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refactor ddf_presched to make config easier. eliminate magic numbers
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@yoachim
yoachim committed Jan 23, 2025
1 parent abe820a commit 38d8da6
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Showing 2 changed files with 114 additions and 42 deletions.
8 changes: 4 additions & 4 deletions rubin_scheduler/scheduler/example/example_scheduler.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1209,7 +1209,7 @@ def generate_twi_blobs(

def ddf_surveys(
detailers=None,
season_unobs_frac=0.2,
offseason_length=73.05,
euclid_detailers=None,
nside=None,
expt=29.2,
Expand All @@ -1233,7 +1233,7 @@ def ddf_surveys(
nsnaps = [1, 2, 2, 2, 2, 2]
if nexp == 1:
nsnaps = [1, 1, 1, 1, 1, 1]
obs_array = generate_ddf_scheduled_obs(season_unobs_frac=season_unobs_frac, expt=expt, nsnaps=nsnaps)
obs_array = generate_ddf_scheduled_obs(offseason_length=offseason_length, expt=expt, nsnaps=nsnaps)
euclid_obs = np.where(
(obs_array["scheduler_note"] == "DD:EDFS_b") | (obs_array["scheduler_note"] == "DD:EDFS_a")
)[0]
Expand Down Expand Up @@ -1546,7 +1546,7 @@ def gen_scheduler(args):
# Parameters that were previously command-line
# arguments.
max_dither = 0.2 # Degrees. For DDFs
ddf_season_frac = 0.2 # Amount of season to use for DDFs
ddf_offseason_length = 365.25 * 0.2 # Amount of season to use for DDFs
illum_limit = 40.0 # Percent. Lunar illumination used for band loading
u_exptime = 38.0 # Deconds
nslice = 2 # N slices for rolling
Expand Down Expand Up @@ -1643,7 +1643,7 @@ def gen_scheduler(args):
]
ddfs = ddf_surveys(
detailers=details,
season_unobs_frac=ddf_season_frac,
offseason_length=ddf_offseason_length,
euclid_detailers=euclid_detailers,
nside=nside,
nexp=nexp,
Expand Down
148 changes: 110 additions & 38 deletions rubin_scheduler/scheduler/surveys/ddf_presched.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -11,7 +11,16 @@
from rubin_scheduler.utils import SURVEY_START_MJD, calc_season, ddf_locations


def ddf_slopes(ddf_name, raw_obs, night_season, season_seq=30, min_season_length=0 / 365.25):
def ddf_slopes(
ddf_name,
raw_obs,
night_season,
season_seq=30,
min_season_length=0,
boost_early_factor=None,
boost_factor_third=2.0,
boost_factor_fractional=0.0,
):
"""
Let's make custom slopes for each DDF
Expand All @@ -32,17 +41,20 @@ def ddf_slopes(ddf_name, raw_obs, night_season, season_seq=30, min_season_length
Number of sequences to try to place into each season.
Default of 30.
min_season_length : `float`, optional
The minimum season length to allow before discarding the
The minimum season length in days to allow before discarding the
season. Default of 0 currently doesn't discard any seasons,
on the basis that most of the short season concerns will be
early in the survey and we'd rather have some observations early
than wait.
boost_early_factor : `float`, optional
Number of early seasons to give a boost to
boost_factor_third : `float`
If boosting, the boot factor to use on the third season.
boost_factor_fractional : `float`
If there is an initial partial season, also boost that one by
the given factor.
"""

# OK, so 258 sequences is ~1% of the survey
# so a 25.8 sequences is a 0.1% season
# COSMOS is going to be 0.7% for 3 years, then 0.175 for the rest.

int_season = np.floor(night_season)

n_season = night_season[np.where(raw_obs)]
Expand All @@ -61,27 +73,19 @@ def ddf_slopes(ddf_name, raw_obs, night_season, season_seq=30, min_season_length
# Adjust other seasons, relative to the max season length.
season_vals = season_vals * season_length / np.max(season_length)
# EXCEPT - throw out seasons which are too short
too_short = np.where(season_length < min_season_length)
too_short = np.where(season_length < (min_season_length / 365.25))
season_vals[too_short] = 0

# Add extra adjustment for COSMOS to boost visits in seasons 0-3
# Also boost -1 season, if it's not too short
boost_early_years = 5
if ddf_name == "COSMOS":
# Add extra adjustment to boost visits in seasons 0, 1, and 2
# and maybe -1.
if boost_early_factor is not None:
early_season = np.where(season_list == -1)[0]
if len(early_season) > 0:
max_n_seq_early = (season_length[early_season][0] * 365.25) / 3
# Choose the minimum of - sequence every third night (?)
# or the standard season sequence * boost_early_years.
season_vals[early_season] = np.min([max_n_seq_early, season_seq * boost_early_years])
if (len(early_season) > 0) & (boost_factor_fractional > 0):
season_vals[early_season] = season_seq * boost_factor_fractional
first_full_two_seasons = np.where((season_list == 0) | (season_list == 1))
season_vals[first_full_two_seasons] *= boost_early_years
season_vals[first_full_two_seasons] *= boost_early_factor
third_season = np.where(season_list == 2)
season_vals[third_season] *= boost_early_years / 2.5

if ddf_name == "EDFS_b":
# EDFS_b ddf visits are allocated some other way
season_vals = season_vals * 0
season_vals[third_season] *= boost_factor_third

# Round the season_vals -- we're looking for integer numbers of sequences
season_vals = np.round(season_vals)
Expand All @@ -98,8 +102,6 @@ def ddf_slopes(ddf_name, raw_obs, night_season, season_seq=30, min_season_length
cumulative = cumulative / cumulative.max() * season_vals[i]
cumulative_desired[this_season] = cumulative + np.max(cumulative_desired)

# print(ddf_name, season_vals, cumulative_desired.max())

return cumulative_desired


Expand Down Expand Up @@ -169,10 +171,14 @@ def optimize_ddf_times(
airmass_limit=2.5,
sky_limit=None,
g_depth_limit=23.5,
season_unobs_frac=0.2,
offseason_length=73.05,
low_season_frac=0,
low_season_rate=0.3,
mjd_start=SURVEY_START_MJD,
season_seq=30,
boost_early_factor=None,
boost_factor_third=2,
boost_factor_fractional=0.0,
):
"""
Expand Down Expand Up @@ -206,12 +212,11 @@ def optimize_ddf_times(
a nominal FWHM_500 seeing at zenith of 0.7" (resulting in airmass
dependent seeing) and exposure time.
Default 23.5. Set to None for no limit.
season_unobs_frac : `float`, optional
Defines the end of the range of the prescheduled observing season.
season runs from 0 (sun's apparent position is at the RA of the DDF)
to 1 (sun returns to an apparent position in the RA of the DDF).
The scheduled season runs from:
season_unobs_frac < season < (1-season_unobs_fract)
offseason_length : `float`, optional
Number of days to have as the unobservable off-season. Observations
are observed when offseason_length < night < 365.25 - offseason_length
counting night=0 as when the sun is at the RA of the DDF. Default of
73.05 days results in observing seasons of 292.2 days.
low_season_frac : `float`, optional
Defines the end of the range of the "low cadence" prescheduled
observing season.
Expand All @@ -231,6 +236,9 @@ def optimize_ddf_times(
starting point when counting seasons.
Default SURVEY_START_MJD.
"""
# Convert to fraction for convienence
season_unobs_frac = offseason_length / 365.25

# Convert sun_limit and sequence_time to values expected internally.
sun_limit = np.radians(sun_limit)
sequence_time = sequence_time / 60.0 / 24.0 # to days
Expand Down Expand Up @@ -293,7 +301,15 @@ def optimize_ddf_times(
raw_obs[out_season] = 0
raw_obs[low_season] = low_season_rate

cumulative_desired = ddf_slopes(ddf_name, raw_obs, night_season)
cumulative_desired = ddf_slopes(
ddf_name,
raw_obs,
night_season,
season_seq=season_seq,
boost_early_factor=boost_early_factor,
boost_factor_third=boost_factor_third,
boost_factor_fractional=boost_factor_fractional,
)

# Identify which nights (only scheduling 1 sequence per night)
# would be usable, based on the masks above.
Expand Down Expand Up @@ -338,9 +354,10 @@ def generate_ddf_scheduled_obs(
mjd_start=SURVEY_START_MJD,
survey_length=10.0,
sequence_time=60.0,
season_unobs_frac=0.2,
offseason_length=36.525,
low_season_frac=0,
low_season_rate=0.3,
ddf_kwargs=None,
):
"""
Expand Down Expand Up @@ -401,6 +418,9 @@ def generate_ddf_scheduled_obs(
of the season. During the standard season, the 'rate' is 1.
This is used in `ddf_slopes` to define the desired number of
cumulative observations for each DDF over time.
ddf_kwargs : `dict`
Dictionary to hold custom kwargs for each DDF. Default of None
will use internal defaults and boost COSMOS early.
"""
if data_file is None:
data_file = os.path.join(get_data_dir(), "scheduler", "ddf_grid.npz")
Expand Down Expand Up @@ -428,18 +448,70 @@ def generate_ddf_scheduled_obs(
in_range = np.where((ddf_grid["mjd"] >= mjd_start) & (ddf_grid["mjd"] <= mjd_max))
ddf_grid = ddf_grid[in_range]

if ddf_kwargs is None:
ddf_kwargs = {}
ddf_kwargs["ELAISS1"] = {
"season_seq": 30,
"boost_early_factor": None,
"boost_factor_third": 0,
"offseason_length": offseason_length,
"sequence_time": sequence_time,
"low_season_frac": low_season_frac,
"low_season_rate": low_season_rate,
}

ddf_kwargs["XMM_LSS"] = {
"season_seq": 30,
"boost_early_factor": None,
"boost_factor_third": 0,
"offseason_length": offseason_length,
"sequence_time": sequence_time,
"low_season_frac": low_season_frac,
"low_season_rate": low_season_rate,
}

ddf_kwargs["ECDFS"] = {
"season_seq": 30,
"boost_early_factor": None,
"boost_factor_third": 0,
"offseason_length": offseason_length,
"sequence_time": sequence_time,
"low_season_frac": low_season_frac,
"low_season_rate": low_season_rate,
}

ddf_kwargs["COSMOS"] = {
"season_seq": 30,
"boost_early_factor": 5.0,
"boost_factor_third": 2,
# Strange looking number for
# mostly backwards compatibility
"boost_factor_fractional": 2.42,
"offseason_length": offseason_length,
"sequence_time": sequence_time,
"low_season_frac": low_season_frac,
"low_season_rate": low_season_rate,
}

ddf_kwargs["EDFS_a"] = {
"season_seq": 30,
"boost_early_factor": None,
"boost_factor_third": 0,
"offseason_length": offseason_length,
"sequence_time": sequence_time,
"low_season_frac": low_season_frac,
"low_season_rate": low_season_rate,
}

all_scheduled_obs = []
for ddf_name in ["ELAISS1", "XMM_LSS", "ECDFS", "COSMOS", "EDFS_a"]:
for ddf_name in ddf_kwargs:
print("Optimizing %s" % ddf_name)

mjds = optimize_ddf_times(
ddf_name,
ddfs[ddf_name][0],
ddf_grid,
season_unobs_frac=season_unobs_frac,
sequence_time=sequence_time,
low_season_frac=low_season_frac,
low_season_rate=low_season_rate,
**ddf_kwargs[ddf_name],
)[0]
for mjd in mjds:
for bandname, nvis, nexp in zip(bands, nvis_master, nsnaps):
Expand Down

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