-                      r5e326a6
+                      re4f421c
     Module that contains classes to hold information read from
     reduced data files.
     A good description of the data members can be found in
     the CanSAS 1D XML data format:
     http://www.smallangles.net/wgwiki/index.php/cansas1d_documentation
 """
 …
 import math
 class plottable_sesans1D:
+class plottable_sesans1D(object):
     """
     SESANS is a place holder for 1D SESANS plottables.
     #TODO: This was directly copied from the plottables_1D. Modified Somewhat.
     #Class has been updated.
 …
     ## Slit smearing width
     dxw = None
     # Units
     _xaxis = ''
 …
     _yaxis = ''
     _yunit = ''
     def __init__(self, x, y, lam, dx=None, dy=None, dlam=None):
 #        print "SESANS plottable working"
 …
         if dlam is not None:
             self.dlam = numpy.asarray(dlam)
+#        if dxl is not None:
+#            self.dxl = numpy.asarray(dxl)
+#        if dxw is not None:
+#            self.dxw = numpy.asarray(dxw)
+#        print "SESANS plottable init fin"
     def xaxis(self, label, unit):
         """
 …
         self._xaxis = label
         self._xunit = unit
+        print "xaxis active"
+        print label
+        print unit
     def yaxis(self, label, unit):
         """
         set the y axis label and unit
         """
-        print "yaxis active"
-        print label
-        print unit
         self._yaxis = label
         self._yunit = unit
 class plottable_1D:
+class plottable_1D(object):
     """
     Data1D is a place holder for 1D plottables.
 …
     ## Slit smearing width
     dxw = None
     # Units
     _xaxis = ''
 …
     _yaxis = ''
     _yunit = ''
     def __init__(self, x, y, dx=None, dy=None, dxl=None, dxw=None):
         self.x = numpy.asarray(x)
 …
         if dxl is not None:
             self.dxl = numpy.asarray(dxl)
         if dxw is not None:
+        if dxw is not None:
             self.dxw = numpy.asarray(dxw)
 …
         self._xaxis = label
         self._xunit = unit
     def yaxis(self, label, unit):
         """
 …
 class plottable_2D:
+class plottable_2D(object):
     """
     Data2D is a place holder for 2D plottables.
 …
     dqy_data = None
     mask = None
     # Units
     _xaxis = ''
 …
     _zaxis = ''
     _zunit = ''
     def __init__(self, data=None, err_data=None, qx_data=None,
                  qy_data=None, q_data=None, mask=None,
 …
         self.err_data = numpy.asarray(err_data)
         if dqx_data is not None:
             self.dqx_data = numpy.asarray(dqx_data)
+            self.dqx_data = numpy.asarray(dqx_data)
         if dqy_data is not None:
             self.dqy_data = numpy.asarray(dqy_data)
+            self.dqy_data = numpy.asarray(dqy_data)
     def xaxis(self, label, unit):
         """
 …
         self._xaxis = label
         self._xunit = unit
     def yaxis(self, label, unit):
         """
 …
         self._yaxis = label
         self._yunit = unit
     def zaxis(self, label, unit):
         """
 …
         self._zunit = unit
 class Vector:
+class Vector(object):
     """
     Vector class to hold multi-dimensional objects
 …
     ## z component
     z = None
     def __init__(self, x=None, y=None, z=None):
         """
         Initialization. Components that are not
         set a set to None by default.
         :param x: x component
         :param y: y component
         :param z: z component
         """
         self.x = x
         self.y = y
         self.z = z
     def __str__(self):
         msg = "x = %s\ty = %s\tz = %s" % (str(self.x), str(self.y), str(self.z))
         return msg
 class Detector:
+class Detector(object):
     """
     Class to hold detector information
 …
     slit_length = None
     slit_length_unit = 'mm'
     def __init__(self):
         """
         Initialize class attribute that are objects...
+        """
+        self.offset      = Vector()
+        """
+        self.offset = Vector()
         self.orientation = Vector()
         self.beam_center = Vector()
         self.pixel_size  = Vector()
+        self.pixel_size = Vector()
     def __str__(self):
         _str  = "Detector:\n"
+        _str = "Detector:\n"
         _str += "   Name:         %s\n" % self.name
         _str += "   Distance:     %s [%s]\n" % \
 …
 class Aperture:
+class Aperture(object):
     ## Name
     name = None
 …
     distance = None
     distance_unit = 'mm'
     def __init__(self):
         self.size = Vector()
 class Collimation:
+class Collimation(object):
     """
     Class to hold collimation information
 …
     ## Aperture
     aperture = None
     def __init__(self):
         self.aperture = []
     def __str__(self):
         _str = "Collimation:\n"
 …
 class Source:
+class Source(object):
     """
     Class to hold source information
 …
     wavelength_spread = None
     wavelength_spread_unit = 'percent'
     def __init__(self):
         self.beam_size = Vector()
     def __str__(self):
         _str  = "Source:\n"
+        _str = "Source:\n"
         _str += "   Radiation:    %s\n" % str(self.radiation)
         _str += "   Shape:        %s\n" % str(self.beam_shape)
 …
             (str(self.beam_size), str(self.beam_size_unit))
         return _str
 """
 Definitions of radiation types
 """
 NEUTRON  = 'neutron'
 XRAY     = 'x-ray'
 MUON     = 'muon'
+NEUTRON = 'neutron'
+XRAY = 'x-ray'
+MUON = 'muon'
 ELECTRON = 'electron'
 class Sample:
+class Sample(object):
     """
     Class to hold the sample description
 …
     ## Details
     details = None
     def __init__(self):
         self.position    = Vector()
+        self.position = Vector()
         self.orientation = Vector()
         self.details     = []
+        self.details = []
     def __str__(self):
         _str  = "Sample:\n"
+        _str = "Sample:\n"
         _str += "   ID:           %s\n" % str(self.ID)
         _str += "   Transmission: %s\n" % str(self.transmission)
 …
         _str += "   Orientation:  %s [%s]\n" % \
             (str(self.orientation), str(self.orientation_unit))
         _str += "   Details:\n"
         for item in self.details:
             _str += "      %s\n" % item
         return _str
 class Process:
+class Process(object):
     """
     Class that holds information about the processes
 …
     term = None
     notes = None
     def __init__(self):
         self.term = []
         self.notes = []
     def __str__(self):
         _str  = "Process:\n"
+        _str = "Process:\n"
         _str += "   Name:         %s\n" % self.name
         _str += "   Date:         %s\n" % self.date
 …
             _str += "   Note:         %s\n" % item
         return _str
+class TransmissionSpectrum:
+class TransmissionSpectrum(object):
     """
     Class that holds information about transmission spectrum
 …
     transmission_deviation = None
     transmission_deviation_unit = ''
     def __init__(self):
         self.wavelength = []
         self.transmission = []
         self.transmission_deviation = []
     def __str__(self):
         _str  = "Transmission Spectrum:\n"
+        _str = "Transmission Spectrum:\n"
         _str += "   Name:             \t{0}\n".format(self.name)
         _str += "   Timestamp:        \t{0}\n".format(self.timestamp)
 …
         _str += "   Number of Pts:    \t{0}\n".format(max(length_list))
         return _str
 class DataInfo:
+class DataInfo(object):
     """
     Class to hold the data read from a file.
 …
     """
     ## Title
     title      = ''
+    title = ''
     ## Run number
     run        = None
+    run = None
     ## Run name
     run_name   = None
+    run_name = None
     ## File name
     filename   = ''
+    filename = ''
     ## Notes
     notes      = None
+    notes = None
     ## Processes (Action on the data)
     process    = None
+    process = None
     ## Instrument name
     instrument = ''
     ## Detector information
     detector   = None
+    detector = None
     ## Sample information
     sample     = None
+    sample = None
     ## Source information
     source     = None
+    source = None
     ## Collimation information
     collimation = None
 …
     trans_spectrum = None
     ## Additional meta-data
     meta_data  = None
+    meta_data = None
     ## Loading errors
     errors = None
     def __init__(self):
         """
         Initialization
         """
         ## Title
         self.title      = ''
+        ## Title
+        self.title = ''
         ## Run number
         self.run        = []
         self.run_name   = {}
+        self.run = []
+        self.run_name = {}
         ## File name
         self.filename   = ''
+        self.filename = ''
         ## Notes
         self.notes      = []
+        self.notes = []
         ## Processes (Action on the data)
         self.process    = []
+        self.process = []
         ## Instrument name
         self.instrument = ''
         ## Detector information
         self.detector   = []
+        self.detector = []
         ## Sample information
         self.sample     = Sample()
+        self.sample = Sample()
         ## Source information
         self.source     = Source()
+        self.source = Source()
         ## Collimation information
         self.collimation = []
 …
         self.trans_spectrum = []
         ## Additional meta-data
         self.meta_data  = {}
+        self.meta_data = {}
         ## Loading errors
         self.errors = []
     def append_empty_process(self):
         """
         """
         self.process.append(Process())
     def add_notes(self, message=""):
         """
 …
         """
         self.notes.append(message)
     def __str__(self):
         """
         Nice printout
         """
         _str =  "File:            %s\n" % self.filename
+        _str = "File:            %s\n" % self.filename
         _str += "Title:           %s\n" % self.title
         _str += "Run:             %s\n" % str(self.run)
 …
             _str += "%s\n" % str(item)
         return _str
     # Private method to perform operation. Not implemented for DataInfo,
     # but should be implemented for each data class inherited from DataInfo
 …
         """
         return NotImplemented
     def _perform_union(self, other):
         """
 …
         """
         Add two data sets
         :param other: data set to add to the current one
         :return: new data set
 …
             return a + b
         return self._perform_operation(other, operation)
     def __radd__(self, other):
         """
         Add two data sets
         :param other: data set to add to the current one
         :return: new data set
         :raise ValueError: raised when two data sets are incompatible
         """
         def operation(a, b):
             return b + a
         return self._perform_operation(other, operation)
     def __sub__(self, other):
         """
         Subtract two data sets
         :param other: data set to subtract from the current one
         :return: new data set
         :raise ValueError: raised when two data sets are incompatible
         """
         def operation(a, b):
             return a - b
         return self._perform_operation(other, operation)
     def __rsub__(self, other):
         """
         Subtract two data sets
         :param other: data set to subtract from the current one
         :return: new data set
         :raise ValueError: raised when two data sets are incompatible
         """
         def operation(a, b):
             return b - a
         return self._perform_operation(other, operation)
     def __mul__(self, other):
         """
         Multiply two data sets
         :param other: data set to subtract from the current one
         :return: new data set
         :raise ValueError: raised when two data sets are incompatible
         """
         def operation(a, b):
             return a * b
         return self._perform_operation(other, operation)
     def __rmul__(self, other):
         """
         Multiply two data sets
         :param other: data set to subtract from the current one
         :return: new data set
         :raise ValueError: raised when two data sets are incompatible
         """
 …
             return b * a
         return self._perform_operation(other, operation)
     def __div__(self, other):
         """
         Divided a data set by another
         :param other: data set that the current one is divided by
         :return: new data set
         :raise ValueError: raised when two data sets are incompatible
         """
         def operation(a, b):
             return a/b
         return self._perform_operation(other, operation)
     def __rdiv__(self, other):
         """
         Divided a data set by another
         :param other: data set that the current one is divided by
         :return: new data set
         :raise ValueError: raised when two data sets are incompatible
         """
         def operation(a, b):
             return b/a
         return self._perform_operation(other, operation)
     def __or__(self, other):
         """
         Union a data set with another
         :param other: data set to be unified
         :return: new data set
         :raise ValueError: raised when two data sets are incompatible
         """
         return self._perform_union(other)
     def __ror__(self, other):
         """
         Union a data set with another
         :param other: data set to be unified
         :return: new data set
         :raise ValueError: raised when two data sets are incompatible
         """
         return self._perform_union(other)
 class SESANSData1D(plottable_sesans1D, DataInfo):
     """
 …
     x_unit = 'nm'
     y_unit = 'a.u.'
     def __init__(self, x=None, y=None, lam=None, dy=None, dx=None, dlam=None):
-#        print "dat init"
         DataInfo.__init__(self)
-#        print "dat init fin"
         plottable_sesans1D.__init__(self, x, y, lam, dx, dy, dlam)
+#        print "SESANSdata1D init"
     def __str__(self):
         """
         Nice printout
         """
+#        print "string printer active"
+        _str =  "%s\n" % DataInfo.__str__(self)
+        _str = "%s\n" % DataInfo.__str__(self)
         _str += "Data:\n"
         _str += "   Type:         %s\n" % self.__class__.__name__
 …
         _str += "   Y-axis:       %s\t[%s]\n" % (self._yaxis, self._yunit)
         _str += "   Length:       %g\n" % len(self.x)
-#        print _str
         return _str
+#
+#    def is_slit_smeared(self):
+#        """
+#        Check whether the data has slit smearing information
+#
+#        :return: True is slit smearing info is present, False otherwise
+#
+#        """
+#        def _check(v):
+#            if (v.__class__ == list or v.__class__ == numpy.ndarray) \
+#                and len(v) > 0 and min(v) > 0:
+#                return True
+#
+#            return False
+#
+#        return _check(self.dxl) or _check(self.dxw)
     def clone_without_data(self, length=0, clone=None):
         """
 …
         will be filled out by a subsequent operation).
         The data arrays will be initialized to zero.
         :param length: length of the data array to be initialized
         :param clone: if provided, the data will be copied to clone
         """
         from copy import deepcopy
-#        print " SESANS data 1D clone active"
         if clone is None or not issubclass(clone.__class__, Data1D):
             x  = numpy.zeros(length)
+            x = numpy.zeros(length)
             dx = numpy.zeros(length)
+            lam  = numpy.zeros(length)
+            dlam = numpy.zeros(length)
+            y  = numpy.zeros(length)
+            y = numpy.zeros(length)
             dy = numpy.zeros(length)
             clone = Data1D(x, y, dx=dx, dy=dy)
         clone.title          = self.title
         clone.run            = self.run
         clone.filename       = self.filename
         clone.instrument     = self.instrument
         clone.notes          = deepcopy(self.notes)
         clone.process        = deepcopy(self.process)
         clone.detector       = deepcopy(self.detector)
         clone.sample         = deepcopy(self.sample)
         clone.source         = deepcopy(self.source)
         clone.collimation    = deepcopy(self.collimation)
+        clone.title = self.title
+        clone.run = self.run
+        clone.filename = self.filename
+        clone.instrument = self.instrument
+        clone.notes = deepcopy(self.notes)
+        clone.process = deepcopy(self.process)
+        clone.detector = deepcopy(self.detector)
+        clone.sample = deepcopy(self.sample)
+        clone.source = deepcopy(self.source)
+        clone.collimation = deepcopy(self.collimation)
         clone.trans_spectrum = deepcopy(self.trans_spectrum)
         clone.meta_data      = deepcopy(self.meta_data)
         clone.errors         = deepcopy(self.errors)
+#        print "SESANS Data 1Dclone done"
+        clone.meta_data = deepcopy(self.meta_data)
+        clone.errors = deepcopy(self.errors)
         return clone
 class Data1D(plottable_1D, DataInfo):
     """
 …
     x_unit = '1/A'
     y_unit = '1/cm'
     def __init__(self, x, y, dx=None, dy=None):
         DataInfo.__init__(self)
         plottable_1D.__init__(self, x, y, dx, dy)
     def __str__(self):
         """
         Nice printout
         """
+        _str =  "%s\n" % DataInfo.__str__(self)
+        _str = "%s\n" % DataInfo.__str__(self)
         _str += "Data:\n"
         _str += "   Type:         %s\n" % self.__class__.__name__
 …
         _str += "   Y-axis:       %s\t[%s]\n" % (self._yaxis, self._yunit)
         _str += "   Length:       %g\n" % len(self.x)
         return _str
 …
         """
         Check whether the data has slit smearing information
         :return: True is slit smearing info is present, False otherwise
         """
         def _check(v):
 …
                 and len(v) > 0 and min(v) > 0:
                 return True
             return False
         return _check(self.dxl) or _check(self.dxw)
     def clone_without_data(self, length=0, clone=None):
         """
 …
         will be filled out by a subsequent operation).
         The data arrays will be initialized to zero.
         :param length: length of the data array to be initialized
         :param clone: if provided, the data will be copied to clone
         """
         from copy import deepcopy
         if clone is None or not issubclass(clone.__class__, Data1D):
             x  = numpy.zeros(length)
+            x = numpy.zeros(length)
             dx = numpy.zeros(length)
             y  = numpy.zeros(length)
+            y = numpy.zeros(length)
             dy = numpy.zeros(length)
             clone = Data1D(x, y, dx=dx, dy=dy)
         clone.title          = self.title
         clone.run            = self.run
         clone.filename       = self.filename
         clone.instrument     = self.instrument
         clone.notes          = deepcopy(self.notes)
         clone.process        = deepcopy(self.process)
         clone.detector       = deepcopy(self.detector)
         clone.sample         = deepcopy(self.sample)
         clone.source         = deepcopy(self.source)
         clone.collimation    = deepcopy(self.collimation)
+        clone.title = self.title
+        clone.run = self.run
+        clone.filename = self.filename
+        clone.instrument = self.instrument
+        clone.notes = deepcopy(self.notes)
+        clone.process = deepcopy(self.process)
+        clone.detector = deepcopy(self.detector)
+        clone.sample = deepcopy(self.sample)
+        clone.source = deepcopy(self.source)
+        clone.collimation = deepcopy(self.collimation)
         clone.trans_spectrum = deepcopy(self.trans_spectrum)
         clone.meta_data      = deepcopy(self.meta_data)
         clone.errors         = deepcopy(self.errors)
+        clone.meta_data = deepcopy(self.meta_data)
+        clone.errors = deepcopy(self.errors)
         return clone
 …
         errors vectors if they were present or vectors
         of zeros when none was found.
         :param other: other data set for operation
         :return: dy for self, dy for other [numpy arrays]
         :raise ValueError: when lengths are not compatible
         """
         dy_other = None
 …
                 msg = "Unable to perform operation: data length are not equal"
                 raise ValueError, msg
             # Here we could also extrapolate between data points
             ZERO = 1.0e-12
 …
                     msg = "Incompatible data sets: x-values do not match"
                     raise ValueError, msg
+                """
+                if self.dxl != None and other.dxl == None:
+                    msg = "Incompatible data sets: dxl-values do not match"
+                    raise ValueError, msg
+                if self.dxl == None and other.dxl != None:
+                    msg = "Incompatible data sets: dxl-values do not match"
+                    raise ValueError, msg
+                if self.dxw != None and other.dxw == None:
+                    msg = "Incompatible data sets: dxw-values do not match"
+                    raise ValueError, msg
+                if self.dxw == None and other.dxw != None:
+                    msg = "Incompatible data sets: dxw-values do not match"
+                    raise ValueError, msg
+                """
             # Check that the other data set has errors, otherwise
             # create zero vector
 …
             if other.dy == None or (len(other.dy) != len(other.y)):
                 dy_other = numpy.zeros(len(other.y))
         # Check that we have errors, otherwise create zero vector
         dy = self.dy
         if self.dy == None or (len(self.dy) != len(self.y)):
             dy = numpy.zeros(len(self.y))
         return dy, dy_other
 …
             if self.dxl is not None and len(self.x) == len(self.dxl):
                 result.dxl[i] = self.dxl[i]
             a = Uncertainty(self.y[i], dy[i]**2)
             if isinstance(other, Data1D):
 …
             else:
                 b = other
             output = operation(a, b)
             result.y[i] = output.x
             result.dy[i] = math.sqrt(math.fabs(output.variance))
         return result
     def _validity_check_union(self, other):
         """
 …
         errors vectors if they were present or vectors
         of zeros when none was found.
         :param other: other data set for operation
         :return: bool
         :raise ValueError: when data types are not compatible
         """
         if not isinstance(other, Data1D):
             msg = "Unable to perform operation: different types of data set"
             raise ValueError, msg
+            raise ValueError, msg
         return True
 …
             result.dxl = result.dxl[ind]
         return result
 class Data2D(plottable_2D, DataInfo):
     """
 …
     ## Units for Q-values
     Q_unit = '1/A'
     ## Units for I(Q) values
     I_unit = '1/cm'
     ## Vector of Q-values at the center of each bin in x
     x_bins = None
     ## Vector of Q-values at the center of each bin in y
     y_bins = None
     def __init__(self, data=None, err_data=None, qx_data=None,
                  qy_data=None, q_data=None, mask=None,
 …
     def __str__(self):
         _str = "%s\n" % DataInfo.__str__(self)
         _str += "Data:\n"
         _str += "   Type:         %s\n" % self.__class__.__name__
         _str += "   X- & Y-axis:  %s\t[%s]\n" % (self._yaxis, self._yunit)
         _str += "   Z-axis:       %s\t[%s]\n" % (self._zaxis, self._zunit)
-        #leny = 0
-        #if len(self.data) > 0:
-        #    leny = len(self.data)
         _str += "   Length:       %g \n" % (len(self.data))
         return _str
     def clone_without_data(self, length=0, clone=None):
         """
 …
         will be filled out by a subsequent operation).
         The data arrays will be initialized to zero.
         :param length: length of the data array to be initialized
         :param clone: if provided, the data will be copied to clone
         """
         from copy import deepcopy
         if clone is None or not issubclass(clone.__class__, Data2D):
             data = numpy.zeros(length)
 …
             dqx_data = None
             dqy_data = None
             clone = Data2D(data=data, err_data=err_data,
                            qx_data=qx_data, qy_data=qy_data,
+            clone = Data2D(data=data, err_data=err_data,
+                           qx_data=qx_data, qy_data=qy_data,
                            q_data=q_data, mask=mask)
         clone.title       = self.title
         clone.run         = self.run
         clone.filename    = self.filename
         clone.instrument  = self.instrument
         clone.notes       = deepcopy(self.notes)
         clone.process     = deepcopy(self.process)
         clone.detector    = deepcopy(self.detector)
         clone.sample      = deepcopy(self.sample)
         clone.source      = deepcopy(self.source)
+        clone.title = self.title
+        clone.run = self.run
+        clone.filename = self.filename
+        clone.instrument = self.instrument
+        clone.notes = deepcopy(self.notes)
+        clone.process = deepcopy(self.process)
+        clone.detector = deepcopy(self.detector)
+        clone.sample = deepcopy(self.sample)
+        clone.source = deepcopy(self.source)
         clone.collimation = deepcopy(self.collimation)
         clone.meta_data   = deepcopy(self.meta_data)
         clone.errors      = deepcopy(self.errors)
+        clone.meta_data = deepcopy(self.meta_data)
+        clone.errors = deepcopy(self.errors)
         return clone
     def _validity_check(self, other):
         """
 …
         errors vectors if they were present or vectors
         of zeros when none was found.
         :param other: other data set for operation
         :return: dy for self, dy for other [numpy arrays]
         :raise ValueError: when lengths are not compatible
         """
         err_other = None
 …
                 msg = "Unable to perform operation: data length are not equal"
                 raise ValueError, msg
-            #if len(self.data) < 1:
-            #    msg = "Incompatible data sets: I-values do not match"
-            #    raise ValueError, msg
             for ind in range(len(self.data)):
                 if self.qx_data[ind] != other.qx_data[ind]:
 …
                     msg = "Incompatible data sets: qy-values do not match"
                     raise ValueError, msg
             # Check that the scales match
             err_other = other.err_data
 …
                 (len(other.err_data) != len(other.data)):
                 err_other = numpy.zeros(len(other.data))
         # Check that we have errors, otherwise create zero vector
         err = self.err_data
 …
             (len(self.err_data) != len(self.data)):
             err = numpy.zeros(len(other.data))
         return err, err_other
     def _perform_operation(self, other, operation):
         """
         Perform 2D operations between data sets
         :param other: other data set
         :param operation: function defining the operation
         """
         # First, check the data compatibility
 …
             if self.err_data is not None and \
                 numpy.size(self.data) == numpy.size(self.err_data):
                 result.err_data[i] = self.err_data[i]
+                result.err_data[i] = self.err_data[i]
             if self.dqx_data is not None:
                 result.dqx_data[i] = self.dqx_data[i]
 …
             result.q_data[i] = self.q_data[i]
             result.mask[i] = self.mask[i]
             a = Uncertainty(self.data[i], dy[i]**2)
             if isinstance(other, Data2D):
 …
                     result.dqx_data[i] += (other.dqx_data[i]**2)
                     result.dqx_data[i] /= 2
                     result.dqx_data[i] = math.sqrt(result.dqx_data[i])
+                    result.dqx_data[i] = math.sqrt(result.dqx_data[i])
                 if other.dqy_data is not None and \
                         result.dqy_data is not None:
 …
             else:
                 b = other
             output = operation(a, b)
             result.data[i] = output.x
             result.err_data[i] = math.sqrt(math.fabs(output.variance))
         return result
     def _validity_check_union(self, other):
         """
 …
         errors vectors if they were present or vectors
         of zeros when none was found.
         :param other: other data set for operation
         :return: bool
         :raise ValueError: when data types are not compatible
         """
         if not isinstance(other, Data2D):
             msg = "Unable to perform operation: different types of data set"
             raise ValueError, msg
+            raise ValueError, msg
         return True
     def _perform_union(self, other):
         """
         Perform 2D operations between data sets
         :param other: other data set
         :param operation: function defining the operation
         """
         # First, check the data compatibility
 …
         result.ymax = self.ymax
         if self.dqx_data == None or self.dqy_data == None or \
                 other.dqx_data == None or other.dqy_data == None :
+                other.dqx_data == None or other.dqy_data == None:
             result.dqx_data = None
             result.dqy_data = None
 …
             result.dqy_data = numpy.zeros(len(self.data) + \
                                          numpy.size(other.data))
         result.data = numpy.append(self.data, other.data)
         result.qx_data = numpy.append(self.qx_data, other.qx_data)

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SasView

Changeset e4f421c in sasview for src/sas

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src/sas/dataloader/data_info.py

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