Changes in src/sas/sascalc/dataloader/data_info.py [1b1a1c1:7988501] in sasview

File:

• src/sas/sascalc/dataloader/data_info.py (modified) (12 diffs)

src/sas/sascalc/dataloader/data_info.py

@@ -25 +25 @@
 import numpy
 import math
-
-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.
-    """
-    # The presence of these should be mutually
-    # exclusive with the presence of Qdev (dx)
-    x = None
-    y = None
-    lam = None
-    dx = None
-    dy = None
-    dlam = None
-    ## Slit smearing length
-    dxl = None
-    ## Slit smearing width
-    dxw = None
-
-    # Units
-    _xaxis = ''
-    _xunit = ''
-    _yaxis = ''
-    _yunit = ''
-
-    def __init__(self, x, y, lam, dx=None, dy=None, dlam=None):
-#        print "SESANS plottable working"
-        self.x = numpy.asarray(x)
-        self.y = numpy.asarray(y)
-        self.lam = numpy.asarray(lam)
-        if dx is not None:
-            self.dx = numpy.asarray(dx)
-        if dy is not None:
-            self.dy = numpy.asarray(dy)
-        if dlam is not None:
-            self.dlam = numpy.asarray(dlam)
-
-    def xaxis(self, label, unit):
-        """
-        set the x axis label and unit
-        """
-        self._xaxis = label
-        self._xunit = unit
-
-    def yaxis(self, label, unit):
-        """
-        set the y axis label and unit
-        """
-        self._yaxis = label
-        self._yunit = unit
-
 
 class plottable_1D(object):
@@ -94 +41 @@
     dxw = None
 
+    ## SESANS specific params (wavelengths for spin echo length calculation)
+
+    lam = None
+    dlam = None
+
     # Units
     _xaxis = ''
@@ -100 +52 @@
     _yunit = ''
 
-    def __init__(self, x, y, dx=None, dy=None, dxl=None, dxw=None):
+    def __init__(self, x, y, dx=None, dy=None, dxl=None, dxw=None, lam=None, dlam=None):
         self.x = numpy.asarray(x)
         self.y = numpy.asarray(y)
@@ -111 +63 @@
         if dxw is not None:
             self.dxw = numpy.asarray(dxw)
+        if lam is not None:
+            self.lam = numpy.asarray(lam)
+        if dlam is not None:
+            self.dlam = numpy.asarray(dlam)
 
     def xaxis(self, label, unit):
@@ -736 +692 @@
         return self._perform_union(other)
 
-class SESANSData1D(plottable_sesans1D, DataInfo):
-    """
-    SESANS 1D data class
-    """
-    x_unit = 'nm'
-    y_unit = 'pol'
-
-    def __init__(self, x=None, y=None, lam=None, dx=None, dy=None, dlam=None):
+class Data1D(plottable_1D, DataInfo):
+    """
+    1D data class
+    """
+    if plottable_1D.lam is None: # This means it's SANS data!
+        x_unit = '1/A'
+        y_unit = '1/cm'
+    elif plottable_1D.lam is not None: # This means it's SESANS data!
+        x_unit = 'A'
+        y_unit = 'pol'
+    else: # and if it's neither, you get punished!
+        raise(TypeError,'This is neither SANS nor SESANS data, what the hell are you doing??')
+
+    def __init__(self, x=None, y=None, dx=None, dy=None, lam=None, dlam=None):
         DataInfo.__init__(self)
-        plottable_sesans1D.__init__(self, x, y, lam, dx, dy, dlam)
+        plottable_1D.__init__(self, x, y, dx, dy,None, None, lam, dlam)
+        if self.lam is None: # This means the lam param was not detected in the data: it's SANS data!
+            x_unit = '1/A'
+            y_unit = '1/cm'
+        elif self.lam is not None: # This means lam was detected (should be an empty ndarray): it's SESANS data!
+            x_unit = 'A'
+            y_unit = 'pol'
+        else: # and if it's neither, you get punished!
+            raise(TypeError,'This is neither SANS nor SESANS data, what the hell are you doing??')
 
     def __str__(self):
@@ -759 +729 @@
         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):
         """
@@ -769 +751 @@
         """
         from copy import deepcopy
+
         if clone is None or not issubclass(clone.__class__, Data1D):
             x = numpy.zeros(length)
@@ -774 +757 @@
             y = numpy.zeros(length)
             dy = numpy.zeros(length)
-            clone = Data1D(x, y, dx=dx, dy=dy)
+            lam = numpy.zeros(length)
+            dlam = numpy.zeros(length)
+            clone = Data1D(x, y, lam=lam, dx=dx, dy=dy, dlam=dlam )
 
         clone.title = self.title
@@ -792 +777 @@
         return clone
 
-class Data1D(plottable_1D, DataInfo):
-    """
-    1D data class
-    """
-    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 += "Data:\n"
-        _str += "   Type:         %s\n" % self.__class__.__name__
-        _str += "   X-axis:       %s\t[%s]\n" % (self._xaxis, self._xunit)
-        _str += "   Y-axis:       %s\t[%s]\n" % (self._yaxis, self._yunit)
-        _str += "   Length:       %g\n" % len(self.x)
-        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):
-        """
-        Clone the current object, without copying the data (which
-        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)
-            dx = 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.trans_spectrum = deepcopy(self.trans_spectrum)
-        clone.meta_data = deepcopy(self.meta_data)
-        clone.errors = deepcopy(self.errors)
-
-        return clone
-
     def _validity_check(self, other):
         """
@@ -881 +797 @@
                 raise ValueError, msg
             # Here we could also extrapolate between data points
-            TOLERANCE = 0.01
+            ZERO = 1.0e-12
             for i in range(len(self.x)):
-                if math.fabs((self.x[i] - other.x[i])/self.x[i]) > TOLERANCE:
+                if math.fabs(self.x[i] - other.x[i]) > ZERO:
                     msg = "Incompatible data sets: x-values do not match"
                     raise ValueError, msg
@@ -1093 +1009 @@
         """
         err_other = None
-        TOLERANCE = 0.01
         if isinstance(other, Data2D):
             # Check that data lengths are the same
@@ -1102 +1017 @@
                 raise ValueError, msg
             for ind in range(len(self.data)):
-                if math.fabs((self.qx_data[ind] - other.qx_data[ind])/self.qx_data[ind]) > TOLERANCE:
-                    msg = "Incompatible data sets: qx-values do not match: %s %s" % (self.qx_data[ind], other.qx_data[ind])
+                if self.qx_data[ind] != other.qx_data[ind]:
+                    msg = "Incompatible data sets: qx-values do not match"
                     raise ValueError, msg
-                if math.fabs((self.qy_data[ind] - other.qy_data[ind])/self.qy_data[ind]) > TOLERANCE:
-                    msg = "Incompatible data sets: qy-values do not match: %s %s" % (self.qy_data[ind], other.qy_data[ind])
+                if self.qy_data[ind] != other.qy_data[ind]:
+                    msg = "Incompatible data sets: qy-values do not match"
                     raise ValueError, msg