import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
import matplotlib.cm as cm
from math import pi
import windrose
from windrose import WindroseAxes, WindAxes, plot_windrose
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
import cartopy.crs as ccrs
import cartopy.io.img_tiles as cimgt

讀取數(shù)據(jù)

df = pd.read_csv("./sample_wind_poitiers.csv", parse_dates=['Timestamp'])
df = df.set_index('Timestamp')

計算風(fēng)速的u、v分量

df['speed_x'] = df['speed'] * np.sin(df['direction'] * pi / 180.0)
df['speed_y'] = df['speed'] * np.cos(df['direction'] * pi / 180.0)

uv風(fēng)速散點圖(含透明度)

fig, ax = plt.subplots(figsize=(8, 8), dpi=80)
x0, x1 = ax.get_xlim()
y0, y1 = ax.get_ylim()
ax.set_aspect(abs(x1-x0)/abs(y1-y0))
ax.set_aspect('equal')
ax.scatter(df['speed_x'], df['speed_y'], alpha=0.25)
df.plot(kind='scatter', x='speed_x', y='speed_y', alpha=0.05, ax=ax)
Vw = 80
ax.set_xlim([-Vw, Vw])
ax.set_ylim([-Vw, Vw])

風(fēng)玫瑰圖(多種形式)

ax = WindroseAxes.from_ax()
ax.bar(df.direction.values, df.speed.values, bins=np.arange(0.01,10,1), cmap=cm.hot, lw=3)
ax.set_legend()

ax = WindroseAxes.from_ax()
ax.box(df.direction.values, df.speed.values, bins=np.arange(0.01,10,1), cmap=cm.hot, lw=3)
ax.set_legend()

plot_windrose(df, kind='contour', bins=np.arange(0.01,8,1), cmap=cm.hot, lw=3)

繪制特定月份風(fēng)玫瑰圖

def plot_month(df, t_year_month, *args, **kwargs):
    by = 'year_month'
    df[by] = df.index.map(lambda dt: (dt.year, dt.month))
    df_month = df[df[by] == t_year_month]
    ax = plot_windrose(df_month, *args, **kwargs)
    return ax
plot_month(df, (2014, 7), kind='contour', bins=np.arange(0, 10, 1), cmap=cm.hot)

plot_month(df, (2014, 8), kind='contour', bins=np.arange(0, 10, 1), cmap=cm.hot)

plot_month(df, (2014, 9), kind='contour', bins=np.arange(0, 10, 1), cmap=cm.hot)

繪制風(fēng)速頻率直方圖

bins = np.arange(0,30+1,1)
bins = bins[1:]
plot_windrose(df, kind='pdf', bins=np.arange(0.01,30,1),normed=True)

在地圖上繪制風(fēng)玫瑰圖

proj = ccrs.PlateCarree()
fig = plt.figure(figsize=(12, 6))
minlon, maxlon, minlat, maxlat = (6.5, 7.0, 45.85, 46.05)
main_ax = fig.add_subplot(1, 1, 1, projection=proj)
main_ax.set_extent([minlon, maxlon, minlat, maxlat], crs=proj)
main_ax.gridlines(draw_labels=True)
main_ax.add_wms(wms='http://vmap0.tiles.osgeo.org/wms/vmap0',layers=['basic'])
cham_lon, cham_lat = (6.8599, 45.9259)
passy_lon, passy_lat = (6.7, 45.9159)
wrax_cham = inset_axes(main_ax,
        width=1,
        height=1,
        loc='center',
        bbox_to_anchor=(cham_lon, cham_lat),
        bbox_transform=main_ax.transData,
        axes_class=windrose.WindroseAxes,

height_deg = 0.1
wrax_passy = inset_axes(main_ax,
        width="100%",
        height="100%",
        bbox_to_anchor=(passy_lon-height_deg/2, passy_lat-height_deg/2, height_deg, height_deg),
        bbox_transform=main_ax.transData,
        axes_class=windrose.WindroseAxes,
        )
wrax_cham.bar(df.direction.values, df.speed.values,bins=np.arange(0.01,10,1), lw=3)
wrax_passy.bar(df.direction.values, df.speed.values,bins=np.arange(0.01,10,1), lw=3)

for ax in [wrax_cham, wrax_passy]:
        ax.tick_params(labelleft=False, labelbottom=False)