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56 lines
1.7 KiB
56 lines
1.7 KiB
# -*- coding: gbk -*-
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import numpy as np
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import matplotlib.pyplot as plt
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import pandas as pd
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from matplotlib.projections.polar import PolarAxes
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from matplotlib.transforms import Affine2D, IdentityTransform
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wind_data = [(0, 10), (45, 15), (90, 20), (135, 25), (180, 30), (225, 25), (270, 20), (315, 15)]
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df = pd.DataFrame(wind_data, columns=['direction', 'frequency'])
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total_frequency = df['frequency'].sum()
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directions_rad = df['direction'].values * np.pi / 180
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sector_angles = df['frequency'] / total_frequency * 2 * np.pi
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def wind_direction_transform(ax):
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theta = np.deg2rad(np.arange(0, 360, 45))
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r = np.ones_like(theta)
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xx, yy = np.meshgrid(theta, r)
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return Affine2D().rotate_deg(90).translate(-xx.ravel(), yy.ravel())
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fig, ax = plt.subplots(subplot_kw={'projection': 'polar'}, figsize=(8, 8))
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colors = ['skyblue', 'deepskyblue', 'dodgerblue', 'blue', 'mediumblue', 'darkblue', 'midnightblue', 'slateblue']
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# 绘制每个风向区段
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for i, ((direction, freq), color) in enumerate(zip(wind_data, colors)):
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angle = direction * np.pi / 180
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ax.bar([angle], [freq], width=2 * np.pi / 360, bottom=0, color=color, edgecolor='white', alpha=0.8)
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theta_ticks = np.deg2rad(np.arange(0, 360, 45)) # 45度间隔的网格线
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for angle in theta_ticks:
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ax.plot([angle, angle], [0, 1], transform=ax.get_yaxis_transform(), color='gray', ls='--', lw=0.5, zorder=1)
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labels = ['N', 'NE', 'E', 'SE', 'S', 'SW', 'W', 'NW']
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angles = np.arange(0, 2*np.pi, 2*np.pi/8)
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ax.set_thetagrids(angles * 180/np.pi, labels, fontproperties={'weight': 'bold'})
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ax.axis('off')
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ax.set_theta_zero_location('N')
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ax.set_theta_direction(-1)
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ax.set_title('Wind Rose', fontweight='bold')
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plt.savefig("风向玫瑰图.png")
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plt.show()
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