Bug report

Bug summary

When a scatter plot is made with data that contains np.nan (NaN), and then a color array is given using set_color, the wrong colors get mapped to the data points.

Code for reproduction

from matplotlib import pyplot
from matplotlib.colors import Normalize
from matplotlib import cm
import numpy as np

x = np.linspace(0.0, 1.0, 50)
y = np.linspace(0.0, 1.0, 50)
norm = Normalize(0.0, 1.0)
colormap = cm.ScalarMappable(norm, 'gnuplot')
colors = colormap.to_rgba(y)

# Expected colors with when x and y do not contain any np.nan.
# Success.
plot = pyplot.scatter(x, y, color=colors)
pyplot.show()

# Add some nan values.  
# If the color array is given during the initial creation of the
# scatter plot, then everything works as expected.
# Success.
x[10:40] = np.nan
plot = pyplot.scatter(x, y, color=colors)
pyplot.show()

# Again add some nan values.  
# If the color array is given as a call to set_color
# then the colors no longer match the data.
# Failure.
x[10:40] = np.nan
plot = pyplot.scatter(x, y)
plot.set_color(colors)
pyplot.show()

Actual outcome

Top: Expected colors with when x and y do not contain any np.nan.

Middle: Add some nan values. If the color array is given during the initial creation of the scatter plot, then everything works as expected.

Bottom: Again add some nan values. If the color array is given as a call to set_color then the colors no longer match the data.

Expected outcome

The colors corresponding to the data points should be displayed, even when data points contain NaN and set_color is used.

Matplotlib version

• Operating system: OSX
• Matplotlib version: 2.0.2
• Matplotlib backend: module://ipykernel.pylab.backend_inline & MacOSX
• Python version: 3.6.3
• Jupyter Notebook version: 5.2.0
• Other libraries: None