Animated interactive plot using matplotlib

Question

While looking for a way to make animated interactive plot using matplotlib, I encountered this piece of code on Stack overflow documentation:

import numpy as         


        

Answer 1

You may adapt the code from this answer to include a slider.

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
import mpl_toolkits.axes_grid1
import matplotlib.widgets

class Player(FuncAnimation):
    def __init__(self, fig, func, frames=None, init_func=None, fargs=None,
                 save_count=None, mini=0, maxi=100, pos=(0.125, 0.92), **kwargs):
        self.i = 0
        self.min=mini
        self.max=maxi
        self.runs = True
        self.forwards = True
        self.fig = fig
        self.func = func
        self.setup(pos)
        FuncAnimation.__init__(self,self.fig, self.update, frames=self.play(), 
                                           init_func=init_func, fargs=fargs,
                                           save_count=save_count, **kwargs )    

    def play(self):
        while self.runs:
            self.i = self.i+self.forwards-(not self.forwards)
            if self.i > self.min and self.i < self.max:
                yield self.i
            else:
                self.stop()
                yield self.i

    def start(self):
        self.runs=True
        self.event_source.start()

    def stop(self, event=None):
        self.runs = False
        self.event_source.stop()

    def forward(self, event=None):
        self.forwards = True
        self.start()
    def backward(self, event=None):
        self.forwards = False
        self.start()
    def oneforward(self, event=None):
        self.forwards = True
        self.onestep()
    def onebackward(self, event=None):
        self.forwards = False
        self.onestep()

    def onestep(self):
        if self.i > self.min and self.i < self.max:
            self.i = self.i+self.forwards-(not self.forwards)
        elif self.i == self.min and self.forwards:
            self.i+=1
        elif self.i == self.max and not self.forwards:
            self.i-=1
        self.func(self.i)
        self.slider.set_val(self.i)
        self.fig.canvas.draw_idle()

    def setup(self, pos):
        playerax = self.fig.add_axes([pos[0],pos[1], 0.64, 0.04])
        divider = mpl_toolkits.axes_grid1.make_axes_locatable(playerax)
        bax = divider.append_axes("right", size="80%", pad=0.05)
        sax = divider.append_axes("right", size="80%", pad=0.05)
        fax = divider.append_axes("right", size="80%", pad=0.05)
        ofax = divider.append_axes("right", size="100%", pad=0.05)
        sliderax = divider.append_axes("right", size="500%", pad=0.07)
        self.button_oneback = matplotlib.widgets.Button(playerax, label='$\u29CF$')
        self.button_back = matplotlib.widgets.Button(bax, label='$\u25C0$')
        self.button_stop = matplotlib.widgets.Button(sax, label='$\u25A0$')
        self.button_forward = matplotlib.widgets.Button(fax, label='$\u25B6$')
        self.button_oneforward = matplotlib.widgets.Button(ofax, label='$\u29D0$')
        self.button_oneback.on_clicked(self.onebackward)
        self.button_back.on_clicked(self.backward)
        self.button_stop.on_clicked(self.stop)
        self.button_forward.on_clicked(self.forward)
        self.button_oneforward.on_clicked(self.oneforward)
        self.slider = matplotlib.widgets.Slider(sliderax, '', 
                                                self.min, self.max, valinit=self.i)
        self.slider.on_changed(self.set_pos)

    def set_pos(self,i):
        self.i = int(self.slider.val)
        self.func(self.i)

    def update(self,i):
        self.slider.set_val(i)


### using this class is as easy as using FuncAnimation:            

fig, ax = plt.subplots()
x = np.linspace(0,6*np.pi, num=100)
y = np.sin(x)

ax.plot(x,y)
point, = ax.plot([],[], marker="o", color="crimson", ms=15)

def update(i):
    point.set_data(x[i],y[i])

ani = Player(fig, update, maxi=len(y)-1)

plt.show()

Answer 2

Here is a simple adaptation of your code to add animation:

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from matplotlib.widgets import Slider

TWOPI = 2*np.pi

fig, ax = plt.subplots()

t = np.arange(0.0, TWOPI, 0.001)
initial_amp = .5
s = initial_amp*np.sin(t)
l, = plt.plot(t, s, lw=2)

ax = plt.axis([0,TWOPI,-1,1])

axamp = plt.axes([0.25, .03, 0.50, 0.02])
# Slider
samp = Slider(axamp, 'Amp', 0, 1, valinit=initial_amp)

# Animation controls
is_manual = False # True if user has taken control of the animation
interval = 100 # ms, time between animation frames
loop_len = 5.0 # seconds per loop
scale = interval / 1000 / loop_len

def update_slider(val):
    global is_manual
    is_manual=True
    update(val)

def update(val):
    # update curve
    l.set_ydata(val*np.sin(t))
    # redraw canvas while idle
    fig.canvas.draw_idle()

def update_plot(num):
    global is_manual
    if is_manual:
        return l, # don't change

    val = (samp.val + scale) % samp.valmax
    samp.set_val(val)
    is_manual = False # the above line called update_slider, so we need to reset this
    return l,

def on_click(event):
    # Check where the click happened
    (xm,ym),(xM,yM) = samp.label.clipbox.get_points()
    if xm < event.x < xM and ym < event.y < yM:
        # Event happened within the slider, ignore since it is handled in update_slider
        return
    else:
        # user clicked somewhere else on canvas = unpause
        global is_manual
        is_manual=False

# call update function on slider value change
samp.on_changed(update_slider)

fig.canvas.mpl_connect('button_press_event', on_click)

ani = animation.FuncAnimation(fig, update_plot, interval=interval)

plt.show()

The main change is the addition of the update_plot function, which is used to make a FuncAnimation in the second to last line. The animation increments from the last slider value that was set.

The variable is_manual keeps track of when the user has clicked on the slider. After the user clicks on it, the variable is set to True and the animation will no longer update the plot.

To resume animation, I added an on_click function which sets is_manual = False when the user clicks somewhere on the canvas OTHER than the slider.

Since this is a quick-and-dirty script I left variables as global, but you could easily write it up in a proper class.

Note that calling samp.set_val implicitly calls the update_slider function, which is also called when the user clicks directly on the slider, so we have to reset is_manual in the update_plot function.