您需要最新 (>= 1.2) 版本的 matplotlib,但是streamplot http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.streamplot做这个。您只需要采用头部的负梯度(也称为地表含水层的“地下水位”)网格。
作为从头部随机点观察生成的一个简单示例:
import numpy as np
from scipy.interpolate import Rbf
import matplotlib.pyplot as plt
# Make data repeatable
np.random.seed(1981)
# Generate some random wells with random head (water table) observations
x, y, z = np.random.random((3, 10))
# Interpolate these onto a regular grid
xi, yi = np.mgrid[0:1:100j, 0:1:100j]
func = Rbf(x, y, z, function='linear')
zi = func(xi, yi)
# -- Plot --------------------------
fig, ax = plt.subplots()
# Plot flowlines
dy, dx = np.gradient(-zi.T) # Flow goes down gradient (thus -zi)
ax.streamplot(xi[:,0], yi[0,:], dx, dy, color='0.8', density=2)
# Contour gridded head observations
contours = ax.contour(xi, yi, zi, linewidths=2)
ax.clabel(contours)
# Plot well locations
ax.plot(x, y, 'ko')
plt.show()