Mercurial > hg > svcore
view base/test/TestColumnOp.h @ 1394:9ef1cc26024c
Add Range01 normalisation method to ColumnOp. This is the normalisation that is actually used in the Colour 3D Plot layer historically when column normalisation is enabled (not Max1 after all).
author | Chris Cannam |
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date | Tue, 28 Feb 2017 14:04:16 +0000 |
parents | bd1eb56df8d5 |
children | 1b688ab5f1b3 |
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/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*- vi:set ts=8 sts=4 sw=4: */ /* Sonic Visualiser An audio file viewer and annotation editor. Centre for Digital Music, Queen Mary, University of London. This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. See the file COPYING included with this distribution for more information. */ #ifndef TEST_COLUMN_OP_H #define TEST_COLUMN_OP_H #include "../ColumnOp.h" #include <QObject> #include <QtTest> #include <QDir> #include <iostream> //#define REPORT 1 using namespace std; class TestColumnOp : public QObject { Q_OBJECT typedef ColumnOp C; typedef ColumnOp::Column Column; typedef vector<double> BinMapping; #ifdef REPORT template <typename T> void report(vector<T> v) { cerr << "Vector is: [ "; for (int i = 0; i < int(v.size()); ++i) { if (i > 0) cerr << ", "; cerr << v[i]; } cerr << " ]\n"; } #else template <typename T> void report(vector<T> ) { } #endif private slots: void applyGain() { QCOMPARE(C::applyGain({}, 1.0), Column()); Column c { 1, 2, 3, -4, 5, 6 }; Column actual(C::applyGain(c, 1.5)); Column expected { 1.5f, 3, 4.5f, -6, 7.5f, 9 }; QCOMPARE(actual, expected); actual = C::applyGain(c, 1.0); QCOMPARE(actual, c); actual = C::applyGain(c, 0.0); expected = { 0, 0, 0, 0, 0, 0 }; QCOMPARE(actual, expected); } void fftScale() { QCOMPARE(C::fftScale({}, 2.0), Column()); Column c { 1, 2, 3, -4, 5 }; Column actual(C::fftScale(c, 8)); Column expected { 0.25f, 0.5f, 0.75f, -1, 1.25f }; QCOMPARE(actual, expected); } void isPeak_null() { QVERIFY(!C::isPeak({}, 0)); QVERIFY(!C::isPeak({}, 1)); QVERIFY(!C::isPeak({}, -1)); } void isPeak_obvious() { Column c { 0.4f, 0.5f, 0.3f }; QVERIFY(!C::isPeak(c, 0)); QVERIFY(C::isPeak(c, 1)); QVERIFY(!C::isPeak(c, 2)); } void isPeak_edges() { Column c { 0.5f, 0.4f, 0.3f }; QVERIFY(C::isPeak(c, 0)); QVERIFY(!C::isPeak(c, 1)); QVERIFY(!C::isPeak(c, 2)); QVERIFY(!C::isPeak(c, 3)); QVERIFY(!C::isPeak(c, -1)); c = { 1.4f, 1.5f }; QVERIFY(!C::isPeak(c, 0)); QVERIFY(C::isPeak(c, 1)); } void isPeak_flat() { Column c { 0.0f, 0.0f, 0.0f }; QVERIFY(C::isPeak(c, 0)); QVERIFY(!C::isPeak(c, 1)); QVERIFY(!C::isPeak(c, 2)); } void isPeak_mixedSign() { Column c { 0.4f, -0.5f, -0.3f, -0.6f, 0.1f, -0.3f }; QVERIFY(C::isPeak(c, 0)); QVERIFY(!C::isPeak(c, 1)); QVERIFY(C::isPeak(c, 2)); QVERIFY(!C::isPeak(c, 3)); QVERIFY(C::isPeak(c, 4)); QVERIFY(!C::isPeak(c, 5)); } void isPeak_duplicate() { Column c({ 0.5f, 0.5f, 0.4f, 0.4f }); QVERIFY(C::isPeak(c, 0)); QVERIFY(!C::isPeak(c, 1)); QVERIFY(!C::isPeak(c, 2)); QVERIFY(!C::isPeak(c, 3)); c = { 0.4f, 0.4f, 0.5f, 0.5f }; QVERIFY(C::isPeak(c, 0)); // counterintuitive but necessary QVERIFY(!C::isPeak(c, 1)); QVERIFY(C::isPeak(c, 2)); QVERIFY(!C::isPeak(c, 3)); } void peakPick() { QCOMPARE(C::peakPick({}), Column()); Column c({ 0.5f, 0.5f, 0.4f, 0.4f }); QCOMPARE(C::peakPick(c), Column({ 0.5f, 0.0f, 0.0f, 0.0f })); c = Column({ 0.4f, -0.5f, -0.3f, -0.6f, 0.1f, -0.3f }); QCOMPARE(C::peakPick(c), Column({ 0.4f, 0.0f, -0.3f, 0.0f, 0.1f, 0.0f })); } void normalize_null() { QCOMPARE(C::normalize({}, ColumnNormalization::None), Column()); QCOMPARE(C::normalize({}, ColumnNormalization::Sum1), Column()); QCOMPARE(C::normalize({}, ColumnNormalization::Max1), Column()); QCOMPARE(C::normalize({}, ColumnNormalization::Range01), Column()); QCOMPARE(C::normalize({}, ColumnNormalization::Hybrid), Column()); } void normalize_none() { Column c { 1, 2, 3, 4 }; QCOMPARE(C::normalize(c, ColumnNormalization::None), c); } void normalize_none_mixedSign() { Column c { 1, 2, -3, -4 }; QCOMPARE(C::normalize(c, ColumnNormalization::None), c); } void normalize_sum1() { Column c { 1, 2, 4, 3 }; QCOMPARE(C::normalize(c, ColumnNormalization::Sum1), Column({ 0.1f, 0.2f, 0.4f, 0.3f })); } void normalize_sum1_mixedSign() { Column c { 1, 2, -4, -3 }; QCOMPARE(C::normalize(c, ColumnNormalization::Sum1), Column({ 0.1f, 0.2f, -0.4f, -0.3f })); } void normalize_max1() { Column c { 4, 3, 2, 1 }; QCOMPARE(C::normalize(c, ColumnNormalization::Max1), Column({ 1.0f, 0.75f, 0.5f, 0.25f })); } void normalize_max1_mixedSign() { Column c { -4, -3, 2, 1 }; QCOMPARE(C::normalize(c, ColumnNormalization::Max1), Column({ -1.0f, -0.75f, 0.5f, 0.25f })); } void normalize_range01() { Column c { 4, 3, 2, 1 }; QCOMPARE(C::normalize(c, ColumnNormalization::Range01), Column({ 1.0f, 2.f/3.f, 1.f/3.f, 0.0f })); } void normalize_range01_mixedSign() { Column c { -2, -3, 2, 1 }; QCOMPARE(C::normalize(c, ColumnNormalization::Range01), Column({ 0.2f, 0.0f, 1.0f, 0.8f })); } void normalize_hybrid() { // with max == 99, log10(max+1) == 2 so scale factor will be 2/99 Column c { 22, 44, 99, 66 }; QCOMPARE(C::normalize(c, ColumnNormalization::Hybrid), Column({ 44.0f/99.0f, 88.0f/99.0f, 2.0f, 132.0f/99.0f })); } void normalize_hybrid_mixedSign() { // with max == 99, log10(max+1) == 2 so scale factor will be 2/99 Column c { 22, 44, -99, -66 }; QCOMPARE(C::normalize(c, ColumnNormalization::Hybrid), Column({ 44.0f/99.0f, 88.0f/99.0f, -2.0f, -132.0f/99.0f })); } void distribute_simple() { Column in { 1, 2, 3 }; BinMapping binfory { 0.0f, 0.5f, 1.0f, 1.5f, 2.0f, 2.5f }; Column expected { 1, 1, 2, 2, 3, 3 }; Column actual(C::distribute(in, 6, binfory, 0, false)); report(actual); QCOMPARE(actual, expected); } void distribute_simple_interpolated() { Column in { 1, 2, 3 }; BinMapping binfory { 0.0f, 0.5f, 1.0f, 1.5f, 2.0f, 2.5f }; // There is a 0.5-bin offset from the distribution you might // expect, because this corresponds visually to the way that // bin values are duplicated upwards in simple_distribution. // It means that switching between interpolated and // non-interpolated views retains the visual position of each // bin peak as somewhere in the middle of the scale area for // that bin. Column expected { 1, 1, 1.5f, 2, 2.5f, 3 }; Column actual(C::distribute(in, 6, binfory, 0, true)); report(actual); QCOMPARE(actual, expected); } void distribute_nonlinear() { Column in { 1, 2, 3 }; BinMapping binfory { 0.0f, 0.2f, 0.5f, 1.0f, 2.0f, 2.5f }; Column expected { 1, 1, 1, 2, 3, 3 }; Column actual(C::distribute(in, 6, binfory, 0, false)); report(actual); QCOMPARE(actual, expected); } void distribute_nonlinear_interpolated() { // See distribute_simple_interpolated Column in { 1, 2, 3 }; BinMapping binfory { 0.0f, 0.2f, 0.5f, 1.0f, 2.0f, 2.5f }; Column expected { 1, 1, 1, 1.5, 2.5, 3 }; Column actual(C::distribute(in, 6, binfory, 0, true)); report(actual); QCOMPARE(actual, expected); } void distribute_shrinking() { Column in { 4, 1, 2, 3, 5, 6 }; BinMapping binfory { 0.0f, 2.0f, 4.0f }; Column expected { 4, 3, 6 }; Column actual(C::distribute(in, 3, binfory, 0, false)); report(actual); QCOMPARE(actual, expected); } void distribute_shrinking_interpolated() { // should be same as distribute_shrinking, we don't // interpolate when resizing down Column in { 4, 1, 2, 3, 5, 6 }; BinMapping binfory { 0.0f, 2.0f, 4.0f }; Column expected { 4, 3, 6 }; Column actual(C::distribute(in, 3, binfory, 0, true)); report(actual); QCOMPARE(actual, expected); } void distribute_nonlinear_someshrinking_interpolated() { // But we *should* interpolate if the mapping involves // shrinking some bins but expanding others. See // distribute_simple_interpolated for note on 0.5 offset Column in { 4, 1, 2, 3, 5, 6 }; BinMapping binfory { 0.0f, 3.0f, 4.0f, 4.5f }; Column expected { 4.0f, 2.5f, 4.0f, 5.0f }; Column actual(C::distribute(in, 4, binfory, 0, true)); report(actual); QCOMPARE(actual, expected); binfory = BinMapping { 0.5f, 1.0f, 2.0f, 5.0f }; expected = { 4.0f, 2.5f, 1.5f, 5.5f }; actual = (C::distribute(in, 4, binfory, 0, true)); report(actual); QCOMPARE(actual, expected); } }; #endif