Note

Click here to download the full example code

# pcolormesh grids and shading¶

`axes.Axes.pcolormesh`

and `pcolor`

have a few options for
how grids are laid out and the shading between the grid points.

Generally, if *Z* has shape *(M, N)* then the grid *X* and *Y* can be
specified with either shape *(M+1, N+1)* or *(M, N)*, depending on the
argument for the `shading`

keyword argument. Note that below we specify
vectors *x* as either length N or N+1 and *y* as length M or M+1, and
`pcolormesh`

internally makes the mesh matrices *X* and *Y* from
the input vectors.

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

## Flat Shading¶

The grid specification with the least assumptions is `shading='flat'`

and if the grid is one larger than the data in each dimension, i.e. has shape
*(M+1, N+1)*. In that case *X* and *Y* specify the corners of quadrilaterals
that are colored with the values in *Z*. Here we specify the edges of the
*(3, 5)* quadrilaterals with *X* and *Y* that are *(4, 6)*.

```
nrows = 3
ncols = 5
Z = np.arange(nrows * ncols).reshape(nrows, ncols)
x = np.arange(ncols + 1)
y = np.arange(nrows + 1)
fig, ax = plt.subplots()
ax.pcolormesh(x, y, Z, shading='flat', vmin=Z.min(), vmax=Z.max())
def _annotate(ax, x, y, title):
# this all gets repeated below:
X, Y = np.meshgrid(x, y)
ax.plot(X.flat, Y.flat, 'o', color='m')
ax.set_xlim(-0.7, 5.2)
ax.set_ylim(-0.7, 3.2)
ax.set_title(title)
_annotate(ax, x, y, "shading='flat'")
```

## Flat Shading, same shape grid¶

Often, however, data is provided where *X* and *Y* match the shape of *Z*.
As of Matplotlib v3.3, `shading='flat'`

is deprecated when this is the
case, a warning is raised, and the last row and column of *Z* are dropped.
This dropping of the last row and column is what Matplotlib did silently
previous to v3.3, and is compatible with what Matlab does.

Out:

```
/home/circleci/project/examples/images_contours_and_fields/pcolormesh_grids.py:66: MatplotlibDeprecationWarning: shading='flat' when X and Y have the same dimensions as C is deprecated since 3.3. Either specify the corners of the quadrilaterals with X and Y, or pass shading='auto', 'nearest' or 'gouraud', or set rcParams['pcolor.shading']. This will become an error two minor releases later.
ax.pcolormesh(x, y, Z, shading='flat', vmin=Z.min(), vmax=Z.max())
```

## Nearest Shading, same shape grid¶

Usually, dropping a row and column of data is not what the user means when
they make *X*, *Y* and *Z* all the same shape. For this case, Matplotlib
allows `shading='nearest'`

and centers the colored quadrilaterals on the
grid points.

If a grid that is not the correct shape is passed with `shading='nearest'`

an error is raised.

```
fig, ax = plt.subplots()
ax.pcolormesh(x, y, Z, shading='nearest', vmin=Z.min(), vmax=Z.max())
_annotate(ax, x, y, "shading='nearest'")
```

## Auto Shading¶

It's possible that the user would like the code to automatically choose which
to use, in this case `shading='auto'`

will decide whether to use 'flat' or
'nearest' shading based on the shapes of *X*, *Y* and *Z*.

```
fig, axs = plt.subplots(2, 1, constrained_layout=True)
ax = axs[0]
x = np.arange(ncols)
y = np.arange(nrows)
ax.pcolormesh(x, y, Z, shading='auto', vmin=Z.min(), vmax=Z.max())
_annotate(ax, x, y, "shading='auto'; X, Y, Z: same shape (nearest)")
ax = axs[1]
x = np.arange(ncols + 1)
y = np.arange(nrows + 1)
ax.pcolormesh(x, y, Z, shading='auto', vmin=Z.min(), vmax=Z.max())
_annotate(ax, x, y, "shading='auto'; X, Y one larger than Z (flat)")
```

## Gouraud Shading¶

Gouraud shading can also
be specified, where the color in the quadrilaterals is linearly interpolated
between the grid points. The shapes of *X*, *Y*, *Z* must be the same.

### References¶

The use of the following functions and methods is shown in this example:

Out:

```
<function pcolormesh at 0x7ff14c720820>
```

**Total running time of the script:** ( 0 minutes 2.557 seconds)

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