Qutip object serialization

qutip_serialization.py

import msgpack
import msgpack_numpy
import pandas as pd
import qutip
from scipy.sparse import csr_matrix

def serialize_csr(arr):
	## Switch to coo format
	coo = arr.tocoo()
	## Separate into the components we need to reconstruct it
	out_dict = {"data": coo.data,
				"col": coo.col,
				"row": coo.row,
				"shape": coo.shape}
	## Return serialized string
	return msgpack.packb(out_dict, default=msgpack_numpy.encode)
def deserialize_csr(bstr):
	## Unpack into dict with components
	coo_dict = msgpack.unpackb(bstr, object_hook=msgpack_numpy.decode)
	## Re-create array with components
	out_arr = csr_matrix((coo_dict["data"], 
						 (coo_dict["row"], coo_dict["col"])),
						 shape=coo_dict["shape"])
	return out_arr


def serialize_qobj(qobj):
	"""
	Serialize a qutip Qobj instance
	"""
	data = serialize_csr(qobj.data)
	dims = qobj.dims
	## Construct a dict
	out_dict = {"data": data, "dims": dims}
	## Serialize the dict
	serial_dict = msgpack.packb(out_dict)
	return serial_dict
def deserialize_qobj(bstr):
	## Unpack bitstring
	in_dict = msgpack.unpackb(bstr)
	## Assign components
	data = deserialize_csr(in_dict["data"])
	dims = in_dict["dims"]
	## Reconstruct qobj
	qobj = qutip.Qobj(inpt=data, dims=dims)
	return qobj


def serialize_df_numeric(data_df):
	"""Serialize a DataFrame containing only numeric dtypes"""
	return msgpack.packb(data_df.to_dict(orient="split"))
def deserialize_df_numeric(bstr):
	"""Deserialize a DataFrame containing only numeric dtypes"""
	return pd.DataFrame(**msgpack.unpackb(bstr))