From 363242972cd1bd7d18d465d7f5ced4ca9c3cab92 Mon Sep 17 00:00:00 2001 From: Matthias Grob Date: Tue, 4 Nov 2025 11:27:26 +0100 Subject: [PATCH] process_sensor_caldata: correct pressure unit to Pascal instead of Hectopascal Barometeric pressure was changed to the SI unit Pascal instead of the non-SI unit Hectopascal/Millibar in 0c31f6389666d942d59b74cd2e107a5d3b263ea6 This script stayed unchanged and suffers from assuming `sensor_baro.pressure` is still in the old unit which would be a 100 times smaller number. --- Tools/process_sensor_caldata.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/Tools/process_sensor_caldata.py b/Tools/process_sensor_caldata.py index e70ffc8878..c0c656e015 100755 --- a/Tools/process_sensor_caldata.py +++ b/Tools/process_sensor_caldata.py @@ -1656,9 +1656,9 @@ sensor_baro_0['pressure'] = median_filter(sensor_baro_0['pressure']) # fit data median_pressure = np.median(sensor_baro_0['pressure']) if noResample: - coef_baro_0_x = np.polyfit(temp_rel,100*(sensor_baro_0['pressure']-median_pressure),5) # convert from hPa to Pa + coef_baro_0_x = np.polyfit(temp_rel,(sensor_baro_0['pressure']-median_pressure),5) # pressure in Pascal else: - temperature, baro = resampleWithDeltaX(temp_rel,100*(sensor_baro_0['pressure']-median_pressure)) # convert from hPa to Pa + temperature, baro = resampleWithDeltaX(temp_rel,(sensor_baro_0['pressure']-median_pressure)) # pressure in Pascal coef_baro_0_x = np.polyfit(temperature,baro,5) baro_0_params['TC_B0_X5'] = coef_baro_0_x[0] @@ -1717,9 +1717,9 @@ if num_baros >= 2: # fit data median_pressure = np.median(sensor_baro_1['pressure']) if noResample: - coef_baro_1_x = np.polyfit(temp_rel,100*(sensor_baro_1['pressure']-median_pressure),5) # convert from hPa to Pa + coef_baro_1_x = np.polyfit(temp_rel,(sensor_baro_1['pressure']-median_pressure),5) # pressure in Pascal else: - temperature, baro = resampleWithDeltaX(temp_rel,100*(sensor_baro_1['pressure']-median_pressure)) # convert from hPa to Pa + temperature, baro = resampleWithDeltaX(temp_rel,(sensor_baro_1['pressure']-median_pressure)) # pressure in Pascal coef_baro_1_x = np.polyfit(temperature,baro,5) baro_1_params['TC_B1_X5'] = coef_baro_1_x[0] @@ -1778,9 +1778,9 @@ if num_baros >= 3: # fit data median_pressure = np.median(sensor_baro_2['pressure']) if noResample: - coef_baro_2_x = np.polyfit(temp_rel,100*(sensor_baro_2['pressure']-median_pressure),5) # convert from hPa to Pa + coef_baro_2_x = np.polyfit(temp_rel,(sensor_baro_2['pressure']-median_pressure),5) # pressure in Pascal else: - temperature, baro = resampleWithDeltaX(temp_rel,100*(sensor_baro_2['pressure']-median_pressure)) # convert from hPa to Pa + temperature, baro = resampleWithDeltaX(temp_rel,(sensor_baro_2['pressure']-median_pressure)) # pressure in Pascal coef_baro_2_x = np.polyfit(temperature,baro,5) baro_2_params['TC_B2_X5'] = coef_baro_2_x[0] @@ -1838,7 +1838,7 @@ if num_baros >= 4: # fit data median_pressure = np.median(sensor_baro_3['pressure']) - coef_baro_3_x = np.polyfit(temp_rel,100*(sensor_baro_3['pressure']-median_pressure),5) # convert from hPa to Pa + coef_baro_3_x = np.polyfit(temp_rel,(sensor_baro_3['pressure']-median_pressure),5) # pressure in Pascal baro_3_params['TC_B3_X5'] = coef_baro_3_x[0] baro_3_params['TC_B3_X4'] = coef_baro_3_x[1] baro_3_params['TC_B3_X3'] = coef_baro_3_x[2]