empyrean.FitSummary

class FitSummary(table, **kwargs)

Bases: Table

One row per input object of a batch orbit determination — delivered or not.

determine() fits every object in the observations. .orbits holds the objects that produced an orbit; this table holds all of them, so a partially successful batch is readable rather than silently shorter than its input. A failed object’s measurement columns are NaN (never 0.0, which would read as a value at the floor) and error says why.

The column names match the fit_summary files the CLI writes, so a table read back from fit_summary.parquet and this one describe a fit identically.

Methods

__init__(table, **kwargs)
apply_mask(mask)	Return a new table with rows filtered to match a boolean mask.
as_column([nullable, metadata])	Embed the Table as a column in another Table.
attributes()	Return a dictionary of the table's attributes.
chunk_counts()	Returns the number of discrete memory chunks that make up each of the Table's underlying arrays.
column(column_name)	Returns the column with the given name as a raw pyarrow ChunkedArray.
drop_duplicates([subset, keep])	Drop duplicate rows from a ~quivr.Table.
empty(**kwargs)	Create an empty instance of the table.
flattened_table()	Completely flatten the Table's underlying Arrow table, taking into account any nested structure, and return the data table itself.
fragmented()	Returns true if the Table has any fragmented arrays.
from_csv(input_file[, validate])	Read a table from a CSV file.
from_dataframe(df[, validate])	Load a DataFrame into the Table.
from_feather(path[, validate])	Read a table from a Feather file.
from_flat_dataframe(df[, validate])	Load a flattened DataFrame into the Table.
from_kwargs([validate, permit_nulls])	Create a Table instance from keyword arguments.
from_parquet(path[, memory_map, ...])	Read a table from a Parquet file.
from_pyarrow(table[, validate, permit_nulls])	Create a new table from a pyarrow Table.
invalid_mask()	Return a boolean mask indicating which rows are invalid.
is_valid()	Validate the table against the schema.
null_mask()	Return a boolean mask indicating which rows of the entire table are null.
nulls(size, **kwargs)	Create a table with nulls.
select(column_name, value)	Select from the table by exact match, returning a new Table which only contains rows for which the value in column_name equals value.
separate_invalid()	Separates rows that have invalid data from those that have valid data.
set_column(name, data)	Return a copy of the table with a particular column replaced with new data.
sort_by(by)	Sorts the Table by the given column name (or multiple columns).
take(row_indices)	Return a new Table with only the rows at the given indices.
to_csv(path[, attribute_columns])	Write the table to a CSV file.
to_dataframe([flatten, attr_handling])	Returns self as a pandas DataFrame.
to_feather(path, **kwargs)	Write the table to a Feather file.
to_parquet(path, **kwargs)	Write the table to a Parquet file.
to_structarray()	Returns self as a StructArray.
unique_indices([subset, keep])	Get the indices of the first or last occurrence of each unique row in the table.
validate()	Validate the table against the schema, raising an exception if invalid.
where(expr)	Return a new table with rows filtered to match an expression.
with_table(table)

Attributes

converged	Did the differential correction reach its stopping criterion?
error	Failure message.
extrapolation_acceptable	fit_acceptable AND the four selection / coverage axes below.
fit_acceptable	Aggregate fit-quality verdict.
fractional_sigma_a	Measured $\sigma_a / |a|$.
fractional_sigma_a_ok	Did $\sigma_a / |a|$ pass its threshold?
fractional_sigma_a_threshold	Threshold for $\sigma_a / |a|$.
iterations	DC iterations used.
n_obs	Observations this object contributed.
n_selected	Observations the fit retained.
object_id	ADES object identifier (permID / provID / trkSub).
reduced_chi2	Reduced $\chi^2$ of the fit.
rms_dec_arcsec	Dec residual RMS (arcsec).
rms_ra_arcsec	RA·cos(Dec) residual RMS (arcsec).
schema
selected_arc_coverage_ok	Do the selected observations still span enough of the arc?
selected_arc_days	Arc span over the selected observations only (days).
selected_arc_fraction	Selected-span / full-span ratio.
selected_arc_fraction_threshold	Minimum span ratio the gate required.
selection_fraction	Fraction of observations retained.
selection_fraction_ok	Did the fit retain enough of its input?
selection_fraction_threshold	Minimum retained fraction the gate required.
solve_for_width	Width of the solved-parameter set (6 for a state-only fit).
status	"delivered" or "failed".
trailing_gap_days	Days between the last selected and the last full-arc observation.
trailing_gap_ok	Were the most-recent observations kept?
trailing_gap_threshold_days	Largest trailing gap the gate allowed (days).
table

Parameters:

• table (Table)

• kwargs (AttributeValueType)

schema: ClassVar[Schema] = object_id: large_string not null status: large_string not null converged: bool not null iterations: int32 not null n_obs: int32 not null n_selected: int32 not null rms_ra_arcsec: double rms_dec_arcsec: double reduced_chi2: double fit_acceptable: bool not null extrapolation_acceptable: bool not null selection_fraction_ok: bool not null selection_fraction: double selection_fraction_threshold: double selected_arc_coverage_ok: bool not null selected_arc_days: double selected_arc_fraction: double selected_arc_fraction_threshold: double trailing_gap_ok: bool not null trailing_gap_days: double trailing_gap_threshold_days: double fractional_sigma_a_ok: bool not null fractional_sigma_a: double fractional_sigma_a_threshold: double solve_for_width: int32 not null error: large_string

object_id

ADES object identifier (permID / provID / trkSub).

status

"delivered" or "failed".

converged

Did the differential correction reach its stopping criterion?

iterations

DC iterations used. 0 on a failed object.

n_obs

Observations this object contributed.

n_selected

Observations the fit retained.

rms_ra_arcsec

RA·cos(Dec) residual RMS (arcsec).

rms_dec_arcsec

Dec residual RMS (arcsec).

reduced_chi2

Reduced $\chi^2$ of the fit.

fit_acceptable

Aggregate fit-quality verdict.

extrapolation_acceptable

fit_acceptable AND the four selection / coverage axes below.

Type:

Aggregate verdict on forward extrapolation

selection_fraction_ok

Did the fit retain enough of its input?

selection_fraction

Fraction of observations retained.

selection_fraction_threshold

Minimum retained fraction the gate required.

selected_arc_coverage_ok

Do the selected observations still span enough of the arc?

selected_arc_days

Arc span over the selected observations only (days).

selected_arc_fraction

Selected-span / full-span ratio.

selected_arc_fraction_threshold

Minimum span ratio the gate required.

trailing_gap_ok

Were the most-recent observations kept?

trailing_gap_days

Days between the last selected and the last full-arc observation.

trailing_gap_threshold_days

Largest trailing gap the gate allowed (days).

fractional_sigma_a_ok

Did $\sigma_a / |a|$ pass its threshold?

fractional_sigma_a

Measured $\sigma_a / |a|$.

fractional_sigma_a_threshold

Threshold for $\sigma_a / |a|$.

solve_for_width

Width of the solved-parameter set (6 for a state-only fit). 0 on a failed object.

error

Failure message. Null on a delivered object.