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Signed-off-by: David Rotermund <54365609+davrot@users.noreply.github.com>
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matplotlib/animation_and_slider/README.md
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@ -187,4 +187,89 @@ Another one is this:
Please check yourself which suits your setup best.
## [matplotlib.widgets.Slider](https://matplotlib.org/stable/api/widgets_api.html#matplotlib.widgets.Slider)
```python
class matplotlib.widgets.Slider(ax, label, valmin, valmax, *, valinit=0.5, valfmt=None, closedmin=True, closedmax=True, slidermin=None, slidermax=None, dragging=True, valstep=None, orientation='horizontal', initcolor='r', track_color='lightgrey', handle_style=None, **kwargs)
```
> A slider representing a floating point range.
>
> Create a slider from valmin to valmax in Axes ax. For the slider to remain responsive you must maintain a reference to it. Call on_changed() to connect to the slider event.
>
> **ax** : Axes
>
> The Axes to put the slider in.
>
> **label** : str
>
> Slider label.
>
> **valmin** : float
>
> The minimum value of the slider.
>
> **valmax** : float
>
> The maximum value of the slider.
>
> **valinit** : float, default: 0.5
> The slider initial position.
>
> **valstep** : float or array-like, default: None
>
> If a float, the slider will snap to multiples of valstep. If an array the slider will snap to the values in the array.
>
> **orientation** : {'horizontal', 'vertical'}, default: 'horizontal'
>
> The orientation of the slider.
### Example
```python
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
from matplotlib.widgets import Slider
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()
axfreq = fig.add_axes([0.4, 0.9, 0.3, 0.03])
slice_slider = Slider(
ax=axfreq, label="Slice", valmin=0, valmax=r.shape[0] - 1, valinit=0, valstep=1
)
slice_slider.on_changed(partial(next_frame, images=r, image_handle=image_handle))
plt.show()
```