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random_forest.py
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54 lines (46 loc) · 1.82 KB
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# ...existing code...
class RandomForest:
@classmethod
def add_vectors(cls, v1, v2):
return [sum(i) for i in zip(v1, v2)]
@staticmethod
def _safe_get(inp, idx, default=0.0):
return inp[idx] if idx < len(inp) else default
@classmethod
def score(cls, input):
"""
对 7 个组分别打票，每组由三个值 x,y,z 构成（组起始索引按 0,21,42,...126）。
返回长度为3的累计 votes 列表：[votes_still, votes_walk, votes_fall]
"""
# 阈值常量（可调）
Z_STILL_TH = 9.019443988800049
XY_WALK_LOW = 2.254075527191162
XY_WALK_HIGH = 8.019443988800049
XY_FALL_TH = 8.019443988800049
votes = [0.0, 0.0, 0.0]
# 7 组，起始索引间隔 21
for g in range(7):
base = g * 21
x = abs(cls._safe_get(input, base, 0.0))
y = abs(cls._safe_get(input, base + 1, 0.0))
z = abs(cls._safe_get(input, base + 2, 0.0))
# 优先判断静止（z 接近重力方向/大值）
if z >= Z_STILL_TH:
var = [1.0, 0.0, 0.0] # 静止
# 行走：x,y 在中间区间
elif (x >= XY_WALK_LOW and x <= XY_WALK_HIGH) and (y >= XY_WALK_LOW and y <= XY_WALK_HIGH):
var = [0.0, 1.0, 0.0] # 行走
# 摔倒：x 或 y 极大
elif (x >= XY_FALL_TH) or (y >= XY_FALL_TH):
var = [0.0, 0.0, 1.0] # 摔倒
else:
# 默认归为行走（可根据实际数据改为更保守策略）
var = [0.0, 1.0, 0.0]
votes = cls.add_vectors(votes, var)
return votes
@classmethod
def run(cls, input: list):
res = cls.score(input)
print(res)
return res.index(max(res))
# ...existing code...