So, I thought this was going to be really simple, but I've been having a lot of difficult finding exactly what I'm looking for in a comprehensible example.

Basically I want to make phase plots, so assuming I have a 2d array, how can I get matplotlib to convert this to a plot that I can attach titles, axes, and legends (color bars) to.

I'm looking for an extremely simple bare bones solution that only uses what is required that will work with any 2D array.

I'm certain this is simple and I'm just being thick somehow, but I'm really having a lot of trouble with this.

I have been tooling with the examples, but they don't seem well suited to what I'm trying to do: I like the general appearance of this graph, I'd just like to be able to pass in a 2dArray and have this same result:

```
import numpy as np
import matplotlib as ml
import matplotlib.pyplot as plt
H = [[1,2,3,4][5,6,7,8][9,10,11,12][13,14,15,16]]
fig = plt.figure(figsize=(6, 3.2))
ax = fig.add_subplot(111)
ax.set_title('colorMap')
X,Y = np.meshgrid(xedges, yedges)
plt.pcolormesh(X, Y, H)
ax.set_aspect('equal')
cax = fig.add_axes([0.12, 0.1, 0.78, 0.8])
cax.get_xaxis().set_visible(False)
cax.get_yaxis().set_visible(False)
cax.patch.set_alpha(0)
cax.set_frame_on(False)
plt.colorbar(orientation='vertical')
plt.show()
```

This question is related to
`python`

`numpy`

`matplotlib`

`plot`

I'm afraid your posted example is not working, since X and Y aren't defined. So instead of `pcolormesh`

let's use `imshow`

:

```
import numpy as np
import matplotlib.pyplot as plt
H = np.array([[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12],
[13, 14, 15, 16]]) # added some commas and array creation code
fig = plt.figure(figsize=(6, 3.2))
ax = fig.add_subplot(111)
ax.set_title('colorMap')
plt.imshow(H)
ax.set_aspect('equal')
cax = fig.add_axes([0.12, 0.1, 0.78, 0.8])
cax.get_xaxis().set_visible(False)
cax.get_yaxis().set_visible(False)
cax.patch.set_alpha(0)
cax.set_frame_on(False)
plt.colorbar(orientation='vertical')
plt.show()
```

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