helikite.classes.output_schemas

Attributes

`flag_pollution_cpc`
`flag_pollution_cpc_ground`
`flag_hovering`
`flag_cloud_mcda`
`shade_pollution_cpc`
`shade_pollution_cpc_ground`
`shade_hovering`
`shade_cloud_mcda`
`shade_filter`

Classes

`Level`	Processing level identifiers.
`Flag`	Definition of a processing flag.
`FlightProfileVariable`	Configuration for plotting a flight profile variable.
`FlightProfileVariableShade`	Configuration for shaded regions in flight profile and size distribution plots.
`OutputSchema`	Campaign-specific output configuration.
`OutputSchemas`	Registry and factory for predefined output schemas.

Functions

`_build_colors_defaultdict`()
`filter_shade_condition`(→ pandas.Series)

Module Contents

helikite.classes.output_schemas._build_colors_defaultdict()

class helikite.classes.output_schemas.Level(*args, **kwds)

Bases: enum.Enum

Processing level identifiers.

LEVEL0 = 0

LEVEL1 = 1

LEVEL1_5 = 1.5

LEVEL2 = 2

class helikite.classes.output_schemas.Flag

Definition of a processing flag.

A flag describes a condition derived from instrument data that marks specific flight or environmental states.

flag_name: str: Name of the flag column in output data.

column_name: str: Source column used to compute the flag.

params: helikite.processing.post.fda.FDAParameters: FDA parameters controlling flag detection.

y_scale: str = 'log': Plotting scale hint for visualization.

__str__()

class helikite.classes.output_schemas.FlightProfileVariable

Configuration for plotting a flight profile variable.

Defines how a variable is displayed in vertical flight profile plots.

column_name: str: Name of the data column to plot.

shade_flags: list[str] = []: Flags for which background shading should be applied.

plot_kwargs: dict: Matplotlib plotting arguments.

alpha_ascent: float = 1.0: Opacity for ascent segment.

alpha_descent: float = 0.5: Opacity for descent segment.

x_min: numbers.Number | None = None: Lower x-axis bound.

x_max: numbers.Number | None = None: Upper x-axis bound.

x_divider: numbers.Number | None = None: Tick spacing hint.

x_label: str | None = None: Axis label override.

class helikite.classes.output_schemas.FlightProfileVariableShade

Configuration for shaded regions in flight profile and size distribution plots.

name: str: Source column used to compute shaded regions.

condition: Callable[[Level, pandas.Series], pandas.Series]: Predicate function that receives a column value and returns True if the corresponding row should be shaded, False otherwise.

label: str: Legend label.

span_kwargs: dict: Matplotlib plotting arguments for shaded spans.

line_name: str | None = None: Optional column name for overlay line to plot in size distribution plot together with the shaded regions.

line_kwargs: dict | None = None: Matplotlib plotting arguments for overlay line

helikite.classes.output_schemas.flag_pollution_cpc

helikite.classes.output_schemas.flag_pollution_cpc_ground

helikite.classes.output_schemas.flag_hovering

helikite.classes.output_schemas.flag_cloud_mcda

helikite.classes.output_schemas.shade_pollution_cpc

helikite.classes.output_schemas.shade_pollution_cpc_ground

helikite.classes.output_schemas.shade_hovering

helikite.classes.output_schemas.shade_cloud_mcda

helikite.classes.output_schemas.filter_shade_condition(level: Level, values: pandas.Series) → pandas.Series

helikite.classes.output_schemas.shade_filter

class helikite.classes.output_schemas.OutputSchema

Campaign-specific output configuration.

Defines instruments, plotting styles, and metadata expectations for a campaign.

campaign: str | None: Campaign name

instruments: list[helikite.instruments.Instrument]: List of instruments whose columns should be present in the output dataframe.

colors: dict[helikite.instruments.Instrument | str, str]: [Instrument|column]-to-color dictionary for the consistent across a campaign plotting.

reference_instrument_candidates: list[helikite.instruments.Instrument]: Reference instrument candidates for the automatic instruments detection

flight_profile_variables: list[FlightProfileVariable] = []: List of flight profile variables to plot.

flight_profile_shades: list[FlightProfileVariableShade]

flags: list[Flag]: List of flags which should be present in the output dataframe.

cpc_mode: str | None = None: CPC measurement mode for this campaign (“V” vertical, “S” surface). Drives which CPC columns are produced during column enumeration. Live runs read the mode from the flight metadata instead.

column_renames: dict[str, str]: Campaign-specific final-column renames, applied last so a campaign can pin its canonical output names (e.g. P/TEMP instead of Pressure/Temperature).

reorder_final_columns: bool = True: Whether level 1.5 applies the standardised final-column reorder/whitelist. Legacy campaigns disable it to keep their canonical column set.

class helikite.classes.output_schemas.OutputSchemas

Registry and factory for predefined output schemas.

Provides access to campaign configurations and allows runtime registration of custom schemas.

_REGISTRY: dict[str, OutputSchema]

ORACLES_24_25

ORACLES_25_26

TURTMANN

ALL

classmethod from_name(name: str) → OutputSchema

Retrieve a schema by name.

Parameters:: name – Schema identifier (case-insensitive).
Returns:: OutputSchema instance.
Raises:: KeyError – If schema is not registered.

classmethod _register_builtin()

classmethod register(name: str, schema: OutputSchema, *, overwrite: bool = False)

Register a custom output schema.

Parameters:

name – Schema identifier.
schema – Schema instance.
overwrite – Whether to replace an existing schema in case of conflict.

Raises:

ValueError – If schema exists and overwrite is False.

classmethod keys()

List registered schema names.

Returns:: Iterable of schema identifiers.