class Graphs extends AnyRef
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!=(arg0: Any): Boolean
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final
def
##(): Int
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- def +(other: String): String
- def ->[B](y: B): (Graphs, B)
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def
==(arg0: Any): Boolean
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def
ALSSyntheticData(): GraphFrame
Some synthetic data that sits in Spark.
Some synthetic data that sits in Spark.
No description available.
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final
def
asInstanceOf[T0]: T0
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def
chain(n: Long): GraphFrame
Returns a chain graph of the given size with Long ID type.
Returns a chain graph of the given size with Long ID type. The vertex IDs are 0, 1, ..., n-1, and the edges are (0, 1), (1, 2), ...., (n-2, n-1).
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def
clone(): AnyRef
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def
empty[T](implicit arg0: scala.reflect.api.JavaUniverse.TypeTag[T]): GraphFrame
Returns an empty GraphFrame of the given ID type.
- def ensuring(cond: (Graphs) ⇒ Boolean, msg: ⇒ Any): Graphs
- def ensuring(cond: (Graphs) ⇒ Boolean): Graphs
- def ensuring(cond: Boolean, msg: ⇒ Any): Graphs
- def ensuring(cond: Boolean): Graphs
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eq(arg0: AnyRef): Boolean
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equals(arg0: Any): Boolean
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finalize(): Unit
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def
friends: GraphFrame
Graph of friends in a social network.
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final
def
getClass(): Class[_]
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def
gridIsingModel(spark: SparkSession, n: Int): GraphFrame
Version of
gridIsingModelwith vStd, eStd set to 1.0. -
def
gridIsingModel(spark: SparkSession, n: Int, vStd: Double, eStd: Double): GraphFrame
This method generates a grid Ising model with random parameters.
This method generates a grid Ising model with random parameters.
Ising models are probabilistic graphical models over binary variables xi. Each binary variable xi corresponds to one vertex, and it may take values -1 or +1. The probability distribution P(X) (over all xi) is parameterized by vertex factors ai and edge factors bij:
P(X) = (1/Z) * exp[ \sum_i a_i x_i + \sum_{ij} b_{ij} x_i x_j ]where Z is the normalization constant (partition function). See Wikipedia for more information on Ising models.
Each vertex is parameterized by a single scalar ai. Each edge is parameterized by a single scalar bij.
- n
Length of one side of the grid. The grid will be of size n x n.
- vStd
Standard deviation of normal distribution used to generate vertex factors "a". Default of 1.0.
- eStd
Standard deviation of normal distribution used to generate edge factors "b". Default of 1.0.
- returns
GraphFrame. Vertices have columns "id" and "a". Edges have columns "src", "dst", and "b". Edges are directed, but they should be treated as undirected in any algorithms run on this model. Vertex IDs are of the form "i,j". E.g., vertex "1,3" is in the second row and fourth column of the grid.
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def
hashCode(): Int
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isInstanceOf[T0]: Boolean
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ne(arg0: AnyRef): Boolean
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notify(): Unit
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final
def
notifyAll(): Unit
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def
star(n: Long): GraphFrame
Returns a star graph with Long ID type, consisting of a central element indexed 0 (the root) and the n other leaf vertices 1, 2, ..., n.
Returns a star graph with Long ID type, consisting of a central element indexed 0 (the root) and the n other leaf vertices 1, 2, ..., n.
- n
the number of leaves
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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def
toString(): String
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def
twoBlobs(blobSize: Int): GraphFrame
Two densely connected blobs (vertices 0->n-1 and n->2n-1) connected by a single edge (0->n)
Two densely connected blobs (vertices 0->n-1 and n->2n-1) connected by a single edge (0->n)
- blobSize
the size of each blob.
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def
wait(): Unit
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wait(arg0: Long, arg1: Int): Unit
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def
wait(arg0: Long): Unit
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Deprecated Value Members
-
def
formatted(fmtstr: String): String
- Implicit
- This member is added by an implicit conversion from Graphs to StringFormat[Graphs] performed by method StringFormat in scala.Predef.
- Definition Classes
- StringFormat
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- @deprecated @inline()
- Deprecated
(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.