rose

Angle histogram plot

rose is not recommended. Use polarhistogram instead.

Syntax

rose(theta)
rose(theta,x)
rose(theta,nbins)
rose(ax,...)
h = rose(...)
[tout,rout] = rose(...)


Description

rose(theta) creates an angle histogram, which is a polar plot showing the distribution of values grouped according to their numeric range, showing the distribution of theta in 20 angle bins or less. The vector theta, expressed in radians, determines the angle of each bin from the origin. The length of each bin reflects the number of elements in theta that fall within a group, which ranges from 0 to the greatest number of elements deposited in any one bin.

rose(theta,x) uses the vector x to specify the number and the locations of bins. length(x) is the number of bins and the values of x specify the center angle of each bin. For example, if x is a five-element vector, rose distributes the elements of theta in five bins centered at the specified x values.

rose(theta,nbins) plots nbins equally spaced bins in the range [0,2*pi]. The default is 20.

rose(ax,...) plots into the axes ax instead of the current axes (gca).

h = rose(...) returns the handle of the line object used to create the graph.

[tout,rout] = rose(...) returns the vectors tout and rout so polar(tout,rout) generates the histogram for the data. This syntax does not generate a plot.

Examples

Create Angle Histogram

Create an angle histogram of values between 0 and $$2\pi$$. Distribute the data among 10 bins.

theta = [0.4 1.4 3.1 2.3 0.4 2.5 3.9 2.8 2.3 1.6 4.6 4.5 6.1 3.9 5.1];
rose(theta,10)

Extended Capabilities

GPU Arrays

Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

Usage notes and limitations:

• This function accepts GPU arrays, but does not run on a GPU.

For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).

Distributed Arrays

Partition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.

Usage notes and limitations:

• This function operates on distributed arrays, but executes in the client MATLAB^®.

For more information, see Run MATLAB Functions with Distributed Arrays (Parallel Computing Toolbox).