鼠标悬停/单击网格时，Python显示相应的配置文件

Question

我有一个二维数组value_1，它取决于lon（经度）和lat（纬度）。 现在，我可以使用pcolormesh将值绘制在一个图形上。

但是，我还有另一个3D数组value_2，它取决于lon，lat和pressure（压力级别）。

如果我想显示配置文件（取决于value_2和pressure）并像这样进行协调：(-120,20)，当鼠标悬停或单击一个网格（lon，lat）时，我该怎么做？

下面是绘制pseudocolor plot和profile plot的示例：

import numpy as np
import matplotlib.pyplot as plt

# coordination
lon = np.arange(-120,-110,1)
lat = np.arange(20,30,1)

# shape of value_1: (lon,lat)
# pseudocolor plot

value_1 = np.random.rand(9,9)
pressure = np.arange(1110,500,-100)
lon,lat = np.meshgrid(lon,lat)
plt.pcolormesh(lon,lat,value_1)

plt.colorbar()
plt.show()

# shape of value_2: (lon,lat,pressure)
# profile plot
# Used to plot profile when mouse hovers on one grid

value_2 = np.random.rand(9,9,pressure.shape[0])

Answer 1

我确信将鼠标悬停在pcolormesh上时，可以找到一种更有效的方法来获取正确的索引，但这可以解决问题：

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as gs
from math import floor

# coordination
lon = np.arange(-120, -110, 1)
lat = np.arange(20, 30, 1)

# shape of value_1: (lon,lat)
# pseudocolor plot
value_1 = np.random.rand(9, 9)
pressure = np.arange(1110, 500, -100)
mlon, mlat = np.meshgrid(lon, lat)

# shape of value_2: (lon,lat,pressure)
# profile plot
# Used to plot profile when mouse hovers on one grid
value_2 = np.random.rand(9, 9, pressure.shape[0])

# global variables to keep track of which values
# are currently plotted in ax2
current_lat, curret_lon = None, None

fig, (ax1, ax2) = plt.subplots(2,1)

m = ax1.pcolormesh(mlon, mlat, value_1)
fig.colorbar(m, ax=ax1)
fig.tight_layout()


def on_move(event):
    global current_lat, current_lon
    if event.inaxes is ax1:
        event_lat = floor(event.ydata)
        event_lon = floor(event.xdata)
        # find the indices corresponding to lat,lon
        id_lat = np.searchsorted(lat, event_lat)
        id_lon = np.searchsorted(lon, event_lon)

        # only plot if we have different values than the previous plot
        if id_lat != current_lat or id_lon != current_lon:
            current_lat = id_lat
            current_lon = id_lon
            ax2.cla()
            ax2.plot(value_2[id_lat, id_lon, :], pressure)
            ax2.set_title("lat: {:.0f}, lon: {:.0f}".format(event_lat, event_lon))
            fig.canvas.draw_idle()

cid = fig.canvas.mpl_connect('motion_notify_event', on_move)

plt.show()