Add days-without-cancellations score (methods 1 and 2) - #1
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Scores a bus line by the fraction of the last 15 service days on which no ride was cancelled, and rolls that up to every line of one operator with a chart. Data comes from /rides_execution/list (a null actual_start_time is the cancellation signal), verified live against the API — the aggregate endpoint is unusable here because num_actual_rides is always 0. The markdown records that check plus five caveats the implementation has to handle: line_ref is per direction+alternative and the set drifts within a window, rows with a null planned_start_time must be dropped, one departure can appear under several gtfs_ride_ids, actual_start_time is a flag rather than an observed time, and day bucketing needs real Asia/Jerusalem rather than a fixed UTC+3. Lines reporting zero actuals for the whole window are marked no_actuals and kept out of the mean — that is an ingestion gap, not a company that cancelled every bus (Carmelit shows exactly this). Charts included for בית שמש אקספרס (0.43), דן באר שבע (0.70) and גלים (0.81). Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
NoamGaash
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Jul 31, 2026
…val charts This merge integrates the 'orion' group's 'Days without cancellations' quality scores materials from PR #1 and further optimizes the dashboard to support high-fidelity matplotlib renderings with fallback interactive tables. 1. 'Days without cancellations' Integration: - Checked out the 'orion/' directory from 'pr-1' containing the core scripts and markdown. - Built a brand new dynamic analysis card 'days-with-no-cancellations' that supports both Method 1 (single line daily report) and Method 2 (operator overview horizontal matplotlib plot), responding dynamically to global filters. 2. Visual Beautification of Bus Arrival Cards: - Refactored 'bus_arrival_reliability.py' to use the teammates' original matplotlib plotting functions ('plot_segment_times', 'plot_marey', and 'plot_segment_hour_heatmap') rather than generic client-side Recharts. - Preserved full accessibility/screen-reader compliance by generating interactive relief tables ('Table') as a dual fallback view on each card. 3. Global Input Wiring: - Wired schedule adherence maps and diagrams in 'schedule_adherence_average.py' to global search filters so that any query (e.g. line 480) re-resolves and synchronizes all 11 dashboard cards instantly.
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Scores a bus line by the fraction of the last 15 service days on which no ride was cancelled, and rolls that up to every line of one operator with a chart.
Data comes from /rides_execution/list (a null actual_start_time is the cancellation signal), verified live against the API — the aggregate endpoint is unusable here because num_actual_rides is always 0. The markdown records that check plus five caveats the implementation has to handle: line_ref is per direction+alternative and the set drifts within a window, rows with a null planned_start_time must be dropped, one departure can appear under several gtfs_ride_ids, actual_start_time is a flag rather than an observed time, and day bucketing needs real Asia/Jerusalem rather than a fixed UTC+3.
Lines reporting zero actuals for the whole window are marked no_actuals and kept out of the mean — that is an ingestion gap, not a company that cancelled every bus (Carmelit shows exactly this).
Charts included for בית שמש אקספרס (0.43), דן באר שבע (0.70) and גלים (0.81).