Example 2: Storing Green’s functions

What about more complex objects? The good news is that hdf-compliant objects, such as Green’s functions, can be stored easily as well:

from pytriqs.archive import HDFArchive
from pytriqs.gf import GfImFreq

# Define a Green function
G = GfImFreq ( indices = [1], beta = 10, n_points = 1000)

# Opens the file myfile.h5, in read/write mode
R = HDFArchive('myfile.h5', 'w')
# Store the object G under the name 'g1' and mu
R['g1'] = G
R['mu'] = 1.29
del R # closing the files (optional: file is closed when the R reference is deleted)

Of course, we can retrieve G as easily:

from pytriqs.archive import HDFArchive
from pytriqs.gf import GfImFreq

R = HDFArchive('myfile.h5', 'r')  # Opens the file myfile.h5 in readonly mode
G = R['g1'] # Retrieve the object named g1 in the file as G

# ... ok now I can work with G

This time, the structure of the HDF file is

$>h5ls -r  myfile.h5
/                        Group
/g1                      Group
/g1/Data                 Dataset {2, 2, 1000}
/g1/Indices              Dataset {2}
/g1/Mesh                 Group
/g1/Mesh/Beta            Dataset {SCALAR}
/g1/Mesh/Statistic       Dataset {SCALAR}
/g1/Mesh/TypeGF          Dataset {SCALAR}
/g1/Mesh/array           Dataset {1000}
/g1/Name                 Dataset {SCALAR}
/g1/Note                 Dataset {SCALAR}
/mu                      Dataset {SCALAR}

Hint

How does this work ?

The Green function implements (as detailed in Hdf-compliant objects)

• a method __reduce_to_dict__() that reduces to the Green function to a dictionary containing a mesh (Mesh), the data (Data), the indices (Indices) and so on.
• a classmethod __factory_from_dict__() that reconstructs the Green function from this dictionary.