trait ViewLayoutComposition extends ViewComposition
all view layout composition (facet, concat, and repeat) can have the following layout properties: align, bounds, center, spacing.
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- This member is added by an implicit conversion from ViewLayoutComposition toany2stringadd[ViewLayoutComposition] performed by method any2stringadd in scala.Predef.
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- def ->[B](y: B): (ViewLayoutComposition, B)
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- This member is added by an implicit conversion from ViewLayoutComposition toArrowAssoc[ViewLayoutComposition] performed by method ArrowAssoc in scala.Predef.
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- def align(row: String, column: String): ViewLayoutComposition
Sets different alignments for rows and columns..
- def align(align: String): ViewLayoutComposition
The alignment to apply to grid rows and columns.
The alignment to apply to grid rows and columns. The supported string values are "all" (the default), "each", and "none".
- For "none", a flow layout will be used, in which adjacent subviews are simply placed one after the other. - For "each", subviews will be aligned into a clean grid structure, but each row or column may be of variable size. - For "all", subviews will be aligned and each row or column will be sized identically based on the maximum observed size. String values for this property will be applied to both grid rows and columns.
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- def autosize(type: String = "pad", resize: Boolean = false, contains: String = "content"): VegaLite
Sets the overall size of the visualization.
Sets the overall size of the visualization. The total size of a Vega-Lite visualization may be determined by multiple factors: specified width, height, and padding values, as well as content such as axes, legends, and titles.
- resize
A boolean flag indicating if autosize layout should be re-calculated on every view update.
- contains
Determines how size calculation should be performed, one of "content" or "padding". The default setting ("content") interprets the width and height settings as the data rectangle (plotting) dimensions, to which padding is then added. In contrast, the "padding" setting includes the padding within the view size calculations, such that the width and height settings indicate the total intended size of the view.
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- VegaLite
- def background(color: String): VegaLite
CSS color property to use as the background of the entire view.
CSS color property to use as the background of the entire view.
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- VegaLite
- def bounds(bounds: String): ViewLayoutComposition
The bounds calculation method to use for determining the extent of a sub-plot.
The bounds calculation method to use for determining the extent of a sub-plot. One of full (the default) or flush.
- If set to full, the entire calculated bounds (including axes, title, and legend) will be used. - If set to flush, only the specified width and height values for the sub-view will be used. The flush setting can be useful when attempting to place sub-plots without axes or legends into a uniform grid structure.
- def center(row: Int, column: Int): ViewLayoutComposition
Sets different spacing values for rows and columns..
- def center(flag: Boolean): ViewLayoutComposition
Boolean flag indicating if subviews should be centered relative to their respective rows or columns.
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- def config(properties: JsObject): VegaLite
Sets Vega-Lite configuration object that lists configuration properties of a visualization for creating a consistent theme.
Sets Vega-Lite configuration object that lists configuration properties of a visualization for creating a consistent theme. This property can only be defined at the top-level of a specification.
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- def data(url: String, format: JsValue = JsUndefined): VegaLite
Sets the url of the data source.
Sets the url of the data source.
- url
An URL from which to load the data set.
- format
Type of input data: "json", "csv", "tsv", "dsv". Default value: The default format type is determined by the extension of the file URL. If no extension is detected, "json" will be used by default.
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- VegaLite
- def data(df: DataFrame): VegaLite
Sets a data frame describing the data source.
Sets a data frame describing the data source.
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- def data(rows: JsObject*): VegaLite
Sets an array of objects describing the data source.
Sets an array of objects describing the data source.
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- def data(json: JsArray): VegaLite
Sets a JSON array describing the data source.
Sets a JSON array describing the data source. Set to null to ignore the parent’s data source. If no data is set, it is derived from the parent.
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- VegaLite
- def description(description: String): VegaLite
Sets the description of this mark for commenting purpose.
Sets the description of this mark for commenting purpose.
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- VegaLite
- def embed: String
Returns the HTML of plot specification with Vega Embed.
Returns the HTML of plot specification with Vega Embed.
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- VegaLite
- def ensuring(cond: (ViewLayoutComposition) => Boolean, msg: => Any): ViewLayoutComposition
- Implicit
- This member is added by an implicit conversion from ViewLayoutComposition toEnsuring[ViewLayoutComposition] performed by method Ensuring in scala.Predef.
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- Ensuring
- def ensuring(cond: (ViewLayoutComposition) => Boolean): ViewLayoutComposition
- Implicit
- This member is added by an implicit conversion from ViewLayoutComposition toEnsuring[ViewLayoutComposition] performed by method Ensuring in scala.Predef.
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- Ensuring
- def ensuring(cond: Boolean, msg: => Any): ViewLayoutComposition
- Implicit
- This member is added by an implicit conversion from ViewLayoutComposition toEnsuring[ViewLayoutComposition] performed by method Ensuring in scala.Predef.
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- Ensuring
- def ensuring(cond: Boolean): ViewLayoutComposition
- Implicit
- This member is added by an implicit conversion from ViewLayoutComposition toEnsuring[ViewLayoutComposition] performed by method Ensuring in scala.Predef.
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- def iframe(id: String = java.util.UUID.randomUUID.toString): String
Returns the HTML wrapped in an iframe to render in notebooks.
Returns the HTML wrapped in an iframe to render in notebooks.
- id
the iframe HTML id.
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- def name(name: String): VegaLite
Sets the name of the visualization for later reference.
Sets the name of the visualization for later reference.
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- def padding(left: Int, top: Int, right: Int, bottom: Int): VegaLite
Specifies padding for each side.
Specifies padding for each side. The visualization padding, in pixels, is from the edge of the visualization canvas to the data rectangle.
- Definition Classes
- VegaLite
- def padding(size: Int): VegaLite
Specifies padding for all sides.
Specifies padding for all sides. The visualization padding, in pixels, is from the edge of the visualization canvas to the data rectangle.
- Definition Classes
- VegaLite
- def resolveAxis(axis: JsObject): ViewComposition
Axis resolutions.
Axis resolutions. For axes, resolutions can be defined for x and y (positional channels).
- Definition Classes
- ViewComposition
- def resolveLegend(legend: JsObject): ViewComposition
Legend resolutions.
Legend resolutions. For legends, resolutions can be defined for color, opacity, shape, and size (non-positional channels).
- Definition Classes
- ViewComposition
- def resolveScale(scale: JsObject): ViewComposition
Scale resolutions.
Scale resolutions. For scales, resolution can be specified for every channel.
- Definition Classes
- ViewComposition
- def spacing(row: Int, column: Int): ViewLayoutComposition
Sets different spacing values for rows and columns..
- def spacing(size: Int): ViewLayoutComposition
The spacing in pixels between sub-views of the composition operator.
- final def synchronized[T0](arg0: => T0): T0
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- def title(title: String): VegaLite
Sets a descriptive title to a chart.
Sets a descriptive title to a chart.
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- def transform(transforms: JsObject*): VegaLite
An array of data transformations such as filter and new field calculation.
An array of data transformations such as filter and new field calculation. Data transformations in Vega-Lite are described via either view-level transforms (the transform property) or field transforms inside encoding (bin, timeUnit, aggregate, sort, and stack).
When both types of transforms are specified, the view-level transforms are executed first based on the order in the array. Then the inline transforms are executed in this order: bin, timeUnit, aggregate, sort, and stack.
- Definition Classes
- VegaLite
- def transform(transforms: JsArray): VegaLite
An array of data transformations such as filter and new field calculation.
An array of data transformations such as filter and new field calculation. Data transformations in Vega-Lite are described via either view-level transforms (the transform property) or field transforms inside encoding (bin, timeUnit, aggregate, sort, and stack).
When both types of transforms are specified, the view-level transforms are executed first based on the order in the array. Then the inline transforms are executed in this order: bin, timeUnit, aggregate, sort, and stack.
- Definition Classes
- VegaLite
- def usermeta(data: JsValue): VegaLite
Optional metadata that will be passed to Vega.
Optional metadata that will be passed to Vega. This object is completely ignored by Vega and Vega-Lite and can be used for custom metadata.
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- def formatted(fmtstr: String): String
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- This member is added by an implicit conversion from ViewLayoutComposition toStringFormat[ViewLayoutComposition] performed by method StringFormat in scala.Predef.
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(Since version 2.12.16) Use
formatString.format(value)instead ofvalue.formatted(formatString), or use thef""string interpolator. In Java 15 and later,formattedresolves to the new method in String which has reversed parameters.
- def →[B](y: B): (ViewLayoutComposition, B)
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- This member is added by an implicit conversion from ViewLayoutComposition toArrowAssoc[ViewLayoutComposition] performed by method ArrowAssoc in scala.Predef.
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(Since version 2.13.0) Use
->instead. If you still wish to display it as one character, consider using a font with programming ligatures such as Fira Code.
Smile (Statistical Machine Intelligence and Learning Engine) is a fast and comprehensive machine learning, NLP, linear algebra, graph, interpolation, and visualization system in Java and Scala. With advanced data structures and algorithms, Smile delivers state-of-art performance.
Smile covers every aspect of machine learning, including classification, regression, clustering, association rule mining, feature selection, manifold learning, multidimensional scaling, genetic algorithms, missing value imputation, efficient nearest neighbor search, etc.