`vmax` has no effects without `vmin`

Description

In the old version of proplot, once I set the vmax, the threshold of the plotting figure will change.

But I have to set both vmin and vmax to make it work for the new version.

Steps to reproduce

import proplot as pplt
import numpy as np

# Sample data
state = np.random.RandomState(51423)
x = y = np.array([-10, -5, 0, 5, 10])
data = state.rand(y.size, x.size)

# Figure
fig = pplt.figure(refwidth=2.3, share=False)
axs = fig.subplots()

m = axs.pcolormesh(x, y, data, vmax=1.35)
axs.colorbar([m], loc='r')

Expected behavior:

Actual behavior: [What actually happened]

Proplot version

Paste the results of import matplotlib; print(matplotlib.__version__); import proplot; print(proplot.version)here.

3.3.4
0.8.1

[lukelbd]

Looks like I missed your last comment.

This actually isn’t a bug – it’s a result of proplot feeding vmin and vmax into an algorithm similar to matplotlib’s _autolev algorithm used to determine contour levels. The algorithm tries to generate nice levels and in general does not guarantee an exact match to vmin and vmax (the idea being that vmin and vmax are very often automatically chosen from the data (by default, or when using the robust keyword), and you don’t want to have a discrete level boundary at e.g. 3.12349...).

Although the behavior shown in your example is kind of silly, since vmax=3 is obviously “nice” and shouldn’t be truncated. Will take a look at the algorithm. Note that repeating your example with discrete=False results in an exact match, because “non-discrete” levels do not have to be ticked at vmin/vmax:

import proplot as pplt
import numpy as np

# Sample data
state = np.random.RandomState(51423)
x = y = np.array([-10, -5, 0, 5, 10])
data = state.rand(y.size, x.size)

# Figure
fig = pplt.figure(refwidth=2.3, share=False)
axs = fig.subplots()

m = axs.pcolormesh(x, y, data, vmin=0, vmax=3, discrete=False)
axs.colorbar([m], loc='r')

[zxdawn]

@lukelbd This issue still exists in version 0.9.3:

import proplot as pplt
import numpy as np

# Sample data
state = np.random.RandomState(51423)
x = y = np.array([-10, -5, 0, 5, 10])
data = state.rand(y.size, x.size)

# Figure
fig = pplt.figure(refwidth=2.3, share=False)
axs = fig.subplots()

m = axs.pcolormesh(x, y, data, vmin=0, vmax=3)
axs.colorbar([m], loc='r')