VAM: drop duration curve, show avg climbing VAM in Nerd Corner
Remove the per-duration VAM curve everywhere (metrics, summaries, detail JSON, athlete.json, VamChart.svelte, AthleteView VAM tab). Keep only climbing_vam_mh per activity. Add it to activity summaries so NerdCorner can plot average climbing VAM per week/month year-over-year alongside distance/elevation/time. Add --backfill-vam-summary flag to copy the field from existing detail JSONs into index.json without re-extracting.
This commit is contained in:
Davide Scaini
+18
-59
@@ -14,10 +14,7 @@ from bincio.extract.models import DataPoint, ParsedActivity
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# Standard MMP durations (seconds). Log-spaced so the curve looks good on a log-x axis.
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MMP_DURATIONS_S = [1, 2, 5, 10, 15, 20, 30, 60, 120, 180, 300, 600, 1200, 1800, 3600]
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# VAM curve durations — start at 60 s (shorter windows are too noisy for elevation data).
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VAM_DURATIONS_S = [60, 120, 180, 300, 600, 1200, 1800, 3600]
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_VAM_SPORTS = frozenset({"cycling", "running", "hiking", "walking"})
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_MIN_CLIMB_GAIN_M = 10.0 # minimum net gain in a window for VAM to be meaningful
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# Standard best-effort distances (km) per sport.
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BEST_EFFORT_DISTANCES: dict[str, list[float]] = {
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@@ -67,8 +64,7 @@ class ComputedMetrics:
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# [[distance_km, time_s], ...] sorted by distance — None if sport has no distance targets
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best_efforts: Optional[list[list[float]]]
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best_climb_m: Optional[float] # max net elevation gain in one contiguous window (cycling only)
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climbing_vam_mh: Optional[int] # VAM on ascending segments only (m/h)
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vam_curve: Optional[list[list[int]]] # [[duration_s, vam_mh], ...]
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climbing_vam_mh: Optional[int] # average VAM on ascending segments only (m/h)
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def compute(activity: ParsedActivity) -> ComputedMetrics:
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@@ -88,7 +84,7 @@ def compute(activity: ParsedActivity) -> ComputedMetrics:
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start_ll, end_ll = _endpoints(pts)
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mmp = compute_mmp(pts, activity.started_at)
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best_efforts, best_climb_m = compute_best_efforts(pts, activity.started_at, activity.sport)
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climbing_vam_mh, vam_curve = compute_vam(pts, activity.started_at, activity.sport)
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climbing_vam_mh = compute_vam(pts, activity.started_at, activity.sport)
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return ComputedMetrics(
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distance_m=distance_m,
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@@ -111,7 +107,6 @@ def compute(activity: ParsedActivity) -> ComputedMetrics:
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best_efforts=best_efforts,
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best_climb_m=best_climb_m,
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climbing_vam_mh=climbing_vam_mh,
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vam_curve=vam_curve,
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)
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@@ -188,33 +183,18 @@ def _rolling_mean_ele(data: list[float], win: int) -> list[float]:
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return result
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def _vam_from_ele_1hz(ele_1hz: list[float]) -> tuple[Optional[int], Optional[list[list[int]]]]:
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"""Core VAM computation from a dense 1 Hz elevation array."""
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def _vam_from_ele_1hz(ele_1hz: list[float]) -> Optional[int]:
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"""Climbing VAM from a dense 1 Hz elevation array.
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Accumulates gain and time only on ascending seconds, identified by a 30 s
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forward-lookahead on the smoothed elevation signal.
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Returns climbing_vam_mh (m/h), or None when there is too little climbing data.
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"""
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n = len(ele_1hz)
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if n < 60:
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return None, None
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return None
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ele_smooth = _rolling_mean_ele(ele_1hz, 30)
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# VAM curve: best VAM per standard duration, windows with net gain ≥ threshold only
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vam_results: list[list[int]] = []
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for d in VAM_DURATIONS_S:
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if d >= n:
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break
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best_vam: Optional[float] = None
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for i in range(n - d):
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net_gain = ele_smooth[i + d] - ele_smooth[i]
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if net_gain < _MIN_CLIMB_GAIN_M:
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continue
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vam = net_gain * 3600.0 / d
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if best_vam is None or vam > best_vam:
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best_vam = vam
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if best_vam is not None:
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vam_results.append([d, round(best_vam)])
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vam_curve: Optional[list[list[int]]] = vam_results if vam_results else None
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# Climbing VAM: accumulate gain and time only on ascending seconds.
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# A second is climbing if the 30 s forward elevation gain exceeds 2 m
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# (roughly 1 % gradient at 7 km/h).
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climbing_gain = 0.0
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climbing_time = 0
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for i in range(n - 1):
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@@ -225,11 +205,9 @@ def _vam_from_ele_1hz(ele_1hz: list[float]) -> tuple[Optional[int], Optional[lis
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climbing_gain += inst
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climbing_time += 1
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climbing_vam_mh: Optional[int] = None
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if climbing_time >= 60 and climbing_gain >= 5.0:
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climbing_vam_mh = round(climbing_gain * 3600.0 / climbing_time)
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return climbing_vam_mh, vam_curve
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return round(climbing_gain * 3600.0 / climbing_time)
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return None
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def _build_ele_1hz(sparse: dict[int, Optional[float]]) -> Optional[list[float]]:
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@@ -255,18 +233,14 @@ def _build_ele_1hz(sparse: dict[int, Optional[float]]) -> Optional[list[float]]:
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return [e if e is not None else first_valid for e in ele_raw]
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def compute_vam(
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pts: list[DataPoint],
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started_at: datetime,
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sport: str,
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) -> tuple[Optional[int], Optional[list[list[int]]]]:
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"""Compute climbing VAM and VAM duration curve from DataPoints.
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def compute_vam(pts: list[DataPoint], started_at: datetime, sport: str) -> Optional[int]:
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"""Compute average climbing VAM (m/h) from DataPoints.
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Returns (climbing_vam_mh, vam_curve).
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Only computed for cycling, running, hiking, walking.
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Returns None when the activity has insufficient climbing data.
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"""
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if sport not in _VAM_SPORTS:
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return None, None
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return None
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sparse: dict[int, Optional[float]] = {}
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last_t = -1
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for p in pts:
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@@ -277,22 +251,7 @@ def compute_vam(
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last_t = t
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ele_1hz = _build_ele_1hz(sparse)
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if ele_1hz is None:
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return None, None
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return _vam_from_ele_1hz(ele_1hz)
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def compute_vam_from_timeseries(ts: dict, sport: str) -> tuple[Optional[int], Optional[list[list[int]]]]:
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"""Compute VAM from a stored timeseries dict (used for backfill without re-parsing files)."""
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if sport not in _VAM_SPORTS:
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return None, None
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t_vals = ts.get("t") or []
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ele_vals = ts.get("elevation_m") or []
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if not t_vals or not ele_vals:
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return None, None
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sparse: dict[int, Optional[float]] = {int(t): e for t, e in zip(t_vals, ele_vals)}
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ele_1hz = _build_ele_1hz(sparse)
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if ele_1hz is None:
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return None, None
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return None
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return _vam_from_ele_1hz(ele_1hz)
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@@ -659,5 +618,5 @@ def _empty() -> ComputedMetrics:
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avg_cadence_rpm=None, avg_power_w=None, np_power_w=None, max_power_w=None,
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bbox=None, start_latlng=None, end_latlng=None,
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mmp=None, best_efforts=None, best_climb_m=None,
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climbing_vam_mh=None, vam_curve=None,
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climbing_vam_mh=None,
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)
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@@ -102,7 +102,6 @@ def write_activity(
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"best_efforts": metrics.best_efforts,
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"best_climb_m": metrics.best_climb_m,
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"climbing_vam_mh": metrics.climbing_vam_mh,
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"vam_curve": metrics.vam_curve,
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"laps": [_serialise_lap(lap) for lap in activity.laps],
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"timeseries_url": f"activities/{activity_id}.timeseries.json" if timeseries else None,
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"source": source,
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@@ -259,7 +258,7 @@ def build_summary(
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"mmp": metrics.mmp,
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"best_efforts": metrics.best_efforts,
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"best_climb_m": metrics.best_climb_m,
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"vam_curve": metrics.vam_curve,
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"climbing_vam_mh": metrics.climbing_vam_mh,
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"source": _infer_source(activity),
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"privacy": privacy,
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"detail_url": f"activities/{activity_id}.json",
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@@ -303,25 +302,6 @@ def write_athlete_json(summaries: list[dict], output_dir: Path, athlete_config:
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mmps_365 = [s["mmp"] for s in summaries if s.get("mmp") and _is_outdoor(s) and s["started_at"] >= cutoff_365]
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mmps_90 = [s["mmp"] for s in summaries if s.get("mmp") and _is_outdoor(s) and s["started_at"] >= cutoff_90]
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# ── VAM curve aggregation ─────────────────────────────────────────────────
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def _merge_vam_curves(vam_lists: list[list[list[int]]]) -> list[list[int]]:
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best: dict[int, int] = {}
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for vc in vam_lists:
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for d, v in vc:
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if d not in best or v > best[d]:
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best[d] = v
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return [[d, v] for d, v in sorted(best.items())]
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_VAM_SPORTS = {"cycling", "running", "hiking", "walking"}
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def _has_vam(s: dict) -> bool:
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return bool(s.get("vam_curve")) and s.get("sport") in _VAM_SPORTS and _is_outdoor(s)
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all_vams = [s["vam_curve"] for s in summaries if _has_vam(s)]
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vams_365 = [s["vam_curve"] for s in summaries if _has_vam(s) and s["started_at"] >= cutoff_365]
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vams_90 = [s["vam_curve"] for s in summaries if _has_vam(s) and s["started_at"] >= cutoff_90]
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# ── Personal records aggregation ──────────────────────────────────────────
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# records[sport][distance_km] = {time_s, activity_id, started_at, title}
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# best_climb[activity_id] = {climb_m, started_at, title}
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@@ -390,11 +370,6 @@ def write_athlete_json(summaries: list[dict], output_dir: Path, athlete_config:
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"last_365d": _merge_mmps(mmps_365) if mmps_365 else None,
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"last_90d": _merge_mmps(mmps_90) if mmps_90 else None,
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},
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"vam_curve": {
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"all_time": _merge_vam_curves(all_vams) if all_vams else None,
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"last_365d": _merge_vam_curves(vams_365) if vams_365 else None,
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"last_90d": _merge_vam_curves(vams_90) if vams_90 else None,
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},
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"records": {
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sport: _serialise_sport_records(records[sport])
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for sport in SPORTS
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+23
-34
@@ -116,7 +116,7 @@ def _rebuild_athlete_json(data: Path, handle: str | None = None) -> None:
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from bincio.render.merge import parse_sidecar, _apply_sidecar_summary
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targets = [data / handle] if handle else _user_dirs(data)
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_COMPUTED = {"bas_version", "generated_at", "power_curve", "vam_curve", "records", "best_climbs"}
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_COMPUTED = {"bas_version", "generated_at", "power_curve", "records", "best_climbs"}
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for user_dir in targets:
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index_path = user_dir / "index.json"
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if not index_path.exists():
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@@ -377,10 +377,12 @@ def _link_data(site: Path, data: Path) -> None:
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console.print(f"Linked data: [cyan]{target}[/cyan] → [cyan]{public_data}[/cyan]")
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def _recompute_vam(data: Path, handle: str | None = None) -> None:
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"""Recompute climbing_vam_mh and vam_curve for all activities from stored timeseries."""
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def _backfill_vam_summary(data: Path, handle: str | None = None) -> None:
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"""Copy climbing_vam_mh from detail JSONs into index.json summaries.
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Needed once after the vam_curve→climbing_vam_mh-in-summary migration.
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"""
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import json
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from bincio.extract.metrics import compute_vam_from_timeseries
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targets = [data / handle] if handle else _user_dirs(data)
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for user_dir in targets:
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@@ -394,31 +396,18 @@ def _recompute_vam(data: Path, handle: str | None = None) -> None:
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continue
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updated = 0
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for act_path in acts_dir.glob("*.json"):
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if act_path.stem.endswith((".timeseries", ".geojson")):
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continue
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ts_path = acts_dir / f"{act_path.stem}.timeseries.json"
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if not ts_path.exists():
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for s in index_data.get("activities", []):
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if "climbing_vam_mh" in s:
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continue # already backfilled
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act_path = acts_dir / f"{s['id']}.json"
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if not act_path.exists():
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continue
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try:
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detail = json.loads(act_path.read_text(encoding="utf-8"))
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sport = detail.get("sport", "other")
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ts = json.loads(ts_path.read_text(encoding="utf-8"))
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new_vam, new_curve = compute_vam_from_timeseries(ts, sport)
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if (new_vam == detail.get("climbing_vam_mh")
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and new_curve == detail.get("vam_curve")):
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continue
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detail["climbing_vam_mh"] = new_vam
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detail["vam_curve"] = new_curve
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act_path.write_text(
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json.dumps(detail, indent=2, ensure_ascii=False), encoding="utf-8"
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)
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act_id = act_path.stem
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for s in index_data.get("activities", []):
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if s.get("id") == act_id:
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s["vam_curve"] = new_curve
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break
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updated += 1
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vam = detail.get("climbing_vam_mh")
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if vam is not None:
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s["climbing_vam_mh"] = vam
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updated += 1
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except Exception:
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pass
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@@ -426,7 +415,7 @@ def _recompute_vam(data: Path, handle: str | None = None) -> None:
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index_path.write_text(
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json.dumps(index_data, indent=2, ensure_ascii=False), encoding="utf-8"
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)
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console.print(f" [cyan]{user_dir.name}[/cyan]: {updated} activity(ies) updated")
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console.print(f" [cyan]{user_dir.name}[/cyan]: {updated} summary(ies) updated")
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@click.command()
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@@ -452,9 +441,9 @@ def _recompute_vam(data: Path, handle: str | None = None) -> None:
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@click.option("--recompute-elevation", "recompute_elevation", is_flag=True,
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help="Recompute elevation_gain_m/loss_m for all activities from stored timeseries "
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"(run once after upgrading the dropout-skip fix).")
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@click.option("--recompute-vam", "recompute_vam", is_flag=True,
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help="Recompute climbing_vam_mh and vam_curve for all activities from stored "
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"timeseries (run once after adding VAM support).")
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@click.option("--backfill-vam-summary", "backfill_vam_summary", is_flag=True,
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help="Copy climbing_vam_mh from detail JSONs into index.json summaries "
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"(run once after the VAM curve → summary migration).")
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def render(
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config_path: Optional[str],
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data_dir: Optional[str],
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@@ -466,7 +455,7 @@ def render(
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no_build: bool,
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recompute_climbs: bool,
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recompute_elevation: bool,
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recompute_vam: bool,
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backfill_vam_summary: bool,
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) -> None:
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"""Build (or serve) the BincioActivity static site from a BAS data store."""
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@@ -484,9 +473,9 @@ def render(
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console.print("Recomputing elevation gain/loss from timeseries…")
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_recompute_elevation(data, handle=handle)
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if recompute_vam:
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console.print("Recomputing VAM from timeseries…")
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_recompute_vam(data, handle=handle)
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if backfill_vam_summary:
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console.print("Backfilling climbing_vam_mh into summaries…")
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_backfill_vam_summary(data, handle=handle)
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_merge_edits(data, handle=handle)
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_rebuild_athlete_json(data, handle=handle)
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@@ -421,7 +421,7 @@ FEED_PAGE_SIZE = 50
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# Extra fields stripped from the combined feed — preview_coords is the biggest
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# contributor (~24% of shard size) but the feed cards need it for thumbnails,
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# so we keep it. mmp is never displayed in feed cards.
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_COMBINED_FEED_STRIP = _FEED_STRIP | {"mmp", "vam_curve"}
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_COMBINED_FEED_STRIP = _FEED_STRIP | {"mmp"}
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def write_combined_feed(data_dir: Path) -> int:
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@@ -2,7 +2,6 @@
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import { onMount } from 'svelte';
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import type { AthleteJson, BASIndex, ActivitySummary } from '../lib/types';
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import MmpChart from './MmpChart.svelte';
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import VamChart from './VamChart.svelte';
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import RecordsView from './RecordsView.svelte';
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import AthleteDrawer from './AthleteDrawer.svelte';
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import Explore from './Explore.svelte';
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@@ -20,13 +19,12 @@
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let athlete: AthleteJson | null = null;
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let activities: ActivitySummary[] = [];
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let vamActivities: ActivitySummary[] = [];
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let allActivities: ActivitySummary[] = [];
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let loading = true;
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let error: string | null = null;
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let drawerOpen = false;
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type Tab = 'power' | 'vam' | 'records' | 'segments' | 'profile' | 'explore' | 'nerd';
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type Tab = 'power' | 'records' | 'segments' | 'profile' | 'explore' | 'nerd';
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let activeTab: Tab = 'power';
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let mounted = false;
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let isOwner = false;
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@@ -96,7 +94,7 @@
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isOwner = (e as CustomEvent<string>).detail === handle;
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}, { once: true });
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}
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const TABS: Tab[] = ['power', 'vam', 'records', 'segments', 'profile', 'explore', 'nerd'];
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const TABS: Tab[] = ['power', 'records', 'segments', 'profile', 'explore', 'nerd'];
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const rawTab = new URLSearchParams(window.location.search).get('tab');
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const resolved = TABS.includes(rawTab as Tab) ? (rawTab as Tab) : 'power';
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activeTab = (resolved === 'explore' && !isOwner) ? 'power' : resolved;
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@@ -133,7 +131,6 @@
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athlete = resolvedAthlete;
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allActivities = index.activities.filter(a => !isUnlisted(a.privacy));
|
||||
activities = allActivities.filter(a => a.mmp);
|
||||
vamActivities = allActivities.filter(a => a.vam_curve);
|
||||
} catch (e: any) {
|
||||
error = e.message;
|
||||
} finally {
|
||||
@@ -159,19 +156,15 @@
|
||||
return hi >= 900 ? `${lo}+ bpm` : `${lo}–${hi} bpm`;
|
||||
}
|
||||
|
||||
const ALL_TABS: { key: Tab; label: string; ownerOnly?: boolean; requiresVam?: boolean }[] = [
|
||||
const ALL_TABS: { key: Tab; label: string; ownerOnly?: boolean }[] = [
|
||||
{ key: 'power', label: 'Power Curve' },
|
||||
{ key: 'vam', label: 'VAM Curve', requiresVam: true },
|
||||
{ key: 'records', label: 'Records' },
|
||||
{ key: 'segments', label: 'Segments' },
|
||||
{ key: 'profile', label: 'Profile' },
|
||||
{ key: 'explore', label: 'Explore', ownerOnly: true },
|
||||
{ key: 'nerd', label: 'Nerd Corner', ownerOnly: true },
|
||||
{ key: 'explore', label: 'Explore', ownerOnly: true },
|
||||
{ key: 'nerd', label: 'Nerd Corner', ownerOnly: true },
|
||||
];
|
||||
$: TABS = ALL_TABS.filter(t =>
|
||||
(!t.ownerOnly || isOwner) &&
|
||||
(!t.requiresVam || athlete?.vam_curve?.all_time != null)
|
||||
);
|
||||
$: TABS = ALL_TABS.filter(t => !t.ownerOnly || isOwner);
|
||||
</script>
|
||||
|
||||
{#if loading}
|
||||
@@ -223,16 +216,6 @@
|
||||
<p class="text-zinc-500 text-sm">No power data found. Make sure your activities include power meter data.</p>
|
||||
{/if}
|
||||
|
||||
<!-- VAM Curve tab -->
|
||||
{:else if activeTab === 'vam'}
|
||||
{#if athlete.vam_curve?.all_time}
|
||||
<div class="bg-zinc-900 rounded-xl p-4 border border-zinc-800">
|
||||
<VamChart {athlete} activities={vamActivities} />
|
||||
</div>
|
||||
{:else}
|
||||
<p class="text-zinc-500 text-sm">No climbing data found.</p>
|
||||
{/if}
|
||||
|
||||
<!-- Records tab -->
|
||||
{:else if activeTab === 'records'}
|
||||
<RecordsView {athlete} {base} />
|
||||
|
||||
@@ -5,7 +5,7 @@
|
||||
|
||||
export let activities: ActivitySummary[] = [];
|
||||
|
||||
type Metric = 'distance' | 'elevation' | 'time';
|
||||
type Metric = 'distance' | 'elevation' | 'time' | 'vam';
|
||||
type Granularity = 'week' | 'month';
|
||||
|
||||
let metric: Metric = 'distance';
|
||||
@@ -15,11 +15,13 @@
|
||||
distance: 'Distance (km)',
|
||||
elevation: 'Elevation gain (m)',
|
||||
time: 'Moving time (h)',
|
||||
vam: 'Avg climbing VAM (m/h)',
|
||||
};
|
||||
const METRIC_FMT: Record<Metric, (v: number) => string> = {
|
||||
distance: v => `${Math.round(v)} km`,
|
||||
elevation: v => `${Math.round(v)} m`,
|
||||
time: v => `${v.toFixed(1)} h`,
|
||||
vam: v => `${Math.round(v)} m/h`,
|
||||
};
|
||||
|
||||
// Cool→warm ramp for past years; current year is always blue-400
|
||||
@@ -57,18 +59,34 @@
|
||||
function buildData(acts: ActivitySummary[], m: Metric, g: Granularity) {
|
||||
const curPeriod = g === 'week' ? weekOfYear(_now) : _now.getMonth() + 1;
|
||||
const byYear = new Map<number, Map<number, number>>();
|
||||
const byYearCnt = new Map<number, Map<number, number>>(); // for VAM averaging
|
||||
|
||||
for (const act of acts) {
|
||||
if (!act.started_at) continue;
|
||||
if (m === 'vam' && act.climbing_vam_mh == null) continue;
|
||||
const d = new Date(act.started_at);
|
||||
const yr = d.getFullYear();
|
||||
const per = g === 'week' ? weekOfYear(d) : d.getMonth() + 1;
|
||||
const val = m === 'distance' ? (act.distance_m ?? 0) / 1000
|
||||
: m === 'elevation' ? (act.elevation_gain_m ?? 0)
|
||||
: m === 'vam' ? (act.climbing_vam_mh ?? 0)
|
||||
: (act.moving_time_s ?? 0) / 3600;
|
||||
if (!byYear.has(yr)) byYear.set(yr, new Map());
|
||||
const ym = byYear.get(yr)!;
|
||||
ym.set(per, (ym.get(per) ?? 0) + val);
|
||||
if (!byYear.has(yr)) byYear.set(yr, new Map());
|
||||
if (!byYearCnt.has(yr)) byYearCnt.set(yr, new Map());
|
||||
const ym = byYear.get(yr)!;
|
||||
const ymc = byYearCnt.get(yr)!;
|
||||
ym.set(per, (ym.get(per) ?? 0) + val);
|
||||
ymc.set(per, (ymc.get(per) ?? 0) + 1);
|
||||
}
|
||||
|
||||
// VAM: convert sums to averages
|
||||
if (m === 'vam') {
|
||||
for (const [yr, ym] of byYear) {
|
||||
const ymc = byYearCnt.get(yr)!;
|
||||
for (const [per, sum] of ym) {
|
||||
ym.set(per, sum / (ymc.get(per) ?? 1));
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
const years = [...byYear.keys()].sort();
|
||||
@@ -241,6 +259,7 @@
|
||||
<button class="pill" class:active={metric === 'distance'} on:click={() => metric = 'distance'}>Distance</button>
|
||||
<button class="pill" class:active={metric === 'elevation'} on:click={() => metric = 'elevation'}>Elevation</button>
|
||||
<button class="pill" class:active={metric === 'time'} on:click={() => metric = 'time'}>Time</button>
|
||||
<button class="pill" class:active={metric === 'vam'} on:click={() => metric = 'vam'}>Climbing VAM</button>
|
||||
</div>
|
||||
<div class="pill-group">
|
||||
<button class="pill" class:active={granularity === 'week'} on:click={() => granularity = 'week'}>Weekly</button>
|
||||
@@ -250,8 +269,10 @@
|
||||
|
||||
<div bind:this={chartEl} class="w-full min-h-[320px]"></div>
|
||||
|
||||
<p class="section-label">Cumulative</p>
|
||||
<div bind:this={chartCumEl} class="w-full min-h-[320px]"></div>
|
||||
{#if metric !== 'vam'}
|
||||
<p class="section-label">Cumulative</p>
|
||||
<div bind:this={chartCumEl} class="w-full min-h-[320px]"></div>
|
||||
{/if}
|
||||
|
||||
{#if !rows.length}
|
||||
<p class="text-zinc-500 text-sm mt-4">No activity data to display.</p>
|
||||
|
||||
@@ -1,188 +0,0 @@
|
||||
<script lang="ts">
|
||||
import { onMount } from 'svelte';
|
||||
import * as Plot from '@observablehq/plot';
|
||||
import type { AthleteJson, MmpCurve, ActivitySummary } from '../lib/types';
|
||||
|
||||
export let athlete: AthleteJson;
|
||||
export let activities: ActivitySummary[] = [];
|
||||
|
||||
type RangeKey = 'all_time' | 'last_365d' | 'last_90d' | string;
|
||||
|
||||
interface Season { name: string; start: string; end: string }
|
||||
const seasons: Season[] = (athlete as any).seasons ?? [];
|
||||
|
||||
let selectedRanges: Set<RangeKey> = new Set(['all_time']);
|
||||
|
||||
const PRESET_LABELS: Record<string, string> = {
|
||||
all_time: 'All time',
|
||||
last_365d: 'Last 365 d',
|
||||
last_90d: 'Last 90 d',
|
||||
};
|
||||
|
||||
const PALETTE = [
|
||||
'#34d399', // emerald-400
|
||||
'#f97316', // orange-500
|
||||
'#60a5fa', // blue-400
|
||||
'#a78bfa', // violet-400
|
||||
'#f43f5e', // rose-500
|
||||
'#facc15', // yellow-400
|
||||
'#22d3ee', // cyan-400
|
||||
];
|
||||
|
||||
function curveColor(key: RangeKey, index: number): string {
|
||||
return PALETTE[index % PALETTE.length];
|
||||
}
|
||||
|
||||
function mergeVams(curves: MmpCurve[]): MmpCurve {
|
||||
const best = new Map<number, number>();
|
||||
for (const curve of curves) {
|
||||
for (const [d, v] of curve) {
|
||||
const prev = best.get(d);
|
||||
if (prev === undefined || v > prev) best.set(d, v);
|
||||
}
|
||||
}
|
||||
return [...best.entries()].sort((a, b) => a[0] - b[0]) as MmpCurve;
|
||||
}
|
||||
|
||||
function vamForRange(key: RangeKey): MmpCurve | null {
|
||||
if (key in PRESET_LABELS) {
|
||||
return athlete.vam_curve?.[key as keyof typeof athlete.vam_curve] ?? null;
|
||||
}
|
||||
const season = seasons.find(s => s.name === key);
|
||||
if (!season) return null;
|
||||
const curves = activities
|
||||
.filter(a => a.vam_curve && a.started_at >= season.start && a.started_at <= season.end + 'T23:59:59')
|
||||
.map(a => a.vam_curve!);
|
||||
return curves.length ? mergeVams(curves) : null;
|
||||
}
|
||||
|
||||
let chartEl: HTMLElement;
|
||||
|
||||
function formatDuration(s: number): string {
|
||||
if (s < 60) return `${s}s`;
|
||||
if (s < 3600) return `${Math.round(s / 60)}min`;
|
||||
return `${s / 3600}h`;
|
||||
}
|
||||
|
||||
$: selectedKeys = [...selectedRanges];
|
||||
|
||||
$: plotData = selectedKeys.flatMap((key, i) => {
|
||||
const curve = vamForRange(key);
|
||||
if (!curve) return [];
|
||||
return curve.map(([d, v]) => ({ d, v, label: key }));
|
||||
});
|
||||
|
||||
$: colorMap = Object.fromEntries(selectedKeys.map((k, i) => [k, curveColor(k, i)]));
|
||||
|
||||
function getAxisColor() {
|
||||
return document.documentElement.getAttribute('data-theme') === 'light' ? '#52525b' : '#a1a1aa';
|
||||
}
|
||||
|
||||
function renderChart(data: typeof plotData, cmap: typeof colorMap) {
|
||||
if (!chartEl) return;
|
||||
chartEl.innerHTML = '';
|
||||
if (!data.length) return;
|
||||
|
||||
const labelFn = (key: string) => PRESET_LABELS[key] ?? key;
|
||||
|
||||
const chart = Plot.plot({
|
||||
width: chartEl.clientWidth || 700,
|
||||
height: 320,
|
||||
marginLeft: 60,
|
||||
marginBottom: 40,
|
||||
style: { background: 'transparent', color: getAxisColor() },
|
||||
x: {
|
||||
type: 'log',
|
||||
label: 'Duration',
|
||||
tickFormat: (d: number) => formatDuration(d),
|
||||
grid: true,
|
||||
domain: [data[0]?.d ?? 60, Math.max(3600, ...data.map(d => d.d))],
|
||||
},
|
||||
y: {
|
||||
label: 'VAM (m/h)',
|
||||
grid: true,
|
||||
zero: true,
|
||||
},
|
||||
color: {
|
||||
domain: selectedKeys,
|
||||
range: selectedKeys.map((k, i) => curveColor(k, i)),
|
||||
legend: selectedKeys.length > 1,
|
||||
},
|
||||
marks: [
|
||||
Plot.line(data, {
|
||||
x: 'd',
|
||||
y: 'v',
|
||||
stroke: 'label',
|
||||
strokeWidth: 2,
|
||||
curve: 'monotone-x',
|
||||
}),
|
||||
Plot.dot(data, {
|
||||
x: 'd',
|
||||
y: 'v',
|
||||
fill: 'label',
|
||||
r: 3,
|
||||
tip: true,
|
||||
title: (d: any) => `${labelFn(d.label)}\n${formatDuration(d.d)}: ${d.v.toLocaleString()} m/h`,
|
||||
}),
|
||||
],
|
||||
});
|
||||
|
||||
chartEl.appendChild(chart);
|
||||
}
|
||||
|
||||
$: renderChart(plotData, colorMap);
|
||||
|
||||
let currentPlotData = plotData;
|
||||
let currentColorMap = colorMap;
|
||||
$: currentPlotData = plotData;
|
||||
$: currentColorMap = colorMap;
|
||||
|
||||
onMount(() => {
|
||||
const ro = new ResizeObserver(() => renderChart(currentPlotData, currentColorMap));
|
||||
ro.observe(chartEl);
|
||||
const mo = new MutationObserver(() => renderChart(currentPlotData, currentColorMap));
|
||||
mo.observe(document.documentElement, { attributes: true, attributeFilter: ['data-theme'] });
|
||||
return () => { ro.disconnect(); mo.disconnect(); };
|
||||
});
|
||||
|
||||
function toggleRange(key: RangeKey) {
|
||||
const next = new Set(selectedRanges);
|
||||
if (next.has(key)) {
|
||||
if (next.size > 1) next.delete(key);
|
||||
} else {
|
||||
next.add(key);
|
||||
}
|
||||
selectedRanges = next;
|
||||
}
|
||||
|
||||
const allRangeKeys = [
|
||||
...Object.keys(PRESET_LABELS),
|
||||
...seasons.map(s => s.name),
|
||||
];
|
||||
</script>
|
||||
|
||||
<style>
|
||||
:global(.plot-tip text) { fill: #18181b !important; }
|
||||
</style>
|
||||
|
||||
<div class="flex flex-wrap gap-2 mb-4">
|
||||
{#each allRangeKeys as key, i}
|
||||
{@const active = selectedRanges.has(key)}
|
||||
{@const color = curveColor(key, i)}
|
||||
<button
|
||||
on:click={() => toggleRange(key)}
|
||||
class="px-3 py-1 rounded-full text-sm font-medium border transition-colors"
|
||||
style={active
|
||||
? `background:${color}22; border-color:${color}; color:${color}`
|
||||
: 'background:transparent; border-color:#3f3f46; color:#71717a'}
|
||||
>
|
||||
{PRESET_LABELS[key] ?? key}
|
||||
</button>
|
||||
{/each}
|
||||
</div>
|
||||
|
||||
<div bind:this={chartEl} class="w-full min-h-[320px]"></div>
|
||||
|
||||
{#if !plotData.length}
|
||||
<p class="text-zinc-500 text-sm mt-4">No VAM data for the selected range.</p>
|
||||
{/if}
|
||||
@@ -36,17 +36,10 @@ export interface BestClimb {
|
||||
title: string;
|
||||
}
|
||||
|
||||
export interface AthleteVamCurve {
|
||||
all_time: MmpCurve | null;
|
||||
last_365d: MmpCurve | null;
|
||||
last_90d: MmpCurve | null;
|
||||
}
|
||||
|
||||
export interface AthleteJson {
|
||||
bas_version: string;
|
||||
generated_at: string;
|
||||
power_curve: AthletePowerCurve;
|
||||
vam_curve?: AthleteVamCurve | null;
|
||||
records?: Record<string, Record<string, EffortRecord | ValueRecord>>;
|
||||
best_climbs?: BestClimb[];
|
||||
max_hr?: number;
|
||||
@@ -73,7 +66,7 @@ export interface ActivitySummary {
|
||||
avg_cadence_rpm: number | null;
|
||||
avg_power_w: number | null;
|
||||
mmp: MmpCurve | null;
|
||||
vam_curve?: MmpCurve | null;
|
||||
climbing_vam_mh?: number | null;
|
||||
source: string | null;
|
||||
privacy: Privacy;
|
||||
detail_url: string | null;
|
||||
@@ -130,7 +123,6 @@ export interface ActivityDetail extends Omit<ActivitySummary, 'detail_url' | 'tr
|
||||
/** URL to fetch the timeseries — present for server-extracted activities. */
|
||||
timeseries_url?: string | null;
|
||||
mmp: MmpCurve | null;
|
||||
climbing_vam_mh?: number | null;
|
||||
strava_id: string | null;
|
||||
duplicate_of: string | null;
|
||||
source_file?: string | null;
|
||||
|
||||
Reference in New Issue
Block a user