def __pow__(self, other):
if isinstance(other,Measurement):
# Haven't calcuated variance in (a+/-da) ** (b+/-db)
return NotImplemented
else:
if (not self.variance is None) and hasattr(other,'variance') and not other.variance is None:
return Measurement(*err1d.pow(self.x,self.variance,other))
else:
return Measurement(pow(self.x,other),None)
def __pow__(self, other):
if isinstance(other, Uncertainty):
# Haven't calcuated variance in (a+/-da) ** (b+/-db)
return NotImplemented
else:
return Uncertainty(*err1d.pow(self.x, self.variance, other))
def __rtruediv__(self, other):
x, variance = err1d.pow(self.x, self.variance, -1)
return Uncertainty(x * other, variance * other**2)
def __rtruediv__(self, other):
if (not self.variance is None) and hasattr(other,'variance') and not other.variance is None:
x,variance = err1d.pow(self.x,self.variance,-1)
return Measurement(other/self.x,variance*other**2)
else:
return Measurement(other/self.x,None)
def __rtruediv__(self, other):
x,variance = err1d.pow(self.x,self.variance,-1)
return Uncertainty(x*other,variance*other**2)
def __pow__(self, other):
if isinstance(other,Uncertainty):
# Haven't calcuated variance in (a+/-da) ** (b+/-db)
return NotImplemented
else:
return Uncertainty(*err1d.pow(self.x,self.variance,other))
def __rtruediv__(self, other):
x,variance = err1d.pow(self.x,self.variance,-1)
return Measurement(x*other,variance*other**2)
def __rtruediv__(self, other):
x, variance = err1d.pow(self.x, self.variance, -1)
return Measurement(x * other, variance * other**2)
