"""MIK North Sea operator app. Data and authority arrive only through the Horizon app host.""" import marimo __generated_with = "0.23.14" app = marimo.App(width="full") @app.cell def _(): import marimo as mo from scrydon import apps return apps, mo @app.cell def _(apps): access = apps.declare( ontologies=[apps.ontology("scrydon-pack-mik-north-sea-v2", alias="mik")], queries=[ apps.query( "tracks", ontology="mik", object_type="MaritimeTrack", properties=[ "trackId", "vesselId", "observationId", "sourceId", "sourceEntityId", "observedAt", "receivedAt", "latitude", "longitude", "heading", "speed", "quality", "freshness", ], max_objects=1000, live=True, stale_after_ms=120_000, max_interpolation_gap_ms=15_000, ), apps.query( "zones", ontology="mik", object_type="MaritimeZone", properties=["areaId", "name", "category", "boundary"], filter=[{"property": "category", "op": "eq", "value": "restricted"}], max_objects=100, live=True, stale_after_ms=86_400_000, ), apps.query( "interest_zones", ontology="mik", object_type="MaritimeZone", properties=["areaId", "name", "category", "boundary"], filter=[{"property": "category", "op": "eq", "value": "interest"}], max_objects=100, live=True, required=False, stale_after_ms=86_400_000, ), apps.query( "vessels", ontology="mik", object_type="MaritimeVessel", properties=[ "vesselId", "name", "mmsi", "imo", "flag", "vesselType", "riskScore", "riskLevel", "riskReasons", "lastLatitude", "lastLongitude", "heading", "lastSeenAt", "provenance", ], max_objects=1000, live=True, required=False, stale_after_ms=86_400_000, ), apps.query( "replay", ontology="mik", object_type="MaritimeReplayEvent", properties=[ "eventId", "rule", "severity", "areaId", "vesselId", "firedAt", "summary", "provenance", ], max_objects=100, live=True, required=False, stale_after_ms=86_400_000, ), apps.query( "exposure", ontology="mik", object_type="MaritimeZoneExposure", properties=[ "exposureId", "vesselId", "vesselName", "areaId", "zoneName", "zoneCategory", "riskLevel", "computedAt", "provenance", ], max_objects=1000, live=True, required=False, stale_after_ms=86_400_000, ), apps.query( "detections", ontology="mik", object_type="MaritimeDetection", properties=[ "detectionId", "watchSlug", "kind", "severity", "areaId", "entityId", "firedAt", "acknowledgementStatus", "acknowledgedBy", "acknowledgedAt", ], max_objects=1000, live=True, required=False, stale_after_ms=120_000, ), ], links=[apps.link( "track-vessel", ontology="mik", link_type="MaritimeTrackVessel", source_query="tracks", target_query="vessels", max_objects=1, required=False, )], actions=[apps.allow_action( "acknowledge-mik-detection", ontology="mik", action_type="acknowledge-mik-detection", input_properties=["detectionId"], required=False, )], watches=[ apps.allow_watch("mik-restricted-area", ontology="mik", watch="mik-restricted-area", required=False), apps.allow_watch("mik-missing-vessel-report", ontology="mik", watch="mik-missing-vessel-report", required=False), ], ) return access @app.cell def _(apps): restricted = apps.zones( "zones", geometry="boundary", label="name", classification="category", title="Restricted area", ) interest = apps.zones( "interest_zones", geometry="boundary", label="name", classification="category", title="Zones of interest (approx.)", ) # Registry vessels have no live track: each draws as a ship at its last # reported position, turned to its last course and coloured by risk. # Selecting one selects it in the "Vessels of interest" list too. last_seen = apps.points( "vessels", latitude="lastLatitude", longitude="lastLongitude", label="name", classification="riskLevel", heading="heading", selection_group="vessels", title="Vessels of interest (last position)", ) picture = apps.map( "tracks", latitude="latitude", longitude="longitude", observed_at="observedAt", received_at="receivedAt", label="vesselId", heading="heading", zone_layers=[restricted, interest], point_layers=[last_seen], center=(2.8, 51.6), zoom=7, selection_group="contacts", title="North Sea picture", ) return (picture,) @app.cell def _(apps): contacts = apps.table( "tracks", columns={ # The first column is the row's select button: the stable trackId, # which an uncorrelated radar contact has and a vesselId it lacks. "trackId": "MaritimeTrack", "vesselId": "MaritimeVessel", "freshness": "Freshness", }, selection_group="contacts", title="Live contacts", ) details = apps.details( "tracks", fields={ "trackId": "Track ID", "vesselId": "Vessel ID", "sourceId": "Accepted source", "sourceEntityId": "Source contact", "observedAt": "Observed", "receivedAt": "Received", "speed": "Speed", "quality": "Quality", }, selection_group="contacts", title="Selected track", ) registry = apps.related( "track-vessel", columns={ "name": "Registered name", "mmsi": "MMSI", "flag": "Flag", "riskLevel": "Risk", }, source_selection_group="contacts", selection_group="registry", title="Linked vessel registry", ) return contacts, details, registry @app.cell def _(apps): watchlist = apps.table( "vessels", columns={ "name": "Vessel", "vesselType": "Type", "flag": "Flag", "riskLevel": "Risk", "riskScore": "Score", }, selection_group="vessels", title="Vessels of interest (fictional)", ) vessel_details = apps.details( "vessels", fields={ "riskReasons": "Why", "riskScore": "Risk score", "imo": "IMO", "mmsi": "MMSI", "lastSeenAt": "Last seen", "provenance": "Provenance", }, selection_group="vessels", title="Selected vessel", ) # Derived by the exposure.py notebook: registry SQL joined with MaritimeZone. exposure = apps.table( "exposure", columns={ "vesselName": "Vessel", "zoneName": "Area", "riskLevel": "Risk", "computedAt": "Computed", }, selection_group="exposure", title="Vessels inside a governed area", ) return exposure, vessel_details, watchlist @app.cell def _(apps): detections = apps.alerts( "detections", columns={ "watchSlug": "Rule", "severity": "Severity", "firedAt": "Detected", "acknowledgementStatus": "Acknowledgement", }, severity="severity", status="acknowledgementStatus", acknowledge_action="acknowledge-mik-detection", acknowledge_input="detectionId", selection_group="alerts", title="Independent watch detections", ) detection_details = apps.details( "detections", fields={ "watchSlug": "Rule", "kind": "Event class", "areaId": "Area", "entityId": "MaritimeTrack", "firedAt": "Detected", "acknowledgedBy": "Acknowledged by", "acknowledgedAt": "Acknowledged at", }, selection_group="alerts", title="Selected detection", ) replayed = apps.table( "replay", columns={ "summary": "Event", "severity": "Severity", "firedAt": "Detected", }, selection_group="replay", title="Replayed events (demo)", ) replay_details = apps.details( "replay", fields={ "rule": "Rule", "areaId": "Area", "vesselId": "Vessel", "provenance": "Provenance", }, selection_group="replay", title="Selected replay", ) return detection_details, detections, replay_details, replayed @app.cell def _( contacts, detection_details, detections, details, exposure, mo, picture, registry, replay_details, replayed, vessel_details, watchlist, ): # The picture takes the viewer's full height (the map sizes itself to the # frame); the rail beside it is a tab per worklist, each with the inspector # its selection drives. mo.hstack( [ picture, mo.ui.tabs({ "Contacts": mo.vstack([contacts, details, registry], gap=0.75), "Vessels of interest": mo.vstack( [watchlist, vessel_details, exposure], gap=0.75, ), "Detections": mo.vstack( [detections, detection_details, replayed, replay_details], gap=0.75, ), }), ], widths=[2, 1], gap=1, align="start", ) return if __name__ == "__main__": app.run()