Python matplotlib.animation Jupyter Notebook

Question

I use Windows 10 / 64 / Google chrome

I found a good set-up for animation over Jupyter with the call %matplotlib notebook as here :

import numpy as np
import scipy.stats as st
%matplotlib notebook
import matplotlib.pyplot as plt
import matplotlib.animation as animation

For exemple, this one is working pretty well :

n = 100
X = st.norm(0,1).rvs(200)
number_of_frames = np.size(X)

def update_hist(num, second_argument):
    plt.cla()
    plt.hist(X[:num], bins = 20)
    plt.title("{}".format(num))
    plt.legend()

fig = plt.figure()
hist = plt.hist(X)

ani = animation.FuncAnimation(fig, update_hist, number_of_frames, fargs=(X, ), repeat = False )
plt.show()

But, weirdly the code below doesn't work while it's the same structure, it puzzles me :

X = np.linspace(-5,5, 150)
number_of_frames = np.size(X)
N_max = 100
N = np.arange(1,N_max+1)
h = 1/np.sqrt(N)

def update_plot(n, second_argument):
    #plt.cla()
    plt.plot(X, [f(x) for x in X], c = "y", label = "densité")
    plt.plot(X, [fen(sample_sort[:n],h[n],x) for x in X], label = "densité")
    plt.title("n = {}".format(n))

fig = plt.figure(6)
plot = plt.plot(X, [f(x) for x in X], c = "y", label = "densité")
    
ani = animation.FuncAnimation(fig, update_plot, number_of_frames, fargs=(X, ), repeat = False )
plt.show()

Thanks for your help, best regards.

EDIT : You don't have the funciton fen(sample_sort[:n],h[n],x) it is a function from float to float taking a x in argument and returning a flot. The argument sample_sort[:n],h[n] it is just maths things I'm trying to understand some statistics anyway, you can remplace with line with what you want np.cos(N[:n]) for exemple.

EDIT : New code according to the suggestion :

N_max = 100
X = np.linspace(-5,5, N_max )
number_of_frames = np.size(X)
N = np.arange(1,N_max+1)
h = 1/np.sqrt(N)

def update_plot(n):
    #plt.cla()
    lines.set_data(X, np.array([fen(sample_sort[:n],h[n],x) for x in X]))
    ax.set_title("n = {}".format(n))
    return lines

fig = plt.figure()

ax = plt.axes(xlim=(-4, 4), ylim=(-0.01, 1))
ax.plot(X, np.array([f(x) for x in X]), 'y-', lw=2, label="d")
lines, = ax.plot([], [], 'b--', lw=3, label="f")

ani = animation.FuncAnimation(fig, update_plot, number_of_frames, repeat = False )
plt.show()

EDIT 2:

I found a code over internet which does exactly what I would like

# Fermi-Dirac Distribution
def fermi(E: float, E_f: float, T: float) -> float:
    return 1/(np.exp((E - E_f)/(k_b * T)) + 1)

# Create figure and add axes
fig = plt.figure(figsize=(6, 4))
ax = fig.add_subplot(111)

# Get colors from coolwarm colormap
colors = plt.get_cmap('coolwarm', 10)

# Temperature values
T = np.array([100*i for i in range(1,11)])

# Create variable reference to plot
f_d, = ax.plot([], [], linewidth=2.5)

# Add text annotation and create variable reference
temp = ax.text(1, 1, '', ha='right', va='top', fontsize=24)

# Set axes labels
ax.set_xlabel('Energy (eV)')
ax.set_ylabel('Fraction')

# Animation function
def animate(i):
    x = np.linspace(0, 1, 100)
    y = fermi(x, 0.5, T[i])
    f_d.set_data(x, y)
    f_d.set_color(colors(i))
    temp.set_text(str(int(T[i])) + ' K')
    temp.set_color(colors(i))

# Create animation
ani = animation.FuncAnimation(fig, animate, frames=range(len(T)), interval=500, repeat=False)

# Ensure the entire plot is visible
fig.tight_layout()

# show animation
plt.show()

Answer 1

What I want to draw is a curve at random because the actual state of the function is unknown. The basic structure looks like this, so please modify it based on this.

import numpy as np
import scipy.stats as st
# %matplotlib notebook
import matplotlib.pyplot as plt
import matplotlib.animation as animation
# from IPython.display import HTML
# from matplotlib.animation import PillowWriter

X = np.linspace(-5,5, 100)
number_of_frames = np.size(X)
N_max = 100
N = np.arange(1,N_max+1)
h = 1/np.sqrt(N)

def update_plot(n):
    #plt.cla()
    lines.set_data(X[:n], h[:n])
    lines2.set_data(X[:n], h[:n]*-1)
    ax.set_title("n = {}".format(n))
    return lines, lines2

fig = plt.figure()
ax = plt.axes(xlim=(-5, 5), ylim=(-1, 1))
lines, = ax.plot([], [], 'y-', lw=2, label="densité")
lines2, = ax.plot([], [], 'b--', lw=3, label="densité2")

ani = animation.FuncAnimation(fig, update_plot, frames=number_of_frames, repeat=False )
plt.show()
# ani.save('lines_ani2.gif', writer='pillow')

# plt.close()
# HTML(ani.to_html5_video())