Source code for sas.sascalc.dataloader.readers.sesans_reader

    SESANS reader (based on ASCII reader)
    Reader for .ses or .sesans file format
    Jurrian Bakker 
import numpy
import os
from sas.sascalc.dataloader.data_info import Data1D

# Check whether we have a converter available
has_converter = True
    from sas.sascalc.data_util.nxsunit import Converter
    has_converter = False
_ZERO = 1e-16

[docs]class Reader: """ Class to load sesans files (6 columns). """ ## File type type_name = "SESANS" ## Wildcards type = ["SESANS files (*.ses)|*.ses", "SESANS files (*..sesans)|*.sesans"] ## List of allowed extensions ext = ['.ses', '.SES', '.sesans', '.SESANS'] ## Flag to bypass extension check allow_all = True
[docs] def read(self, path): # print "reader triggered" """ Load data file :param path: file path :return: SESANSData1D 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) _, extension = os.path.splitext(basename) if self.allow_all or extension.lower() in self.ext: try: # Read in binary mode since GRASP frequently has no-ascii # characters that brakes the open operation input_f = open(path,'rb') except: raise RuntimeError, "sesans_reader: cannot open %s" % path buff = lines = buff.splitlines() x = numpy.zeros(0) y = numpy.zeros(0) dy = numpy.zeros(0) lam = numpy.zeros(0) dlam = numpy.zeros(0) dx = numpy.zeros(0) #temp. space to sort data tx = numpy.zeros(0) ty = numpy.zeros(0) tdy = numpy.zeros(0) tlam = numpy.zeros(0) tdlam = numpy.zeros(0) tdx = numpy.zeros(0) output = Data1D(x=x, y=y, lam=lam, dy=dy, dx=dx, dlam=dlam, isSesans=True) self.filename = output.filename = basename paramnames=[] paramvals=[] zvals=[] dzvals=[] lamvals=[] dlamvals=[] Pvals=[] dPvals=[] for line in lines: # Initial try for CSV (split on ,) line=line.strip() toks = line.split('\t') if len(toks)==2: paramnames.append(toks[0]) paramvals.append(toks[1]) if len(toks)>5: zvals.append(toks[0]) dzvals.append(toks[3]) lamvals.append(toks[4]) dlamvals.append(toks[5]) Pvals.append(toks[1]) dPvals.append(toks[2]) else: continue x=[] y=[] lam=[] dx=[] dy=[] dlam=[] lam_header = lamvals[0].split() data_conv_z = None default_z_unit = "A" data_conv_P = None default_p_unit = " " # Adjust unit for axis (L^-3) lam_unit = lam_header[1].replace("[","").replace("]","") if lam_unit == 'AA': lam_unit = 'A' varheader=[zvals[0],dzvals[0],lamvals[0],dlamvals[0],Pvals[0],dPvals[0]] valrange=range(1, len(zvals)) for i in valrange: x.append(float(zvals[i])) y.append(float(Pvals[i])) lam.append(float(lamvals[i])) dy.append(float(dPvals[i])) dx.append(float(dzvals[i])) dlam.append(float(dlamvals[i])) x,y,lam,dy,dx,dlam = [ numpy.asarray(v, 'double') for v in (x,y,lam,dy,dx,dlam) ] input_f.close() output.x, output.x_unit = self._unit_conversion(x, lam_unit, default_z_unit) output.y = y output.y_unit = r'\AA^{-2} cm^{-1}' # output y_unit added output.dx, output.dx_unit = self._unit_conversion(dx, lam_unit, default_z_unit) output.dy = dy output.lam, output.lam_unit = self._unit_conversion(lam, lam_unit, default_z_unit) output.dlam, output.dlam_unit = self._unit_conversion(dlam, lam_unit, default_z_unit) output.xaxis(r"\rm{z}", output.x_unit) output.yaxis(r"\rm{ln(P)/(t \lambda^2)}", output.y_unit) # Adjust label to ln P/(lam^2 t), remove lam column refs # Store loading process information output.meta_data['loader'] = self.type_name #output.sample.thickness = float(paramvals[6]) = paramvals[1] output.sample.ID = paramvals[0] zaccept_unit_split = paramnames[7].split("[") zaccept_unit = zaccept_unit_split[1].replace("]","") if zaccept_unit.strip() == r'\AA^-1' or zaccept_unit.strip() == r'\A^-1': zaccept_unit = "1/A" output.sample.zacceptance=(float(paramvals[7]),zaccept_unit) output.vars = varheader if len(output.x) < 1: raise RuntimeError, "%s is empty" % path return output else: raise RuntimeError, "%s is not a file" % path return None
def _unit_conversion(self, value, value_unit, default_unit): if has_converter == True and value_unit != default_unit: data_conv_q = Converter(value_unit) value = data_conv_q(value, units=default_unit) new_unit = default_unit else: new_unit = value_unit return value, new_unit