mirror of
https://github.com/manifoldbt/manifoldbt.git
synced 2026-08-24 14:38:04 +00:00
93 lines
2.9 KiB
Python
93 lines
2.9 KiB
Python
"""2D Parameter Sweep Heatmap -- EMA crossover t-stat(alpha).
|
||
|
||
Demonstrates:
|
||
- param() in indicator periods (engine re-compiles per combo)
|
||
- run_sweep() for Cartesian grid search
|
||
- Heatmap visualization with mbt.plot.heatmap_2d()
|
||
|
||
Data: shared store — real market data from `data/` (see examples/README.md)
|
||
|
||
Usage:
|
||
python examples/08_sweep_2d_heatmap.py
|
||
"""
|
||
import os
|
||
import time
|
||
import manifoldbt as mbt
|
||
from manifoldbt.indicators import close, ema
|
||
from manifoldbt.helpers import time_range, Slippage, Interval
|
||
|
||
# -- Strategy (single definition, param() in periods) ------------------------
|
||
fast = ema(close, mbt.param("fast"))
|
||
slow = ema(close, mbt.param("slow"))
|
||
|
||
signal = mbt.when(fast > slow, 0.25, mbt.when(fast < slow, -0.25, 0.0))
|
||
|
||
strategy = (
|
||
mbt.Strategy.create("ema_cross")
|
||
.signal("fast", fast)
|
||
.signal("slow", slow)
|
||
.size(signal)
|
||
)
|
||
|
||
# -- Config -------------------------------------------------------------------
|
||
start, end = time_range("2021-01-01", "2026-01-01")
|
||
|
||
config = mbt.BacktestConfig(
|
||
universe={"binance": ["BTC-USDT:perp"]},
|
||
time_range_start=start,
|
||
time_range_end=end,
|
||
bar_interval=Interval.hours(1),
|
||
initial_capital=10_000,
|
||
execution=mbt.ExecutionConfig(
|
||
allow_short=True,
|
||
max_position_pct=0.5,
|
||
),
|
||
fees=mbt.FeeConfig.binance_perps(),
|
||
slippage=Slippage.fixed_bps(2),
|
||
warmup_bars=80,
|
||
output_resolution=Interval.days(1),
|
||
)
|
||
|
||
# -- Run ----------------------------------------------------------------------
|
||
if __name__ == "__main__":
|
||
root = os.path.join(os.path.dirname(__file__), "..")
|
||
data_root = os.path.abspath(os.path.join(root, "data"))
|
||
store = mbt.DataStore(
|
||
data_root=data_root,
|
||
metadata_db=os.path.abspath(os.path.join(root, "metadata", "metadata.sqlite")),
|
||
arrow_dir=os.path.join(data_root, "mega"),
|
||
)
|
||
|
||
fast_values = list(range(5, 1000, 5))
|
||
slow_values = list(range(10, 5000, 5))
|
||
|
||
print(f"Running 2D sweep ({len(fast_values)*len(slow_values)} combos)...")
|
||
t0 = time.perf_counter()
|
||
batch = mbt.run_sweep_lite(
|
||
strategy,
|
||
{"fast": fast_values, "slow": slow_values},
|
||
config,
|
||
store,
|
||
)
|
||
elapsed = time.perf_counter() - t0
|
||
|
||
# run_sweep_lite iterates sorted keys: fast (outer) × slow (inner)
|
||
# Reshape into grid[slow][fast] for heatmap (y=slow, x=fast)
|
||
metric_grid = [[0.0] * len(fast_values) for _ in slow_values]
|
||
idx = 0
|
||
for fi, f_val in enumerate(fast_values):
|
||
for si, s_val in enumerate(slow_values):
|
||
metric_grid[si][fi] = batch[idx].metrics.get("tstat_alpha", 0.0)
|
||
idx += 1
|
||
|
||
print(f"\n{len(batch)} combos in {elapsed:.2f}s")
|
||
|
||
mbt.plot.heatmap_2d({
|
||
"x_param": "fast",
|
||
"y_param": "slow",
|
||
"x_values": fast_values,
|
||
"y_values": slow_values,
|
||
"metric": "t-stat(alpha)",
|
||
"metric_grid": metric_grid,
|
||
})
|