mirror of
https://github.com/ilyakooo0/nixpkgs.git
synced 2024-11-11 15:27:20 +03:00
56 lines
2.1 KiB
Diff
56 lines
2.1 KiB
Diff
diff --git a/src/tools/imagery/imagery_maxent/me.cpp b/src/tools/imagery/imagery_maxent/me.cpp
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index c5da854..d3e9cff 100755
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--- a/src/tools/imagery/imagery_maxent/me.cpp
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+++ b/src/tools/imagery/imagery_maxent/me.cpp
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@@ -21,7 +21,7 @@
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#ifdef _SAGA_MSW
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#define isinf(x) (!_finite(x))
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#else
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-#define isinf(x) (!finite(x))
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+#define isinf(x) (!isfinite(x))
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#endif
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/** The input array contains a set of log probabilities lp1, lp2, lp3
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@@ -47,7 +47,7 @@ double sumLogProb(vector<double>& logprobs)
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/** returns log (e^logprob1 + e^logprob2). */
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double sumLogProb(double logprob1, double logprob2)
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{
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- if (isinf(logprob1) && isinf(logprob2))
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+ if (isinf(logprob1) && isinf(logprob2))
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return logprob1; // both prob1 and prob2 are 0, return log 0.
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if (logprob1>logprob2)
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return logprob1+log(1+exp(logprob2-logprob1));
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@@ -70,8 +70,8 @@ void MaxEntModel::print(ostream& ostrm, MaxEntTrainer& trainer)
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for (FtMap::iterator it = _index.begin(); it!=_index.end(); it++) {
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unsigned long i = it->second;
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for (unsigned long c = 0; c<_classes; c++) {
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- ostrm << "lambda(" << trainer.className(c) << ", "
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- << trainer.getStr(it->first) << ")="
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+ ostrm << "lambda(" << trainer.className(c) << ", "
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+ << trainer.getStr(it->first) << ")="
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<< _lambda[i+c] << endl;
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}
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}
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@@ -86,7 +86,7 @@ int MaxEntModel::getProbs(MaxEntEvent& event, vector<double>& probs)
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double s = 0;
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for (unsigned int f = 0; f<event.size(); f++) {
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FtMap::iterator it = _index.find(event[f]);
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- if (it!=_index.end())
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+ if (it!=_index.end())
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s += _lambda[it->second+c];
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}
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probs[c] = s;
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@@ -142,10 +142,10 @@ double MaxEntModel::getObsCounts(EventSet& events, vector<double>& obsCounts)
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double ftSum = 0;
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for (unsigned long j=0; j<e.size(); j++) {
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FtMap::iterator it = _index.find(e[j]);
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- if (it!=_index.end())
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+ if (it!=_index.end())
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obsCounts[it->second+c] += count;
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else { // new feature, need to expand obsCounts and _lambda
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- for (unsigned int k = 0; k<_classes; k++)
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+ for (unsigned int k = 0; k<_classes; k++)
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obsCounts.push_back(0);
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obsCounts[_lambda.size()+c] += count;
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addFeature(e[j]);
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