如何在matplotlib中制作两个滑块

我想在 matplotlib 中制作两个滑块来手动更改捕食者-猎物模型中的 N 和 P 值：

import numpy as np
import matplotlib.pyplot as plt
from scipy.integrate import odeint

def lotka(x,t,params):
    N, P = x 
    alpha, beta, gamma, delta = params 
    derivs = [alpha*N - beta*N*P, gamma*N*P - delta*P] 
    return derivs

N=2
P=1
alpha=3
beta=0.5
gamma=0.4
delta=3

params = [alpha, beta, gamma, delta]
x0=[N,P]
maxt = 20
tstep = 0.01

t=np.arange(0,maxt,tstep)
equation=odeint(lotka, x0, t, args=(params,))

plt.plot(t,equation)
plt.xlabel("Time")
plt.ylabel("Population size")
plt.legend(["Prey", "Predator"], loc="upper right")

plt.title('Prey & Predator Static Model')
plt.grid(color="b", alpha=0.5, linestyle="dashed", linewidth=0.5)

这是我的代码，它生成 N 和 P 的固定初始值的图表。但是，我想更改它们以查看绘图如何变化。为此，我想使用如下滑块：http://matplotlib.org/users/screenshots.html#slider-demo但我不知道如何将其添加到我的代码中......

有人可以给我任何指示吗？非常感谢！！ xx

从这个例子中，希望评论能帮助你理解什么是：

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.widgets import Slider, Button, RadioButtons
from scipy.integrate import odeint

# Function to draw
def lotka(x, t, params):
    N, P = x
    alpha, beta, gamma, delta = params 
    derivs = [alpha*N - beta*N*P, gamma*N*P - delta*P] 
    return derivs

# Parameters
Nmin = 1
Nmax = 100
Pmin = 1
Pmax = 100
N0 = 2
P0 = 1
alpha = 3
beta = 0.5
gamma = 0.4
delta = 3

params = [alpha, beta, gamma, delta]
x0=[N0,P0]
maxt = 20
tstep = 0.01

# Initial function values
t = np.arange(0, maxt, tstep)
prey, predator = odeint(lotka, x0, t, args=(params,)).T
# odeint returne a shape (2000, 2) array, with the value for
# each population in [[n_preys, n_predators], ...]
# The .T at the end transponses the array, so now we get each population
# over time in each line of the resultint (2, 2000) array.

# Create a figure and an axis to plot in:
fig = plt.figure()
ax = fig.add_axes([0.10, 0.3, 0.8, 0.6])
prey_plot = ax.plot(t, prey, label="Prey")[0]
predator_plot = ax.plot(t, predator, label="Predator")[0]

ax.set_xlabel("Time")
ax.set_ylabel("Population size")
ax.legend(loc="upper right")
ax.set_title('Prey & Predator Static Model')
ax.grid(color="b", alpha=0.5, linestyle="dashed", linewidth=0.5)
ax.set_ylim([0, np.max([prey, predator])])

# create a space in the figure to place the two sliders:
axcolor = 'lightgoldenrodyellow'
axis_N = fig.add_axes([0.10, 0.1, 0.8, 0.03], facecolor=axcolor)
axis_P = fig.add_axes([0.10, 0.15, 0.8, 0.03], facecolor=axcolor)
# the first argument is the rectangle, with values in percentage of the figure
# size: [left, bottom, width, height]

# create each slider on its corresponding place:
slider_N = Slider(axis_N, 'N', Nmin, Nmax, valinit=N0)
slider_P = Slider(axis_P, 'P', Pmin, Pmax, valinit=P0)

def update(val):
    # retrieve the values from the sliders
    x = [slider_N.val, slider_P.val]
    # recalculate the function values
    prey, predator = odeint(lotka, x, t, args=(params,)).T
    # update the value on the graph
    prey_plot.set_ydata(prey)
    predator_plot.set_ydata(predator)
    # redraw the graph
    fig.canvas.draw_idle()
    ax.set_ylim([0, np.max([prey, predator])])

# set both sliders to call update when their value is changed:
slider_N.on_changed(update)
slider_P.on_changed(update)

# create the reset button axis (where its drawn)
resetax = plt.axes([0.8, 0.025, 0.1, 0.04])
# and the button itself
button = Button(resetax, 'Reset', color=axcolor, hovercolor='0.975')

def reset(event):
    slider_N.reset()
    slider_P.reset()

button.on_clicked(reset)

但请注意，您应该有显示了您的尝试方式使示例适应您所拥有的情况以及它的错误行为。

尽管如此，欢迎来到 Stackoverflow。