def __init__(self, passbands=('g', 'r'), contextual_info=('redshift',), nobs=50, mintime=-70, maxtime=80,
timestep=3.0, reread_data=False, bcut=True, zcut=None, ignore_classes=(), class_name_map=None,
nchunks=10000, training_set_dir='data/training_set_files', data_dir='data/ZTF_20190512/',
save_dir='data/saved_light_curves/', get_data_func=None, augment_data=False, redo_processing=False):
PrepareArrays.__init__(self, passbands, contextual_info, nobs, mintime, maxtime, timestep)
self.reread_data = reread_data
self.redo_processing = redo_processing
self.bcut = bcut
self.zcut = zcut
self.ignore_classes = ignore_classes
self.nchunks = nchunks
self.training_set_dir = training_set_dir
self.data_dir = data_dir
self.save_dir = save_dir
self.light_curves = {}
self.get_data_func = get_data_func
self.augment_data = augment_data
if 'redshift' in contextual_info:
self.known_redshift = True
else:
self.known_redshift = False
if class_name_map is None:
self.class_name_map = helpers.get_sntypes()
else:
self.class_name_map = class_name_map
if not os.path.exists(self.training_set_dir):
os.makedirs(self.training_set_dir)
def __init__(self,
passbands=('g', 'r'),
contextual_info=('redshift', ),
bcut=True,
zcut=None,
nobs=50,
mintime=-70,
maxtime=80,
timestep=3.0):
PrepareArrays.__init__(self, passbands, contextual_info, nobs, mintime,
maxtime, timestep)
self.bcut = bcut
self.zcut = zcut
def __init__(self,
passbands=('g', 'r'),
contextual_info=('redshift', ),
nobs=50,
mintime=-70,
maxtime=80,
timestep=3.0,
reread_data=False,
bcut=True,
zcut=None,
ignore_classes=(),
class_name_map=None,
nchunks=10000,
training_set_dir='data/training_set_files',
data_dir='data/ZTF_20190512/',
save_dir='data/saved_light_curves/',
get_data_func=None,
augment_data=False,
redo_processing=False,
spline_interp=True,
**kwargs):
self.spline_interp = spline_interp
PrepareArrays.__init__(self,
passbands,
contextual_info,
nobs,
mintime,
maxtime,
timestep,
spline_interp=self.spline_interp)
self.reread_data = reread_data
self.redo_processing = redo_processing
self.bcut = bcut
self.zcut = zcut
self.ignore_classes = ignore_classes
self.nchunks = nchunks
self.training_set_dir = training_set_dir
self.data_dir = data_dir
self.save_dir = save_dir
self.light_curves = {}
self.get_data_func = get_data_func
self.augment_data = augment_data
self.calculate_t0 = True
if 'redshift' in contextual_info:
self.known_redshift = True
else:
self.known_redshift = False
if kwargs['PLAsTiCC'] and class_name_map is None:
self.class_name_map = helpers.get_sntypes_PLAsTiCC()
elif class_name_map is None:
self.class_name_map = helpers.get_sntypes()
else:
self.class_name_map = class_name_map
if not os.path.exists(self.training_set_dir):
os.makedirs(self.training_set_dir)
if 'calculate_t0' in kwargs.keys():
self.calculate_t0 = kwargs['calculate_t0']
if 'single_class' in kwargs.keys():
self.single_class = kwargs['single_class']
else:
self.single_class = False