)
obsco = "Obs coord.: {0:8.4f}$^\circ$, {1:8.4f}$^\circ$, {2:4f} m".format(obs['longitude'], obs['latitude'], obs['altitude'])
plt.text(0.01,0.97, obsco, transform=fig.transFigure, ha='left', va='center', fontsize=10)
plt.text(0.01,0.95, obs['name'], transform=fig.transFigure, ha='left', va='center', fontsize=10)
# interactive!
if hover:
main_axis = fig.axes[0]
all_lines = set(main_axis.get_lines())
def on_plot_hover(event):
for line in main_axis.get_lines():
if line.contains(event)[0]:
line.set_color('red') # make this line red
# and all others black
all_other_lines = all_lines - set([line])
for other_line in all_other_lines:
other_line.set_color('black')
fig.canvas.draw_idle()
fig.canvas.mpl_connect('motion_notify_event', on_plot_hover)
return fig
def JupiterAirmass(DateUT, BandID, Grating):
import sys
sys.path.append('f:\Astronomy\Projects\Jupiter\Spectral Data')
sys.path.append('f:\\Astronomy\Python Play')
sys.path.append('f:\\Astronomy\Python Play\Utils')
sys.path.append('f:\\Astronomy\Python Play\Spectrophotometry\Spectroscopy')
import astropy.units as u
from astropy.time import Time
from astropy.coordinates import SkyCoord, EarthLocation, AltAz
import numpy as np
import ephem
import EquivWidthUtils as EWU
from PyAstronomy import pyasl
import matplotlib.pyplot as pl
import PlotUtils as PU
TimePlot = PU.PlotSetup("JupiterEWSpecPlotConfig.txt")
TimePlot.loadplotparams("f:", "Jupiter_" + BandID, "Time")
AirmassPlot = PU.PlotSetup("JupiterEWSpecPlotConfig.txt")
AirmassPlot.loadplotparams("f:", "Jupiter_" + BandID, "Airmass")
CMIIPlot = PU.PlotSetup("JupiterEWSpecPlotConfig.txt")
CMIIPlot.loadplotparams("f:", "Jupiter_" + BandID, "CMII")
Pollux = SkyCoord.from_name('Pollux')
datestring = '2015-01-23 08:20:00'
observer = ephem.Observer()
#Location from Google Maps at 483 S Oneida Way, Denver 80224
observer.lon = ephem.degrees('-104.907985')
observer.lat = ephem.degrees('39.708200')
print float(observer.lat) * 180 / np.pi
Oneida = EarthLocation(lat=float(observer.lat) * u.rad,
lon=float(observer.lon) * u.rad,
height=1500 * u.m)
utcoffset = 0 * u.hour # Universal Time
time = Time('2015-01-23 05:54:00') - utcoffset
Polluxaltaz = Pollux.transform_to(AltAz(obstime=time, location=Oneida))
print Polluxaltaz.alt.deg
print("Pollux's Altitude = {0.alt:.2}".format(Polluxaltaz))
print Polluxaltaz.secz
EWs = EWU.EWObservations("../EWs/" + DateUT + "-" + Grating +
"-Albedo-EW.txt")
EWs.load_records("Jupiter", BandID)
#print EWs.DateTimeUTObs
#print EWs.EW
TimePlot.Setup_PlotDate(min(EWs.DateTimeUTObs), max(EWs.DateTimeUTObs), 1)
pl.plot_date(EWs.DateTimeUTObs, EWs.EW)
print "Average EW, Std. Dev., 95% Conf.= ",np.mean(EWs.EW),np.std(EWs.EW),\
1.96*np.std(EWs.EW)/np.sqrt(len(EWs.EW))
######################
airmass = []
CMII = []
for d in EWs.DateTimeUTObs:
observer.date = d
Planet = ephem.Jupiter(d)
Planet.compute(observer)
#print float(Planet.alt)*180./np.pi
airmass.extend([pyasl.airmassPP(90. - Planet.alt * 180. / np.pi)])
#print Planet.cmlII
CMII.append(Planet.cmlII * 180. / np.pi)
#print airmass
AirmassPlot.Setup_Plot()
pl.scatter(np.array(airmass), EWs.EW)
Coefs = np.polyfit(np.array(airmass), EWs.EW, 1)
EWFit = Coefs[1] + Coefs[0] * np.array(airmass)
pl.plot(np.array(airmass), EWFit)
corr = np.corrcoef([np.array(airmass), EWs.EW])
print "Coefs= ", Coefs
print "Correlation Coef.= ", corr[0, 1]
#CoefsUT=np.polyfit(np.array(EWs.DateTimeUTObs), EWs.EW, 1)
CMIIPlot.Setup_Plot()
pl.scatter(np.array(CMII), EWs.EW)