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geotrellis.spark.filter

ToSpatial

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object ToSpatial

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  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  4. def apply[K, V, M[_]](rdd: RDD[(K, V)] with Metadata[M[K]])(implicit arg0: SpatialComponent[K], arg1: TemporalComponent[K], arg2: Component[M[K], Bounds[K]], arg3: Functor[M]): RDD[(SpatialKey, V)] with Metadata[M[SpatialKey]]

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  5. def apply[K, V, M[_]](rdd: RDD[(K, V)] with Metadata[M[K]], mergeFun: Option[(V, V) ⇒ V], partitioner: Option[Partitioner] = None)(implicit arg0: ClassTag[K], arg1: SpatialComponent[K], arg2: TemporalComponent[K], arg3: Component[M[K], Bounds[K]], arg4: ClassTag[V], arg5: Functor[M]): RDD[(SpatialKey, V)] with Metadata[M[SpatialKey]]

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  6. def apply[K, V, M[_]](rdd: RDD[(K, V)] with Metadata[M[K]], instant: Long)(implicit arg0: SpatialComponent[K], arg1: TemporalComponent[K], arg2: Component[M[K], Bounds[K]], arg3: Functor[M]): RDD[(SpatialKey, V)] with Metadata[M[SpatialKey]]

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    Restrict a tile layer and its metadata to two spatial dimensions.

    Restrict a tile layer and its metadata to two spatial dimensions.

    To project not only Tiles, but also Metadata (M) information and to get a consistent result type, it is possible to define additional constraints on Metadata. M should depend on a K type (M[K]), and two type classes should be provided: geotrellis.util.Component, to extract key bounds from M[K], and cats.Functor to map M[K] to M[SpatialKey].

    For those reading the source code directly,

    K: λ[α => Component[M[α], Bounds[α]]

    is further syntax sugar on top of the usual

    K: ...

    pattern. It expands into the following Scala implicit evidences:

    ev0: Component[M[K], Bounds[K]]

    K: ... }}} It expands into the following Scala implicit evidences:

    ev0: Component[M[K], Bounds[K]]
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