Histogram.cc revision 7039 
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;
9 * redistributions in binary form must reproduce the above copyright
10 * notice, this list of conditions and the following disclaimer in the
11 * documentation and/or other materials provided with the distribution;
12 * neither the name of the copyright holders nor the names of its
13 * contributors may be used to endorse or promote products derived from
14 * this software without specific prior written permission.
15 *
16 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
17 * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
18 * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
19 * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
20 * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
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}
195