TrackTableValidate¶
TrackTableValidate validates required tracking dataframe columns and basic table consistency.
The tool is a DataFrameTool: pass an upstream track dataframe positionally.
The input dataframe must contain track_id, frame, label, y, and x.
Outputs are validation rows with severity, message, valid, and error_count.
No validation CSV artifact is written.
Dependencies and Core Libraries¶
BioImageFlow core APIs and package-local numeric table validation helpers.
Minimal Example¶
import pandas as pd
from bioimageflow_core import Arguments
from bioimageflow_tracking_tools import TrackTableValidate
tracks = pd.DataFrame([
{"track_id": 1, "frame": 0, "label": 1, "y": 0.0, "x": 0.0},
])
report = TrackTableValidate().transform(tracks, Arguments())
Expected Results¶
Valid input returns an informational row; duplicate track/frame rows or blank required values are reported as error rows.
Failure Modes¶
Malformed numeric values raise validation errors in the output dataframe.