#include <H5Slice_traits.hpp>
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| Selection | select (const HyperSlab &hyperslab) const |
| | Select an hyperslab in the current Slice/Dataset.
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| Selection | select (const HyperSlab &hyperslab, const DataSpace &memspace) const |
| | Select an hyperslab in the current Slice/Dataset.
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| Selection | select (const std::vector< size_t > &offset, const std::vector< size_t > &count, const std::vector< size_t > &stride={}, const std::vector< size_t > &block={}) const |
| | Select a region in the current Slice/Dataset of count points at offset separated by stride. If strides are not provided they will default to 1 in all dimensions.
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| Selection | select (const std::vector< size_t > &columns) const |
| | Select a set of columns in the last dimension of this dataset.
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| Selection | select (const ElementSet &elements) const |
| | Select a region in the current Slice/Dataset out of a list of elements.
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| template<typename T > |
| T | read (const DataTransferProps &xfer_props=DataTransferProps()) const |
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| template<typename T > |
| void | read (T &array, const DataTransferProps &xfer_props=DataTransferProps()) const |
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| template<typename T > |
| void | read (T *array, const DataType &dtype, const DataTransferProps &xfer_props=DataTransferProps()) const |
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| template<typename T > |
| void | read (T *array, const DataTransferProps &xfer_props=DataTransferProps()) const |
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| template<typename T > |
| void | read_raw (T *array, const DataType &dtype, const DataTransferProps &xfer_props=DataTransferProps()) const |
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| template<typename T > |
| void | read_raw (T *array, const DataTransferProps &xfer_props=DataTransferProps()) const |
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| template<typename T > |
| void | write (const T &buffer, const DataTransferProps &xfer_props=DataTransferProps()) |
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| template<typename T > |
| void | write_raw (const T *buffer, const DataType &mem_datatype, const DataTransferProps &xfer_props=DataTransferProps()) |
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| template<typename T > |
| void | write_raw (const T *buffer, const DataTransferProps &xfer_props=DataTransferProps()) |
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◆ read() [1/4]
template<typename Derivate >
template<typename T >
◆ read() [2/4]
template<typename Derivate >
template<typename T >
Read the entire dataset into a buffer
An exception is raised is if the numbers of dimension of the buffer and of the dataset are different.
The array type can be a N-pointer or a N-vector. For plain pointers not dimensionality checking will be performed, it is the user's responsibility to ensure that the right amount of space has been allocated.
◆ read() [3/4]
template<typename Derivate >
template<typename T >
Read the entire dataset into a raw buffer
- Deprecated
- Use
read_raw instead.
Same as read(T*, const DataType&, const DataTransferProps&). However, this overload deduces the HDF5 datatype of the element of array from T. Note, that the file datatype is already fixed.
- Parameters
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| array | A buffer containing enough space for the data |
| xfer_props | Data Transfer properties |
◆ read() [4/4]
template<typename Derivate >
template<typename T >
Read the entire dataset into a raw buffer
- Deprecated
- Use
read_raw instead.
No dimensionality checks will be performed, it is the user's responsibility to ensure that the right amount of space has been allocated.
- Parameters
-
| array | A buffer containing enough space for the data |
| dtype | The datatype of elements of the in memory buffer. |
| xfer_props | Data Transfer properties |
◆ read_raw() [1/2]
template<typename Derivate >
template<typename T >
Read the entire dataset into a raw buffer
Same as read(T*, const DataType&, const DataTransferProps&). However, this overload deduces the HDF5 datatype of the element of array from T. Note, that the file datatype is already fixed.
- Parameters
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| array | A buffer containing enough space for the data |
| xfer_props | Data Transfer properties |
◆ read_raw() [2/2]
template<typename Derivate >
template<typename T >
Read the entire dataset into a raw buffer
No dimensionality checks will be performed, it is the user's responsibility to ensure that the right amount of space has been allocated.
- Parameters
-
| array | A buffer containing enough space for the data |
| dtype | The type of the data, in case it cannot be automatically guessed |
| xfer_props | Data Transfer properties |
◆ select() [1/5]
template<typename Derivate >
Select a region in the current Slice/Dataset out of a list of elements.
◆ select() [2/5]
template<typename Derivate >
Select an hyperslab in the current Slice/Dataset.
HyperSlabs can be either regular or irregular. Irregular hyperslabs are typically generated by taking the union of regular hyperslabs. An irregular hyperslab, in general, does not fit nicely into a multi-dimensional array, but only a subset of such an array.
Therefore, the only memspaces supported for general hyperslabs are one-dimensional arrays.
◆ select() [3/5]
template<typename Derivate >
Select an hyperslab in the current Slice/Dataset.
If the selection can be read into a simple, multi-dimensional dataspace, then this overload enable specifying the shape of the memory dataspace with memspace. Note, that simple implies no offsets, strides or number of blocks, just the size of the block in each dimension.
◆ select() [4/5]
template<typename Derivate >
Select a set of columns in the last dimension of this dataset.
The column indices must be smaller than the dimension size.
◆ select() [5/5]
template<typename Derivate >
| Selection HighFive::SliceTraits< Derivate >::select |
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const std::vector< size_t > & | offset, |
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const std::vector< size_t > & | count, |
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const std::vector< size_t > & | stride = {}, |
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const std::vector< size_t > & | block = {} ) const |
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inline |
Select a region in the current Slice/Dataset of count points at offset separated by stride. If strides are not provided they will default to 1 in all dimensions.
vector offset and count have to be from the same dimension
◆ write()
template<typename Derivate >
template<typename T >
Write the integrality N-dimension buffer to this dataset An exception is raised is if the numbers of dimension of the buffer and of the dataset are different
The array type can be a N-pointer or a N-vector ( e.g int** integer two dimensional array )
◆ write_raw() [1/2]
template<typename Derivate >
template<typename T >
Write from a raw pointer into this dataset.
Same as write_raw(const T*, const DataTransferProps&). However, this overload attempts to guess the data type of buffer, i.e. the memory datatype. Note that the file datatype is already fixed.
◆ write_raw() [2/2]
template<typename Derivate >
template<typename T >
Write from a raw pointer into this dataset.
No dimensionality checks will be performed, it is the user's responsibility to ensure that the buffer holds the right amount of elements. For n-dimensional matrices the buffer layout follows H5 default conventions.
Note, this is the shallowest wrapper around H5Dwrite and should be used if full control is needed. Generally prefer write.
- Parameters
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| buffer | A buffer containing the data to be written |
| dtype | The datatype of buffer, i.e. the memory data type. |
| xfer_props | The HDF5 data transfer properties, e.g. collective MPI-IO. |
The documentation for this class was generated from the following files:
1.10.0