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Updated ExplodeTiles to work with proj_raster type. #332

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Merged
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Sep 6, 2019
Merged

Updated ExplodeTiles to work with proj_raster type. #332

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9b9f993
Updated ExplodeTiles to work with proj_raster type.
metasim Sep 3, 2019
3614338
Run python tile exploder test for projected raster
vpipkt Sep 6, 2019
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14 changes: 8 additions & 6 deletions core/src/main/scala/org/locationtech/rasterframes/expressions/generators/ExplodeTiles.scala
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Expand Up @@ -21,16 +21,15 @@

package org.locationtech.rasterframes.expressions.generators

import org.locationtech.rasterframes._
import org.locationtech.rasterframes.encoders.CatalystSerializer._
import org.locationtech.rasterframes.util._
import geotrellis.raster._
import org.apache.spark.sql._
import org.apache.spark.sql.catalyst.InternalRow
import org.apache.spark.sql.catalyst.expressions.codegen.CodegenFallback
import org.apache.spark.sql.catalyst.expressions.{Expression, Generator, GenericInternalRow}
import org.apache.spark.sql.rf.TileUDT
import org.apache.spark.sql.types._
import org.locationtech.rasterframes._
import org.locationtech.rasterframes.expressions.DynamicExtractors
import org.locationtech.rasterframes.util._
import spire.syntax.cfor.cfor

/**
Expand Down Expand Up @@ -67,8 +66,11 @@ case class ExplodeTiles(
override def eval(input: InternalRow): TraversableOnce[InternalRow] = {
val tiles = Array.ofDim[Tile](children.length)
cfor(0)(_ < tiles.length, _ + 1) { index =>
val row = children(index).eval(input).asInstanceOf[InternalRow]
tiles(index) = if(row != null) row.to[Tile](TileUDT.tileSerializer) else null
val c = children(index)
val row = c.eval(input).asInstanceOf[InternalRow]
tiles(index) = if(row != null)
DynamicExtractors.tileExtractor(c.dataType)(row)._1
else null
}
val dims = tiles.filter(_ != null).map(_.dimensions)
if(dims.isEmpty) Seq.empty[InternalRow]
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8 changes: 3 additions & 5 deletions core/src/main/scala/org/locationtech/rasterframes/ml/TileColumnSupport.scala
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Expand Up @@ -21,8 +21,8 @@

package org.locationtech.rasterframes.ml

import org.apache.spark.sql.rf.TileUDT
import org.apache.spark.sql.types.{StructField, StructType}
import org.locationtech.rasterframes.expressions.DynamicExtractors

/**
* Utility mix-in for separating out tile columns from non-tile columns.
Expand All @@ -31,13 +31,11 @@ import org.apache.spark.sql.types.{StructField, StructType}
*/
trait TileColumnSupport {
protected def isTile(field: StructField) =
field.dataType.typeName.equalsIgnoreCase(TileUDT.typeName)
DynamicExtractors.tileExtractor.isDefinedAt(field.dataType)

type TileFields = Array[StructField]
type NonTileFields = Array[StructField]
protected def selectTileAndNonTileFields(schema: StructType): (TileFields, NonTileFields) = {
val tiles = schema.fields.filter(isTile)
val nonTiles = schema.fields.filterNot(isTile)
(tiles, nonTiles)
schema.fields.partition(f => DynamicExtractors.tileExtractor.isDefinedAt(f.dataType))
}
}
32 changes: 26 additions & 6 deletions core/src/test/scala/org/locationtech/rasterframes/ml/TileExploderSpec.scala
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Expand Up @@ -21,28 +21,48 @@

package org.locationtech.rasterframes.ml

import org.locationtech.rasterframes.TestData
import geotrellis.raster.Tile
import org.apache.spark.sql.functions.lit
import org.locationtech.rasterframes.TestEnvironment
import geotrellis.proj4.LatLng
import geotrellis.raster.{IntCellType, Tile}
import org.apache.spark.sql.functions.{avg, lit}
import org.locationtech.rasterframes.{TestData, TestEnvironment}
/**
*
* @since 2/16/18
*/
class TileExploderSpec extends TestEnvironment with TestData {
describe("Tile explode transformer") {
it("should explode tiles") {
import spark.implicits._
import spark.implicits._
it("should explode tile") {
val df = Seq[(Tile, Tile)]((byteArrayTile, byteArrayTile)).toDF("tile1", "tile2").withColumn("other", lit("stuff"))

val exploder = new TileExploder()
val newSchema = exploder.transformSchema(df.schema)

val exploded = exploder.transform(df)

assert(newSchema === exploded.schema)
assert(exploded.columns.length === 5)
assert(exploded.count() === 9)
write(exploded)
exploded.agg(avg($"tile1")).as[Double].first() should be (byteArrayTile.statisticsDouble.get.mean)
}

it("should explode proj_raster") {
val randPRT = TestData.projectedRasterTile(10, 10, scala.util.Random.nextInt(), extent, LatLng, IntCellType)

val df = Seq(randPRT).toDF("proj_raster").withColumn("other", lit("stuff"))

val exploder = new TileExploder()
val newSchema = exploder.transformSchema(df.schema)

val exploded = exploder.transform(df)

assert(newSchema === exploded.schema)
assert(exploded.columns.length === 4)
assert(exploded.count() === randPRT.size)
write(exploded)

exploded.agg(avg($"proj_raster")).as[Double].first() should be (randPRT.statisticsDouble.get.mean)
}
}
}
4 changes: 4 additions & 0 deletions docs/src/main/paradox/release-notes.md
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Expand Up @@ -2,6 +2,10 @@

## 0.8.x

### 0.8.2

* Fixed `TileExploder` to support `proj_raster` struct [(#287)](https://github.com/locationtech/rasterframes/issues/287).

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We probably need to confirm that we've kept this up to date since 0.8.1

### 0.8.1

* Added `rf_local_no_data`, `rf_local_data` and `rf_interpret_cell_type_as` raster functions.
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2 changes: 1 addition & 1 deletion pyrasterframes/src/main/python/docs/vector-data.pymd
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Expand Up @@ -93,7 +93,7 @@ l8_filtered = l8 \
.filter(st_intersects(l8.geom, st_bufferPoint(l8.paducah, lit(50000.0)))) \
.filter(l8.acquisition_date > '2018-02-01') \
.filter(l8.acquisition_date < '2018-04-01')
l8_filtered.select('product_id', 'entity_id', 'acquisition_date', 'cloud_cover_pct').toPandas()
l8_filtered.select('product_id', 'entity_id', 'acquisition_date', 'cloud_cover_pct')
```

[GeoPandas]: http://geopandas.org
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1 change: 0 additions & 1 deletion pyrasterframes/src/main/python/tests/ExploderTests.py
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Expand Up @@ -33,7 +33,6 @@

class ExploderTests(TestEnvironment):

@unittest.skip("See issue https://github.com/locationtech/rasterframes/issues/163")
def test_tile_exploder_pipeline_for_prt(self):
# NB the tile is a Projected Raster Tile
df = self.spark.read.raster(self.img_uri)
Expand Down