Merge pull request #990 from OSOceanAcoustics/dev

Release/v0.6.4.1
OSOceanAcoustics · Mar 16, 2023 · f8082ca · f8082ca
2 parents f12322c + e65a921
commit f8082ca
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diff --git a/docs/source/whats-new.md b/docs/source/whats-new.md
@@ -4,6 +4,22 @@ What's new
 See [GitHub releases page](https://github.com/OSOceanAcoustics/echopype/releases) for the complete history.
 
 
+# v0.6.4.1 (2023 March 15)
+
+## Overview
+
+This is a minor release that includes a small bug fix and an enhancement, which removes excessive warnings due to changes in v0.6.4.
+
+## Bug fix
+- Fix a bug that prevented passing in `env_params` for EK60 calibration (#987)
+
+## Enhancement
+- Handling non-positive values that causes log10 warnings on EK calibration (#986)
+
+
+
+
+
 # v0.6.4 (2023 March 13)
 
 ## Overview

diff --git a/echopype/calibrate/calibrate_ek.py b/echopype/calibrate/calibrate_ek.py
@@ -65,6 +65,8 @@ def _cal_power_samples(self, cal_type: str, power_ed_group: str = None) -> xr.Da
         tvg_mod_range = range_mod_TVG_EK(
             self.echodata, self.ed_group, self.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)
         absorption_loss = 2 * absorption * tvg_mod_range
 
@@ -132,7 +134,7 @@ def __init__(self, echodata, env_params, cal_params, **kwargs):
         self.sonar_type = "EK60"
 
         # Get env_params
-        self.env_params = get_env_params_EK60(echodata=echodata, user_env_dict=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"
 
@@ -375,11 +377,14 @@ def _cal_complex_samples(self, cal_type: str, complex_ed_group: str) -> xr.Datas
 
         # TVG compensation with modified range
         tvg_mod_range = range_mod_TVG_EK(self.echodata, self.ed_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)
         absorption_loss = 2 * absorption * tvg_mod_range
 
         # Get power from complex samples
         prx = self._get_power_from_complex(beam=beam, chirp=tx, z_et=z_et, z_er=z_er)
+        prx = prx.where(prx > 0, np.nan)
 
         # Compute based on cal_type
         if cal_type == "Sv":