Exemple #1
0
    output_dir = os.path.abspath('/Users/bmmorris/data')
elif os.path.exists('/usr/lusers/bmmorris/data/hat11/'):
    # on Hyak
    light_curve_paths = glob('/usr/lusers/bmmorris/data/hat11/*slc.fits')
    output_dir = os.path.abspath('/gscratch/stf/bmmorris/friedrich/hat11_flip_lambda')
elif os.path.exists('/local/tmp/hat11'):
    # on mist
    light_curve_paths = glob('/local/tmp/hat11/*slc.fits')
    output_dir = os.path.abspath('./')
else:
    raise ValueError('No input files found.')

hat11_params = hat11_params_morris_flip_lambda()

# Construct light curve object from the raw data
whole_lc = LightCurve.from_raw_fits(light_curve_paths, name='HAT11')
transits = LightCurve(**whole_lc.mask_out_of_transit(hat11_params,
                                                     oot_duration_fraction=0.5)
                      ).get_transit_light_curves(hat11_params)

# Compute maxes for each quarter
available_quarters = whole_lc.get_available_quarters()
quarters = [whole_lc.get_quarter(q) for q in whole_lc.get_available_quarters()]

quarterly_maxes = {}
set_upper_limit = 4e10
for i, quarter_number, lc in zip(range(len(available_quarters)),
                                 available_quarters, quarters):
    fluxes = lc.fluxes[lc.fluxes < set_upper_limit]
    smoothed_fluxes = gaussian_filter(fluxes, sigma=20)
    quarterly_maxes[quarter_number] = np.max(smoothed_fluxes)
Exemple #2
0
from friedrich.lightcurve import (LightCurve, generate_lc_depth,
                                  kepler17_params_db)
from friedrich.fitting import peak_finder, summed_gaussians, gaussian

import matplotlib.pyplot as plt
import numpy as np
from astropy.utils.console import ProgressBar

# Settings:
plots = True
light_curve_paths = glob('/Users/bmmorris/data/kepler17/*slc.fits')
depth = 0.13031**2
kepler17_params = kepler17_params_db()

# Construct light curve object from the raw data
whole_lc = LightCurve.from_raw_fits(light_curve_paths, name='Kepler17')
transits = LightCurve(**whole_lc.mask_out_of_transit(kepler17_params)
                      ).get_transit_light_curves(kepler17_params)

delta_chi2 = {}

with ProgressBar(len(transits)) as bar:
    for i, lc in enumerate(transits):
        # Remove linear out-of-transit trend from transit
        lc.remove_linear_baseline(kepler17_params)

        # Subtract out a transit model
        transit_model = generate_lc_depth(lc.times_jd, depth, kepler17_params)
        residuals = lc.fluxes - transit_model

        # Find peaks in the light curve residuals