Source code for qutip.fileio

# This file is part of QuTiP: Quantum Toolbox in Python.
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#    Copyright (c) 2011 and later, Paul D. Nation and Robert J. Johansson.
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__all__ = ['file_data_store', 'file_data_read', 'qsave', 'qload']

import pickle
import numpy as np
import sys
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. """ with open(name + ".qu", "rb") as fileObject: if sys.version_info >= (3, 0): out = pickle.load(fileObject, encoding='latin1') else: out = pickle.load(fileObject) 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