""" TODO: docstring """ __author__ = "adrn <*****@*****.**>" # Standard library import os import sys # Third-party import numpy as np # Project import ptf.globals as pg import ptf.util as pu logger = pu.get_logger("num_simulations.py") import ptf.db.photometric_database as pdb import ptf.variability_indices as vi from ptf.simulation import simulate_light_curves_compute_indices def read_light_curves_from_field(field, ccd=None, N_per_ccd=0, clean=True, randomize=False): """ Read some number of light curves from a given PTF field Parameters ---------- field : int, pdb.Field The PTF field ccd : int, pdb.CCD (optional) The PTF CCD to grab light curves from. If None, uses all CCDs N_per_ccd : int The number of light curves to grab PER CCD. 0 means all.
import numpy as np import matplotlib matplotlib.use("Agg") import matplotlib.cm as cm import matplotlib.colors as mc import matplotlib.pyplot as plt from matplotlib.patches import Rectangle import tables import apwlib.geometry as g # Project import ptf.db.photometric_database as pdb from ptf.globals import camera_size_degrees, all_fields import ptf.globals as pg import ptf.util as pu logger = pu.get_logger("survey_coverage") class SurveyInfo(object): """ Some example use cases for this object: TODO: Fill this in! """ def __init__(self, filter, overwrite=False): """ Convenience class for getting information about the PTF survey Parameters ---------- filter : int, str, ptf.photometricdatabase.Filter Any parseable, unambiguous filter representation. overwrite : bool (optional)
import warnings warnings.simplefilter("ignore") # Third-party import numpy as np import matplotlib.pyplot as plt from apwlib.globals import greenText # Project import ptf.db.photometric_database as pdb import ptf.db.mongodb as mongo import ptf.analyze as pa import ptf.variability_indices as vi from ptf.globals import min_number_of_good_observations from ptf.util import get_logger, source_index_name_to_pdb_index, richards_qso logger = get_logger(__name__) def plot_lc(lc): plt.clf() ax = lc.plot() try: x = np.linspace(lc.mjd.min(),lc.mjd.max(),1000) mag = pa.microlensing_model(lc.features, x) ax.plot(x, mag, 'r-') except KeyError: logger.debug("Not plotting microlensing fit.") pass plt.savefig("plots/tests/{0}_{1}_{2}.png".format(lc.field_id,lc.ccd_id, lc.source_id))
from __future__ import division, print_function """ TODO: docstring """ __author__ = "adrn <*****@*****.**>" # Standard library import os import sys # Third-party import numpy as np # Project import ptf.globals as pg import ptf.util as pu logger = pu.get_logger("num_simulations.py") import ptf.db.photometric_database as pdb import ptf.variability_indices as vi from ptf.simulation import simulate_light_curves_compute_indices def read_light_curves_from_field(field, ccd=None, N_per_ccd=0, clean=True, randomize=False): """ Read some number of light curves from a given PTF field Parameters ---------- field : int, pdb.Field