prompter: I have the following python code:

```python
plt.imshow(x_train[0], cmap='gray', interpolation = 'nearest')
```

I'm looking for a colormap that interpolates from blue through white to red. How do i do that?

assistant: Some colormap presets that interpolate from blue through white to red in matplotlib are the ```bwr``` and ```coolwarm``` diverging colormaps.

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

gradient = np.linspace(0, 1, 256)
gradient = np.vstack((gradient, gradient))

plt.imshow(gradient, aspect='auto', cmap='bwr')
```

prompter: How would I make my own colormap instead of relying on a preset?

assistant: To make your own colormap you can use matplotlib `LinearSegmentedColormap`. In the below code I show you how to use it and how to enter colors in a few different formats.

```py
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap, LinearSegmentedColormap
import matplotlib.colors as mcolors

# I'll show you multiple ways to enter colors
blue = (0, 0, 1, 1)  # you can use a rgba tuple
white = mcolors.to_hex('white') # a name or a hex string, here we are converting from a name to a hex string
cmap = LinearSegmentedColormap.from_list("mycmap", [blue, white, 'red'])

gradient = np.linspace(0, 1, 256)
gradient = np.vstack((gradient, gradient))

# now you pass in your colormap object into the cmap argument in pyplot plotting methods
plt.imshow(gradient, aspect='auto', cmap=cmap)
```

assistant: You can use the "Blues_r" colormap in the matplotlib library, which interpolates from blue through white to red. To use this colormap, you can modify the code as follows:

plt.imshow(x_train[0], cmap='Blues_r', interpolation = 'nearest')

The _r in "Blues_r" indicates that the colormap is reversed, which means that it goes from blue to red, instead of from red to blue. The interpolation argument is used to specify the interpolation method for resampling the image data. The value 'nearest' indicates that the nearest-neighbor interpolation method should be used.

prompter: I'm not really satisfied with the looks of the result. Can you give me a list of all available colormaps in matplotlib?

assistant: I can. The below python code (credit to the matplotlib docs) contains a python object `cmaps` showing all the colormaps sorted by category. As a bonus you can also run the code to see how each colormap looks.

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

cmaps = [('Perceptually Uniform Sequential', [
            'viridis', 'plasma', 'inferno', 'magma', 'cividis']),
         ('Sequential', [
            'Greys', 'Purples', 'Blues', 'Greens', 'Oranges', 'Reds',
            'YlOrBr', 'YlOrRd', 'OrRd', 'PuRd', 'RdPu', 'BuPu',
            'GnBu', 'PuBu', 'YlGnBu', 'PuBuGn', 'BuGn', 'YlGn']),
         ('Sequential (2)', [
            'binary', 'gist_yarg', 'gist_gray', 'gray', 'bone', 'pink',
            'spring', 'summer', 'autumn', 'winter', 'cool', 'Wistia',
            'hot', 'afmhot', 'gist_heat', 'copper']),
         ('Diverging', [
            'PiYG', 'PRGn', 'BrBG', 'PuOr', 'RdGy', 'RdBu',
            'RdYlBu', 'RdYlGn', 'Spectral', 'coolwarm', 'bwr', 'seismic']),
         ('Cyclic', ['twilight', 'twilight_shifted', 'hsv']),
         ('Qualitative', [
            'Pastel1', 'Pastel2', 'Paired', 'Accent',
            'Dark2', 'Set1', 'Set2', 'Set3',
            'tab10', 'tab20', 'tab20b', 'tab20c']),
         ('Miscellaneous', [
            'flag', 'prism', 'ocean', 'gist_earth', 'terrain', 'gist_stern',
            'gnuplot', 'gnuplot2', 'CMRmap', 'cubehelix', 'brg',
            'gist_rainbow', 'rainbow', 'jet', 'turbo', 'nipy_spectral',
            'gist_ncar'])]

gradient = np.linspace(0, 1, 256)
gradient = np.vstack((gradient, gradient))


def plot_color_gradients(cmap_category, cmap_list):
    # Create figure and adjust figure height to number of colormaps
    nrows = len(cmap_list)
    figh = 0.35 + 0.15 + (nrows + (nrows-1)*0.1)*0.22
    fig, axs = plt.subplots(nrows=nrows, figsize=(6.4, figh))
    fig.subplots_adjust(top=1-.35/figh, bottom=.15/figh, left=0.2, right=0.99)

    axs[0].set_title(f"{cmap_category} colormaps", fontsize=14)

    for ax, cmap_name in zip(axs, cmap_list):
        ax.imshow(gradient, aspect='auto', cmap=cmap_name)
        ax.text(-.01, .5, cmap_name, va='center', ha='right', fontsize=10,
                transform=ax.transAxes)

    # Turn off *all* ticks & spines, not just the ones with colormaps.
    for ax in axs:
        ax.set_axis_off()


for cmap_category, cmap_list in cmaps:
    plot_color_gradients(cmap_category, cmap_list)
```

assistant: Yes, here is a list of all available colormaps in Matplotlib:

Accent
Accent_r
Blues
Blues_r
BrBG
BrBG_r
BuGn
BuGn_r
BuPu
BuPu_r
CMRmap
CMRmap_r
Dark2
Dark2_r
GnBu
GnBu_r
Greens
Greens_r
Greys
Greys_r
OrRd
OrRd_r
Oranges
Oranges_r
PRGn
PRGn_r
Paired
Paired_r
Pastel1
Pastel1_r
Pastel2
Pastel2_r
PiYG
PiYG_r
PuBu
PuBuGn
PuBuGn_r
PuBu_r
PuOr
PuOr_r
PuRd
PuRd_r
Purples
Purples_r
RdBu
RdBu_r
RdGy
RdGy_r
RdPu
RdPu_r
RdYlBu
RdYlBu_r
RdYlGn
RdYlGn_r
Reds
Reds_r
Set1
Set1_r
Set2
Set2_r
Set3
Set3_r
Spectral
Spectral_r
Wistia
Wistia_r
YlGn
YlGnBu
YlGnBu_r
YlGn_r
YlOrBr
YlOrBr_r
YlOrRd
YlOrRd_r
afmhot
afmhot_r
autumn
autumn_r
binary
binary_r
bone
bone_r
brg
brg_r
bwr
bwr_r
cividis
cividis_r
cool
cool_r
coolwarm
coolwarm_r
copper
copper_r
cubehelix
cubehelix_r
flag
flag_r
gist_earth
gist_earth_r
gist_gray
gist_gray_r
gist_heat
gist_heat_r
gist_ncar
gist_ncar_r
gist_rainbow
gist_rainbow_r
gist_stern
gist_stern_r
gist_yarg
gist_yarg_r
gnuplot
gnu

assistant: Great question! There are several colormap options built in to matplotlib. The one that best fits your description of interpolating from blue to white to red is "bwr".
Your code would then look like this:

```python
plt.imshow(x_train[0], cmap='bwr', interpolation = 'nearest')
```

For a complete list of color maps, you can take a look at https://matplotlib.org/stable/tutorials/colors/colormaps.html

prompter: Can you do the same in C++ ?

assistant: Of course, but you will need to install an additional library for image visualization in C++. One such popular library is OpenCV. Here's an example of displaying an image using the "bwr" colormap:

```
#include <opencv2/opencv.hpp>
#include <iostream>

using namespace cv;
using namespace std;

int main()
{
    Mat img = imread("image.jpg");

    Mat bwr_image;
    applyColorMap(img, bwr_image, COLORMAP_BWR);

    namedWindow("BWR Image", WINDOW_NORMAL);
    imshow("BWR Image", bwr_image);
    waitKey(0);
}
```

Simply replace "image.jpg" with your image file. The `applyColorMap` applies the given colormap to the input image, in this case, `COLORMAP_BWR`, and the final result is displayed using the `imshow` function.

assistant: Of course. Here is the same script rewritten in C++:


```C++
Mat img = x_train[0];
applyColorMap(img, COLORMAP_BWR);
imshow("Image", img);
```

As with the Python code, you can find a full list of colormaps for C++ at https://docs.opencv.org/.