Describe the bug When you add the filtered volume in the metadata

frontend/node-red-dashboard: filtered volume is dropped from metadata export in the single-location sample type,about planktoscope/planktoscope

Comments (1)

ethanjli commented on June 11, 2024

I attempted to perform some test image acquisitions with various sample types, with the "Filtered volume" field set to 42 in each type, and the "Concentrated sample volume" and "Dilution Factor" fields left blank.

Here's the update_config command which Node-RED sends to the Python hardware controller in the "Single location" sample type:

{
    "action": "update_config",
    "config": {
        "description": {
            "sample_project": "Project's name",
            "sample_id": "Sample ID",
            "sample_uuid": "Sample UUID (Autogenerated)",
            "sample_ship": "Ship's name",
            "sample_operator": "Operator's name",
            "sample_sampling_gear": "Sampling gear used",
            "sample_concentrated_sample_volume": "Volume of concentrated sample, in mL",
            "sample_total_volume": "Total volume filtered by the net used, in L",
            "sample_dilution_factor": "Dilution factor of the sample, 0.5 if diluted by 2, 2 if concentrated by 2",
            "sample_speed_through_water": "Speed of the boat through water when sampling, in kts",
            "acq_id": "Acquisition ID",
            "acq_uuid": "Acquisition UUID (Autogenerated)",
            "acq_instrument": "Instrument type",
            "acq_instrument_id": "Instrument ID",
            "acq_celltype": "Flow cell dimension thickness, in µm",
            "acq_minimum_mesh": "Minimum filtration mesh size, in µm",
            "acq_maximum_mesh": "Maximum filtration mesh size, in µm",
            "acq_min_esd": "",
            "acq_max_esd": "",
            "acq_volume": "Pumped volume, in mL",
            "acq_imaged_volume": "Total imaged volume, in mL",
            "acq_magnification": "Optical magnification",
            "acq_fnumber_objective": "Focal length of the objective, in mm",
            "acq_camera_name": "Name of the camera used",
            "acq_nb_frame": "Number of picture taken",
            "acq_local_datetime": "Instrument local datetime",
            "acq_camera_resolution": "Resolution of the images",
            "acq_camera_iso": "ISO Number of the images",
            "acq_camera_shutter_speed": "Shutter speed of the images, in µs",
            "acq_software": "Software version number",
            "object_date": "Sample collection date (or beginning if using a net)",
            "object_time": "Sample collection time (or beginning if using a net)",
            "object_lat": "Sample collection latitude (or beginning if using a net)",
            "object_lon": "Sample collection longitude (or beginning if using a net)",
            "object_depth_min": "Sample collection minimal depth, in m",
            "object_depth_max": "Sample collection maximum depth, in m",
            "process_pixel": "Pixel imaging resolution, in µm/pixel",
            "process_datetime": "Segmentation timestamp",
            "process_id": "Segmentation ID",
            "process_uuid": "Segmentation UUID (Autogenerated)",
            "process_source": "Code source link of the executed code",
            "process_commit": "Version reference of the executed code",
            "sample_gear_net_opening": "Sample mouth opening dimension, in mm",
            "object_date_end": "Sample end collection date when using a net",
            "object_time_end": "Sample end collection time when using a net",
            "object_lat_end": "Sample end collection latitude when using a net",
            "object_lon_end": "Sample end collection longitude when using a net",
        },
        "sample_project": "dev",
        "sample_id": "dev_1",
        "sample_ship": "troubleshooting",
        "sample_operator": "ethanjli",
        "sample_sampling_gear": "single_location",
        "acq_id": "dev_1_1",
        "acq_instrument": "PlanktoScope v2.1",
        "acq_instrument_id": "bitter-floor-43365",
        "acq_celltype": 200,
        "acq_minimum_mesh": 10,
        "acq_maximum_mesh": 200,
        "acq_volume": "0.01",
        "acq_magnification": "ERROR",
        "acq_fnumber_objective": 16,
        "acq_nb_frame": 5,
        "acq_software": "PlanktoScope v2023.9.0-25-g8214208",
        "object_date": "20240127",
        "object_time": "1144",
        "object_lat": "0.0000",
        "object_lon": "0.0000",
        "object_depth_min": 1,
        "object_depth_max": 2,
        "process_pixel": 0.75,
        "process_source": "github.com/PlanktoScope/PlanktoScope",
        "process_commit": "8214208909a06c13ef3fbbf8b6b8103a84a69b9e",
    },
}

Here's the update_config command which Node-RED sends to the Python hardware controller in the "Pass hull" sample type:

{
    "action": "update_config",
    "config": {
        "description": {
            "sample_project": "Project's name",
            "sample_id": "Sample ID",
            "sample_uuid": "Sample UUID (Autogenerated)",
            "sample_ship": "Ship's name",
            "sample_operator": "Operator's name",
            "sample_sampling_gear": "Sampling gear used",
            "sample_concentrated_sample_volume": "Volume of concentrated sample, in mL",
            "sample_total_volume": "Total volume filtered by the net used, in L",
            "sample_dilution_factor": "Dilution factor of the sample, 0.5 if diluted by 2, 2 if concentrated by 2",
            "sample_speed_through_water": "Speed of the boat through water when sampling, in kts",
            "acq_id": "Acquisition ID",
            "acq_uuid": "Acquisition UUID (Autogenerated)",
            "acq_instrument": "Instrument type",
            "acq_instrument_id": "Instrument ID",
            "acq_celltype": "Flow cell dimension thickness, in µm",
            "acq_minimum_mesh": "Minimum filtration mesh size, in µm",
            "acq_maximum_mesh": "Maximum filtration mesh size, in µm",
            "acq_min_esd": "",
            "acq_max_esd": "",
            "acq_volume": "Pumped volume, in mL",
            "acq_imaged_volume": "Total imaged volume, in mL",
            "acq_magnification": "Optical magnification",
            "acq_fnumber_objective": "Focal length of the objective, in mm",
            "acq_camera_name": "Name of the camera used",
            "acq_nb_frame": "Number of picture taken",
            "acq_local_datetime": "Instrument local datetime",
            "acq_camera_resolution": "Resolution of the images",
            "acq_camera_iso": "ISO Number of the images",
            "acq_camera_shutter_speed": "Shutter speed of the images, in µs",
            "acq_software": "Software version number",
            "object_date": "Sample collection date (or beginning if using a net)",
            "object_time": "Sample collection time (or beginning if using a net)",
            "object_lat": "Sample collection latitude (or beginning if using a net)",
            "object_lon": "Sample collection longitude (or beginning if using a net)",
            "object_depth_min": "Sample collection minimal depth, in m",
            "object_depth_max": "Sample collection maximum depth, in m",
            "process_pixel": "Pixel imaging resolution, in µm/pixel",
            "process_datetime": "Segmentation timestamp",
            "process_id": "Segmentation ID",
            "process_uuid": "Segmentation UUID (Autogenerated)",
            "process_source": "Code source link of the executed code",
            "process_commit": "Version reference of the executed code",
            "sample_gear_net_opening": "Sample mouth opening dimension, in mm",
            "object_date_end": "Sample end collection date when using a net",
            "object_time_end": "Sample end collection time when using a net",
            "object_lat_end": "Sample end collection latitude when using a net",
            "object_lon_end": "Sample end collection longitude when using a net",
        },
        "sample_project": "dev",
        "sample_id": "dev_1",
        "sample_ship": "troubleshooting",
        "sample_operator": "ethanjli",
        "sample_sampling_gear": "pass_hull",
        "acq_id": "dev_1_2",
        "acq_instrument": "PlanktoScope v2.1",
        "acq_instrument_id": "bitter-floor-43365",
        "acq_celltype": 200,
        "acq_minimum_mesh": 10,
        "acq_maximum_mesh": 200,
        "acq_volume": "0.00",
        "acq_magnification": "ERROR",
        "acq_fnumber_objective": 16,
        "acq_nb_frame": 1,
        "acq_software": "PlanktoScope v2023.9.0-25-g8214208",
        "object_date": "20240127",
        "object_time": "1148",
        "object_lat": "0.0000",
        "object_lon": "0.0000",
        "object_depth_min": 1,
        "object_depth_max": 2,
        "process_pixel": 0.75,
        "process_source": "github.com/PlanktoScope/PlanktoScope",
        "process_commit": "8214208909a06c13ef3fbbf8b6b8103a84a69b9e",
    },
}

Here's the update_config command which Node-RED sends to the Python hardware controller in the "Lab culture" sample type:

{
    "action": "update_config",
    "config": {
        "description": {
            "sample_project": "Project's name",
            "sample_id": "Sample ID",
            "sample_uuid": "Sample UUID (Autogenerated)",
            "sample_ship": "Ship's name",
            "sample_operator": "Operator's name",
            "sample_sampling_gear": "Sampling gear used",
            "sample_concentrated_sample_volume": "Volume of concentrated sample, in mL",
            "sample_total_volume": "Total volume filtered by the net used, in L",
            "sample_dilution_factor": "Dilution factor of the sample, 0.5 if diluted by 2, 2 if concentrated by 2",
            "sample_speed_through_water": "Speed of the boat through water when sampling, in kts",
            "acq_id": "Acquisition ID",
            "acq_uuid": "Acquisition UUID (Autogenerated)",
            "acq_instrument": "Instrument type",
            "acq_instrument_id": "Instrument ID",
            "acq_celltype": "Flow cell dimension thickness, in µm",
            "acq_minimum_mesh": "Minimum filtration mesh size, in µm",
            "acq_maximum_mesh": "Maximum filtration mesh size, in µm",
            "acq_min_esd": "",
            "acq_max_esd": "",
            "acq_volume": "Pumped volume, in mL",
            "acq_imaged_volume": "Total imaged volume, in mL",
            "acq_magnification": "Optical magnification",
            "acq_fnumber_objective": "Focal length of the objective, in mm",
            "acq_camera_name": "Name of the camera used",
            "acq_nb_frame": "Number of picture taken",
            "acq_local_datetime": "Instrument local datetime",
            "acq_camera_resolution": "Resolution of the images",
            "acq_camera_iso": "ISO Number of the images",
            "acq_camera_shutter_speed": "Shutter speed of the images, in µs",
            "acq_software": "Software version number",
            "object_date": "Sample collection date (or beginning if using a net)",
            "object_time": "Sample collection time (or beginning if using a net)",
            "object_lat": "Sample collection latitude (or beginning if using a net)",
            "object_lon": "Sample collection longitude (or beginning if using a net)",
            "object_depth_min": "Sample collection minimal depth, in m",
            "object_depth_max": "Sample collection maximum depth, in m",
            "process_pixel": "Pixel imaging resolution, in µm/pixel",
            "process_datetime": "Segmentation timestamp",
            "process_id": "Segmentation ID",
            "process_uuid": "Segmentation UUID (Autogenerated)",
            "process_source": "Code source link of the executed code",
            "process_commit": "Version reference of the executed code",
            "sample_gear_net_opening": "Sample mouth opening dimension, in mm",
            "object_date_end": "Sample end collection date when using a net",
            "object_time_end": "Sample end collection time when using a net",
            "object_lat_end": "Sample end collection latitude when using a net",
            "object_lon_end": "Sample end collection longitude when using a net",
        },
        "sample_project": "dev",
        "sample_id": "dev_1",
        "sample_ship": "troubleshooting",
        "sample_operator": "ethanjli",
        "sample_sampling_gear": "culture",
        "acq_id": "dev_1_3",
        "acq_instrument": "PlanktoScope v2.1",
        "acq_instrument_id": "bitter-floor-43365",
        "acq_celltype": 200,
        "acq_minimum_mesh": 10,
        "acq_maximum_mesh": 200,
        "acq_volume": "0.00",
        "acq_magnification": "ERROR",
        "acq_fnumber_objective": 16,
        "acq_nb_frame": 1,
        "acq_software": "PlanktoScope v2023.9.0-25-g8214208",
        "object_date": "20240127",
        "object_time": "195121",
        "object_lat": "-90.0000",
        "object_lon": "0.0000",
        "object_depth_min": 1,
        "object_depth_max": 2,
        "process_pixel": 0.75,
        "process_source": "github.com/PlanktoScope/PlanktoScope",
        "process_commit": "8214208909a06c13ef3fbbf8b6b8103a84a69b9e",
    },
}

Here's the update_config command which Node-RED sends to the Python hardware controller in the "Niskin bottle 12L" sample type:

{
    "action": "update_config",
    "config": {
        "description": {
            "sample_project": "Project's name",
            "sample_id": "Sample ID",
            "sample_uuid": "Sample UUID (Autogenerated)",
            "sample_ship": "Ship's name",
            "sample_operator": "Operator's name",
            "sample_sampling_gear": "Sampling gear used",
            "sample_concentrated_sample_volume": "Volume of concentrated sample, in mL",
            "sample_total_volume": "Total volume filtered by the net used, in L",
            "sample_dilution_factor": "Dilution factor of the sample, 0.5 if diluted by 2, 2 if concentrated by 2",
            "sample_speed_through_water": "Speed of the boat through water when sampling, in kts",
            "acq_id": "Acquisition ID",
            "acq_uuid": "Acquisition UUID (Autogenerated)",
            "acq_instrument": "Instrument type",
            "acq_instrument_id": "Instrument ID",
            "acq_celltype": "Flow cell dimension thickness, in µm",
            "acq_minimum_mesh": "Minimum filtration mesh size, in µm",
            "acq_maximum_mesh": "Maximum filtration mesh size, in µm",
            "acq_min_esd": "",
            "acq_max_esd": "",
            "acq_volume": "Pumped volume, in mL",
            "acq_imaged_volume": "Total imaged volume, in mL",
            "acq_magnification": "Optical magnification",
            "acq_fnumber_objective": "Focal length of the objective, in mm",
            "acq_camera_name": "Name of the camera used",
            "acq_nb_frame": "Number of picture taken",
            "acq_local_datetime": "Instrument local datetime",
            "acq_camera_resolution": "Resolution of the images",
            "acq_camera_iso": "ISO Number of the images",
            "acq_camera_shutter_speed": "Shutter speed of the images, in µs",
            "acq_software": "Software version number",
            "object_date": "Sample collection date (or beginning if using a net)",
            "object_time": "Sample collection time (or beginning if using a net)",
            "object_lat": "Sample collection latitude (or beginning if using a net)",
            "object_lon": "Sample collection longitude (or beginning if using a net)",
            "object_depth_min": "Sample collection minimal depth, in m",
            "object_depth_max": "Sample collection maximum depth, in m",
            "process_pixel": "Pixel imaging resolution, in µm/pixel",
            "process_datetime": "Segmentation timestamp",
            "process_id": "Segmentation ID",
            "process_uuid": "Segmentation UUID (Autogenerated)",
            "process_source": "Code source link of the executed code",
            "process_commit": "Version reference of the executed code",
            "sample_gear_net_opening": "Sample mouth opening dimension, in mm",
            "object_date_end": "Sample end collection date when using a net",
            "object_time_end": "Sample end collection time when using a net",
            "object_lat_end": "Sample end collection latitude when using a net",
            "object_lon_end": "Sample end collection longitude when using a net",
        },
        "sample_project": "dev",
        "sample_id": "dev_1",
        "sample_ship": "troubleshooting",
        "sample_operator": "ethanjli",
        "sample_sampling_gear": "niskin_12L",
        "acq_id": "dev_1_4",
        "acq_instrument": "PlanktoScope v2.1",
        "acq_instrument_id": "bitter-floor-43365",
        "acq_celltype": 200,
        "acq_minimum_mesh": 10,
        "acq_maximum_mesh": 200,
        "acq_volume": "0.00",
        "acq_magnification": "ERROR",
        "acq_fnumber_objective": 16,
        "acq_nb_frame": 1,
        "acq_software": "PlanktoScope v2023.9.0-25-g8214208",
        "object_date": "20240127",
        "object_time": "1153",
        "object_lat": "0.0000",
        "object_lon": "0.0000",
        "object_depth_min": 1,
        "object_depth_max": 2,
        "process_pixel": 0.75,
        "process_source": "github.com/PlanktoScope/PlanktoScope",
        "process_commit": "8214208909a06c13ef3fbbf8b6b8103a84a69b9e",
    },
}

Here's the update_config command which Node-RED sends to the Python hardware controller in the "Plankton net" sample type:

{
    "action": "update_config",
    "config": {
        "description": {
            "sample_project": "Project's name",
            "sample_id": "Sample ID",
            "sample_uuid": "Sample UUID (Autogenerated)",
            "sample_ship": "Ship's name",
            "sample_operator": "Operator's name",
            "sample_sampling_gear": "Sampling gear used",
            "sample_concentrated_sample_volume": "Volume of concentrated sample, in mL",
            "sample_total_volume": "Total volume filtered by the net used, in L",
            "sample_dilution_factor": "Dilution factor of the sample, 0.5 if diluted by 2, 2 if concentrated by 2",
            "sample_speed_through_water": "Speed of the boat through water when sampling, in kts",
            "acq_id": "Acquisition ID",
            "acq_uuid": "Acquisition UUID (Autogenerated)",
            "acq_instrument": "Instrument type",
            "acq_instrument_id": "Instrument ID",
            "acq_celltype": "Flow cell dimension thickness, in µm",
            "acq_minimum_mesh": "Minimum filtration mesh size, in µm",
            "acq_maximum_mesh": "Maximum filtration mesh size, in µm",
            "acq_min_esd": "",
            "acq_max_esd": "",
            "acq_volume": "Pumped volume, in mL",
            "acq_imaged_volume": "Total imaged volume, in mL",
            "acq_magnification": "Optical magnification",
            "acq_fnumber_objective": "Focal length of the objective, in mm",
            "acq_camera_name": "Name of the camera used",
            "acq_nb_frame": "Number of picture taken",
            "acq_local_datetime": "Instrument local datetime",
            "acq_camera_resolution": "Resolution of the images",
            "acq_camera_iso": "ISO Number of the images",
            "acq_camera_shutter_speed": "Shutter speed of the images, in µs",
            "acq_software": "Software version number",
            "object_date": "Sample collection date (or beginning if using a net)",
            "object_time": "Sample collection time (or beginning if using a net)",
            "object_lat": "Sample collection latitude (or beginning if using a net)",
            "object_lon": "Sample collection longitude (or beginning if using a net)",
            "object_depth_min": "Sample collection minimal depth, in m",
            "object_depth_max": "Sample collection maximum depth, in m",
            "process_pixel": "Pixel imaging resolution, in µm/pixel",
            "process_datetime": "Segmentation timestamp",
            "process_id": "Segmentation ID",
            "process_uuid": "Segmentation UUID (Autogenerated)",
            "process_source": "Code source link of the executed code",
            "process_commit": "Version reference of the executed code",
            "sample_gear_net_opening": "Sample mouth opening dimension, in mm",
            "object_date_end": "Sample end collection date when using a net",
            "object_time_end": "Sample end collection time when using a net",
            "object_lat_end": "Sample end collection latitude when using a net",
            "object_lon_end": "Sample end collection longitude when using a net",
        },
        "sample_project": "dev",
        "sample_id": "dev_1",
        "sample_ship": "troubleshooting",
        "sample_operator": "ethanjli",
        "sample_sampling_gear": "net",
        "acq_id": "dev_1_5",
        "acq_instrument": "PlanktoScope v2.1",
        "acq_instrument_id": "bitter-floor-43365",
        "acq_celltype": 200,
        "acq_minimum_mesh": 10,
        "acq_maximum_mesh": 200,
        "acq_volume": "0.00",
        "acq_magnification": "ERROR",
        "acq_fnumber_objective": 16,
        "acq_nb_frame": 1,
        "acq_software": "PlanktoScope v2023.9.0-25-g8214208",
        "object_date": "20240127",
        "object_time": "1159",
        "object_lat": "0.0000",
        "object_lon": "0.0000",
        "object_depth_min": 1,
        "object_depth_max": 2,
        "process_pixel": 0.75,
        "process_source": "github.com/PlanktoScope/PlanktoScope",
        "process_commit": "8214208909a06c13ef3fbbf8b6b8103a84a69b9e",
        "sample_gear_net_opening": 40,
        "object_date_end": "20240127",
        "object_time_end": "1159",
        "object_lat_end": "0.0000",
        "object_lon_end": "0.0000",
        "sample_total_volume": "42",
    },
}

Here's the update_config command which Node-RED sends to the Python hardware controller in the "High Speed Net" sample type:

{
    "action": "update_config",
    "config": {
        "description": {
            "sample_project": "Project's name",
            "sample_id": "Sample ID",
            "sample_uuid": "Sample UUID (Autogenerated)",
            "sample_ship": "Ship's name",
            "sample_operator": "Operator's name",
            "sample_sampling_gear": "Sampling gear used",
            "sample_concentrated_sample_volume": "Volume of concentrated sample, in mL",
            "sample_total_volume": "Total volume filtered by the net used, in L",
            "sample_dilution_factor": "Dilution factor of the sample, 0.5 if diluted by 2, 2 if concentrated by 2",
            "sample_speed_through_water": "Speed of the boat through water when sampling, in kts",
            "acq_id": "Acquisition ID",
            "acq_uuid": "Acquisition UUID (Autogenerated)",
            "acq_instrument": "Instrument type",
            "acq_instrument_id": "Instrument ID",
            "acq_celltype": "Flow cell dimension thickness, in µm",
            "acq_minimum_mesh": "Minimum filtration mesh size, in µm",
            "acq_maximum_mesh": "Maximum filtration mesh size, in µm",
            "acq_min_esd": "",
            "acq_max_esd": "",
            "acq_volume": "Pumped volume, in mL",
            "acq_imaged_volume": "Total imaged volume, in mL",
            "acq_magnification": "Optical magnification",
            "acq_fnumber_objective": "Focal length of the objective, in mm",
            "acq_camera_name": "Name of the camera used",
            "acq_nb_frame": "Number of picture taken",
            "acq_local_datetime": "Instrument local datetime",
            "acq_camera_resolution": "Resolution of the images",
            "acq_camera_iso": "ISO Number of the images",
            "acq_camera_shutter_speed": "Shutter speed of the images, in µs",
            "acq_software": "Software version number",
            "object_date": "Sample collection date (or beginning if using a net)",
            "object_time": "Sample collection time (or beginning if using a net)",
            "object_lat": "Sample collection latitude (or beginning if using a net)",
            "object_lon": "Sample collection longitude (or beginning if using a net)",
            "object_depth_min": "Sample collection minimal depth, in m",
            "object_depth_max": "Sample collection maximum depth, in m",
            "process_pixel": "Pixel imaging resolution, in µm/pixel",
            "process_datetime": "Segmentation timestamp",
            "process_id": "Segmentation ID",
            "process_uuid": "Segmentation UUID (Autogenerated)",
            "process_source": "Code source link of the executed code",
            "process_commit": "Version reference of the executed code",
            "sample_gear_net_opening": "Sample mouth opening dimension, in mm",
            "object_date_end": "Sample end collection date when using a net",
            "object_time_end": "Sample end collection time when using a net",
            "object_lat_end": "Sample end collection latitude when using a net",
            "object_lon_end": "Sample end collection longitude when using a net",
        },
        "sample_project": "dev",
        "sample_id": "dev_1",
        "sample_ship": "troubleshooting",
        "sample_operator": "ethanjli",
        "sample_sampling_gear": "net_hsn",
        "acq_id": "dev_1_6",
        "acq_instrument": "PlanktoScope v2.1",
        "acq_instrument_id": "bitter-floor-43365",
        "acq_celltype": 200,
        "acq_minimum_mesh": 10,
        "acq_maximum_mesh": 200,
        "acq_volume": "0.00",
        "acq_magnification": "ERROR",
        "acq_fnumber_objective": 16,
        "acq_nb_frame": 1,
        "acq_software": "PlanktoScope v2023.9.0-25-g8214208",
        "object_date": "20240127",
        "object_time": "1202",
        "object_lat": "0.0000",
        "object_lon": "0.0000",
        "object_depth_min": 1,
        "object_depth_max": 2,
        "process_pixel": 0.75,
        "process_source": "github.com/PlanktoScope/PlanktoScope",
        "process_commit": "8214208909a06c13ef3fbbf8b6b8103a84a69b9e",
        "sample_gear_net_opening": 40,
        "object_date_end": "20240127",
        "object_time_end": "1202",
        "object_lat_end": "0.0000",
        "object_lon_end": "0.0000",
        "sample_total_volume": "42",
    },
}

Here's the update_config command which Node-RED sends to the Python hardware controller in the "Tara Decknet" sample type:

{
    "action": "update_config",
    "config": {
        "description": {
            "sample_project": "Project's name",
            "sample_id": "Sample ID",
            "sample_uuid": "Sample UUID (Autogenerated)",
            "sample_ship": "Ship's name",
            "sample_operator": "Operator's name",
            "sample_sampling_gear": "Sampling gear used",
            "sample_concentrated_sample_volume": "Volume of concentrated sample, in mL",
            "sample_total_volume": "Total volume filtered by the net used, in L",
            "sample_dilution_factor": "Dilution factor of the sample, 0.5 if diluted by 2, 2 if concentrated by 2",
            "sample_speed_through_water": "Speed of the boat through water when sampling, in kts",
            "acq_id": "Acquisition ID",
            "acq_uuid": "Acquisition UUID (Autogenerated)",
            "acq_instrument": "Instrument type",
            "acq_instrument_id": "Instrument ID",
            "acq_celltype": "Flow cell dimension thickness, in µm",
            "acq_minimum_mesh": "Minimum filtration mesh size, in µm",
            "acq_maximum_mesh": "Maximum filtration mesh size, in µm",
            "acq_min_esd": "",
            "acq_max_esd": "",
            "acq_volume": "Pumped volume, in mL",
            "acq_imaged_volume": "Total imaged volume, in mL",
            "acq_magnification": "Optical magnification",
            "acq_fnumber_objective": "Focal length of the objective, in mm",
            "acq_camera_name": "Name of the camera used",
            "acq_nb_frame": "Number of picture taken",
            "acq_local_datetime": "Instrument local datetime",
            "acq_camera_resolution": "Resolution of the images",
            "acq_camera_iso": "ISO Number of the images",
            "acq_camera_shutter_speed": "Shutter speed of the images, in µs",
            "acq_software": "Software version number",
            "object_date": "Sample collection date (or beginning if using a net)",
            "object_time": "Sample collection time (or beginning if using a net)",
            "object_lat": "Sample collection latitude (or beginning if using a net)",
            "object_lon": "Sample collection longitude (or beginning if using a net)",
            "object_depth_min": "Sample collection minimal depth, in m",
            "object_depth_max": "Sample collection maximum depth, in m",
            "process_pixel": "Pixel imaging resolution, in µm/pixel",
            "process_datetime": "Segmentation timestamp",
            "process_id": "Segmentation ID",
            "process_uuid": "Segmentation UUID (Autogenerated)",
            "process_source": "Code source link of the executed code",
            "process_commit": "Version reference of the executed code",
            "sample_gear_net_opening": "Sample mouth opening dimension, in mm",
            "object_date_end": "Sample end collection date when using a net",
            "object_time_end": "Sample end collection time when using a net",
            "object_lat_end": "Sample end collection latitude when using a net",
            "object_lon_end": "Sample end collection longitude when using a net",
        },
        "sample_project": "dev",
        "sample_id": "dev_1",
        "sample_ship": "troubleshooting",
        "sample_operator": "ethanjli",
        "sample_sampling_gear": "net_decknet",
        "acq_id": "dev_1_7",
        "acq_instrument": "PlanktoScope v2.1",
        "acq_instrument_id": "bitter-floor-43365",
        "acq_celltype": 200,
        "acq_minimum_mesh": 10,
        "acq_maximum_mesh": 200,
        "acq_volume": "0.00",
        "acq_magnification": "ERROR",
        "acq_fnumber_objective": 16,
        "acq_nb_frame": 1,
        "acq_software": "PlanktoScope v2023.9.0-25-g8214208",
        "object_date": "20240127",
        "object_time": "1203",
        "object_lat": "0.0000",
        "object_lon": "0.0000",
        "object_depth_min": 1,
        "object_depth_max": 2,
        "process_pixel": 0.75,
        "process_source": "github.com/PlanktoScope/PlanktoScope",
        "process_commit": "8214208909a06c13ef3fbbf8b6b8103a84a69b9e",
        "sample_gear_net_opening": 40,
        "object_date_end": "20240127",
        "object_time_end": "1203",
        "object_lat_end": "0.0000",
        "object_lon_end": "0.0000",
        "sample_total_volume": "42",
    },
}

As we can see from these above data structures, the filtered volume is sent along as the sample_total_volume metadata field only for the horizontal sampling sample types ("Plankton net", "High Speed Net", "Tara Decknet"). This suggests that by default the filtered volume is not passed to the Python hardware controller as a metadata field, and instead it's only passed as a special case for the horizontal sampling sample types. So solving this problem will require figuring out what is causing the sample_total_volume field to be sent in those cases.

I also determined that, when running an image acquisition routine with the "Single location" sample type right after running an image acquisition routine with the "Plankton net" sample type, the sample_total_volume field still does not appear in the metadata for the "Single location" acquisition.

from planktoscope.

frontend/node-red-dashboard: filtered volume is dropped from metadata export in the single-location sample type about planktoscope HOT 1 CLOSED

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