spark-instrumented-optimizer/python/pyspark/mllib/stat/KernelDensity.py
zero323 01321bc0fe [SPARK-33252][PYTHON][DOCS] Migration to NumPy documentation style in MLlib (pyspark.mllib.*)
### What changes were proposed in this pull request?

This PR proposes migration of `pyspark.mllib` to NumPy documentation style.

### Why are the changes needed?

To improve documentation style.

Before:

![old](https://user-images.githubusercontent.com/1554276/100097941-90234980-2e5d-11eb-8b4d-c25d98d85191.png)

After:

![new](https://user-images.githubusercontent.com/1554276/100097966-987b8480-2e5d-11eb-9e02-07b18c327624.png)

### Does this PR introduce _any_ user-facing change?

Yes, this changes both rendered HTML docs and console representation (SPARK-33243).

### How was this patch tested?

`dev/lint-python` and manual inspection.

Closes #30413 from zero323/SPARK-33252.

Authored-by: zero323 <mszymkiewicz@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2020-11-25 10:24:41 +09:00

57 lines
1.9 KiB
Python

#
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# 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
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# http://www.apache.org/licenses/LICENSE-2.0
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import numpy as np
from pyspark.mllib.common import callMLlibFunc
from pyspark.rdd import RDD
class KernelDensity(object):
"""
Estimate probability density at required points given an RDD of samples
from the population.
Examples
--------
>>> kd = KernelDensity()
>>> sample = sc.parallelize([0.0, 1.0])
>>> kd.setSample(sample)
>>> kd.estimate([0.0, 1.0])
array([ 0.12938758, 0.12938758])
"""
def __init__(self):
self._bandwidth = 1.0
self._sample = None
def setBandwidth(self, bandwidth):
"""Set bandwidth of each sample. Defaults to 1.0"""
self._bandwidth = bandwidth
def setSample(self, sample):
"""Set sample points from the population. Should be a RDD"""
if not isinstance(sample, RDD):
raise TypeError("samples should be a RDD, received %s" % type(sample))
self._sample = sample
def estimate(self, points):
"""Estimate the probability density at points"""
points = list(points)
densities = callMLlibFunc(
"estimateKernelDensity", self._sample, self._bandwidth, points)
return np.asarray(densities)