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Adding adler-day draft script #180

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Nov 5, 2024
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Binary file added adler-day-testing.db
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114 changes: 114 additions & 0 deletions src/adler/adler_day.py
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from adler.objectdata.AdlerPlanetoid import AdlerPlanetoid
from adler.science.PhaseCurve import PhaseCurve
import pandas as pd
import astropy.units as u
import numpy as np


def run_adler_day(ssobject_list):
"""Runs the Adler day process for a list of SSObjectIds.

Parameters
-----------
ssobject_list : list of str
List of strings of the SSObjectIDs we want to investigate.

"""

phase_model = "HG12_Pen16"

for ssoid in ssobject_list:

# date range is start of survey to "today's" date, these are dummy dates
# this should also pull in the most recent alert packet, which should be in Cassandra by now?
planetoid = AdlerPlanetoid.construct_from_cassandra(ssoid, date_range=[60290.0, 61902])

try:
planetoid.attach_previous_adler_data("adler-day-testing.db")
previousAdlerData = True # this could be a flag on the AdlerPlanetoid object
except ValueError:
# no AdlerData for this object ID as yet
previousAdlerData = False

for filt in planetoid.filter_list:
obs = planetoid.observations_in_filter(filt)
df_obs = pd.DataFrame(obs.__dict__)

######## DO WE FIT? ########

# here we assume that there have been enough new points to justify refitting the phase curve
# ie: that triage has already been done in adler-night
# whether we refit depends on some complex considerations (n_obs, phase angle range, minimum phase angle)
# however: could do a basic check: five new data points?

######## FIT NEW PHASE CURVE ########

if previousAdlerData:
params = planetoid.PreviousAdlerData.get_phase_parameters_in_filter(filt, phase_model)
H = params.H
G = params.phase_parameter_1
else:
sso = planetoid.SSObject_in_filter(filt)
H = sso.H
G = sso.G12

if np.isnan(H) or np.isnan(G):
print(
"No H and/or phase parameter value found for this object and filter in SSObject or Adler databases."
)
print("Using guess values. Fit may take longer.")
H = 15.0
G = 0.5

pc = PhaseCurve(
H=H * u.mag,
phase_parameter_1=G,
model_name=phase_model,
)

pc_fit = pc.FitModel(
np.array(df_obs["phaseAngle"]) * u.deg,
np.array(df_obs["reduced_mag"]) * u.mag,
np.array(df_obs["magErr"]) * u.mag,
)

pc_fit = pc.InitModelSbpy(pc_fit)
pc_fit.__dict__["H"] = pc_fit.__dict__["H"].value

planetoid.AdlerData.populate_phase_parameters(filt, **pc_fit.__dict__)

######## OUTLIER DETECTION: ONE METHOD ########

# can do phase curve fit including all but last point for outlier detection
# use H and G from alert if first time, otherwise pull from AdlerData

# check for that phase curve model what the predicted values are, check alert point against those within threshold
# can later compare to LSST-predicted mag

# of course this only checks the most recent point - what if the outlier was ten alerts ago but we didn't know?
# what if it was an alert we triaged out?

# write new row to Adler database
# planetoid.AdlerData.write_row_to_database("adler-day-testing.db")


if __name__ == "__main__":

# an assumption that these are the ssObjectIds of interest
# in the future, there will be a function which reads from the Kafka topic of triaged alerts from adler-night
# and returns this list.
# why are some of them negative? Ken doesn't know
ssobject_list = [
"685835657114313227",
"-6411717652251119994",
"3881603647193383121",
"6711448832195578320",
"2959207197656523004",
"-8724852777827460529",
"-7394109909111663666",
"2154070653759973672",
"-7805034407650925178",
"-4490542680786866656",
]

run_adler_day(ssobject_list)
File renamed without changes.
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