import h5py
import numpy as np

# Open hdf5 file in read mode
h5f = h5py.File('bn_dist_z2.h5', 'r')

# Extract the thermal properties
thermal_properties = h5f['Thermal_properties'].value

# Unpack information, note that there is a column with identifiers
identifiers, logT0s, gammas, lam_Ps = np.transpose(thermal_properties)

# Parameters were saved as string, so let's transform them into np arrays of floats
logT0s, gammas, lam_Ps = np.array(logT0s, dtype=float), np.array(
    gammas, dtype=float), np.array(lam_Ps, dtype=float)

# Any desired b-N distribution can be retrieved using the identifiers.
# For instance the identifier with index 20 is
index = 20
print('Id : {}'.format(identifiers[index].decode()))

# With corresponding thermal Parameters
print('logT0 = {}, gamma = {}, lambdaP {}'.format(logT0s[index], gammas[index], lam_Ps[index]))

# To retrieve the corresponding logb vs. logNHI distribution simply call the h5f object
# using the identifier as key
bN_data = h5f[identifiers[index]].value

h5f.close()