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STYLE: Replace ELEMENT_WRITE with TryToWriteToStore variadic template
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Replaced the original `ELEMENT_WRITE` macro with a variadic template, using a
C++17 fold-expression.

Follow-up to pull request #67
commit 77a2f45
"STYLE: Replace READ_ELEMENT_IF with TryToReadFromStore variadic template"
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@N-Dekker
N-Dekker committed Aug 22, 2024
1 parent a4dd225 commit 679a165
Showing 1 changed file with 95 additions and 83 deletions.
178 changes: 95 additions & 83 deletions src/itkOMEZarrNGFFImageIO.cxx
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Original file line number Diff line number Diff line change
Expand Up @@ -33,14 +33,14 @@
#include <nlohmann/json.hpp>

// Evaluate tensorstore future (statement) and error-check the result.
#define TS_EVAL_CHECK(statement) \
{ \
auto result = statement.result(); \
if (!result.ok()) /* error */ \
{ \
itkExceptionMacro("tensorstore error: " << result.status()); \
} \
} \
#define TS_EVAL_CHECK(statement) \
{ \
auto result = statement.result(); \
if (!result.ok()) /* error */ \
{ \
itkGenericExceptionMacro("tensorstore error: " << result.status()); \
} \
} \
ITK_NOOP_STATEMENT


Expand Down Expand Up @@ -257,6 +257,92 @@ TryToReadFromStore(TypeList<TPixel...>,
return (ReadFromStoreIfTypesMatch<TPixel>(componentType, store, storeIORegion, buffer) || ...);
}

// Writes to the store if the specified pixel type and the ITK component type match.
template <typename TPixel>
bool
WriteToStoreIfTypesMatch(const IOComponentEnum componentType,
tensorstore::TensorStore<> & store,
tensorstore::Context & tsContext,
const std::string & fileName,
const std::string & path,
const std::vector<int64_t> & shape,
const void * const buffer)
{
if (tensorstoreToITKComponentType(tensorstore::dtype_v<TPixel>) == componentType)
{
std::string dtype;
// we prefer to write using our own endianness, so no conversion is necessary
if (ByteSwapper<int>::SystemIsBigEndian())
{
dtype = ">";
}
else
{
dtype = "<";
}

if (sizeof(TPixel) == 1)
{
dtype = "|";
}
if (std::numeric_limits<TPixel>::is_integer)
{
if (std::numeric_limits<TPixel>::is_signed)
{
dtype += 'i';
}
else
{
dtype += 'u';
}
}
else
{
dtype += 'f';
}
dtype += std::to_string(sizeof(TPixel));

auto openFuture = tensorstore::Open(
{
{ "driver", "zarr" },
{ "kvstore", { { "driver", getKVstoreDriver(fileName) }, { "path", fileName + "/" + path } } },
{ "metadata",
{
{ "compressor", { { "id", "blosc" } } },
{ "dtype", dtype },
{ "shape", shape },
} },
},
tsContext,
tensorstore::OpenMode::create | tensorstore::OpenMode::delete_existing,
tensorstore::ReadWriteMode::read_write);
TS_EVAL_CHECK(openFuture);

auto writeStore = openFuture.value();
auto * p = static_cast<TPixel const *>(buffer);
auto arr = tensorstore::Array(p, shape, tensorstore::c_order);
auto writeFuture = tensorstore::Write(tensorstore::UnownedToShared(arr), writeStore);
TS_EVAL_CHECK(writeFuture);
return true;
}
return false;
}

// Tries to write to the specified store, trying any of the specified pixel types.
template <typename... TPixel>
bool
TryToWriteToStore(TypeList<TPixel...>,
const IOComponentEnum componentType,
tensorstore::TensorStore<> & store,
tensorstore::Context & tsContext,
const std::string & fileName,
const std::string & path,
const std::vector<int64_t> & shape,
const void * const buffer)
{
return (WriteToStoreIfTypesMatch<TPixel>(componentType, store, tsContext, fileName, path, shape, buffer) || ...);
}

// Update an existing "read" specification for an "http" driver to retrieve remote files.
// Note that an "http" driver specification may operate on an HTTP or HTTPS connection.
void
Expand Down Expand Up @@ -721,54 +807,6 @@ OMEZarrNGFFImageIO::WriteImageInformation()
}


// We need to specify dtype for opening. As dtype is dependent on component type, this macro is long.
#define ELEMENT_WRITE(typeName) \
else if (tensorstoreToITKComponentType(tensorstore::dtype_v<typeName>) == this->GetComponentType()) \
{ \
if (sizeof(typeName) == 1) \
{ \
dtype = "|"; \
} \
if (std::numeric_limits<typeName>::is_integer) \
{ \
if (std::numeric_limits<typeName>::is_signed) \
{ \
dtype += 'i'; \
} \
else \
{ \
dtype += 'u'; \
} \
} \
else \
{ \
dtype += 'f'; \
} \
dtype += std::to_string(sizeof(typeName)); \
\
auto openFuture = tensorstore::Open( \
{ \
{ "driver", "zarr" }, \
{ "kvstore", { { "driver", driver }, { "path", this->m_FileName + "/" + path } } }, \
{ "metadata", \
{ \
{ "compressor", { { "id", "blosc" } } }, \
{ "dtype", dtype }, \
{ "shape", shape }, \
} }, \
}, \
tsContext, \
tensorstore::OpenMode::create | tensorstore::OpenMode::delete_existing, \
tensorstore::ReadWriteMode::read_write); \
TS_EVAL_CHECK(openFuture); \
\
auto writeStore = openFuture.value(); \
auto * p = reinterpret_cast<typeName const *>(buffer); \
auto arr = tensorstore::Array(p, shape, tensorstore::c_order); \
auto writeFuture = tensorstore::Write(tensorstore::UnownedToShared(arr), writeStore); \
TS_EVAL_CHECK(writeFuture); \
}

void
OMEZarrNGFFImageIO::Write(const void * buffer)
{
Expand Down Expand Up @@ -797,33 +835,7 @@ OMEZarrNGFFImageIO::Write(const void * buffer)
shape[shape.size() - 1 - d] = dSize; // convert IJK into KJI
}

std::string dtype;
// we prefer to write using our own endianness, so no conversion is necessary
if (ByteSwapper<int>::SystemIsBigEndian())
{
dtype = ">";
}
else
{
dtype = "<";
}

std::string driver = getKVstoreDriver(this->GetFileName());

if (false) // start with a plain "if"
{
} // so element statements can all be "else if"
ELEMENT_WRITE(int8_t)
ELEMENT_WRITE(uint8_t)
ELEMENT_WRITE(int16_t)
ELEMENT_WRITE(uint16_t)
ELEMENT_WRITE(int32_t)
ELEMENT_WRITE(uint32_t)
ELEMENT_WRITE(int64_t)
ELEMENT_WRITE(uint64_t)
ELEMENT_WRITE(float)
ELEMENT_WRITE(double)
else
if (!TryToWriteToStore(supportedPixelTypes, componentType, store, tsContext, m_FileName, path, shape, buffer))
{
itkExceptionMacro("Unsupported component type: " << GetComponentTypeAsString(componentType));
}
Expand Down

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