import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from matplotlib.projections.polar import PolarAxes
from matplotlib.transforms import Affine2D, IdentityTransform

# 假设你的风向数据如下
wind_data = [(0, 10), (45, 15), (90, 20), (135, 25), (180, 30), (225, 25), (270, 20), (315, 15)]

# 创建DataFrame并计算总频率
df = pd.DataFrame(wind_data, columns=['direction', 'frequency'])
total_frequency = df['frequency'].sum()

# 转换角度为弧度
directions_rad = df['direction'].values * np.pi / 180

# 计算每个扇区的弧度长度
sector_angles = df['frequency'] / total_frequency * 2 * np.pi

# 定义自定义变换，用于添加网格线
def wind_direction_transform(ax):
    theta = np.deg2rad(np.arange(0, 360, 45))
    r = np.ones_like(theta)
    xx, yy = np.meshgrid(theta, r)
    return Affine2D().rotate_deg(90).translate(-xx.ravel(), yy.ravel())


# 绘制玫瑰图
fig, ax = plt.subplots(subplot_kw={'projection': 'polar'}, figsize=(8, 8))

# 自定义颜色
colors = ['skyblue', 'deepskyblue', 'dodgerblue', 'blue', 'mediumblue', 'darkblue', 'midnightblue', 'slateblue']

# 绘制每个风向区段
for i, ((direction, freq), color) in enumerate(zip(wind_data, colors)):
    angle = direction * np.pi / 180
    ax.bar([angle], [freq], width=2 * np.pi / 360, bottom=0, color=color, edgecolor='white', alpha=0.8)

# 手动绘制网格线
theta_ticks = np.deg2rad(np.arange(0, 360, 45))  # 45度间隔的网格线
for angle in theta_ticks:
    ax.plot([angle, angle], [0, 1], transform=ax.get_yaxis_transform(), color='gray', ls='--', lw=0.5, zorder=1)


# 添加指南针标签
labels = ['N', 'NE', 'E', 'SE', 'S', 'SW', 'W', 'NW']
angles = np.arange(0, 2*np.pi, 2*np.pi/8)
ax.set_thetagrids(angles * 180/np.pi, labels, fontproperties={'weight': 'bold'})

# 隐藏中心轴
ax.axis('off')  # 替换掉原来的ax.set_raxis_visible(False)

# 自定义中心点
ax.set_theta_zero_location('N')
ax.set_theta_direction(-1)

# 添加标题
ax.set_title('Wind Rose Diagram', fontweight='bold')

plt.show()