feat(family-11): add DeMark suite (TD Setup, Sequential, DeMarker, REI, Pressure) (#48)
* feat(family-11): add DeMark suite (TD Setup, Sequential, DeMarker, REI, Pressure)
Family 11 (DeMark) was previously empty; this PR adds five
streaming-first DeMark indicators in one batch.
- **TD Setup** (`TdSetup`): parameterised buy/sell setup counter.
Counts consecutive bars whose close is less-than (buy) or
greater-than (sell) the close `lookback` bars earlier, saturating
at `target`. Emits a signed `f64` so callers read direction from
the sign and run length from the magnitude. Classic config:
`lookback = 4`, `target = 9`.
- **TD Sequential** (`TdSequential`): the canonical Setup + Countdown
exhaustion pattern. Output struct `{ setup, countdown, direction }`
exposes both phase counts as signed numbers plus the active
countdown direction (+1 buy / -1 sell / 0 none). Countdown
activates when a setup completes and tracks the close-vs-high/low
comparison `countdown_lookback` bars back, capped at
`countdown_target`. Classic: 4/9/2/13.
- **TD DeMarker** (`TdDeMarker`): bounded [0, 1] oscillator from the
rolling average of upward high expansion (DeMax) and downward low
expansion (DeMin). Falls back to the neutral 0.5 on a flat market
(denominator zero).
- **TD REI** (`TdRei`): Range Expansion Index, bounded [-100, 100].
Per-bar numerator gated on a range-overlap condition vs the bars
5 and 6 back, normalised by a `period`-bar sum of absolute moves.
Classic period = 5. Saturates at +100 in a slow steady uptrend
and at -100 in the mirror downtrend; emits 0 on a flat market.
- **TD Pressure** (`TdPressure`): volume-weighted buying / selling
pressure normalised to [-100, 100]. Per-bar pressure is the
intra-bar close-vs-open ratio scaled by volume; the output is the
rolling mean divided by the rolling mean volume. Zero-range bars
contribute zero (avoid the undefined ratio) and a flat zero-volume
window falls back to 0.
Bindings: all five exposed in Python (`ta.TDSetup`, `ta.TDSequential`,
`ta.TDDeMarker`, `ta.TDREI`, `ta.TDPressure`), Node (`wickra.TDSetup`
etc.), and WASM. Multi-output classes (`TDSequential`) return either
a struct `{ setup, countdown, direction }` per bar (streaming) or a
flat interleaved Float64Array of length `3 * n` (batch).
Tests: 47 unit tests across the five new core files (pure-trend
saturation, flat-market neutral fallback, batch-equals-streaming,
zero-parameter rejection, reset semantics, accessors). Python
test_new_indicators.py picks up all five plus a multi-output TD
Sequential block. Node indicators.test.js picks up all five.
Reference values added to test_known_values.py.
Fuzz: candle fuzz target sweeps all five DeMark indicators with the
existing `Vec<f64>` -> `Vec<Candle>` driver.
Benches: BTCUSDT 1-minute dataset benches for each DeMark indicator
in `crates/wickra/benches/indicators.rs`.
Docs: README family table gains a "DeMark" row; indicator counter
bumped 71 -> 76. CHANGELOG entry added under [Unreleased]. Wiki
drafts (deep-dive pages + Sidebar / Overview / Warmup-Periods / Home
deltas) live under `indicator-ideas/families/wiki/family-11-demark/`
for manual merge into the wiki repo.
* feat(family-11): add 7 missing DeMark indicators
Complete the DeMark suite (family 11) with the seven indicators not
covered by the first commit: TD Combo, TD Countdown, TD Lines (TDST),
TD Range Projection, TD Differential, TD Open, and TD Risk Level.
- TdCombo: aggressive countdown variant with three strictness rules
on top of the classic close-vs-low/high lookback rule (monotone
low/high, monotone close vs prior bar).
- TdCountdown: standalone 13-bar countdown packaging only the signed
countdown count (the setup machine runs internally).
- TdLines: TDST horizontal support/resistance levels from the
highest-high / lowest-low bars of the most-recently-completed
setup, exposed as a multi-output struct.
- TdRangeProjection: DeMark X-projection of the next bar's high and
low from the current bar's OHLC via an open-vs-close-weighted
pivot (three branches: close<open, close>open, close==open).
- TdDifferential: two-bar buying-pressure vs selling-pressure
reversal pattern emitting +1/-1/0.
- TdOpen: gap-and-fade reversal pattern (open outside prior range
with subsequent recovery into it) emitting +1/-1/0.
- TdRiskLevel: protective stop levels derived from the setup
extreme bar +/- its true range.
All seven are wired through Rust core, Python, Node and WASM
bindings, registered in the candle-stream fuzz target, given
benchmark entries on the BTCUSDT 1-minute dataset, and covered by
streaming-vs-batch equivalence, reference-value, lifecycle and
input-validation tests on the Python and Node sides. README counter
moves 76 -> 83 and the CHANGELOG "family 11" entry is extended to
list all twelve indicators.
* fix(td_risk_level tests): check first emission at idx 12, not last bar
TdRiskLevel re-ratchets the sell-risk level on each subsequent setup
completion, so a strictly rising series produces 22.0 at idx 19 (latest
setup) rather than 15.0 (first setup). The test comment already named
idx 12 as the reference; switch the assertion from out[-1] to out[12]
to match the reference computation.
* test(family-11): cover buy-direction branches in TD indicators
Add downtrend tests to TdSequential, TdCombo and TdCountdown so the
buy-side countdown/combo increment branches are exercised; remove an
empty `if buy_countdown == target {}` block in TdSequential whose
behavior is already enforced by the outer strict `<` guard.
Closes codecov/patch gaps reported on PR #48 (10 missed lines across
the three files).
This commit is contained in:
kingchenc
@@ -332,6 +332,113 @@ def test_obv_cumulative_known_sequence():
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np.testing.assert_allclose(out, [0.0, 20.0, -10.0, -10.0, 0.0])
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# --- DeMark family ---------------------------------------------------------
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def test_td_setup_buy_setup_completes_at_minus_9_uptrend():
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# Strictly rising closes -> every bar has close > close[-4] (sell setup);
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# the streak hits -9 at index 12 and caps there.
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h = np.arange(2.0, 22.0)
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l = h - 1.0
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c = h - 0.5
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out = ta.TDSetup(4, 9).batch(h, l, c)
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assert out[12] == pytest.approx(-9.0)
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assert out[-1] == pytest.approx(-9.0)
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def test_td_demarker_downtrend_pegs_at_zero():
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n = 20
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h = np.arange(30.0, 30.0 - n, -1.0)
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l = h - 2.0
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out = ta.TDDeMarker(5).batch(h, l)
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assert out[-1] == pytest.approx(0.0)
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def test_td_pressure_pure_bearish_yields_minus_100():
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n = 20
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open_ = np.full(n, 11.0)
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high = np.full(n, 11.0)
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low = np.full(n, 9.0)
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close = np.full(n, 9.0)
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volume = np.full(n, 100.0)
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out = ta.TDPressure(5).batch(open_, high, low, close, volume)
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assert out[-1] == pytest.approx(-100.0)
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def test_td_combo_uptrend_completes_to_minus_13():
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# Pure uptrend -> setup completes, then combo conditions (close>=high[-2],
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# high>=prev.high, close>prev.close) all hold for every subsequent bar
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# -> sell combo saturates at -13.
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n = 40
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high = np.arange(1.0, 1.0 + n) + 0.5
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low = high - 1.0
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close = high - 0.5
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out = ta.TDCombo().batch(high, low, close)
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assert out[-1] == pytest.approx(-13.0)
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def test_td_countdown_uptrend_completes_to_minus_13():
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n = 40
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high = np.arange(1.0, 1.0 + n) + 0.5
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low = high - 1.0
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close = high - 0.5
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out = ta.TDCountdown().batch(high, low, close)
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assert out[-1] == pytest.approx(-13.0)
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def test_td_range_projection_doji_reference():
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# open=close=10, high=12, low=9 -> doji branch.
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# pivot_sum = 12 + 9 + 2*10 = 41; half = 20.5.
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# projHigh = 20.5 - 9 = 11.5; projLow = 20.5 - 12 = 8.5.
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out = ta.TDRangeProjection().batch(
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np.array([10.0]), np.array([12.0]), np.array([9.0]), np.array([10.0])
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)
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assert out[0, 0] == pytest.approx(11.5)
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assert out[0, 1] == pytest.approx(8.5)
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def test_td_open_sell_signal_reference():
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# Prev high=12. Curr open=13 > 12, curr low=11 < 12 -> -1.
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td = ta.TDOpen()
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assert td.update((10.0, 12.0, 9.0, 11.0, 1.0, 0)) is None
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assert td.update((13.0, 13.5, 11.0, 11.5, 1.0, 1)) == pytest.approx(-1.0)
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def test_td_differential_sell_signal_reference():
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# Prev high=10, low=8, close=9: buying=1, selling=1.
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# Curr high=12, low=9.8, close=10.5: close>prev.close, selling=1.5>1,
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# buying=0.7<1 -> sell signal -1.
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td = ta.TDDifferential()
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assert td.update((9.0, 10.0, 8.0, 9.0, 1.0, 0)) is None
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assert td.update((10.5, 12.0, 9.8, 10.5, 1.0, 1)) == pytest.approx(-1.0)
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def test_td_lines_uptrend_support_reference():
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# Strictly rising series -> sell setup completes at idx 12, the
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# lowest low across bars 4..=12 is the low at idx 4 = 4.5.
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n = 20
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high = np.arange(1.0, 1.0 + n) + 0.5
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low = high - 1.0
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close = high - 0.5
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out = ta.TDLines().batch(high, low, close)
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assert math.isnan(out[-1, 0])
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assert out[-1, 1] == pytest.approx(4.5)
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def test_td_risk_level_uptrend_sell_risk_reference():
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# Strictly rising series -> sell setup completes at idx 12 with high
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# 13.5 and true range 1.5 -> sell_risk = 13.5 + 1.5 = 15.0.
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# Subsequent setups re-ratchet the level, so we check the first emission
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# at idx 12 rather than the latest value.
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n = 20
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high = np.arange(1.0, 1.0 + n) + 0.5
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low = high - 1.0
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close = high - 0.5
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out = ta.TDRiskLevel().batch(high, low, close)
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assert math.isnan(out[12, 0])
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assert out[12, 1] == pytest.approx(15.0)
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def test_percentage_trailing_stop_seed_and_ratchet():
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# 10% trail: first close 100 -> stop 90; next 110 -> stop max(90, 99) = 99.
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s = ta.PercentageTrailingStop(10.0)
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@@ -274,6 +274,30 @@ CANDLE_SCALAR = {
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lambda: ta.YangZhangVolatility(20, 252),
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lambda ind, h, l, c, v: ind.batch(c, h, l, c),
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),
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"TDSetup": (
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lambda: ta.TDSetup(4, 9),
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lambda ind, h, l, c, v: ind.batch(h, l, c),
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),
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"TDDeMarker": (
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lambda: ta.TDDeMarker(14),
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lambda ind, h, l, c, v: ind.batch(h, l),
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),
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"TDREI": (
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lambda: ta.TDREI(5),
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lambda ind, h, l, c, v: ind.batch(h, l),
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),
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"TDCombo": (
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lambda: ta.TDCombo(4, 9, 2, 13),
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lambda ind, h, l, c, v: ind.batch(h, l, c),
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),
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"TDCountdown": (
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lambda: ta.TDCountdown(4, 9, 2, 13),
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lambda ind, h, l, c, v: ind.batch(h, l, c),
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),
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"TDDifferential": (
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lambda: ta.TDDifferential(),
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lambda ind, h, l, c, v: ind.batch(h, l, c),
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),
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}
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@@ -526,6 +550,55 @@ def test_multi_scalar_streaming_matches_batch(name, ohlcv):
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assert _eq_nan(batch, np.array(rows, dtype=np.float64)), f"{name} mismatch"
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# --- TD Pressure (OHLCV-input) -------------------------------------------
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def test_td_pressure_streaming_matches_batch(ohlcv):
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high, low, close, volume = ohlcv
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open_ = close.copy() # TD Pressure needs open; reuse close as the open column.
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batch = ta.TDPressure(5).batch(open_, high, low, close, volume)
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assert batch.shape == close.shape
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streamer = ta.TDPressure(5)
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streamed = []
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for i in range(close.size):
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candle = (
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float(open_[i]),
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float(high[i]),
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float(low[i]),
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float(close[i]),
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float(volume[i]),
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i,
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)
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v = streamer.update(candle)
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streamed.append(math.nan if v is None else float(v))
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assert _eq_nan(batch, np.array(streamed, dtype=np.float64))
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# --- TD Sequential (3-column multi-output) ------------------------------
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def test_td_sequential_streaming_matches_batch(ohlcv):
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high, low, close, volume = ohlcv
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batch = ta.TDSequential().batch(high, low, close)
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assert batch.shape == (close.size, 3)
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streamer = ta.TDSequential()
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rows = []
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for i in range(close.size):
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candle = (
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float(close[i]),
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float(high[i]),
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float(low[i]),
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float(close[i]),
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float(volume[i]),
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i,
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)
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v = streamer.update(candle)
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rows.append([math.nan, math.nan, math.nan] if v is None else list(v))
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assert _eq_nan(batch, np.array(rows, dtype=np.float64))
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# --- ZeroLagMACD (scalar input, 3-tuple output: macd / signal / histogram) -
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@@ -815,6 +888,124 @@ def test_z_score_reference():
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assert out[1] == pytest.approx(1.0)
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def test_td_setup_pure_uptrend_reaches_minus_9():
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# Every close is strictly greater than four bars ago -> sell-setup -9.
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h = np.arange(2.0, 22.0)
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l = h - 1.0
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c = h - 0.5
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out = ta.TDSetup(4, 9).batch(h, l, c)
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# Setup completes at index 12 (warmup is 5 -> first emit at index 4 with
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# value -1, increments to -9 at index 12).
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assert out[12] == pytest.approx(-9.0)
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def test_td_demarker_uptrend_pegs_at_one():
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# Strictly higher highs, strictly higher lows -> DeMax > 0, DeMin == 0
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# -> indicator == 1 after warmup.
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h = np.arange(11.0, 31.0)
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l = h - 2.0
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out = ta.TDDeMarker(5).batch(h, l)
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assert out[-1] == pytest.approx(1.0)
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def test_td_demarker_flat_market_emits_05():
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# All highs and lows equal -> denominator is zero -> neutral fallback 0.5.
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h = np.full(20, 11.0)
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l = np.full(20, 9.0)
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out = ta.TDDeMarker(5).batch(h, l)
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assert out[-1] == pytest.approx(0.5)
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def test_td_pressure_pure_bullish_yields_100():
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# Every bar closes at its high (close == high, open == low) -> per-bar
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# pressure ratio is +1 -> indicator == 100.
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n = 20
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open_ = np.full(n, 9.0)
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high = np.full(n, 11.0)
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low = np.full(n, 9.0)
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close = np.full(n, 11.0)
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volume = np.full(n, 100.0)
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out = ta.TDPressure(5).batch(open_, high, low, close, volume)
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assert out[-1] == pytest.approx(100.0)
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def test_td_combo_uptrend_saturates_at_minus_13():
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# Strictly increasing closes -> sell setup completes; combo conditions
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# (close >= high[i-2], high[i] >= high[i-1], close > close[i-1]) all
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# hold so combo saturates at -13.
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n = 40
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high = np.arange(1.0, 1.0 + n) + 0.5
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low = high - 1.0
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close = high - 0.5
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out = ta.TDCombo().batch(high, low, close)
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assert out[-1] == pytest.approx(-13.0)
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def test_td_countdown_uptrend_saturates_at_minus_13():
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n = 40
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high = np.arange(1.0, 1.0 + n) + 0.5
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low = high - 1.0
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close = high - 0.5
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out = ta.TDCountdown().batch(high, low, close)
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assert out[-1] == pytest.approx(-13.0)
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def test_td_lines_uptrend_sets_support_at_first_run_low():
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# Strictly rising closes -> sell setup completes at idx 12; the
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# lowest low among the setup bars (idx 4..=12) is the low at idx 4.
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n = 20
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high = np.arange(1.0, 1.0 + n) + 0.5
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low = high - 1.0
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close = high - 0.5
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out = ta.TDLines().batch(high, low, close)
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# support is column 1; resistance is NaN at -1.
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assert math.isnan(out[-1, 0])
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# low at idx 4 = 5 + 0.5 - 1.0 = 4.5.
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assert out[-1, 1] == pytest.approx(4.5)
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def test_td_range_projection_bullish_bar_reference():
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# open=10, high=12, low=9, close=11 (close > open) ->
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# pivot_sum = 2*12 + 9 + 11 = 44; half = 22.
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# projHigh = 22 - 9 = 13; projLow = 22 - 12 = 10.
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out = ta.TDRangeProjection().batch(
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np.array([10.0]), np.array([12.0]), np.array([9.0]), np.array([11.0])
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)
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assert out[0, 0] == pytest.approx(13.0)
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assert out[0, 1] == pytest.approx(10.0)
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def test_td_differential_buy_signal_reference():
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# Bar 0: high=10, low=8, close=9 -> warmup, returns None.
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# Bar 1: high=9, low=7, close=8.5 -> close < prev.close, more buying
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# pressure (1.5 > 1), less selling pressure (0.5 < 1) -> +1.
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td = ta.TDDifferential()
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assert td.update((9.0, 10.0, 8.0, 9.0, 1.0, 0)) is None
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assert td.update((8.5, 9.0, 7.0, 8.5, 1.0, 1)) == pytest.approx(1.0)
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def test_td_open_buy_signal_reference():
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# Prev bar low=10. Curr open=9 < 10, curr high=11 > 10 -> +1.
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td = ta.TDOpen()
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assert td.update((10.0, 11.0, 10.0, 10.5, 1.0, 0)) is None
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assert td.update((9.0, 11.0, 8.5, 9.5, 1.0, 1)) == pytest.approx(1.0)
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def test_td_risk_level_uptrend_sets_sell_risk():
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# Strictly rising closes -> sell setup completes at idx 12.
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# The highest high is at idx 12 (= 13.5) with true range 1.5 ->
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# sell_risk = 13.5 + 1.5 = 15.0. Subsequent setups re-ratchet the level
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# so we check the first emission at idx 12.
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n = 20
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high = np.arange(1.0, 1.0 + n) + 0.5
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low = high - 1.0
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close = high - 0.5
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out = ta.TDRiskLevel().batch(high, low, close)
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# buy_risk is column 0; sell_risk is column 1.
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assert math.isnan(out[12, 0])
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assert out[12, 1] == pytest.approx(15.0)
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|
||||
|
||||
def test_classic_pivots_reference():
|
||||
# H=110, L=90, C=105 -> PP = 305/3, R1 = 2·PP − L, S1 = 2·PP − H.
|
||||
cp = ta.ClassicPivots()
|
||||
@@ -1013,6 +1204,14 @@ def test_new_indicators_expose_lifecycle():
|
||||
instances += [ta.VwapStdDevBands(2.0)]
|
||||
instances.append(ta.Alligator(13, 8, 5))
|
||||
instances.append(ta.ZeroLagMACD(12, 26, 9))
|
||||
instances += [
|
||||
ta.TDPressure(5),
|
||||
ta.TDSequential(),
|
||||
ta.TDLines(),
|
||||
ta.TDRiskLevel(),
|
||||
ta.TDRangeProjection(),
|
||||
ta.TDOpen(),
|
||||
]
|
||||
for ind in instances:
|
||||
assert ind.is_ready() is False
|
||||
assert ind.warmup_period() >= 1
|
||||
|
||||
Reference in New Issue
Block a user