Source code for sas.dataloader.readers.IgorReader

"""
    IGOR 2D reduced file 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. 
#If you use DANSE applications to do scientific research that leads to 
#publication, we ask that you acknowledge the use of the software with the 
#following sentence:
#This work benefited from DANSE software developed under NSF award DMR-0520547. 
#copyright 2008, University of Tennessee
#############################################################################
import os
import numpy
import math
#import logging
from sas.dataloader.data_info import Data2D
from sas.dataloader.data_info import Detector
from sas.dataloader.manipulations import reader2D_converter

# Look for unit converter
has_converter = True
try:
    from sas.data_util.nxsunit import Converter
except:
    has_converter = False


[docs]class Reader: """ Simple data reader for Igor data files """ ## File type type_name = "IGOR 2D" ## Wildcards type = ["IGOR 2D files (*.ASC)|*.ASC"] ## Extension ext=['.ASC', '.asc']
[docs] def read(self, filename=None): """ Read file """ if not os.path.isfile(filename): raise ValueError, \ "Specified file %s is not a regular file" % filename # Read file f = open(filename, 'r') buf = f.read() # Instantiate data object output = Data2D() output.filename = os.path.basename(filename) detector = Detector() if len(output.detector) > 0: print str(output.detector[0]) output.detector.append(detector) # Get content dataStarted = False lines = buf.split('\n') itot = 0 x = [] y = [] ncounts = 0 xmin = None xmax = None ymin = None ymax = None i_x = 0 i_y = -1 i_tot_row = 0 isInfo = False isCenter = False data_conv_q = None data_conv_i = None if has_converter == True and output.Q_unit != '1/A': data_conv_q = Converter('1/A') # Test it data_conv_q(1.0, output.Q_unit) if has_converter == True and output.I_unit != '1/cm': data_conv_i = Converter('1/cm') # Test it data_conv_i(1.0, output.I_unit) for line in lines: # Find setup info line if isInfo: isInfo = False line_toks = line.split() # Wavelength in Angstrom try: wavelength = float(line_toks[1]) except: msg = "IgorReader: can't read this file, missing wavelength" raise ValueError, msg #Find # of bins in a row assuming the detector is square. if dataStarted == True: try: value = float(line) except: # Found a non-float entry, skip it continue # Get total bin number i_tot_row += 1 i_tot_row = math.ceil(math.sqrt(i_tot_row)) - 1 #print "i_tot", i_tot_row size_x = i_tot_row # 192#128 size_y = i_tot_row # 192#128 output.data = numpy.zeros([size_x, size_y]) output.err_data = numpy.zeros([size_x, size_y]) #Read Header and 2D data for line in lines: # Find setup info line if isInfo: isInfo = False line_toks = line.split() # Wavelength in Angstrom try: wavelength = float(line_toks[1]) except: msg = "IgorReader: can't read this file, missing wavelength" raise ValueError, msg # Distance in meters try: distance = float(line_toks[3]) except: msg = "IgorReader: can't read this file, missing distance" raise ValueError, msg # Distance in meters try: transmission = float(line_toks[4]) except: msg = "IgorReader: can't read this file, " msg += "missing transmission" raise ValueError, msg if line.count("LAMBDA") > 0: isInfo = True # Find center info line if isCenter: isCenter = False line_toks = line.split() # Center in bin number: Must substrate 1 because #the index starts from 1 center_x = float(line_toks[0]) - 1 center_y = float(line_toks[1]) - 1 if line.count("BCENT") > 0: isCenter = True # Find data start if line.count("***")>0: dataStarted = True # Check that we have all the info if wavelength == None \ or distance == None \ or center_x == None \ or center_y == None: msg = "IgorReader:Missing information in data file" raise ValueError, msg if dataStarted == True: try: value = float(line) except: # Found a non-float entry, skip it continue # Get bin number if math.fmod(itot, i_tot_row) == 0: i_x = 0 i_y += 1 else: i_x += 1 output.data[i_y][i_x] = value ncounts += 1 # Det 640 x 640 mm # Q = 4pi/lambda sin(theta/2) # Bin size is 0.5 cm #REmoved +1 from theta = (i_x-center_x+1)*0.5 / distance # / 100.0 and #REmoved +1 from theta = (i_y-center_y+1)*0.5 / # distance / 100.0 #ToDo: Need complete check if the following # covert process is consistent with fitting.py. theta = (i_x - center_x) * 0.5 / distance / 100.0 qx = 4.0 * math.pi / wavelength * math.sin(theta/2.0) if has_converter == True and output.Q_unit != '1/A': qx = data_conv_q(qx, units=output.Q_unit) if xmin == None or qx < xmin: xmin = qx if xmax == None or qx > xmax: xmax = qx theta = (i_y - center_y) * 0.5 / distance / 100.0 qy = 4.0 * math.pi / wavelength * math.sin(theta / 2.0) if has_converter == True and output.Q_unit != '1/A': qy = data_conv_q(qy, units=output.Q_unit) if ymin == None or qy < ymin: ymin = qy if ymax == None or qy > ymax: ymax = qy if not qx in x: x.append(qx) if not qy in y: y.append(qy) itot += 1 theta = 0.25 / distance / 100.0 xstep = 4.0 * math.pi / wavelength * math.sin(theta / 2.0) theta = 0.25 / distance / 100.0 ystep = 4.0 * math.pi/ wavelength * math.sin(theta / 2.0) # Store all data ###################################### # Store wavelength if has_converter == True and output.source.wavelength_unit != 'A': conv = Converter('A') wavelength = conv(wavelength, units=output.source.wavelength_unit) output.source.wavelength = wavelength # Store distance if has_converter == True and detector.distance_unit != 'm': conv = Converter('m') distance = conv(distance, units=detector.distance_unit) detector.distance = distance # Store transmission output.sample.transmission = transmission # Store pixel size pixel = 5.0 if has_converter == True and detector.pixel_size_unit != 'mm': conv = Converter('mm') pixel = conv(pixel, units=detector.pixel_size_unit) detector.pixel_size.x = pixel detector.pixel_size.y = pixel # Store beam center in distance units detector.beam_center.x = center_x * pixel detector.beam_center.y = center_y * pixel # Store limits of the image (2D array) xmin = xmin - xstep / 2.0 xmax = xmax + xstep / 2.0 ymin = ymin - ystep / 2.0 ymax = ymax + ystep / 2.0 if has_converter == True and output.Q_unit != '1/A': xmin = data_conv_q(xmin, units=output.Q_unit) xmax = data_conv_q(xmax, units=output.Q_unit) ymin = data_conv_q(ymin, units=output.Q_unit) ymax = data_conv_q(ymax, units=output.Q_unit) output.xmin = xmin output.xmax = xmax output.ymin = ymin output.ymax = ymax # Store x and y axis bin centers output.x_bins = x output.y_bins = y # Units if data_conv_q is not None: output.xaxis("\\rm{Q_{x}}", output.Q_unit) output.yaxis("\\rm{Q_{y}}", output.Q_unit) else: output.xaxis("\\rm{Q_{x}}", 'A^{-1}') output.yaxis("\\rm{Q_{y}}", 'A^{-1}') if data_conv_i is not None: output.zaxis("\\rm{Intensity}", output.I_unit) else: output.zaxis("\\rm{Intensity}", "cm^{-1}") # Store loading process information output.meta_data['loader'] = self.type_name output = reader2D_converter(output) return output