Stan Math Library
4.9.0
Automatic Differentiation
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inline |
Specialization for use when the first input is a (non-nested) std::vector and the second is a scalar.
Specialization for use when the one input is an `var_value<Eigen> type and the other is a scalar.
Specialization for use with one var_value<Eigen vector>
(row or column) and a one-dimensional std::vector of integer types.
Specialization for use with combinations of Eigen::Matrix
and var_value<Eigen::Matrix>
inputs.
Specialization for use when the first input is a scalar and the second is a nested std::vector.
Specialization for use when the first input is a nested std::vector and the second is a scalar.
Specialization for use when the first input is a scalar and the second is a (non-nested) std::vector.
The std::vector input is mapped to an Eigen column vector and then the result is evaluated directly into the returned std::vector (via Eigen::Map).
The returned scalar type is deduced to allow for cases where the input and return scalar types differ (e.g., functions implicitly promoting integers).
T1 | Type of std::vector to which functor is applied. |
T2 | Type of scalar to which functor is applied. |
F | Type of functor to apply. |
x | std::vector input to which operation is applied. |
y | Scalar input to which operation is applied. |
f | functor to apply to std::vector and scalar inputs. |
The std::vector input is mapped to an Eigen column vector and then the result is evaluated directly into the returned std::vector (via Eigen::Map).
The returned scalar type is deduced to allow for cases where the input and return scalar types differ (e.g., functions implicitly promoting integers).
T1 | Type of scalar to which functor is applied. |
T2 | Type of std::vector to which functor is applied. |
F | Type of functor to apply. |
x | Scalar input to which operation is applied. |
y | std::vector input to which operation is applied. |
f | functor to apply to std::vector and scalar inputs. |
The returned scalar type is deduced to allow for cases where the input and return scalar types differ (e.g., functions implicitly promoting integers).
T1 | Type of std::vector to which functor is applied. |
T2 | Type of scalar to which functor is applied. |
F | Type of functor to apply. |
x | std::vector input to which operation is applied. |
y | Scalar input to which operation is applied. |
f | functor to apply to inputs. |
The returned scalar type is deduced to allow for cases where the input and return scalar types differ (e.g., functions implicitly promoting integers).
T1 | Type of scalar to which functor is applied. |
T2 | Type of std::vector to which functor is applied. |
F | Type of functor to apply. |
x | Scalar input to which operation is applied. |
y | std::vector input to which operation is applied. |
f | functor to apply to inputs. |
Eigen's binaryExpr framework is used for more efficient indexing of both row- and column-major inputs without separate loops.
T1 | Type of first argument to which functor is applied. |
T2 | Type of second argument to which functor is applied. |
F | Type of functor to apply. |
x | First Matrix input to which operation is applied. |
y | Second Matrix input to which operation is applied. |
f | functor to apply to Matrix inputs. |
var_value<Matrix>
with result of applying functor to inputs.T1 | Type of first argument to which functor is applied. |
T2 | Type of second argument to which functor is applied. |
F | Type of functor to apply. |
x | Matrix input to which operation is applied. |
y | Integer std::vector input to which operation is applied. |
f | functor to apply to inputs. |
T1 | Type of either var_value<Matrix> or scalar object to which functor is applied. |
T2 | Type of either var_value<Matrix> or scalar object to which functor is applied. |
F | Type of functor to apply. |
x | Matrix or Scalar input to which operation is applied. |
x | Matrix or Scalar input to which operation is applied. |
f | functor to apply to var matrix and scalar inputs. |
Definition at line 288 of file apply_scalar_binary.hpp.