From b080ec4d2de5403da0b8a09b0e8cd67b5c079184 Mon Sep 17 00:00:00 2001
From: Dmitry Yurov <d.yurov@fz-juelich.de>
Date: Tue, 26 Mar 2019 16:27:15 +0100
Subject: [PATCH] Make all the necessary constructors of ranged distributions
visible from python
---
Core/Parametrization/RangedDistributions.cpp | 70 ++++++++++++++++++++
Core/Parametrization/RangedDistributions.h | 52 +++++++++++++--
2 files changed, 116 insertions(+), 6 deletions(-)
diff --git a/Core/Parametrization/RangedDistributions.cpp b/Core/Parametrization/RangedDistributions.cpp
index 3f1ae7cd18a..5da29632430 100644
--- a/Core/Parametrization/RangedDistributions.cpp
+++ b/Core/Parametrization/RangedDistributions.cpp
@@ -114,6 +114,20 @@ void RangedDistribution::checkInitialization()
"shall not exceed the upper one.");
}
+RangedDistributionGate::RangedDistributionGate() : RangedDistribution() {}
+
+RangedDistributionGate::RangedDistributionGate(size_t n_samples, double sigma_factor,
+ const RealLimits& limits)
+ : RangedDistribution(n_samples, sigma_factor, limits)
+{
+}
+
+RangedDistributionGate::RangedDistributionGate(size_t n_samples, double sigma_factor, double min,
+ double max)
+ : RangedDistribution(n_samples, sigma_factor, min, max)
+{
+}
+
RangedDistributionGate* RangedDistributionGate::clone() const
{
return makeCopy(*this).release();
@@ -132,6 +146,20 @@ RangedDistributionGate::distribution_impl(double mean, double stddev) const
return std::make_unique<DistributionGate>(x_min, x_max);
}
+RangedDistributionLorentz::RangedDistributionLorentz() : RangedDistribution() {}
+
+RangedDistributionLorentz::RangedDistributionLorentz(size_t n_samples, double hwhm_factor,
+ const RealLimits& limits)
+ : RangedDistribution(n_samples, hwhm_factor, limits)
+{
+}
+
+RangedDistributionLorentz::RangedDistributionLorentz(size_t n_samples, double hwhm_factor,
+ double min, double max)
+ : RangedDistribution(n_samples, hwhm_factor, min, max)
+{
+}
+
RangedDistributionLorentz* RangedDistributionLorentz::clone() const
{
return makeCopy(*this).release();
@@ -148,6 +176,20 @@ RangedDistributionLorentz::distribution_impl(double median, double hwhm) const
return std::make_unique<DistributionLorentz>(median, hwhm);
}
+RangedDistributionGaussian::RangedDistributionGaussian() : RangedDistribution() {}
+
+RangedDistributionGaussian::RangedDistributionGaussian(size_t n_samples, double sigma_factor,
+ const RealLimits& limits)
+ : RangedDistribution(n_samples, sigma_factor, limits)
+{
+}
+
+RangedDistributionGaussian::RangedDistributionGaussian(size_t n_samples, double sigma_factor,
+ double min, double max)
+ : RangedDistribution(n_samples, sigma_factor, min, max)
+{
+}
+
RangedDistributionGaussian* RangedDistributionGaussian::clone() const
{
return makeCopy(*this).release();
@@ -164,6 +206,20 @@ RangedDistributionGaussian::distribution_impl(double mean, double stddev) const
return std::make_unique<DistributionGaussian>(mean, stddev);
}
+RangedDistributionLogNormal::RangedDistributionLogNormal() : RangedDistribution() {}
+
+RangedDistributionLogNormal::RangedDistributionLogNormal(size_t n_samples, double sigma_factor,
+ const RealLimits& limits)
+ : RangedDistribution(n_samples, sigma_factor, limits)
+{
+}
+
+RangedDistributionLogNormal::RangedDistributionLogNormal(size_t n_samples, double sigma_factor,
+ double min, double max)
+ : RangedDistribution(n_samples, sigma_factor, min, max)
+{
+}
+
RangedDistributionLogNormal* RangedDistributionLogNormal::clone() const
{
return makeCopy(*this).release();
@@ -187,6 +243,20 @@ RangedDistributionLogNormal::distribution_impl(double mean, double stddev) const
return std::make_unique<DistributionLogNormal>(median, scale);
}
+RangedDistributionCosine::RangedDistributionCosine() : RangedDistribution() {}
+
+RangedDistributionCosine::RangedDistributionCosine(size_t n_samples, double sigma_factor,
+ const RealLimits& limits)
+ : RangedDistribution(n_samples, sigma_factor, limits)
+{
+}
+
+RangedDistributionCosine::RangedDistributionCosine(size_t n_samples, double sigma_factor,
+ double min, double max)
+ : RangedDistribution(n_samples, sigma_factor, min, max)
+{
+}
+
RangedDistributionCosine* RangedDistributionCosine::clone() const
{
return makeCopy(*this).release();
diff --git a/Core/Parametrization/RangedDistributions.h b/Core/Parametrization/RangedDistributions.h
index 5969e408a6b..c67249ad529 100644
--- a/Core/Parametrization/RangedDistributions.h
+++ b/Core/Parametrization/RangedDistributions.h
@@ -41,7 +41,7 @@ public:
const RealLimits& limits = RealLimits::limitless());
//! Initializes Ranged distribution with given number of samples, sigma factor
//! (range in standard deviations to take into account during sample generation)
- //! and limits (either RealLimits object or just min and max values for such an object).
+ //! and limits (either RealLimits object or just min and max limits).
//! By default _n_samples_ = 5, _sigma_factor_ = 2.0, while the limits are (-inf, +inf).
RangedDistribution(size_t n_samples, double sigma_factor, double min, double max);
RangedDistribution* clone() const override = 0;
@@ -97,7 +97,15 @@ private:
class BA_CORE_API_ RangedDistributionGate : public RangedDistribution
{
public:
- using RangedDistribution::RangedDistribution;
+ RangedDistributionGate();
+ RangedDistributionGate(size_t n_samples, double sigma_factor,
+ const RealLimits& limits = RealLimits::limitless());
+ //! Initializes Ranged distribution with given number of samples, sigma factor
+ //! (range in standard deviations to take into account during sample generation)
+ //! and limits (either RealLimits object or just min and max limits).
+ //! By default _n_samples_ = 5, _sigma_factor_ = 2.0, while the limits are (-inf, +inf).
+ RangedDistributionGate(size_t n_samples, double sigma_factor, double min, double max);
+
RangedDistributionGate* clone() const override;
~RangedDistributionGate() override = default;
@@ -115,7 +123,15 @@ protected:
class BA_CORE_API_ RangedDistributionLorentz : public RangedDistribution
{
public:
- using RangedDistribution::RangedDistribution;
+ RangedDistributionLorentz();
+ RangedDistributionLorentz(size_t n_samples, double hwhm_factor,
+ const RealLimits& limits = RealLimits::limitless());
+ //! Initializes Ranged distribution with given number of samples, sigma factor
+ //! (range in standard deviations to take into account during sample generation)
+ //! and limits (either RealLimits object or just min and max limits).
+ //! By default _n_samples_ = 5, _hwhm_factor_ = 2.0, while the limits are (-inf, +inf).
+ RangedDistributionLorentz(size_t n_samples, double hwhm_factor, double min, double max);
+
RangedDistributionLorentz* clone() const override;
~RangedDistributionLorentz() override = default;
@@ -133,7 +149,15 @@ protected:
class BA_CORE_API_ RangedDistributionGaussian: public RangedDistribution
{
public:
- using RangedDistribution::RangedDistribution;
+ RangedDistributionGaussian();
+ RangedDistributionGaussian(size_t n_samples, double sigma_factor,
+ const RealLimits& limits = RealLimits::limitless());
+ //! Initializes Ranged distribution with given number of samples, sigma factor
+ //! (range in standard deviations to take into account during sample generation)
+ //! and limits (either RealLimits object or just min and max limits).
+ //! By default _n_samples_ = 5, _sigma_factor_ = 2.0, while the limits are (-inf, +inf).
+ RangedDistributionGaussian(size_t n_samples, double sigma_factor, double min, double max);
+
RangedDistributionGaussian* clone() const override;
~RangedDistributionGaussian() override = default;
@@ -151,7 +175,15 @@ protected:
class BA_CORE_API_ RangedDistributionLogNormal: public RangedDistribution
{
public:
- using RangedDistribution::RangedDistribution;
+ RangedDistributionLogNormal();
+ RangedDistributionLogNormal(size_t n_samples, double sigma_factor,
+ const RealLimits& limits = RealLimits::limitless());
+ //! Initializes Ranged distribution with given number of samples, sigma factor
+ //! (range in standard deviations to take into account during sample generation)
+ //! and limits (either RealLimits object or just min and max limits).
+ //! By default _n_samples_ = 5, _sigma_factor_ = 2.0, while the limits are (-inf, +inf).
+ RangedDistributionLogNormal(size_t n_samples, double sigma_factor, double min, double max);
+
RangedDistributionLogNormal* clone() const override;
~RangedDistributionLogNormal() override = default;
@@ -169,7 +201,15 @@ protected:
class BA_CORE_API_ RangedDistributionCosine: public RangedDistribution
{
public:
- using RangedDistribution::RangedDistribution;
+ RangedDistributionCosine();
+ RangedDistributionCosine(size_t n_samples, double sigma_factor,
+ const RealLimits& limits = RealLimits::limitless());
+ //! Initializes Ranged distribution with given number of samples, sigma factor
+ //! (range in standard deviations to take into account during sample generation)
+ //! and limits (either RealLimits object or just min and max limits).
+ //! By default _n_samples_ = 5, _sigma_factor_ = 2.0, while the limits are (-inf, +inf).
+ RangedDistributionCosine(size_t n_samples, double sigma_factor, double min, double max);
+
RangedDistributionCosine* clone() const override;
~RangedDistributionCosine() override = default;
--
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