__all__ = ['file_data_store', 'file_data_read', 'qsave', 'qload']
import pickle
import numpy as np
import sys
from pathlib import Path
# -----------------------------------------------------------------------------
# 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 or pathlib.Path
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 or pathlib.Path
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 or pathlib.Path
Name of output data file.
"""
# open the file for writing
path = Path(name)
path = path.with_suffix(path.suffix + ".qu")
with open(path, "wb") as fileObject:
# this writes the object a to the file named 'filename.qu'
pickle.dump(data, fileObject)
[docs]def qload(name):
"""
Loads data file from file named 'filename.qu' in current directory.
Parameters
----------
name : str or pathlib.Path
Name of data file to be loaded.
Returns
-------
qobject : instance / array_like
Object retrieved from requested file.
"""
path = Path(name)
path = path.with_suffix(path.suffix + ".qu")
with open(path, "rb") as fileObject:
if sys.version_info >= (3, 0):
out = pickle.load(fileObject, encoding='latin1')
else:
out = pickle.load(fileObject)
return out