def using_gtvt(ra,
dec,
instrument,
targetName='noName',
ephFileName=None,
output='bokeh'):
"""Plot the visibility (at a range of position angles) against time.
Parameters
----------
ra : str
The RA of the target (in degrees) hh:mm:ss.s or dd:mm:ss.s or representing a float
dec : str
The Dec of the target (in degrees) hh:mm:ss.s or dd:mm:ss.s or representing a float
instrument : str
Name of the instrument. Can either be (case-sensitive):
'NIRISS', 'NIRCam', 'MIRI', 'FGS', or 'NIRSpec'
ephFileName : str
The filename of the ephemeris file.
output : str
Switches on plotting with Bokeh. Parameter value must be 'bokeh'.
Returns
-------
paGood : float
The good position angle.
paBad : float
The bad position angle.
gd : matplotlib.dates object
The gregorian date.
fig : bokeh.plotting.figure object
The plotted figure.
"""
# Getting calculations from GTVT (General Target Visibility Tool)
tab = get_table(ra, dec)
gd = tab['Date']
paMin = tab[str(instrument) + ' min']
paMax = tab[str(instrument) + ' max']
paNom = tab[str(instrument) + ' nom']
v3min = tab['V3PA min']
v3max = tab['V3PA max']
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~NOTE~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Addressing NIRSpec issue*
# *the issue that NIRSpec's angle goes beyond 360 degrees with some targs,
# thus resetting back to 0 degrees, which can make the plot look weird
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
index = np.arange(0, len(paNom), 1)
for idx in index:
try:
a1 = paNom[idx]
b1 = paNom[idx + 1]
if (np.isfinite(a1)) & (np.isfinite(b1)):
delta = np.abs(a1 - b1)
if delta > 250:
gd = np.insert(gd, idx + 1, np.nan)
paMin = np.insert(paMin, idx + 1, np.nan)
paMax = np.insert(paMax, idx + 1, np.nan)
paNom = np.insert(paNom, idx + 1, np.nan)
v3min = np.insert(v3min, idx + 1, np.nan)
v3max = np.insert(v3min, idx + 1, np.nan)
except BaseException:
pass
# Setting up HoverTool parameters & other variables
COLOR = 'green'
TOOLS = 'pan, wheel_zoom, box_zoom, reset, save'
SOURCE = ColumnDataSource(
data=dict(pamin=paMin, panom=paNom, pamax=paMax, date=gd))
TOOLTIPS = [('Date', '@date{%F}'), ('Maximum Aperture PA', '@pamax'),
('Nominal Aperture PA', '@panom'),
('Minimum Aperture PA', '@pamin')]
# Time to plot
if output == 'bokeh':
fig = figure(tools=TOOLS,
plot_width=800,
plot_height=400,
x_axis_type='datetime',
title='{} Visibility with {}'.format(
targetName, instrument))
# Draw the curve and PA min/max circles
try:
nom = fig.line('date',
'panom',
line_color=COLOR,
legend_label='Nominal Aperture PA',
alpha=.5,
source=SOURCE)
except AttributeError:
nom = fig.line('date',
'panom',
line_color=COLOR,
legend='Nominal Aperture PA',
alpha=.5,
source=SOURCE)
fig.circle('date', 'pamin', color=COLOR, size=1, source=SOURCE)
fig.circle('date', 'pamax', color=COLOR, size=1, source=SOURCE)
# Adding HoverTool
fig.add_tools(
HoverTool(renderers=[nom],
tooltips=TOOLTIPS,
formatters={'date': 'datetime'},
mode='vline'))
# Plot formatting
fig.xaxis.axis_label = 'Date'
fig.yaxis.axis_label = 'Aperture Position Angle (degrees)'
fig.y_range = ranges.Range1d(0, 360)
# Making the output table
# Creating new lists w/o the NaN values
v3minnan, v3maxnan, paNomnan, paMinnan, paMaxnan, gdnan, mjds = \
[], [], [], [], [], [], []
for vmin, vmax, pnom, pmin, pmax, date in zip(v3min, v3max, paNom, paMin,
paMax, gd):
if np.isfinite(pmin):
v3minnan.append(vmin)
v3maxnan.append(vmax)
paNomnan.append(pnom)
paMinnan.append(pmin)
paMaxnan.append(pmax)
gdnan.append(date)
# Adding MJD column
mjdnan = []
for date in gdnan:
t = Time(str(date), format='iso')
mjd = t.mjd
mjdnan.append(mjd)
# Adding lists to a table object
table = Table(
[v3minnan, v3maxnan, paMinnan, paMaxnan, paNomnan, gdnan, mjdnan],
names=('min_V3_PA', 'max_V3_PA', 'min_Aperture_PA', 'max_Aperture_PA',
'nom_Aperture_PA', 'Gregorian', 'MJD'))
# Getting bad PAs
allPAs = np.arange(0, 360, 1)
badPAs = []
for pa in allPAs:
if (pa not in np.round(paMinnan)) & \
(pa not in np.round(paMaxnan)) & \
(pa not in np.round(paNomnan)):
badPAs.append(pa)
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~NOTE~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# This addresses a bokeh shading issue that accidentally shades
# accessible PAs (e.g: trappist-1b)
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
remove_pa = []
for badpa in badPAs:
for panom in paNomnan:
diff = np.abs(badpa - panom)
if diff < 7:
remove_pa.append(badpa)
for pa in np.unique(remove_pa):
badPAs.remove(pa)
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~NOTE~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Grouping the bad PAs into lists within the badPAs list.
# This will make bad PA shading easier in the contamination Bokeh plot
# (sossContamFig.py)
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
badPAs = np.sort(badPAs)
if len(badPAs > 0):
grouped_badPAs = [[badPAs[0]]]
for idx in range(1, len(badPAs)):
if ((badPAs[idx - 1] + 1) == badPAs[idx]):
grouped_badPAs[len(grouped_badPAs) - 1].append(badPAs[idx])
elif ((badPAs[idx - 1] + 1) < badPAs[idx]):
grouped_badPAs.append([badPAs[idx]])
grouped_badPAs = np.asarray(grouped_badPAs)
else: # Accounting for targets with 100% visibility
grouped_badPAs = np.asarray([])
return paMin, paMax, gd, fig, table, grouped_badPAs
def using_gtvt(ra, dec, instrument, ephFileName=None, output='bokeh'):
"""Plot the visibility (at a range of position angles) against time.
Parameters
----------
ra : float
The RA of the target.
dec : float
The Dec of the target.
instrument : str
Name of the instrument. Can either be (case-sensitive):
'NIRISS', 'NIRCam', 'MIRI', 'FGS', or 'NIRSpec'
ephFileName : str
The filename of the ephemeris file.
output : str
Switches on plotting with Bokeh. Parameter value must be 'bokeh'.
Returns
-------
paGood : float
The good position angle.
paBad : float
The bad position angle.
gd : matplotlib.dates object
The gregorian date.
fig : bokeh.plotting.figure object
The plotted figure.
"""
# getting calculations from GTVT (General Target Visibility Tool)
tab = get_table(ra, dec)
gd = tab['Date']
paMin = tab[str(instrument) + ' min']
paMax = tab[str(instrument) + ' max']
paNom = tab[str(instrument) + ' nom']
v3min = tab['V3PA min']
v3max = tab['V3PA max']
# addressing NIRSpec issue*
# *the issue that NIRSpec's angle goes beyond 360 degrees with some targs,
# thus resetting back to 0 degrees, which can make the plot look weird
index = np.arange(0, len(paNom), 1)
for idx in index:
try:
a1 = paNom[idx]
b1 = paNom[idx + 1]
if (np.isfinite(a1) == True) & (np.isfinite(b1) == True):
delta = np.abs(a1 - b1)
if delta > 250:
print(a1, b1, delta)
gd = np.insert(gd, idx + 1, np.nan)
paMin = np.insert(paMin, idx + 1, np.nan)
paMax = np.insert(paMax, idx + 1, np.nan)
paNom = np.insert(paNom, idx + 1, np.nan)
v3min = np.insert(v3min, idx + 1, np.nan)
v3max = np.insert(v3min, idx + 1, np.nan)
except:
pass
# Setting up HoverTool parameters & other variables
COLOR = 'green'
TOOLS = 'pan, wheel_zoom, box_zoom, reset, save'
SOURCE = ColumnDataSource(data=dict(pamin=paMin,\
panom=paNom,\
pamax=paMax,\
date=gd))
TOOLTIPS = [('Date','@date{%F}'),\
('Maximum Aperture PA', '@pamax'),\
('Nominal Aperture PA', '@panom'),\
('Minimum Aperture PA', '@pamin')]
# Time to plot
if output == 'bokeh':
fig = figure(tools=TOOLS,\
plot_width=800,\
plot_height=400,\
x_axis_type='datetime',\
title='Target Visibility with '+str(instrument))
# Draw the curve and PA min/max patch
fig.circle('date', 'panom', color=COLOR, size=1, legend='Nominal Aperture PA',\
source=SOURCE, alpha=.5)
fig.circle('date', 'pamin', color=COLOR, size=1, source=SOURCE)
fig.circle('date', 'pamax', color=COLOR, size=1, source=SOURCE)
# Adding HoverTool
fig.add_tools(HoverTool(tooltips=TOOLTIPS,\
formatters={'date':'datetime'},\
mode='vline'))
# Plot formatting
fig.xaxis.axis_label = 'Date'
fig.yaxis.axis_label = 'Position Angle (degrees)'
fig.y_range = ranges.Range1d(0, 360)
# Making the output table
# Creating new lists w/o the NaN values
v3minnan, v3maxnan, paNomnan, paMinnan, paMaxnan, gdnan, mjds = \
[], [], [], [], [], [], []
for vmin, vmax, pnom, pmin, pmax, date in zip(v3min, v3max, paNom, paMin,
paMax, gd):
if np.isfinite(pmin) == True:
v3minnan.append(vmin)
v3maxnan.append(vmax)
paNomnan.append(pnom)
paMinnan.append(pmin)
paMaxnan.append(pmax)
gdnan.append(date)
# Adding MJD column
mjdnan = []
for date in gdnan:
t = Time(str(date), format='iso')
mjd = t.mjd
mjdnan.append(mjd)
# Adding lists to a table object
table = Table([v3minnan, v3maxnan, paMinnan, paMaxnan, paNomnan, gdnan, mjdnan],\
names=('#min_V3_PA', 'max_V3_PA','min_Aperture_PA',\
'max_Aperture_PA', 'nom_Aperture_PA', 'Gregorian', 'MJD'))
return paMin, paMax, gd, fig, table