""" 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
