示例03 sklearn 风格接口与 thresh 调参

"""ex03_sklearn_rips.py — 第 1、4 章 sklearn 风格 Rips 类与 thresh 调参

对应教程：tutorials/01-environment.md 1.6、1.7 节，tutorials/04-ripser-api.md。

演示：

• Rips 类的 fit / fit_transform / transform 用法
• thresh 截断对边数与速度的影响
• 同一 Rips 对象对多个点云 transform

运行：
python ex03_sklearn_rips.py
"""

import time
import numpy as np
from ripser import Rips

from common import sample_circle, sample_random

def main():
np.random.seed(0)

data = sample_circle(n=200, noise=0.05, seed=0)

# ── 1. Rips 类：构造时固定参数 ──
rips = Rips(maxdim=1, thresh=1.0, verbose=False)
dgms = rips.fit_transform(data)
print("=== Rips.fit_transform ===")
for d, dgm in enumerate(dgms):
    pers = (dgm[:, 1] - dgm[:, 0])
    pers = pers[np.isfinite(pers)]
    print(f"  H{d}: {len(dgm)} 点, max persistence = "
          f"{pers.max() if len(pers) else 0:.4f}")

# rips 对象上还有 num_edges_、dgms_、dgm2all_ 等
print(f"  num_edges_ = {rips.num_edges_ if hasattr(rips,'num_edges_') else '?'}")

# ── 2. thresh 对速度与边数的影响 ──
print("\n=== thresh 调参对比 ===")
for thresh in [0.5, 1.0, 1.5, 2.0, np.inf]:
    t0 = time.perf_counter()
    r = rips.fit_transform(data)
    # 重新构造一个 Rips，因为 thresh 在构造时固定
    r2 = Rips(maxdim=1, thresh=thresh, verbose=False)
    t0 = time.perf_counter()
    r2.fit_transform(data)
    dt = time.perf_counter() - t0
    n_edges = getattr(r2, 'num_edges_', '?')
    print(f"  thresh={str(thresh):>6s}  time={dt:.3f}s  edges={n_edges}")

# ── 3. transform：对另一个点云复用参数 ──
print("\n=== transform 另一点云 ===")
random_data = sample_random(n=200, dim=2, seed=5)
rips2 = Rips(maxdim=1, thresh=1.5)
rips2.fit(data)               # 用圆环「定标」
dgms_rand = rips2.transform(random_data)
print(f"  随机点 H1 点数: {len(dgms_rand[1])}")
print("  对比：圆环 H1 显著点数应远多于随机点（第 5 章主题）")
​

if name == "main":
main()