""" @package tests.test_swarm unit tests for pmsco.swarm the purpose of these tests is to help debugging the code. to run the tests, change to the directory which contains the tests directory, and execute =nosetests=. @pre nose must be installed (python-nose package on Debian). @author Matthias Muntwiler, matthias.muntwiler@psi.ch @copyright (c) 2015 by Paul Scherrer Institut @n Licensed under the Apache License, Version 2.0 (the "License"); @n 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 """ import unittest import os import os.path import tempfile import shutil import numpy as np import pmsco.swarm as mo import pmsco.project as mp POP_SIZE = 5 class TestPopulation(unittest.TestCase): def setUp(self): self.test_dir = tempfile.mkdtemp() self.domain = mp.Domain() self.domain.add_param('A', 1.5, 1.0, 2.0, 0.1) self.domain.add_param('B', 2.5, 2.0, 3.0, 0.1) self.domain.add_param('C', 3.5, 3.0, 4.0, 0.1) self.expected_names = ('A', 'B', 'C', '_particle', '_gen', '_model', '_rfac') self.size = POP_SIZE self.pop = mo.Population() self.optimum1 = {'A': 1.045351, 'B': 2.346212, 'C': 3.873627} def tearDown(self): # after each test method self.pop = None shutil.rmtree(self.test_dir) @classmethod def setup_class(cls): # before any methods in this class pass @classmethod def teardown_class(cls): # teardown_class() after any methods in this class pass def rfactor1(self, pos): r = (pos['A'] - self.optimum1['A'])**2 \ + (pos['B'] - self.optimum1['B'])**2 \ + (pos['C'] - self.optimum1['C'])**2 r /= 3.0 return r def test_setup(self): self.pop.setup(self.size, self.domain) self.assertItemsEqual(self.pop.pos.dtype.names, self.expected_names) self.assertEqual(self.pop.pos.shape, (POP_SIZE,)) self.assertItemsEqual(np.arange(POP_SIZE), self.pop.pos['_particle']) self.assertItemsEqual(np.zeros((POP_SIZE)), self.pop.pos['_gen']) self.assertItemsEqual(np.arange(POP_SIZE), self.pop.pos['_model']) self.assertAlmostEqual(2.1, self.pop.pos['_rfac'][0], 3) self.assertAlmostEqual(2.1, self.pop.pos['_rfac'][1], 3) self.assertAlmostEqual(2.1, self.pop.pos['_rfac'][2], 3) self.assertAlmostEqual(2.1, self.pop.pos['_rfac'][3], 3) self.assertAlmostEqual(2.1, self.pop.pos['_rfac'][4], 3) self.assertEqual(0, self.pop.generation) self.assertEqual(POP_SIZE, self.pop.model_count) def test_setup_with_results(self): data_dir = os.path.dirname(os.path.abspath(__file__)) data_file = os.path.join(data_dir, "test_swarm.setup_with_results.1.dat") self.pop.setup(self.size, self.domain, data_file, False) self.assertItemsEqual(self.pop.pos.dtype.names, self.expected_names) self.assertEqual(self.pop.pos.shape, (POP_SIZE,)) self.assertEqual(0, self.pop.generation) self.assertEqual(3, self.pop.model_count) self.assertItemsEqual(np.arange(POP_SIZE), self.pop.pos['_particle']) self.assertItemsEqual([-1, -1, 0, 0, 0], self.pop.pos['_gen']) self.assertItemsEqual([-1, -2, 0, 1, 2], self.pop.pos['_model']) self.assertAlmostEqual(0.3, self.pop.pos['_rfac'][0], 3) self.assertAlmostEqual(0.6, self.pop.pos['_rfac'][1], 3) self.assertAlmostEqual(2.1, self.pop.pos['_rfac'][2], 3) self.assertAlmostEqual(2.1, self.pop.pos['_rfac'][3], 3) self.assertAlmostEqual(2.1, self.pop.pos['_rfac'][4], 3) self.assertAlmostEqual(1.3, self.pop.pos['A'][0], 3) self.assertAlmostEqual(1.1, self.pop.pos['A'][1], 3) self.assertAlmostEqual(1.5, self.pop.pos['A'][4], 3) self.assertAlmostEqual(2.3, self.pop.pos['B'][0], 3) self.assertAlmostEqual(2.1, self.pop.pos['B'][1], 3) self.assertAlmostEqual(2.5, self.pop.pos['B'][4], 3) self.assertAlmostEqual(3.3, self.pop.pos['C'][0], 3) self.assertAlmostEqual(3.1, self.pop.pos['C'][1], 3) self.assertAlmostEqual(3.5, self.pop.pos['C'][4], 3) def test_setup_with_results_recalc(self): data_dir = os.path.dirname(os.path.abspath(__file__)) data_file = os.path.join(data_dir, "test_swarm.setup_with_results.1.dat") self.pop.setup(self.size, self.domain, data_file, True) self.assertItemsEqual(self.pop.pos.dtype.names, self.expected_names) self.assertEqual(self.pop.pos.shape, (POP_SIZE,)) self.assertEqual(self.pop.generation, 0) self.assertEqual(self.pop.model_count, POP_SIZE) self.assertItemsEqual(self.pop.pos['_particle'], np.arange(POP_SIZE)) self.assertItemsEqual(self.pop.pos['_gen'], [0, 0, 0, 0, 0]) self.assertItemsEqual(self.pop.pos['_model'], np.arange(POP_SIZE)) self.assertAlmostEqual(2.1, self.pop.pos['_rfac'][0], 3) self.assertAlmostEqual(2.1, self.pop.pos['_rfac'][1], 3) self.assertAlmostEqual(2.1, self.pop.pos['_rfac'][2], 3) self.assertAlmostEqual(2.1, self.pop.pos['_rfac'][3], 3) self.assertAlmostEqual(2.1, self.pop.pos['_rfac'][4], 3) self.assertAlmostEqual(1.3, self.pop.pos['A'][0], 3) self.assertAlmostEqual(1.1, self.pop.pos['A'][1], 3) self.assertAlmostEqual(1.5, self.pop.pos['A'][4], 3) self.assertAlmostEqual(2.3, self.pop.pos['B'][0], 3) self.assertAlmostEqual(2.1, self.pop.pos['B'][1], 3) self.assertAlmostEqual(2.5, self.pop.pos['B'][4], 3) self.assertAlmostEqual(3.3, self.pop.pos['C'][0], 3) self.assertAlmostEqual(3.1, self.pop.pos['C'][1], 3) self.assertAlmostEqual(3.5, self.pop.pos['C'][4], 3) def test_pos_gen(self): self.pop.setup(self.size, self.domain) for index, item in enumerate(self.pop.pos_gen()): self.assertIsInstance(item, dict) self.assertItemsEqual(item.keys(), self.expected_names) self.assertEqual(item['_particle'], index) def test_randomize(self): self.pop.setup(self.size, self.domain) self.pop.randomize() m = np.mean(self.pop.pos['A']) self.assertGreaterEqual(m, self.domain.min['A']) self.assertLessEqual(m, self.domain.max['A']) def test_seed(self): self.pop.setup(self.size, self.domain) self.pop.seed(self.domain.start) self.assertAlmostEqual(self.pop.pos['A'][0], self.domain.start['A'], delta=0.001) def test_best_friend(self): self.pop.setup(self.size, self.domain) self.pop.best['_rfac'] = np.arange(self.size) friend = self.pop.best_friend(0) self.assertNotIsInstance(friend, np.ndarray) self.assertItemsEqual(friend.dtype.names, self.expected_names) def test_advance_particle(self): self.pop.setup(self.size, self.domain) self.pop.pos['A'] = np.linspace(1.0, 2.0, POP_SIZE) self.pop.pos['B'] = np.linspace(2.0, 3.0, POP_SIZE) self.pop.pos['C'] = np.linspace(3.0, 4.0, POP_SIZE) self.pop.pos['_rfac'] = np.linspace(2.0, 1.0, POP_SIZE) self.pop.vel['A'] = np.linspace(-0.1, 0.1, POP_SIZE) self.pop.vel['B'] = np.linspace(-0.1, 0.1, POP_SIZE) self.pop.vel['C'] = np.linspace(-0.1, 0.1, POP_SIZE) pos0 = self.pop.pos['A'][0] self.pop.advance_particle(0) pos1 = self.pop.pos['A'][0] self.assertNotAlmostEqual(pos0, pos1, delta=0.001) for key in ['A','B','C']: for pos in self.pop.pos[key]: self.assertGreaterEqual(pos, self.domain.min[key]) self.assertLessEqual(pos, self.domain.max[key]) def test_add_result(self): self.pop.setup(self.size, self.domain) i_sample = 1 i_result = 0 result = self.pop.pos[i_sample] self.pop.add_result(result, 0.0) self.assertEqual(self.pop.results.shape[0], 1) self.assertItemsEqual(self.pop.results[i_result], result) self.assertItemsEqual(self.pop.best[i_sample], result) def test_is_converged(self): self.pop.setup(self.size, self.domain) self.assertFalse(self.pop.is_converged()) i_sample = 0 result = self.pop.pos[i_sample] for i in range(POP_SIZE): rfac = 1.0 - float(i)/POP_SIZE self.pop.add_result(result, rfac) self.assertFalse(self.pop.is_converged()) for i in range(POP_SIZE): rfac = (1.0 - float(i)/POP_SIZE) / 1000.0 self.pop.add_result(result, rfac) self.assertTrue(self.pop.is_converged()) def test_save_population(self): self.pop.setup(self.size, self.domain) filename = os.path.join(self.test_dir, "test_save_population.pop") self.pop.save_population(filename) def test_save_results(self): self.pop.setup(self.size, self.domain) i_sample = 1 result = self.pop.pos[i_sample] self.pop.add_result(result, 1.0) filename = os.path.join(self.test_dir, "test_save_results.dat") self.pop.save_results(filename) def test_save_array(self): self.pop.setup(self.size, self.domain) filename = os.path.join(self.test_dir, "test_save_array.pos") self.pop.save_array(filename, self.pop.pos) def test_load_array(self): n = 3 filename = os.path.join(self.test_dir, "test_load_array") self.pop.setup(self.size, self.domain) # expected array dt_exp = self.pop.get_model_dtype(self.domain.start) a_exp = np.zeros((n,), dtype=dt_exp) a_exp['A'] = np.linspace(0, 1, n) a_exp['B'] = np.linspace(1, 2, n) a_exp['C'] = np.linspace(3, 4, n) a_exp['_rfac'] = np.linspace(5, 6, n) a_exp['_gen'] = np.array([3, 4, 7]) a_exp['_particle'] = np.array([1, 0, 2]) a_exp['_model'] = np.array([3, 6, 1]) # test array is a expected array with different column order dt_test = [('A', 'f4'), ('_particle', 'i4'), ('_rfac', 'f4'), ('C', 'f4'), ('_gen', 'i4'), ('B', 'f4'), ('_model', 'i4')] names_test = [a[0] for a in dt_test] a_test = np.zeros((n,), dtype=dt_test) for name in names_test: a_test[name] = a_exp[name] header = " ".join(names_test) np.savetxt(filename, a_test, fmt='%g', header=header) result = np.zeros((n,), dtype=dt_exp) result = self.pop.load_array(filename, result) self.assertItemsEqual(result.dtype.names, a_exp.dtype.names) for name in a_exp.dtype.names: np.testing.assert_almost_equal(result[name], a_exp[name], err_msg=name) def test_constrain_position(self): # upper pos1 = 11.0 vel1 = 5.0 min1 = 0.0 max1 = 10.0 pos2, vel2, min2, max2 = mo.Population.constrain_position(pos1, vel1, min1, max1, 're-enter') self.assertAlmostEqual(pos2, 1.0) self.assertAlmostEqual(vel2, vel1) self.assertAlmostEqual(min1, min2) self.assertAlmostEqual(max1, max2) pos2, vel2, min2, max2 = mo.Population.constrain_position(pos1, vel1, min1, max1, 'bounce') self.assertAlmostEqual(pos2, 9.0) self.assertAlmostEqual(vel2, -vel1) self.assertAlmostEqual(min1, min2) self.assertAlmostEqual(max1, max2) pos2, vel2, min2, max2 = mo.Population.constrain_position(pos1, vel1, min1, max1, 'scatter') self.assertGreaterEqual(pos2, 6.0) self.assertLessEqual(pos2, 10.0) self.assertGreaterEqual(vel2, 0.0) self.assertLessEqual(vel2, vel1) self.assertAlmostEqual(min1, min2) self.assertAlmostEqual(max1, max2) pos2, vel2, min2, max2 = mo.Population.constrain_position(pos1, vel1, min1, max1, 'stick') self.assertAlmostEqual(pos2, max1) self.assertAlmostEqual(vel2, max1 - (pos1 - vel1)) self.assertAlmostEqual(min1, min2) self.assertAlmostEqual(max1, max2) pos2, vel2, min2, max2 = mo.Population.constrain_position(pos1, vel1, min1, max1, 'random') self.assertGreaterEqual(pos2, 0.0) self.assertLessEqual(pos2, 10.0) self.assertGreaterEqual(vel2, -(max1 - min1)) self.assertLessEqual(vel2, (max1 - min1)) self.assertAlmostEqual(min1, min2) self.assertAlmostEqual(max1, max2) pos2, vel2, min2, max2 = mo.Population.constrain_position(pos1, vel1, min1, max1, 'expand') self.assertAlmostEqual(pos2, pos1) self.assertAlmostEqual(vel2, vel1) self.assertAlmostEqual(min1, min2) self.assertAlmostEqual(max2, pos1) self.assertRaises(ValueError, mo.Population.constrain_position, pos1, vel1, min1, max1, 'undefined') # lower pos1 = -1.0 vel1 = -5.0 min1 = 0.0 max1 = 10.0 pos2, vel2, min2, max2 = mo.Population.constrain_position(pos1, vel1, min1, max1, 're-enter') self.assertAlmostEqual(pos2, 9.0) self.assertAlmostEqual(vel2, vel1) self.assertAlmostEqual(min1, min2) self.assertAlmostEqual(max1, max2) pos2, vel2, min2, max2 = mo.Population.constrain_position(pos1, vel1, min1, max1, 'bounce') self.assertAlmostEqual(pos2, 1.0) self.assertAlmostEqual(vel2, -vel1) self.assertAlmostEqual(min1, min2) self.assertAlmostEqual(max1, max2) pos2, vel2, min2, max2 = mo.Population.constrain_position(pos1, vel1, min1, max1, 'scatter') self.assertGreaterEqual(pos2, 0.0) self.assertLessEqual(pos2, 4.0) self.assertGreaterEqual(vel2, vel1) self.assertLessEqual(vel2, 0.0) self.assertAlmostEqual(min1, min2) self.assertAlmostEqual(max1, max2) pos2, vel2, min2, max2 = mo.Population.constrain_position(pos1, vel1, min1, max1, 'stick') self.assertAlmostEqual(pos2, min1) self.assertAlmostEqual(vel2, min1 - (pos1 - vel1)) self.assertAlmostEqual(min1, min2) self.assertAlmostEqual(max1, max2) pos2, vel2, min2, max2 = mo.Population.constrain_position(pos1, vel1, min1, max1, 'random') self.assertGreaterEqual(pos2, 0.0) self.assertLessEqual(pos2, 10.0) self.assertGreaterEqual(vel2, -(max1 - min1)) self.assertLessEqual(vel2, max1 - min1) self.assertAlmostEqual(min1, min2) self.assertAlmostEqual(max1, max2) pos2, vel2, min2, max2 = mo.Population.constrain_position(pos1, vel1, min1, max1, 'expand') self.assertAlmostEqual(pos2, pos1) self.assertAlmostEqual(vel2, vel1) self.assertAlmostEqual(min2, pos1) self.assertAlmostEqual(max2, max1) self.assertRaises(ValueError, mo.Population.constrain_position, pos1, vel1, min1, max1, 'undefined') def test_convergence_1(self): self.pop.setup(self.size, self.domain) self.pop.pos['A'] = np.linspace(1.0, 2.0, POP_SIZE) self.pop.pos['B'] = np.linspace(2.0, 3.0, POP_SIZE) self.pop.pos['C'] = np.linspace(3.0, 4.0, POP_SIZE) self.pop.pos['_rfac'] = np.linspace(2.0, 1.0, POP_SIZE) self.pop.vel['A'] = np.linspace(-0.1, 0.1, POP_SIZE) self.pop.vel['B'] = np.linspace(-0.1, 0.1, POP_SIZE) self.pop.vel['C'] = np.linspace(-0.1, 0.1, POP_SIZE) for i in range(10): self.pop.advance_population() for pos in self.pop.pos: self.pop.add_result(pos, self.rfactor1(pos)) for pos in self.pop.pos: self.assertLess(pos['_rfac'], 0.2) if __name__ == '__main__': unittest.main()