# This file is part of QuTiP: Quantum Toolbox in Python.
#
# Copyright (c) 2011 and later, Paul D. Nation and Robert J. Johansson.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# 1. Redistributions of source code must retain the above copyright notice,
# this list of conditions and the following disclaimer.
#
# 2. Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
#
# 3. Neither the name of the QuTiP: Quantum Toolbox in Python nor the names
# of its contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
###############################################################################
__all__ = ['file_data_store', 'file_data_read', 'qsave', 'qload']
import pickle
import numpy as np
from qutip.qobj import Qobj
from qutip.solver import Result
# -----------------------------------------------------------------------------
# Write matrix data to a file
#
[docs]def file_data_store(filename, data, numtype="complex", numformat="decimal",
sep=","):
"""Stores a matrix of data to a file to be read by an external program.
Parameters
----------
filename : str
Name of data file to be stored, including extension.
data: array_like
Data to be written to file.
numtype : str {'complex, 'real'}
Type of numerical data.
numformat : str {'decimal','exp'}
Format for written data.
sep : str
Single-character field seperator. Usually a tab, space, comma,
or semicolon.
"""
if filename is None or data is None:
raise ValueError("filename or data is unspecified")
M, N = np.shape(data)
f = open(filename, "w")
f.write("# Generated by QuTiP: %dx%d %s matrix " % (M, N, numtype) +
"in %s format ['%s' separated values].\n" % (numformat, sep))
if numtype == "complex":
if numformat == "exp":
for m in range(M):
for n in range(N):
if np.imag(data[m, n]) >= 0.0:
f.write("%.10e+%.10ej" % (np.real(data[m, n]),
np.imag(data[m, n])))
else:
f.write("%.10e%.10ej" % (np.real(data[m, n]),
np.imag(data[m, n])))
if n != N - 1:
f.write(sep)
f.write("\n")
elif numformat == "decimal":
for m in range(M):
for n in range(N):
if np.imag(data[m, n]) >= 0.0:
f.write("%.10f+%.10fj" % (np.real(data[m, n]),
np.imag(data[m, n])))
else:
f.write("%.10f%.10fj" % (np.real(data[m, n]),
np.imag(data[m, n])))
if n != N - 1:
f.write(sep)
f.write("\n")
else:
raise ValueError("Illegal numformat value (should be " +
"'exp' or 'decimal')")
elif numtype == "real":
if numformat == "exp":
for m in range(M):
for n in range(N):
f.write("%.10e" % (np.real(data[m, n])))
if n != N - 1:
f.write(sep)
f.write("\n")
elif numformat == "decimal":
for m in range(M):
for n in range(N):
f.write("%.10f" % (np.real(data[m, n])))
if n != N - 1:
f.write(sep)
f.write("\n")
else:
raise ValueError("Illegal numformat value (should be " +
"'exp' or 'decimal')")
else:
raise ValueError("Illegal numtype value (should be " +
"'complex' or 'real')")
f.close()
# -----------------------------------------------------------------------------
# Read matrix data from a file
#
[docs]def file_data_read(filename, sep=None):
"""Retrieves an array of data from the requested file.
Parameters
----------
filename : str
Name of file containing reqested data.
sep : str
Seperator used to store data.
Returns
-------
data : array_like
Data from selected file.
"""
if filename is None:
raise ValueError("filename is unspecified")
f = open(filename, "r")
#
# first count lines and numbers of
#
M = N = 0
for line in f:
# skip comment lines
if line[0] == '#' or line[0] == '%':
continue
# find delim
if N == 0 and sep is None:
if len(line.rstrip().split(",")) > 1:
sep = ","
elif len(line.rstrip().split(";")) > 1:
sep = ";"
elif len(line.rstrip().split(":")) > 1:
sep = ":"
elif len(line.rstrip().split("|")) > 1:
sep = "|"
elif len(line.rstrip().split()) > 1:
# sepical case for a mix of white space deliminators
sep = None
else:
raise ValueError("Unrecognized column deliminator")
# split the line
line_vec = line.split(sep)
n = len(line_vec)
if N == 0 and n > 0:
N = n
# check type
if ("j" in line_vec[0]) or ("i" in line_vec[0]):
numtype = "complex"
else:
numtype = "np.real"
# check format
if ("e" in line_vec[0]) or ("E" in line_vec[0]):
numformat = "exp"
else:
numformat = "decimal"
elif N != n:
raise ValueError("Badly formatted data file: " +
"unequal number of columns")
M += 1
#
# read data and store in a matrix
#
f.seek(0)
if numtype == "complex":
data = np.zeros((M, N), dtype="complex")
m = n = 0
for line in f:
# skip comment lines
if line[0] == '#' or line[0] == '%':
continue
n = 0
for item in line.rstrip().split(sep):
data[m, n] = complex(item)
n += 1
m += 1
else:
data = np.zeros((M, N), dtype="float")
m = n = 0
for line in f:
# skip comment lines
if line[0] == '#' or line[0] == '%':
continue
n = 0
for item in line.rstrip().split(sep):
data[m, n] = float(item)
n += 1
m += 1
f.close()
return data
[docs]def qsave(data, name='qutip_data'):
"""
Saves given data to file named 'filename.qu' in current directory.
Parameters
----------
data : instance/array_like
Input Python object to be stored.
filename : str
Name of output data file.
"""
# open the file for writing
fileObject = open(name + '.qu', 'wb')
# this writes the object a to the file named 'filename.qu'
pickle.dump(data, fileObject)
fileObject.close()
[docs]def qload(name):
"""
Loads data file from file named 'filename.qu' in current directory.
Parameters
----------
name : str
Name of data file to be loaded.
Returns
-------
qobject : instance / array_like
Object retrieved from requested file.
"""
fileObject = open(name + '.qu', 'rb') # open the file for reading
out = pickle.load(fileObject) # return the object from the file
if isinstance(out, Qobj): # for quantum objects
print('Loaded Qobj object:')
str1 = "Quantum object: " + "dims = " + str(out.dims) \
+ ", shape = " + str(out.shape) + ", type = " + out.type
if out.type == 'oper' or out.type == 'super':
str1 += ", isHerm = " + str(out.isherm) + "\n"
else:
str1 += "\n"
print(str1)
elif isinstance(out, Result):
print('Loaded Result object:')
print(out)
else:
print("Loaded " + str(type(out).__name__) + " object.")
return out