309bcc7475
paper-backfill calls each as_of-aware sleeve's current_weights(as_of) once per date (~1650 dates). UnlockShortRunner + StableReversionRunner re-did date-independent work on every call: rebuilt events_norm, re-ran eligibility, and full-panel-scanned+sorted just to find the latest day <= as_of (O(panel) per call -> O(N*panel) over the backfill). - UnlockShortRunner: memoize events_norm (now a property), _eligible() result, and the sorted all-days axis; current_weights finds the latest day via bisect_right over the memoized axis. run() reuses the same caches. - StableReversionRunner: memoize the sorted all-days axis; current_weights uses bisect_right; run() reuses it. Bit-identical output (drives the live paper track + replay; live==replay): golden sweep tests recompute expected weights via the naive pre-optimization logic across ~20 as_of dates (before-data, mid-stream, in/out of unlock window, after last day) and assert exact dict equality. Verified the references also match the old src (git-stash check). Per-call complexity O(panel) -> O(log days + active names). Full suite: 693 passed. TsTrendForward.current_weights left alone: it does no thrown-away date-independent work per call (load_panel is an O(1) ref in backfill; the per-symbol sort is date-dependent on the closes feeding the signal). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
57 lines
2.4 KiB
Python
57 lines
2.4 KiB
Python
from fxhnt.application.stablecoin_runner import StableReversionRunner
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def test_current_weights_shorts_rich_names():
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# panel = {symbol: {epoch_day: close}}; day 20000 has USDT rich (>1+thresh), DAI at peg
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panel = {"USDTUSD": {20000: 1.01}, "DAIUSD": {20000: 1.0001}}
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r = StableReversionRunner(panel, thresh_bp=50.0)
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w = r.current_weights("epoch:20000")
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assert w["USDTUSD"] < 0 # rich -> short
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assert w.get("DAIUSD", 0.0) == 0.0
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def test_current_weights_uses_latest_day_on_or_before_as_of():
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panel = {"USDTUSD": {19990: 1.0001, 20000: 1.02}}
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r = StableReversionRunner(panel, thresh_bp=50.0)
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# day 19990 not rich -> {}; day 20000 rich -> short
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assert r.current_weights("epoch:19995") == {}
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assert r.current_weights("epoch:20005")["USDTUSD"] < 0
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def test_current_weights_empty_when_no_data():
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r = StableReversionRunner({"USDTUSD": {20000: 1.01}}, thresh_bp=50.0)
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assert r.current_weights("epoch:19000") == {}
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def _reference_current_weights(panel, thresh_bp, as_of):
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"""Recompute current_weights via the NAIVE pre-optimization logic (full-panel scan/sort for the
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latest day every call) so the golden sweep pins the memoized+bisect impl to a from-scratch baseline."""
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from fxhnt.application._date_axis import as_of_day
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from fxhnt.domain.stablecoin_reversion import short_rich_weights
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th = thresh_bp / 1e4
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day_lim = as_of_day(as_of)
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days = sorted({d for s in panel.values() for d in s if d <= day_lim})
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if not days:
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return {}
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d = days[-1]
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dev = {s: series[d] - 1.0 for s, series in panel.items()
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if d in series and series[d] > 0}
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return short_rich_weights(dev, th)
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def test_golden_sweep_bit_identical():
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# multi-symbol panel over many days, mixed rich/cheap/at-peg; sweep ~20 as_of dates incl.
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# before-data, mid-stream (incl. a day where no name is rich -> {}), and after the last day.
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panel = {
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"USDTUSD": {d: 1.0 + 0.0001 * ((d % 7) - 3) for d in range(19990, 20010)},
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"DAIUSD": {d: 1.0 + 0.0003 * ((d % 5) - 2) for d in range(19990, 20010)},
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"TUSDUSD": {d: 1.0 + 0.01 if d % 3 == 0 else 1.0 for d in range(19990, 20010)},
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}
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thresh_bp = 50.0
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r = StableReversionRunner(panel, thresh_bp=thresh_bp)
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as_ofs = [f"epoch:{x}" for x in range(19985, 20012)] # before-data .. after-last-day
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for ao in as_ofs:
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expected = _reference_current_weights(panel, thresh_bp, ao)
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assert r.current_weights(ao) == expected, ao
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