Source code for sas.dataloader.readers.hfir1d_reader

"""
    HFIR 1D 4-column data reader
"""
#####################################################################
#This software was developed by the University of Tennessee as part of the
#Distributed Data Analysis of Neutron Scattering Experiments (DANSE)
#project funded by the US National Science Foundation.
#See the license text in license.txt
#copyright 2008, University of Tennessee
######################################################################
import numpy
import os
from sas.dataloader.data_info import Data1D

# Check whether we have a converter available
has_converter = True
try:
    from sas.data_util.nxsunit import Converter
except:
    has_converter = False

[docs]class Reader(object): """ Class to load HFIR 1D 4-column files """ ## File type type_name = "HFIR 1D" ## Wildcards type = ["HFIR 1D files (*.d1d)|*.d1d"] ## List of allowed extensions ext = ['.d1d']
[docs] def read(self, path): """ Load data file :param path: file path :return: Data1D object, or None :raise RuntimeError: when the file can't be opened :raise ValueError: when the length of the data vectors are inconsistent """ if os.path.isfile(path): basename = os.path.basename(path) root, extension = os.path.splitext(basename) if extension.lower() in self.ext: try: input_f = open(path,'r') except: raise RuntimeError, "hfir1d_reader: cannot open %s" % path buff = input_f.read() lines = buff.split('\n') x = numpy.zeros(0) y = numpy.zeros(0) dx = numpy.zeros(0) dy = numpy.zeros(0) output = Data1D(x, y, dx=dx, dy=dy) self.filename = output.filename = basename data_conv_q = None data_conv_i = None if has_converter == True and output.x_unit != '1/A': data_conv_q = Converter('1/A') # Test it data_conv_q(1.0, output.x_unit) if has_converter == True and output.y_unit != '1/cm': data_conv_i = Converter('1/cm') # Test it data_conv_i(1.0, output.y_unit) for line in lines: toks = line.split() try: _x = float(toks[0]) _y = float(toks[1]) _dx = float(toks[3]) _dy = float(toks[2]) if data_conv_q is not None: _x = data_conv_q(_x, units=output.x_unit) _dx = data_conv_q(_dx, units=output.x_unit) if data_conv_i is not None: _y = data_conv_i(_y, units=output.y_unit) _dy = data_conv_i(_dy, units=output.y_unit) x = numpy.append(x, _x) y = numpy.append(y, _y) dx = numpy.append(dx, _dx) dy = numpy.append(dy, _dy) except: # Couldn't parse this line, skip it pass # Sanity check if not len(y) == len(dy): msg = "hfir1d_reader: y and dy have different length" raise RuntimeError, msg if not len(x) == len(dx): msg = "hfir1d_reader: x and dx have different length" raise RuntimeError, msg # If the data length is zero, consider this as # though we were not able to read the file. if len(x) == 0: raise RuntimeError, "hfir1d_reader: could not load file" output.x = x output.y = y output.dy = dy output.dx = dx if data_conv_q is not None: output.xaxis("\\rm{Q}", output.x_unit) else: output.xaxis("\\rm{Q}", 'A^{-1}') if data_conv_i is not None: output.yaxis("\\rm{Intensity}", output.y_unit) else: output.yaxis("\\rm{Intensity}", "cm^{-1}") # Store loading process information output.meta_data['loader'] = self.type_name return output else: raise RuntimeError, "%s is not a file" % path return None