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