# Matplotlib animation step

I am creating a Matplotlib animation of a step function. I am using the following code ...

``````import numpy as np
from matplotlib import pyplot as plt
from matplotlib import animation

fig = plt.figure()
ax = plt.axes(xlim=(0, 2), ylim=(-2, 2))

line, = ax.step([], [])

def init():
line.set_data([], [])
return line,

def animate(i):
x = np.linspace(0, 2, 10)
y = np.sin(2 * np.pi * (x - 0.01 * i))
line.set_data(x, y)
return line,

anim = animation.FuncAnimation(fig, animate, init_func=init,
frames=100, interval=20, blit=True)

plt.show()
```

```

This vaguely resembles what I want (something like a gif below), but instead of the values ​​being constant and scrolling over time, each step is dynamic and moves up and down. How would my code change to achieve this change?

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`step`

explicitly displays steps between input data points. He can never build a partial "step".

You want animation with "partial steps" in between.

Instead of using, `ax.step`

use `ax.plot`

but make a staggered series by building `y = y - y % step_size`

.

In other words, something like:

``````import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0, 10, 1000) # Using a series of 1000 points...
y = np.sin(x)

# Make *y* increment in steps of 0.3
y -= y % 0.3

fig, ax = plt.subplots()
ax.plot(x, y)
plt.show()
```

```

Notice the partial "steps" at the beginning and end

By incorporating this into our animation example, we end up with something similar to:

``````import numpy as np
from matplotlib import pyplot as plt
from matplotlib import animation

fig = plt.figure()
ax = plt.axes(xlim=(0, 2), ylim=(-2, 2))

line, = ax.plot([], [])

def init():
line.set_data([], [])
return line,

def animate(i):
x = np.linspace(0, 2, 1000)
y = np.sin(2 * np.pi * (x - 0.01 * i))
y -= y % 0.3
line.set_data(x, y)
return line,

anim = animation.FuncAnimation(fig, animate, init_func=init,
frames=100, interval=20, blit=True)

plt.show()
```

```

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