| |
| """诊断外部测试集: 每个域的样本数 / 标签纯度 / 常数预测基线。""" |
| import sys |
| import numpy as np |
| import torch |
|
|
| sys.path.insert(0, "/work/liuyuanjie/headless") |
| sys.path.insert(0, "/work/liuyuanjie/headless/tests") |
| from run_lm4_wave import (build_feature_matrix, build_windows, assign_domains) |
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| |
| t1, d1, F1, ok1 = build_feature_matrix("/work/liuyuanjie/headless/data/wave", |
| bands=13, use_wfr=True, use_lshell=True) |
| X1, yl1 = build_windows(t1, d1, F1, ok1) |
| y1, qs = assign_domains(yl1, 6) |
| print("训练年 2015 边界:", [round(float(q), 2) for q in qs]) |
| print("训练年 2015 每域样本:", np.bincount(y1, minlength=6).tolist()) |
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| |
| t2, d2, F2, ok2 = build_feature_matrix("/work/liuyuanjie/headless/data/wave2016", |
| bands=13, use_wfr=True, use_lshell=True) |
| X2, yl2 = build_windows(t2, d2, F2, ok2) |
| y2, _ = assign_domains(yl2, 6, qs=qs) |
| print("\n测试年 2016 每域样本 (沿用 2015 边界):", np.bincount(y2, minlength=6).tolist()) |
| print("测试年 log10(density) 范围:", round(float(yl2.min()), 2), "~", round(float(yl2.max()), 2)) |
| print("训练年 log10(density) 范围:", round(float(yl1.min()), 2), "~", round(float(yl1.max()), 2)) |
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| |
| print("\n每个域子集的样本数 (若某域样本极少, 其准确率噪声极大):") |
| for dd in range(6): |
| n = int((y2 == dd).sum()) |
| print(f" D{dd}: {n} 条") |
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|
