ArcObjects Library Reference (Display)  

AlgorithmicColorRamp CoClass

Defines an algorithmic color ramp, where ramp is defined by two colors and the algorithm used to traverse the intervening color space between them.

Product Availability

Available with ArcGIS Engine, ArcGIS Desktop, and ArcGIS Server.

Description

Determines the colors that occur between a FromColor and a ToColor. These colors can be used when assigning symbology to a ClassBreaksRenderer, RasterClassifyColorRampRenderer, or to an object that supports ITinColorRampRenderer.

Supported Platforms

Windows, Solaris, Linux

Interfaces

Interfaces Description
IAlgorithmicColorRamp Provides access to members that control the AlgorithmicColorRamp. A color ramp defined by two colors and the algorithm used to traverse the intervening color space between them.
IClone (esriSystem) Provides access to members that control cloning of objects.
IColorRamp Provides access to the methods and properties common to all color ramp objects.
IPersist Defines the single method GetClassID, which is designed to supply the CLSID of an object that can be stored persistently in the system. IPersist is the base interface for three other interfaces: IPersistStorage, IPersistStream, and IPersistFile.
IPersistStream (esriSystem)
IXMLSerialize (esriSystem) Provides access to members that XML serialize and deserialize an object to/from XML.

Remarks

There are several methods to ramp colors. The current method is accessible via IAlgorithmicColorRamp::Algorithm.

The default method for this object is an HSV (Hue, Saturation, Value) algorithm, where the values of H, S, and V are all interpolated. The second available method is CieLab's algorithm which creates the intervening colors by intelligently blending the From and To colors. A third method is the LabLCh method, which is a modified version of CieLab's method and can create better results in some cases. In general the HSV produces brighter results, especially when the From and To colors are not of similar hues. However, the CieLab's and LCH methods may produce more intuitive results. This is because most casual map readers have more difficulty associating progression through a series of hues versus a smooth blend of colors.