合并达成度功能

utils/function.py

@@ -1,5 +1,185 @@
 import os
 import sys
+import io
+import matplotlib
+from matplotlib import pyplot as plt
+import re
+
+
+def format_ranges(nums):
+    """格式化区间，支持特殊标记"""
+    if not nums:
+        return ""
+
+    def parse_value(val):
+        """解析值，返回主数值和次要标记"""
+        if isinstance(val, int):
+            return val, ""
+        match = re.match(r"(\d+)[(（](.*?)[)）]", str(val))
+        if match:
+            return int(match.group(1)), match.group(2)
+        return int(val), ""
+
+    # 排序规则：主数值优先，次要标记其次
+    sorted_nums = sorted(nums, key=lambda x: parse_value(x))
+
+    result = []
+    start = sorted_nums[0]
+    end = sorted_nums[0]
+
+    def is_continuous(val1, val2):
+        """判断两个值是否连续"""
+        main1, sub1 = parse_value(val1)
+        main2, sub2 = parse_value(val2)
+        # 主数值连续，且次要标记为空（特殊标记视为不连续）
+        return main2 == main1 + 1 and not sub2
+
+    for i in range(1, len(sorted_nums)):
+        if is_continuous(end, sorted_nums[i]):
+            end = sorted_nums[i]
+        else:
+            # 处理一个区间
+            if parse_value(start)[0] == parse_value(end)[0]:  # 单值或特殊标记
+                result.append(str(start))
+            elif parse_value(end)[0] - parse_value(start)[0] >= 2:  # 连续区间
+                result.append(f"{parse_value(start)[0]}~{parse_value(end)[0]}")
+            else:  # 非连续的单值
+                result.extend(map(str, [start, end]))
+            start = end = sorted_nums[i]
+
+    # 添加最后一段区间
+    if parse_value(start)[0] == parse_value(end)[0]:  # 单值或特殊标记
+        result.append(str(start))
+    elif parse_value(end)[0] - parse_value(start)[0] >= 2:  # 连续区间
+        result.append(f"{parse_value(start)[0]}~{parse_value(end)[0]}")
+    else:  # 非连续的单值
+        result.extend(map(str, [start, end]))
+
+    return "、".join(result)
+
+
+def support_version_str(lst: list[str]) -> str:
+    """支持的版本字符串"""
+    if len(lst) == 1:
+        return lst[0]
+    elif len(lst) == 2:
+        return f"{lst[0]}、{lst[1]}"
+    else:
+        return f"{lst[0]}~{lst[-1]}"
+
+
+def get_rank(score: int | float) -> str:
+    """根据分数获取等级"""
+    if score >= 0.9:
+        return "优秀"
+    elif score >= 0.8:
+        return "良好"
+    elif score >= 0.7:
+        return "中等"
+    elif score >= 0.6:
+        return "及格"
+    else:
+        return "不及格"
+
+
+def min_score_people_name(data: list, kpi_number: int, start_index: int, end_index: int) -> list[tuple[str]]:
+    """获取最低分人名"""
+    # 0             1       2       3   4   5       6   7   8   9       10      11  12  13
+    # 20060510XX	覃XX	40.5	45	49	0.738 	16	17	0	0.330 	24.5	15	14	0.695
+    remove_indices = [5, 9, 13, 17, 21]
+    # 更新后的数据
+    # 0             1       2       3   4    5  6  7   8      9   10
+    # 20060510XX	覃XX	40.5	45	49	 16	17	0	24.5   15  14
+    index = 2 + kpi_number * 3
+    updated_data = [[item for j, item in enumerate(row) if j not in remove_indices] for row in data]
+    result = [(), (), ()]
+    min_scores = [min(updated_data[start_index:end_index],
+                      key=lambda x: x[index + i] if x[index + i] is not None else 0)[index + i] for i in range(3)]
+    for row in updated_data[start_index:end_index]:
+        for i in range(3):
+            if row[index + i] == min_scores[i]:
+                result[i] += (row[1],)
+    return result
+
+
+def get_class_index_range(lst: list[int], num: int):
+    """获取班级的索引范围"""
+    if num < 0 or num > len(lst):
+        raise ValueError("OutOfRange")
+    # 计算前num-1项和加一
+    first_value = sum(lst[:num])
+    # 计算前num项和加一
+    second_value = sum(lst[:num + 1]) if num < len(lst) else "OutOfRange"
+    return (first_value, second_value)
+
+
+def check_version(version, compatible_versions):
+    # 将版本字符串转换为数字列表以便比较
+    version_nums = [int(v) for v in version.split('.')]
+    min_version_nums = [int(v) for v in compatible_versions[0].split('.')]
+    max_version_nums = [int(v) for v in compatible_versions[-1].split('.')]
+
+    # 比较版本
+    if version_nums < min_version_nums:
+        return False, "不支持低于{}的版本，如需尝试生成请勾选‘关闭兼容性检查’".format(compatible_versions[0])
+    elif version_nums > max_version_nums:
+        return True, "版本过高可能会导致兼容性问题"
+    else:
+        return True, ""
+
+
+def gen_picture(data: list[list[str]], kpi_number: int, start_index: int, end_index: int):
+    # 设置全局字体
+    matplotlib.rcParams['font.family'] = ['Times New Roman', 'KaiTi']
+    matplotlib.rcParams['font.size'] = 10
+
+    # 将厘米转换为英寸
+    width_in_inches = 8 * 0.393701
+    height_in_inches = 6 * 0.393701
+
+    # 创建一个图形和三个子图
+    fig, axs = plt.subplots(1, kpi_number, figsize=(width_in_inches * kpi_number, height_in_inches))
+
+    # 遍历每个指定的索引来生成散点图
+    for ax, index in zip(axs, range(kpi_number)):
+        # 处理数据
+        data_indices = [5, 9, 13, 17, 21]
+        update_data = [[float(item) for j, item in enumerate(row) if j in data_indices] for row in data]
+        x = [i for i in range(end_index - start_index)]
+        y = [row[index] for row in update_data[start_index:end_index]]
+
+        # 绘制散点图
+        ax.scatter(x, y, label=f'目标{index + 1}达成值', s=10)
+        # 添加期望值直线
+        ax.axhline(y=0.65, color='r', linestyle='-', label='期望值')
+        # 设置轴标签
+        ax.set_xlabel('学生学号')
+        ax.set_ylabel('达成值')
+        # 设置y轴范围和刻度
+        ax.set_ylim(0, 1)
+        ax.set_yticks([i * 0.2 for i in range(6)])
+        # 设置图例
+        ax.legend(loc='upper center', bbox_to_anchor=(0.5, -0.35), ncol=2, frameon=False)
+        # 设置坐标原点为(0, 0)
+        ax.set_xlim(x.index(x[0]), None)
+
+    # 调整子图间距
+    plt.tight_layout()
+    # 创建一个内存中的文件对象
+    buf = io.BytesIO()
+    # 保存图形
+    plt.savefig(buf, format='png', dpi=300, bbox_inches='tight')
+    # 将文件对象转换为字节对象
+    res = buf.getvalue()
+    buf.close()
+
+    return res
+
+
+if __name__ == '__main__':
+    nums = [1, 2, 3, '4(1)', '4（2）']
+    formatted_ranges = format_ranges(nums)
+    print(formatted_ranges)
 
 
 def resource_path(relative_path: str) -> str: