68 lines
1.8 KiB
Python
68 lines
1.8 KiB
Python
# -*- coding: utf-8 -*-
|
|
|
|
#
|
|
# report_diff.py
|
|
#
|
|
# Date Created: July 11, 2018
|
|
#
|
|
# Author: Michael E. Tryby
|
|
# US EPA - ORD/NRMRL
|
|
#
|
|
|
|
# system imports
|
|
import itertools as it
|
|
|
|
# third party imports
|
|
import numpy as np
|
|
|
|
# project imports
|
|
import nrtest_epanet.output_reader as ordr
|
|
|
|
|
|
def report_diff(path_test, path_ref, min_cdd):
|
|
for (test, ref) in it.izip(ordr.output_generator(path_test),
|
|
ordr.output_generator(path_ref)):
|
|
|
|
if len(test[0]) != len(ref[0]):
|
|
raise ValueError('Inconsistent lengths')
|
|
|
|
# Skip over arrays that are equal
|
|
if np.array_equal(test[0], ref[0]):
|
|
continue
|
|
else:
|
|
lre = log_relative_error(test[0], ref[0])
|
|
idx = np.unravel_index(np.argmin(lre), lre.shape)
|
|
|
|
if lre[idx] < min_cdd:
|
|
print_diff(idx, lre, test, ref)
|
|
|
|
return
|
|
|
|
|
|
def log_relative_error(q, c):
|
|
'''
|
|
Computes log relative error, a measure of numerical accuracy.
|
|
|
|
Single precision machine epsilon is between 2^-24 and 2^-23.
|
|
|
|
Reference:
|
|
McCullough, B. D. "Assessing the Reliability of Statistical Software: Part I."
|
|
The American Statistician, vol. 52, no. 4, 1998, pp. 358-366.
|
|
'''
|
|
diff = np.subtract(q, c)
|
|
tmp_c = np.copy(c)
|
|
# If ref value is small compute absolute error
|
|
tmp_c[np.fabs(tmp_c) <= 1.0e-6] = 1.0
|
|
|
|
re = np.fabs(diff)/np.fabs(tmp_c)
|
|
# If re is tiny set lre to number of digits
|
|
re[re < 1.0e-7] = 1.0e-7
|
|
# If re is very large set lre to zero
|
|
re[re > 2.0] = 1.0
|
|
|
|
return np.negative(np.log10(re))
|
|
|
|
|
|
def print_diff(idx, lre, test, ref):
|
|
print("LRE: %f\nIdx: %s\nSut: %f\nRef: %f\n"
|
|
% ((lre[idx]),(idx[0], ref[1]),(test[0][idx[0]]),(ref[0][idx[0]]))) |