Merge pull request #251 from s22s/feature/unit-test-163

Breaking unit test in python for issue 163 tile exploder with Project…

Author: vpipkt

pyrasterframes/src/main/python/tests/ExploderTests.py

@@ -0,0 +1,59 @@
+#
+# This software is licensed under the Apache 2 license, quoted below.
+#
+# Copyright 2019 Astraea, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License"); you may not
+# use this file except in compliance with the License. You may obtain a copy of
+# the License at
+#
+# [http://www.apache.org/licenses/LICENSE-2.0]
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
+# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
+# License for the specific language governing permissions and limitations under
+# the License.
+#
+# SPDX-License-Identifier: Apache-2.0
+#
+
+from . import TestEnvironment
+
+from pyrasterframes.rasterfunctions import *
+from pyrasterframes.rf_types import *
+from pyrasterframes import TileExploder
+
+from pyspark.ml.feature import VectorAssembler
+from pyspark.ml import Pipeline
+from pyspark.sql.functions import *
+
+import unittest
+
+
+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)
+        t_col = 'proj_raster'
+        self.assertTrue(t_col in df.columns)
+
+        assembler = VectorAssembler().setInputCols([t_col])
+        pipe = Pipeline().setStages([TileExploder(), assembler])
+        pipe_model = pipe.fit(df)
+        tranformed_df = pipe_model.transform(df)
+        self.assertTrue(tranformed_df.count() > df.count())
+
+    def test_tile_exploder_pipeline_for_tile(self):
+        t_col = 'tile'
+        df = self.spark.read.raster(self.img_uri) \
+            .withColumn(t_col, rf_tile('proj_raster')) \
+            .drop('proj_raster')
+
+        assembler = VectorAssembler().setInputCols([t_col])
+        pipe = Pipeline().setStages([TileExploder(), assembler])
+        pipe_model = pipe.fit(df)
+        tranformed_df = pipe_model.transform(df)
+        self.assertTrue(tranformed_df.count() > df.count())