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run_seeds.py
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import json
from pathlib import Path
import astropy.units as u
import numpy as np
from astroplan import AirmassConstraint, AtNightConstraint
from astropy.time import Time
from RVtoImaging.builder import BaseBuilder
# def run_scenario(seed, builder, rv_dataset_info):
# def run_scenario(args):
# seed, builder, run_sets = args
# builder = copy.deepcopy(builder)
# builder.seeds = [seed]
# for dataset_name, obs_runs in run_sets.items():
# print(f"Seed {seed} for {dataset_name} dataset")
# builder.rv_dataset_params = {
# "dataset_name": dataset_name,
# "rv_observing_runs": obs_runs,
# "available_targets_file": ".cache/NETS100.csv",
# "approx_systems_to_observe": approx_systems_to_observe,
# }
# builder.run_seeds()
# # builder.rv_dataset_params = {
# # "dataset_name": dataset_name,
# # "rv_observing_runs": obs_runs,
# # "available_targets_file": ".cache/NETS100.csv",
# # "approx_systems_to_observe": 85,
# # }
# # builder.run_seeds()
# def run_search(path):
# base_path = Path(".cache/universe_309864d7/HIP_101997/")
# rv_df = pd.read_csv(Path(base_path, path, "rv.csv"))
# print("test")
# searcher = search.Search(
# rv_df, workers=7, mcmc=True, verbose=True, max_planets=4, n_vary=np.inf
# )
# searcher.run_search()
if __name__ == "__main__":
# Load settings for this machine
settings_file = Path(".config.json")
with open(settings_file, "r") as f:
settings = json.load(f)
cache_dir = settings["cache_dir"]
workers = settings["workers"]
first_seed = settings["first_seed"]
last_seed = settings["last_seed"]
# Set up director and builder objects
# director = Director()
builder = BaseBuilder(cache_dir=cache_dir, workers=workers)
# director.builder = builder
######################################################################
# Set up universe generation
######################################################################
builder.universe_params = {
"universe_type": "exosims",
"script": "test.json",
}
# builder.universe_params = {
# "universe_type": "exovista",
# "data_path": ".cache/data/",
# "universe_number": 0,
# }
######################################################################
# Orbit fitting
######################################################################
builder.rv_fits_params = {
"fitting_method": "rvsearch",
"max_planets": 4,
"vary_planets": np.inf,
}
######################################################################
# Set up precursor observation information
######################################################################
# Create base instrument parameters
mission_start = Time(2043, format="decimalyear")
# This is the location of the APF
# APF = {
# "name": "APF",
# "location": "Lick Observatory",
# "precision": 1 * u.m / u.s,
# "start_time": mission_start - 15 * u.yr,
# # "end_time": mission_start * u.yr,
# "observation_scheme": "consistent",
# "observation_rate": 2 / u.week,
# }
# observations at 2 m/s by various instruments
simple_sigma_terms = {"rv": 2 * u.m / u.s}
simple_observation_scheme = {
"type": "random",
"observations_per_star_per_year": 10,
"bad_weather_prob": 0.0,
"exposure_time": 30 * u.min,
"astroplan_constraints": [
AtNightConstraint.twilight_astronomical(),
AirmassConstraint(min=1, max=1.5),
],
}
# Kinda simulating HIRES which at Keck
simple_run = {
"name": "2 m/s instruments",
"location": "W. M. Keck Observatory",
"timezone": "US/Hawaii",
"start_time": Time(2010, format="decimalyear"),
"end_time": Time(2035, format="decimalyear"),
"sigma_terms": simple_sigma_terms,
"observation_scheme": simple_observation_scheme,
}
# NEID Earth Twin Survey values
NETS_sigma_terms = {
"instrument": 0.27 * u.m / u.s,
"photon": 0.21213 * u.m / u.s,
"pmode_oscillation": 0.21213 * u.m / u.s,
"granulation": 1.0 * u.m / u.s,
"magnetic": 1.0 * u.m / u.s,
}
NETS_observation_scheme = {
"type": "constraint",
"bad_weather_prob": 0,
"obs_night_schedule": "random",
"n_obs_nights": 24,
"exposure_time": 20 * u.min,
"astroplan_constraints": [
AtNightConstraint.twilight_astronomical(),
AirmassConstraint(min=1, max=1.5),
],
}
NETS_run = {
"name": "NETS",
"location": "Kitt Peak",
"timezone": "US/Mountain",
"start_time": Time(2023, format="decimalyear"),
"end_time": Time(2028, format="decimalyear"),
"observation_scheme": NETS_observation_scheme,
"sigma_terms": NETS_sigma_terms,
}
# UPGRADE TO NEID
NEID_upgrade_run_1 = {
"name": "NEID 50cm/s",
"location": "Kitt Peak",
"timezone": "US/Mountain",
"start_time": Time(2030, format="decimalyear"),
"end_time": Time(2035, format="decimalyear"),
"observation_scheme": NETS_observation_scheme,
"sigma_terms": {"sigma_rv": 0.5 * u.m / u.s},
}
NEID_upgrade_run_2 = {
"name": "NEID 40cm/s",
"location": "Kitt Peak",
"timezone": "US/Mountain",
"start_time": Time(2038, format="decimalyear"),
"end_time": Time(2043, format="decimalyear"),
"observation_scheme": NETS_observation_scheme,
"sigma_terms": {"sigma_rv": 0.4 * u.m / u.s},
}
# EPRV observation run
EPRV_observation_scheme = {
"type": "constraint",
"bad_weather_prob": 0,
"obs_night_schedule": "random",
"n_obs_nights": 24,
"exposure_time": 20 * u.min,
"astroplan_constraints": [
AtNightConstraint.twilight_astronomical(),
AirmassConstraint(min=1, max=1.5),
],
}
EPRV_run = {
"name": "EPRV",
"location": "W. M. Keck Observatory",
"timezone": "US/Hawaii",
"start_time": Time(2038, format="decimalyear"),
"end_time": Time(2043, format="decimalyear"),
"observation_scheme": EPRV_observation_scheme,
"sigma_terms": {"sigma_rv": 0.1 * u.m / u.s},
}
observing_runs = [simple_run]
# observing_runs = [simple_run, NETS_run]
approx_systems_to_observe = 84
target_list_constraints = {"": ""}
# builder.rv_dataset_params = {
# "dataset_name": "simple",
# "rv_observing_runs": [simple_run],
# "available_targets_file": ".cache/NETS100.csv",
# "approx_systems_to_observe": approx_systems_to_observe,
# }
baseline_sigma_terms = {"rv": 1 * u.m / u.s}
baseline_observation_scheme = {
"type": "random",
"observations_per_star_per_year": 10,
"bad_weather_prob": 0.0,
"exposure_time": 30 * u.min,
"astroplan_constraints": [
AtNightConstraint.twilight_astronomical(),
AirmassConstraint(min=1, max=1.5),
],
}
# Kinda simulating HIRES which at Keck
baseline_run = {
"name": "1 m/s instruments",
"location": "W. M. Keck Observatory",
"timezone": "US/Hawaii",
"start_time": Time(2010, format="decimalyear"),
"end_time": Time(2043, format="decimalyear"),
"sigma_terms": baseline_sigma_terms,
"observation_scheme": baseline_observation_scheme,
}
baseline = [baseline_run]
conservative = [simple_run, NETS_run, NEID_upgrade_run_1, NEID_upgrade_run_2]
optimistic = [simple_run, NETS_run, NEID_upgrade_run_1, EPRV_run]
run_sets = {
"conservative": conservative,
"baseline": baseline,
"optimistic": optimistic,
}
seeds = [int(seed) for seed in np.arange(first_seed, last_seed + 1, 1)]
builder.rv_dataset_params = {
"dataset_name": "conservative",
"rv_observing_runs": conservative,
"available_targets_file": f"{cache_dir}/NETS100.csv",
"approx_systems_to_observe": approx_systems_to_observe,
}
# for seed in seeds:
# builder.seeds = [seed]
# for dataset_name, obs_runs in run_sets.items():
# builder.rv_dataset_params = {
# "dataset_name": dataset_name,
# "rv_observing_runs": obs_runs,
# "available_targets_file": f"{cache_dir}/NETS100.csv",
# "approx_systems_to_observe": approx_systems_to_observe,
# }
# builder.run_seeds()
# args = []
# for seed in seeds:
# args.append((seed, builder, run_sets))
######################################################################
# Probability of detection
######################################################################
builder.pdet_params = {
"script": "scripts/caseA.json",
"construction_method": {"name": "multivariate gaussian", "cov_samples": 1000},
"number_of_orbits": 10000,
"start_time": mission_start,
"end_time": mission_start + 2 * u.yr,
"min_int_time": 1 * u.hr,
"max_int_time": 10 * u.day,
}
builder.img_schedule_params = {
"coeff_multiple": 10,
"sim_length": 1 * u.yr,
"window_length": 2 * u.hr,
"block_multiples": [1, 6, 36],
"max_observations_per_star": 10,
"planet_threshold": 0.9,
"requested_planet_observations": 3,
"min_required_wait_time": 10 * u.d,
"max_required_wait_time": 0.25 * u.yr,
"max_time_in_seconds": 60 * 60,
"log_search_progress": True,
}
builder.seeds = seeds
builder.run_seeds()
# builder.precursor_data.list_parts()
# print("\n")
# print("Standard full featured precursor_data: ")
# director.build_full_info()
# builder.precursor_data.list_parts()
# print("\n")
# # Remember, the Builder pattern can be used without a Director class.
# print("Custom precursor_data: ")
# builder.create_universe()
# builder.simulate_observations()
# builder.precursor_data.list_parts()