source: sasview/DataLoader/readers/IgorReader.py @ 31f3f661

"""
    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, sys
import numpy
import math, logging
from DataLoader.data_info import Data2D, Detector

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

class Reader:
    """ Simple data reader for Igor data files """
    ## File type
    type = ["IGOR 2D files (*.ASC)|*.ASC"]
    ## Extension
    ext=['.ASC', '.asc']

    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:
                    raise ValueError,"IgorReader: can't read this file, missing wavelength"
                
            #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:
                    raise ValueError,"IgorReader: can't read this file, missing wavelength"
                # Distance in meters
                try:
                    distance = float(line_toks[3])
                except:
                    raise ValueError,"IgorReader: can't read this file, missing distance"
                
                # Distance in meters
                try:
                    transmission = float(line_toks[4])
                except:
                    raise ValueError,"IgorReader: can't read this file, missing transmission"
                                            
            if line.count("LAMBDA")>0:
                isInfo = True
                
            # Find center info line
            if isCenter:
                isCenter = False                
                line_toks = line.split()
                # Center in bin number
                center_x = float(line_toks[0])
                center_y = float(line_toks[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:
                    raise ValueError, "IgorReader:Missing information in data file"
                
            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("\\{I(Q)}", output.I_unit)
        else:
            output.zaxis("\\rm{I(Q)}","cm^{-1}")
    
        
        return output
    
if __name__ == "__main__": 
    reader = Reader()
    print reader.read("../test/MAR07232_rest.ASC")