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diff --git a/src/tools/imagery/imagery_maxent/me.cpp b/src/tools/imagery/imagery_maxent/me.cpp
index c5da854..d3e9cff 100755
--- a/src/tools/imagery/imagery_maxent/me.cpp
+++ b/src/tools/imagery/imagery_maxent/me.cpp
@@ -21,7 +21,7 @@
#ifdef _SAGA_MSW
#define isinf(x) (!_finite(x))
#else
-#define isinf(x) (!finite(x))
+#define isinf(x) (!isfinite(x))
#endif
/** The input array contains a set of log probabilities lp1, lp2, lp3
@@ -47,7 +47,7 @@ double sumLogProb(vector<double>& logprobs)
/** returns log (e^logprob1 + e^logprob2). */
double sumLogProb(double logprob1, double logprob2)
{
- if (isinf(logprob1) && isinf(logprob2))
+ if (isinf(logprob1) && isinf(logprob2))
return logprob1; // both prob1 and prob2 are 0, return log 0.
if (logprob1>logprob2)
return logprob1+log(1+exp(logprob2-logprob1));
@@ -70,8 +70,8 @@ void MaxEntModel::print(ostream& ostrm, MaxEntTrainer& trainer)
for (FtMap::iterator it = _index.begin(); it!=_index.end(); it++) {
unsigned long i = it->second;
for (unsigned long c = 0; c<_classes; c++) {
- ostrm << "lambda(" << trainer.className(c) << ", "
- << trainer.getStr(it->first) << ")="
+ ostrm << "lambda(" << trainer.className(c) << ", "
+ << trainer.getStr(it->first) << ")="
<< _lambda[i+c] << endl;
}
}
@@ -86,7 +86,7 @@ int MaxEntModel::getProbs(MaxEntEvent& event, vector<double>& probs)
double s = 0;
for (unsigned int f = 0; f<event.size(); f++) {
FtMap::iterator it = _index.find(event[f]);
- if (it!=_index.end())
+ if (it!=_index.end())
s += _lambda[it->second+c];
}
probs[c] = s;
@@ -142,10 +142,10 @@ double MaxEntModel::getObsCounts(EventSet& events, vector<double>& obsCounts)
double ftSum = 0;
for (unsigned long j=0; j<e.size(); j++) {
FtMap::iterator it = _index.find(e[j]);
- if (it!=_index.end())
+ if (it!=_index.end())
obsCounts[it->second+c] += count;
else { // new feature, need to expand obsCounts and _lambda
- for (unsigned int k = 0; k<_classes; k++)
+ for (unsigned int k = 0; k<_classes; k++)
obsCounts.push_back(0);
obsCounts[_lambda.size()+c] += count;
addFeature(e[j]);
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