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Added toeplitz operator #683

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Jul 25, 2024
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Added toeplitz operator #683

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f996d12
Added toeplitz operator
cliffburdick Jul 24, 2024
8805c36
Update toeplitz.rst
cliffburdick Jul 25, 2024
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10 changes: 5 additions & 5 deletions docs_input/api/creation/tensors/make.rst
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Expand Up @@ -18,18 +18,18 @@ Return by Value
.. doxygenfunction:: make_tensor( TensorType &tensor, ShapeType &&shape, matxMemorySpace_t space = MATX_MANAGED_MEMORY, cudaStream_t stream = 0)
.. doxygenfunction:: make_tensor( TensorType &tensor, matxMemorySpace_t space = MATX_MANAGED_MEMORY, cudaStream_t stream = 0)
.. doxygenfunction:: make_tensor( T *data, const index_t (&shape)[RANK], bool owning = false)
.. doxygenfunction:: make_tensor( TensorType &tensor, typename TensorType::scalar_type *data, const index_t (&shape)[TensorType::Rank()], bool owning = false)
.. doxygenfunction:: make_tensor( TensorType &tensor, typename TensorType::value_type *data, const index_t (&shape)[TensorType::Rank()], bool owning = false)
.. doxygenfunction:: make_tensor( T *data, ShapeType &&shape, bool owning = false)
.. doxygenfunction:: make_tensor( TensorType &tensor, typename TensorType::scalar_type *data, typename TensorType::shape_container &&shape, bool owning = false)
.. doxygenfunction:: make_tensor( TensorType &tensor, typename TensorType::scalar_type *ptr, bool owning = false)
.. doxygenfunction:: make_tensor( TensorType &tensor, typename TensorType::value_type *data, typename TensorType::shape_container &&shape, bool owning = false)
.. doxygenfunction:: make_tensor( TensorType &tensor, typename TensorType::value_type *ptr, bool owning = false)
.. doxygenfunction:: make_tensor( Storage &&s, ShapeType &&shape)
.. doxygenfunction:: make_tensor( TensorType &tensor, typename TensorType::storage_type &&s, typename TensorType::shape_container &&shape)
.. doxygenfunction:: make_tensor( T* const data, D &&desc, bool owning = false)
.. doxygenfunction:: make_tensor( TensorType &tensor, typename TensorType::scalar_type* const data, typename TensorType::desc_type &&desc, bool owning = false)
.. doxygenfunction:: make_tensor( TensorType &tensor, typename TensorType::value_type* const data, typename TensorType::desc_type &&desc, bool owning = false)
.. doxygenfunction:: make_tensor( D &&desc, matxMemorySpace_t space = MATX_MANAGED_MEMORY, cudaStream_t stream = 0)
.. doxygenfunction:: make_tensor( TensorType &&tensor, typename TensorType::desc_type &&desc, matxMemorySpace_t space = MATX_MANAGED_MEMORY, cudaStream_t stream = 0)
.. doxygenfunction:: make_tensor( T *const data, const index_t (&shape)[RANK], const index_t (&strides)[RANK], bool owning = false)
.. doxygenfunction:: make_tensor( TensorType &tensor, typename TensorType::scalar_type *const data, const index_t (&shape)[TensorType::Rank()], const index_t (&strides)[TensorType::Rank()], bool owning = false)
.. doxygenfunction:: make_tensor( TensorType &tensor, typename TensorType::value_type *const data, const index_t (&shape)[TensorType::Rank()], const index_t (&strides)[TensorType::Rank()], bool owning = false)

Return by Pointer
~~~~~~~~~~~~~~~~~
Expand Down
33 changes: 33 additions & 0 deletions docs_input/api/linalg/other/toeplitz.rst
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@@ -0,0 +1,33 @@
.. _toeplitz_func:

toeplitz
========

Generate a toeplitz matrix

`c` represents the first column of the matrix while `r` represents the first row. `c` and `r` must
have the same first value; if they don't match, the first value from `c` will be used.

Passing a single array/operator as input is equivalent to passing the conjugate of the same
input as the second parameter.

.. doxygenfunction:: toeplitz(const T (&c)[D])
.. doxygenfunction:: toeplitz(const Op &c)
.. doxygenfunction:: toeplitz(const T (&c)[D1], const T (&r)[D2])
.. doxygenfunction:: toeplitz(const COp &cop, const ROp &rop)

Examples
~~~~~~~~

.. literalinclude:: ../../../../test/00_operators/OperatorTests.cu
:language: cpp
:start-after: example-begin toeplitz-test-1
:end-before: example-end toeplitz-test-1
:dedent:

.. literalinclude:: ../../../../test/00_operators/OperatorTests.cu
:language: cpp
:start-after: example-begin toeplitz-test-2
:end-before: example-end toeplitz-test-2
:dedent:

4 changes: 2 additions & 2 deletions docs_input/api/signalimage/general/chirp.rst
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Expand Up @@ -6,7 +6,7 @@ chirp
Creates a real chirp signal (swept-frequency cosine)

.. doxygenfunction:: chirp(index_t num, TimeType last, FreqType f0, TimeType t1, FreqType f1, ChirpMethod method = ChirpMethod::CHIRP_METHOD_LINEAR)
.. doxygenfunction:: chirp(SpaceOp t, FreqType f0, typename SpaceOp::scalar_type t1, FreqType f1, ChirpMethod method = ChirpMethod::CHIRP_METHOD_LINEAR)
.. doxygenfunction:: chirp(SpaceOp t, FreqType f0, typename SpaceOp::value_type t1, FreqType f1, ChirpMethod method = ChirpMethod::CHIRP_METHOD_LINEAR)

Examples
~~~~~~~~
Expand All @@ -24,7 +24,7 @@ cchirp
Creates a complex chirp signal (swept-frequency cosine)

.. doxygenfunction:: cchirp(index_t num, TimeType last, FreqType f0, TimeType t1, FreqType f1, ChirpMethod method = ChirpMethod::CHIRP_METHOD_LINEAR)
.. doxygenfunction:: cchirp(SpaceOp t, FreqType f0, typename SpaceOp::scalar_type t1, FreqType f1, ChirpMethod method = ChirpMethod::CHIRP_METHOD_LINEAR)
.. doxygenfunction:: cchirp(SpaceOp t, FreqType f0, typename SpaceOp::value_type t1, FreqType f1, ChirpMethod method = ChirpMethod::CHIRP_METHOD_LINEAR)

Examples
~~~~~~~~
Expand Down
2 changes: 1 addition & 1 deletion docs_input/api/stats/hist/hist.rst
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Expand Up @@ -5,7 +5,7 @@ hist

Compute a histogram of input `a` with bounds specified by `upper` and `lower`

.. doxygenfunction:: hist(const InputOperator &a, const typename InputOperator::scalar_type lower, const typename InputOperator::scalar_type upper)
.. doxygenfunction:: hist(const InputOperator &a, const typename InputOperator::value_type lower, const typename InputOperator::value_type upper)

Examples
~~~~~~~~
Expand Down
2 changes: 1 addition & 1 deletion include/matx/core/file_io.h
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Expand Up @@ -158,7 +158,7 @@ void read_csv(TensorType &t, const std::string fname,
auto np = pybind11::module_::import("numpy");
auto obj = np.attr("genfromtxt")("fname"_a = fname.c_str(), "delimiter"_a = delimiter,
"skip_header"_a = skip_header,
"dtype"_a = detail::MatXPybind::GetNumpyDtype<typename TensorType::scalar_type>());
"dtype"_a = detail::MatXPybind::GetNumpyDtype<typename TensorType::value_type>());
pb->NumpyToTensorView(t, obj);
}

Expand Down
6 changes: 2 additions & 4 deletions include/matx/core/iterator.h
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Expand Up @@ -47,8 +47,7 @@ namespace matx {
template <typename OperatorType, bool ConvertType = true>
struct RandomOperatorIterator {
using self_type = RandomOperatorIterator<OperatorType, ConvertType>;
using value_type = typename std::conditional_t<ConvertType, detail::convert_matx_type_t<typename OperatorType::scalar_type>, typename OperatorType::scalar_type>;
using scalar_type = value_type;
using value_type = typename std::conditional_t<ConvertType, detail::convert_matx_type_t<typename OperatorType::value_type>, typename OperatorType::value_type>;
// using stride_type = std::conditional_t<is_tensor_view_v<OperatorType>, typename OperatorType::desc_type::stride_type,
// index_t>;
using stride_type = index_t;
Expand Down Expand Up @@ -174,8 +173,7 @@ __MATX_INLINE__ __MATX_HOST__ __MATX_DEVICE__ index_t operator-(const RandomOper
template <typename OperatorType, bool ConvertType = true>
struct RandomOperatorOutputIterator {
using self_type = RandomOperatorOutputIterator<OperatorType, ConvertType>;
using value_type = typename std::conditional_t<ConvertType, detail::convert_matx_type_t<typename OperatorType::scalar_type>, typename OperatorType::scalar_type>;
using scalar_type = value_type;
using value_type = typename std::conditional_t<ConvertType, detail::convert_matx_type_t<typename OperatorType::value_type>, typename OperatorType::value_type>;
// using stride_type = std::conditional_t<is_tensor_view_v<OperatorType>, typename OperatorType::desc_type::stride_type,
// index_t>;
using stride_type = index_t;
Expand Down
30 changes: 15 additions & 15 deletions include/matx/core/make_tensor.h
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Expand Up @@ -78,7 +78,7 @@ void make_tensor( TensorType &tensor,
cudaStream_t stream = 0) {
MATX_NVTX_START("", matx::MATX_NVTX_LOG_API)

auto tmp = make_tensor<typename TensorType::scalar_type, TensorType::Rank()>(shape, space, stream);
auto tmp = make_tensor<typename TensorType::value_type, TensorType::Rank()>(shape, space, stream);
tensor.Shallow(tmp);
}

Expand Down Expand Up @@ -166,7 +166,7 @@ auto make_tensor( TensorType &tensor,
cudaStream_t stream = 0) {
MATX_NVTX_START("", matx::MATX_NVTX_LOG_API)

auto tmp = make_tensor<typename TensorType::scalar_type, ShapeType>(std::forward<ShapeType>(shape), space, stream);
auto tmp = make_tensor<typename TensorType::value_type, ShapeType>(std::forward<ShapeType>(shape), space, stream);
tensor.Shallow(tmp);
}

Expand Down Expand Up @@ -225,7 +225,7 @@ auto make_tensor_p( TensorType &tensor,
cudaStream_t stream = 0) {
MATX_NVTX_START("", matx::MATX_NVTX_LOG_API)

auto tmp = make_tensor<typename TensorType::scalar_type, typename TensorType::shape_container>(std::forward<typename TensorType::shape_container>(shape), space, stream);
auto tmp = make_tensor<typename TensorType::value_type, typename TensorType::shape_container>(std::forward<typename TensorType::shape_container>(shape), space, stream);
tensor.Shallow(tmp);
}

Expand Down Expand Up @@ -261,7 +261,7 @@ template <typename TensorType,
auto make_tensor( TensorType &tensor,
matxMemorySpace_t space = MATX_MANAGED_MEMORY,
cudaStream_t stream = 0) {
auto tmp = make_tensor<typename TensorType::scalar_type>({}, space, stream);
auto tmp = make_tensor<typename TensorType::value_type>({}, space, stream);
tensor.Shallow(tmp);
}

Expand Down Expand Up @@ -322,12 +322,12 @@ auto make_tensor( T *data,
template <typename TensorType,
std::enable_if_t<is_tensor_view_v<TensorType>, bool> = true>
auto make_tensor( TensorType &tensor,
typename TensorType::scalar_type *data,
typename TensorType::value_type *data,
const index_t (&shape)[TensorType::Rank()],
bool owning = false) {
MATX_NVTX_START("", matx::MATX_NVTX_LOG_API)

auto tmp = make_tensor<typename TensorType::scalar_type, TensorType::Rank()>(data, shape, owning);
auto tmp = make_tensor<typename TensorType::value_type, TensorType::Rank()>(data, shape, owning);
tensor.Shallow(tmp);
}

Expand Down Expand Up @@ -373,12 +373,12 @@ auto make_tensor( T *data,
template <typename TensorType,
std::enable_if_t<is_tensor_view_v<TensorType>, bool> = true>
auto make_tensor( TensorType &tensor,
typename TensorType::scalar_type *data,
typename TensorType::value_type *data,
typename TensorType::shape_container &&shape,
bool owning = false) {
MATX_NVTX_START("", matx::MATX_NVTX_LOG_API)

auto tmp = make_tensor<typename TensorType::scalar_type, typename TensorType::shape_container>(data, std::forward<typename TensorType::shape_container>(shape), owning);
auto tmp = make_tensor<typename TensorType::value_type, typename TensorType::shape_container>(data, std::forward<typename TensorType::shape_container>(shape), owning);
tensor.Shallow(tmp);
}

Expand Down Expand Up @@ -414,9 +414,9 @@ auto make_tensor( T *ptr,
template <typename TensorType,
std::enable_if_t<is_tensor_view_v<TensorType>, bool> = true>
auto make_tensor( TensorType &tensor,
typename TensorType::scalar_type *ptr,
typename TensorType::value_type *ptr,
bool owning = false) {
auto tmp = make_tensor<typename TensorType::scalar_type>(ptr, owning);
auto tmp = make_tensor<typename TensorType::value_type>(ptr, owning);
tensor.Shallow(tmp);
}

Expand Down Expand Up @@ -534,12 +534,12 @@ auto make_tensor( T* const data,
template <typename TensorType,
std::enable_if_t<is_tensor_view_v<TensorType>, bool> = true>
auto make_tensor( TensorType &tensor,
typename TensorType::scalar_type* const data,
typename TensorType::value_type* const data,
typename TensorType::desc_type &&desc,
bool owning = false) {
MATX_NVTX_START("", matx::MATX_NVTX_LOG_API)

auto tmp = make_tensor<typename TensorType::scalar_type, typename TensorType::desc_type>(data, std::forward<typename TensorType::desc_type>(desc), owning);
auto tmp = make_tensor<typename TensorType::value_type, typename TensorType::desc_type>(data, std::forward<typename TensorType::desc_type>(desc), owning);
tensor.Shallow(tmp);
}

Expand Down Expand Up @@ -585,7 +585,7 @@ auto make_tensor( TensorType &&tensor,
cudaStream_t stream = 0) {
MATX_NVTX_START("", matx::MATX_NVTX_LOG_API)

auto tmp = make_tensor<typename TensorType::scalar_type, typename TensorType::desc_type>(std::forward<typename TensorType::desc_type>(desc), space, stream);
auto tmp = make_tensor<typename TensorType::value_type, typename TensorType::desc_type>(std::forward<typename TensorType::desc_type>(desc), space, stream);
tensor.Shallow(tmp);
}

Expand Down Expand Up @@ -633,13 +633,13 @@ auto make_tensor( T *const data,
template <typename TensorType,
std::enable_if_t<is_tensor_view_v<TensorType>, bool> = true>
auto make_tensor( TensorType &tensor,
typename TensorType::scalar_type *const data,
typename TensorType::value_type *const data,
const index_t (&shape)[TensorType::Rank()],
const index_t (&strides)[TensorType::Rank()],
bool owning = false) {
MATX_NVTX_START("", matx::MATX_NVTX_LOG_API)

auto tmp = make_tensor<typename TensorType::scalar_type, TensorType::Rank()>(data, shape, strides, owning);
auto tmp = make_tensor<typename TensorType::value_type, TensorType::Rank()>(data, shape, strides, owning);
tensor.Shallow(tmp);
}

Expand Down
12 changes: 6 additions & 6 deletions include/matx/core/operator_utils.h
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Expand Up @@ -44,13 +44,13 @@ namespace matx {
if (out.IsContiguous()) {
if constexpr(ConvertType) {
return func( in,
reinterpret_cast<detail::convert_matx_type_t<typename remove_cvref_t<OutputOp>::scalar_type> *>(out.Data()),
reinterpret_cast<detail::convert_matx_type_t<typename remove_cvref_t<OutputOp>::value_type> *>(out.Data()),
bi,
ei);
}
else {
return func( in,
reinterpret_cast<typename remove_cvref_t<OutputOp>::scalar_type *>(out.Data()),
reinterpret_cast<typename remove_cvref_t<OutputOp>::value_type *>(out.Data()),
bi,
ei);
}
Expand All @@ -70,14 +70,14 @@ namespace matx {
if constexpr (ConvertType) {
return ReduceOutput<ConvertType>( std::forward<Func>(func),
std::forward<OutputOp>(out),
reinterpret_cast<detail::convert_matx_type_t<typename remove_cvref_t<InputOp>::scalar_type> *>(in_base.Data()),
reinterpret_cast<detail::convert_matx_type_t<typename remove_cvref_t<InputOp>::value_type> *>(in_base.Data()),
BeginOffset{in_base},
EndOffset{in_base});
}
else {
return ReduceOutput<ConvertType>( std::forward<Func>(func),
std::forward<OutputOp>(out),
reinterpret_cast<typename remove_cvref_t<InputOp>::scalar_type *>(in_base.Data()),
reinterpret_cast<typename remove_cvref_t<InputOp>::value_type *>(in_base.Data()),
BeginOffset{in_base},
EndOffset{in_base});
}
Expand Down Expand Up @@ -118,9 +118,9 @@ namespace matx {
namespace detail {
// Used inside of transforms to allocate temporary output
template <typename TensorType, typename Executor, typename ShapeType>
__MATX_HOST__ __MATX_INLINE__ void AllocateTempTensor(TensorType &tensor, Executor &&ex, ShapeType &&shape, typename TensorType::scalar_type **ptr) {
__MATX_HOST__ __MATX_INLINE__ void AllocateTempTensor(TensorType &tensor, Executor &&ex, ShapeType &&shape, typename TensorType::value_type **ptr) {
const auto ttl_size = std::accumulate(shape.begin(), shape.end(), static_cast<index_t>(1),
std::multiplies<index_t>()) * sizeof(typename TensorType::scalar_type);
std::multiplies<index_t>()) * sizeof(typename TensorType::value_type);
if constexpr (is_cuda_executor_v<Executor>) {
matxAlloc((void**)ptr, ttl_size, MATX_ASYNC_DEVICE_MEMORY, ex.getStream());
make_tensor(tensor, *ptr, shape);
Expand Down
12 changes: 6 additions & 6 deletions include/matx/core/pybind.h
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Expand Up @@ -176,7 +176,7 @@ class MatXPybind {
template <typename TensorType>
static pybind11::object GetEmptyNumpy(const TensorType &ten)
{
using T = typename TensorType::scalar_type;
using T = typename TensorType::value_type;
auto np = pybind11::module_::import("numpy");
pybind11::list dims;

Expand Down Expand Up @@ -329,7 +329,7 @@ class MatXPybind {
void NumpyToTensorView(TensorType ten,
const pybind11::object &np_ten)
{
using T = typename TensorType::scalar_type;
using T = typename TensorType::value_type;
constexpr int RANK = TensorType::Rank();
static_assert(RANK <=5, "NumpyToTensorView only supports max(RANK) = 5 at the moment.");

Expand Down Expand Up @@ -377,7 +377,7 @@ class MatXPybind {
template <typename TensorType>
auto NumpyToTensorView(const pybind11::object &np_ten)
{
using T = typename TensorType::scalar_type;
using T = typename TensorType::value_type;
constexpr int RANK = TensorType::Rank();
using ntype = matx_convert_complex_type<T>;
auto ften = pybind11::array_t<ntype, pybind11::array::c_style | pybind11::array::forcecast>(np_ten);
Expand All @@ -398,7 +398,7 @@ class MatXPybind {

template <typename TensorType>
auto TensorViewToNumpy(const TensorType &ten) {
using tensor_type = typename TensorType::scalar_type;
using tensor_type = typename TensorType::value_type;
using ntype = matx_convert_complex_type<tensor_type>;
constexpr int RANK = TensorType::Rank();

Expand Down Expand Up @@ -466,12 +466,12 @@ class MatXPybind {


template <typename TensorType,
typename CT = matx_convert_cuda_complex_type<typename TensorType::scalar_type>>
typename CT = matx_convert_cuda_complex_type<typename TensorType::value_type>>
std::optional<TestFailResult<CT>>
CompareOutput(const TensorType &ten,
const std::string fname, double thresh, bool debug = false)
{
using raw_type = typename TensorType::scalar_type;
using raw_type = typename TensorType::value_type;
using ntype = matx_convert_complex_type<raw_type>;
using ctype = matx_convert_cuda_complex_type<raw_type>;
auto resobj = res_dict[fname.c_str()];
Expand Down
2 changes: 1 addition & 1 deletion include/matx/core/tensor.h
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Expand Up @@ -87,7 +87,7 @@ class tensor_t : public detail::tensor_impl_t<T,RANK,Desc> {
public:
// Type specifier for reflection on class
using type = T; ///< Type of traits
using scalar_type = T; ///< Type of traits
using value_type = T; ///< Type of traits
// Type specifier for signaling this is a matx operation or tensor view
using matxop = bool; ///< Indicate this is a MatX operator
using matxoplvalue = bool; ///< Indicate this is a MatX operator that can be on the lhs of an equation
Expand Down
1 change: 0 additions & 1 deletion include/matx/core/tensor_impl.h
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Expand Up @@ -71,7 +71,6 @@ class tensor_impl_t {
public:
// Type specifier for reflection on class
using type = T; // TODO is this necessary
using scalar_type = T;
using value_type = T;
using tensor_view = bool;
using desc_type = Desc;
Expand Down
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