The errorshade function plots a shaded region to indicate gaussian uncertainty. This function works by generating an RGB image of a specified color, and setting transparency of the RGB image corresponding to uncertainty values.

## Syntax

errorshade(x,y,sigma,color)
h = errorshade(...)

## Description

errorshade(x,y,sigma,color) plots a gaussian shaded region centered about the line given by x,y. The input sigma represents one standard deviation of shading weight, and color is a three-element vector containing rgb values of the shading color.

errorshade(...,'resolution',res) specifies resolution of the underlying RGB image. res can be a scalar value or a two-element vector in the form [xres yres]. Default resolution is 2500 pixels. Larger values may take longer to plot, smaller values may appear jittery.

errorshade(...,'average',N) specifies an N point moving average to smooth out local spikes in data. Use an odd-numbered integer value because even numbers will result in a slight offset on the horizontal direction. The averaging option requires the Image Processing

h = errorshade(...) returns a handle h of the plotted RGB image.

## Example

This example assumes you have some true value of a quantity, say in units of mV, and you have a noisy measurement of the true value. You know your sensor noise is characterized by +/- 8.5 mV uncertainty. Here's the data:

x = 0:10:500;
y_true =  30*sind(x) + x/10;

sigma = 8.5;
y_measured = y_true + sigma*randn(size(x));


Here's a simple plot of the true and measured values. Below I used my rgb function (also available on File Exchange) to find that the rgb values of dark green are [0.0118 0.2078 0].

figure
plot(x,y_true,'k','linewidth',2)
hold on
plot(x,y_measured,'color',[0.0118 0.2078 0])
ylabel 'some values in mV'
legend('true value','measured value','location','northwest')
legend boxoff But that plot lacks any depiction of uncertainty. It's common to fill in the +/- 1 sigma region with a solid color to represent uncertainty, but if you prefer a little more nuance, here's some shading that's proportional to the actual uncertainty:

h=errorshade(x,y_measured,sigma,[0.0824 0.6902 0.1020]);
legend('true value','measured value \pm\sigma = 8.5 mV uncertainty','location','northwest')
legend boxoff
axis tight In some cases you may want less noisy-looking uncertainty. If that's the case, try shading a moving average. You can specify the length over which the moving average is specified like this, here I'm specifying a 3-point moving average. Also, above I used the h=errorshade(...) syntax in antipation of deleting the old errorshade now:

delete(h) 