96 lines
2.6 KiB
Python
96 lines
2.6 KiB
Python
# -*- coding: utf-8 -*-
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#
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# report_diff.py
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#
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# Date Created: July 11, 2018
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#
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# Author: Michael E. Tryby
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# US EPA - ORD/NRMRL
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#
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# system imports
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import itertools as it
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# third party imports
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import numpy as np
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# project imports
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import nrtest_epanet.output_reader as ordr
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def _binary_diff(path_test, path_ref, min_cdd):
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for (test, ref) in it.izip(ordr.output_generator(path_test),
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ordr.output_generator(path_ref)):
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if len(test[0]) != len(ref[0]):
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raise ValueError('Inconsistent lengths')
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# Skip over arrays that are equal
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if np.array_equal(test[0], ref[0]):
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continue
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else:
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lre = _log_relative_error(test[0], ref[0])
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idx = np.unravel_index(np.argmin(lre), lre.shape)
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if lre[idx] < min_cdd:
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_print_diff(idx, lre, test, ref)
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return
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def _log_relative_error(q, c):
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'''
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Computes log relative error, a measure of numerical accuracy.
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Single precision machine epsilon is between 2^-24 and 2^-23.
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Reference:
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McCullough, B. D. "Assessing the Reliability of Statistical Software: Part I."
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The American Statistician, vol. 52, no. 4, 1998, pp. 358-366.
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'''
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diff = np.subtract(q, c)
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tmp_c = np.copy(c)
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# If ref value is small compute absolute error
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tmp_c[np.fabs(tmp_c) < 1.0e-6] = 1.0
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re = np.fabs(diff)/np.fabs(tmp_c)
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# If re is tiny set lre to number of digits
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re[re < 1.0e-7] = 1.0e-7
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# If re is very large set lre to zero
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re[re > 2.0] = 1.0
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return np.negative(np.log10(re))
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def _print_diff(idx, lre, test, ref):
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idx_val = (idx[0], ref[1])
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test_val = (test[0][idx[0]])
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ref_val = (ref[0][idx[0]])
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diff_val = (test_val - ref_val)
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lre_val = (lre[idx[0]])
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print("Idx: %s\nSut: %f Ref: %f Diff: %f LRE: %f\n"
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% (idx_val, test_val, ref_val, diff_val, lre_val))
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def report(args):
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_binary_diff(args.test, args.ref, args.mincdd)
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if __name__ == '__main__':
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from argparse import ArgumentParser
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parser = ArgumentParser(description='EPANET benchmark difference reporting')
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parser.set_defaults(func=report)
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parser.add_argument('-t', '--test', default=None,
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help='Path to test benchmark')
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parser.add_argument('-r', '--ref', default=None,
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help='Path to reference benchmark')
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parser.add_argument('-mc', '--mincdd', type=int, default=3,
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help='Minimum correct decimal digits')
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args = parser.parse_args()
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args.func(args)
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