Wsrtjtyk

I have a 2D array value_1 which depends on lon(longitude) and lat(latitude).
Now, I can use pcolormesh to plot the value on one figure.

But, I have another 3D array value_2 which depends on lon, lat and pressure (levels of pressure).

If I want to show the profile (depends on value_2 and pressure) and coordinate like this: (-120,20) when the mouse hover or click on one grid(lon,lat), how could I make it?

Here's the example of plotting pseudocolor plot and profile plot:

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])

I'm sure there a more efficient way to get the right indices when hovering over the pcolormesh, but this does the trick:

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()