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open_iA 2023.02
A tool for the visual analysis and processing of volumetric datasets, with a focus on industrial computed tomography.
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Functions | |
| double | covariance (FuncType const &func1, FuncType const &func2, double mean1, double mean2, bool correctDF) |
| Compute covariance between two functions. | |
| std::vector< double > | derivative (std::vector< double > const &func) |
| Calculate first derivative of a given function. | |
| double | gaussian (double x, double sigma) |
| Compute Gaussian function for the given value x and parameter sigma (mean = 0). | |
| std::vector< double > | gaussianKernel (double kernelSigma, size_t kernelSteps) |
| Compute a gaussian kernel with the given sigma (mean = 0). | |
| std::vector< double > | gaussianSmoothing (std::vector< double > const &data, double kernelSigma, int kernelSteps) |
| Convolutes the given function with a Gaussian kernel with the given sigma and steps. | |
| FuncType | getNormedRanks (FuncType const &func) |
| Compute ranks for a given list of values. | |
| double | mean (FuncType const &func) |
| Compute the mean of a function. | |
| double | pearsonsCorrelationCoefficient (FuncType const &func1, FuncType const &func2) |
| Calculate the Pearson's correlation coefficient between two functions. | |
| double | spearmansCorrelationCoefficient (FuncType const &func1, FuncType const &func2) |
| Calculate the Spearman's correlation coefficient between two functions. | |
| double | standardDeviation (FuncType const &func, double meanVal, bool correctDF) |
| Compute the standard deviation of a function. mean can be given (to improve speed). | |
| double | variance (FuncType const &func, double meanVal, bool correctDF) |
| Compute the variation of a function. If known, mean can be given (to improve speed). | |
| double covariance | ( | FuncType const & | func1, |
| FuncType const & | func2, | ||
| double | mean1, | ||
| double | mean2, | ||
| bool | correctDF | ||
| ) |
Compute covariance between two functions.
| std::vector< double > derivative | ( | std::vector< double > const & | func | ) |
Calculate first derivative of a given function.
| double gaussian | ( | double | x, |
| double | sigma | ||
| ) |
Compute Gaussian function for the given value x and parameter sigma (mean = 0).
| std::vector< double > gaussianKernel | ( | double | kernelSigma, |
| size_t | kernelSteps | ||
| ) |
Compute a gaussian kernel with the given sigma (mean = 0).
| std::vector< double > gaussianSmoothing | ( | FuncType const & | data, |
| double | kernelSigma, | ||
| int | kernelSteps | ||
| ) |
Convolutes the given function with a Gaussian kernel with the given sigma and steps.
TODO: number of steps could be calculated from sigma (cut off kernel when factor gets very small)
| double mean | ( | FuncType const & | func | ) |
Compute the mean of a function.
Calculate the Pearson's correlation coefficient between two functions.
Calculate the Spearman's correlation coefficient between two functions.
| double standardDeviation | ( | FuncType const & | func, |
| double | meanVal, | ||
| bool | correctDF | ||
| ) |
Compute the standard deviation of a function. mean can be given (to improve speed).
| double variance | ( | FuncType const & | func, |
| double | meanVal, | ||
| bool | correctDF | ||
| ) |
Compute the variation of a function. If known, mean can be given (to improve speed).