If you are interested, the HighFive hdf5 C++ bindings allow you to read / write
any 2 dimensional using boost::ublas::matrix with only few lines of codes :
https://github.com/BlueBrain/HighFive/blob/master/src/examples/boost_ublas_double.cpp
PS: I am one of the author of HighFive.
Regards,
Adrien Devresse
On July 19, 2017 8:32:40 PM GMT+02:00, "Nelson, Jarom" <nelso...@llnl.gov>
wrote:
>I think for a variable size multidimensional array in C++, it's more
>common to just use a one-dimensional array, and do the array indexing
>math yourself (or with inline utility methods). Using an array of
>pointers to arrays just adds extra levels of indirection, more memory
>lookups, slower code.
>
>Your second code snippet will not work, because the H5Dread is going to
>write the values to the buffer directly, not to the arrays pointed to
>by the buffer. You'll want to do this instead:
>T* buffer = new T[dims[1] * dims[0]];
>
>Rather than trying to shoehorn the built-in multi-dim array syntax for
>your array by using the array of pointers, consider building up a
>wrapper class that owns the single-dim array, and having inline
>accessor methods can help with the semantics of lookup. And internally,
>you can have it use smart pointers, or ensure aligned data, or
>whatever. Then you can have something like:
>
>ArrayWrapper<double> v(128,256);
>v.value(123,234) = 1234.5678;
>cout << v.value(1,2) << endl;
>
>H5Dread(dataset_id, dataset_type_id, H5S_ALL, H5S_ALL, H5P_DEFAULT,
>v.data());
>
>Your compiler should be able to inline the calls to .value() so that it
>is equivalent to v.data()[v.xsize()*y + x]. If not, it will still be
>much faster than loading the address of a sub-array from memory and
>then reading from that address. (as long as your access patterns match
>the memory layout of the array)
>
>Jarom
>
>From: Hdf-forum [mailto:hdf-forum-boun...@lists.hdfgroup.org] On Behalf
>Of Deepak 8 Kumar
>Sent: Wednesday, July 19, 2017 6:50 AM
>To: hdf-forum@lists.hdfgroup.org
>Subject: [Hdf-forum] Reading dataset values with number of dimension 2.
>
>I have a HDF5 based application to read the hdf5 file which has dataset
>values with number of dimensions 2. I am using HDF 1.10.1 Windows10
>x64.
>I allocate array of pointers to read the data values in the same way as
>given in the hdf5 documentation. Here is the code which is reading the
>dataset values.
>In this code, the dynamic 2D array of pointers is not initialized as
>per the standard way using a loop.
>
>unique_ptr<T*[]> apbuffer = make_unique<T*[]>(size_of_dimensions[0]);
>T** buffer = apbuffer.get();
>unique_ptr<T[]> apbuffer1 = make_unique<T[]>(size_of_dimensions[0] *
>size_of_dimensions[1]);
>buffer[0] = apbuffer1.get();
>for (int i = 1; i < size_of_dimensions[0]; i++) {
> buffer[i] = buffer[0] + i * size_of_dimensions[1];
>}
>H5Dread(dataset_id, dataset_type_id, H5S_ALL, H5S_ALL, H5P_DEFAULT,
>buffer[0]);
>
>Can we allocate the buffer like the below code?
>T** buffer= new T*[dims[0]];
>for(int i = 0; i < dims[0]; ++i)
> buffer[i] = new T[dims[1]];
>
>I would like to know, what are other possible ways to allocate the
>buffer to read 2 dimension dataset values?
>Any insight is greatly appreciated.
--
Sent from my Android device with K-9 Mail. Please excuse my brevity._______________________________________________
Hdf-forum is for HDF software users discussion.
Hdf-forum@lists.hdfgroup.org
http://lists.hdfgroup.org/mailman/listinfo/hdf-forum_lists.hdfgroup.org
Twitter: https://twitter.com/hdf5
