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Ensure env_params intake for calibration (#985)
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* add get_env_params_EK60 to CalibrateEK60.__init__, make sure CalibrateEK80.__init__ env param intake uses self.echodata and self.env_params

* add a narrow integration test to ensure env_params intake for CalibrateEK60

* add a narrow integration test to ensure env_params intake for CalibrateAZFP

* add sanitize_user_env_dict, revise get_env_params_AZFP to use new func

* revise get_env_params_EK60, add sound speed and absorption formula sources as env params, fix tests

* fix EK60 env params intake and tests

* use get_env_params_EK for EK60 intake, add EK60 integration test without input

* use get_env_params_EK in CalibrateEK80, add test_env_params_intake_EK80_no_input

* add test_env_params_intake_EK80_with_input, fix condition to use values from EK80 data

* add sound speed to FG absorption input in get_env_params_EK, shorten formula name

* fix pre-commit errors

* change to include pH in terms of whether to recompute sound speed/absorption, add input data array test case

* remove get_env_params_EK80 completely from codebase

* add test_sanitize_user_env_dict, fix typing for sanitize_user_*_dict

* add test_get_env_params_AZFP

* add test_get_env_params_EK60_calculate/from_data

* add partial test_get_env_params_EK80_from_data

* fix test_get_env_params_EK80_from_data, revise get_env_params_EK comments

* change ed_group to ed_beam_group

* fix azfp tests involving mean temperature

* remove redundancy in passing in extra ed_beam_group in _cal_power_samples and _cal_complex_samples

* add missed test cases in test_sanitize_user_env_dict

* change list to List in typing

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Emilio Mayorga <[email protected]>
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@leewujung @pre-commit-ci @emiliom
3 people authored Mar 18, 2023
1 parent da0a9e9 commit edc1d15
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Showing 13 changed files with 846 additions and 217 deletions.
8 changes: 2 additions & 6 deletions echopype/calibrate/cal_params.py
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Original file line number Diff line number Diff line change
Expand Up @@ -49,10 +49,6 @@
}


# TODO: need a function (something like "_check_param_freq_dep")
# to check user input cal_params and env_params


def param2da(p_val: Union[int, float, list], channel: Union[list, xr.DataArray]) -> xr.DataArray:
"""
Organize individual parameter in scalar or list to xr.DataArray with channel coordinate.
Expand Down Expand Up @@ -88,7 +84,7 @@ def param2da(p_val: Union[int, float, list], channel: Union[list, xr.DataArray])

def sanitize_user_cal_dict(
sonar_type: Literal["EK60", "EK80", "AZFP"],
user_dict: Dict[str, Union[int, float, xr.DataArray]],
user_dict: Dict[str, Union[int, float, list, xr.DataArray]],
channel: Union[List, xr.DataArray],
) -> Dict[str, Union[int, float, xr.DataArray]]:
"""
Expand Down Expand Up @@ -126,7 +122,7 @@ def sanitize_user_cal_dict(

# Screen parameters: only retain those defined in CAL_PARAMS
# -- transform params in scalar or list to xr.DataArray
# -- directly pass through those that are xr.DataArray
# -- directly pass through those that are xr.DataArray and pass the check for coordinates
out_dict = dict.fromkeys(CAL_PARAMS[sonar_type])
for p_name, p_val in user_dict.items():
if p_name in out_dict:
Expand Down
2 changes: 1 addition & 1 deletion echopype/calibrate/calibrate_azfp.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,7 @@ def __init__(self, echodata: EchoData, env_params=None, cal_params=None, **kwarg
self.sonar_type = "AZFP"

# load env and cal parameters
self.env_params = get_env_params_AZFP(echodata=self.echodata, user_env_dict=self.env_params)
self.env_params = get_env_params_AZFP(echodata=self.echodata, user_dict=self.env_params)
self.cal_params = get_cal_params_AZFP(
beam=self.echodata["Sonar/Beam_group1"],
vend=self.echodata["Vendor_specific"],
Expand Down
76 changes: 41 additions & 35 deletions echopype/calibrate/calibrate_ek.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,7 +9,7 @@
from .cal_params import get_cal_params_EK
from .calibrate_base import CalibrateBase
from .ek80_complex import compress_pulse, get_filter_coeff, get_tau_effective, get_transmit_signal
from .env_params import get_env_params_EK60, get_env_params_EK80
from .env_params import get_env_params_EK
from .range import compute_range_EK, range_mod_TVG_EK

logger = _init_logger(__name__)
Expand All @@ -19,6 +19,8 @@ class CalibrateEK(CalibrateBase):
def __init__(self, echodata: EchoData, env_params, cal_params):
super().__init__(echodata, env_params, cal_params)

self.ed_beam_group = None # will be assigned in child class

def compute_echo_range(self, chan_sel: xr.DataArray = None):
"""
Compute echo range for EK echosounders.
Expand All @@ -36,24 +38,22 @@ def compute_echo_range(self, chan_sel: xr.DataArray = None):
chan_sel=chan_sel,
)

def _cal_power_samples(self, cal_type: str, power_ed_group: str = None) -> xr.Dataset:
def _cal_power_samples(self, cal_type: str) -> xr.Dataset:
"""Calibrate power data from EK60 and EK80.
Parameters
----------
cal_type: str
'Sv' for calculating volume backscattering strength, or
'TS' for calculating target strength
power_ed_group:
The ``EchoData`` beam group path containing the power data
Returns
-------
xr.Dataset
The calibrated dataset containing Sv or TS
"""
# Select source of backscatter data
beam = self.echodata[power_ed_group]
beam = self.echodata[self.ed_beam_group]

# Derived params
wavelength = self.env_params["sound_speed"] / beam["frequency_nominal"] # wavelength
Expand All @@ -63,7 +63,7 @@ def _cal_power_samples(self, cal_type: str, power_ed_group: str = None) -> xr.Da
sound_speed = self.env_params["sound_speed"]
absorption = self.env_params["sound_absorption"]
tvg_mod_range = range_mod_TVG_EK(
self.echodata, self.ed_group, self.range_meter, sound_speed
self.echodata, self.ed_beam_group, self.range_meter, sound_speed
)
tvg_mod_range = tvg_mod_range.where(tvg_mod_range > 0, np.nan)

Expand Down Expand Up @@ -130,26 +130,31 @@ class CalibrateEK60(CalibrateEK):
def __init__(self, echodata, env_params, cal_params, **kwargs):
super().__init__(echodata, env_params, cal_params)

# Set sonar_type
# Set sonar_type and waveform/encode mode
self.sonar_type = "EK60"

# Get env_params
self.env_params = get_env_params_EK60(echodata=echodata, user_env_dict=self.env_params)
self.waveform_mode = "CW"
self.encode_mode = "power"

# Compute range
self.compute_echo_range()

# Get the right ed_group for CW power samples
self.ed_group = retrieve_correct_beam_group(
# Get the right ed_beam_group for CW power samples
self.ed_beam_group = retrieve_correct_beam_group(
echodata=self.echodata, waveform_mode=self.waveform_mode, encode_mode=self.encode_mode
)

# Get env_params
self.env_params = get_env_params_EK(
sonar_type=self.sonar_type,
beam=self.echodata[self.ed_beam_group],
env=self.echodata["Environment"],
user_dict=self.env_params,
)

# Compute range
self.compute_echo_range()

# Set the channels to calibrate
# For EK60 this is all channels
self.chan_sel = self.echodata[self.ed_group]["channel"]
beam = self.echodata[self.ed_group]
self.chan_sel = self.echodata[self.ed_beam_group]["channel"]
beam = self.echodata[self.ed_beam_group]

# Get cal_params
self.cal_params = get_cal_params_EK(
Expand All @@ -162,10 +167,10 @@ def __init__(self, echodata, env_params, cal_params, **kwargs):
)

def compute_Sv(self, **kwargs):
return self._cal_power_samples(cal_type="Sv", power_ed_group=self.ed_group)
return self._cal_power_samples(cal_type="Sv")

def compute_TS(self, **kwargs):
return self._cal_power_samples(cal_type="TS", power_ed_group=self.ed_group)
return self._cal_power_samples(cal_type="TS")


class CalibrateEK80(CalibrateEK):
Expand Down Expand Up @@ -197,23 +202,23 @@ def __init__(self, echodata, env_params, cal_params, waveform_mode, encode_mode)
self.encode_mode = encode_mode
self.echodata = echodata

# Get the right ed_group given waveform and encode mode
self.ed_group = retrieve_correct_beam_group(
# Get the right ed_beam_group given waveform and encode mode
self.ed_beam_group = retrieve_correct_beam_group(
echodata=self.echodata, waveform_mode=self.waveform_mode, encode_mode=self.encode_mode
)

# Select the channels to calibrate
if self.encode_mode == "power":
# Power sample only possible under CW mode,
# and all power samples will live in the same group
self.chan_sel = self.echodata[self.ed_group]["channel"]
self.chan_sel = self.echodata[self.ed_beam_group]["channel"]
else:
# Complex samples can be CW or BB, so select based on waveform mode
chan_dict = self._get_chan_dict(self.echodata[self.ed_group])
chan_dict = self._get_chan_dict(self.echodata[self.ed_beam_group])
self.chan_sel = chan_dict[self.waveform_mode]

# Subset of the right Sonar/Beam_groupX group given the selected channels
beam = self.echodata[self.ed_group].sel(channel=self.chan_sel)
beam = self.echodata[self.ed_beam_group].sel(channel=self.chan_sel)

# Use center frequency if in BB mode, else use nominal channel frequency
if self.waveform_mode == "BB":
Expand All @@ -226,11 +231,12 @@ def __init__(self, echodata, env_params, cal_params, waveform_mode, encode_mode)
self.freq_center = beam["frequency_nominal"].sel(channel=self.chan_sel)

# Get env_params: depends on waveform mode
self.env_params = get_env_params_EK80(
echodata=echodata,
self.env_params = get_env_params_EK(
sonar_type=self.sonar_type,
beam=beam,
env=self.echodata["Environment"],
user_dict=self.env_params,
freq=self.freq_center,
user_env_dict=env_params,
ed_group=self.ed_group,
)

# Get cal_params: depends on waveform and encode mode
Expand Down Expand Up @@ -333,24 +339,22 @@ def _get_B_theta_phi_m(self):

return B_theta_phi_m

def _cal_complex_samples(self, cal_type: str, complex_ed_group: str) -> xr.Dataset:
def _cal_complex_samples(self, cal_type: str) -> xr.Dataset:
"""Calibrate complex data from EK80.
Parameters
----------
cal_type : str
'Sv' for calculating volume backscattering strength, or
'TS' for calculating target strength
complex_ed_group : str
The ``EchoData`` beam group path containing complex data
Returns
-------
xr.Dataset
The calibrated dataset containing Sv or TS
"""
# Select source of backscatter data
beam = self.echodata[complex_ed_group].sel(channel=self.chan_sel)
beam = self.echodata[self.ed_beam_group].sel(channel=self.chan_sel)
vend = self.echodata["Vendor_specific"].sel(channel=self.chan_sel)

# Get transmit signal
Expand All @@ -376,7 +380,9 @@ def _cal_complex_samples(self, cal_type: str, complex_ed_group: str) -> xr.Datas
transmit_power = beam["transmit_power"]

# TVG compensation with modified range
tvg_mod_range = range_mod_TVG_EK(self.echodata, self.ed_group, range_meter, sound_speed)
tvg_mod_range = range_mod_TVG_EK(
self.echodata, self.ed_beam_group, range_meter, sound_speed
)
tvg_mod_range = tvg_mod_range.where(tvg_mod_range > 0, np.nan)

spreading_loss = 20 * np.log10(tvg_mod_range)
Expand Down Expand Up @@ -476,10 +482,10 @@ def _compute_cal(self, cal_type) -> xr.Dataset:

if flag_complex:
# Complex samples can be BB or CW
ds_cal = self._cal_complex_samples(cal_type=cal_type, complex_ed_group=self.ed_group)
ds_cal = self._cal_complex_samples(cal_type=cal_type)
else:
# Power samples only make sense for CW mode data
ds_cal = self._cal_power_samples(cal_type=cal_type, power_ed_group=self.ed_group)
ds_cal = self._cal_power_samples(cal_type=cal_type)

return ds_cal

Expand Down
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