Note

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# How to use the LineAnimator¶

This example shows off some ways in which you can use the LineAnimator object to animate line plots.

```
import matplotlib.pyplot as plt
import numpy as np
from mpl_animators import LineAnimator
```

Animate a 2D cube of random data as a line plot along an axis where the x-axis drifts with time.

```
# Define some random data
data_shape0 = (10, 20)
data0 = np.random.rand(*data_shape0)
```

Define the axis that will make up the line plot.

```
plot_axis0 = 1
slider_axis0 = 0
```

Let’s customize the values along the x-axis. To do this, we must define the edges of the pixels/bins being plotted along the x-axis. This requires us to supply an array, say xdata, of length equal to data.shape[plot_axis_index]+1. In this example, the data has a shape of (10, 20) and let’s say we are iterating through the 0th axis and plotting the 1st axis, i.e. plot_axis_index=1. Therefore we need to define an xdata array of length 21. This will give the same customized x-axis values for each frame of the animation. However, what if we want the x-axis values to change as we animate through the other dimensions of the cube? To do this we supply a (10, 21) xdata where each row (i.e. xdata[i, :]) gives the pixel/bin edges along the x-axis for the of the i-th frame of the animation. Note that this API extends in the same way to higher dimension. In our 2D case here though, we can define our non-constant x-axis values like so:

```
xdata = np.tile(np.linspace(0, 100, (data_shape0[plot_axis0] + 1)), (data_shape0[slider_axis0], 1))
```

Generate animation object with variable x-axis data.

```
ani = LineAnimator(data0, plot_axis_index=plot_axis0, axis_ranges=[None, xdata])
plt.show()
```

**Total running time of the script:** ( 0 minutes 0.217 seconds)