pytutorial/matplotlib/animation_and_slider/README.md

# Animation and Slider
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## The goal


Questions to [David Rotermund](mailto:davrot@uni-bremen.de)


## Test data

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

axis = np.arange(-100, 101) / 100.0

x = axis[:, np.newaxis, np.newaxis].copy()
y = axis[np.newaxis, :, np.newaxis].copy()
z = axis[np.newaxis, np.newaxis, :].copy()

r = np.sqrt(x**2 + y**2 + z**2)

mask_0 = r > 0.75
r = 1.0 / (r + 1.0)
r[mask_0] = 0

plt.imshow(r[100, :, :], cmap="hot")
plt.colorbar()
plt.title("Cut through center of x-axis")
plt.show()
```

![image0](image0.png)

## Animation

### [functools.partial](https://docs.python.org/3/library/functools.html#functools.partial)

```python
functools.partial(func, /, *args, **keywords)
```

> Return a new partial object which when called will behave like func called with the positional arguments args and keyword arguments keywords. If more arguments are supplied to the call, they are appended to args. If additional keyword arguments are supplied, they extend and override keywords. 

### [matplotlib.animation.FuncAnimation](https://matplotlib.org/stable/api/_as_gen/matplotlib.animation.FuncAnimation.html#matplotlib-animation-funcanimation)

```python
class matplotlib.animation.FuncAnimation(fig, func, frames=None, init_func=None, fargs=None, save_count=None, *, cache_frame_data=True, **kwargs)
```

> **fig**: Figure
> 
> The figure object used to get needed events, such as draw or resize.
> 
> **func**: callable
> 
> The function to call at each frame. The first argument will be the next value in frames. Any additional positional arguments can be supplied using functools.partial or via the fargs parameter.
>
> 
> It is often more convenient to provide the arguments using functools.partial. In this way it is also possible to pass keyword arguments. To pass a function with both positional and keyword arguments, set all arguments as keyword arguments, just leaving the frame argument unset:

```python
def func(frame, art, *, y=None):
    ...

ani = FuncAnimation(fig, partial(func, art=ln, y='foo'))
```

> **frames** : iterable, int, generator function, or None, optional
> 
> Source of data to pass func and each frame of the animation
> 
> If an iterable, then simply use the values provided. If the iterable has a length, it will override the save_count kwarg.
> 
> **If an integer, then equivalent to passing range(frames)**
> 
> If a generator function, then must have the signature:

```python
def gen_function() -> obj
```

> If None, then equivalent to passing itertools.count.
> 
> In all of these cases, the values in frames is simply passed through to the user-supplied func and thus can be of any type.
>
> **interval** : int, default: 200
> Delay between frames in milliseconds.
> 
> **repeat_delay** : int, default: 0
> The delay in milliseconds between consecutive animation runs, if repeat is True.
> 
> **repeat** : bool, default: True
> Whether the animation repeats when the sequence of frames is completed.


### Example

```python
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation
from functools import partial


def next_frame(
    i: int, images: np.ndarray, image_handle: matplotlib.image.AxesImage
) -> None:
    image_handle.set_data(images[i, :, :])
    plt.title(f"Position: {i}")
    return


axis = np.arange(-100, 101) / 100.0

x = axis[:, np.newaxis, np.newaxis].copy()
y = axis[np.newaxis, :, np.newaxis].copy()
z = axis[np.newaxis, np.newaxis, :].copy()

r = np.sqrt(x**2 + y**2 + z**2)

mask_0 = r > 0.75
r = 1.0 / (r + 1.0)
r[mask_0] = 0

number_of_frames: int = r.shape[0]
repeat_movie: bool = False
interval_between_frames_in_ms: int = 100

fig: matplotlib.figure.Figure = plt.figure()
# Generate the initial image
# and set the value range for the whole images array
image_handle = plt.imshow(r[0, :, :], vmin=r.min(), vmax=r.max(), cmap="hot")
plt.colorbar()

animation = matplotlib.animation.FuncAnimation(
    fig,
    partial(next_frame, images=r, image_handle=image_handle),
    frames=number_of_frames,
    interval=interval_between_frames_in_ms,
    repeat=repeat_movie,
)

plt.show()
```

## Save the animation

```python
save(filename[, writer, fps, dpi, codec, ...])
```

> Save the animation as a movie file by drawing every frame.

You need to add the save-method between **animation = matplotlib.animation.FuncAnimation(...)** and **plt.show()**.

```python
movie_filename: str | None = "movie.mp4"

if movie_filename is not None:
    animation.save(movie_filename)
```

Please note that you may need the [ffmpeg binaries](https://www.ffmpeg.org/download.html) for MP4. The ffmpeg files need to be accessable by Python. i.e. Python needs to know where they are. Under Windows it is helpful to place the three exe files in the binary directory of Python. Under Linux, the distribution package manager should take care of it.  

## Interactive Python session

There are several options if you don't run it from VS Code interactively. One options is this: 

```python
# %%
%matplotlib widget
```

Another one is this: 

```python
# %%
%matplotlib tk
```

Please check yourself which suits your setup best.