-                      r9a5097c
+                      r574adc7
 Uncertainty propagation class for arithmetic, log and exp.
 Based on scalars or numpy vectors, this class allows you to store and
+Based on scalars or numpy vectors, this class allows you to store and
 manipulate values+uncertainties, with propagation of gaussian error for
 addition, subtraction, multiplication, division, power, exp and log.
 Storage properties are determined by the numbers used to set the value
 and uncertainty.  Be sure to use floating point uncertainty vectors
+and uncertainty.  Be sure to use floating point uncertainty vectors
 for inplace operations since numpy does not do automatic type conversion.
 Normal operations can use mixed integer and floating point.  In place
 …
 import numpy as np
+import err1d
+from formatnum import format_uncertainty
+from .import err1d
+from .formatnum import format_uncertainty
 __all__ = ['Uncertainty']
 …
     # Make standard deviation available
     def _getdx(self): return np.sqrt(self.variance)
     def _setdx(self,dx):
+    def _setdx(self,dx):
         # Direct operation
         #    variance = dx**2
 …
     # Constructor
     def __init__(self, x, variance=None):
         self.x, self.variance = x, variance
+        self.x, self.variance = x, variance
     # Numpy array slicing operations
     def __len__(self):
+    def __len__(self):
         return len(self.x)
     def __getitem__(self,key):
+    def __getitem__(self,key):
         return Uncertainty(self.x[key],self.variance[key])
     def __setitem__(self,key,value):
 …
     def __idiv__(self, other): return self.__itruediv__(other)
     # Unary ops
     def __neg__(self):
 …
             return format_uncertainty(self.x,np.sqrt(self.variance))
         else:
             return [format_uncertainty(v,dv)
+            return [format_uncertainty(v,dv)
                     for v,dv in zip(self.x,np.sqrt(self.variance))]
     def __repr__(self):
 …
     z = a/4
     assert z.x == 5./4 and z.variance == 3./4**2
     # Reverse scalar operations
     z = 4+a
 …
     z = 4/a
     assert z.x == 4./5 and abs(z.variance - 3./5**4 * 4**2) < 1e-15
     # Power operations
     z = a**2
 …
     assert z.x == 5./4 and abs(z.variance - (3./5**2 + 2./4**2)*(5./4)**2) < 1e-15
     # ===== Inplace operations =====
+    # ===== Inplace operations =====
     # Scalar operations
     y = a+0; y += 4
 …
     assert (z.x == 5./4).all()
     assert (abs(z.variance - (3./5**2 + 2./4**2)*(5./4)**2) < 1e-15).all()
     # printing; note that sqrt(3) ~ 1.7
     assert str(Uncertainty(5,3)) == "5.0(17)"

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Changeset 574adc7 in sasview for src/sas/sascalc/data_util/uncertainty.py

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src/sas/sascalc/data_util/uncertainty.py

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