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+
+/*
+ * Copyright (c) 1999-2008 Mark D. Hill and David A. Wood
+ * All rights reserved.
+ *
+ * Redistribution and use in source and binary forms, with or without
+ * modification, are permitted provided that the following conditions are
+ * met: redistributions of source code must retain the above copyright
+ * notice, this list of conditions and the following disclaimer;
+ * redistributions in binary form must reproduce the above copyright
+ * notice, this list of conditions and the following disclaimer in the
+ * documentation and/or other materials provided with the distribution;
+ * neither the name of the copyright holders nor the names of its
+ * contributors may be used to endorse or promote products derived from
+ * this software without specific prior written permission.
+ *
+ * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+ * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+ * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+ * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+ * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+ * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+ * LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+ * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+ * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+ * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+ */
+
+/*
+ * $Id$
+ *
+ */
+
+#include "Histogram.hh"
+
+Histogram::Histogram(int binsize, int bins)
+{
+ m_binsize = binsize;
+ m_bins = bins;
+ clear();
+}
+
+Histogram::~Histogram()
+{
+}
+
+void Histogram::clear(int binsize, int bins)
+{
+ m_binsize = binsize;
+ clear(bins);
+}
+
+void Histogram::clear(int bins)
+{
+ m_bins = bins;
+ m_largest_bin = 0;
+ m_max = 0;
+ m_data.setSize(m_bins);
+ for (int i = 0; i < m_bins; i++) {
+ m_data[i] = 0;
+ }
+ m_count = 0;
+ m_max = 0;
+
+ m_sumSamples = 0;
+ m_sumSquaredSamples = 0;
+}
+
+
+void Histogram::add(int64 value)
+{
+ assert(value >= 0);
+ m_max = max(m_max, value);
+ m_count++;
+
+ m_sumSamples += value;
+ m_sumSquaredSamples += (value*value);
+
+ int index;
+ if (m_binsize == -1) {
+ // This is a log base 2 histogram
+ if (value == 0) {
+ index = 0;
+ } else {
+ index = int(log(double(value))/log(2.0))+1;
+ if (index >= m_data.size()) {
+ index = m_data.size()-1;
+ }
+ }
+ } else {
+ // This is a linear histogram
+ while (m_max >= (m_bins * m_binsize)) {
+ for (int i = 0; i < m_bins/2; i++) {
+ m_data[i] = m_data[i*2] + m_data[i*2 + 1];
+ }
+ for (int i = m_bins/2; i < m_bins; i++) {
+ m_data[i] = 0;
+ }
+ m_binsize *= 2;
+ }
+ index = value/m_binsize;
+ }
+ assert(index >= 0);
+ m_data[index]++;
+ m_largest_bin = max(m_largest_bin, index);
+}
+
+void Histogram::add(const Histogram& hist)
+{
+ assert(hist.getBins() == m_bins);
+ assert(hist.getBinSize() == -1); // assume log histogram
+ assert(m_binsize == -1);
+
+ for (int j = 0; j < hist.getData(0); j++) {
+ add(0);
+ }
+
+ for (int i = 1; i < m_bins; i++) {
+ for (int j = 0; j < hist.getData(i); j++) {
+ add(1<<(i-1)); // account for the + 1 index
+ }
+ }
+
+}
+
+// Computation of standard deviation of samples a1, a2, ... aN
+// variance = [SUM {ai^2} - (SUM {ai})^2/N]/(N-1)
+// std deviation equals square root of variance
+double Histogram::getStandardDeviation() const
+{
+ double variance;
+ if(m_count > 1){
+ variance = (double)(m_sumSquaredSamples - m_sumSamples*m_sumSamples/m_count)/(m_count - 1);
+ } else {
+ return 0;
+ }
+ return sqrt(variance);
+}
+
+void Histogram::print(ostream& out) const
+{
+ printWithMultiplier(out, 1.0);
+}
+
+void Histogram::printPercent(ostream& out) const
+{
+ if (m_count == 0) {
+ printWithMultiplier(out, 0.0);
+ } else {
+ printWithMultiplier(out, 100.0/double(m_count));
+ }
+}
+
+void Histogram::printWithMultiplier(ostream& out, double multiplier) const
+{
+ if (m_binsize == -1) {
+ out << "[binsize: log2 ";
+ } else {
+ out << "[binsize: " << m_binsize << " ";
+ }
+ out << "max: " << m_max << " ";
+ out << "count: " << m_count << " ";
+ // out << "total: " << m_sumSamples << " ";
+ if (m_count == 0) {
+ out << "average: NaN |";
+ out << "standard deviation: NaN |";
+ } else {
+ out << "average: " << setw(5) << ((double) m_sumSamples)/m_count << " | ";
+ out << "standard deviation: " << getStandardDeviation() << " |";
+ }
+ for (int i = 0; i < m_bins && i <= m_largest_bin; i++) {
+ if (multiplier == 1.0) {
+ out << " " << m_data[i];
+ } else {
+ out << " " << double(m_data[i]) * multiplier;
+ }
+ }
+ out << " ]";
+}
+
+bool node_less_then_eq(const Histogram* n1, const Histogram* n2)
+{
+ return (n1->size() > n2->size());
+}