Summary

The hallmd.data package contains a folder for each unique thruster. The experimental data for each thruster is further divided by folders for each individual paper or reference. The raw experimental data is contained within these folders in any arbitrary format (hdf4, json, csv, etc.). Each set of raw experimental data should come with a dataloader.py file that reads from the raw data into standardized Python objects. Any additional documentation for the datasets is encouraged (e.g. citations, descriptions, summaries, etc.) and can be included in the data folders.

Thrusters

• SPT-100 - currently the only available thruster.

Top-level loader.py

This module provides high-level convenience functions for loading data for specific thrusters. If you plan to add experimental data for a new thruster, this would be a good location for a wrapper function to load this data.

loader.py

Module for loading experimental data for specific thrusters.

Includes

• spt100_data() - loads data for the SPT-100

Loading raw data

Raw data is loaded as best as possible into a standard format from any raw data source (.csv, .json, .hdf, etc.). The raw data files are included where possible along with wrapper Python dataloader functions that manage prepping the standard format. When adding new data to the repository, create a new folder for each thruster and always include corresponding dataloader.py files. You can then add top-level loaders for thrusters like spt100_data() here.

The standard data format

Data from a single experiment is loaded as best as possible into a Python dict with four fields: [x, y, loc, var_y] as explained in the example below. The experimental operating conditions x should be framed in the same units and format as any of your models would expect. Likewise, the measurements y should be directly comparable to the predictions of your models. loc is optional, but should be used when your data has spatial or temporal dependence (use loc in these cases to specify the Cartesian, spherical, etc. coordinates where the measurements were taken). var_y summarizes experimental noise in terms of additive Gaussian white noise with this variance.

data = dict(x=x,  # `(N, x_dim)` `np.ndarray` with `x_dim` experimental operating conditions for `N` data points
            y=y,  # `(N, y_dim)` `np.ndarray` with measurements of `y_dim` QoIs, corresponding to the `N` samples
            loc=loc,      # `(N, loc_dim)`, array with the `loc_dim` coordinates where the QoIs were measured
            var_y=var_y,  # `(N, y_dim)`, array with the experimental noise variance for all measurements
            )

spt100_data(qois=None)

Return a dict with experimental data for each specified quantity for the SPT-100.

PARAMETER	DESCRIPTION
qois	a list specifying the experimental data to return, must be in ['V_cc', 'T', 'uion', 'jion'] TYPE: list[str] DEFAULT: None

RETURNS	DESCRIPTION
dict[str:list[ExpData]]	map of qoi->data, where data is a list of experimental data sets

Source code in src/hallmd/data/loader.py

def spt100_data(qois: list[str] = None) -> dict[str: list[ExpData]]:
    """Return a dict with experimental data for each specified quantity for the SPT-100.

    :param qois: a list specifying the experimental data to return, must be in `['V_cc', 'T', 'uion', 'jion']`
    :returns: map of `qoi->data`, where `data` is a list of experimental data sets
    """
    if qois is None:
        qois = ['V_cc', 'T', 'uion', 'jion', 'I_D']
    exp_data = dict()

    # Load Vcc data
    if 'V_cc' in qois:
        from .spt100.diamant2014.dataloader import load_vcc
        exp_data['V_cc'] = [load_vcc()]

    # Load thrust data
    if 'T' in qois:
        from .spt100.diamant2014.dataloader import load_thrust as thrust1
        from .spt100.sankovic1993.dataloader import load_thrust as thrust2
        exp_data['T'] = [thrust1(), thrust2()]

    # Load discharge current data
    if 'I_D' in qois:
        from .spt100.sankovic1993.dataloader import load_discharge_current
        exp_data['I_D'] = [load_discharge_current()]

    # Load ion velocity data
    if 'uion' in qois:
        from .spt100.macdonald2019.dataloader import load_uion
        exp_data['uion'] = [load_uion()]

    # Load ion velocity data
    if 'jion' in qois:
        from .spt100.diamant2014.dataloader import load_jion
        exp_data['jion'] = [load_jion()]

    return exp_data