五度标调法调域统计分析工具
"""
tone_statistics_analyzer.py
五度标调法调域统计分析工具
增强版：包含数据验证、统计指标计算和加权支持
"""
import math
from typing import List, Optional
class ToneStatisticsAnalyzer:
"""
五度标调法调域统计分析工具
提供调值中值、调类中值、调系中值计算，以及调域范围、标准差等统计指标
"""
MIN_TONE_LEVEL = 1
MAX_TONE_LEVEL = 5
@staticmethod
def validate_pitch_levels(pitch_levels: List[int]) -> None:
"""
验证五度值是否在有效范围内(1-5)
:param pitch_levels: 调值列表
:raises ValueError: 如果调值不在1-5范围内
"""
if not pitch_levels:
raise ValueError("调值列表不能为空")
for level in pitch_levels:
if not (ToneStatisticsAnalyzer.MIN_TONE_LEVEL <= level <= ToneStatisticsAnalyzer.MAX_TONE_LEVEL):
raise ValueError(
f"五度值必须在{ToneStatisticsAnalyzer.MIN_TONE_LEVEL}-{ToneStatisticsAnalyzer.MAX_TONE_LEVEL}之间，当前值: {level}")
@staticmethod
def calculate_tone_value_stats(pitch_levels: List[int], weights: Optional[List[float]] = None) -> dict:
"""
计算单个调值的统计指标(中值、范围、标准差)
:param pitch_levels: 调值列表
:param weights: 可选权重列表(用于加权计算)
:return: 包含统计指标的字典
"""
ToneStatisticsAnalyzer.validate_pitch_levels(pitch_levels)
if weights and len(weights) != len(pitch_levels):
raise ValueError("权重列表长度必须与调值列表相同")
n = len(pitch_levels)
if weights:
# 加权计算
weighted_sum = sum(t * w for t, w in zip(pitch_levels, weights))
total_weight = sum(weights)
mean = weighted_sum / total_weight
# 加权标准差
variance = sum(w * (t - mean)**2 for t,
w in zip(pitch_levels, weights)) / total_weight
else:
# 普通计算
mean = sum(pitch_levels) / n
variance = sum((t - mean)**2 for t in pitch_levels) / n
return {
'median': mean,
'range': max(pitch_levels) - min(pitch_levels),
'std_dev': math.sqrt(variance),
'min': min(pitch_levels),
'max': max(pitch_levels)
}
@staticmethod
def calculate_tone_category_stats(tone_values_stats: List[dict], weights: Optional[List[float]] = None) -> dict:
"""
计算调类统计指标
:param tone_values_stats: 该调类的多个调值统计指标列表
:param weights: 可选权重列表
:return: 调类统计指标
"""
if not tone_values_stats:
raise ValueError("调值统计指标列表不能为空")
medians = [stat['median'] for stat in tone_values_stats]
if weights:
if len(weights) != len(medians):
raise ValueError("权重列表长度必须与调值统计指标列表相同")
weighted_sum = sum(m * w for m, w in zip(medians, weights))
total_weight = sum(weights)
category_median = weighted_sum / total_weight
else:
category_median = sum(medians) / len(medians)
return {
'median': category_median,
'range': max(medians) - min(medians),
'std_dev': math.sqrt(sum((m - category_median)**2 for m in medians) / len(medians))
}
@staticmethod
def calculate_tone_system_stats(category_stats: List[dict]) -> dict:
"""
计算调系统计指标
:param category_stats: 各调类统计指标列表
:return: 调系统计指标
"""
if not category_stats:
raise ValueError("调类统计指标列表不能为空")
medians = [stat['median'] for stat in category_stats]
system_median = sum(medians) / len(medians)
return {
'median': system_median,
'range': max(medians) - min(medians),
'std_dev': math.sqrt(sum((m - system_median)**2 for m in medians) / len(medians))
}
@staticmethod
def calculate_variation_coefficient(values):
"""计算变异系数（标准差/均值）评估离散程度"""
mean = sum(values) / len(values)
std_dev = (sum((x - mean)**2 for x in values) / len(values))**0.5
return std_dev / mean
# 应用示例
shangsheng_vc = calculate_variation_coefficient(
[1.33, 4.00, 2.33]) # 上声变异系数
qusheng_vc = calculate_variation_coefficient([3.33, 4.00]) # 去声变异系数示例使用
if name == "main ":
print("五度标调法调域统计分析示例\n")
# 1. 计算各调值统计指标
yinping = ToneStatisticsAnalyzer.calculate_tone_value_stats([5, 5, 5])
yangping = ToneStatisticsAnalyzer.calculate_tone_value_stats([3, 4, 5])
shangsheng1 = ToneStatisticsAnalyzer.calculate_tone_value_stats([2, 1, 1])
shangsheng2 = ToneStatisticsAnalyzer.calculate_tone_value_stats([3, 4, 5])
shangsheng3 = ToneStatisticsAnalyzer.calculate_tone_value_stats([2, 1, 4])
qusheng1 = ToneStatisticsAnalyzer.calculate_tone_value_stats([5, 4, 1])
qusheng2 = ToneStatisticsAnalyzer.calculate_tone_value_stats([5, 4, 3])
print("=== 调值统计 ===")
print(
f"阴平[555]: 中值={yinping['median']:.2f}, 范围={yinping['range']}, 标准差={yinping['std_dev']:.2f}")
print(
f"阳平[345]: 中值={yangping['median']:.2f}, 范围={yangping['range']}, 标准差={yangping['std_dev']:.2f}")
print(
f"上声1[211]: 中值={shangsheng1['median']:.2f}, 范围={shangsheng1['range']}, 标准差={shangsheng1['std_dev']:.2f}")
print(
f"上声2[345]: 中值={shangsheng2['median']:.2f}, 范围={shangsheng2['range']}, 标准差={shangsheng2['std_dev']:.2f}")
print(
f"上声3[214]: 中值={shangsheng3['median']:.2f}, 范围={shangsheng3['range']}, 标准差={shangsheng3['std_dev']:.2f}")
print(
f"去声1[541]: 中值={qusheng1['median']:.2f}, 范围={qusheng1['range']}, 标准差={qusheng1['std_dev']:.2f}")
print(
f"去声2[543]: 中值={qusheng2['median']:.2f}, 范围={qusheng2['range']}, 标准差={qusheng2['std_dev']:.2f}")
# 2. 计算各调类统计指标
yinping_stats = ToneStatisticsAnalyzer.calculate_tone_category_stats([
yinping])
yangping_stats = ToneStatisticsAnalyzer.calculate_tone_category_stats([
yangping])
shangsheng_stats = ToneStatisticsAnalyzer.calculate_tone_category_stats(
[shangsheng1, shangsheng2, shangsheng3])
qusheng_stats = ToneStatisticsAnalyzer.calculate_tone_category_stats([
qusheng1, qusheng2])
print("\n=== 调类统计 ===")
print(
f"阴平: 中值={yinping_stats['median']:.2f}, 范围={yinping_stats['range']:.2f}, 标准差={yinping_stats['std_dev']:.2f}")
print(
f"阳平: 中值={yangping_stats['median']:.2f}, 范围={yangping_stats['range']:.2f}, 标准差={yangping_stats['std_dev']:.2f}")
print(
f"上声: 中值={shangsheng_stats['median']:.2f}, 范围={shangsheng_stats['range']:.2f}, 标准差={shangsheng_stats['std_dev']:.2f}")
print(
f"去声: 中值={qusheng_stats['median']:.2f}, 范围={qusheng_stats['range']:.2f}, 标准差={qusheng_stats['std_dev']:.2f}")
# 3. 计算调系统计指标
system_stats = ToneStatisticsAnalyzer.calculate_tone_system_stats([
yinping_stats, yangping_stats, shangsheng_stats, qusheng_stats
])
print("\n=== 调系统计 ===")
print(f"调系中值: {system_stats['median']:.2f}")
print(f"调域范围: {system_stats['range']:.2f}")
print(f"标准差: {system_stats['std_dev']:.2f}")