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# coneplot

Plot velocity vectors as cones in 3-D vector field

## Syntax

coneplot(X,Y,Z,U,V,W,Cx,Cy,Cz)
coneplot(U,V,W,Cx,Cy,Cz)
coneplot(...,s)
coneplot(...,color)
coneplot(...,'quiver')
coneplot(...,'method')
coneplot(X,Y,Z,U,V,W,'nointerp')
coneplot(axes_handle,...)
h = coneplot(...)

## Description

coneplot(X,Y,Z,U,V,W,Cx,Cy,Cz) plots velocity vectors as cones pointing in the direction of the velocity vector and having a length proportional to the magnitude of the velocity vector. X, Y, Z define the coordinates for the vector field. U, V, W define the vector field. These arrays must be the same size, monotonic, and represent a Cartesian, axis-aligned grid (such as the data produced by meshgrid). Cx, Cy, Cz define the location of the cones in the vector field. The section Specifying Starting Points for Stream Plots in Visualization Techniques provides more information on defining starting points.

coneplot(U,V,W,Cx,Cy,Cz) (omitting the X, Y, and Z arguments) assumes [X,Y,Z] = meshgrid(1:n,1:m,1:p), where [m,n,p]= size(U).

coneplot(...,s) automatically scales the cones to fit the graph and then stretches them by the scale factor s. If you do not specify a value for s, coneplot uses a value of 1. Use s = 0 to plot the cones without automatic scaling.

coneplot(...,color) interpolates the array color onto the vector field and then colors the cones according to the interpolated values. The size of the color array must be the same size as the U, V, W arrays. This option works only with cones (that is, not with the quiver option).

coneplot(...,'quiver') draws arrows instead of cones (see quiver3 for an illustration of a quiver plot).

coneplot(...,'method') specifies the interpolation method to use. method can be linear, cubic, or nearest. linear is the default. (See interp3 for a discussion of these interpolation methods.)

coneplot(X,Y,Z,U,V,W,'nointerp') does not interpolate the positions of the cones into the volume. The cones are drawn at positions defined by X, Y, Z and are oriented according to U, V, W. Arrays X, Y, Z, U, V, W must all be the same size.

coneplot(axes_handle,...) plots into the axes with the handle axes_handle instead of into the current axes (gca).

h = coneplot(...) returns the handle to the patch object used to draw the cones. You can use the set command to change the properties of the cones.

coneplot automatically scales the cones to fit the graph, while keeping them in proportion to the respective velocity vectors.

## Examples

Plot the velocity vector cones for vector volume data representing the motion of air through a rectangular region of space:

Load the data. The winds data set contains six 3-D arrays: u, v, and w specify the vector components at each of the coordinates specified in x, y, and z. The coordinates define a lattice grid structure where the data is sampled within the volume. load wind.

`load wind`

Now establish the range of the data to place the slice planes and to specify where you want the cone plots (min, max):

```xmin = min(x(:));
xmax = max(x(:));
ymin = min(y(:));
ymax = max(y(:));
zmin = min(z(:));```

Use daspect to set the data aspect ratio of the axes before calling coneplot.

`daspect([2,2,1])`

Decide where in data space you want to plot cones. This example selects the full range of x and y in eight steps and the range 3 to 15 in four steps in z using linspace and meshgrid.

```xrange = linspace(xmin,xmax,8);
yrange = linspace(ymin,ymax,8);
zrange = 3:4:15;
[cx cy cz] = meshgrid(xrange,yrange,zrange);```

Draw the cones, setting the scale factor to 5 to make the cones larger than the default size:

`hcones = coneplot(x,y,z,u,v,w,cx,cy,cz,5);`

Use the jet colormap:

`colormap jet`

Set the coloring of each cone using FaceColor and EdgeColor:

`set(hcones,'FaceColor','red','EdgeColor','none')`

Calculate the magnitude of the vector field (which represents wind speed) to generate scalar data for the slice command:

```hold on
wind_speed = sqrt(u.^2 + v.^2 + w.^2);```

Create slice planes along the x-axis at xmin and xmax, along the y-axis at ymax, and along the z-axis at zmin:

`hsurfaces = slice(x,y,z,wind_speed,[xmin,xmax],ymax,zmin);`

Specify interpolated face color so the slice coloring indicates wind speed, and do not draw edges (hold, slice, FaceColor, EdgeColor):

```set(hsurfaces,'FaceColor','interp','EdgeColor','none')
hold off```

Use the axis command to set the axis limits equal to the range of the data. axis tight. Orient the view to azimuth = 30 and elevation = 40. (rotate3d is a useful command for selecting the best view.)

`view(30,40);axis off`

Select perspective projection to provide a more realistic looking volume using camproj:

`camproj perspective;`

Zoom in on the scene a little to make the plot as large as possible using camzoom:

`camzoom(1.5)`

The light source affects both the slice planes (surfaces) and the cone plots (patches). However, you can set the lighting characteristics of each independently.

Add a light source to the right of the camera and use Gouraud lighting to give the cones and slice planes a smooth, three-dimensional appearance using camlight and lighting:

`camlight right; lighting gouraud`

Increase the value of the AmbientStrength property for each slice plane to improve the visibility of the dark blue colors:

`set(hsurfaces,'AmbientStrength',0.6)`

Increase the value of the DiffuseStrength property of the cones to brighten particularly those cones not showing specular reflections:

`set(hcones,'DiffuseStrength',0.8)`

## Tutorials

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