d4_scale library

Scales map a dimension of abstract data to a visual representation.

Although most often used for encoding data as position, say to map time and temperature to a horizontal and vertical position in a scatterplot, scales can represent virtually any visual encoding, such as color, stroke width, or symbol size. Scales can also be used with virtually any type of data, such as named categorical data or discrete data that requires sensible breaks.

For color schemes, see d4_scale_chromatic.

Classes

Scale<X, Y>

A generic mapper from an input domain to an output range.

ScaleBand<X>

Band scales are like ordinal scales except the output range is continuous and numeric.

ScaleDiverging<Y>

Diverging scales are similar to linear scales, but the input domain and output range always have exactly three elements.

ScaleDivergingLog<Y>

A diverging scale with a logarithmic transform, analogous to ScaleLog.

ScaleDivergingPow<Y>

A diverging scale with an exponential transform, analogous to a ScalePow.

ScaleDivergingSymlog<Y>

A diverging scale with a logarithmic transform, analogous to a ScaleSymlog.

ScaleIdentity

Identity scales are a special case of linear scales where the domain and range are identical.

ScaleLinear<Y>

Linear scales map a continuous, quantitative input domain to a continuous output range using a linear transformation (translate and scale).

ScaleLog<Y>

Logarithmic (“log”) scales are like linear scales except that a logarithmic transform is applied to the input domain value before the output range value is computed.

ScaleOrdinal<X, Y>

Unlike continuous scales, ordinal scales have a discrete domain and range.

ScalePoint<X>

Point scales are a variant of band scales with the bandwidth fixed to zero.

ScalePow<Y>

Power (“pow”) scales are similar to linear scales, except an exponential transform is applied to the input domain value before the output range value is computed.

ScaleQuantile<Y>

Quantile scales map a sampled input domain to a discrete range.

ScaleQuantize<Y>

Quantize scales are similar to linear scales, except they use a discrete rather than continuous range.

ScaleRadial

Radial scales are a variant of linear scales where the range is internally squared so that an input value corresponds linearly to the squared output value.

ScaleSequential<Y>

Sequential scales are similar to linear scales, but the input domain and output range always have exactly three elements.

ScaleSequentialLog<Y>

A sequential scale with a logarithmic transform, analogous to ScaleLog.

ScaleSequentialPow<Y>

A sequential scale with an exponential transform, analogous to a ScalePow.

ScaleSequentialQuantile<Y>

A sequential scale with a p-quantile transform, analogous to a ScaleQuantile.

ScaleSequentialSymlog<Y>

A sequential scale with a logarithmic transform, analogous to a ScaleSymlog.

ScaleSymlog<Y>

See A bi-symmetric log transformation for wide-range data by Webber for details. Unlike a ScaleLog, a symlog scale domain can include zero.

ScaleThreshold<X, Y>

Threshold scales are similar to quantize scales, except they allow you to map arbitrary subsets of the domain to discrete values in the range.

ScaleTime<Y>

Time scales are a variant of linear scales that have a temporal domain.

Extensions

ScaleContinuousNumberExtension on ScaleContinuousBase<X, num>

Adds invert and rangeRound methods to continuous scales with numeric range.

ScaleDivergingNumberExtension on ScaleDiverging<num>

Adds rangeRound method to diverging scales with numeric range.

ScaleSequentialNumberExtension on ScaleSequential<num>

Adds rangeRound method to sequential scales with numeric range.

Functions

tickFormat(num start, num stop, num count, [String? specifier]) → String Function(num)

Returns a number format function suitable for displaying a tick value, automatically computing the appropriate precision based on the fixed interval between tick values, as determined by tickStep.