| # 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. |
| |
| import unittest |
| from datasketches import req_ints_sketch, req_floats_sketch |
| import numpy as np |
| |
| class reqTest(unittest.TestCase): |
| def test_req_example(self): |
| k = 12 |
| n = 2 ** 20 |
| |
| # create a sketch and inject ~1 million N(0,1) points as an array and as a single item |
| req = req_floats_sketch(k, True) # high rank accuracy |
| req.update(np.random.normal(size=n-1)) |
| req.update(0.0) |
| |
| # 0 should be near the median |
| self.assertAlmostEqual(0.5, req.get_rank(0.0), delta=0.03) |
| |
| # the median should be near 0 |
| self.assertAlmostEqual(0.0, req.get_quantile(0.5), delta=0.03) |
| |
| # we also track the min/max independently from the rest of the data |
| # which lets us know the full observed data range |
| self.assertLessEqual(req.get_min_value(), req.get_quantile(0.01)) |
| self.assertLessEqual(0.0, req.get_rank(req.get_min_value())) |
| self.assertGreaterEqual(req.get_max_value(), req.get_quantile(0.99)) |
| self.assertGreaterEqual(1.0, req.get_rank(req.get_max_value())) |
| |
| # we can also extract a list of values at a time, |
| # here the values should give us something close to [-2, -1, 0, 1, 2]. |
| # then get the CDF, which will return something close to |
| # the original values used in get_quantiles() |
| # finally, can check the normalized rank error bound |
| pts = req.get_quantiles([0.0228, 0.1587, 0.5, 0.8413, 0.9772]) |
| cdf = req.get_cdf(pts) # include 1.0 at end to account for all probability mass |
| self.assertEqual(len(cdf), len(pts)+1) |
| |
| # For relative error quantiles, the error depends on the actual rank |
| # so we need to use that to detemrine the bounds |
| est = req.get_rank(0.999, True) |
| lb = req.get_rank_lower_bound(est, 1) |
| ub = req.get_rank_upper_bound(est, 1) |
| self.assertLessEqual(lb, est) |
| self.assertLessEqual(est, ub) |
| |
| # and a few basic queries about the sketch |
| self.assertFalse(req.is_empty()) |
| self.assertTrue(req.is_estimation_mode()) |
| self.assertEqual(req.get_n(), n) |
| self.assertLess(req.get_num_retained(), n) |
| self.assertEqual(req.get_k(), k) |
| |
| # merging itself will double the number of items the sketch has seen |
| req.merge(req) |
| self.assertEqual(req.get_n(), 2*n) |
| |
| # we can then serialize and reconstruct the sketch |
| req_bytes = req.serialize() |
| new_req = req.deserialize(req_bytes) |
| self.assertEqual(req.get_num_retained(), new_req.get_num_retained()) |
| self.assertEqual(req.get_min_value(), new_req.get_min_value()) |
| self.assertEqual(req.get_max_value(), new_req.get_max_value()) |
| self.assertEqual(req.get_quantile(0.7), new_req.get_quantile(0.7)) |
| self.assertEqual(req.get_rank(0.0), new_req.get_rank(0.0)) |
| |
| def test_req_ints_sketch(self): |
| k = 100 |
| n = 10 |
| req = req_ints_sketch(k) |
| for i in range(0, n): |
| req.update(i) |
| |
| self.assertEqual(req.get_min_value(), 0) |
| self.assertEqual(req.get_max_value(), n-1) |
| self.assertEqual(req.get_n(), n) |
| self.assertFalse(req.is_empty()) |
| self.assertFalse(req.is_estimation_mode()) # n < k |
| self.assertEqual(req.get_k(), k) |
| |
| pmf = req.get_pmf([round(n/2)]) |
| self.assertIsNotNone(pmf) |
| self.assertEqual(len(pmf), 2) |
| |
| cdf = req.get_cdf([round(n/2)]) |
| self.assertIsNotNone(cdf) |
| self.assertEqual(len(cdf), 2) |
| |
| self.assertEqual(req.get_quantile(0.5), round(n/2)) |
| quants = req.get_quantiles([0.25, 0.5, 0.75]) |
| self.assertIsNotNone(quants) |
| self.assertEqual(len(quants), 3) |
| |
| self.assertEqual(req.get_rank(round(n/2)), 0.5) |
| |
| # merge self |
| req.merge(req) |
| self.assertEqual(req.get_n(), 2 * n) |
| |
| sk_bytes = req.serialize() |
| self.assertTrue(isinstance(req_ints_sketch.deserialize(sk_bytes), req_ints_sketch)) |
| |
| def test_req_floats_sketch(self): |
| # already tested ints and it's templatized, so just make sure it instantiates properly |
| k = 75 |
| req = req_floats_sketch(k, False) # low rank accuracy |
| self.assertTrue(req.is_empty()) |
| self.assertFalse(req.is_hra()) |
| |
| if __name__ == '__main__': |
| unittest.main() |
