jamesmudd

// ignores the higher 16 bits
public static float toFloat( int hbits )
{
    int mant = hbits & 0x03ff;            // 10 bits mantissa
    int exp =  hbits & 0x7c00;            // 5 bits exponent
    if( exp == 0x7c00 )                   // NaN/Inf
        exp = 0x3fc00;                    // -> NaN/Inf
    else if( exp != 0 )                   // normalized value
    {
        exp += 0x1c000;                   // exp - 15 + 127

jamesmudd

import numpy as np
import h5py

if __name__ == '__main__':
    print('Making large attribute test files...')

    # Can only work with latest
    f = h5py.File('large_attribute.hdf5', 'w', libver='latest')

    # Small test dataset with large attributes

jamesmudd

from tables import *
import numpy as np

# Open a file in "w"rite mode
file = open_file("bitfield.hdf5", mode ="w")

# Create the last table in group2
data = [bool(i % 2) for i in range(15)]
file.create_array("/", "bitfield", data)
file.create_carray("/", "chnunked_bitfield", chunkshape=(2,), obj=data)

jamesmudd

#-------------------------------------------------------------------------------
# This file is part of jHDF. A pure Java library for accessing HDF5 files.
# 
# http://jhdf.io
# 
# Copyright 2019 James Mudd
# 
# MIT License see 'LICENSE' file
#-------------------------------------------------------------------------------
import h5py

jamesmudd

package examples.datasets;

import static java.util.stream.Collectors.joining;

import java.io.File;
import java.lang.reflect.Array;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.HashMap;
import java.util.List;