[Rsiena-commits] r248 - in pkg/RSiena: . man src/model/effects src/model/variables
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Thu Nov 28 15:01:32 CET 2013
Author: ortmann
Date: 2013-11-28 15:01:32 +0100 (Thu, 28 Nov 2013)
New Revision: 248
Modified:
pkg/RSiena/
pkg/RSiena/DESCRIPTION
pkg/RSiena/changeLog
pkg/RSiena/man/RSiena-package.Rd
pkg/RSiena/src/model/effects/AltersCovariateAvSimEffect.cpp
pkg/RSiena/src/model/effects/AltersCovariateTotSimEffect.cpp
pkg/RSiena/src/model/variables/DiffusionEffectValueTable.cpp
pkg/RSiena/src/model/variables/EffectValueTable.cpp
Log:
update:
- version number
bug fix:
- ambiguous call of abs in AlterCovariateAv/TotSimEffect by
replacing cmath by cstdlib
- problem with using namespace std in DiffusionEffectValueTable
and EffectValueTable
Property changes on: pkg/RSiena
___________________________________________________________________
Added: svn:ignore
+ .cproject
.project
Modified: pkg/RSiena/DESCRIPTION
===================================================================
--- pkg/RSiena/DESCRIPTION 2013-11-28 13:54:20 UTC (rev 247)
+++ pkg/RSiena/DESCRIPTION 2013-11-28 14:01:32 UTC (rev 248)
@@ -1,7 +1,7 @@
Package: RSiena
Type: Package
Title: Siena - Simulation Investigation for Empirical Network Analysis
-Version: 1.1-246
+Version: 1.1-247
Date: 2013-10-31
Author: Ruth Ripley, Krists Boitmanis, Tom A.B. Snijders
Depends: R (>= 2.15.0)
Modified: pkg/RSiena/changeLog
===================================================================
--- pkg/RSiena/changeLog 2013-11-28 13:54:20 UTC (rev 247)
+++ pkg/RSiena/changeLog 2013-11-28 14:01:32 UTC (rev 248)
@@ -1,3 +1,12 @@
+2013-11-28 R-Forge Revision 247
+Changes in RSiena and RSienaTest:
+ * Fix problem with std::map<int,int>::const_iterator constructor
+ call in IncidentTieIterator.cpp
+ * Fix ambiguous call of abs in AlterCovariateAv/TotSimEffect by
+ replacing cmath by cstdlib
+ * Fix problem with using namespace std in DiffusionEffectValueTable
+ and EffectValueTable
+
2013-10-31 R-Forge Revision 246
Changes in RSiena and RSienaTest:
* New behavior objective function effects avSimAltX, totSimAltX and
Modified: pkg/RSiena/man/RSiena-package.Rd
===================================================================
--- pkg/RSiena/man/RSiena-package.Rd 2013-11-28 13:54:20 UTC (rev 247)
+++ pkg/RSiena/man/RSiena-package.Rd 2013-11-28 14:01:32 UTC (rev 248)
@@ -43,7 +43,7 @@
\tabular{ll}{
Package: \tab RSiena\cr
Type: \tab Package\cr
-Version: \tab 1.1-246\cr
+Version: \tab 1.1-247\cr
Date: \tab 2013-10-31\cr
Depends: \tab R (>= 2.15.0)\cr
Imports: \tab Matrix\cr
Modified: pkg/RSiena/src/model/effects/AltersCovariateAvSimEffect.cpp
===================================================================
--- pkg/RSiena/src/model/effects/AltersCovariateAvSimEffect.cpp 2013-11-28 13:54:20 UTC (rev 247)
+++ pkg/RSiena/src/model/effects/AltersCovariateAvSimEffect.cpp 2013-11-28 14:01:32 UTC (rev 248)
@@ -10,7 +10,7 @@
*****************************************************************************/
#include <stdexcept>
-#include <cmath>
+#include <cstdlib>
#include "AltersCovariateAvSimEffect.h"
#include "data/Data.h"
@@ -23,55 +23,48 @@
#include "model/EffectInfo.h"
#include "model/variables/BehaviorVariable.h"
-namespace siena
-{
+namespace siena {
/**
* Constructor.
*/
AltersCovariateAvSimEffect::AltersCovariateAvSimEffect(
- const EffectInfo * pEffectInfo) :
- CovariateAndNetworkBehaviorEffect(pEffectInfo)
-{
+ const EffectInfo * pEffectInfo) :
+ CovariateAndNetworkBehaviorEffect(pEffectInfo) {
}
-
-
/**
* Calculates the change in the statistic corresponding to this effect if
* the given actor would change his behavior by the given amount.
*/
double AltersCovariateAvSimEffect::calculateChangeContribution(int actor,
- int difference)
-{
+ int difference) {
double contribution = 0;
const Network * pNetwork = this->pNetwork();
-
+
if (pNetwork->outDegree(actor) > 0) // otherwise, nothing to calculate...
- {
+ {
- int oldValue = this->value(actor); // ego's behavior value before moving on behavior scale
- int newValue = oldValue + difference; // ego's behavior value after moving on behavior scale
+ int oldValue = this->value(actor); // ego's behavior value before moving on behavior scale
+ int newValue = oldValue + difference; // ego's behavior value after moving on behavior scale
double totalChange = 0; // will keep track of changes
for (IncidentTieIterator iter = pNetwork->outTies(actor); // loops over outgoing ties of ego
- iter.valid();
- iter.next())
- {
+ iter.valid(); iter.next()) {
int j = iter.actor(); // identifies alter
- int alterValue = this->value(j); // identifies behavior value of alter
- int change =
- abs(oldValue - alterValue) - abs(newValue - alterValue);
- // calculates impact of ego's movement on absolute difference to alter
+ int alterValue = this->value(j); // identifies behavior value of alter
+ int change = std::abs(oldValue - alterValue)
+ - std::abs(newValue - alterValue);
+ // calculates impact of ego's movement on absolute difference to alter
totalChange += change * this->covariateValue(j); // weighting change statistic acc. to covariate value of alter
}
contribution = totalChange / this->range(); // standardize by behavior range for SIMILARITY function
- contribution /= pNetwork->outDegree(actor); // divide by outdegree to get AVERAGE similarity change statistic
+ contribution /= pNetwork->outDegree(actor); // divide by outdegree to get AVERAGE similarity change statistic
- }
+ }
return contribution;
@@ -81,80 +74,71 @@
* Returns the statistic corresponding to the given ego with respect to the
* given values of the behavior variable.
*/
-double AltersCovariateAvSimEffect::egoStatistic(int ego, double * currentValues)
-{
+double AltersCovariateAvSimEffect::egoStatistic(int ego,
+ double * currentValues) {
const Network * pNetwork = this->pNetwork();
double statistic = 0;
int neighborCount = 0;
- for (IncidentTieIterator iter = pNetwork->outTies(ego);
- iter.valid();
- iter.next())
- {
+ for (IncidentTieIterator iter = pNetwork->outTies(ego); iter.valid();
+ iter.next()) {
int j = iter.actor();
- if (!this->missing(this->period(), j) &&
- !this->missing(this->period() + 1, j) &&
- !this->missingCovariate(j,this->period()))
- {
- double tieStatistic =
- this->similarity(currentValues[ego], currentValues[j]);
+ if (!this->missing(this->period(), j)
+ && !this->missing(this->period() + 1, j)
+ && !this->missingCovariate(j, this->period())) {
+ double tieStatistic = this->similarity(currentValues[ego],
+ currentValues[j]);
statistic += tieStatistic * this->covariateValue(j);
neighborCount++;
}
}
- if (neighborCount > 0)
- {
+ if (neighborCount > 0) {
statistic /= neighborCount;
}
-
+
return statistic;
}
-
/**
* Returns the statistic corresponding to the given ego as part of
* the endowment function with respect to the initial values of a
* behavior variable and the current values.
*/
double AltersCovariateAvSimEffect::egoEndowmentStatistic(int ego,
- const int * difference,
- double * currentValues)
-{
+ const int * difference, double * currentValues) {
double statistic = 0;
const Network * pNetwork = this->pNetwork();
- if (difference[ego] > 0 && !this->missingDummy(ego) && (pNetwork->outDegree(ego) > 0)) // otherwise, nothing to calculate...
- {
+ if (difference[ego] > 0 && !this->missingDummy(ego)
+ && (pNetwork->outDegree(ego) > 0)) // otherwise, nothing to calculate...
+ {
- int oldValue = this->value(ego); // ego's behavior value before moving on behavior scale
- int newValue = oldValue + difference[ego]; // ego's behavior value after moving on behavior scale
+ int oldValue = this->value(ego); // ego's behavior value before moving on behavior scale
+ int newValue = oldValue + difference[ego]; // ego's behavior value after moving on behavior scale
double totalChange = 0; // will keep track of changes
for (IncidentTieIterator iter = pNetwork->outTies(ego); // loops over outgoing ties of ego
- iter.valid();
- iter.next())
- {
+ iter.valid(); iter.next()) {
int j = iter.actor(); // identifies alter
- int alterValue = this->value(j); // identifies behavior value of alter
- int change =
- abs(oldValue - alterValue) - abs(newValue - alterValue);
- // calculates impact of ego's movement on absolute difference to alter
+ int alterValue = this->value(j); // identifies behavior value of alter
+ int change = std::abs(oldValue - alterValue)
+ - std::abs(newValue - alterValue);
+ // calculates impact of ego's movement on absolute difference to alter
totalChange += change * this->covariateValue(j); // weighting change statistic acc. to covariate value of alter
}
statistic -= totalChange / this->range(); // standardize by behavior range for SIMILARITY function
- statistic /= pNetwork->outDegree(ego); // divide by outdegree to get AVERAGE similarity change statistic
-
+ statistic /= pNetwork->outDegree(ego); // divide by outdegree to get AVERAGE similarity change statistic
+
}
return statistic;
}
-
}
Modified: pkg/RSiena/src/model/effects/AltersCovariateTotSimEffect.cpp
===================================================================
--- pkg/RSiena/src/model/effects/AltersCovariateTotSimEffect.cpp 2013-11-28 13:54:20 UTC (rev 247)
+++ pkg/RSiena/src/model/effects/AltersCovariateTotSimEffect.cpp 2013-11-28 14:01:32 UTC (rev 248)
@@ -10,7 +10,7 @@
*****************************************************************************/
#include <stdexcept>
-#include <cmath>
+#include <cstdlib>
#include "AltersCovariateTotSimEffect.h"
#include "data/Data.h"
@@ -23,53 +23,46 @@
#include "model/EffectInfo.h"
#include "model/variables/BehaviorVariable.h"
-namespace siena
-{
+namespace siena {
/**
* Constructor.
*/
AltersCovariateTotSimEffect::AltersCovariateTotSimEffect(
- const EffectInfo * pEffectInfo) :
- CovariateAndNetworkBehaviorEffect(pEffectInfo)
-{
+ const EffectInfo * pEffectInfo) :
+ CovariateAndNetworkBehaviorEffect(pEffectInfo) {
}
-
-
/**
* Calculates the change in the statistic corresponding to this effect if
* the given actor would change his behavior by the given amount.
*/
double AltersCovariateTotSimEffect::calculateChangeContribution(int actor,
- int difference)
-{
+ int difference) {
double contribution = 0;
const Network * pNetwork = this->pNetwork();
-
+
if (pNetwork->outDegree(actor) > 0) // otherwise, nothing to calculate...
- {
+ {
- int oldValue = this->value(actor); // ego's behavior value before moving on behavior scale
- int newValue = oldValue + difference; // ego's behavior value after moving on behavior scale
+ int oldValue = this->value(actor); // ego's behavior value before moving on behavior scale
+ int newValue = oldValue + difference; // ego's behavior value after moving on behavior scale
double totalChange = 0; // will keep track of changes
for (IncidentTieIterator iter = pNetwork->outTies(actor); // loops over outgoing ties of ego
- iter.valid();
- iter.next())
- {
+ iter.valid(); iter.next()) {
int j = iter.actor(); // identifies alter
- int alterValue = this->value(j); // identifies behavior value of alter
- int change =
- abs(oldValue - alterValue) - abs(newValue - alterValue);
- // calculates impact of ego's movement on absolute difference to alter
+ int alterValue = this->value(j); // identifies behavior value of alter
+ int change = std::abs(oldValue - alterValue)
+ - std::abs(newValue - alterValue);
+ // calculates impact of ego's movement on absolute difference to alter
totalChange += change * this->covariateValue(j); // weighting change statistic acc. to covariate value of alter
}
contribution = ((double) totalChange) / this->range(); // standardize by behavior range for SIMILARITY function
- }
+ }
return contribution;
@@ -79,71 +72,63 @@
* Returns the statistic corresponding to the given ego with respect to the
* given values of the behavior variable.
*/
-double AltersCovariateTotSimEffect::egoStatistic(int ego, double * currentValues)
-{
+double AltersCovariateTotSimEffect::egoStatistic(int ego,
+ double * currentValues) {
const Network * pNetwork = this->pNetwork();
double statistic = 0;
-
- for (IncidentTieIterator iter = pNetwork->outTies(ego);
- iter.valid();
- iter.next())
- {
+
+ for (IncidentTieIterator iter = pNetwork->outTies(ego); iter.valid();
+ iter.next()) {
int j = iter.actor();
- if (!this->missing(this->period(), j) &&
- !this->missing(this->period() + 1, j) &&
- !this->missingCovariate(j,this->period()))
- {
- double tieStatistic =
- this->similarity(currentValues[ego], currentValues[j]);
+ if (!this->missing(this->period(), j)
+ && !this->missing(this->period() + 1, j)
+ && !this->missingCovariate(j, this->period())) {
+ double tieStatistic = this->similarity(currentValues[ego],
+ currentValues[j]);
statistic += tieStatistic * this->covariateValue(j);
}
}
-
+
return statistic;
}
-
/**
* Returns the statistic corresponding to the given ego as part of
* the endowment function with respect to the initial values of a
* behavior variable and the current values.
*/
double AltersCovariateTotSimEffect::egoEndowmentStatistic(int ego,
- const int * difference,
- double * currentValues)
-{
+ const int * difference, double * currentValues) {
double statistic = 0;
const Network * pNetwork = this->pNetwork();
- if (difference[ego] > 0 && !this->missingDummy(ego) && (pNetwork->outDegree(ego) > 0)) // otherwise, nothing to calculate...
- {
+ if (difference[ego] > 0 && !this->missingDummy(ego)
+ && (pNetwork->outDegree(ego) > 0)) // otherwise, nothing to calculate...
+ {
- int oldValue = this->value(ego); // ego's behavior value before moving on behavior scale
- int newValue = oldValue + difference[ego]; // ego's behavior value after moving on behavior scale
+ int oldValue = this->value(ego); // ego's behavior value before moving on behavior scale
+ int newValue = oldValue + difference[ego]; // ego's behavior value after moving on behavior scale
double totalChange = 0; // will keep track of changes
for (IncidentTieIterator iter = pNetwork->outTies(ego); // loops over outgoing ties of ego
- iter.valid();
- iter.next())
- {
+ iter.valid(); iter.next()) {
int j = iter.actor(); // identifies alter
- int alterValue = this->value(j); // identifies behavior value of alter
- int change =
- abs(oldValue - alterValue) - abs(newValue - alterValue);
- // calculates impact of ego's movement on absolute difference to alter
+ int alterValue = this->value(j); // identifies behavior value of alter
+ int change = std::abs(oldValue - alterValue)
+ - std::abs(newValue - alterValue);
+ // calculates impact of ego's movement on absolute difference to alter
totalChange += change * this->covariateValue(j); // weighting change statistic acc. to covariate value of alter
}
statistic -= totalChange / this->range(); // standardize by behavior range for SIMILARITY function
-
+
}
return statistic;
}
-
}
Modified: pkg/RSiena/src/model/variables/DiffusionEffectValueTable.cpp
===================================================================
--- pkg/RSiena/src/model/variables/DiffusionEffectValueTable.cpp 2013-11-28 13:54:20 UTC (rev 247)
+++ pkg/RSiena/src/model/variables/DiffusionEffectValueTable.cpp 2013-11-28 14:01:32 UTC (rev 248)
@@ -8,20 +8,17 @@
* Description: This file contains the implementation of the
* DiffusionEffectValueTable class.
*****************************************************************************/
-using namespace std;
#include <cmath>
#include "DiffusionEffectValueTable.h"
-namespace siena
-{
+namespace siena {
/**
* Creates a new look-up table for <i>n</i> actors.
*/
DiffusionEffectValueTable::DiffusionEffectValueTable(int numeratorRange,
- int denominatorRange)
-{
+ int denominatorRange) {
this->lvalues = new double[numeratorRange * denominatorRange];
this->lparameterValues = new double[numeratorRange * denominatorRange];
@@ -31,8 +28,7 @@
this->ldenominatorRange = denominatorRange;
this->lnumeratorRange = numeratorRange;
- for (int i = 0; i < numeratorRange * denominatorRange; i++)
- {
+ for (int i = 0; i < numeratorRange * denominatorRange; i++) {
// exp(0) = 1
this->lvalues[i] = 1;
@@ -43,8 +39,7 @@
/**
* Deallocates this look-up table.
*/
-DiffusionEffectValueTable::~DiffusionEffectValueTable()
-{
+DiffusionEffectValueTable::~DiffusionEffectValueTable() {
delete[] this->lvalues;
delete[] this->lparameterValues;
@@ -52,41 +47,34 @@
this->lparameterValues = 0;
}
-
/**
* Returns the current value of the effect parameter.
*/
-double DiffusionEffectValueTable::parameter() const
-{
+double DiffusionEffectValueTable::parameter() const {
return this->lparameter;
}
-
/**
* Stores the effect parameter.
*/
-void DiffusionEffectValueTable::parameter(double value)
-{
+void DiffusionEffectValueTable::parameter(double value) {
this->lparameter = value;
}
-
/**
* Returns the value of the effect.
*/
-double DiffusionEffectValueTable::value(int numerator, int denominator)
-{
- int arrayIndex = ((numerator - 1) * this->ldenominatorRange) +
- (denominator - 1);
+double DiffusionEffectValueTable::value(int numerator, int denominator) {
+ int arrayIndex = ((numerator - 1) * this->ldenominatorRange)
+ + (denominator - 1);
- if (this->lparameterValues[arrayIndex] != this->lparameter)
- {
+ if (this->lparameterValues[arrayIndex] != this->lparameter) {
// The value stored in the table was calculated for a different
// parameter, hence we must recalculate the value.
- this->lvalues[arrayIndex] = exp(this->lparameter *
- (double)numerator / (double)denominator);
+ this->lvalues[arrayIndex] = std::exp(
+ this->lparameter * (double) numerator / (double) denominator);
this->lparameterValues[arrayIndex] = this->lparameter;
}
Modified: pkg/RSiena/src/model/variables/EffectValueTable.cpp
===================================================================
--- pkg/RSiena/src/model/variables/EffectValueTable.cpp 2013-11-28 13:54:20 UTC (rev 247)
+++ pkg/RSiena/src/model/variables/EffectValueTable.cpp 2013-11-28 14:01:32 UTC (rev 248)
@@ -8,19 +8,16 @@
* Description: This file contains the implementation of the
* EffectValueTable class.
*****************************************************************************/
-using namespace std;
#include <cmath>
#include "EffectValueTable.h"
-namespace siena
-{
+namespace siena {
/**
* Creates a new look-up table for <i>n</i> actors and the given function.
*/
-EffectValueTable::EffectValueTable(int n, double (* pFunction)(int))
-{
+EffectValueTable::EffectValueTable(int n, double (*pFunction)(int)) {
this->lpFunction = pFunction;
this->lvalues = new double[n];
this->lparameterValues = new double[n];
@@ -29,8 +26,7 @@
this->lparameter = 0;
- for (int i = 0; i < n; i++)
- {
+ for (int i = 0; i < n; i++) {
// exp(0) = 1
this->lvalues[i] = 1;
@@ -38,12 +34,10 @@
}
}
-
/**
* Deallocates this look-up table.
*/
-EffectValueTable::~EffectValueTable()
-{
+EffectValueTable::~EffectValueTable() {
delete[] this->lvalues;
delete[] this->lparameterValues;
@@ -52,36 +46,29 @@
this->lpFunction = 0;
}
-
/**
* Returns the current value of the effect parameter.
*/
-double EffectValueTable::parameter() const
-{
+double EffectValueTable::parameter() const {
return this->lparameter;
}
-
/**
* Stores the effect parameter.
*/
-void EffectValueTable::parameter(double value)
-{
+void EffectValueTable::parameter(double value) {
this->lparameter = value;
}
-
/**
* Returns the value of the effect for the argument <i>i</i>.
*/
-double EffectValueTable::value(int i)
-{
- if (this->lparameterValues[i] != this->lparameter)
- {
+double EffectValueTable::value(int i) {
+ if (this->lparameterValues[i] != this->lparameter) {
// The value stored in the table was calculated for a different
// parameter, hence we must recalculate the value.
- this->lvalues[i] = exp(this->lparameter * this->lpFunction(i));
+ this->lvalues[i] = std::exp(this->lparameter * this->lpFunction(i));
this->lparameterValues[i] = this->lparameter;
}
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