#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You 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.
#
__all__ = ['ParamGridBuilder']
class ParamGridBuilder(object):
"""
Builder for a param grid used in grid search-based model selection.
>>> from classification import LogisticRegression
>>> lr = LogisticRegression()
>>> output = ParamGridBuilder().baseOn({lr.labelCol: 'l'}) \
.baseOn([lr.predictionCol, 'p']) \
.addGrid(lr.regParam, [1.0, 2.0, 3.0]) \
.addGrid(lr.maxIter, [1, 5]) \
.addGrid(lr.featuresCol, ['f']) \
.build()
>>> expected = [ \
{lr.regParam: 1.0, lr.featuresCol: 'f', lr.maxIter: 1, lr.labelCol: 'l', lr.predictionCol: 'p'}, \
{lr.regParam: 2.0, lr.featuresCol: 'f', lr.maxIter: 1, lr.labelCol: 'l', lr.predictionCol: 'p'}, \
{lr.regParam: 3.0, lr.featuresCol: 'f', lr.maxIter: 1, lr.labelCol: 'l', lr.predictionCol: 'p'}, \
{lr.regParam: 1.0, lr.featuresCol: 'f', lr.maxIter: 5, lr.labelCol: 'l', lr.predictionCol: 'p'}, \
{lr.regParam: 2.0, lr.featuresCol: 'f', lr.maxIter: 5, lr.labelCol: 'l', lr.predictionCol: 'p'}, \
{lr.regParam: 3.0, lr.featuresCol: 'f', lr.maxIter: 5, lr.labelCol: 'l', lr.predictionCol: 'p'}]
>>> fail_count = 0
>>> for e in expected:
... if e not in output:
... fail_count += 1
>>> if len(expected) != len(output):
... fail_count += 1
>>> fail_count
0
"""
def __init__(self):
self._param_grid = {}
def addGrid(self, param, values):
"""
Sets the given parameters in this grid to fixed values.
"""
self._param_grid[param] = values
return self
def baseOn(self, *args):
"""
Sets the given parameters in this grid to fixed values.
Accepts either a parameter dictionary or a list of (parameter, value) pairs.
"""
if isinstance(args[0], dict):
self.baseOn(*args[0].items())
else:
for (param, value) in args:
self.addGrid(param, [value])
return self
def build(self):
"""
Builds and returns all combinations of parameters specified
by the param grid.
"""
param_maps = [{}]
for (param, values) in self._param_grid.items():
new_param_maps = []
for value in values:
for old_map in param_maps:
copied_map = old_map.copy()
copied_map[param] = value
new_param_maps.append(copied_map)
param_maps = new_param_maps
return param_maps
if __name__ == "__main__":
import doctest
doctest.testmod()
