pRC
multi-purpose Tensor Train library for C++
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Namespaces | Functions
is_approx.hpp File Reference
#include <prc/core/basic/functions/min.hpp>
#include <prc/core/functors/absolute_error.hpp>
#include <prc/core/functors/norm.hpp>
#include <prc/core/value/functions/absolute_error.hpp>
#include <prc/core/value/functions/norm.hpp>
#include <prc/core/value/limits.hpp>

Go to the source code of this file.

Namespaces

namespace  pRC
 

Functions

template<class XA , class XB , class RA = RemoveReference<XA>, class RB = RemoveReference<XB>, class TT = Common<typename RA::Value, typename RB::Value>, class T = Common<typename RA::Value, typename RB::Value, TT>, If< IsValue< TT > > = 0, If< IsInvocable< AbsoluteError, XA, XB > > = 0, If< IsInvocable< Norm<>, XA > > = 0, If< IsInvocable< Norm<>, XB > > = 0, If< IsConstructible< T, ResultOf< AbsoluteError, XA, XB > > > = 0, If< IsConstructible< T, ResultOf< Norm<>, XA > > > = 0, If< IsConstructible< T, ResultOf< Norm<>, XB > > > = 0>
static constexpr auto pRC::isApprox (XA &&a, XB &&b, TT const &tolerance=NumericLimits< TT >::tolerance())
 Checks if two pRC objects agree up to a given tolerance.