Skip to content

Add set_proxy_parameters() for time period based setting of proxy_cal_factor and proxy_ratio_adinos. #27

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
MBARIMike merged 1 commit into from
Jun 2, 2025
Merged

Add set_proxy_parameters() for time period based setting of proxy_cal_factor and proxy_ratio_adinos. #27

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion .vscode/launch.json
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -140,7 +140,7 @@
//"args": ["--auv_name", "dorado", "--mission", "2024.317.01", "-v", "1"],
//"args": ["--auv_name", "dorado", "--mission", "2010.341.00", "-v", "1", "--plot", "--plot_seconds", "82000"],
//"args": ["--auv_name", "dorado", "--mission", "2020.337.00", "-v", "1"],
"args": ["--auv_name", "dorado", "--mission", "2023.123.00",],
"args": ["--auv_name", "dorado", "--mission", "2023.123.00", "-v", "1"],
},
{
"name": "5.0 - archive.py",
Expand Down
77 changes: 74 additions & 3 deletions src/data/resample.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -409,7 +409,14 @@ def select_nighttime_bl_raw(
.to_pandas()
.dropna()
)
nighttime_bl_raw = pd.concat([nighttime_bl_raw, nighttime_data])
# This complication is needed because concat will not like an empty DataFrame
nighttime_bl_raw = (
nighttime_bl_raw.copy()
if nighttime_data.empty
else nighttime_data.copy()
if nighttime_bl_raw.empty
else pd.concat([nighttime_bl_raw, nighttime_data]) # if both DataFrames non empty
)

if not sunsets or not sunrises:
self.logger.info("No sunset or sunrise found during this mission.")
Expand Down Expand Up @@ -453,14 +460,75 @@ def add_profile(self, depth_threshold: float = 15) -> None:
"long_name": "Profile number",
}

def set_proxy_parameters(self, mission_start: datetime) -> tuple[float, float]:
# The parameters used to calculate bioluminescence proxies should be changed depending
# on the time period considered, as described below.

# Changes in HS2/biolum configurations:

# beginning of UBAT surveys
# [period1]
# 2007.344.00 first survey with bathyphotometer mounted in the nose instead of side-mounted
# [period2]
# Jan 1st 2009 changing HS2 sensor (new bbp channels), first mission is 2009.055.05 I believe # noqa: E501
# [period3]
# new UBAT installed in 2010 (first mission 2010.277.01)
# [period4]
# UBAT serviced early 2025, may require a new parameterization in the future but we can keep
# period4 for now until present.

# Parameters should be:

# period1: calibration=0.0016691, ratioAdinos=5.0119E13
# period2: calibration=0.0016691, ratioAdinos=2.5119E13
# period3: calibration=0.0047101, ratioAdinos=1.0000E14
# period4: calibration=0.0049859, ratioAdinos=3.8019E13 to test (previously based on
# 2010-2020: calibration=0.0047118, ratioAdinos=3.9811E13)

# Set start datetime from year and year-day
period1_start = datetime(2003, 1, 1) + timedelta(days=225) # noqa: DTZ001
period2_start = datetime(2007, 1, 1) + timedelta(days=343) # noqa: DTZ001
period3_start = datetime(2009, 1, 1) + timedelta(days=54) # noqa: DTZ001
period4_start = datetime(2010, 1, 1) + timedelta(days=276) # noqa: DTZ001
if mission_start >= period1_start and mission_start < period2_start:
# period1: 2003.225 to 2007.343
self.logger.info("Setting biolume proxy parameters for period1")
proxy_cal_factor = 0.0016691
proxy_ratio_adinos = 5.0119e13
elif mission_start >= period2_start and mission_start < period3_start:
# period2: 2007.343 to 2009.054
self.logger.info("Setting biolume proxy parameters for period2")
proxy_cal_factor = 0.0016691
proxy_ratio_adinos = 2.5119e13
elif mission_start >= period3_start and mission_start < period4_start:
# period3: 2009.054 to 2010.275
self.logger.info("Setting biolume proxy parameters for period3")
proxy_cal_factor = 0.0047101
proxy_ratio_adinos = 1.0000e14
elif mission_start >= period4_start:
# period4: 2010.275 to present
self.logger.info("Setting biolume proxy parameters for period4")
proxy_cal_factor = 0.0049859
proxy_ratio_adinos = 3.8019e13
else:
# Should not happen, but if it does, use the values used in Notebook 5.2
self.logger.warning(
"Mission start %s is before period1_start %s - Setting original parameters",
mission_start,
period1_start,
)
proxy_cal_factor = 0.0047118
proxy_ratio_adinos = 3.9811e13
return proxy_cal_factor, proxy_ratio_adinos

def add_biolume_proxies( # noqa: PLR0913, PLR0915
self,
freq,
window_size_secs: int = 5,
envelope_mini: float = 1.5e10,
flash_threshold: float = FLASH_THRESHOLD,
proxy_ratio_adinos: float = 3.9811e13, # 4-Oct-2010 to 2-Dec-2020 value
proxy_cal_factor=0.00470, # Same as used in 5.2-mpm-bg_biolume-PiO-paper.ipynb
proxy_cal_factor: float = 0.00470, # Same as used in 5.2-mpm-bg_biolume-PiO-paper.ipynb
) -> tuple[pd.Series, list[datetime], list[datetime]]:
# Add variables via the calculations according to Appendix B in
# "Using fluorescence and bioluminescence sensors to characterize
Expand Down Expand Up @@ -905,7 +973,10 @@ def resample_variable( # noqa: PLR0913
if instr == "biolume" and variable == "biolume_raw":
# Only biolume_avg_biolume and biolume_flow treated like other data
# All other biolume variables in self.df_r[] are computed from biolume_raw
biolume_fluo, biolume_sunsets, biolume_sunrises = self.add_biolume_proxies(freq)
proxy_cal_factor, proxy_ratio_adinos = self.set_proxy_parameters(mission_start)
biolume_fluo, biolume_sunsets, biolume_sunrises = self.add_biolume_proxies(
freq=freq, proxy_cal_factor=proxy_cal_factor, proxy_ratio_adinos=proxy_ratio_adinos
)
self.correct_biolume_proxies(biolume_fluo, biolume_sunsets, biolume_sunrises)
else:
self.df_o[variable] = self.ds[variable].to_pandas()
Expand Down