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Weather_Visual/WindRoser.py

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+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()