86 lines
2.9 KiB
Python
86 lines
2.9 KiB
Python
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#
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# Licensed to the Apache Software Foundation (ASF) under one or more
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# contributor license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright ownership.
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# The ASF licenses this file to You under the Apache License, Version 2.0
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# (the "License"); you may not use this file except in compliance with
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# the License. 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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import sys
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if sys.version_info[:2] <= (2, 6):
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try:
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import unittest2 as unittest
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except ImportError:
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sys.stderr.write('Please install unittest2 to test with Python 2.6 or earlier')
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sys.exit(1)
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else:
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import unittest
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from pyspark.sql.types import DoubleType, IntegerType
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from pyspark.testing.mlutils import MockDataset, MockEstimator, MockUnaryTransformer, \
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SparkSessionTestCase
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class UnaryTransformerTests(SparkSessionTestCase):
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def test_unary_transformer_validate_input_type(self):
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shiftVal = 3
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transformer = MockUnaryTransformer(shiftVal=shiftVal) \
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.setInputCol("input").setOutputCol("output")
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# should not raise any errors
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transformer.validateInputType(DoubleType())
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with self.assertRaises(TypeError):
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# passing the wrong input type should raise an error
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transformer.validateInputType(IntegerType())
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def test_unary_transformer_transform(self):
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shiftVal = 3
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transformer = MockUnaryTransformer(shiftVal=shiftVal) \
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.setInputCol("input").setOutputCol("output")
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df = self.spark.range(0, 10).toDF('input')
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df = df.withColumn("input", df.input.cast(dataType="double"))
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transformed_df = transformer.transform(df)
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results = transformed_df.select("input", "output").collect()
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for res in results:
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self.assertEqual(res.input + shiftVal, res.output)
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class EstimatorTest(unittest.TestCase):
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def testDefaultFitMultiple(self):
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N = 4
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data = MockDataset()
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estimator = MockEstimator()
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params = [{estimator.fake: i} for i in range(N)]
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modelIter = estimator.fitMultiple(data, params)
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indexList = []
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for index, model in modelIter:
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self.assertEqual(model.getFake(), index)
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indexList.append(index)
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self.assertEqual(sorted(indexList), list(range(N)))
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if __name__ == "__main__":
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from pyspark.ml.tests.test_base import *
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try:
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import xmlrunner
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testRunner = xmlrunner.XMLTestRunner(output='target/test-reports')
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except ImportError:
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testRunner = None
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unittest.main(testRunner=testRunner, verbosity=2)
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