def test_julian2num():
mdates._reset_epoch_test_example()
mdates.set_epoch('0000-12-31')
# 2440587.5 is julian date for 1970-01-01T00:00:00
# https://en.wikipedia.org/wiki/Julian_day
assert mdates.julian2num(2440588.5) == 719164.0
assert mdates.num2julian(719165.0) == 2440589.5
# set back to the default
mdates._reset_epoch_test_example()
mdates.set_epoch('1970-01-01T00:00:00')
assert mdates.julian2num(2440588.5) == 1.0
assert mdates.num2julian(2.0) == 2440589.5
def testrow(row, currenttime, mindeg, toolate, tooearly, TimePre, TimePost):
testime = float(row[6])
now2 = dates.date2num(currenttime)
testtime = dates.julian2num(testime)
tester1 = False
if now2 >= testtime:
res = False
else:
if row[4] < mindeg:
res = False
elif row[12] < mindeg:
res = False
else:
ht = int(toolate[0:2])
mt = int(toolate[3:5])
time = jd2gd(float(row[14]))[1]
if time[-2:] == "AM":
h = int(time[0:2])
m = int(time[3:5]) + TimePost # the additional 20 is for post transit observations
if m > 60:
m = m - 60
h = h + 1
if h == ht:
if m <= mt:
tester1 = True
else:
res = False
elif h < ht:
tester1 = True
else:
res = False
if tester1 == True:
tester1 = False
ht = int(tooearly[0:2])
mt = int(tooearly[3:5])
time = jd2gd(float(row[6]))[1]
if time[-2:] == "AM":
h = int(time[0:2])
m = int(time[3:5]) - TimePre # the additional 20 is for post transit observations
if m < 0:
m = m + 60
h = h - 1
if h == ht:
if m >= mt:
tester1 = True
else:
res = False
elif h > ht:
tester1 = True
else:
res = False
if tester1 == True:
res = True
else:
res = False
else:
res = False
return res
def doy2date(year, doy):
"""
Convert day of year to date if year is known
"""
date_0 = datetime
jul_0 = dates.num2julian(dates.date2num(date_0.date(year, 1, 1)))
date = dates.num2date(dates.julian2num(jul_0 + doy -
1)) #jul2date(jul_0+doy-1)
return date
def na_back_tree(
data_root=RAW_DATA_ROOT,
start=None,
stop=None,
calibration=None,
photometry=None,
show=False,
ccddata_cls=FwRedCorData, # less verbose
**kwargs):
dirs_dates = get_dirs_dates(data_root, start=start, stop=stop)
dirs, _ = zip(*dirs_dates)
if len(dirs) == 0:
log.warning('No directories found')
return
if calibration is None:
calibration = Calibration(reduce=True)
if photometry is None:
photometry = Photometry(precalc=True, **kwargs)
to_plot_list = []
na_back_list = []
for d in dirs:
nb = na_back_directory(d,
calibration=calibration,
photometry=photometry,
ccddata_cls=ccddata_cls,
**kwargs)
if nb == {}:
continue
na_back_list.extend(nb['na_back_list'])
del nb['na_back_list']
to_plot_list.append(nb)
# --> write to_plot_list
df = pd.DataFrame(to_plot_list)
plot_dates = julian2num(df['jd'])
f = plt.figure() #figsize=[8.5, 11])
plt.suptitle(
f"Na background {df['date'].iloc[0]} -- {df['date'].iloc[-1]}")
plt.plot_date(plot_dates, df['biweight_back'], 'k.')
plt.plot_date(plot_dates, df['biweight_back'] + df['mad_std_back'], 'kv')
plt.plot_date(plot_dates, df['biweight_back'] - df['mad_std_back'], 'k^')
#plt.errorbar(plot_dates, df['biweight_back'])
plt.ylim([0, 0.07])
plt.ylabel('electron/s/pix^2')
plt.gcf().autofmt_xdate() # orient date labels at a slant
if show:
plt.show()
return to_plot_list
def jd2gd(juldat):
""" Convert a numerial Julian date into a Gregorian date using Pylab.
Timezone returned will be UTC.
:EXAMPLES:
::
print jd2gd(2454324.5) #--> 2007-08-12 00:00:00
print jd2gd(2451545) #--> 2000-01-01 12:00:00
:SEE ALSO: :func:`gd2jd`"""
# 2008-08-26 14:03 IJC: Created
# 2011-01-22 16:24 IJC: Removed arbitrary (?) subtraction of 3442850 from 'd'
import matplotlib.dates as dates
d = dates.julian2num(juldat)
gd = dates.num2date(d )
return gd
def jd2gd(juldat):
""" Convert a numerial Julian date into a Gregorian date using Pylab.
Timezone returned will be UTC.
:EXAMPLES:
::
print jd2gd(2454324.5) #--> 2007-08-12 00:00:00
print jd2gd(2451545) #--> 2000-01-01 12:00:00
:SEE ALSO: :func:`gd2jd`"""
# 2008-08-26 14:03 IJC: Created
# 2011-01-22 16:24 IJC: Removed arbitrary (?) subtraction of 3442850 from 'd'
import matplotlib.dates as dates
d = dates.julian2num(juldat)
gd = dates.num2date(d)
return gd
def jd2gd(juldat):
""" Convert a numerial Julian date into a Gregorian date using Pylab.
Timezone returned will be UTC.
EXAMPLES:
print jd2gd(2454324.5) --> 2007-08-12 00:00:00
print jd2gd(2451545) --> 2000-01-01 12:00:00
SEE ALSO: gd2jd"""
# 2008-08-26 14:03 IJC: Created
strtest = str(juldat)[0] + str(juldat)[1]
if not strtest == "24":
juldattsrt = "24" + str(juldat)
juldat = float(juldattsrt)
d = dates.julian2num(juldat)
# gd = dates.num2date(d - 3442850)
gd = dates.num2date(d)
Date = str(gd.month) + "/" + str(gd.day) + "/" + str(gd.year)[2:]
hour = gd.hour
if hour > 12:
hrn = hour - 12
hr = str(hrn)
AMPM = "PM"
if hrn < 10:
hr = "0" + hr
else:
hr = str(hour)
AMPM = "AM"
if hour < 10:
hr = "0" + hr
if gd.minute < 10:
mnH = gd.minute
mn = "0" + str(mnH)
else:
mn = str(gd.minute)
if gd.second < 10:
scH = gd.second
sc = "0" + str(scH)
else:
sc = str(gd.second)
Time = hr + ":" + mn + ":" + sc + " " + AMPM
return Date, Time
def checkVisPA(ra, dec, targetName=None, ephFileName=None, fig=None):
"""Check the visibility at a range of position angles.
Parameters
----------
ra: str
The RA of the target in hh:mm:ss.s or dd:mm:ss.s or representing a float
dec: str
The Dec of the target in hh:mm:ss.s or dd:mm:ss.s or representing a float
targetName: str
The target name
ephFileName: str
The filename of the ephemeris file
fig: bokeh.plotting.figure
The figure to plot to
Returns
-------
paGood : float
The good position angle.
paBad : float
The bad position angle.
gd : matplotlib.dates object
The greogrian date.
fig : bokeh.plotting.figure object
The plotted figure.
"""
if ephFileName is None:
eph_file = 'data/contam_visibility/JWST_ephem_short.txt'
ephFileName = pkg_resources.resource_filename('exoctk', eph_file)
if ra.find(':') > -1: # format is hh:mm:ss.s or dd:mm:ss.s
ra = convert_ddmmss_to_float(ra) * 15. * D2R
dec = convert_ddmmss_to_float(dec) * D2R
else: # format is decimal
ra = float(ra) * D2R
dec = float(dec) * D2R
# load ephemeris
eclFlag = False
eph = EPH.Ephemeris(ephFileName, eclFlag)
# convert dates from MJD to Gregorian calendar dates
mjd = np.array(eph.datelist)
d = mdates.julian2num(mjd + 2400000.5)
gd = mdates.num2date(d)
# loop through dates and determine VIS and PAs (nominal, min, max)
vis = np.empty(mjd.size, dtype=bool)
paNom = np.empty(mjd.size)
paMin = np.empty(mjd.size)
paMax = np.empty(mjd.size)
for i in range(mjd.size):
# is it visible?
vis[i] = eph.in_FOR(mjd[i], ra, dec)
# nominal PA at this date
pa = eph.normal_pa(mjd[i], ra, dec)
# search for minimum PA allowed by roll
pa0 = pa
while eph.is_valid(mjd[i], ra, dec, pa0 - 0.002):
pa0 -= 0.002
# search for maximum PA allowed by roll
pa1 = pa
while eph.is_valid(mjd[i], ra, dec, pa1 + 0.002):
pa1 += 0.002
paNom[i] = (pa * R2D) % 360
paMin[i] = (pa0 * R2D) % 360
paMax[i] = (pa1 * R2D) % 360
# does PA go through 360 deg?
wrap = np.any(np.abs(np.diff(paNom[np.where(vis)[0]])) > 350)
# Determine good and bad PA ranges
# Good PAs
i, = np.where(vis)
pa = np.concatenate((paNom[i], paMin[i], paMax[i]))
if wrap:
pa = np.append(pa, (0., 360.))
pa.sort()
i1, = np.where(np.diff(pa) > 10)
i0 = np.insert(i1 + 1, 0, 0)
i1 = np.append(i1, -1)
paGood = np.dstack((pa[i0], pa[i1])).round(1).reshape(-1, 2).tolist()
# bad PAs (complement of the good PAs)
paBad = []
if paGood[0][0] > 0:
paBad.append([0., paGood[0][0]])
for i in range(1, len(paGood)):
paBad.append([paGood[i - 1][1], paGood[i][0]])
if paGood[-1][1] < 360.:
paBad.append([paGood[-1][1], 360.])
# Make a figure
if fig is None or fig:
tools = 'crosshair, reset, hover, save'
radec = ', '.join([str(ra), str(dec)])
fig = figure(tools=tools,
plot_width=800,
plot_height=400,
x_axis_type='datetime',
title=targetName or radec)
# Do all figure calculations
iBad, = np.where(vis == False)
paMasked = np.copy(paNom)
paMasked[iBad] = np.nan
gdMasked = np.copy(gd)
i = np.argmax(paNom)
if paNom[i + 1] < 10:
i += 1
paMasked = np.insert(paMasked, i, np.nan)
gdMasked = np.insert(gdMasked, i, gdMasked[i])
i = np.argmax(paMin)
goUp = paMin[i - 2] < paMin[i - 1] # PA going up at wrap point?
# Top part
i0_top = 0 if goUp else i
i1_top = i if goUp else paMin.size - 1
paMaxTmp = np.copy(paMax)
paMaxTmp[np.where(paMin > paMax)[0]] = 360
# Bottom part
i = np.argmin(paMax)
i0_bot = i if goUp else 0
i1_bot = paMin.size - 1 if goUp else i
paMinTmp = np.copy(paMin)
paMinTmp[np.where(paMin > paMax)[0]] = 0
# Convert datetime to a number for Bokeh
gdMaskednum = [
datetime.date(2019, 6, 1) + datetime.timedelta(days=n)
for n, d in enumerate(gdMasked)
]
color = 'green'
# Draw the curve and error
try:
fig.line(gdMaskednum,
paMasked,
legend_label='cutoff',
line_color=color)
except AttributeError:
fig.line(gdMaskednum, paMasked, legend='cutoff', line_color=color)
# Top
terr_y = np.concatenate(
[paMin[i0_top:i1_top + 1], paMaxTmp[i0_top:i1_top + 1][::-1]])
terr_x = np.concatenate(
[gdMaskednum[i0_top:i1_top + 1], gdMaskednum[i0_top:i1_top + 1][::-1]])
fig.patch(terr_x, terr_y, color=color, fill_alpha=0.2, line_alpha=0)
# Bottom
berr_y = np.concatenate(
[paMinTmp[i0_bot:i1_bot + 1], paMax[i0_bot:i1_bot + 1][::-1]])
berr_x = np.concatenate(
[gdMaskednum[i0_bot:i1_bot + 1], gdMaskednum[i0_bot:i1_bot + 1][::-1]])
fig.patch(berr_x, berr_y, color='red', fill_alpha=0.2, line_alpha=0)
from bokeh.plotting import show
show(fig)
# Plot formatting
fig.xaxis.axis_label = 'Date'
fig.yaxis.axis_label = 'Aperture Position Angle (degrees)'
return paGood, paBad, gd, fig
def na_back_directory(directory,
calibration=True,
read_pout=True,
write_pout=True,
write_plot=True,
create_outdir=True,
show=False,
**kwargs):
rd = reduced_dir(directory, create=False)
poutname = os.path.join(rd, 'Na_back.pout')
pout = cached_pout(na_back_pipeline,
poutname=poutname,
read_pout=read_pout,
write_pout=write_pout,
create_outdir=create_outdir,
directory=directory,
**kwargs)
if len(pout) == 0:
log.debug(f'no Na background measurements found in {directory}')
return {}
_, pipe_meta = zip(*pout)
na_back_list = [pm['Na_back'] for pm in pipe_meta]
df = pd.DataFrame(na_back_list)
df.sort_values('jd')
just_date = df['date'].iloc[0]
instr_mag = u.Magnitude(df['best_back'] * u.electron / u.s / u.pix**2)
df['instr_mag'] = instr_mag
#tdf = df.loc[df['airmass'] < 2.0]
tdf = df.loc[df['airmass'] < 2.5]
mean_back = np.mean(tdf['best_back'])
std_back = np.std(tdf['best_back'])
biweight_back = biweight_location(tdf['best_back'])
mad_std_back = mad_std(tdf['best_back'])
# https://stackoverflow.com/questions/20664980/pandas-iterate-over-unique-values-of-a-column-that-is-already-in-sorted-order
# and
# https://pandas.pydata.org/pandas-docs/stable/user_guide/groupby.html
#https://matplotlib.org/stable/tutorials/intermediate/color_cycle.html
offset_cycler = cycler(color=['r', 'g', 'b', 'y'])
plt.rc('axes', prop_cycle=offset_cycler)
f = plt.figure(figsize=[8.5, 11])
plt.suptitle(f"Na background {just_date}")
offset_groups = df.groupby(['raoff', 'decoff']).groups
ax = plt.subplot(3, 1, 1)
for offset_idx in offset_groups:
gidx = offset_groups[offset_idx]
gdf = df.iloc[gidx]
plot_dates = julian2num(gdf['jd'])
plt.plot_date(plot_dates,
gdf['best_back'],
label=f"dRA {gdf.iloc[0]['raoff']} "
f"dDEC {gdf.iloc[0]['decoff']} armin")
plt.axhline(y=biweight_back, color='red')
plt.axhline(y=biweight_back + mad_std_back,
linestyle='--',
color='k',
linewidth=1)
plt.axhline(y=biweight_back - mad_std_back,
linestyle='--',
color='k',
linewidth=1)
plt.text(0.5,
biweight_back + 0.1 * mad_std_back,
f'{biweight_back:.4f} +/- {mad_std_back:.4f}',
ha='center',
transform=ax.get_yaxis_transform())
plt.xlabel('date')
plt.ylabel('electron/s')
ax.legend()
ax = plt.subplot(3, 1, 2)
for offset_idx in offset_groups:
gidx = offset_groups[offset_idx]
gdf = df.iloc[gidx]
plt.plot(gdf['airmass'], gdf['instr_mag'], '.')
#plt.axhline(y=biweight_back, color='red')
#plt.axhline(y=biweight_back+mad_std_back,
# linestyle='--', color='k', linewidth=1)
#plt.axhline(y=biweight_back-mad_std_back,
# linestyle='--', color='k', linewidth=1)
plt.xlabel('Airmass')
plt.ylabel('mag (electron/s/pix^2')
ax = plt.subplot(3, 1, 3)
for offset_idx in offset_groups:
gidx = offset_groups[offset_idx]
gdf = df.iloc[gidx]
plt.plot(gdf['alt'], gdf['best_back'], '.')
plt.axhline(y=biweight_back, color='red')
plt.axhline(y=biweight_back + mad_std_back,
linestyle='--',
color='k',
linewidth=1)
plt.axhline(y=biweight_back - mad_std_back,
linestyle='--',
color='k',
linewidth=1)
plt.xlabel('Alt')
plt.ylabel('electron/s')
f.subplots_adjust(hspace=0.3)
if write_plot is True:
write_plot = os.path.join(rd, 'Na_back.png')
if isinstance(write_plot, str):
plt.savefig(write_plot, transparent=True)
if show:
plt.show()
plt.close()
# Problem discussed in https://mail.python.org/pipermail/tkinter-discuss/2019-December/004153.html
gc.collect()
return {
'date': just_date,
'jd': np.floor(df['jd'].iloc[0]),
'biweight_back': biweight_back,
'mad_std_back': mad_std_back,
'na_back_list': na_back_list
}
def jul2date(jul_date):
date1 = dates.num2date(dates.julian2num(jul_date))
return '%d.%d.%d'%(date1.year, date1.month, date1.day)
def doy2date(year, doy):
date_0 = datetime
jul_0 = dates.num2julian( dates.date2num(date_0.date(year,1,1)) )
date = dates.num2date(dates.julian2num(jul_0+doy-1)) #jul2date(jul_0+doy-1)
return date
def jul2date2(jul_date):
date1 = dates.num2date(dates.julian2num(jul_date))
return date1
def checkVisPA(ra, dec, targetName=None, ephFileName=None, fig=None):
"""Check the visibility at a range of position angles
Parameters
----------
ra: float
The RA of the target
dec: float
The Dec of the target
targetName: str
The target name
ephFileName: str
The filename of the ephemeris file
fig: matplotlib.pyplot.figure, bokeh.plotting.figure
The figure to plot to
Returns
-------
paGood : float
The good position angle.
paBad : float
The bad position angle.
gd : matplotlib.dates object
The greogrian date.
fig : matplotlib.pyplot object
The plotted figure.
"""
if ephFileName is None:
eph_file = 'data/contam_visibility/JWST_ephem_short.txt'
ephFileName = pkg_resources.resource_filename('exoctk', eph_file)
if ra.find(':') > -1: # format is hh:mm:ss.s or dd:mm:ss.s
ra = convert_ddmmss_to_float(ra) * 15. * D2R
dec = convert_ddmmss_to_float(dec) * D2R
else: # format is decimal
ra = float(ra) * D2R
dec = float(dec) * D2R
# load ephemeris
eclFlag = False
eph = EPH.Ephemeris(ephFileName, eclFlag)
# convert dates from MJD to Gregorian calendar dates
mjd = np.array(eph.datelist)
d = mdates.julian2num(mjd + 2400000.5)
gd = mdates.num2date(d)
# loop through dates and determine VIS and PAs (nominal, min, max)
vis = np.empty(mjd.size, dtype=bool)
paNom = np.empty(mjd.size)
paMin = np.empty(mjd.size)
paMax = np.empty(mjd.size)
for i in range(mjd.size):
# is it visible?
vis[i] = eph.in_FOR(mjd[i], ra, dec)
# nominal PA at this date
pa = eph.normal_pa(mjd[i], ra, dec)
# search for minimum PA allowed by roll
pa0 = pa
while eph.is_valid(mjd[i], ra, dec, pa0 - 0.002):
pa0 -= 0.002
# search for maximum PA allowed by roll
pa1 = pa
while eph.is_valid(mjd[i], ra, dec, pa1 + 0.002):
pa1 += 0.002
paNom[i] = (pa * R2D) % 360
paMin[i] = (pa0 * R2D) % 360
paMax[i] = (pa1 * R2D) % 360
# does PA go through 360 deg?
wrap = np.any(np.abs(np.diff(paNom[np.where(vis)[0]])) > 350)
# Determine good and bad PA ranges
# Good PAs
i, = np.where(vis)
pa = np.concatenate((paNom[i], paMin[i], paMax[i]))
if wrap:
pa = np.append(pa, (0., 360.))
pa.sort()
i1, = np.where(np.diff(pa) > 10)
i0 = np.insert(i1 + 1, 0, 0)
i1 = np.append(i1, -1)
paGood = np.dstack((pa[i0], pa[i1])).round(1).reshape(-1, 2).tolist()
# bad PAs (complement of the good PAs)
paBad = []
if paGood[0][0] > 0:
paBad.append([0., paGood[0][0]])
for i in range(1, len(paGood)):
paBad.append([paGood[i - 1][1], paGood[i][0]])
if paGood[-1][1] < 360.:
paBad.append([paGood[-1][1], 360.])
# Make a figure
if fig is None or fig == True:
fig = plt.gcf()
# Do all figure calculations
iBad, = np.where(vis == False)
paMasked = np.copy(paNom)
paMasked[iBad] = np.nan
gdMasked = np.copy(gd)
i = np.argmax(paNom)
if paNom[i + 1] < 10:
i += 1
paMasked = np.insert(paMasked, i, np.nan)
gdMasked = np.insert(gdMasked, i, gdMasked[i])
i = np.argmax(paMin)
goUp = paMin[i - 2] < paMin[i - 1] # PA going up at wrap point?
# Top part
i0_top = 0 if goUp else i
i1_top = i if goUp else paMin.size - 1
paMaxTmp = np.copy(paMax)
paMaxTmp[np.where(paMin > paMax)[0]] = 360
# Bottom part
i = np.argmin(paMax)
i0_bot = i if goUp else 0
i1_bot = paMin.size - 1 if goUp else i
paMinTmp = np.copy(paMin)
paMinTmp[np.where(paMin > paMax)[0]] = 0
# Add fits to matplotlib
if isinstance(fig, matplotlib.figure.Figure):
# Make axes
ax = plt.axes()
plt.title(targetName)
# plot nominal PA
plt.plot(gdMasked, paMasked, color='k')
# plot ranges allowed through roll
if wrap:
i = np.argmax(paMin)
goUp = paMin[i - 2] < paMin[i - 1] # PA going up at wrap point?
# top part
plt.fill_between(gd[i0_top:i1_top + 1],
paMin[i0_top:i1_top + 1],
paMaxTmp[i0_top:i1_top + 1],
where=vis[i0_top:i1_top + 1],
lw=0,
facecolor='k',
alpha=0.5)
# bottom part
plt.fill_between(gd[i0_bot:i1_bot + 1],
paMinTmp[i0_bot:i1_bot + 1],
paMax[i0_bot:i1_bot + 1],
where=vis[i0_bot:i1_bot + 1],
lw=0,
facecolor='k',
alpha=0.5)
else:
plt.fill_between(gd,
paMin,
paMax,
where=vis,
lw=0,
facecolor='k',
alpha=0.5)
plt.ylabel('Position Angle (degrees)')
plt.xlim(min(gd), max(gd))
ax.xaxis.set_major_locator(mdates.MonthLocator())
ax.xaxis.set_major_formatter(mdates.DateFormatter("%b '%y"))
ax.xaxis.set_minor_locator(mdates.DayLocator(list(range(1, 32, 5))))
plt.ylim(0, 360)
ax.yaxis.set_major_locator(MultipleLocator(25))
ax.yaxis.set_minor_locator(MultipleLocator(5))
plt.grid()
for label in ax.get_xticklabels():
label.set_rotation(45)
# Or to bokeh!
else:
# Convert datetime to a number for Bokeh
gdMaskednum = [
datetime.date(2019, 6, 1) + datetime.timedelta(days=n)
for n, d in enumerate(gdMasked)
]
color = 'green'
# Draw the curve and error
fig.line(gdMaskednum, paMasked, legend='cutoff', line_color=color)
# Top
err_y = np.concatenate(
[paMin[i0_top:i1_top + 1], paMaxTmp[i0_top:i1_top + 1][::-1]])
err_x = np.concatenate([
gdMaskednum[i0_top:i1_top + 1],
gdMaskednum[i0_top:i1_top + 1][::-1]
])
fig.patch(err_x, err_y, color=color, fill_alpha=0.2, line_alpha=0)
# Bottom
err_y = np.concatenate(
[paMinTmp[i0_bot:i1_bot + 1], paMax[i0_bot:i1_bot + 1][::-1]])
err_x = np.concatenate([
gdMaskednum[i0_bot:i1_bot + 1],
gdMaskednum[i0_bot:i1_bot + 1][::-1]
])
fig.patch(err_x, err_y, color=color, fill_alpha=0.2, line_alpha=0)
# Plot formatting
fig.xaxis.axis_label = 'Date'
fig.yaxis.axis_label = 'Position Angle (degrees)'
return paGood, paBad, gd, fig
def conj_time_save_to_file(filename, sys_conj_time, r_mode, dps_mode, conjunction_crit, \
global_s_time, global_e_time, date_format='jd', pickle_file = False, to_append = False):
"""
-filename: string (doesn't include format)
-sys_conj_time: dictionary
-r_mode: string
-dps_mode: string
-global_s_time: float
-global_e_time: float
-verbose: bool
# always write to txt file
"""
fns = []
if pickle_file:
if to_append:
pkfile = open(filename + '.pickle', 'a+b')
else:
pkfile = open(filename + '.pickle', 'w')
fns.append(filename + '.pickle')
pickle.dump(sys_conj_time, pkfile)
pkfile.close()
if to_append:
datafile = open(filename + '.txt', 'a+b')
else:
datafile = open(filename + '.txt', 'w')
fns.append(filename + '.txt')
if date_format == 'jd':
global_s_time_str = str(global_s_time)
global_e_time_str = str(global_e_time)
else:
global_s_time_str = str(dates.num2date(
dates.julian2num(global_s_time)))
global_e_time_str = str(dates.num2date(
dates.julian2num(global_e_time)))
datafile.write('Search for planet conjuction from time ' +
global_s_time_str + ' to ' + global_e_time_str + ': \n')
datafile.write('*********************************\n')
datafile.write('Planet radius : ' + r_mode + '\n')
datafile.write(
'Distance from the planet to (earth-star) line of sight : ' +
dps_mode + '\n')
datafile.write('*********************************\n')
datafile.write('Criterion for conjunction (distance <= ?): ' +
conjunction_crit + '\n')
datafile.write('*********************************\n')
for sys_n in sorted(sys_conj_time.keys()):
# datafile.write('System '+str(sys_n)+' (number of planets: '+ \
# str(sys_conj_time[sys_n]['n_planets'])+'): \n')
sys_str = 'System '+str(sys_n)+' (number of planets: '+ \
str(sys_conj_time[sys_n]['n_planets'])+'): \n'
sys_str_print = 0
for n_members in sorted(sys_conj_time[sys_n].keys()):
if n_members == 'n_planets':
continue
# datafile.write('\t----------------\n')
# datafile.write('\tSearching alignment of '+str(n_members)+' planets: \n')
search_str = '\t----------------\n\tSearching alignment of ' + str(
n_members) + ' planets: \n'
search_str_print = 0
for participants in sorted(sys_conj_time[sys_n][n_members].keys()):
n_conjs = sys_conj_time[sys_n][n_members][participants][
'n_conjs']
if n_conjs <= 0:
continue
else:
if sys_str_print == 0:
datafile.write(sys_str)
sys_str_print = 1
if search_str_print == 0:
datafile.write(search_str)
search_str_print = 1
datafile.write('\t\t----------------\n')
datafile.write('\t\tParticipants: ' + str(participants) +
': \n')
start_times = sys_conj_time[sys_n][n_members][participants][
'start_points']
end_times = sys_conj_time[sys_n][n_members][participants][
'end_points']
mid_times = sys_conj_time[sys_n][n_members][participants][
'mid_points']
s_ang_sep = sys_conj_time[sys_n][n_members][participants][
's_ang_sep']
e_ang_sep = sys_conj_time[sys_n][n_members][participants][
'e_ang_sep']
conj_crit = sys_conj_time[sys_n][n_members][participants][
'conj_crit']
conjunction_period = sys_conj_time[sys_n][n_members][
participants]['conjunction_period']
non_conjunction_period = sys_conj_time[sys_n][n_members][
participants]['non_conjunction_period']
p_pers = sys_conj_time[sys_n][n_members][participants][
'participants_periods']
p_radii = sys_conj_time[sys_n][n_members][participants][
'participants_radii']
p_teqs = sys_conj_time[sys_n][n_members][participants][
'participants_teqs']
s_angs = sys_conj_time[sys_n][n_members][participants][
's_angs']
e_angs = sys_conj_time[sys_n][n_members][participants][
'e_angs']
incomplete_flag = sys_conj_time[sys_n][n_members][
participants]['incomplete_flag']
notes = sys_conj_time[sys_n][n_members][participants]['notes']
datafile.write('\t\tConjunctions start at: \n')
if date_format == 'jd':
datafile.write('\t\t\t' +
str([x + 2454900
for x in start_times]) + '\n')
else:
for x in start_times:
datafile.write('\t\t\t')
datafile.write(
str(dates.num2date(dates.julian2num(x +
2454900))) +
'\n')
datafile.write('\t\tConjunctions end at: \n')
if date_format == 'jd':
datafile.write('\t\t\t' +
str([x + 2454900
for x in end_times]) + '\n')
else:
for x in end_times:
if x < 0:
x_str = '0'
else:
x_str = str(
dates.num2date(dates.julian2num(x + 2454900)))
datafile.write('\t\t\t' + x_str + '\n')
datafile.write('\t\t>>> Mid time: \n')
if date_format == 'jd':
datafile.write('\t\t\t' +
str([x + 2454900
for x in mid_times]) + '\n')
else:
for x in mid_times:
datafile.write('\t\t\t')
datafile.write(
str(dates.num2date(dates.julian2num(x +
2454900))) +
'\n')
datafile.write(
'\t\t Conjunction Criterion (unit: Solar Radius): \n')
datafile.write('\t\t\t' + str(conj_crit) + '\n')
datafile.write('\t\t Number of Conjunctions: \n')
datafile.write('\t\t\t' + str(n_conjs) + '\n')
datafile.write(
'\t\t Maximum separation among planets when conjunction starts (unit: Solar Radius): \n'
)
datafile.write('\t\t\t' + str(s_ang_sep) + '\n')
datafile.write(
'\t\t Maximum separation among planets when conjunction ended (unit: Solar Radius): \n'
)
datafile.write('\t\t\t' + str(e_ang_sep) + '\n')
datafile.write('\t\t Conjunction durations (hours): \n')
datafile.write('\t\t\t' +
str([p * 24.0
for p in conjunction_period]) + '\n')
datafile.write(
'\t\t Time period between conjunctions (hours): \n')
datafile.write('\t\t\t' +
str([p * 24.0
for p in non_conjunction_period]) + '\n')
datafile.write('\t\t Period of participants (days): \n')
datafile.write('\t\t\t' + str(p_pers) + '\n')
datafile.write(
'\t\t Radii of participants (unit: Solar Radius):\n')
datafile.write('\t\t\t' + str(p_radii) + '\n')
datafile.write(
'\t\t Equilibrium temperature of participants (unit: Solar Radius):\n'
)
datafile.write('\t\t\t' + str(p_teqs) + '\n')
datafile.write(
'\t\t Position (angular) of participants at start time(unit: radian): \n'
)
datafile.write('\t\t\t' + str(s_angs) + '\n')
datafile.write(
'\t\t Position (angular) of participants at end time(unit: radian): \n'
)
datafile.write('\t\t\t' + str(e_angs) + '\n')
if incomplete_flag:
datafile.write(
'\t\tNote: there are incomplete conjunctions recorded!\n'
)
for note_item in notes:
datafile.write('\t\t\t' + note_item + '\n')
datafile.write('\t\t----------------\n')
if search_str_print:
datafile.write('\t----------------\n')
if sys_str_print:
datafile.write('\n------------------------------------\n')
datafile.close()
return fns
def checkVisPA(ra, dec, targetName=None, ephFileName=pkg_resources.resource_filename('ExoCTK', 'data/contam_visibility/JWST_ephem_short.txt'), save=False, fig=''):
if ra.find(':')>-1: #format is hh:mm:ss.s or dd:mm:ss.s
ra = convert_ddmmss_to_float(ra) * 15. * D2R
dec = convert_ddmmss_to_float(dec) * D2R
else: #format is decimal
ra = float(ra) * D2R
dec = float(dec) * D2R
#load ephemeris
eclFlag = False
eph = EPH.Ephemeris(ephFileName, eclFlag)
#convert dates from MJD to Gregorian calendar dates
mjd = np.array(eph.datelist)
d = mdates.julian2num(mjd+2400000.5)
gd = mdates.num2date(d)
#loop through dates and determine VIS and PAs (nominal, min, max)
vis = np.empty(mjd.size,dtype=bool)
paNom, paMin, paMax = np.empty(mjd.size), np.empty(mjd.size), np.empty(mjd.size)
for i in range(mjd.size):
#is it visible?
vis[i] = eph.in_FOR(mjd[i],ra,dec)
#nominal PA at this date
pa = eph.normal_pa(mjd[i],ra,dec)
#search for minimum PA allowed by roll
pa0 = pa
while eph.is_valid(mjd[i],ra,dec,pa0-0.002):
pa0 -= 0.002
#search for maximum PA allowed by roll
pa1 = pa
while eph.is_valid(mjd[i],ra,dec,pa1+0.002):
pa1 += 0.002
paNom[i] = (pa*R2D)%360
paMin[i] = (pa0*R2D)%360
paMax[i] = (pa1*R2D)%360
#does PA go through 360 deg?
wrap = np.any(np.abs(np.diff(paNom[np.where(vis)[0]])) > 350)
#Determine good and bad PA ranges
#Good PAs
i, = np.where(vis)
pa = np.concatenate((paNom[i],paMin[i],paMax[i]))
if wrap:
pa = np.append(pa,(0.,360.))
pa.sort()
i1, = np.where(np.diff(pa)>10)
i0 = np.insert(i1+1,0,0)
i1 = np.append(i1,-1)
paGood = np.dstack((pa[i0],pa[i1])).round(1).reshape(-1,2).tolist()
#bad PAs (complement of the good PAs)
paBad = []
if paGood[0][0]>0:
paBad.append([0.,paGood[0][0]])
for i in range(1,len(paGood)):
paBad.append([paGood[i-1][1],paGood[i][0]])
if paGood[-1][1]<360.:
paBad.append([paGood[-1][1],360.])
#print results to file
"""
if save:
fName='visibilityPA-'+targetName+'.txt'
fic=open(fName,'w')
fic.write('#Date MJD VIS? PAnom PArange\n')
for i in range(vis.size):
tmp1='{:7.3f}'.format(paNom[i]) if vis[i] else 7*'-'
tmp2='{:7.3f}--{:7.3f}'.format(paMin[i],paMax[i]) if vis[i] else 16*'-'
#fic.write(gd[i].strftime("%y-%m-%d")+' {:f} {:5s} {:7.3f} {:7.3f}--{:7.3f} \n'.format(mjd[i],str(vis[i]),paNom[i],paMin[i],paMax[i]))
fic.write(gd[i].strftime("%y-%m-%d")+' {:f} {:5s} {} {} \n'.format(mjd[i],str(vis[i]),tmp1,tmp2))
fic.write("\n")
fic.write("Accessible PA ranges: ")
fic.write(','.join([str(x) for x in paGood]))
fic.write("\n")
fic.write("Non-accessible PA ranges: ")
fic.write(','.join([str(x) for x in paBad]))
fic.write("\n")
fic.close()
"""
# Make a figure
if not fig or fig==True:
fig = plt.gcf()
# Do all figure calculations
iBad, = np.where(vis==False)
paMasked = np.copy(paNom)
paMasked[iBad] = np.nan
gdMasked = np.copy(gd)
i = np.argmax(paNom)
if paNom[i+1]<10:
i+=1
paMasked = np.insert(paMasked,i,np.nan)
gdMasked = np.insert(gdMasked,i,gdMasked[i])
i = np.argmax(paMin)
goUp = paMin[i-2]<paMin[i-1] #PA going up at wrap point?
# Top part
i0_top = 0 if goUp else i
i1_top = i if goUp else paMin.size-1
paMaxTmp = np.copy(paMax)
paMaxTmp[np.where(paMin>paMax)[0]] = 360
# Bottom part
i = np.argmin(paMax)
i0_bot = i if goUp else 0
i1_bot = paMin.size-1 if goUp else i
paMinTmp = np.copy(paMin)
paMinTmp[np.where(paMin>paMax)[0]] = 0
# Add fits to matplotlib
if isinstance(fig, matplotlib.figure.Figure):
# Make axes
ax = plt.axes()
plt.title(targetName)
#plot nominal PA
plt.plot(gdMasked,paMasked,color='k')
#plot ranges allowed through roll
if wrap:
i = np.argmax(paMin)
goUp = paMin[i-2]<paMin[i-1] #PA going up at wrap point?
#top part
plt.fill_between(gd[i0_top:i1_top+1],paMin[i0_top:i1_top+1],paMaxTmp[i0_top:i1_top+1],where=vis[i0_top:i1_top+1],lw=0,facecolor='k',alpha=0.5)
#bottom part
plt.fill_between(gd[i0_bot:i1_bot+1],paMinTmp[i0_bot:i1_bot+1],paMax[i0_bot:i1_bot+1],where=vis[i0_bot:i1_bot+1],lw=0,facecolor='k',alpha=0.5)
else:
plt.fill_between(gd,paMin,paMax,where=vis,lw=0,facecolor='k',alpha=0.5)
plt.ylabel('Position Angle (degrees)')
plt.xlim(min(gd),max(gd))
ax.xaxis.set_major_locator(mdates.MonthLocator())
ax.xaxis.set_major_formatter(mdates.DateFormatter("%b '%y"))
ax.xaxis.set_minor_locator(mdates.DayLocator(list(range(1,32,5))))
plt.ylim(0,360)
ax.yaxis.set_major_locator(MultipleLocator(25))
ax.yaxis.set_minor_locator(MultipleLocator(5))
plt.grid()
for label in ax.get_xticklabels():
label.set_rotation(45)
# Or to bokeh!
else:
# Convert datetime to a number for Bokeh
gdMaskednum = [datetime.date(2019, 6, 1)+datetime.timedelta(days=n) for n,d in enumerate(gdMasked)]
color = 'green'
# Draw the curve and error
fig.line(gdMaskednum, paMasked, legend='cutoff', line_color=color)
# Top
err_y = np.concatenate([paMin[i0_top:i1_top+1],paMaxTmp[i0_top:i1_top+1][::-1]])
# err_x = np.concatenate([[d.timestamp() for d in gd[i0_top:i1_top+1]],[d.timestamp() for d in gd[i0_top:i1_top+1]][::-1]])
err_x = np.concatenate([gdMaskednum[i0_top:i1_top+1],gdMaskednum[i0_top:i1_top+1][::-1]])
fig.patch(err_x, err_y, color=color, fill_alpha=0.2, line_alpha=0)
# Bottom
err_y = np.concatenate([paMinTmp[i0_bot:i1_bot+1],paMax[i0_bot:i1_bot+1][::-1]])
# err_x = np.concatenate([[d.timestamp() for d in gd[i0_bot:i1_bot+1]],[d.timestamp() for d in gd[i0_bot:i1_bot+1]][::-1]])
err_x = np.concatenate([gdMaskednum[i0_bot:i1_bot+1],gdMaskednum[i0_bot:i1_bot+1][::-1]])
fig.patch(err_x, err_y, color=color, fill_alpha=0.2, line_alpha=0)
# Plot formatting
fig.xaxis.axis_label = 'Date'
fig.yaxis.axis_label = 'Position Angle (degrees)'
return paGood, paBad, gd, fig
def checkVisPA(ra, dec, targetName=None, save=False):
if ra.find(':') > -1: #format is hh:mm:ss.s or dd:mm:ss.s
ra = convert_ddmmss_to_float(ra) * 15. * D2R
dec = convert_ddmmss_to_float(dec) * D2R
else: #format is decimal
ra = float(ra) * D2R
dec = float(dec) * D2R
#load ephemeris
ephFileName, eclFlag = os.path.join(os.path.dirname(
ExoCTK.__file__), 'data/tor/JWST_ephem_short.txt'), False
eph = EPH.Ephemeris(ephFileName, eclFlag)
#convert dates from MJD to Gregorian calendar dates
mjd = np.array(eph.datelist)
d = mdates.julian2num(mjd + 2400000.5)
gd = mdates.num2date(d)
#loop through dates and determine VIS and PAs (nominal, min, max)
vis = np.empty(mjd.size, dtype=bool)
paNom, paMin, paMax = np.empty(mjd.size), np.empty(mjd.size), np.empty(
mjd.size)
for i in range(mjd.size):
vis[i] = eph.in_FOR(mjd[i], ra, dec) #is it visible?
pa = eph.normal_pa(mjd[i], ra, dec) #nominal PA at this date
#search for minimum PA allowed by roll
pa0 = pa
while eph.is_valid(mjd[i], ra, dec, pa0 - 0.002):
pa0 -= 0.002
#search for maximum PA allowed by roll
pa1 = pa
while eph.is_valid(mjd[i], ra, dec, pa1 + 0.002):
pa1 += 0.002
paNom[i] = (pa * R2D) % 360
paMin[i] = (pa0 * R2D) % 360
paMax[i] = (pa1 * R2D) % 360
#does PA go through 360 deg?
wrap = np.any(np.abs(np.diff(paNom[np.where(vis)[0]])) > 350)
#Determine good and bad PA ranges
#Good PAs
i, = np.where(vis)
pa = np.concatenate((paNom[i], paMin[i], paMax[i]))
if wrap: pa = np.append(pa, (0., 360.))
pa.sort()
i1, = np.where(np.diff(pa) > 10)
i0 = np.insert(i1 + 1, 0, 0)
i1 = np.append(i1, -1)
paGood = np.dstack((pa[i0], pa[i1])).round(1).reshape(-1, 2).tolist()
#bad PAs (complement of the good PAs)
paBad = []
if paGood[0][0] > 0: paBad.append([0., paGood[0][0]])
for i in range(1, len(paGood)):
paBad.append([paGood[i - 1][1], paGood[i][0]])
if paGood[-1][1] < 360.: paBad.append([paGood[-1][1], 360.])
#print results to file
"""
if save:
fName='visibilityPA-'+targetName+'.txt'
fic=open(fName,'w')
fic.write('#Date MJD VIS? PAnom PArange\n')
for i in range(vis.size):
tmp1='{:7.3f}'.format(paNom[i]) if vis[i] else 7*'-'
tmp2='{:7.3f}--{:7.3f}'.format(paMin[i],paMax[i]) if vis[i] else 16*'-'
#fic.write(gd[i].strftime("%y-%m-%d")+' {:f} {:5s} {:7.3f} {:7.3f}--{:7.3f} \n'.format(mjd[i],str(vis[i]),paNom[i],paMin[i],paMax[i]))
fic.write(gd[i].strftime("%y-%m-%d")+' {:f} {:5s} {} {} \n'.format(mjd[i],str(vis[i]),tmp1,tmp2))
fic.write("\n")
fic.write("Accessible PA ranges: ")
fic.write(','.join([str(x) for x in paGood]))
fic.write("\n")
fic.write("Non-accessible PA ranges: ")
fic.write(','.join([str(x) for x in paBad]))
fic.write("\n")
fic.close()
"""
#make the plot
fig = plt.figure()
ax = plt.axes()
plt.title(targetName)
#plot nominal PA
iBad, = np.where(vis == False)
paMasked = np.copy(paNom)
paMasked[iBad] = np.nan
gdMasked = np.copy(gd)
if wrap:
i = np.argmax(paNom)
if paNom[i + 1] < 10: i += 1
paMasked = np.insert(paMasked, i, np.nan)
gdMasked = np.insert(gdMasked, i, gdMasked[i])
plt.plot(gdMasked, paMasked, color='k')
# plt.xticks(rotation = 'vertical')
#plot ranges allowed through roll
if wrap:
i = np.argmax(paMin)
goUp = paMin[i - 2] < paMin[i - 1] #PA going up at wrap point?
#top part
i0 = 0 if goUp else i
i1 = i if goUp else paMin.size - 1
paMaxTmp = np.copy(paMax)
paMaxTmp[np.where(paMin > paMax)[0]] = 360
plt.fill_between(gd[i0:i1 + 1],
paMin[i0:i1 + 1],
paMaxTmp[i0:i1 + 1],
where=vis[i0:i1 + 1],
lw=0,
facecolor='k',
alpha=0.5)
#bottom part
i = np.argmin(paMax)
i0 = i if goUp else 0
i1 = paMin.size - 1 if goUp else i
paMinTmp = np.copy(paMin)
paMinTmp[np.where(paMin > paMax)[0]] = 0
plt.fill_between(gd[i0:i1 + 1],
paMinTmp[i0:i1 + 1],
paMax[i0:i1 + 1],
where=vis[i0:i1 + 1],
lw=0,
facecolor='k',
alpha=0.5)
else:
plt.fill_between(gd,
paMin,
paMax,
where=vis,
lw=0,
facecolor='k',
alpha=0.5)
plt.ylabel('Position Angle (degrees)')
plt.xlim(min(gd), max(gd))
ax.xaxis.set_major_locator(mdates.MonthLocator())
ax.xaxis.set_major_formatter(mdates.DateFormatter("%b '%y"))
ax.xaxis.set_minor_locator(mdates.DayLocator(list(range(1, 32, 5))))
plt.ylim(0, 360)
ax.yaxis.set_major_locator(MultipleLocator(25))
ax.yaxis.set_minor_locator(MultipleLocator(5))
plt.grid()
for label in ax.get_xticklabels():
label.set_rotation(45)
if save:
# fname=tmpDir+'/visibilityPA-'+targetName+'.png'
png = mpld3.fig_to_html(fig)
return png
def conj_time_save_to_file(filename, sys_conj_time, r_mode, dps_mode, conjunction_crit, \
global_s_time, global_e_time, date_format='jd', pickle_file = False, to_append = False):
"""
-filename: string (doesn't include format)
-sys_conj_time: dictionary
-r_mode: string
-dps_mode: string
-global_s_time: float
-global_e_time: float
-verbose: bool
# always write to txt file
"""
fns = []
if pickle_file:
if to_append:
pkfile = open(filename+'.pickle', 'a+b')
else:
pkfile = open(filename+'.pickle', 'w')
fns.append(filename+'.pickle')
pickle.dump(sys_conj_time, pkfile)
pkfile.close()
if to_append:
datafile = open(filename+'.txt','a+b')
else:
datafile = open(filename+'.txt','w')
fns.append(filename+'.txt')
if date_format == 'jd':
global_s_time_str = str(global_s_time)
global_e_time_str = str(global_e_time)
else:
global_s_time_str = str(dates.num2date(dates.julian2num(global_s_time)))
global_e_time_str = str(dates.num2date(dates.julian2num(global_e_time)))
datafile.write('Search for planet conjuction from time '+global_s_time_str+' to '+global_e_time_str+': \n')
datafile.write('*********************************\n')
datafile.write('Planet radius : ' + r_mode +'\n')
datafile.write('Distance from the planet to (earth-star) line of sight : '+ dps_mode + '\n')
datafile.write('*********************************\n')
datafile.write('Criterion for conjunction (distance <= ?): '+conjunction_crit+'\n')
datafile.write('*********************************\n')
for sys_n in sorted(sys_conj_time.keys()):
# datafile.write('System '+str(sys_n)+' (number of planets: '+ \
# str(sys_conj_time[sys_n]['n_planets'])+'): \n')
sys_str = 'System '+str(sys_n)+' (number of planets: '+ \
str(sys_conj_time[sys_n]['n_planets'])+'): \n'
sys_str_print = 0
for n_members in sorted(sys_conj_time[sys_n].keys()):
if n_members == 'n_planets':
continue
# datafile.write('\t----------------\n')
# datafile.write('\tSearching alignment of '+str(n_members)+' planets: \n')
search_str = '\t----------------\n\tSearching alignment of '+str(n_members)+' planets: \n'
search_str_print = 0
for participants in sorted(sys_conj_time[sys_n][n_members].keys()):
n_conjs = sys_conj_time[sys_n][n_members][participants]['n_conjs']
if n_conjs <= 0:
continue
else:
if sys_str_print == 0:
datafile.write(sys_str)
sys_str_print = 1
if search_str_print == 0:
datafile.write(search_str)
search_str_print = 1
datafile.write('\t\t----------------\n')
datafile.write('\t\tParticipants: '+ str(participants)+': \n')
start_times = sys_conj_time[sys_n][n_members][participants]['start_points']
end_times = sys_conj_time[sys_n][n_members][participants]['end_points']
mid_times = sys_conj_time[sys_n][n_members][participants]['mid_points']
s_ang_sep = sys_conj_time[sys_n][n_members][participants]['s_ang_sep']
e_ang_sep = sys_conj_time[sys_n][n_members][participants]['e_ang_sep']
conj_crit = sys_conj_time[sys_n][n_members][participants]['conj_crit']
conjunction_period = sys_conj_time[sys_n][n_members][participants]['conjunction_period']
non_conjunction_period = sys_conj_time[sys_n][n_members][participants]['non_conjunction_period']
p_pers = sys_conj_time[sys_n][n_members][participants]['participants_periods']
p_radii = sys_conj_time[sys_n][n_members][participants]['participants_radii']
p_teqs = sys_conj_time[sys_n][n_members][participants]['participants_teqs']
s_angs = sys_conj_time[sys_n][n_members][participants]['s_angs']
e_angs = sys_conj_time[sys_n][n_members][participants]['e_angs']
incomplete_flag = sys_conj_time[sys_n][n_members][participants]['incomplete_flag']
notes = sys_conj_time[sys_n][n_members][participants]['notes']
datafile.write('\t\tConjunctions start at: \n')
if date_format == 'jd':
datafile.write('\t\t\t'+str([x+2454900 for x in start_times])+'\n')
else:
for x in start_times:
datafile.write('\t\t\t')
datafile.write(str(dates.num2date(dates.julian2num(x+2454900)))+'\n')
datafile.write('\t\tConjunctions end at: \n')
if date_format =='jd':
datafile.write('\t\t\t'+str([x+2454900 for x in end_times])+'\n')
else:
for x in end_times:
if x < 0:
x_str = '0'
else:
x_str =str(dates.num2date(dates.julian2num(x+2454900)))
datafile.write('\t\t\t'+x_str+'\n')
datafile.write('\t\t>>> Mid time: \n')
if date_format == 'jd':
datafile.write('\t\t\t'+str([x+2454900 for x in mid_times])+'\n')
else:
for x in mid_times:
datafile.write('\t\t\t')
datafile.write(str(dates.num2date(dates.julian2num(x+2454900)))+'\n')
datafile.write('\t\t Conjunction Criterion (unit: Solar Radius): \n')
datafile.write('\t\t\t'+str(conj_crit)+'\n')
datafile.write('\t\t Number of Conjunctions: \n')
datafile.write('\t\t\t'+str(n_conjs)+'\n')
datafile.write('\t\t Maximum separation among planets when conjunction starts (unit: Solar Radius): \n')
datafile.write('\t\t\t'+str(s_ang_sep)+'\n')
datafile.write('\t\t Maximum separation among planets when conjunction ended (unit: Solar Radius): \n')
datafile.write('\t\t\t'+str(e_ang_sep)+'\n')
datafile.write('\t\t Conjunction durations (hours): \n')
datafile.write('\t\t\t'+str([p*24.0 for p in conjunction_period])+'\n')
datafile.write('\t\t Time period between conjunctions (hours): \n')
datafile.write('\t\t\t'+str([p*24.0 for p in non_conjunction_period])+'\n')
datafile.write('\t\t Period of participants (days): \n')
datafile.write('\t\t\t'+str(p_pers)+'\n')
datafile.write('\t\t Radii of participants (unit: Solar Radius):\n')
datafile.write('\t\t\t'+str(p_radii)+'\n')
datafile.write('\t\t Equilibrium temperature of participants (unit: Solar Radius):\n')
datafile.write('\t\t\t'+str(p_teqs)+'\n')
datafile.write('\t\t Position (angular) of participants at start time(unit: radian): \n')
datafile.write('\t\t\t'+str(s_angs)+'\n')
datafile.write('\t\t Position (angular) of participants at end time(unit: radian): \n')
datafile.write('\t\t\t'+str(e_angs)+'\n')
if incomplete_flag:
datafile.write('\t\tNote: there are incomplete conjunctions recorded!\n')
for note_item in notes:
datafile.write('\t\t\t'+note_item+'\n')
datafile.write('\t\t----------------\n')
if search_str_print:
datafile.write('\t----------------\n')
if sys_str_print:
datafile.write('\n------------------------------------\n')
datafile.close()
return fns