def test_sc_pipeline(): """ """ sc = ShortCadence(ticid=TICID, sap_mask="pipeline", quality_bitmask=QUALITY_BITMASK) _ = sc.get_lc() assert isinstance(sc.lc_pdcsap, lk.LightCurve) assert isinstance(sc.lc_sap, lk.LightCurve)
def test_sc_percentile(): """ """ sc = ShortCadence( ticid=TICID, sap_mask="percentile", percentile=90, quality_bitmask=QUALITY_BITMASK, ) _ = sc.make_custom_lc() assert isinstance(sc.lc_custom, lk.LightCurve)
def test_sc_threshold(): """ """ sc = ShortCadence( ticid=TICID, sap_mask="threshold", threshold_sigma=5, quality_bitmask=QUALITY_BITMASK, ) _ = sc.make_custom_lc() assert isinstance(sc.lc_custom, lk.LightCurve)
def test_sc_round(): """ """ sc = ShortCadence( ticid=TICID, sap_mask="round", aper_radius=1, quality_bitmask=QUALITY_BITMASK, ) _ = sc.make_custom_lc() assert isinstance(sc.lc_custom, lk.LightCurve)
def test_sc_square(): """ """ sc = ShortCadence( ticid=TICID, sap_mask="square", aper_radius=1, threshold_sigma=5, percentile=95, quality_bitmask=QUALITY_BITMASK, ) _ = sc.make_custom_lc() assert isinstance(sc.lc_custom, lk.LightCurve)
def test_sc_triceratops(): """ """ sc = ShortCadence(ticid=TICID, calc_fpp=True) # df = sc.get_NEB_depths() # df = sc.get_fpp(flat=flat, plot=False) assert sc.triceratops is not None
from matplotlib.axes import Axes from matplotlib.figure import Figure import lightkurve as lk from chronos import ShortCadence from chronos.plot import ( plot_archival_images, get_dss_data, plot_dss_image, plot_possible_NEBs, ) # TICID = 460205581 TOIID = 837 s = ShortCadence( # ticid=TICID, toiid=TOIID) lc = s.lc_pdcsap gaia_sources = s.query_gaia_dr2_catalog(radius=60) def test_archival(): fig = plot_archival_images( ra=s.target_coord.ra.deg, dec=s.target_coord.dec.deg, survey1="dss1", survey2="poss2ukstu_red", # or ps1 which requires panstarrs3 library return_baseline=False, ) assert isinstance(fig, Figure)