Merge remote-tracking branch 'company/dev' into dev

# Conflicts:
#	models/uf-rl/训练/uf_data_process/plot.py
#	models/uf-rl/训练/uf_train/env/reset_plot.py
#	models/uf-rl/训练/uf_train/rl_model/DQN/model/reward.png

.idea/misc.xml

@@ -0,0 +1,6 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="Black">
+    <option name="sdkName" value="env_gpu" />
+  </component>
+</project>

models/uf-rl/uf_data_process/plot.py

@@ -1,93 +0,0 @@
-import os
-import glob
-import pandas as pd
-import numpy as np
-import matplotlib.pyplot as plt
-from matplotlib.font_manager import FontProperties
-
-# ===================== 配置 =====================
-data_dir = r"E:\Greentech\models\uf-rl\datasets\processed\segments"
-target_col = "cycle_long_r2"
-
-# ===================== 中文字体设置 =====================
-# 注意：这里使用 SimHei 字体，可显示中文
-font = FontProperties(fname=r"C:\Windows\Fonts\simhei.ttf", size=12)
-
-# ===================== 读取所有 CSV =====================
-all_files = glob.glob(os.path.join(data_dir, "*.csv"))
-
-values = []
-
-for file in all_files:
-    try:
-        df = pd.read_csv(file)
-        if target_col in df.columns:
-            vals = df[target_col].dropna().values
-            values.append(vals)
-    except Exception as e:
-        print(f"读取失败: {file}, 错误: {e}")
-
-# 合并所有数据
-if len(values) == 0:
-    raise ValueError("未在任何 CSV 中找到有效的 cycle_long_R2 数据")
-
-data = np.concatenate(values)
-total_count = len(data)
-
-# ===================== 定义区间 =====================
-bins = [
-    -np.inf,
-    0.0,
-    0.5,
-    0.6,
-    0.7,
-    0.8,
-    0.9,
-    1.0
-]
-
-labels = [
-    "<0",
-    "0 – 0.5",
-    "0.5 – 0.6",
-    "0.6 – 0.7",
-    "0.7 – 0.8",
-    "0.8 – 0.9",
-    "0.9 – 1.0"
-]
-
-# ===================== 统计分布 =====================
-counts = pd.cut(
-    data,
-    bins=bins,
-    labels=labels,
-    right=True,
-    include_lowest=True
-).value_counts().sort_index()
-
-ratios = counts / total_count * 100
-
-# ===================== 输出结果 =====================
-result = pd.DataFrame({
-    "样本数": counts,
-    "占比 (%)": ratios.round(2)
-})
-
-print(f"\n总样本数: {total_count}\n")
-print(result)
-
-# ===================== 绘制柱状图 =====================
-plt.figure(figsize=(10, 6))
-plt.bar(labels, ratios, color='skyblue', edgecolor='black')
-plt.title("cycle_long_R2 数据分布柱状图", fontproperties=font)
-plt.xlabel("区间", fontproperties=font)
-plt.ylabel("占比 (%)", fontproperties=font)
-plt.ylim(0, 100)
-plt.grid(axis='y', linestyle='--', alpha=0.7)
-
-# 在柱子上显示百分比
-for i, v in enumerate(ratios):
-    plt.text(i, v + 1, f"{v:.1f}%", ha='center', va='bottom', fontsize=10, fontproperties=font)
-
-plt.tight_layout()
-plt.show()

models/uf-rl/uf_train/env/reset_plot.py

@@ -1,58 +0,0 @@
-import numpy as np
-import matplotlib.pyplot as plt
-
-# 训练进度
-progress = np.linspace(0, 1, 200)
-
-# -----------------------------
-# 参数设置（可调）
-# -----------------------------
-alpha = 0.5    # 虚拟工况最终最大占比
-k = 10.0       # Sigmoid 陡峭程度
-p0 = 0.7       # 虚拟工况启动拐点
-beta = 0.5     # 扰动工况线性增长系数
-
-# -----------------------------
-# 权重定义
-# -----------------------------
-# 虚拟工况（非线性，后期快速增长）
-w_virtual = alpha / (1.0 + np.exp(-k * (progress - p0)))
-
-# 扰动工况（线性增长）
-w_perturb = beta * progress
-
-# 真实工况（剩余比例）
-w_real = 1.0 - w_virtual - w_perturb
-w_real = np.clip(w_real, 0.0, 1.0)  # 数值安全
-
-# -----------------------------
-# 扰动幅度
-# -----------------------------
-perturb_scale = 0.02 + 0.04 * progress
-
-# -----------------------------
-# 绘图
-# -----------------------------
-fig, ax1 = plt.subplots(figsize=(8, 5))
-
-ax1.plot(progress, w_real, label="w_real", linewidth=2)
-ax1.plot(progress, w_perturb, label="w_perturb", linewidth=2)
-ax1.plot(progress, w_virtual, label="w_virtual", linewidth=2)
-
-ax1.set_xlabel("Training Progress")
-ax1.set_ylabel("Sampling Weights")
-ax1.set_ylim(0, 1.05)
-ax1.grid(True, linestyle="--", alpha=0.5)
-ax1.legend(loc="upper left")
-
-# 第二纵轴：扰动幅度
-ax2 = ax1.twinx()
-ax2.plot(progress, perturb_scale, label="perturb_scale",
-         linestyle="--", linewidth=2)
-ax2.set_ylabel("Perturb Scale")
-ax2.set_ylim(0, 0.07)
-ax2.legend(loc="upper right")
-
-plt.title("Progressive Reset Sampling Strategy")
-plt.tight_layout()
-plt.show()