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Merge branch 'main' of https://gitlab.psi.ch/apog/acsmnode

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This updates todo.md
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florez_j
2025-05-26 13:12:52 +02:00
parent 52fdb7a8ad e8327f7bd7
commit 989e99078a
3 changed files with 13 additions and 7 deletions
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10
TODO.md
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@ -1,8 +1,10 @@
# TODO
* [from Leïla] Add flagging based on CPC flags
* [from Leïla] Correct calibration_params copying
* [from Leïla] Plot for auto flags visualization should be able to zoom in vertically
* [from Leïla] Remove inletP column in level 2 .nas data
* [from Leïla] Correct error when flags are loaded in the flagging app
* [from Leïla] End the file at end of year (or filter only current year)
* [from Leïla] Change "9999.999" to "9999999.9999" in header
* [from Leïla] Update Detection limit values in L2 header: take the ones (1h) from limits_of_detection.yaml
* [from Leïla] For PAY, calculate error as 50% of concentration
* [from Leïla] Correct errors (uncertainties) that they can't be lower than 0.0001
* [from Leïla] Change flow rate values to 10% of flow rate ref
* [New] Create data flows to validate and replace existing data chain params. data/campaignData/param/ -> pipelines/params and campaignDescriptor.yaml -> acsm data converter.
* [New] DIMA. Add dictionaries to explain variables at different levels.

8
campaignDescriptor.yaml
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@ -30,8 +30,10 @@ originator:
email: leila.simon@psi.ch
affiliation: Paul Scherrer Institute, PSI
department: Laboratory of Atmospheric Chemistry
city: Villigen PSI
address_line_1: ""
address_line_2: ""
postal_code: 5232
city: Villigen PSI
country: Switzerland
submitter:
@ -39,6 +41,8 @@ submitter:
email: leila.simon@psi.ch
affiliation: Paul Scherrer Institute, PSI
department: Laboratory of Atmospheric Chemistry
city: Villigen PSI
address_line_1: ""
address_line_2: ""
postal_code: 5232
city: Villigen PSI
country: Switzerland

2
pipelines/steps/generate_flags.py
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@ -264,7 +264,7 @@ def generate_species_flags(data_table : pd.DataFrame, calib_param_dict : dict, f
numflag_columns = [col for col in data_table.columns if 'numflag_' in col]
if interpolated_cpc_flags:
if len(interpolated_cpc_flags)>0:
data_table = reconcile_flags(data_table, interpolated_cpc_flags, 0, interpolated_cpc_flags.size, numflag_columns)