5867f71450
* feat(core): add 3 trade-flow microstructure indicators SignedVolume (per-trade size signed by aggressor), CumulativeVolumeDelta (running signed-volume total), and TradeImbalance (rolling buy/sell volume imbalance over a trade window). All consume the Trade type, with full unit coverage. Extends the Microstructure family. * feat(bindings): expose trade-flow microstructure indicators Python, Node and WASM bindings for SignedVolume, CumulativeVolumeDelta and TradeImbalance. Each takes a trade via update(price, size, is_buy); Python and Node expose a batch over three parallel arrays, WASM exposes per-trade update. Regenerates node index.d.ts/.js. * test(bindings,fuzz,bench): cover trade-flow microstructure indicators Python and Node: reference values, streaming-vs-batch, lifecycle/repr and input validation (zero window, negative size, non-positive price, mismatched batch lengths). New indicator_update_trade fuzz target. Synthetic trade-tape benches (signed_volume cheapest, trade_imbalance windowed/expensive). * docs: add trade-flow indicators + bump counter to 227 README Microstructure family row gains signed volume / CVD / trade imbalance and the counter goes 224 -> 227; CHANGELOG records the trade-flow indicators.
175 lines
4.6 KiB
Python
175 lines
4.6 KiB
Python
"""Tests for the indicator lifecycle methods: reset, is_ready, warmup_period, repr."""
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from __future__ import annotations
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import numpy as np
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import pytest
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import wickra as ta
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SCALAR_INDICATORS = [
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(ta.SMA, (14,)),
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(ta.EMA, (14,)),
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(ta.WMA, (14,)),
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(ta.RSI, (14,)),
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(ta.MACD, ()),
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(ta.BollingerBands, ()),
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]
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@pytest.mark.parametrize("cls, args", SCALAR_INDICATORS)
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def test_is_ready_transitions_after_warmup(cls, args):
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ind = cls(*args)
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assert not ind.is_ready()
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series = np.linspace(1.0, 200.0, 200)
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ind.batch(series)
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assert ind.is_ready()
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@pytest.mark.parametrize("cls, args", SCALAR_INDICATORS)
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def test_reset_returns_to_initial_state(cls, args):
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ind = cls(*args)
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ind.batch(np.linspace(1.0, 200.0, 200))
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assert ind.is_ready()
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ind.reset()
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assert not ind.is_ready()
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@pytest.mark.parametrize(
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"cls, args, period",
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[
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(ta.SMA, (14,), 14),
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(ta.EMA, (14,), 14),
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(ta.WMA, (14,), 14),
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(ta.RSI, (14,), 15),
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(ta.BollingerBands, (20, 2.0), 20),
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],
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)
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def test_warmup_period(cls, args, period):
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assert cls(*args).warmup_period() == period
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def test_repr_contains_class_and_parameters():
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assert "SMA" in repr(ta.SMA(14))
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assert "14" in repr(ta.SMA(14))
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assert "BollingerBands" in repr(ta.BollingerBands(20, 2.0))
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def test_constructor_rejects_zero_period():
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with pytest.raises(ValueError):
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ta.SMA(0)
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with pytest.raises(ValueError):
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ta.RSI(0)
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def test_macd_rejects_fast_geq_slow():
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with pytest.raises(ValueError):
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ta.MACD(fast=26, slow=12, signal=9)
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def test_bollinger_rejects_non_positive_multiplier():
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with pytest.raises(ValueError):
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ta.BollingerBands(20, 0.0)
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with pytest.raises(ValueError):
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ta.BollingerBands(20, -1.0)
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def test_candle_dict_input_supported():
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atr = ta.ATR(2)
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atr.update({"open": 10.0, "high": 11.0, "low": 9.0, "close": 10.5, "volume": 1.0})
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v = atr.update({"open": 10.5, "high": 12.0, "low": 10.0, "close": 11.0, "volume": 1.0})
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assert v is not None
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def test_candle_tuple_input_supported():
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atr = ta.ATR(2)
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atr.update((10.0, 11.0, 9.0, 10.5, 1.0, 0))
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v = atr.update((10.5, 12.0, 10.0, 11.0, 1.0, 1))
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assert v is not None
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def test_initial_balance_reset_unlocks():
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ib = ta.InitialBalance(2)
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assert not ib.is_ready()
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ib.update((101.0, 102.0, 100.0, 101.0, 0.0, 0))
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ib.update((102.0, 103.0, 101.0, 102.0, 0.0, 1))
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assert ib.is_ready()
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assert ib.is_locked()
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ib.reset()
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assert not ib.is_ready()
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assert not ib.is_locked()
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def test_opening_range_reset_unlocks():
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or_ind = ta.OpeningRange(2)
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or_ind.update((101.0, 102.0, 100.0, 101.0, 0.0, 0))
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or_ind.update((102.0, 103.0, 101.0, 102.0, 0.0, 1))
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assert or_ind.is_locked()
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or_ind.reset()
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assert not or_ind.is_locked()
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def test_value_area_warmup_equals_period():
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assert ta.ValueArea(20, 50, 0.70).warmup_period() == 20
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assert ta.ValueArea(10, 30, 0.80).warmup_period() == 10
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def test_ehlers_indicators_lifecycle():
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# Spot-check a few Family-10 entries beyond what test_new_indicators covers.
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series = np.linspace(1.0, 200.0, 200) + np.sin(np.arange(200) * 0.3) * 5.0
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for ind in [
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ta.SuperSmoother(10),
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ta.FisherTransform(10),
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ta.MAMA(),
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ta.HilbertDominantCycle(),
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ta.SineWave(),
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]:
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assert not ind.is_ready()
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ind.batch(series)
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assert ind.is_ready()
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ind.reset()
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assert not ind.is_ready()
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def test_orderbook_lifecycle():
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snapshot = ([100.0], [1.0], [101.0], [1.0])
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for ind in [
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ta.OrderBookImbalanceTop1(),
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ta.OrderBookImbalanceTopN(3),
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ta.OrderBookImbalanceFull(),
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ta.Microprice(),
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ta.QuotedSpread(),
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]:
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assert ind.warmup_period() == 1
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assert not ind.is_ready()
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ind.update(*snapshot)
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assert ind.is_ready()
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ind.reset()
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assert not ind.is_ready()
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def test_orderbook_topn_repr():
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assert repr(ta.OrderBookImbalanceTopN(5)) == "OrderBookImbalanceTopN(levels=5)"
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def test_tradeflow_lifecycle():
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for ind in [ta.SignedVolume(), ta.CumulativeVolumeDelta()]:
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assert ind.warmup_period() == 1
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assert not ind.is_ready()
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ind.update(100.0, 1.0, True)
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assert ind.is_ready()
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ind.reset()
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assert not ind.is_ready()
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def test_trade_imbalance_lifecycle_and_repr():
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ti = ta.TradeImbalance(3)
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assert ti.warmup_period() == 3
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assert not ti.is_ready()
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for _ in range(3):
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ti.update(100.0, 1.0, True)
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assert ti.is_ready()
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ti.reset()
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assert not ti.is_ready()
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assert repr(ta.TradeImbalance(4)) == "TradeImbalance(window=4)"
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