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1.6 KiB
Python

def find_liquidity_levels(swings, tolerance=0.015, max_distance=100):
levels = []
highs = [s for s in swings if s["type"] == "high"]
lows = [s for s in swings if s["type"] == "low"]
used = set()
for i, h1 in enumerate(highs):
if i in used:
continue
cluster = [h1]
for j, h2 in enumerate(highs):
if j != i and j not in used:
if abs(h1["price"] - h2["price"]) <= tolerance and abs(h1["index"] - h2["index"]) <= max_distance:
cluster.append(h2)
used.add(j)
if len(cluster) >= 2:
avg_price = sum(s["price"] for s in cluster) / len(cluster)
levels.append({
"price": avg_price,
"type": "equal_highs",
"count": len(cluster),
"indexes": [s["index"] for s in cluster],
})
used.add(i)
used = set()
for i, l1 in enumerate(lows):
if i in used:
continue
cluster = [l1]
for j, l2 in enumerate(lows):
if j != i and j not in used:
if abs(l1["price"] - l2["price"]) <= tolerance and abs(l1["index"] - l2["index"]) <= max_distance:
cluster.append(l2)
used.add(j)
if len(cluster) >= 2:
avg_price = sum(s["price"] for s in cluster) / len(cluster)
levels.append({
"price": avg_price,
"type": "equal_lows",
"count": len(cluster),
"indexes": [s["index"] for s in cluster],
})
used.add(i)
return levels