def _in_region(pos):
"""Returns a list of booleans."""
positions = _parse_pos(pos)
return [
c9.inMicrolensRegion(poscrd.ra.deg, poscrd.dec.deg)
for poscrd in positions
]
def check_in_superstamp( target ):
(ra, dec) = target.get_location()
if ra == None or dec == None:
print target.summary([])
exit()
result = c9.inMicrolensRegion(ra, dec)
return result
def checkMicrolensRegion(RA_string, Dec_string):
"""Check if strings RA and Dec coordinates are within K2 Campaign 9 microlensing region (units: degrees)."""
# Convert strings to floats and output to logger
RA = float(RA_string)
Dec = float(Dec_string)
logger.info("RA: " + str(RA) + " Dec: " + str(Dec) + " (Units: Degrees)")
# pass to K2fov.c9 module method (from the K2 tools) to get whether coordinates are in the region
return inMicrolensRegion(RA, Dec)
'dc_col'),
comment='#')
targetlist_doug.to_csv('input/late_targets_K2C9b_v2_morc.dat.csv')
targetlist = targetlist_radek.join(targetlist_doug)
targetlist.to_csv('input/c9b-targetlist.csv')
################
# SANITY CHECKS
################
# Ensure both targetlists had the same target on each row
assert (np.all((targetlist.ra - targetlist.dc_ra) == 0.0))
assert (np.all((targetlist.dec - targetlist.dc_dec) == 0.0))
# Ensure both targetlists agree on the CCD channel
assert (np.all((targetlist.k2fov_channel - targetlist.dc_channel) == 0))
# K2fov is expected to be accurate to within 10px
delta = np.hypot(targetlist.k2fov_col - targetlist.dc_col,
targetlist.k2fov_row - targetlist.dc_row)
assert (np.all(delta < 10))
print("Pixel conversion offset: "
"median {:.2f}, min {:.2f}, max {:.2f}".format(delta.median(),
delta.min(), delta.max()))
# Are targets already in the microlensing region?
from K2fov import c9
for target in targetlist.itertuples():
if c9.inMicrolensRegion(target.ra, target.dec, padding=5):
print("Warning: {} already in superstamp".format(target.name))
def _in_region(pos):
"""Returns a list of booleans."""
positions = _parse_pos(pos)
return [c9.inMicrolensRegion(poscrd.ra.deg, poscrd.dec.deg)
for poscrd in positions]
names=('dc_ra', 'dc_dec', 'dc_module', 'dc_output',
'dc_channel', 'dc_row', 'dc_col'),
comment='#')
targetlist_doug.to_csv('input/late_targets_K2C9b_v2_morc.dat.csv')
targetlist = targetlist_radek.join(targetlist_doug)
targetlist.to_csv('input/c9b-targetlist.csv')
################
# SANITY CHECKS
################
# Ensure both targetlists had the same target on each row
assert(np.all((targetlist.ra - targetlist.dc_ra) == 0.0))
assert(np.all((targetlist.dec - targetlist.dc_dec) == 0.0))
# Ensure both targetlists agree on the CCD channel
assert(np.all((targetlist.k2fov_channel - targetlist.dc_channel) == 0))
# K2fov is expected to be accurate to within 10px
delta = np.hypot(targetlist.k2fov_col - targetlist.dc_col,
targetlist.k2fov_row - targetlist.dc_row)
assert(np.all(delta < 10))
print("Pixel conversion offset: "
"median {:.2f}, min {:.2f}, max {:.2f}".format(delta.median(), delta.min(), delta.max()))
# Are targets already in the microlensing region?
from K2fov import c9
for target in targetlist.itertuples():
if c9.inMicrolensRegion(target.ra, target.dec, padding=5):
print("Warning: {} already in superstamp".format(target.name))
"""
Removes points which are not on the K2C9 superstamp.
"""
import sys
from K2fov.c9 import inMicrolensRegion
with open(sys.argv[1]) as data:
lines = data.readlines()
for line in lines:
ra = float(line.split()[1])
dec = float(line.split()[2])
if inMicrolensRegion(ra, dec):
print(line[:-1])
