/* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * Copyright by The HDF Group. * * All rights reserved. * * * * This file is part of HDF5. The full HDF5 copyright notice, including * * terms governing use, modification, and redistribution, is contained in * * the COPYING file, which can be found at the root of the source code * * distribution tree, or in https://www.hdfgroup.org/licenses. * * If you do not have access to either file, you may request a copy from * * help@hdfgroup.org. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */ /* * Purpose: This file contains declarations which define macros for the * H5S package. Including this header means that the source file * is part of the H5S package. */ #ifndef H5Smodule_H #define H5Smodule_H /* Define the proper control macros for the generic FUNC_ENTER/LEAVE and error * reporting macros. */ #define H5S_MODULE #define H5_MY_PKG H5S #define H5_MY_PKG_ERR H5E_DATASPACE /** \page H5S_UG Dataspaces and Partial I/O * * * \section sec_dataspace HDF5 Dataspaces and Partial I/O * * HDF5 dataspaces describe the \Emph{shape} of datasets in memory or in HDF5 * files. Dataspaces can be empty (#H5S_NULL), a singleton (#H5S_SCALAR), or * a multi-dimensional, regular grid (#H5S_SIMPLE). Dataspaces can be re-shaped. * * Subsets of dataspaces can be "book-marked" or used to restrict I/O operations * using \Emph{selections}. Furthermore, certain set operations are supported * for selections. * * \subsection subsec_dataspace_intro Introduction * * The HDF5 \Emph{dataspace} is a required component of an HDF5 dataset or attribute definition. The dataspace * defines the size and shape of the dataset or attribute raw data. In other words, a dataspace defines the * number of dimensions and the size of each dimension of the multidimensional array in which the raw data * is represented. The dataspace must be defined when the dataset or attribute is created. * * The \Emph{dataspace} is also used during dataset I/O operations, defining the elements of the dataset that * participate in the I/O operation. * * This chapter explains the \Emph{dataspace} object and its use in dataset and attribute creation and data * transfer. It also describes selection operations on a dataspace used to implement sub‐setting, * sub‐sampling, and scatter‐gather access to datasets. * * \subsection subsec_dataspace_function Dataspace Function Summaries * @see H5S reference manual provides a reference list of dataspace functions, the H5S APIs. * * \subsection subsec_dataspace_program Definition of Dataspace Objects and the Dataspace Programming Model * * This section introduces the notion of the HDF5 dataspace object and a programming model for creating * and working with dataspaces. * * \subsubsection subsubsec_dataspace_program_object Dataspace Objects * * An HDF5 dataspace is a required component of an HDF5 dataset or attribute. A dataspace defines the size * and the shape of a dataset's or an attribute's raw data. Currently, HDF5 supports the following types of * the dataspaces: * \li Scalar dataspaces * \li Simple dataspaces * \li Null dataspaces * * A scalar dataspace, #H5S_SCALAR, represents just one element, a scalar. Note that the datatype of this one * element may be very complex; example would be a compound structure with members being of any * allowed HDF5 datatype, including multidimensional arrays, strings, and nested compound structures. By * convention, the rank of a scalar dataspace is always 0 (zero); think of it geometrically as a single, * dimensionless point, though that point may be complex. * * A simple dataspace, #H5S_SIMPLE , is a multidimensional array of elements. The dimensionality of the * dataspace (or the rank of the array) is fixed and is defined at creation time. The size of each dimension * can grow during the life time of the dataspace from the current size up to the maximum size. Both the * current size and the maximum size are specified at creation time. The sizes of dimensions at any particular * time in the life of a dataspace are called the current dimensions, or the dataspace extent. They can be * queried along with the maximum sizes. * * A null dataspace, #H5S_NULL, contains no data elements. Note that no selections can be applied to a null * dataset as there is nothing to select. * * As shown in the UML diagram in the figure below, an HDF5 simple dataspace object has three attributes: * the rank or number of dimensions; the current sizes, expressed as an array of length rank with each element * of the array denoting the current size of the corresponding dimension; and the maximum sizes, * expressed as an array of length rank with each element of the array denoting the maximum size of the * corresponding dimension. * * * * * *
* \image html Dspace_simple.gif "A simple dataspace" *
* * \em Note: A simple dataspace is defined by its rank, the current size of each dimension, and the maximum * size of each dimension. * * The size of a current dimension cannot be greater than the maximum size, which can be unlimited, specified * as #H5S_UNLIMITED. Note that while the HDF5 file format and library impose no maximum size on an * unlimited dimension, practically speaking its size will always be limited to the biggest integer available * on the particular system being used. * * Dataspace rank is restricted to 32, the standard limit in C on the rank of an array, in the current * implementation of the HDF5 Library. The HDF5 file format, on the other hand, allows any rank up to the * maximum integer value on the system, so the library restriction can be raised in the future if higher * dimensionality is required. * * Note that most of the time Fortran applications calling HDF5 will work with dataspaces of rank less than * or equal to seven, since seven is the maximum number of dimensions in a Fortran array. But dataspace rank * is not limited to seven for Fortran applications. * * The current dimensions of a dataspace, also referred to as the dataspace extent, define the bounding box * for dataset elements that can participate in I/O operations. * * \subsubsection subsubsec_dataspace_program_model Dataspace Programming Model * * The programming model for creating and working with HDF5 dataspaces can be summarized as follows: * \li 1. Create a dataspace * \li 2. Use the dataspace to create a dataset in the file or to describe a data array in memory * \li 3. Modify the dataspace to define dataset elements that will participate in I/O operations * \li 4. Use the modified dataspace while reading/writing dataset raw data or to create a region reference * \li 5. Close the dataspace when no longer needed * * The rest of this section will address steps 1, 2, and 5 of the programming model; steps 3 and 4 will be * discussed in later sections of this chapter. * *

Creating a Dataspace

* * A dataspace can be created by calling the \ref H5Screate function. Since the * definition of a simple dataspace requires the specification of dimensionality (or rank) and initial and * maximum dimension sizes, the HDF5 Library provides a convenience API, \ref H5Screate_simple to create a * simple dataspace in one step. * * The following examples illustrate the usage of these APIs. * *

Creating a Scalar Dataspace

* * Creating a Scalar Dataspace * \code * hid_t space_id; * . . . * space_id = H5Screate(H5S_SCALAR); * \endcode * As mentioned above, the dataspace will contain only one element. Scalar dataspaces are used more often * for describing attributes that have just one value. For example, the attribute temperature with the value * Celsius is used to indicate that the dataset with this attribute stores temperature values using the * Celsius scale. * *

Creating a Null Dataspace

* * A null dataspace is created with the \ref H5Screate function. * \code * hid_t space_id; * . . . * space_id = H5Screate(H5S_NULL); * \endcode * As mentioned above, the dataspace will contain no elements. * *

Creating a Simple Dataspace

* * Let's assume that an application wants to store a two‐dimensional array of data, A(20,100). During the * life of the application, the first dimension of the array can grow up to 30; there is no restriction on * the size of the second dimension. The following steps are used to declare a dataspace for the dataset * in which the array data will be stored. * \code * hid_t space_id; * int rank = 2; * hsize_t current_dims[2] = {20, 100}; * hsize_t max_dims[2] = {30, H5S_UNLIMITED}; * . . . * space_id = H5Screate(H5S_NULL); * H5Sset_extent_simple(space_id, rank, current_dims, max_dims); * \endcode * * Alternatively, the convenience APIs H5Screate_simple/h5screate_simple_f can replace the * H5Screate/h5screate_f and H5Sset_extent_simple/h5sset_extent_simple_f calls. * \code * space_id = H5Screate_simple(rank, current_dims, max_dims); * \endcode * * In this example, a dataspace with current dimensions of 20 by 100 is created. The first dimension can be * extended only up to 30. The second dimension, however, is declared unlimited; it can be extended up to * the largest available integer value on the system. * * Note that when there is a difference between the current dimensions and the maximum dimensions of an * array, then chunking storage must be used. In other words, if the number of dimensions may change over * the life of the dataset, then chunking must be used. If the array dimensions are fixed (if the number of * current dimensions is equal to the maximum number of dimensions when the dataset is created), then * contiguous storage can be used. For more information, see "Data Transfer". * * Maximum dimensions can be the same as current dimensions. In such a case, the sizes of dimensions * cannot be changed during the life of the dataspace object. In C, \c NULL can be used to indicate to the * \ref H5Screate_simple and \ref H5Sset_extent_simple functions that the maximum sizes of all dimensions * are the same as the current sizes. * \code * space_id = H5Screate_simple(rank, current_dims, NULL); * \endcode * The created dataspace will have current and maximum dimensions of 20 and 100 correspondingly, and the * sizes of those dimensions cannot be changed. * *

C versus Fortran Dataspaces

* * Dataspace dimensions are numbered from 1 to rank. HDF5 uses C storage conventions, assuming that the * last listed dimension is the fastest‐changing dimension and the first‐listed dimension is the slowest * changing. The HDF5 file format storage layout specification adheres to the C convention and the HDF5 * Library adheres to the same convention when storing dataspace dimensions in the file. This affects how * C programs and tools interpret data written from Fortran programs and vice versa. The example below * illustrates the issue. * * When a Fortran application describes a dataspace to store an array as A(20,100), it specifies the value of * the first dimension to be 20 and the second to be 100. Since Fortran stores data by columns, the * first‐listed dimension with the value 20 is the fastest‐changing dimension and the last‐listed dimension * with the value 100 is the slowest‐changing. In order to adhere to the HDF5 storage convention, the HDF5 * Fortran wrapper transposes dimensions, so the first dimension becomes the last. The dataspace dimensions * stored in the file will be 100,20 instead of 20,100 in order to correctly describe the Fortran data that * is stored in 100 columns, each containing 20 elements. * * When a Fortran application reads the data back, the HDF5 Fortran wrapper transposes the dimensions * once more, returning the first dimension to be 20 and the second to be 100, describing correctly the sizes * of the array that should be used to read data in the Fortran array A(20,100). * * When a C application reads data back, the dimensions will come out as 100 and 20, correctly describing * the size of the array to read data into, since the data was written as 100 records of 20 elements each. * Therefore C tools such as h5dump and h5ls always display transposed dimensions and values for the data * written by a Fortran application. * * Consider the following simple example of equivalent C 3 x 5 and Fortran 5 x 3 arrays. As illustrated in * the figure below, a C application will store a 3 x 5 2‐dimensional array as three 5‐element rows. In order * to store the same data in the same order, a Fortran application must view the array as a 5 x 3 array with * three 5‐element columns. The dataspace of this dataset, as written from Fortran, will therefore be * described as 5 x 3 in the application but stored and described in the file according to the C convention * as a 3 x 5 array. This ensures that C and Fortran applications will always read the data in the order in * which it was written. The HDF5 Fortran interface handles this transposition automatically. * \code * // C * \#define NX 3 // dataset dimensions * \#define NY 5 * . . . * int data[NX][NY]; // data to write * . . . * // Data and output buffer initialization. * for (j = 0; j < NX; j++) * for (i = 0; i < NY; i++) * data[j][i] = i + j; * // * // 1 2 3 4 5 * // 6 7 8 9 10 * // 11 12 13 14 15 * // * . . . * dims[0] = NX; * dims[1] = NY; * dataspace = H5Screate_simple(RANK, dims, NULL); * \endcode * * \code * ! Fortran * INTEGER, PARAMETER :: NX = 3 * INTEGER, PARAMETER :: NX = 5 * . . . * INTEGER(HSIZE_T), DIMENSION(2) :: dims = (/NY, NX/) ! Dataset dimensions * . . . * ! * ! Initialize data * ! * do i = 1, NY * do j = 1, NX * data(i,j) = i + (j-1)*NY * enddo * enddo * ! * ! Data * ! * ! 1 6 11 * ! 2 7 12 * ! 3 8 13 * ! 4 9 14 * ! 5 10 15 * . . . * CALL h5screate_simple_f(rank, dims, dspace_id, error) * \endcode * * * * * * * * * * * * * * * * * * * * * * * * * * * *
Comparing C and Fortran dataspaces
* A dataset stored by a C program in a 3 x 5 array: *
* \image html Dspace_CvsF1.gif *
* The same dataset stored by a Fortran program in a 5 x 3 array: *
* \image html Dspace_CvsF2.gif *
* The first dataset above as written to an HDF5 file from C or the second dataset above as written * from Fortran: *
* \image html Dspace_CvsF3.gif *
* The first dataset above as written to an HDF5 file from Fortran: *
* \image html Dspace_CvsF4.gif *
* * Note: The HDF5 Library stores arrays along the fastest‐changing dimension. This approach is often * referred to as being “in C order.” C, C++, and Java work with arrays in row‐major order. In other words, * the row, or the last dimension, is the fastest‐changing dimension. Fortran, on the other hand, handles * arrays in column‐major order making the column, or the first dimension, the fastest‐changing dimension. * Therefore, the C and Fortran arrays illustrated in the top portion of this figure are stored identically * in an HDF5 file. This ensures that data written by any language can be meaningfully read, interpreted, * and manipulated by any other. * *

Finding Dataspace Characteristics

* * The HDF5 Library provides several APIs designed to query the characteristics of a dataspace. * * The function \ref H5Sis_simple returns information about the type of a dataspace. * This function is rarely used and currently supports only simple and scalar dataspaces. * * To find out the dimensionality, or rank, of a dataspace, use \ref H5Sget_simple_extent_ndims. * \ref H5Sget_simple_extent_dims can also be used to find out the rank. See * the example below. If both functions return 0 for the value of rank, then the dataspace is scalar. * * To query the sizes of the current and maximum dimensions, use \ref H5Sget_simple_extent_dims. * * The following example illustrates querying the rank and dimensions of a dataspace using these functions. * \code * hid_t space_id; * int rank; * hsize_t *current_dims; * hsize_t *max_dims; * . . . * rank = H5Sget_simple_extent_ndims(space_id); * // (or rank = H5Sget_simple_extent_dims(space_id, NULL, NULL);) * current_dims = (hsize_t)malloc(rank * sizeof(hsize_t)); * max_dims = (hsize_t)malloc(rank * sizeof(hsize_t)); * H5Sget_simple_extent_dims(space_id, current_dims, max_dims); * // Print values here * \endcode * * \subsection subsec_dataspace_transfer Dataspaces and Data Transfer * * Read and write operations transfer data between an HDF5 file on disk and in memory. The shape that the * array data takes in the file and in memory may be the same, but HDF5 also allows users the ability to * represent data in memory in a different shape than in the file. If the shape of an array in the file and * in memory will be the same, then the same dataspace definition can be used for both. If the shape of an * array in memory needs to be different than the shape in the file, then the dataspace definition for the * shape of the array in memory can be changed. During a read operation, the array will be read into the * different shape in memory, and during a write operation, the array will be written to the file in the * shape specified by the dataspace in the file. The only qualification is that the number of elements read * or written must be the same in both the source and the destination dataspaces. * * Item a in the figure below shows a simple example of a read operation in which the data is stored as a 3 * by 4 array in the file (item b) on disk, but the program wants it to be a 4 by 3 array in memory. This is * accomplished by setting the memory dataspace to describe the desired memory layout, as in item c. The read * operation reads the data in the file array into the memory array. * * * * * *
* \image html Dspace_read.gif "Data layout before and after a read operation" *
* * * * * *
* \image html Dspace_move.gif "Moving data from disk to memory" *
* Both the source and destination are stored as contiguous blocks of storage with the elements in the order * specified by the dataspace. The figure above shows one way the elements might be organized. In item a, * the elements are stored as 3 blocks of 4 elements. The destination is an array of 12 elements in memory * (see item c). As the figure suggests, the transfer reads the disk blocks into a memory buffer (see item b), * and then writes the elements to the correct locations in memory. A similar process occurs in reverse when * data is written to disk. * * \subsubsection subsubsec_dataspace_transfer_select Data Selection * * In addition to rearranging data, the transfer may select the data elements from the source and destination. * * Data selection is implemented by creating a dataspace object that describes the selected elements (within * the hyper rectangle) rather than the whole array. Two dataspace objects with selections can be used in * data transfers to read selected elements from the source and write selected elements to the destination. * When data is transferred using the dataspace object, only the selected elements will be transferred. * * This can be used to implement partial I/O, including: * \li Sub‐setting ‐ reading part of a large dataset * \li Sampling ‐ reading selected elements (for example, every second element) of a dataset * \li Scatter‐gather ‐ read non‐contiguous elements into contiguous locations (gather) or read contiguous * elements into non‐contiguous locations (scatter) or both * * To use selections, the following steps are followed: * \li 1. Get or define the dataspace for the source and destination * \li 2. Specify one or more selections for source and destination dataspaces * \li 3. Transfer data using the dataspaces with selections * * A selection is created by applying one or more selections to a dataspace. A selection may override any * other selections (#H5S_SELECT_SET) or may be “Ored” with previous selections on the same dataspace * (#H5S_SELECT_OR). In the latter case, the resulting selection is the union of the selection and all * previously selected selections. Arbitrary sets of points from a dataspace can be selected by specifying * an appropriate set of selections. * * Two selections are used in data transfer, so the source and destination must be compatible, as described * below. * * There are two forms of selection, hyperslab and point. A selection must be either a point selection or a * set of hyperslab selections. Selections cannot be mixed. * * The definition of a selection within a dataspace, not the data in the selection, cannot be saved to the * file unless the selection definition is saved as a region reference. For more information, * see \ref subsec_dataspace_refer. * *

Hyperslab Selection

* * A hyperslab is a selection of elements from a hyper rectangle. An HDF5 hyperslab is a rectangular pattern * defined by four arrays. The four arrays are summarized in the table below. * * The offset defines the origin of the hyperslab in the original dataspace. * * The stride is the number of elements to increment between selected elements. A stride of ‘1’ is every * element, a stride of ‘2’ is every second element, etc. Note that there may be a different stride for * each dimen‐sion of the dataspace. The default stride is 1. * * The count is the number of elements in the hyperslab selection. When the stride is 1, the selection is a * hyper rectangle with a corner at the offset and size count[0] by count[1] by.... When stride is greater * than one, the hyperslab bounded by the offset and the corners defined by stride[n] * count[n]. * * * * * * * * * * * * * * * * * * * * * * * *
Hyperslab elements
* Parameter * * Description *
* Offset * * The starting location for the hyperslab. *
* Stride * * The number of elements to separate each element or block to be selected. *
* Count * * The number of elements or blocks to select along each dimension. *
* Block * * The size of the block selected from the dataspace. *
* * The block is a count on the number of repetitions of the hyperslab. The default block size is '1', which is * one hyperslab. A block of 2 would be two hyperslabs in that dimension, with the second starting at * offset[n] + (count[n] * stride[n]) + 1. * * A hyperslab can be used to access a sub‐set of a large dataset. The figure below shows an example of a * hyperslab that reads a rectangle from the middle of a larger two dimensional array. The destination is the * same shape as the source. * * * * * *
* \image html Dspace_subset.gif "Access a sub‐set of data with a hyperslab" *
* * Hyperslabs can be combined to select complex regions of the source and destination. The figure below * shows an example of a transfer from one non‐rectangular region into another non‐rectangular region. The * source is defined as the union of two hyperslabs, and the destination is the union of three hyperslabs. * * * * * *
* \image html Dspace_complex.gif "Build complex regions with hyperslab unions" *
* * Hyperslabs may also be used to collect or scatter data from regular patterns. The figure below shows an * example where the source is a repeating pattern of blocks, and the destination is a single, one dimensional * array. * * * * * *
* \image html Dspace_combine.gif "Use hyperslabs to combine or disperse data" *
* *

Select Points

* * The second type of selection is an array of points such as coordinates. Essentially, this selection is a * list of all the points to include. The figure below shows an example of a transfer of seven elements from * a two dimensional dataspace to a three dimensional dataspace using a point selection to specify the points. * * * * * *
* \image html Dspace_point.gif "Point selection" *
* *

Rules for Defining Selections

* * A selection must have the same number of dimensions (rank) as the dataspace it is applied to, although it * may select from only a small region such as a plane from a 3D dataspace. Selections do not affect the * extent of the dataspace, the selection may be larger than the dataspace. The boundaries of selections are * reconciled with the extent at the time of the data transfer. * *

Data Transfer with Selections

* * A data transfer (read or write) with selections is the same as any read or write, except the source * and destination dataspace have compatible selections. * * During the data transfer, the following steps are executed by the library: * \li The source and destination dataspaces are checked to assure that the selections are compatible. * * \li The data is transferred, element by element. * * Selections have an iteration order for the points selected, which can be any permutation of the dimensions * involved (defaulting to 'C' array order) or a specific order for the selected points, for selections * composed of single array elements with \ref H5Sselect_elements. * * The elements of the selections are transferred in row‐major, or C order. That is, it is assumed that the * first dimension varies slowest, the second next slowest, and so forth. For hyperslab selections, the order * can be any permutation of the dimensions involved (defaulting to ‘C’ array order). When multiple hyperslabs * are combined, the hyperslabs are coalesced into contiguous reads and writes. * * In the case of point selections, the points are read and written in the order specified. * * \subsubsection subsubsec_dataspace_transfer_model Programming Model * *

Selecting Hyperslabs

* * Suppose we want to read a 3x4 hyperslab from a dataset in a file beginning at the element <1,2> in the * dataset, and read it into a 7 x 7 x 3 array in memory. See the figure below. In order to do this, we must * create a dataspace that describes the overall rank and dimensions of the dataset in the file as well as * the position and size of the hyperslab that we are extracting from that dataset. * * * * * *
* \image html Dspace_select.gif "Selecting a hyperslab" *
* * The code in the first example below illustrates the selection of the hyperslab in the file dataspace. * The second example below shows the definition of the destination dataspace in memory. Since the in‐memory * dataspace has three dimensions, the hyperslab is an array with three dimensions with the last dimension * being 1: <3,4,1>. The third example below shows the read using the source and destination dataspaces * with selections. * * Selecting a hyperslab * \code * //get the file dataspace. * dataspace = H5Dget_space(dataset); // dataspace identifier * * // Define hyperslab in the dataset. * offset[0] = 1; * offset[1] = 2; * count[0] = 3; * count[1] = 4; * status = H5Sselect_hyperslab(dataspace, H5S_SELECT_SET, offset, NULL, count, NULL); * \endcode * * Defining the destination memory * \code * // Define memory dataspace. * dimsm[0] = 7; * dimsm[1] = 7; * dimsm[2] = 3; * memspace = H5Screate_simple(3,dimsm,NULL); * * // Define memory hyperslab. * offset_out[0] = 3; * offset_out[1] = 0; * offset_out[2] = 0; * count_out[0] = 3; * count_out[1] = 4; * count_out[2] = 1; * status = H5Sselect_hyperslab(memspace, H5S_SELECT_SET, offset_out, NULL, count_out, NULL); * \endcode * * A sample read specifying source and destination dataspaces * \code * ret = H5Dread(dataset, H5T_NATIVE_INT, memspace,dataspace, H5P_DEFAULT, data); * \endcode * *

Example with Strides and Blocks

* * Consider an 8 x 12 dataspace into which we want to write eight 3 x 2 blocks in a two dimensional array * from a source dataspace in memory that is a 50‐element one dimensional array. See the figure below. * * * * * *
* \image html Dspace_write1to2.gif "Write from a one dimensional array to a two dimensional array" *
* * The example below shows code to write 48 elements from the one dimensional array to the file dataset * starting with the second element in vector. The destination hyperslab has the following parameters: * offset=(0,1), stride=(4,3), count=(2,4), block=(3,2). The source has the parameters: offset=(1), * stride=(1), count=(48), block=(1). After these operations, the file dataspace will have the values * shown in item b in the figure above. Notice that the values are inserted in the file dataset in * row‐major order. * * Write from a one dimensional array to a two dimensional array * \code * // Select hyperslab for the dataset in the file, using 3 x 2 blocks, (4,3) stride (2,4) * // count starting at the position (0,1). * offset[0] = 0; offset[1] = 1; * stride[0] = 4; stride[1] = 3; * count[0] = 2; count[1] = 4; * block[0] = 3; block[1] = 2; * ret = H5Sselect_hyperslab(fid, H5S_SELECT_SET, offset, stride, count, block); * * // Create dataspace for the first dataset. * mid1 = H5Screate_simple(MSPACE1_RANK, dim1, NULL); * * // Select hyperslab. * // We will use 48 elements of the vector buffer starting * // at the second element. Selected elements are * // 1 2 3 . . . 48 * offset[0] = 1; * stride[0] = 1; * count[0] = 48; * block[0] = 1; * ret = H5Sselect_hyperslab(mid1, H5S_SELECT_SET, offset, stride, count, block); * * // Write selection from the vector buffer to the dataset in the file. * ret = H5Dwrite(dataset, H5T_NATIVE_INT, midd1, fid, H5P_DEFAULT, vector) * \endcode * *

Selecting a Union of Hyperslabs

* * The HDF5 Library allows the user to select a union of hyperslabs and write or read the selection into * another selection. The shapes of the two selections may differ, but the number of elements must be * equal. * * * * * *
* \image html Dspace_transfer.gif "Transferring hyperslab unions" *
* * The figure above shows the transfer of a selection that is two overlapping hyperslabs from the dataset * into a union of hyperslabs in the memory dataset. Note that the destination dataset has a different shape * from the source dataset. Similarly, the selection in the memory dataset could have a different shape than * the selected union of hyperslabs in the original file. For simplicity, the selection is that same shape * at the destination. * * To implement this transfer, it is necessary to: * \li 1. Get the source dataspace * \li 2. Define one hyperslab selection for the source * \li 3. Define a second hyperslab selection, unioned with the first * \li 4. Get the destination dataspace * \li 5. Define one hyperslab selection for the destination * \li 6. Define a second hyperslab selection, unioned with the first * \li 7. Execute the data transfer (H5Dread or H5Dwrite) using the source and destination dataspaces * * The example below shows example code to create the selections for the source dataspace (the file). The * first hyperslab is size 3 x 4 and the left upper corner at the position (1,2). The hyperslab is a simple * rectangle, so the stride and block are 1. The second hyperslab is 6 x 5 at the position (2,4). The second * selection is a union with the first hyperslab (#H5S_SELECT_OR). * * Select source hyperslabs * \code * fid = H5Dget_space(dataset); * * // Select first hyperslab for the dataset in the file. * offset[0] = 1; offset[1] = 2; * block[0] = 1; block[1] = 1; * stride[0] = 1; stride[1] = 1; * count[0] = 3; count[1] = 4; * ret = H5Sselect_hyperslab(fid, H5S_SELECT_SET, offset, stride, count, block); * * // Add second selected hyperslab to the selection. * offset[0] = 2; offset[1] = 4; * block[0] = 1; block[1] = 1; * stride[0] = 1; stride[1] = 1; * count[0] = 6; count[1] = 5; * ret = H5Sselect_hyperslab(fid, H5S_SELECT_OR, offset, stride, count, block); * \endcode * * The example below shows example code to create the selection for the destination in memory. The steps * are similar. In this example, the hyperslabs are the same shape, but located in different positions in the * dataspace. The first hyperslab is 3 x 4 and starts at (0,0), and the second is 6 x 5 and starts at (1,2). * Finally, the H5Dread call transfers the selected data from the file dataspace to the selection in memory. * In this example, the source and destination selections are two overlapping rectangles. In general, any * number of rectangles can be OR’ed, and they do not have to be contiguous. The order of the selections * does not matter, but the first should use #H5S_SELECT_SET ; subsequent selections are unioned using * #H5S_SELECT_OR. * * It is important to emphasize that the source and destination do not have to be the same shape (or number * of rectangles). As long as the two selections have the same number of elements, the data can be * transferred. * * Select destination hyperslabs * \code * // Create memory dataspace. * mid = H5Screate_simple(MSPACE_RANK, mdim, NULL); * * // Select two hyperslabs in memory. Hyperslabs has the * // same size and shape as the selected hyperslabs for * // the file dataspace. * offset[0] = 0; offset[1] = 0; * block[0] = 1; block[1] = 1; * stride[0] = 1; stride[1] = 1; * count[0] = 3; count[1] = 4; * ret = H5Sselect_hyperslab(mid, H5S_SELECT_SET, offset, stride, count, block); * * offset[0] = 1; offset[1] = 2; * block[0] = 1; block[1] = 1; * stride[0] = 1; stride[1] = 1; * count[0] = 6; count[1] = 5; * ret = H5Sselect_hyperslab(mid, H5S_SELECT_OR, offset, stride, count, block); * * ret = H5Dread(dataset, H5T_NATIVE_INT, mid, fid, H5P_DEFAULT, matrix_out); * \endcode * *

Selecting a List of Independent Points

* * It is also possible to specify a list of elements to read or write using the function H5Sselect_elements. * * The procedure is similar to hyperslab selections. * \li 1. Get the source dataspace * \li 2. Set the selected points * \li 3. Get the destination dataspace * \li 4. Set the selected points * \li 5. Transfer the data using the source and destination dataspaces * * The figure below shows an example where four values are to be written to four separate points in a two * dimensional dataspace. The source dataspace is a one dimensional array with the values 53, 59, 61, 67. * The destination dataspace is an 8 x 12 array. The elements are to be written to the points * (0,0), (3,3), (3,5), and (5,6). In this example, the source does not require a selection. The example * below the figure shows example code to implement this transfer. * * A point selection lists the exact points to be transferred and the order they will be transferred. The * source and destination are required to have the same number of elements. A point selection can be used * with a hyperslab (for example, the source could be a point selection and the destination a hyperslab, * or vice versa), so long as the number of elements selected are the same. * * * * * *
* \image html Dspace_separate.gif "Write data to separate points" *
* * Write data to separate points * \code * hsize_t dim2[] = {4}; * int values[] = {53, 59, 61, 67}; * * // file dataspace * hssize_t coord[4][2]; * * // Create dataspace for the second dataset. * mid2 = H5Screate_simple(1, dim2, NULL); * * // Select sequence of NPOINTS points in the file dataspace. * coord[0][0] = 0; coord[0][1] = 0; * coord[1][0] = 3; coord[1][1] = 3; * coord[2][0] = 3; coord[2][1] = 5; * coord[3][0] = 5; coord[3][1] = 6; * * ret = H5Sselect_elements(fid, H5S_SELECT_SET, NPOINTS, (const hssize_t **)coord); * * ret = H5Dwrite(dataset, H5T_NATIVE_INT, mid2, fid, H5P_DEFAULT, values); * \endcode * *

Combinations of Selections

* * Selections are a very flexible mechanism for reorganizing data during a data transfer. With different * combinations of dataspaces and selections, it is possible to implement many kinds of data transfers * including sub‐setting, sampling, and reorganizing the data. The table below gives some example combinations * of source and destination, and the operations they implement. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
Selection operations
*

Source

* 		*

Destination

* 		*

Operation

*
*

All

* 		*

All

* 		*

Copy whole array

*
*

All

* 		*

All (different shape)

* 		*

Copy and reorganize array

*
*

Hyperslab

* 		*

All

* 		*

Sub-set

*
*

Hyperslab

* 		*

Hyperslab (same shape)

* 		*

Selection

*
*

Hyperslab

* 		*

Hyperslab (different shape)

* 		*

Select and rearrange

*
*

Hyperslab with stride or block

* 		*

All or hyperslab with stride 1

* 		*

Sub-sample, scatter

*
*

Hyperslab

* 		*

Points

* 		*

Scatter

*
*

Points

* 		*

Hyperslab or all

* 		*

Gather

*
*

Points

* 		*

Points (same)

* 		*

Selection

*
*

Points

* 		*

Points (different)

* 		*

Reorder points

*
* * \subsection subsec_dataspace_select Dataspace Selection Operations and Data Transfer * * This section is under construction. * * \subsection subsec_dataspace_refer References to Dataset Regions * * Another use of selections is to store a reference to a region of a dataset. An HDF5 object reference * object is a pointer to an object (dataset, group, or committed datatype) in the file. A selection can * be used to create a pointer to a set of selected elements of a dataset, called a region reference. The * selection can be either a point selection or a hyperslab selection. * * A region reference is an object maintained by the HDF5 Library. The region reference can be stored in a * dataset or attribute, and then read. The dataset or attribute is defined to have the special datatype, * #H5T_STD_REF_DSETREG. * * To discover the elements and/or read the data, the region reference can be dereferenced. The * #H5Rdereference call returns an identifier for the dataset, and then the selected dataspace can be * retrieved with a call to #H5Rget_region(). The selected dataspace can be used to read the selected data * elements. * * For more information, \see subsubsec_datatype_other_refs. * * \subsubsection subsubsec_dataspace_refer_use Example Uses for Region References * * Region references are used to implement stored pointers to data within a dataset. For example, features * in a large dataset might be indexed by a table. See the figure below. This table could be stored as an * HDF5 dataset with a compound datatype, for example, with a field for the name of the feature and a region * reference to point to the feature in the dataset. See the second figure below. * * * * * *
* \image html Dspace_features.gif " Features indexed by a table" *
* * * * * *
* \image html Dspace_features_cmpd.gif "Storing the table with a compound datatype" *
* * * \subsubsection subsubsec_dataspace_refer_create Creating References to Regions * * To create a region reference: * \li 1. Create or open the dataset that contains the region * \li 2. Get the dataspace for the dataset * \li 3. Define a selection that specifies the region * \li 4. Create a region reference using the dataset and dataspace with selection * \li 5. Write the region reference(s) to the desired dataset or attribute * * The figure below shows a diagram of a file with three datasets. Dataset D1 and D2 are two dimensional * arrays of integers. Dataset R1 is a one dimensional array of references to regions in D1 and D2. The * regions can be any valid selection of the dataspace of the target dataset. * * * * *
* \image html Dspace_three_datasets.gif "A file with three datasets" *
* Note: In the figure above, R1 is a 1 D array of region pointers; each pointer refers to a selection * in one dataset. * * The example below shows code to create the array of region references. The references are created in an * array of type #hdset_reg_ref_t. Each region is defined as a selection on the dataspace of the dataset, * and a reference is created using \ref H5Rcreate(). The call to \ref H5Rcreate() specifies the file, * dataset, and the dataspace with selection. * * Create an array of region references * \code * // create an array of 4 region references * hdset_reg_ref_t ref[4]; * * // Create a reference to the first hyperslab in the first Dataset. * offset[0] = 1; offset[1] = 1; * count[0] = 3; count[1] = 2; * status = H5Sselect_hyperslab(space_id, H5S_SELECT_SET, offset, NULL, count, NULL); * status = H5Rcreate(&ref[0], file_id, "D1", H5R_DATASET_REGION, space_id); * * // The second reference is to a union of hyperslabs in the first Dataset * offset[0] = 5; offset[1] = 3; * count[0] = 1; count[1] = 4; * status = H5Sselect_none(space_id); * status = H5Sselect_hyperslab(space_id, H5S_SELECT_SET, offset, NULL, count, NULL); * offset[0] = 6; offset[1] = 5; * count[0] = 1; count[1] = 2; * status = H5Sselect_hyperslab(space_id, H5S_SELECT_OR, offset, NULL, count, NULL); * status = H5Rcreate(&ref[1], file_id, "D1", H5R_DATASET_REGION, space_id); * * // the fourth reference is to a selection of points in the first Dataset * status = H5Sselect_none(space_id); * coord[0][0] = 4; coord[0][1] = 4; * coord[1][0] = 2; coord[1][1] = 6; * coord[2][0] = 3; coord[2][1] = 7; * coord[3][0] = 1; coord[3][1] = 5; * coord[4][0] = 5; coord[4][1] = 8; * * status = H5Sselect_elements(space_id, H5S_SELECT_SET, num_points, (const hssize_t **)coord); * status = H5Rcreate(&ref[3], file_id, "D1", H5R_DATASET_REGION, space_id); * * // the third reference is to a hyperslab in the second Dataset * offset[0] = 0; offset[1] = 0; * count[0] = 4; count[1] = 6; * status = H5Sselect_hyperslab(space_id2, H5S_SELECT_SET, offset, NULL, count, NULL); * status = H5Rcreate(&ref[2], file_id, "D2", H5R_DATASET_REGION, space_id2); * \endcode * * When all the references are created, the array of references is written to the dataset R1. The * dataset is declared to have datatype #H5T_STD_REF_DSETREG. See the example below. * * Write the array of references to a dataset * \code * Hsize_t dimsr[1]; * dimsr[0] = 4; * * // Dataset with references. * spacer_id = H5Screate_simple(1, dimsr, NULL); * dsetr_id = H5Dcreate(file_id, "R1", H5T_STD_REF_DSETREG, spacer_id, H5P_DEFAULT, H5P_DEFAULT, * H5P_DEFAULT); * * // Write dataset with the references. * status = H5Dwrite(dsetr_id, H5T_STD_REF_DSETREG, H5S_ALL, H5S_ALL, H5P_DEFAULT, ref); * * \endcode * * When creating region references, the following rules are enforced. * \li The selection must be a valid selection for the target dataset, just as when transferring data * \li The dataset must exist in the file when the reference is created; #H5Rcreate * \li The target dataset must be in the same file as the stored reference * * \subsubsection subsubsec_dataspace_refer_read Reading References to Regions * * To retrieve data from a region reference, the reference must be read from the file, and then the data can * be retrieved. The steps are: * \li 1. Open the dataset or attribute containing the reference objects * \li 2. Read the reference object(s) * \li 3. For each region reference, get the dataset (#H5Rdereference) and dataspace (#H5Rget_region) * \li 4. Use the dataspace and datatype to discover what space is needed to store the data, allocate the * correct storage and create a dataspace and datatype to define the memory data layout * * The example below shows code to read an array of region references from a dataset, and then read the * data from the first selected region. Note that the region reference has information that records the * dataset (within the file) and the selection on the dataspace of the dataset. After dereferencing the * regions reference, the datatype, number of points, and some aspects of the selection can be discovered. * (For a union of hyperslabs, it may not be possible to determine the exact set of hyperslabs that has been * combined.) * The table below the code example shows the inquiry functions. * * When reading data from a region reference, the following rules are enforced: * \li The target dataset must be present and accessible in the file * \li The selection must be a valid selection for the dataset * * Read an array of region references; read from the first selection * \code * dsetr_id = H5Dopen (file_id, "R1", H5P_DEFAULT); * status = H5Dread(dsetr_id, H5T_STD_REF_DSETREG, H5S_ALL, H5S_ALL, H5P_DEFAULT, ref_out); * * // Dereference the first reference. * // 1) get the dataset (H5Rdereference) * // 2) get the selected dataspace (H5Rget_region) * * dsetv_id = H5Rdereference(dsetr_id, H5R_DATASET_REGION, &ref_out[0]); * space_id = H5Rget_region(dsetr_id, H5R_DATASET_REGION, &ref_out[0]); * * // Discover how many points and shape of the data * ndims = H5Sget_simple_extent_ndims(space_id); * H5Sget_simple_extent_dims(space_id,dimsx,NULL); * * // Read and display hyperslab selection from the dataset. * dimsy[0] = H5Sget_select_npoints(space_id); * spacex_id = H5Screate_simple(1, dimsy, NULL); * * status = H5Dread(dsetv_id, H5T_NATIVE_INT, H5S_ALL, space_id, H5P_DEFAULT, data_out); * printf("Selected hyperslab: "); * for (i = 0; i < 8; i++) { * printf("\n"); * for (j = 0; j < 10; j++) * printf("%d ", data_out[i][j]); * } * printf("\n"); * \endcode * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
The inquiry functions
*

Function

* 		*

Information

*
* @ref H5Sget_select_npoints * *

The number of elements in the selection (hyperslab or point selection).

*
* @ref H5Sget_select_bounds * *

The bounding box that encloses the selected points (hyperslab or point selection).

*
* @ref H5Sget_select_hyper_nblocks * *

The number of blocks in the selection.

*
* @ref H5Sget_select_hyper_blocklist * *

A list of the blocks in the selection.

*
* @ref H5Sget_select_elem_npoints * *

The number of points in the selection.

*
* @ref H5Sget_select_elem_pointlist * *

The points.

*
* * * \subsection subsec_dataspace_sample Sample Programs * * This section contains the full programs from which several of the code examples in this chapter were * derived. The h5dump output from the program's output file immediately follows each program. * * h5_write.c * \code * #include "hdf5.h" * * #define H5FILE_NAME "SDS.h5" * #define DATASETNAME "C Matrix" * #define NX 3 * #define NY 5 * #define RANK 2 // dataset dimensions * * int * main (void) * { * hid_t file, dataset; // file and dataset identifiers * hid_t datatype, dataspace; // identifiers * hsize_t dims[2]; // dataset dimensions * herr_t status; * int data[NX][NY]; // data to write * int i, j; * * // * // Data and output buffer initialization. * for (j = 0; j < NX; j++) { * for (i = 0; i < NY; i++) * data[j][i] = i + 1 + j*NY; * } * // 1 2 3 4 5 * // 6 7 8 9 10 * // 11 12 13 14 15 * * // Create a new file using H5F_ACC_TRUNC access, * // default file creation properties, and default file * // access properties. * file = H5Fcreate(H5FILE_NAME, H5F_ACC_TRUNC, H5P_DEFAULT, H5P_DEFAULT); * * // Describe the size of the array and create the data space for fixed * // size dataset. * dims[0] = NX; * dims[1] = NY; * dataspace = H5Screate_simple(RANK, dims, NULL); * * // Create a new dataset within the file using defined dataspace and * // datatype and default dataset creation properties. * dataset = H5Dcreate(file, DATASETNAME, H5T_NATIVE_INT, dataspace, H5P_DEFAULT, * H5P_DEFAULT, H5P_DEFAULT); * * // Write the data to the dataset using default transfer properties. * status = H5Dwrite(dataset, H5T_NATIVE_INT, H5S_ALL, H5S_ALL, H5P_DEFAULT, data); * * // Close/release resources. * H5Sclose(dataspace); * H5Dclose(dataset); * H5Fclose(file); * * return 0; * } * * SDS.out * ------- * HDF5 "SDS.h5" { * GROUP "/" { * DATASET "C Matrix" { * DATATYPE H5T_STD_I32BE * DATASPACE SIMPLE { ( 3, 5 ) / ( 3, 5 ) } * DATA { * 1, 2, 3, 4, 5, * 6, 7, 8, 9, 10, * 11, 12, 13, 14, 15 * } * } * * \endcode * * h5_write.f90 * \code * ---------- * PROGRAM DSETEXAMPLE * * USE HDF5 ! This module contains all necessary modules * * IMPLICIT NONE * * CHARACTER(LEN=7), PARAMETER :: filename = "SDSf.h5" ! File name * CHARACTER(LEN=14), PARAMETER :: dsetname = "Fortran Matrix" ! Dataset name * INTEGER, PARAMETER :: NX = 3 * INTEGER, PARAMETER :: NY = 5 * * INTEGER(HID_T) :: file_id ! File identifier * INTEGER(HID_T) :: dset_id ! Dataset identifier * INTEGER(HID_T) :: dspace_id ! Dataspace identifier * * INTEGER(HSIZE_T), DIMENSION(2) :: dims = (/3,5/) ! Dataset dimensions * INTEGER :: rank = 2 ! Dataset rank * INTEGER :: data(NX,NY) * INTEGER :: error ! Error flag * INTEGER :: i, j * * ! * ! Initialize data * ! * do i = 1, NX * do j = 1, NY * data(i,j) = j + (i-1)*NY * enddo * enddo * ! * ! Data * ! * ! 1 2 3 4 5 * ! 6 7 8 9 10 * ! 11 12 13 14 15 * * ! * ! Initialize FORTRAN interface. * ! * CALLh5open_f(error) * * ! * ! Create a new file using default properties. * ! * CALL h5fcreate_f(filename, H5F_ACC_TRUNC_F, file_id, error) * * ! * ! Create the dataspace. * ! * CALL h5screate_simple_f(rank, dims, dspace_id, error) * * ! * ! Create and write dataset using default properties. * ! * CALL h5dcreate_f(file_id, dsetname, H5T_NATIVE_INTEGER, dspace_id, & * dset_id, error, H5P_DEFAULT_F, H5P_DEFAULT_F, & * H5P_DEFAULT_F) * * CALL h5dwrite_f(dset_id, H5T_NATIVE_INTEGER, data, dims, error) * * ! * ! End access to the dataset and release resources used by it. * ! * CALL h5dclose_f(dset_id, error) * * ! * ! Terminate access to the data space. * ! * CALL h5sclose_f(dspace_id, error) * * ! * ! Close the file. * ! * CALL h5fclose_f(file_id, error) * * ! * ! Close FORTRAN interface. * ! * CALL h5close_f(error) * * END PROGRAM DSETEXAMPLE * * SDSf.out * -------- * HDF5 "SDSf.h5" { * GROUP "/" { * DATASET "Fortran Matrix" { * DATATYPE H5T_STD_I32BE * DATASPACE SIMPLE { ( 5, 3 ) / ( 5, 3 ) } * DATA { * 1, 6, 11, * 2, 7, 12, * 3, 8, 13, * 4, 9, 14, * 5, 10, 15 * } * } * } * } * * \endcode * * h5_write_tr.f90 * \code * PROGRAM DSETEXAMPLE * * USE HDF5 ! This module contains all necessary modules * * IMPLICIT NONE * * CHARACTER(LEN=10), PARAMETER :: filename = "SDSf_tr.h5" ! File name * CHARACTER(LEN=24), PARAMETER :: dsetname = "Fortran Transpose Matrix"! Dataset name * * INTEGER, PARAMETER :: NX = 3 * INTEGER, PARAMETER :: NY = 5 * * INTEGER(HID_T) :: file_id ! File identifier * INTEGER(HID_T) :: dset_id ! Dataset identifier * INTEGER(HID_T) :: dspace_id ! Dataspace identifier * * INTEGER(HSIZE_T), DIMENSION(2) :: dims = (/NY, NX/) ! Dataset dimensions * INTEGER :: rank = 2 ! Dataset rank * INTEGER :: data(NY,NX) * * INTEGER :: error ! Error flag * INTEGER :: i, j * * ! * ! Initialize data * ! * do i = 1, NY * do j = 1, NX * data(i,j) = i + (j-1)*NY * enddo * enddo * * ! * ! Data * ! * ! 1 6 11 * ! 2 7 12 * ! 3 8 13 * ! 4 9 14 * ! 5 10 15 * * ! * ! Initialize FORTRAN interface. * ! * CALL h5open_f(error) * * ! * ! Create a new file using default properties. * ! * CALL h5fcreate_f(filename, H5F_ACC_TRUNC_F, file_id, error) * * ! * ! Create the dataspace. * ! * CALL h5screate_simple_f(rank, dims, dspace_id, error) * * ! * ! Create and write dataset using default properties. * ! * CALL h5dcreate_f(file_id, dsetname, H5T_NATIVE_INTEGER, dspace_id, & * dset_id, error, H5P_DEFAULT_F, H5P_DEFAULT_F, & * H5P_DEFAULT_F) * CALL h5dwrite_f(dset_id, H5T_NATIVE_INTEGER, data, dims, error) * * ! * ! End access to the dataset and release resources used by it. * ! * CALL h5dclose_f(dset_id, error) * * ! * ! Terminate access to the data space. * ! * CALL h5sclose_f(dspace_id, error) * * ! * ! Close the file. * ! * CALL h5fclose_f(file_id, error) * * ! * ! Close FORTRAN interface. * ! * CALL h5close_f(error) * * END PROGRAM DSETEXAMPLE * * SDSf_tr.out * ----------- * HDF5 "SDSf_tr.h5" { * GROUP "/" { * DATASET "Fortran Transpose Matrix" { * DATATYPE H5T_STD_I32LE * DATASPACE SIMPLE { ( 3, 5 ) / ( 3, 5 ) } * DATA { * 1, 2, 3, 4, 5, * 6, 7, 8, 9, 10, * 11, 12, 13, 14, 15 * } * } * } * } * * \endcode * * Previous Chapter \ref sec_datatype - Next Chapter \ref sec_attribute * */ /** * \defgroup H5S Dataspaces (H5S) * * Use the functions in this module to manage HDF5 dataspaces \Emph{and} selections. * * HDF5 dataspaces describe the \Emph{shape} of datasets in memory or in HDF5 * files. Dataspaces can be empty (#H5S_NULL), a singleton (#H5S_SCALAR), or * a multi-dimensional, regular grid (#H5S_SIMPLE). Dataspaces can be re-shaped. * * Subsets of dataspaces can be "book-marked" or used to restrict I/O operations * using \Emph{selections}. Furthermore, certain set operations are supported * for selections. * * */ #endif /* H5Smodule_H */