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James McClain
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Unit Tests For Time Series Capability
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‎spark/src/test/scala/geotrellis/spark/timeseries/RDDTimeSeriesMethodsSpec.scala

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/*
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* Copyright 2017 Azavea
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package geotrellis.spark.costdistance
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import geotrellis.proj4.LatLng
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import geotrellis.raster._
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import geotrellis.spark._
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import geotrellis.spark.testkit.TestEnvironment
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import geotrellis.spark.tiling.LayoutDefinition
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import geotrellis.vector._
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import org.apache.spark.rdd.RDD
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import org.scalatest._
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class RDDTimeSeriesMethodsSpec extends FunSpec
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with Matchers
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with TestEnvironment {
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val rdd = {
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val tile1 = IntConstantNoDataArrayTile(Array.fill[Int](25)(1), 5, 5)
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val tile2 = IntConstantNoDataArrayTile(Array.fill[Int](25)(2), 5, 5)
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val tile3 = IntConstantNoDataArrayTile(Array.fill[Int](25)(3), 5, 5)
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val tile4 = IntConstantNoDataArrayTile(Array.fill[Int](25)(4), 5, 5)
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val extent = Extent(0, 0, 10, 5)
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val gridExtent = GridExtent(extent, 1, 1) // 10×5 pixels
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val layoutDefinition = LayoutDefinition(gridExtent, 10, 5)
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val bounds = Bounds(SpaceTimeKey(0, 0, 0), SpaceTimeKey(1, 0, 1))
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val tileLayerMetadata = TileLayerMetadata(
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IntConstantNoDataCellType,
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layoutDefinition,
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extent,
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LatLng,
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bounds
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)
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val list: List[(SpaceTimeKey, Tile)] = List(
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(SpaceTimeKey(0, 0, 0), tile1),
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(SpaceTimeKey(1, 0, 0), tile2),
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(SpaceTimeKey(0, 0, 1), tile3),
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(SpaceTimeKey(1, 0, 1), tile4)
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)
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ContextRDD(sc.parallelize(list), tileLayerMetadata)
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}
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val polygon = MultiPolygon(Polygon(
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Point(-100,-100),
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Point(+100,-100),
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Point(+100,+100),
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Point(-100,+100),
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Point(-100,-100)
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))
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describe("Time Series Extentension Methods") {
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it("Mean") {
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val expected = List(1.5, 3.5)
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val actual = rdd.meanSeries(polygon).map({ case (_, x) => x })
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actual should be (expected)
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}
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it("Min") {
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val expected = List(1.0, 3.0)
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val actual = rdd.minSeries(polygon).map({ case (_, x) => x })
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actual should be (expected)
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}
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it("Max") {
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val expected = List(2.0, 4.0)
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val actual = rdd.maxSeries(polygon).map({ case (_, x) => x })
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actual should be (expected)
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}
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it("Histogram") {
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val expected = List(Some(1.0), Some(3.0))
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val actual = rdd.histogramSeries(polygon).map({ case (_, x) => x.minValue() })
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actual should be (expected)
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}
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it("Sum") {
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val expected = List(25.0*(1+2), 25.0*(3+4))
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val actual = rdd.sumSeries(polygon).map({ case (_, x) => x })
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actual should be (expected)
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}
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}
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}

‎spark/src/test/scala/geotrellis/spark/timeseries/TimeSeriesSpec.scala

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/*
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* Copyright 2017 Azavea
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package geotrellis.spark.timeseries
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import geotrellis.proj4.LatLng
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import geotrellis.raster._
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import geotrellis.spark._
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import geotrellis.spark.testkit.TestEnvironment
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import geotrellis.spark.tiling.LayoutDefinition
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import geotrellis.vector._
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import org.scalatest._
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object TimeSeriesSpecFunctions {
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def projection(tile: Tile): Set[Int] =
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tile.toArray.toSet.filter(_ > 0)
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def reduction(left: Set[Int], right: Set[Int]): Set[Int] =
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left ++ right
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}
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class TimeSeriesSpec extends FunSpec
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with Matchers
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with TestEnvironment {
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val rdd = {
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val tile1 = IntArrayTile(Array.fill[Int](25)(1), 5, 5)
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val tile2 = IntArrayTile(Array.fill[Int](25)(2), 5, 5)
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val tile3 = IntArrayTile(Array.fill[Int](25)(3), 5, 5)
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val tile4 = IntArrayTile(Array.fill[Int](25)(4), 5, 5)
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val extent = Extent(0, 0, 10, 5)
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val gridExtent = GridExtent(extent, 1, 1) // 10×5 pixels
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val layoutDefinition = LayoutDefinition(gridExtent, 10, 5)
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val bounds = Bounds(SpaceTimeKey(0, 0, 0), SpaceTimeKey(1, 0, 1))
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val tileLayerMetadata = TileLayerMetadata(
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IntConstantNoDataCellType,
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layoutDefinition,
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extent,
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LatLng,
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bounds
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)
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val list: List[(SpaceTimeKey, Tile)] = List(
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(SpaceTimeKey(0, 0, 0), tile1),
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(SpaceTimeKey(1, 0, 0), tile2),
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(SpaceTimeKey(0, 0, 1), tile3),
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(SpaceTimeKey(1, 0, 1), tile4)
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)
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ContextRDD(sc.parallelize(list), tileLayerMetadata)
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}
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describe("Time Series Capability") {
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it("Should handle queries within tile boundaries") {
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val polygon = MultiPolygon(Polygon(
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Point(0,0),
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Point(4,0),
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Point(4,4),
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Point(0,4),
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Point(0,0)
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))
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val expected = List(Set(1), Set(3))
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val actual =
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TimeSeries(
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rdd,
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TimeSeriesSpecFunctions.projection,
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TimeSeriesSpecFunctions.reduction,
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List(polygon)
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)
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.collect()
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.toList
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.map({ case (_, s) => s })
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actual should be (expected)
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}
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it("Should handle queries across tile boundaries") {
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val polygon = MultiPolygon(Polygon(
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Point(0,0),
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Point(11,0),
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Point(11,5),
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Point(0,5),
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Point(0,0)
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))
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val expected = List(Set(1,2), Set(3,4))
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val actual =
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TimeSeries(
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rdd,
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TimeSeriesSpecFunctions.projection,
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TimeSeriesSpecFunctions.reduction,
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List(polygon)
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)
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.collect()
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.toList
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.map({ case (_, s) => s })
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actual should be (expected)
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}
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}
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}

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