初始化

2026-04-22 12:27:49 +08:00
commit 4857cb6e45
73 changed files with 20927 additions and 0 deletions
--- a/tools/core/utils/common_utils.py
+++ b/tools/core/utils/common_utils.py
@@ -0,0 +1,291 @@
+import arcpy
+import numpy as np
+
+
+def get_data_type(data_path):
+    """获取数据类型
+
+    :param data_path: 数据路径
+    :return: 数据类型
+    """
+    if arcpy.Exists(data_path):
+        try:
+            desc = arcpy.Describe(data_path)
+            return desc.dataType
+        except:
+            return False
+    else:
+        return False
+
+def get_config_key(every_string: str) -> str:
+    config_dict = {
+        "AB": "有效硼","ACU": "有效铜","AMN": "有效锰","AMO": "有效钼","AS1": "有效硫","AZN": "有效锌","CEC": "阳离子交换量","ECA": "交换性钙",
+        "EMG": "交换性镁","TSE": "全硒","TN": "全氮","TP": "全磷","TK": "全钾","AFE": "有效铁","AK": "速效钾","AP": "有效磷", "TRRZ": "土壤容重","LSFD":"砾石丰度",
+        "OM": "有机质","FL": "粉粒含量","NL": "黏粒含量","SL": "砂粒含量","PH": "土壤 pH","YXTCHD": "有效土层厚度","GZCHD": "耕作层厚度","TRZD": "土壤质地","TRZD12": "土壤质地",
+        "三普PH": "三普PH","二普PH": "二普PH","测土PH": "测土PH","二普-三普": "二普-三普","测土-三普": "测土-三普","二普-测土": "二普-测土"
+    }
+    try:
+        for key in config_dict.keys():
+            in_key = every_string.split("_")[0]
+            if key == in_key:
+                return key
+            
+        return ""
+    
+    except Exception as e:
+        return ""
+
+def parse_raster_standard(standard_str):
+    """解析重分类标准字符串，返回数值范围
+    
+    例如：
+    "＞2.00" -> (2.0, float('inf'))
+    "1.00～2.00" -> (1.0, 2.0)
+    "≤0.20" -> (0, 0.2)
+    """
+    if "," in standard_str:
+        temp = []
+        parts = standard_str.split(",\n")
+        for part in parts:
+            temp_part = parse_raster_standard(part)
+            temp.append(temp_part)
+        return temp
+    if "＞" in standard_str:
+        value = float(standard_str.replace("＞", ""))
+        return (value, float('inf'))
+    elif "～" in standard_str:
+        parts = standard_str.split("～")
+        return (float(parts[0]), float(parts[1]))
+    elif "≤" in standard_str:
+        value = float(standard_str.replace("≤", ""))
+        return (0, value)
+    else:
+        # 尝试直接解析为数值
+        try:
+            value = float(standard_str)
+            return (value, value)
+        except ValueError:
+            return None
+
+def create_remap_table(standards_dict):
+    """根据标准配置创建重分类映射表
+    
+    参数:
+    standards_config -- 标准配置，格式为: 
+                      {"标准1":5-6, "标准2":7-8, ...}
+    remap_values -- 重分类值数组，默认为从1开始的整数序列
+    
+    返回:
+    重分类映射表，格式为 [[old_min, old_max, new_value], ...]
+    """
+    
+    # 确保我们有一个有效的标准列表
+    if not standards_dict or not isinstance(standards_dict, dict):
+        print("警告: 没有有效的标准数据")
+        return []
+
+    # 设置重分类值
+    standards_length = len(standards_dict)
+    remap_values = list(range(1, 2*standards_length + 1))
+    
+    remap_table = []
+    for i, (key, value) in enumerate(standards_dict.items()):
+        range_tuple = parse_raster_standard(value)
+
+        if range_tuple:
+            if type(range_tuple) is list:
+                m = 0
+                for range_tuple_item in range_tuple:
+                    j = m * standards_length + i
+                    remap_table.append([range_tuple_item[0], range_tuple_item[1], remap_values[j]])
+                    m = m + 1
+            else:
+                remap_table.append([range_tuple[0], range_tuple[1], remap_values[i]])
+    
+    return remap_table
+
+
+def check_fields_exist_describe(feature_class, field_names):
+    """
+    使用Describe函数检查要素类中字段是否存在
+    """
+    try:
+        desc = arcpy.Describe(feature_class)
+        existing_fields = [field.name for field in desc.fields]
+        
+        for field_name in field_names:
+            if field_name not in existing_fields:
+                return False
+        
+        return True
+        
+    except Exception as e:
+        print(f"检查字段时出错: {e}")
+        return None
+
+def get_grade_by_standard(value, grade_standards):
+    """
+    通用的等级判断函数
+    value: 数值
+    grade_standards: 分级标准字典，如 {"等级一": "＞2.00", "等级二": "1.00～2.00"}
+    """
+    if value is None:
+        return "无数据"
+    
+    # 按等级顺序检查（从高到低）
+    sorted_grades = sorted(grade_standards.items(), 
+                          key=lambda x: list(grade_standards.keys()).index(x[0]))
+    
+    for grade_name, grade_standard in sorted_grades:
+        if is_value_in_grade(value, grade_standard):
+            return grade_name
+    
+    return "超出范围"
+
+def is_value_in_grade(value, grade_standard):
+    """
+    判断数值是否在分级标准范围内
+    """
+    # 处理特殊字符
+    grade_standard = grade_standard.replace('＞', '>').replace('≤', '<=').replace('～', '~')
+    
+    # 处理多范围情况（如pH值）
+    if ',' in grade_standard:
+        ranges = grade_standard.split(',')
+        for range_str in ranges:
+            if is_value_in_single_range(value, range_str.strip()):
+                return True
+        return False
+    else:
+        return is_value_in_single_range(value, grade_standard)
+
+def is_value_in_single_range(value, range_str):
+    """
+    判断数值是否在单个范围内
+    """
+    import re
+    
+    # 提取数值
+    numbers = re.findall(r'[-+]?\d*\.\d+|\d+', range_str)
+    numbers = [float(num) for num in numbers]
+    
+    if '>' in range_str and '~' in range_str:
+        # 格式：>下限~上限
+        return numbers[0] < value <= numbers[1]
+    elif '>' in range_str:
+        # 格式：>数值
+        return value > numbers[0]
+    elif '<=' in range_str:
+        # 格式：<=数值
+        return value <= numbers[0]
+    elif '~' in range_str:
+        # 格式：下限~上限
+        return numbers[0] < value <= numbers[1]
+    else:
+        # 无法解析，使用字符串匹配
+        return str(value) == range_str
+
+def vectorized_grade_assignment(values, grade_standards):
+    """
+    向量化的等级分配（性能更好）
+    """
+    # 确保输入值是数值类型，如果是字符串则转换为浮点数
+    if isinstance(values, np.ndarray) and values.dtype.kind in 'OUS':  # 字符串类型
+        values = values.astype(float)
+    elif hasattr(values, 'dtype') and values.dtype == object:  # 对象类型，可能包含字符串
+        values = values.astype(float)
+
+    conditions = []
+    choices = []
+    
+    # 按等级顺序构建条件
+    # 创建两个列表来分别存储上段和下段范围
+    upper_ranges = []
+    lower_ranges = []
+
+    # 遍历排序后的等级
+    for i, (level, ranges) in enumerate(sorted(grade_standards.items(), key=lambda x: list(grade_standards.keys()).index(x[0])), 1):
+        # 分割范围字符串
+        range_list = [r.strip() for r in ranges.split(',')]
+        
+        if len(range_list) >= 1:
+            upper_ranges.append((i, range_list[0]))
+        
+        if len(range_list) >= 2:
+            # 计算下段范围的索引（原始索引 + 等级总数）
+            lower_index = i + len(grade_standards)
+            lower_ranges.append((lower_index, range_list[1]))
+
+    # 合并结果
+    sorted_grades = upper_ranges + lower_ranges
+    # sorted_grades = sorted(grade_standards.items(), key=lambda x: list(grade_standards.keys()).index(x[0]))
+    
+    for grade_name, grade_standard in sorted_grades:
+        condition = create_condition(values, grade_standard)
+        conditions.append(condition)
+        choices.append(grade_name)
+    
+    # 使用np.select进行向量化操作
+    result = np.select(conditions, choices, default="超出范围")
+    return result
+
+def create_condition(values, grade_standard):
+    """
+    创建numpy条件
+    """
+    # 清理字符串：替换特殊字符并移除换行符和空格
+    grade_standard = (grade_standard.replace('＞', '>')
+                      .replace('≤', '<=')
+                      .replace('～', '~')
+                      .replace('\n', '')  # 移除换行符
+                      .replace(' ', ''))  # 移除空格
+    
+    if ',' in grade_standard:
+        # 多范围处理
+        ranges = grade_standard.split(',')
+        condition = None
+        for range_str in ranges:
+            if range_str:  # 确保不是空字符串
+                range_condition = create_single_condition(values, range_str.strip())
+                if condition is None:
+                    condition = range_condition
+                else:
+                    condition = condition | range_condition
+        return condition
+    else:
+        return create_single_condition(values, grade_standard)
+
+def create_single_condition(values, range_str):
+    """
+    创建单个范围的条件
+    """
+    import re
+    
+    # 调试输出，帮助排查问题
+    # print(f"处理范围字符串: '{range_str}'")
+    
+    # 提取数字
+    numbers = re.findall(r'[-+]?\d*\.\d+|\d+', range_str)
+    numbers = [float(num) for num in numbers]
+    
+    if not numbers:
+        raise ValueError(f"无法从字符串 '{range_str}' 中提取数字")
+    
+    # 根据范围符号创建条件
+    if '>' in range_str and '<=' in range_str:
+        # 处理 >x<=y 的情况（虽然不常见）
+        return (values > numbers[0]) & (values <= numbers[1])
+    elif '>' in range_str and '~' in range_str:
+        return (values > numbers[0]) & (values <= numbers[1])
+    elif '>' in range_str:
+        return values > numbers[0]
+    elif '<=' in range_str:
+        return values <= numbers[0]
+    elif '~' in range_str:
+        return (values > numbers[0]) & (values <= numbers[1])
+    else:
+        # 如果是单个数字
+        try:
+            return values == float(range_str)
+        except ValueError:
+            raise ValueError(f"无法解析的范围字符串: '{range_str}'")