Instrument Classes

Spray Glider

Simple Class to hold glider data

class profiler.gliderdata.SprayData(datafile: str, dataset: str, in_field: bool = False)

Bases: ADCPData

Class to hold a full, standard Spray

dtype = 'Spray'

base_key: str = None

scalar_keys: list = []

__init__(datafile: str, dataset: str, in_field: bool = False)

in_field: bool = None

classmethod from_QG_glider(glider_df, meta, missid)

Build a SprayData instance from QG-sampled glider velocities.

Unlike DrifterData.from_QG_trajectory(), this uses the pre-sampled u_qg, v_qg columns directly — no finite differencing.

Parameters:

• glider_df (pd.DataFrame) – Glider velocity output with columns: x, y, time, missid, x_m, y_m, u_qg, v_qg

• meta (dict) – Metadata dict (must contain ‘dx’, ‘nx’).

• missid (int) – Glider mission ID to extract.

Return type:

SprayData

classmethod all_from_QG_glider(glider_df, meta)

Build a list of SprayData objects, one per glider mission ID.

Parameters:

• glider_df (pd.DataFrame) – Glider velocity output (all gliders).

• meta (dict) – Metadata dict.

Return type:

list of SprayData

rstr_settings()

Return the representation of the CTDData object

class profiler.gliderdata.SlocumData(datafile: str, dataset: str, in_field: bool = False, binned: bool = False)

Bases: ProfilerData

Class to hold a full, standard Slocum glider

platform: str = 'Slocum'

scalar_keys: list = []

loader_dict = {'s': 'salinity', 't': 'temperature'}

__init__(datafile: str, dataset: str, in_field: bool = False, binned: bool = False)

in_field: bool = None

class profiler.gliderdata.SeagliderData(datafile: str, dataset: str, in_field: bool = False, binned: bool = False)

Bases: ADCPData

Class to hold a full, standard Seaglider glider

platform: str = 'Seaglider'

scalar_keys: list = []

loader_dict = {'s': 'S', 't': 'T'}

__init__(datafile: str, dataset: str, in_field: bool = False, binned: bool = False)

in_field: bool = None

class profiler.gliderdata.SprayData(datafile: str, dataset: str, in_field: bool = False)

Bases: ADCPData

Class to hold a full, standard Spray

dtype = 'Spray'

base_key: str = None

scalar_keys: list = []

__init__(datafile: str, dataset: str, in_field: bool = False)

in_field: bool = None

classmethod from_QG_glider(glider_df, meta, missid)

Build a SprayData instance from QG-sampled glider velocities.

Unlike DrifterData.from_QG_trajectory(), this uses the pre-sampled u_qg, v_qg columns directly — no finite differencing.

Parameters:

• glider_df (pd.DataFrame) – Glider velocity output with columns: x, y, time, missid, x_m, y_m, u_qg, v_qg

• meta (dict) – Metadata dict (must contain ‘dx’, ‘nx’).

• missid (int) – Glider mission ID to extract.

Return type:

SprayData

classmethod all_from_QG_glider(glider_df, meta)

Build a list of SprayData objects, one per glider mission ID.

Parameters:

• glider_df (pd.DataFrame) – Glider velocity output (all gliders).

• meta (dict) – Metadata dict.

Return type:

list of SprayData

rstr_settings()

Return the representation of the CTDData object

Solo Float

Simple Class to hold glider data

class profiler.floatdata.SoloData(datafile: str, dataset: str, in_field: bool = False)

Bases: ProfilerData

Class to hold a Solo float

platform: str = 'Solo'

scalar_keys: list = []

raw_loader()

Load raw data from a file

Parameters:

datafile (str) – The path to the data file.

Returns:

The data dictionary and the dictionary of arrays.

Return type:

dict, dict

__init__(datafile: str, dataset: str, in_field: bool = False)

in_field: bool = None

base_key: str = None

class profiler.floatdata.FlipData(datafile: str, dataset: str, in_field: bool = False)

Bases: ProfilerData

Class to hold a full, standard Spray

platform: str = 'Flip'

scalar_keys: list = []

raw_loader()

Load raw data from a file

Parameters:

datafile (str) – The path to the data file.

Returns:

The data dictionary and the dictionary of arrays.

Return type:

dict, dict

__init__(datafile: str, dataset: str, in_field: bool = False)

in_field: bool = None

base_key: str = None

class profiler.floatdata.EMApexData(datafile: str, dataset: str, in_field: bool = False)

Bases: SoloData

Class to hold a full, standard EM Apex

platform: str = 'EMApex'

in_field: bool = None

base_key: str = None

scalar_keys: list = []

class profiler.floatdata.AltoData(datafile: str, dataset: str, in_field: bool = False)

Bases: SoloData

Class to hold a full, standard Alto

platform: str = 'Alto'

in_field: bool = None

base_key: str = None

scalar_keys: list = []

class profiler.floatdata.SoloData(datafile: str, dataset: str, in_field: bool = False)

Bases: ProfilerData

Class to hold a Solo float

platform: str = 'Solo'

scalar_keys: list = []

raw_loader()

Load raw data from a file

Parameters:

datafile (str) – The path to the data file.

Returns:

The data dictionary and the dictionary of arrays.

Return type:

dict, dict

__init__(datafile: str, dataset: str, in_field: bool = False)

in_field: bool = None

base_key: str = None

EM-APEX Float

class profiler.floatdata.EMApexData(datafile: str, dataset: str, in_field: bool = False)

Bases: SoloData

Class to hold a full, standard EM Apex

platform: str = 'EMApex'

in_field: bool = None

base_key: str = None

scalar_keys: list = []

VMP

Simple Class to hold VMP data

class profiler.vmpdata.VMPData(datafile: str, dataset: str, in_field: bool = False, binned: bool = False)

Bases: ProfilerData

Class to hold a standard VMP dataset

platform: str = 'VMP'

scalar_keys: list = []

__init__(datafile: str, dataset: str, in_field: bool = False, binned: bool = False)

in_field: bool = None

base_key: str = None

class profiler.vmpdata.VMPData(datafile: str, dataset: str, in_field: bool = False, binned: bool = False)

Bases: ProfilerData

Class to hold a standard VMP dataset

platform: str = 'VMP'

scalar_keys: list = []

__init__(datafile: str, dataset: str, in_field: bool = False, binned: bool = False)

in_field: bool = None

base_key: str = None

Triaxus

Simple Class to hold Triaxus data

class profiler.triaxusdata.TriaxusData(datafile: str, dataset: str, in_field: bool = False, binned: bool = False)

Bases: ADCPData

Class to hold a standard Triaxus dataset

platform: str = 'Triaxus'

scalar_keys: list = []

__init__(datafile: str, dataset: str, in_field: bool = False, binned: bool = False)

in_field: bool = None

base_key: str = None

class profiler.triaxusdata.TriaxusData(datafile: str, dataset: str, in_field: bool = False, binned: bool = False)

Bases: ADCPData

Class to hold a standard Triaxus dataset

platform: str = 'Triaxus'

scalar_keys: list = []

__init__(datafile: str, dataset: str, in_field: bool = False, binned: bool = False)

in_field: bool = None

base_key: str = None