Schemas

The schemas module holds wire-format message types: the catalog/observation interchange shapes and the CCSDS Navigation Data Messages.

keplime parses and serializes three CCSDS message types in both the KVN (KEY = value) and XML (NDM/XML) encodings, mapping each to and from keplime's native types:

OMM — Orbit Mean-Elements Message (CCSDS 502.0-B). Round-trips losslessly to a TLE via OMM.to_tle / OMM.from_tle. Carries the SGP4 / SGP4-XP mean elements and catalog metadata (OMMMetadata, OMMMeanElements, OMMTLEParameters).
OEM — Orbit Ephemeris Message (CCSDS 502.0-B). Maps one Ephemeris per segment via OEM.to_ephemerides / OEM.from_ephemeris, with optional covariance records (OEMSegment, OEMMetadata, OEMCovarianceRecord).
CDM — Conjunction Data Message (CCSDS 508.0-B). CDM.from_conjunction builds a standard-conformant message from a computed encounter (miss distance, RTN relative state, RTN object covariances); the object metadata (CDMObjectData, CDMRelativeMetadata, CDMODParameters, CDMAdditionalParameters) is then filled in before emit.

Each message exposes a uniform codec surface:

Method	Purpose
`from_kvn(text)`	Parse the KVN encoding.
`from_xml(text)`	Parse the XML (NDM/XML) encoding.
`from_str_any(text)`	Parse either encoding, sniffing XML versus KVN.
`from_file(path)`	Read a file, sniffing the encoding by content.
`to_kvn()`	Serialize to KVN.
`to_xml()`	Serialize to XML.

Units

In-memory structs hold keplime-native units (angles in radians, lengths in km); CCSDS unit conversion (degrees, meters) happens only at the read/write boundary. The shared ODM header is NDMHeader; CDM carries its own CDMHeader and uses UTC for all epochs.

The CCSDS enums — MeanElementTheory, InterpolationMethod, CDMManeuverable, CDMCovarianceMethod — are documented under Enums.

API reference

`schemas`

`CDM`

A CCSDS Conjunction Data Message.

Build the emit path with from_conjunction, customize the object metadata, then to_kvn. Parse external CDMs with from_kvn / from_file.

Attributes:

Name	Type	Description
`header`	`CDMHeader`	CDM header.
`relative_metadata`	`CDMRelativeMetadata`	Conjunction geometry and Pc.
`object1`	`CDMObjectData`	Object 1 data.
`object2`	`CDMObjectData`	Object 2 data.

`header` `property`

CDM header.

`from_conjunction(header, tca, state1, state2, covariance1, covariance2, collision_probability=None)` `staticmethod`

Builds a CDM from a computed conjunction (the emit path).

Both states must be at TCA in the same inertial frame. The miss distance, relative speed, and object-1-RTN relative position/velocity are computed; each covariance is converted to RTN against its own object's state. Object metadata is filled with neutral defaults.

Parameters:

Name	Type	Description	Default
`header`	`CDMHeader`	The CDM header.	required
`tca`	`ModifiedJulianDate`	Time of closest approach [UTC].	required
`state1`	`CartesianState`	Object 1 state at TCA [inertial; km, km/s].	required
`state2`	`CartesianState`	Object 2 state at TCA [same frame].	required
`covariance1`	`CovarianceMatrix`	Object 1 covariance.	required
`covariance2`	`CovarianceMatrix`	Object 2 covariance.	required
`collision_probability`	`float \| None`	Optional Pc to record.	`None`

Returns:

Type	Description
`CDM`	A CDM ready for `to_kvn`.

Raises:

Type	Description
`ValueError`	If the states are not in the same frame, a state lacks a velocity, a covariance cannot be rotated to RTN, or the frame has no CDM label.

`from_file(path)` `staticmethod`

Reads a CDM from a KVN file.

Parameters:

Name	Type	Description	Default
`path`	`str`	Path to a KVN CDM file.	required

Returns:

Type	Description
`CDM`	The parsed CDM.

Raises:

Type	Description
`ValueError`	If the file cannot be read or fails to parse.

`from_kvn(text)` `staticmethod`

Parses a CDM from its KVN text encoding.

Parameters:

Name	Type	Description	Default
`text`	`str`	The CDM KVN document.	required

Returns:

Type	Description
`CDM`	The parsed CDM.

Raises:

Type	Description
`ValueError`	On any syntax error, missing required keyword, bad epoch, unsupported frame, or inconsistent covariance.

`from_str_any(text)` `staticmethod`

Parses a CDM from either encoding, sniffing XML versus KVN.

Parameters:

Name	Type	Description	Default
`text`	`str`	A CDM in XML or KVN.	required

Returns:

Type	Description
`CDM`	The parsed CDM.

Raises:

Type	Description
`ValueError`	On any parse failure.

`from_xml(text)` `staticmethod`

Parses a CDM from its XML (NDM/XML) encoding.

Parameters:

Name	Type	Description	Default
`text`	`str`	The CDM XML document.	required

Returns:

Type	Description
`CDM`	The parsed CDM.

Raises:

Type	Description
`ValueError`	On malformed XML or any parse-contract violation.

`to_kvn()`

Serializes this CDM to its KVN text encoding.

Returns:

Type	Description
`str`	The CDM as a KVN string (trailing newline).

Raises:

Type	Description
`ValueError`	If an object's state frame has no CCSDS emit label or a covariance is not at least 6x6.

`to_xml()`

Serializes this CDM to its XML (NDM/XML) encoding.

Returns:

Type	Description
`str`	The CDM as an XML string (with prolog, trailing newline).

Raises:

Type	Description
`ValueError`	If an object's state frame has no CCSDS emit label or a covariance is not at least 6x6.

`CDMAdditionalParameters`

CDM additional object-property parameters block (all optional; m-based).

Attributes:

Name	Type	Description
`area_pc`	`float \| None`	`AREA_PC` [m**2].
`cd_area_over_mass`	`float \| None`	`CD_AREA_OVER_MASS` [m**2/kg].
`cr_area_over_mass`	`float \| None`	`CR_AREA_OVER_MASS` [m**2/kg].
`thrust_acceleration`	`float \| None`	`THRUST_ACCELERATION` [m/s**2].
`sedr`	`float \| None`	`SEDR` [W/kg].

`init()`

Creates an empty additional-parameters block; set fields as needed.

`CDMHeader`

CDM header block (all CDM epochs are UTC).

Attributes:

Name	Type	Description
`comments`	`list[str]`	`COMMENT` lines.
`message_version`	`str`	`CCSDS_CDM_VERS` (e.g. `"1.0"`).
`creation_date`	`ModifiedJulianDate`	`CREATION_DATE` [UTC].
`originator`	`str`	`ORIGINATOR`.
`message_for`	`str \| None`	`MESSAGE_FOR`.
`message_id`	`str`	`MESSAGE_ID`.

`creation_date` `property`

CREATION_DATE [UTC].

`message_version` `property`

CCSDS_CDM_VERS value, verbatim (e.g. "1.0").

`init(message_version, creation_date, originator, message_id, comments=..., message_for=None)`

Creates a CDM header.

Parameters:

Name	Type	Description	Default
`message_version`	`str`	`CCSDS_CDM_VERS` (`"1.0"`).	required
`creation_date`	`ModifiedJulianDate`	`CREATION_DATE` [UTC].	required
`originator`	`str`	`ORIGINATOR`.	required
`message_id`	`str`	`MESSAGE_ID`.	required
`comments`	`list[str]`	Optional header comments (default empty).	`...`
`message_for`	`str \| None`	Optional `MESSAGE_FOR`.	`None`

`CDMODParameters`

CDM orbit-determination parameters block (all optional).

Attributes:

Name	Type	Description
`time_lastob_start`	`ModifiedJulianDate \| None`	`TIME_LASTOB_START`.
`time_lastob_end`	`ModifiedJulianDate \| None`	`TIME_LASTOB_END`.
`recommended_od_span`	`float \| None`	`RECOMMENDED_OD_SPAN` [days].
`actual_od_span`	`float \| None`	`ACTUAL_OD_SPAN` [days].
`obs_available`	`int \| None`	`OBS_AVAILABLE`.
`obs_used`	`int \| None`	`OBS_USED`.
`tracks_available`	`int \| None`	`TRACKS_AVAILABLE`.
`tracks_used`	`int \| None`	`TRACKS_USED`.
`residuals_accepted`	`float \| None`	`RESIDUALS_ACCEPTED` [%].
`weighted_rms`	`float \| None`	`WEIGHTED_RMS`.

`init()`

Creates an empty OD-parameters block; set fields as needed.

`CDMObjectData`

CDM per-object data: metadata, OD/additional parameters, state, covariance.

The state, covariance, and reference frame are set by CDM.from_conjunction; the metadata fields are settable.

Attributes:

Name	Type	Description
`object_designator`	`str`	`OBJECT_DESIGNATOR`.
`catalog_name`	`str`	`CATALOG_NAME`.
`object_name`	`str`	`OBJECT_NAME`.
`international_designator`	`str`	`INTERNATIONAL_DESIGNATOR`.
`object_type`	`str \| None`	`OBJECT_TYPE`.
`operator_organization`	`str \| None`	`OPERATOR_ORGANIZATION`.
`ephemeris_name`	`str`	`EPHEMERIS_NAME`.
`covariance_method`	`CDMCovarianceMethod`	`COVARIANCE_METHOD`.
`maneuverable`	`CDMManeuverable`	`MANEUVERABLE`.
`reference_frame`	`ReferenceFrame`	`REF_FRAME` of the state.
`od_parameters`	`CDMODParameters \| None`	OD-parameters block.
`additional_parameters`	`CDMAdditionalParameters \| None`	Additional block.
`state`	`CartesianState`	State at TCA [km, km/s].
`covariance`	`CovarianceMatrix`	RTN (Relative) covariance [km**2].

`covariance` `property`

RTN (Relative) covariance [km**2].

`reference_frame` `property`

REF_FRAME of the state.

`state` `property`

State at TCA [km, km/s].

`CDMRelativeMetadata`

CDM relative metadata: the conjunction geometry and Pc.

The geometry fields are computed by CDM.from_conjunction; the screening and Pc-method fields are settable.

Attributes:

Name	Type	Description
`comments`	`list[str]`	`COMMENT` lines.
`tca`	`ModifiedJulianDate`	`TCA` [UTC].
`miss_distance`	`float`	`MISS_DISTANCE` [km].
`relative_speed`	`float \| None`	`RELATIVE_SPEED` [km/s].
`collision_probability`	`float \| None`	`COLLISION_PROBABILITY`.
`collision_probability_method`	`str \| None`	`COLLISION_PROBABILITY_METHOD`.

`miss_distance` `property`

MISS_DISTANCE [km].

`relative_speed` `property`

RELATIVE_SPEED [km/s], or None.

`tca` `property`

TCA [UTC].

`NDMHeader`

Common ODM header block shared by OEM and OMM messages.

CDM carries its own header. Construct one to supply to OMM.from_tle. The ODM v3 optional fields (message_id, classification) are None for v1/v2 messages.

Attributes:

Name	Type	Description
`comments`	`list[str]`	`COMMENT` lines at the top of the message.
`message_version`	`str`	`CCSDS_<MSG>_VERS` value, verbatim (e.g. `"2.0"`).
`creation_date`	`ModifiedJulianDate`	`CREATION_DATE` [UTC].
`originator`	`str`	`ORIGINATOR`.
`message_id`	`str \| None`	`MESSAGE_ID` (ODM v3).
`classification`	`str \| None`	`CLASSIFICATION` (ODM v3).

`init(message_version, creation_date, originator, comments=..., message_id=None, classification=None)`

Creates an ODM header.

Parameters:

Name	Type	Description	Default
`message_version`	`str`	`CCSDS_<MSG>_VERS` value (e.g. `"2.0"`).	required
`creation_date`	`ModifiedJulianDate`	`CREATION_DATE` [UTC].	required
`originator`	`str`	`ORIGINATOR`.	required
`comments`	`list[str]`	Optional header comments (default empty).	`...`
`message_id`	`str \| None`	Optional `MESSAGE_ID` (ODM v3).	`None`
`classification`	`str \| None`	Optional `CLASSIFICATION` (ODM v3).	`None`

`OEM`

A CCSDS Orbit Ephemeris Message.

One or more segments, each a tabulated trajectory. Parse with from_kvn / from_file, build from an Ephemeris with from_ephemeris, and map each segment back to an Ephemeris with to_ephemerides.

Attributes:

Name	Type	Description
`header`	`NDMHeader`	Common ODM header.
`segments`	`list[OEMSegment]`	One or more ephemeris segments.

`header` `property`

Common ODM header.

`segments` `property`

One or more ephemeris segments.

`covariance_at_epoch(epoch)`

Returns the covariance record nearest at-or-before epoch.

Parameters:

Name	Type	Description	Default
`epoch`	`ModifiedJulianDate`	The query epoch.	required

Returns:

Type	Description
`OEMCovarianceRecord \| None`	The nearest record at-or-before `epoch`, or `None` if every
`OEMCovarianceRecord \| None`	record is after it.

`from_ephemeris(ephemeris, frame, time_system, header, object_id)` `staticmethod`

Builds a single-segment OEM from an Ephemeris.

States are emitted verbatim, each converted from the ephemeris's native TEME to frame (ITRF EOP-guarded). Acceleration columns are emitted iff every state carries acceleration.

Parameters:

Name	Type	Description	Default
`ephemeris`	`Ephemeris`	The source ephemeris (TEME).	required
`frame`	`ReferenceFrame`	Frame to express the emitted states in.	required
`time_system`	`TimeSystem`	Time system to tag the emitted epochs with.	required
`header`	`NDMHeader`	The ODM header to attach.	required
`object_id`	`str`	The international designator for `OBJECT_ID`.	required

Returns:

Type	Description
`OEM`	A single-segment OEM.

Raises:

Type	Description
`ValueError`	If the ephemeris has no states, `frame` has no CCSDS label, or a state cannot be converted to `frame`.

`from_file(path)` `staticmethod`

Reads an OEM from a KVN file.

Parameters:

Name	Type	Description	Default
`path`	`str`	Path to a KVN OEM file.	required

Returns:

Type	Description
`OEM`	The parsed OEM.

Raises:

Type	Description
`ValueError`	If the file cannot be read or fails to parse.

`from_kvn(text)` `staticmethod`

Parses an OEM from its KVN text encoding.

Parameters:

Name	Type	Description	Default
`text`	`str`	The OEM KVN document.	required

Returns:

Type	Description
`OEM`	The parsed OEM.

Raises:

Type	Description
`ValueError`	On any syntax error, missing required keyword, bad epoch or state row, or unsupported frame / time system.

`from_str_any(text)` `staticmethod`

Parses an OEM from either encoding, sniffing XML versus KVN.

Parameters:

Name	Type	Description	Default
`text`	`str`	An OEM in XML or KVN.	required

Returns:

Type	Description
`OEM`	The parsed OEM.

Raises:

Type	Description
`ValueError`	On any parse failure.

`from_xml(text)` `staticmethod`

Parses an OEM from its XML (NDM/XML) encoding.

Parameters:

Name	Type	Description	Default
`text`	`str`	The OEM XML document.	required

Returns:

Type	Description
`OEM`	The parsed OEM.

Raises:

Type	Description
`ValueError`	On malformed XML or any parse-contract violation.

`to_ephemerides()`

Maps each segment to an Ephemeris (states converted to TEME).

Returns:

Type	Description
`list[Ephemeris]`	One Ephemeris per segment, in order.

Raises:

Type	Description
`ValueError`	If a segment's center is not EARTH, a state cannot be converted to TEME (including ITRF epochs outside EOP coverage), or a segment has no states.

`to_kvn()`

Serializes this OEM to its KVN text encoding.

Returns:

Type	Description
`str`	The OEM as a KVN string (trailing newline).

Raises:

Type	Description
`ValueError`	If a segment or covariance frame has no CCSDS emit label.

`to_xml()`

Serializes this OEM to its XML (NDM/XML) encoding.

Returns:

Type	Description
`str`	The OEM as an XML string (with prolog, trailing newline).

Raises:

Type	Description
`ValueError`	If a segment or covariance frame has no CCSDS emit label.

`OEMCovarianceRecord`

One OEM covariance record: a 6x6 covariance at an epoch.

Attributes:

Name	Type	Description
`epoch`	`ModifiedJulianDate`	The epoch the covariance applies at.
`covariance`	`CovarianceMatrix`	The 6x6 covariance [km-based units].

`covariance` `property`

The 6x6 covariance [km-based units].

`epoch` `property`

The epoch the covariance applies at.

`OEMMetadata`

OEM segment metadata block.

Attributes:

Name	Type	Description
`comments`	`list[str]`	`COMMENT` lines in the segment.
`object_name`	`str`	`OBJECT_NAME`.
`object_id`	`str`	`OBJECT_ID`.
`center_name`	`str`	`CENTER_NAME`; only `EARTH` maps to an Ephemeris.
`reference_frame`	`ReferenceFrame`	`REF_FRAME` of the states.
`ref_frame_epoch`	`ModifiedJulianDate \| None`	`REF_FRAME_EPOCH`.
`time_system`	`TimeSystem`	`TIME_SYSTEM`.
`start_time`	`ModifiedJulianDate`	`START_TIME`.
`useable_start_time`	`ModifiedJulianDate \| None`	`USEABLE_START_TIME`.
`useable_stop_time`	`ModifiedJulianDate \| None`	`USEABLE_STOP_TIME`.
`stop_time`	`ModifiedJulianDate`	`STOP_TIME`.
`interpolation`	`tuple[InterpolationMethod, int] \| None`	`INTERPOLATION` method and `INTERPOLATION_DEGREE`.

`center_name` `property`

CENTER_NAME; only EARTH maps to an Ephemeris.

`comments` `property`

COMMENT lines in the segment.

`interpolation` `property`

INTERPOLATION method and INTERPOLATION_DEGREE, or None.

`object_id` `property`

OBJECT_ID.

`object_name` `property`

OBJECT_NAME.

`ref_frame_epoch` `property`

REF_FRAME_EPOCH, or None.

`reference_frame` `property`

REF_FRAME of the states.

`start_time` `property`

START_TIME.

`stop_time` `property`

STOP_TIME.

`time_system` `property`

TIME_SYSTEM.

`useable_start_time` `property`

USEABLE_START_TIME, or None.

`useable_stop_time` `property`

USEABLE_STOP_TIME, or None.

`OEMSegment`

One OEM segment: metadata, tabulated states, and covariance records.

Attributes:

Name	Type	Description
`metadata`	`OEMMetadata`	Segment metadata.
`states`	`list[CartesianState]`	Tabulated states in the segment's frame.
`covariance_records`	`list[OEMCovarianceRecord]`	Covariance records.

`covariance_records` `property`

Covariance records, in epoch order.

`metadata` `property`

Segment metadata.

`states` `property`

Tabulated states in the segment's frame [km, km/s].

`OMM`

A CCSDS Orbit Mean-Elements Message.

Carries one set of mean orbital elements (the SGP4 elements a TLE encodes) plus catalog metadata. Parse with from_kvn / from_file, build from a TLE with from_tle, and convert back with to_tle. Angles in the mean-element block are radians; MEAN_MOTION stays in rev/day.

Attributes:

Name	Type	Description
`header`	`NDMHeader`	Common ODM header.
`metadata`	`OMMMetadata`	Object identity, frame, time system, theory.
`mean_elements`	`OMMMeanElements`	Mean orbital elements at epoch.
`tle_parameters`	`OMMTLEParameters \| None`	SGP4/SGP4-XP catalog and force-model parameters, when present.
`covariance`	`CovarianceMatrix \| None`	Optional ODM covariance block.
`user_defined`	`list[tuple[str, str]]`	`USER_DEFINED_*` keys preserved verbatim.

`covariance` `property`

Optional ODM covariance block.

`header` `property`

Common ODM header.

`mean_elements` `property`

Mean orbital elements at epoch.

`metadata` `property`

Object identity, frame, time system, theory.

`tle_parameters` `property`

SGP4/SGP4-XP catalog and force-model parameters, when present.

`user_defined` `property`

USER_DEFINED_* keys preserved verbatim.

`from_file(path)` `staticmethod`

Reads an OMM from a KVN file.

Parameters:

Name	Type	Description	Default
`path`	`str`	Path to a KVN OMM file.	required

Returns:

Type	Description
`OMM`	The parsed OMM.

Raises:

Type	Description
`ValueError`	If the file cannot be read or fails to parse.

`from_kvn(text)` `staticmethod`

Parses an OMM from its KVN text encoding.

Parameters:

Name	Type	Description	Default
`text`	`str`	The OMM KVN document.	required

Returns:

Type	Description
`OMM`	The parsed OMM.

Raises:

Type	Description
`ValueError`	On any syntax error, unsupported version, missing required keyword, unit mismatch, bad epoch, or unsupported frame / time system / mean-element theory.

`from_str_any(text)` `staticmethod`

Parses an OMM from either encoding, sniffing XML versus KVN.

Parameters:

Name	Type	Description	Default
`text`	`str`	An OMM in XML or KVN.	required

Returns:

Type	Description
`OMM`	The parsed OMM.

Raises:

Type	Description
`ValueError`	On any parse failure.

`from_tle(tle, header)` `staticmethod`

Builds an OMM from a NORAD TLE.

Parameters:

Name	Type	Description	Default
`tle`	`TLE`	The source TLE.	required
`header`	`NDMHeader`	The ODM header to attach.	required

Returns:

Type	Description
`OMM`	The equivalent OMM (TEME / UTC / EARTH).

Raises:

Type	Description
`ValueError`	If the conversion fails.

`from_xml(text)` `staticmethod`

Parses an OMM from its XML (NDM/XML) encoding.

Parameters:

Name	Type	Description	Default
`text`	`str`	The OMM XML document.	required

Returns:

Type	Description
`OMM`	The parsed OMM.

Raises:

Type	Description
`ValueError`	On malformed XML or any parse-contract violation.

`to_kvn()`

Serializes this OMM to its KVN text encoding.

Returns:

Type	Description
`str`	The OMM as a KVN string (trailing newline).

Raises:

Type	Description
`ValueError`	If the metadata or covariance frame has no CCSDS emit label.

`to_tle()`

Converts this OMM to a NORAD TLE.

Returns:

Type	Description
`TLE`	A TLE at the OMM epoch in TEME.

Raises:

Type	Description
`ValueError`	If `tle_parameters` is absent, the elements give a semi-major axis but no mean motion, the center is not EARTH, the frame is not TEME, the time system is not UTC, or the ephemeris type is not 0/2/4.

`to_xml()`

Serializes this OMM to its XML (NDM/XML) encoding.

Returns:

Type	Description
`str`	The OMM as an XML string (with prolog, trailing newline).

Raises:

Type	Description
`ValueError`	If the metadata or covariance frame has no CCSDS emit label.

`OMMMeanElements`

OMM mean orbital elements at epoch.

Exactly one of mean_motion / semi_major_axis is set. Angles are radians; mean_motion is rev/day.

Attributes:

Name	Type	Description
`epoch`	`ModifiedJulianDate`	`EPOCH` in the metadata time system.
`mean_motion`	`float \| None`	`MEAN_MOTION` [rev/day].
`semi_major_axis`	`float \| None`	`SEMI_MAJOR_AXIS` [km].
`eccentricity`	`float`	`ECCENTRICITY` [dimensionless; 0..1).
`inclination`	`float`	`INCLINATION` [rad].
`ascending_node`	`float`	`RA_OF_ASC_NODE` [rad].
`argument_of_periapsis`	`float`	`ARG_OF_PERICENTER` [rad].
`mean_anomaly`	`float`	`MEAN_ANOMALY` [rad].
`gm`	`float \| None`	`GM` [km3/s2].

`argument_of_periapsis` `property`

ARG_OF_PERICENTER [rad].

`ascending_node` `property`

RA_OF_ASC_NODE [rad].

`eccentricity` `property`

ECCENTRICITY [dimensionless; 0..1).

`epoch` `property`

EPOCH in the metadata time system.

`gm` `property`

GM [km3/s2], or None.

`inclination` `property`

INCLINATION [rad].

`mean_anomaly` `property`

MEAN_ANOMALY [rad].

`mean_motion` `property`

MEAN_MOTION [rev/day], or None.

`semi_major_axis` `property`

SEMI_MAJOR_AXIS [km], or None.

`OMMMetadata`

OMM metadata block: object identity, frame, time system, theory.

Attributes:

Name	Type	Description
`comments`	`list[str]`	`COMMENT` lines in the metadata block.
`object_name`	`str`	`OBJECT_NAME`.
`object_id`	`str`	`OBJECT_ID` (COSPAR designator, e.g. `1998-067A`).
`center_name`	`str`	`CENTER_NAME`; only `EARTH` converts to a TLE.
`reference_frame`	`ReferenceFrame`	`REF_FRAME`; `TEME` for SGP4.
`time_system`	`TimeSystem`	`TIME_SYSTEM`.
`mean_element_theory`	`MeanElementTheory`	`MEAN_ELEMENT_THEORY`.

`center_name` `property`

CENTER_NAME; only EARTH converts to a TLE.

`comments` `property`

COMMENT lines in the metadata block.

`mean_element_theory` `property`

MEAN_ELEMENT_THEORY.

`object_id` `property`

OBJECT_ID (COSPAR international designator).

`object_name` `property`

OBJECT_NAME.

`reference_frame` `property`

REF_FRAME; TEME for SGP4.

`time_system` `property`

TIME_SYSTEM.

`OMMTLEParameters`

OMM optional SGP4/SGP4-XP catalog and force-model parameters.

SGP4 uses bstar; SGP4-XP uses bterm and agom. Per ADR 0020, mean_motion_dot/mean_motion_ddot are round-trip only — propagation does not read them for GP/XP.

Attributes:

Name	Type	Description
`ephemeris_type`	`int`	`EPHEMERIS_TYPE` (0/2 SGP4, 4 SGP4-XP).
`classification`	`Classification`	`CLASSIFICATION_TYPE` (U/C/S).
`norad_cat_id`	`int`	`NORAD_CAT_ID`.
`element_set_no`	`int`	`ELEMENT_SET_NO`.
`rev_at_epoch`	`int`	`REV_AT_EPOCH`.
`bstar`	`float \| None`	`BSTAR` [1/Earth-radii] — SGP4.
`bterm`	`float \| None`	`BTERM` [m**2/kg] — SGP4-XP.
`mean_motion_dot`	`float`	`MEAN_MOTION_DOT` [rev/day**2].
`mean_motion_ddot`	`float \| None`	`MEAN_MOTION_DDOT` [rev/day**3] — SGP4.
`agom`	`float \| None`	`AGOM` [m**2/kg] — SGP4-XP.

`agom` `property`

AGOM [m**2/kg] — SGP4-XP only, or None.

`bstar` `property`

BSTAR [1/Earth-radii] — SGP4 drag term, or None.

`bterm` `property`

BTERM [m**2/kg] — SGP4-XP drag term, or None.

`classification` `property`

CLASSIFICATION_TYPE (U/C/S).

`element_set_no` `property`

ELEMENT_SET_NO.

`ephemeris_type` `property`

EPHEMERIS_TYPE (0/2 SGP4, 4 SGP4-XP).

`mean_motion_ddot` `property`

MEAN_MOTION_DDOT [rev/day**3] — SGP4 only, or None.

`mean_motion_dot` `property`

MEAN_MOTION_DOT [rev/day**2]; round-trip only.

`norad_cat_id` `property`

NORAD_CAT_ID.

`rev_at_epoch` `property`

REV_AT_EPOCH.

`audit_citra_doa(citra_elsets, citra_observations, latest_span, full_span, expected_limits=...)`

Summarize direction-of-arrival (TDOA) residual stats per DOA antenna.

Grouping, dedupe, the count fields, the per-sensor windowing rule, and expected_limits semantics match audit_citra_optical. Per-sensor keys are the DOA primary_antenna_id. Per-sensor stat-block fields: tdoa_bias / tdoa_noise [s] and ingest_delay_bias / ingest_delay_noise [s]. angular / angular_rate are not exposed at this level because DOA observations don't carry pointing data; the unified antenna block (audit_citra_sensors) surfaces them when a sister radar observation provides them.

Parameters:

Name	Type	Description	Default
`citra_elsets`	`list[dict[str, object]]`	List of CITRA elset dicts (same per-element shape as the elset arg of `get_citra_residuals`).	required
`citra_observations`	`list[dict[str, object]]`	List of CITRA DOA observation dicts.	required
`latest_span`	`TimeSpan`	Width of the short window applied to sensors that appear in `expected_limits`. Acts as a cap. Must satisfy `latest_span <= full_span`.	required
`full_span`	`TimeSpan`	Minimum calibration history required for sensors that do not appear in `expected_limits`. Sensors with less than `full_span` of data are omitted from the output; sensors that meet the minimum are calibrated over their entire sample set (no cap).	required
`expected_limits`	`list[dict[str, object]] \| None`	Optional list of per-sensor limit dicts. See `audit_citra_optical` for the full shape.	`...`

Returns:

Type	Description
`list[dict[str, object]]`	List of per-sensor stat blocks (one per DOA antenna that
`list[dict[str, object]]`	produced data and met the calibration minimum, or that is listed
`list[dict[str, object]]`	in `expected_limits`). Each block contains the common fields
`list[dict[str, object]]`	documented on `audit_citra_optical` plus DOA-specific
`list[dict[str, object]]`	measurement fields: `tdoa_bias` / `tdoa_noise` [s] and
`list[dict[str, object]]`	`ingest_delay_bias` / `ingest_delay_noise` [s]. Angular
`list[dict[str, object]]`	fields are not included because DOA observations do not carry
`list[dict[str, object]]`	pointing data.

Raises:

Type	Description
`ValueError`	`latest_span` is greater than `full_span`; or a CITRA record fails to parse.

Per-satellite construction, ephemeris caching, or residual computation failures are logged at WARN and the offending satellite is dropped from the audit; they do not raise.

`audit_citra_optical(citra_elsets, citra_observations, latest_span, full_span, expected_limits=...)`

Summarize optical residual stats per telescope.

Each optical observation is attributed to an elset by matching the observation's satellite_id to the elset's satellite_id. Input elsets that share a satellite_id are deduped by first occurrence; later duplicates are silently dropped. Each observation also carries a sensor identifier (telescope_id for optical), used to break the residual stats out per sensor. Observations whose satellite_id is None are reported as uncorrelated_observation_count under the sensor that produced them and contribute no residual samples. A sensor that produces no usable bias / noise values across any field — e.g., uncorrelated tracks only, with no upstream creation_epoch to populate ingest_delay — is omitted from the output entirely.

Per-sensor window selection driven by expected_limits:

Sensors with an entry in expected_limits are evaluated over the short window [S_last - latest_span, S_last], and the per-sensor status is checked against the supplied bias / noise bounds. latest_span is a cap — even a newly-active sensor with little data still gets a block.
Sensors without an entry in expected_limits (the un-characterized ones) are calibrated over every sample the sensor has produced. full_span here is a minimum required calibration history: if the sensor's S_last - S_first span is less than full_span, the sensor is omitted from the output entirely — there isn't enough baseline to calibrate against. There is no cap on the long-baseline path: a 36-hour query against a 12-hour minimum runs over the full 36 hours.

S_last is the sensor's own latest sample, so a sensor whose data ends earlier than another's still gets evaluated against its own recent activity.

Parameters:

Name	Type	Description	Default
`citra_elsets`	`list[dict[str, object]]`	List of CITRA elset dicts (same per-element shape as the elset arg of `get_citra_residuals`).	required
`citra_observations`	`list[dict[str, object]]`	List of CITRA optical observation dicts.	required
`latest_span`	`TimeSpan`	Width of the short window applied to sensors that appear in `expected_limits`. Acts as a cap. Must satisfy `latest_span <= full_span`.	required
`full_span`	`TimeSpan`	Minimum calibration history required for sensors that do not appear in `expected_limits`. Sensors with less than `full_span` of data are omitted from the output; sensors that meet the minimum are calibrated over their entire sample set (no cap).	required
`expected_limits`	`list[dict[str, object]] \| None`	Optional list of per-sensor limit dicts. Each entry is `{"sensor_id": <sensor_uuid>, "<field>_bias": float, "<field>_noise": float, ...}` (other keys are silently ignored, so the prior audit's output list can be passed back in directly). Missing bias/noise keys mean "do not check that field". Sensors absent from the list go on the calibration (`full_span` minimum) path with `status = "nominal"`.	`...`

Returns:

Type	Description
`list[dict[str, object]]`	List of per-sensor stat blocks (`[{...}, {...}]`). Each
`list[dict[str, object]]`	block contains:
`list[dict[str, object]]`	`id` (str): fresh UUIDv4 identifying this audit record (generated per call). Use this when persisting audit history.
`list[dict[str, object]]`	`sensor_id` (str): the telescope / antenna UUID this audit block is for. Match on this when correlating across runs or providing limits.
`list[dict[str, object]]`	`sensor_type` (str): `"telescope"` or `"antenna"`.
`list[dict[str, object]]`	`audit_type` (str): `"trend"` when this sensor was listed in `expected_limits` (short window, status-checking path) or `"baseline"` when it wasn't (calibration path, full sample set).
`list[dict[str, object]]`	`uncorrelated_observation_count` (int): observations from this sensor in the window with no `satellite_id`.
`list[dict[str, object]]`	`correlated_observation_count` (int): observations from this sensor in the window matched to a deduped elset.
`list[dict[str, object]]`	`observed_satellite_count` (int): distinct correlated `satellite_id` values produced by this sensor in the window. Uncorrelated tracks contribute zero.
`list[dict[str, object]]`	`first_epoch` (str \| None): earliest sample epoch within this sensor's chosen window, ISO 8601 UTC.
`list[dict[str, object]]`	`last_epoch` (str \| None): the sensor's own latest sample epoch, ISO 8601 UTC. Anchors the window thresholds.
`list[dict[str, object]]`	`time_bias` [s], `time_noise` [s], `angular_bias` [deg], `angular_noise` [deg] (great-circle separation between observed and expected pointing direction), `angular_rate_bias` [deg/s], `angular_rate_noise` [deg/s] (L2 magnitude with the standard `cos(dec)` scaling on the RA-rate component), `ingest_delay_bias` [s], `ingest_delay_noise` [s] (`creation_epoch - epoch` when the upstream observation carried a `creation_epoch`): each is either a float (`bias` is the signed sample median, `noise` is a robust 1-σ (`1.4826 * MAD`), always `>= 0`) or `None` when the field's sample pool in the window is empty.
`list[dict[str, object]]`	`<field>_status` (str, one per measurement-quality field): `"nominal"` or `"degraded"` for that field. Flagged `"degraded"` when the sensor is listed in `expected_limits`, the field's pool is non-empty, and either drift bound is exceeded: `\|new_bias\| > \|expected_<field>_bias\| + 2 * expected_<field>_noise` `new_noise > 2 * expected_<field>_noise` Both bounds use `expected_<field>_noise` (an observed robust 1-σ) as the measurement-uncertainty unit, so casual run-to-run variance doesn't trip the check. If the caller didn't supply `<field>_noise`, neither bound fires. Empty pools, unlisted fields, and sensors absent from `expected_limits` all stay `"nominal"`. `ingest_delay` is informational metadata and does not get a `_status` key; `ingest_delay_*` entries in `expected_limits` are ignored.
`list[dict[str, object]]`	`status` (str): aggregate, `"nominal"` or `"degraded"`. `"degraded"` iff any per-field `<field>_status` is `"degraded"` — use the per-field keys to find which one tripped.

Raises:

Type	Description
`ValueError`	`latest_span` is greater than `full_span`; or a CITRA record fails to parse.

Per-satellite construction, ephemeris caching, or residual computation failures are logged at WARN and the offending satellite is dropped from the audit; they do not raise.

`audit_citra_radar(citra_elsets, citra_observations, latest_span, full_span, expected_limits=...)`

Summarize radar residual stats per radar antenna.

Grouping, dedupe, the count fields, the per-sensor windowing rule, and expected_limits semantics match audit_citra_optical. Per-sensor keys are the radar antenna_id. Per-sensor stat-block fields: range_bias / range_noise [km], range_rate_bias / range_rate_noise [km/s], angular_bias / angular_noise [deg], angular_rate_bias / angular_rate_noise [deg/s], and ingest_delay_bias / ingest_delay_noise [s]. Radar observations may carry RA/Dec independently of monostatic vs. bistatic geometry; the angular pools draw from any radar observation that has them. Observations whose measurement field is missing still count toward correlated_observation_count but contribute no samples to that field's pool.

Parameters:

Name	Type	Description	Default
`citra_elsets`	`list[dict[str, object]]`	List of CITRA elset dicts (same per-element shape as the elset arg of `get_citra_residuals`).	required
`citra_observations`	`list[dict[str, object]]`	List of CITRA radar observation dicts.	required
`latest_span`	`TimeSpan`	Width of the short window applied to sensors that appear in `expected_limits`. Acts as a cap. Must satisfy `latest_span <= full_span`.	required
`full_span`	`TimeSpan`	Minimum calibration history required for sensors that do not appear in `expected_limits`. Sensors with less than `full_span` of data are omitted from the output; sensors that meet the minimum are calibrated over their entire sample set (no cap).	required
`expected_limits`	`list[dict[str, object]] \| None`	Optional list of per-sensor limit dicts. See `audit_citra_optical` for the full shape.	`...`

Returns:

Type	Description
`list[dict[str, object]]`	List of per-sensor stat blocks (one per radar antenna that
`list[dict[str, object]]`	produced data and met the calibration minimum, or that is listed
`list[dict[str, object]]`	in `expected_limits`). Each block contains the common fields
`list[dict[str, object]]`	documented on `audit_citra_optical` plus radar-specific
`list[dict[str, object]]`	measurement fields: `range_bias` / `range_noise` [km],
`list[dict[str, object]]`	`range_rate_bias` / `range_rate_noise` [km/s], `angular_bias`
`list[dict[str, object]]`	/ `angular_noise` [deg], `angular_rate_bias` /
`list[dict[str, object]]`	`angular_rate_noise` [deg/s], and `ingest_delay_bias` /
`list[dict[str, object]]`	`ingest_delay_noise` [s].

Raises:

Type	Description
`ValueError`	`latest_span` is greater than `full_span`; or a CITRA record fails to parse.

Per-satellite construction, ephemeris caching, or residual computation failures are logged at WARN and the offending satellite is dropped from the audit; they do not raise.

`audit_citra_sensors(citra_elsets, sensors, observations, latest_span, full_span, expected_limits=...)`

Audit a fleet of CITRA sensors per sensor.

Unified entry point. Optical observations are aggregated per telescope_id (each block tagged "sensor_type": "telescope"); radar and DOA observations are aggregated per antenna identifier (antenna_id for radar, primary_antenna_id for DOA) and each block tagged "sensor_type": "antenna". Telescope and antenna blocks are returned in a single flat list — split downstream by the sensor_type key if you need per-type views.

Only sensors that produced at least one usable bias / noise value appear in the output. Catalog sensors listed in sensors but with no observations are omitted regardless of whether they appear in expected_limits, and sensors whose observations all fail to populate a bias / noise pool (e.g., uncorrelated tracks only, with no upstream creation_epoch) are likewise omitted. Callers that need to detect silent or content-free sensors must cross-reference the input catalog themselves. Per-sensor windowing and expected_limits semantics match audit_citra_optical.

Parameters:

Name	Type	Description	Default
`citra_elsets`	`list[dict[str, object]]`	List of CITRA elset dicts.	required
`sensors`	`dict[str, list[dict[str, object]]]`	`{"telescopes": [<telescope_dict>, ...], "antennas": [<antenna_dict>, ...]}`. Each sensor dict must carry a string `id`; richer schema fields are accepted and ignored. Missing top-level keys default to empty lists.	required
`observations`	`dict[str, list[dict[str, object]]]`	`{"optical": [...], "radar": [...], "doa": [...]}`. Each list is the same shape as the observation arg of the per-type audit functions. Missing keys default to empty lists.	required
`latest_span`	`TimeSpan`	Width of the short window applied to sensors that appear in `expected_limits`. Acts as a cap. Must satisfy `latest_span <= full_span`.	required
`full_span`	`TimeSpan`	Minimum calibration history required for sensors that do not appear in `expected_limits`. Sensors with less than `full_span` of data are omitted from the output; sensors that meet the minimum are calibrated over their entire sample set (no cap).	required
`expected_limits`	`list[dict[str, object]] \| None`	Optional list of per-sensor limit dicts. Each entry is `{"sensor_id": <sensor_uuid>, "<field>_bias": float, ...}`; non-bias/noise keys (counts, epochs, status, type, ...) are silently ignored, so the prior audit's output list can be passed back in directly. Sensors absent from this list go on the calibration (`full_span` minimum) path.	`...`

Returns:

Type	Description
`list[dict[str, object]]`	Flat list of per-sensor stat blocks
`list[dict[str, object]]`	(``[{"id": , "sensor_id": ,
`list[dict[str, object]]`	"sensor_type": "telescope" \| "antenna", "audit_type":
`list[dict[str, object]]`	"trend" \| "baseline", ...}, ...]``).
`list[dict[str, object]]`	Telescope blocks carry the optical fields documented on
`list[dict[str, object]]`	`audit_citra_optical`; antenna blocks carry the union
`list[dict[str, object]]`	of radar + DOA fields (`range_`, `range_rate_`,
`list[dict[str, object]]`	`angular_`, `angular_rate_`, `tdoa_*`,
`list[dict[str, object]]`	`ingest_delay_*` — each as a flat `_bias` / `_noise`
`list[dict[str, object]]`	pair, plus `_status` for every measurement-quality field).

Raises:

Type	Description
`ValueError`	`latest_span` is greater than `full_span`; or a CITRA record fails to parse.

Per-satellite construction, ephemeris caching, or residual computation failures are logged at WARN and the offending satellite is dropped from the audit; they do not raise.

`citra_data_to_observations(citra_observations, calibrations=..., telescope_limits=..., antenna_limits=...)`

Convert a CITRA observation envelope into keplime observations.

Records are converted and returned in the canonical order optical, radar, doa. Measurement noise is resolved per observation in two stages: a per-sensor calibration override, then a per-sensor-type limit clamp.

When calibrations is supplied, each converted observation whose sensor id matches a calibration's sensor_id has its present noise fields replaced (angular fields given in degrees, converted to radians). The override is purely per-sensor, matched by id — there is no per-modality logic. An observation whose sensor has no matching calibration keeps the noise reported on its record, so to leave a sensor's noise untouched (for example a trusted telescope) simply omit it from calibrations.

The resolved noise is then bounded to the supplied SensorCalibrationLimits for the observation's sensor type — optical observations use telescope_limits, radar and DOA observations use antenna_limits. Clamping runs for every observation whether or not a calibration matched, so unphysical record noise (e.g. milli-arcsecond optical, kilometre-scale range) is corrected even with no calibration. A None limits argument skips clamping for that sensor type.

Parameters:

Name	Type	Description	Default
`citra_observations`	`dict[str, list[dict[str, object]]]`	`{"optical": [...], "radar": [...], "doa": [...]}` mapping. Each list holds CITRA observation dicts for that type; missing keys default to empty lists.	required
`calibrations`	`list[dict[str, object]] \| None`	Optional list of per-sensor noise-override mappings. Each must carry `sensor_id` and may carry any of `angular_noise` [deg], `range_noise` [km], `range_rate_noise` [km/s], `angular_rate_noise` [deg/s], `tdoa_noise` [s], `fdoa_noise` [Hz]; unknown keys (e.g. baseline biases) are ignored. Defaults to `None` (no overrides).	`...`
`telescope_limits`	`SensorCalibrationLimits \| None`	Optional `SensorCalibrationLimits` applied to optical (telescope) observations. Defaults to `None`.	`...`
`antenna_limits`	`SensorCalibrationLimits \| None`	Optional `SensorCalibrationLimits` applied to radar and DOA (antenna) observations. Defaults to `None`.	`...`

Returns:

Type	Description
`list[Observation]`	Observations in the TEME frame, in optical -> radar -> doa order.

Raises:

Type	Description
`ValueError`	If a record is missing a required field, an epoch cannot be parsed, or a sensor location cannot be propagated to its epoch.

`dnd_postgres_df_to_observations(dataframe)`

Converts DND PostgreSQL observation rows into keplime observations.

The input is expected to be the Polars DataFrame returned by pl.read_database_uri for the DND observation query. Required columns are id, epoch, sensor_id, sensor_latitude, sensor_longitude, and sensor_altitude. Optional columns are right_ascension, declination, range, visual_magnitude, radar_cross_section, provider_id, and dnd_id.

Angles and sensor geodetic coordinates are interpreted in radians. Range and sensor altitude are interpreted in km. sensor_id is stored on Observation.sensor.id, provider_id is stored on Observation.expected_satellite_id, dnd_id is stored on Observation.observed_satellite_id, and radar_cross_section is stored on Observation.radar_cross_section. Converted sensors use the package default measurement noise constants: angular observations receive 0.0005 deg (stored in radians), range observations receive 0.1 km, and absent measurement types leave their corresponding noise fields unset. Polars datetime epochs are read from their Arrow-backed integer storage and interpreted as UTC Unix timestamps. String epochs are parsed directly.

Parameters:

Name	Type	Description	Default
`dataframe`	`Any`	Polars dataframe returned by the DND PostgreSQL query.	required

Returns:

Type	Description
`list[Observation]`	Converted `Observation` objects in
`list[Observation]`	input row order.

Raises:

Type	Description
`TypeError`	If `dataframe` is not a Polars dataframe.
`ValueError`	If a row is missing a required column, a required value is null, an epoch cannot be parsed, or sensor coordinates cannot be propagated.

`dnd_postgres_elset_df_to_constellation(dataframe, start, end, step, purge_on_fail=..., reference_frame=...)`

Builds a constellation with stitched ephemeris from a DND elset query.

The input is a Polars DataFrame with the required columns dnd_id, elset_line_1, and elset_line_2, plus an optional name column. Rows are grouped by dnd_id (each dnd_id becomes one satellite); elset_line_1 / elset_line_2 are parsed as a two-line element set and the epoch is read from the TLE itself. When present, name (taken to be constant per dnd_id) sets each satellite's human-readable name.

For a satellite with a single element set the ephemeris is a plain SGP4 arc over [start, end]. For a satellite with multiple element sets, one arc is propagated per set across the span between consecutive epochs and the arcs are joined at their closest-approach crossovers (see Ephemeris.stitch), then resampled onto the uniform [start, end, step] grid so every satellite in the returned constellation shares the same epoch lattice. Each returned satellite is keyed by its dnd_id and carries the freshest element set as its TLE metadata.

Element sets are de-duplicated by epoch (records within 1 ms collapse to the latest), and only the sets relevant to [start, end] are propagated.

Parameters:

Name	Type	Description	Default
`dataframe`	`Any`	Polars dataframe with required `dnd_id`, `elset_line_1`, `elset_line_2` columns and an optional `name` column.	required
`start`	`ModifiedJulianDate`	Start of the ephemeris window.	required
`end`	`ModifiedJulianDate`	End of the ephemeris window.	required
`step`	`TimeSpan`	Propagation / resampling step.	required
`purge_on_fail`	`bool`	When `True`, a satellite whose element sets fail to parse or whose arcs cannot be stitched is dropped (and logged) and the rest are still returned. When `False` (the default), the first such failure raises. Defaults to `False`.	`...`
`reference_frame`	`ReferenceFrame \| None`	Frame for the cached states; defaults to TEME.	`...`

Returns:

Type	Description
`Constellation`	One `Satellite` per `dnd_id` in a
`Constellation`	`Constellation`, each carrying a stitched
`Constellation`	ephemeris over `[start, end]`.

Raises:

Type	Description
`TypeError`	If `dataframe` is not a Polars dataframe.
`ValueError`	If a required column is missing, a value is null, an element set cannot be parsed, or (when `purge_on_fail` is `False`) a satellite's ephemeris cannot be built.

`get_citra_residuals(citra_elset, citra_observations)`

Compute citra-format residuals for a batch of citra observations.

Returns one dict per input observation (in input order: optical, then radar, then doa). Each dict carries identifiers (satellite_id, observation_id, elset_id, elset_username, elset_user_group_name, review_status), the source observation epoch (echoed from input), the residual total_error (cross-line-of-sight, km), the type ("optical" / "radar" / "doa"), and the residual numbers (range km, range_rate km/s, right_ascension / declination / right_ascension_rate / declination_rate in degrees, tdoa s, fdoa Hz). visual_magnitude is populated only for optical entries.

Note: elset_username and elset_user_group_name are populated from the citra elset dict's user_id and user_group_id fields (UUID strings). If you need resolved human-readable names, do that join in your own DB after this call.

Parameters:

Name	Type	Description	Default
`citra_elset`	`dict[str, object]`	CITRA elset dict. Must carry at minimum `satellite_id` and `id` (UUID strings), plus `user_id` and `user_group_id` to populate `elset_username` / `elset_user_group_name`.	required
`citra_observations`	`dict[str, list[dict[str, object]]]`	`{"optical": [...], "radar": [...], "doa": [...]}` mapping. Each list contains CITRA observation dicts for that type. Missing keys default to empty lists.	required

Returns:

Type	Description
`list[dict[str, object]]`	One residual dict per input observation, in input order
`list[dict[str, object]]`	(optical, then radar, then DOA). Each dict carries the identifier
`list[dict[str, object]]`	and residual fields described above.

Raises:

Type	Description
`ValueError`	If a CITRA record fails to parse, the satellite cannot be constructed from the elset, or residual computation fails.

Schemas

CCSDS Navigation Data Messages

API reference

schemas

CDM

header property

from_conjunction(header, tca, state1, state2, covariance1, covariance2, collision_probability=None) staticmethod

from_file(path) staticmethod

from_kvn(text) staticmethod

from_str_any(text) staticmethod

from_xml(text) staticmethod

to_kvn()

to_xml()

CDMAdditionalParameters

__init__()

CDMHeader

creation_date property

message_version property

__init__(message_version, creation_date, originator, message_id, comments=..., message_for=None)

CDMODParameters

__init__()

CDMObjectData

covariance property

reference_frame property

state property

CDMRelativeMetadata

miss_distance property

relative_speed property

tca property

NDMHeader

__init__(message_version, creation_date, originator, comments=..., message_id=None, classification=None)

OEM

header property

segments property

covariance_at_epoch(epoch)

from_ephemeris(ephemeris, frame, time_system, header, object_id) staticmethod

from_file(path) staticmethod

from_kvn(text) staticmethod

from_str_any(text) staticmethod

from_xml(text) staticmethod

to_ephemerides()

to_kvn()

to_xml()

OEMCovarianceRecord

covariance property

epoch property

OEMMetadata

center_name property

comments property

interpolation property

object_id property

object_name property

ref_frame_epoch property

reference_frame property

start_time property

stop_time property

time_system property

useable_start_time property

useable_stop_time property

OEMSegment

covariance_records property

metadata property

states property

OMM

covariance property

header property

mean_elements property

metadata property

tle_parameters property

user_defined property

from_file(path) staticmethod

from_kvn(text) staticmethod

from_str_any(text) staticmethod

from_tle(tle, header) staticmethod

from_xml(text) staticmethod

to_kvn()

to_tle()

to_xml()

OMMMeanElements

argument_of_periapsis property

`schemas`

`CDM`

`header` `property`

`from_conjunction(header, tca, state1, state2, covariance1, covariance2, collision_probability=None)` `staticmethod`

`from_file(path)` `staticmethod`

`from_kvn(text)` `staticmethod`

`from_str_any(text)` `staticmethod`

`from_xml(text)` `staticmethod`

`to_kvn()`

`to_xml()`

`CDMAdditionalParameters`

`init()`

`CDMHeader`

`creation_date` `property`

`message_version` `property`

`init(message_version, creation_date, originator, message_id, comments=..., message_for=None)`

`CDMODParameters`

`init()`

`CDMObjectData`

`covariance` `property`

`reference_frame` `property`

`state` `property`

`CDMRelativeMetadata`

`miss_distance` `property`

`relative_speed` `property`

`tca` `property`

`NDMHeader`

`init(message_version, creation_date, originator, comments=..., message_id=None, classification=None)`

`OEM`

`header` `property`

`segments` `property`

`covariance_at_epoch(epoch)`

`from_ephemeris(ephemeris, frame, time_system, header, object_id)` `staticmethod`

`from_file(path)` `staticmethod`

`from_kvn(text)` `staticmethod`

`from_str_any(text)` `staticmethod`

`from_xml(text)` `staticmethod`

`to_ephemerides()`

`to_kvn()`

`to_xml()`

`OEMCovarianceRecord`

`covariance` `property`

`epoch` `property`

`OEMMetadata`

`center_name` `property`

`comments` `property`

`interpolation` `property`

`object_id` `property`

`object_name` `property`

`ref_frame_epoch` `property`

`reference_frame` `property`

`start_time` `property`

`stop_time` `property`

`time_system` `property`

`useable_start_time` `property`

`useable_stop_time` `property`

`OEMSegment`

`covariance_records` `property`

`metadata` `property`

`states` `property`

`OMM`

`covariance` `property`

`header` `property`

`mean_elements` `property`

`metadata` `property`

`tle_parameters` `property`

`user_defined` `property`

`from_file(path)` `staticmethod`

`from_kvn(text)` `staticmethod`

`from_str_any(text)` `staticmethod`

`from_tle(tle, header)` `staticmethod`

`from_xml(text)` `staticmethod`

`to_kvn()`

`to_tle()`

`to_xml()`

`OMMMeanElements`

`argument_of_periapsis` `property`

`ascending_node` `property`

`eccentricity` `property`

`epoch` `property`