Histogram.cc revision 7002:48a19d52d939 
1
2/*
3 * Copyright (c) 1999-2008 Mark D. Hill and David A. Wood
4 * All rights reserved.
5 *
6 * Redistribution and use in source and binary forms, with or without
7 * modification, are permitted provided that the following conditions are
8 * met: redistributions of source code must retain the above copyright
9 * notice, this list of conditions and the following disclaimer;
10 * redistributions in binary form must reproduce the above copyright
11 * notice, this list of conditions and the following disclaimer in the
12 * documentation and/or other materials provided with the distribution;
13 * neither the name of the copyright holders nor the names of its
14 * contributors may be used to endorse or promote products derived from
15 * this software without specific prior written permission.
16 *
17 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
18 * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
19 * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
20 * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
21 * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
22 * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
23 * LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
24 * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
25 * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
26 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
27 * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
28 */
29
30/*
31 * $Id$
32 *
33 */
34
35#include <cmath>
36#include <iomanip>
37
38#include "mem/ruby/common/Histogram.hh"
39
40using namespace std;
41
42Histogram::Histogram(int binsize, int bins)
43{
44  m_binsize = binsize;
45  m_bins = bins;
46  clear();
47}
48
49Histogram::~Histogram()
50{
51}
52
53void Histogram::clear(int binsize, int bins)
54{
55  m_binsize = binsize;
56  clear(bins);
57}
58
59void Histogram::clear(int bins)
60{
61  m_bins = bins;
62  m_largest_bin = 0;
63  m_max = 0;
64  m_data.setSize(m_bins);
65  for (int i = 0; i < m_bins; i++) {
66    m_data[i] = 0;
67  }
68  m_count = 0;
69  m_max = 0;
70
71  m_sumSamples = 0;
72  m_sumSquaredSamples = 0;
73}
74
75
76void Histogram::add(int64 value)
77{
78  assert(value >= 0);
79  m_max = max(m_max, value);
80  m_count++;
81
82  m_sumSamples += value;
83  m_sumSquaredSamples += (value*value);
84
85  int index;
86  if (m_binsize == -1) {
87    // This is a log base 2 histogram
88    if (value == 0) {
89      index = 0;
90    } else {
91      index = int(log(double(value))/log(2.0))+1;
92      if (index >= m_data.size()) {
93        index = m_data.size()-1;
94      }
95    }
96  } else {
97    // This is a linear histogram
98    while (m_max >= (m_bins * m_binsize)) {
99      for (int i = 0; i < m_bins/2; i++) {
100        m_data[i] = m_data[i*2] + m_data[i*2 + 1];
101      }
102      for (int i = m_bins/2; i < m_bins; i++) {
103        m_data[i] = 0;
104      }
105      m_binsize *= 2;
106    }
107    index = value/m_binsize;
108  }
109  assert(index >= 0);
110  m_data[index]++;
111  m_largest_bin = max(m_largest_bin, index);
112}
113
114void Histogram::add(const Histogram& hist)
115{
116  assert(hist.getBins() == m_bins);
117  assert(hist.getBinSize() == -1);  // assume log histogram
118  assert(m_binsize == -1);
119
120  for (int j = 0; j < hist.getData(0); j++) {
121    add(0);
122  }
123
124  for (int i = 1; i < m_bins; i++) {
125    for (int j = 0; j < hist.getData(i); j++) {
126      add(1<<(i-1));  // account for the + 1 index
127    }
128  }
129
130}
131
132// Computation of standard deviation of samples a1, a2, ... aN
133// variance = [SUM {ai^2} - (SUM {ai})^2/N]/(N-1)
134// std deviation equals square root of variance
135double Histogram::getStandardDeviation() const
136{
137  double variance;
138  if(m_count > 1){
139    variance = (double)(m_sumSquaredSamples - m_sumSamples*m_sumSamples/m_count)/(m_count - 1);
140  } else {
141    return 0;
142  }
143  return sqrt(variance);
144}
145
146void Histogram::print(ostream& out) const
147{
148  printWithMultiplier(out, 1.0);
149}
150
151void Histogram::printPercent(ostream& out) const
152{
153  if (m_count == 0) {
154    printWithMultiplier(out, 0.0);
155  } else {
156    printWithMultiplier(out, 100.0/double(m_count));
157  }
158}
159
160void Histogram::printWithMultiplier(ostream& out, double multiplier) const
161{
162  if (m_binsize == -1) {
163    out << "[binsize: log2 ";
164  } else {
165    out << "[binsize: " << m_binsize << " ";
166  }
167  out << "max: " << m_max << " ";
168  out << "count: " << m_count << " ";
169  //  out << "total: " <<  m_sumSamples << " ";
170  if (m_count == 0) {
171    out << "average: NaN |";
172    out << "standard deviation: NaN |";
173  } else {
174    out << "average: " << setw(5) << ((double) m_sumSamples)/m_count << " | ";
175    out << "standard deviation: " << getStandardDeviation() << " |";
176  }
177  for (int i = 0; i < m_bins && i <= m_largest_bin; i++) {
178    if (multiplier == 1.0) {
179      out << " " << m_data[i];
180    } else {
181      out << " " << double(m_data[i]) * multiplier;
182    }
183  }
184  out << " ]";
185}
186
187bool node_less_then_eq(const Histogram* n1, const Histogram* n2)
188{
189  return (n1->size() > n2->size());
190}
191