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@@ -568,7 +568,7 @@ size_t Curve :: EstimateSampleCount(float a, float b) const
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}
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// ------------------------------------------------------------------------------------------------
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-float RecursiveSearch(const Curve* cv, const aiVector3D& val, float a, float b, unsigned int samples, float treshold, unsigned int recurse = 0, unsigned int max_recurse = 15)
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+float RecursiveSearch(const Curve* cv, const aiVector3D& val, float a, float b, unsigned int samples, float threshold, unsigned int recurse = 0, unsigned int max_recurse = 15)
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{
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ai_assert(samples>1);
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@@ -592,7 +592,7 @@ float RecursiveSearch(const Curve* cv, const aiVector3D& val, float a, float b,
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}
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ai_assert(min_diff[0] != inf && min_diff[1] != inf);
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- if ( fabs(a-min_point[0]) < treshold || recurse >= max_recurse) {
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+ if ( fabs(a-min_point[0]) < threshold || recurse >= max_recurse) {
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return min_point[0];
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}
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@@ -608,7 +608,7 @@ float RecursiveSearch(const Curve* cv, const aiVector3D& val, float a, float b,
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}
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}
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- return RecursiveSearch(cv,val,min_point[0],min_point[1],samples,treshold,recurse+1,max_recurse);
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+ return RecursiveSearch(cv,val,min_point[0],min_point[1],samples,threshold,recurse+1,max_recurse);
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}
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// ------------------------------------------------------------------------------------------------
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@@ -618,12 +618,12 @@ bool Curve :: ReverseEval(const aiVector3D& val, float& paramOut) const
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// in all possible cases, but it will always return at least some value so this function
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// will never fail in the default implementation.
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- // XXX derive treshold from curve topology
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- const float treshold = 1e-4f;
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+ // XXX derive threshold from curve topology
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+ const float threshold = 1e-4f;
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const unsigned int samples = 16;
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const ParamRange& range = GetParametricRange();
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- paramOut = RecursiveSearch(this,val,range.first,range.second,samples,treshold);
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+ paramOut = RecursiveSearch(this,val,range.first,range.second,samples,threshold);
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return true;
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}
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