LineIntegralConvolutionPlot

LineIntegralConvolutionPlot[{{vx,vy},image},{x,xmin,xmax},{y,ymin,ymax}]

generates a line integral convolution plot of image convolved with the vector field {vx,vy} as a function of x and y.

LineIntegralConvolutionPlot[{vx,vy},{x,xmin,xmax},{y,ymin,ymax}]

generates a line integral convolution plot of white noise with the vector field {vx,vy}.

Details and Options

Examples

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Basic Examples  (2)

Plot the line integral convolution for a vector field starting with a random background:

Use an imported image:

Scope  (12)

Sampling  (5)

Transform an image by a line integral convolution:

Use an image directly as input:

Use an image created from a sparse matrix:

Use a white noise background image with different levels of color quantization:

Plot a field image, increasing the line integral convolution length:

Presentation  (7)

Plot a field image and overlaid streamlines:

Plot a field image and overlaid field vectors:

Plot a field image and overlaid vectors at random positions:

Color the field magnitude:

Specify a color function that blends two colors by the coordinate:

Fix the lighting angle at 0 (right of the plot), and vary the altitude from 0 to :

Use a theme with detailed ticks and a legend:

Options  (48)

AspectRatio  (2)

By default, the aspect ratio is 1:

Set the aspect ratio:

Background  (1)

Use colored backgrounds:

ColorFunction  (5)

Color the field magnitude using Hue:

Use any named color gradient from ColorData:

Use ColorData for predefined color gradients:

Specify a color function that blends two colors by the coordinate:

Use ColorFunctionScaling->False to get unscaled values:

ColorFunctionScaling  (4)

By default, scaled values are used:

Use ColorFunctionScaling->False to get unscaled values:

Use unscaled coordinates in the direction and scaled coordinates in the direction:

Explicitly specify the scaling for each color function argument:

EvaluationMonitor  (1)

Count the number of times the vector field function is evaluated:

Frame  (1)

Toggle the frame around the plot:

FrameLabel  (1)

Label the axes:

FrameTicks  (8)

Place frame tick marks and labels automatically:

Put a frame, but no ticks:

Place frame ticks and labels on all the edges:

Place frame ticks on the right and top edges:

Place frame tick marks at the specified positions:

Draw frame ticks at the specified positions with the specific labels:

Specify the style of each frame tick:

Specify overall frame ticks style, including frame tick labels, using FrameTicksStyle:

LightingAngle  (2)

Vary the lighting angle from 0 (right of the plot) to (top of the plot):

Fix the lighting angle at 0 (right of the plot) and vary the altitude from 0 to :

LineIntegralConvolutionScale  (2)

An automatic scale is used by default:

Use a specific scale:

PerformanceGoal  (2)

Generate a higher-quality plot:

Emphasize performance, possibly at the cost of quality:

PlotLegends  (2)

Use a legend to show the vector field gradient colors:

Legends automatically pick up settings of ColorFunction:

PlotRange  (7)

The full plot range is used by default:

Specify an explicit limit for both and ranges:

Specify an explicit range:

Specify an explicit minimum range:

Specify an explicit range:

Specify an explicit maximum range:

Specify different and ranges:

PlotRangePadding  (6)

Padding is computed automatically by default:

Specify no padding for all , , and ranges:

Specify an explicit padding for all , , and ranges:

Add 10% padding to all , , and ranges:

Specify different padding for and ranges:

Specify padding for the range:

PlotTheme  (2)

Use a theme with simple ticks in a vibrant color scheme:

Change the color scheme:

RasterSize  (2)

By default, an automatic raster size is used:

Set a specific raster size:

Applications  (5)

Use a line integral convolution plot as a background for an interactive demo:

Display characteristics of several different types of linear planar systems:

Show the local direction of the gradient of a function along with its level curves:

Use the image as a background for investigating different unconstrained optimization methods:

Apply to a texture from ExampleData:

Apply to rasterized text:

Properties & Relations  (4)

Use ListLineIntegralConvolutionPlot to plot data:

Other alternatives for visualizing vector field functions:

Other alternatives for visualizing vector field data:

Use VectorPlot3D to visualize 3D vector fields:

Neat Examples  (1)

Algorithmic texture generation:

Introduced in 2008
 (7.0)
 |
Updated in 2012
 (9.0)
2014
 (10.0)