1/* 2 * Copyright (c) 1999-2008 Mark D. Hill and David A. Wood 3 * All rights reserved. 4 * 5 * Redistribution and use in source and binary forms, with or without 6 * modification, are permitted provided that the following conditions are 7 * met: redistributions of source code must retain the above copyright 8 * notice, this list of conditions and the following disclaimer; --- 12 unchanged lines hidden (view full) --- 21 * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT 22 * LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, 23 * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY 24 * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT 25 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE 26 * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 27 */ 28 |
29#include <cmath> 30#include <iomanip> 31 |
32#include "base/intmath.hh" |
33#include "mem/ruby/common/Histogram.hh" 34 35using namespace std; 36 37Histogram::Histogram(int binsize, int bins) 38{ |
39 m_binsize = binsize; 40 m_bins = bins; 41 clear(); |
42} 43 44Histogram::~Histogram() 45{ 46} 47 |
48void 49Histogram::clear(int binsize, int bins) |
50{ |
51 m_binsize = binsize; 52 clear(bins); |
53} 54 |
55void 56Histogram::clear(int bins) |
57{ |
58 m_bins = bins; 59 m_largest_bin = 0; 60 m_max = 0; 61 m_data.setSize(m_bins); 62 for (int i = 0; i < m_bins; i++) { 63 m_data[i] = 0; 64 } 65 m_count = 0; 66 m_max = 0; |
67 |
68 m_sumSamples = 0; 69 m_sumSquaredSamples = 0; |
70} 71 72 |
73void 74Histogram::add(int64 value) |
75{ |
76 assert(value >= 0); 77 m_max = max(m_max, value); 78 m_count++; |
79 |
80 m_sumSamples += value; 81 m_sumSquaredSamples += (value*value); |
82 |
83 int index; 84 if (m_binsize == -1) { 85 // This is a log base 2 histogram 86 if (value == 0) { 87 index = 0; 88 } else { 89 index = floorLog2(value) + 1; 90 if (index >= m_data.size()) { 91 index = m_data.size() - 1; 92 } 93 } |
94 } else { |
95 // This is a linear histogram 96 while (m_max >= (m_bins * m_binsize)) { 97 for (int i = 0; i < m_bins/2; i++) { 98 m_data[i] = m_data[i*2] + m_data[i*2 + 1]; 99 } 100 for (int i = m_bins/2; i < m_bins; i++) { 101 m_data[i] = 0; 102 } 103 m_binsize *= 2; 104 } 105 index = value/m_binsize; |
106 } |
107 assert(index >= 0); 108 m_data[index]++; 109 m_largest_bin = max(m_largest_bin, index); |
110} 111 |
112void 113Histogram::add(const Histogram& hist) |
114{ |
115 assert(hist.getBins() == m_bins); 116 assert(hist.getBinSize() == -1); // assume log histogram 117 assert(m_binsize == -1); |
118 |
119 for (int j = 0; j < hist.getData(0); j++) { 120 add(0); |
121 } |
122 |
123 for (int i = 1; i < m_bins; i++) { 124 for (int j = 0; j < hist.getData(i); j++) { 125 add(1<<(i-1)); // account for the + 1 index 126 } 127 } |
128} 129 130// Computation of standard deviation of samples a1, a2, ... aN 131// variance = [SUM {ai^2} - (SUM {ai})^2/N]/(N-1) 132// std deviation equals square root of variance |
133double 134Histogram::getStandardDeviation() const |
135{ |
136 if (m_count <= 1) 137 return 0.0; 138 139 double variance = 140 (double)(m_sumSquaredSamples - m_sumSamples * m_sumSamples / m_count) 141 / (m_count - 1); 142 return sqrt(variance); |
143} 144 |
145void 146Histogram::print(ostream& out) const |
147{ |
148 printWithMultiplier(out, 1.0); |
149} 150 |
151void 152Histogram::printPercent(ostream& out) const |
153{ |
154 if (m_count == 0) { 155 printWithMultiplier(out, 0.0); 156 } else { 157 printWithMultiplier(out, 100.0 / double(m_count)); 158 } |
159} 160 |
161void 162Histogram::printWithMultiplier(ostream& out, double multiplier) const |
163{ |
164 if (m_binsize == -1) { 165 out << "[binsize: log2 "; |
166 } else { |
167 out << "[binsize: " << m_binsize << " "; |
168 } |
169 out << "max: " << m_max << " "; 170 out << "count: " << m_count << " "; 171 // out << "total: " << m_sumSamples << " "; 172 if (m_count == 0) { 173 out << "average: NaN |"; 174 out << "standard deviation: NaN |"; 175 } else { 176 out << "average: " << setw(5) << ((double) m_sumSamples)/m_count 177 << " | "; 178 out << "standard deviation: " << getStandardDeviation() << " |"; 179 } 180 for (int i = 0; i < m_bins && i <= m_largest_bin; i++) { 181 if (multiplier == 1.0) { 182 out << " " << m_data[i]; 183 } else { 184 out << " " << double(m_data[i]) * multiplier; 185 } 186 } 187 out << " ]"; |
188} 189 |
190bool 191node_less_then_eq(const Histogram* n1, const Histogram* n2) |
192{ |
193 return (n1->size() > n2->size()); |
194} |