#!/usr/bin/env python
# coding: utf-8

# ## for SO https://stackoverflow.com/q/75006292/8508004
# 
# The example by Louis Tiao (see http://louistiao.me/posts/notebooks/embedding-matplotlib-animations-in-jupyter-as-interactive-javascript-widgets/) seems to be what Gulraiz is using even though no attribution is given. (Louis Tiao cites Jake VanderPlas.)
# 
# There was stuff missing. I probably have a version of this somewhere but these work in [this environment January 2023](https://github.com/fomightez/animated_matplotlib-binder/tree/9cebb12b49ffe2c297398ad95a5a66afa39dcaf1)(specific commit used recorded in link).  
# And I saw they worked in JupyterLab in that environment as well.

# This first is based example by Louis Tiao (see http://louistiao.me/posts/notebooks/embedding-matplotlib-animations-in-jupyter-as-interactive-javascript-widgets/) and source code from StackOverflow with approach like https://nbviewer.org/github/raphaelquast/jupyter_notebook_intro/blob/master/jupyter_nb_introduction.ipynb#pre-render-animations-and-export-to-HTML

# In[3]:


import numpy as np
import matplotlib.pyplot as plt
from matplotlib import animation
from IPython.display import HTML, display
plt.style.use('seaborn-v0_8-pastel')

def generate_animation():
    fig = plt.figure()
    ax = plt.axes(xlim=(0, 4), ylim=(-2, 2))
    lineplot, = ax.plot([], [], lw=3)
    
    def init():
        lineplot.set_data([], [])
        return lineplot, #return [lineplot] also works like in https://nbviewer.org/github/raphaelquast/jupyter_notebook_intro/blob/master/jupyter_nb_introduction.ipynb#pre-render-animations-and-export-to-HTML

    def animate(i):
        x = np.linspace(0, 4, 1000)
        y = np.sin(2 * np.pi * (x - 0.01 * i))
        lineplot.set_data([x], [y])
        return [lineplot]

    anim = animation.FuncAnimation(fig, animate, init_func=init,
                               frames=200, interval=20, blit=True)

    display(HTML(anim.to_jshtml()))
    plt.close(fig)

generate_animation()


# This second is based on more along line of example by Louis Tiao (see http://louistiao.me/posts/notebooks/embedding-matplotlib-animations-in-jupyter-as-interactive-javascript-widgets/) and source code from StackOverflow  where uses rcParams to set jshtml. I've used something much similar like that [here](https://gist.github.com/fomightez/d862333d8eefb94a74a79022840680b1) and that is sort of what I based it on. It basically handles the `display(HTML(anim.to_jshtml()))` part a little more implicitly (albeit maybe explicitly is the better way to go in most cases [plus that method doesn't seem to require running twice at present??] - I had used the other somewhere and so easier to have both examples around).

# In[3]:


# RUN THIS TWICE. SECOND TIME WILL BE NICE SINGLE PLOT DIPLAYED.
# January 2023 I was finding first time I ran this or code like at https://nbviewer.org/gist/fomightez/d862333d8eefb94a74a79022840680b1 that it output a non-interactive frame of plot, too. Just re-ran and then it is just the interactive one with widget.

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import animation
from IPython.display import HTML, display
plt.rcParams["animation.html"] = "jshtml"
plt.ioff() #needed so the second time you run it you get only single plot
plt.style.use('seaborn-v0_8-pastel')

fig = plt.figure()
ax = plt.axes(xlim=(0, 4), ylim=(-2, 2))
lineplot, = ax.plot([], [], lw=3)
    
def init():
    lineplot.set_data([], [])
    return lineplot, #return [lineplot] also works like in https://nbviewer.org/github/raphaelquast/jupyter_notebook_intro/blob/master/jupyter_nb_introduction.ipynb#pre-render-animations-and-export-to-HTML

def animate(i):
    x = np.linspace(0, 4, 1000)
    y = np.sin(2 * np.pi * (x - 0.01 * i))
    lineplot.set_data([x], [y])
    return [lineplot]

anim = animation.FuncAnimation(fig, animate, init_func=init,
                           frames=200, interval=20, blit=True)
anim


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