Write me a python function that takes a 2d numpy array which represents a depth map and visualizes it by creating a plot, say, with matplotlib. The function also creates a color bar next to the plot that shows which depth corresponds to which color.
user
Sure. A depth map can be visualized as a matplotlib colormap with the function `matplotlib.colors.LinearSegmentedColormap.from_list()`. Here is the function:
```python
from matplotlib import color
import matplotlib.pyplot as plt

def depth_to_colormap (depth, colorlist):
    cmap = colors.LinearSegmentedColormap.from_list('depth_colormap', colorlist)
    fig, axe  = plt.subplots()
    colormap = axe.imshow(randDepth, aspect="auto", origin="upper", cmap=cmap)
    cbar = fig.colorbar(colormap, ax=axe)
    return
```
`colorlist` is a list of the colors that will be mapped to the depth map, which can be changed to your preference. An example program is as follows:
```python
randDepth = np.random.rand(64, 64)
colorlist = ['#FF0000', '#00FF00', '#0000FF']
depth_to_colormap(randDepth, colorlist)
plt.show()
```
assistant
Great, thanks! One question, what if I want to set the minimum and maximum depth values for the color map? Can I add an option for that in the function?
user
Yes, you can add an option to set the minimum and maximum depth values for the color map in the function. Here's an updated version of the function with the new option:

```python
from matplotlib import colors
import matplotlib.pyplot as plt

def depth_to_colormap(depth, colorlist, vmin=None, vmax=None):
cmap = colors.LinearSegmentedColormap.from_list('depth_colormap', colorlist)
fig, ax = plt.subplots()
colormap = ax.imshow(depth, aspect="auto", origin="upper", cmap=cmap, vmin=vmin, vmax=vmax)
cbar = fig.colorbar(colormap, ax=ax)
return
```

The vmin and vmax arguments set the minimum and maximum values for the color map, respectively. You can pass None for either or both arguments to use the default minimum and maximum values. Here's an example of how to use the new option:

```python
randDepth = np.random.rand(64, 64)
colorlist = ['#FF0000', '#00FF00', '#0000FF']
depth_to_colormap(randDepth, colorlist, vmin=0, vmax=1)
plt.show()
```

In this example, the minimum value for the color map is set to 0 and the maximum value is set to 1.
assistant