ListLineIntegralConvolutionPlot

ListLineIntegralConvolutionPlot[{array,image}]

generates a line integral convolution plot of image convolved with the vector field defined by an array of vector field values.

ListLineIntegralConvolutionPlot[array]

generates a line integral convolution plot of white noise convolved with the vector field defined by array.

ListLineIntegralConvolutionPlot[{{{{x1,y1},{vx1,vy1}},},image}]

generates a line integral convolution plot of image convolved with the vector field defined by vectors {vxi,vyi} at specified points {xi,yi}.

ListLineIntegralConvolutionPlot[{{{x1,y1},{vx1,vy1}},}]

generates a line integral convolution plot of white noise convolved with the vector field defined by {vxi,vyi}.

Details and Options

Examples

open allclose all

Basic Examples  (2)

Plot a line integral convolution of a vector field interpolated from a specified set of vectors:

Plot the line integral convolution from data specifying coordinates and vectors:

Scope  (10)

Sampling  (6)

Plot a field image for a regular collection of vectors, and give a data range for the domain:

Plot a field image for an irregular collection of vectors:

Convolve an image with a regular collection of vectors:

Use an image directly as input:

Convolve an image with an irregular collection of vectors:

Use an image created from a sparse matrix:

Presentation  (4)

Plot a field image with overlaid streamlines:

Plot with overlaid field vectors:

Plot all the specified vectors in the data:

Color the field magnitude:

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

Options  (46)

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:

DataRange  (1)

By default, the data range is taken to be the index range of the data array:

Specify the data range for the domain:

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 frame:

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:

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  (1)

Add a color bar legend for the convolution:

Place the legend below the plot:

Use BarLegend to modify the legend:

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 monochrome theme for the plot:

Use a theme with minimal styling:

RasterSize  (2)

By default an automatic raster size is used:

Set a specific raster size:

Applications  (2)

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

Display characteristics of several different types of linear planar systems:

Properties & Relations  (4)

Use LineIntegralConvolutionPlot to plot functions:

Other alternatives for visualizing vector field data:

Other alternatives for visualizing vector field functions:

Use VectorPlot3D to visualize 3D vector fields:

Wolfram Research (2008), ListLineIntegralConvolutionPlot, Wolfram Language function, https://reference.wolfram.com/language/ref/ListLineIntegralConvolutionPlot.html (updated 2014).

Text

Wolfram Research (2008), ListLineIntegralConvolutionPlot, Wolfram Language function, https://reference.wolfram.com/language/ref/ListLineIntegralConvolutionPlot.html (updated 2014).

BibTeX

@misc{reference.wolfram_2020_listlineintegralconvolutionplot, author="Wolfram Research", title="{ListLineIntegralConvolutionPlot}", year="2014", howpublished="\url{https://reference.wolfram.com/language/ref/ListLineIntegralConvolutionPlot.html}", note=[Accessed: 14-May-2021 ]}

BibLaTeX

@online{reference.wolfram_2020_listlineintegralconvolutionplot, organization={Wolfram Research}, title={ListLineIntegralConvolutionPlot}, year={2014}, url={https://reference.wolfram.com/language/ref/ListLineIntegralConvolutionPlot.html}, note=[Accessed: 14-May-2021 ]}

CMS

Wolfram Language. 2008. "ListLineIntegralConvolutionPlot." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2014. https://reference.wolfram.com/language/ref/ListLineIntegralConvolutionPlot.html.

APA

Wolfram Language. (2008). ListLineIntegralConvolutionPlot. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/ListLineIntegralConvolutionPlot.html