You're reading the documentation for a development version. For the latest released version, please have a look at v0.5.

Dataset structure

The dataset is an essential concept of the ASpecD framework and in turn the cwepr package, as it abstracts the different vendor formats and combines both, numerical data and metadata, in an easily accessible way. Even more, the general structure of a dataset allows to compare data of entirely different origin (read: spectroscopic method), as long as their axes are compatible.

Developers of the cwepr package frequently need to get an overview of the structure of the dataset and its different subclasses, namely the ExperimentalDataset and CalculatedDataset. Whereas the API documentation of each class, cwepr.dataset.ExperimentalDataset and cwepr.dataset.CalculatedDataset, provides a lot of information, a simple and accessible presentation of the dataset structure is often what is needed.

Therefore, the structure of each of the dataset classes is provided below in YAML format, automatically generated from the actual source code.

Experimental dataset

Entity containing both, numerical data as well as the corresponding metadata that are specific for the cw-EPR method. For implementation details, see the API documentation of cwepr.dataset.ExperimentalDataset and cwepr.dataset.ExperimentalDatasetMetadata.

data:
  calculated: false
  data:
    type: numpy.ndarray
    dtype: float64
    array: []
  axes:
  - quantity: ''
    symbol: ''
    unit: ''
    label: ''
    values:
      type: numpy.ndarray
      dtype: float64
      array: []
  - quantity: ''
    symbol: ''
    unit: ''
    label: ''
    values:
      type: numpy.ndarray
      dtype: float64
      array: []
metadata:
  measurement:
    label: ''
    start: null
    end: null
    purpose: ''
    operator: ''
    labbook_entry: ''
  sample:
    description: ''
    solvent: ''
    preparation: ''
    tube: ''
    name: ''
    id: null
    loi: ''
  temperature_control:
    cryostat: ''
    cryogen: ''
    temperature:
      unit: ''
      dimension: ''
      name: ''
      value: 0.0
    controller: ''
  experiment:
    type: ''
    runs: null
    variable_parameter: ''
    increment: null
    harmonic: null
  spectrometer:
    model: ''
    software: ''
  magnetic_field:
    start:
      unit: ''
      dimension: ''
      name: ''
      value: 0.0
    stop:
      unit: ''
      dimension: ''
      name: ''
      value: 0.0
    sweep_width:
      unit: ''
      dimension: ''
      name: ''
      value: 0.0
    points: 0
    field_probe_type: ''
    field_probe_model: ''
    sequence: ''
    controller: ''
    power_supply: ''
  bridge:
    model: ''
    controller: ''
    attenuation:
      unit: ''
      dimension: ''
      name: ''
      value: 0.0
    power:
      unit: ''
      dimension: ''
      name: ''
      value: 0.0
    detection: ''
    frequency_counter: ''
    mw_frequency:
      unit: ''
      dimension: ''
      name: ''
      value: 0.0
    q_value: null
  signal_channel:
    model: ''
    modulation_amplifier: ''
    accumulations: 0
    modulation_frequency:
      unit: ''
      dimension: ''
      name: ''
      value: 0.0
    modulation_amplitude:
      unit: ''
      dimension: ''
      name: ''
      value: 0.0
    receiver_gain:
      unit: ''
      dimension: ''
      name: ''
      value: 0.0
    conversion_time:
      unit: ''
      dimension: ''
      name: ''
      value: 0.0
    time_constant:
      unit: ''
      dimension: ''
      name: ''
      value: 0.0
    phase:
      unit: ''
      dimension: ''
      name: ''
      value: 0.0
    offset: 0.0
  probehead:
    type: ''
    model: ''
    coupling: ''
  metadata_modifications: []
history: []
analyses: []
annotations: []
representations: []
id: ''
label: ''
references: []
tasks: []
_origdata:
  calculated: false
  data:
    type: numpy.ndarray
    dtype: float64
    array: []
  axes:
  - quantity: ''
    symbol: ''
    unit: ''
    label: ''
    values:
      type: numpy.ndarray
      dtype: float64
      array: []
  - quantity: ''
    symbol: ''
    unit: ''
    label: ''
    values:
      type: numpy.ndarray
      dtype: float64
      array: []
_package_name: cwepr
_history_pointer: -1

Calculated dataset

Entity consisting of calculated data and corresponding metadata. For implementation details, see the API documentation of cwepr.dataset.CalculatedDataset.

data:
  calculated: true
  data:
    type: numpy.ndarray
    dtype: float64
    array: []
  axes:
  - quantity: ''
    symbol: ''
    unit: ''
    label: ''
    values:
      type: numpy.ndarray
      dtype: float64
      array: []
  - quantity: ''
    symbol: ''
    unit: ''
    label: ''
    values:
      type: numpy.ndarray
      dtype: float64
      array: []
metadata:
  calculation:
    type: ''
    parameters: {}
history: []
analyses: []
annotations: []
representations: []
id: ''
label: ''
references: []
tasks: []
_origdata:
  calculated: true
  data:
    type: numpy.ndarray
    dtype: float64
    array: []
  axes:
  - quantity: ''
    symbol: ''
    unit: ''
    label: ''
    values:
      type: numpy.ndarray
      dtype: float64
      array: []
  - quantity: ''
    symbol: ''
    unit: ''
    label: ''
    values:
      type: numpy.ndarray
      dtype: float64
      array: []
_package_name: cwepr
_history_pointer: -1