def isValid(self):
# Valid dimensions?
if (not (len(self._dimensions)==1
and isinstance(self._dimensions[0], IndexMarker)) #IndexMarkers are valid and...
and not (self.data.shape == (1,) and len(self._dimensions)==0)): #...so are zero dim fields.
dimshape = []
for d in self._dimensions:
if len(d.data.shape)>1:
_logger.debug("Dimension %s is not 1-d." % d.longname)
return False
dimshape.append(d.data.shape[0])
if self.data.shape!=tuple(dimshape):
_logger.debug("Shape of data %s and of dimensions %s do not match for field\n:%s" %
(self.data.shape, dimshape, self))
return False
for d in self._dimensions:
if not d.isValid():
_logger.debug("Invalid dimension %s."%d.longname)
return False
# Valid mask?
if (self.mask!=None) and (self.data.shape!=self.mask.shape):
_logger.debug("Shape of data %s and of mask %s do not match."%(self.data.shape, self.mask.shape))
return False
# Valid error?
if (self.error!=None) and (self.data.shape!=self.error.shape):
_logger.debug("Shape of data %s and of error %s do not match."%(self.data.shape, self.error.shape))
return False
return True
def isValid(self):
# Valid dimensions?
if (not (len(self._dimensions) == 1
and isinstance(self._dimensions[0], IndexMarker)
) #IndexMarkers are valid and...
and not (self.data.shape == (1, ) and len(self._dimensions)
== 0)): #...so are zero dim fields.
dimshape = []
for d in self._dimensions:
if len(d.data.shape) > 1:
_logger.debug("Dimension %s is not 1-d." % d.longname)
return False
dimshape.append(d.data.shape[0])
if self.data.shape != tuple(dimshape):
_logger.debug(
"Shape of data %s and of dimensions %s do not match for field\n:%s"
% (self.data.shape, dimshape, self))
return False
for d in self._dimensions:
if not d.isValid():
_logger.debug("Invalid dimension %s." % d.longname)
return False
# Valid mask?
if (self.mask != None) and (self.data.shape != self.mask.shape):
_logger.debug("Shape of data %s and of mask %s do not match." %
(self.data.shape, self.mask.shape))
return False
# Valid error?
if (self.error != None) and (self.data.shape != self.error.shape):
_logger.debug("Shape of data %s and of error %s do not match." %
(self.data.shape, self.error.shape))
return False
return True
def __eq__(self, other, rtol=1e-5, atol=1e-8):
if type(self) != type(other):
if type(other) != IndexMarker and type(other) != NoneType:
_logger.debug('Cannot compare objects with different type (%s and %s).' % (type(self),type(other)))
return False
if not (self.typeString == other.typeString):
_logger.debug('The typeString is not identical.')
return False
if (self.mask==None) and (other.mask!=None):
_logger.debug('The mask of the first field container has not been set, while the mask of the second field container is set to %s.' % other.mask)
return False
elif self.mask!=None and (other.mask==None):
_logger.debug('The mask of the second field container has not been set, while the mask of the first field container is set to %s.' % self.mask)
return False
if not (numpy.alltrue(self.mask==other.mask)):
_logger.debug('The masks are not identical: %s\n%s' % (self.mask,other.mask))
return False
if self.mask!=None:
data = self.data[numpy.logical_not(self.mask)]
otherData = other.data[numpy.logical_not(other.mask)]
if self.error!=None:
error = self.error[numpy.logical_not(self.mask)]
else:
error = self.error
if other.error!=None:
otherError = other.error[numpy.logical_not(other.mask)]
else:
otherError = other.error
else:
data = self.data
error = self.error
otherData = other.data
otherError = other.error
if (isQuantity(self.unit) or isQuantity(other.unit)):
try:
if not (self.unit.inBaseUnits().unit == other.unit.inBaseUnits().unit):
_logger.debug('The units are different.')
return False
except AttributeError:
_logger.debug('Cannot compare unit with normed quantity: %s, %s' % (self.unit,other.unit))
return False
try:
scaledData = data*self.unit.value
scaledOtherData = otherData*other.unit.inUnitsOf(self.unit.unit).value
if not numpy.allclose(scaledData,scaledOtherData,rtol,atol):
if numpy.sometrue(numpy.isnan(scaledData)):
_logger.debug('The fields cannot be compared, because some elements of the first field are NaN and the mask has not been set.')
if numpy.sometrue(numpy.isnan(scaledOtherData)):
_logger.debug('The fields cannot be compared, because some elements of the second field are NaN and the mask has not been set.')
else:
difference = numpy.abs(scaledData-scaledOtherData)
_logger.debug('The scaled fields differ, data-otherData: %s\n%s\n%s' % (difference.max(),
scaledData,
scaledOtherData))
return False
except ValueError:
_logger.debug('Shape mismatch: %s != %s' % (self.data.shape,other.data.shape))
return False
if error!=None:
scaledError = error*self.unit.value
if otherError!=None:
otherScaledError = otherError*other.unit.inUnitsOf(self.unit.unit).value
else:
_logger.debug('The errors differ: The error of the second argument is none, while the error of the first argument is %s.' % error)
return False
if not numpy.allclose(scaledError,otherScaledError,rtol,atol):
_logger.debug('The normed errors differ: %s\n%s' % (scaledError,otherScaledError))
return False
else:
if not data.dtype.char in ['S','U']:
try:
scaledData = data*self.unit
scaledOtherData = otherData*other.unit
if not numpy.allclose(scaledData,scaledOtherData,rtol,atol):
_logger.debug('The scaled fields differ: %s\n%s'%(scaledData,scaledOtherData))
return False
except ValueError:
_logger.debug('Shape mismatch: %s != %s' % (self.data.shape,other.data.shape))
return False
if error==None:
if not (otherError==None):
_logger.debug('The errors differ: Error of first argument is None, but the error of the second argument is not None.')
return False
else:
scaledError = error*self.unit
otherScaledError = otherError*other.unit
if not numpy.allclose(scaledError,otherScaledError,rtol,atol):
_logger.debug('The errors differ: %s\n%s' % (scaledError,otherScaledError))
return False
if not self.attributes == other.attributes:
_logger.debug('The attribute dictionary differs.')
return False
for dimSelf,dimOther in zip(self._dimensions,other.dimensions):
if dimSelf != dimOther:
_logger.debug('Different dimensions: %s, %s' % (dimSelf,dimOther))
return False
return True
def __eq__(self, other, rtol=1e-5, atol=1e-8):
if type(self) != type(other):
if type(other) != IndexMarker and type(other) != NoneType:
_logger.debug(
'Cannot compare objects with different type (%s and %s).' %
(type(self), type(other)))
return False
if not (self.typeString == other.typeString):
_logger.debug('The typeString is not identical.')
return False
if (self.mask == None) and (other.mask != None):
_logger.debug(
'The mask of the first field container has not been set, while the mask of the second field container is set to %s.'
% other.mask)
return False
elif self.mask != None and (other.mask == None):
_logger.debug(
'The mask of the second field container has not been set, while the mask of the first field container is set to %s.'
% self.mask)
return False
if not (numpy.alltrue(self.mask == other.mask)):
_logger.debug('The masks are not identical: %s\n%s' %
(self.mask, other.mask))
return False
if self.mask != None:
data = self.data[numpy.logical_not(self.mask)]
otherData = other.data[numpy.logical_not(other.mask)]
if self.error != None:
error = self.error[numpy.logical_not(self.mask)]
else:
error = self.error
if other.error != None:
otherError = other.error[numpy.logical_not(other.mask)]
else:
otherError = other.error
else:
data = self.data
error = self.error
otherData = other.data
otherError = other.error
if (isQuantity(self.unit) or isQuantity(other.unit)):
try:
if not (self.unit.inBaseUnits().unit
== other.unit.inBaseUnits().unit):
_logger.debug('The units are different.')
return False
except AttributeError:
_logger.debug(
'Cannot compare unit with normed quantity: %s, %s' %
(self.unit, other.unit))
return False
try:
scaledData = data * self.unit.value
scaledOtherData = otherData * other.unit.inUnitsOf(
self.unit.unit).value
if not numpy.allclose(scaledData, scaledOtherData, rtol, atol):
if numpy.sometrue(numpy.isnan(scaledData)):
_logger.debug(
'The fields cannot be compared, because some elements of the first field are NaN and the mask has not been set.'
)
if numpy.sometrue(numpy.isnan(scaledOtherData)):
_logger.debug(
'The fields cannot be compared, because some elements of the second field are NaN and the mask has not been set.'
)
else:
difference = numpy.abs(scaledData - scaledOtherData)
_logger.debug(
'The scaled fields differ, data-otherData: %s\n%s\n%s'
% (difference.max(), scaledData, scaledOtherData))
return False
except ValueError:
_logger.debug('Shape mismatch: %s != %s' %
(self.data.shape, other.data.shape))
return False
if error != None:
scaledError = error * self.unit.value
if otherError != None:
otherScaledError = otherError * other.unit.inUnitsOf(
self.unit.unit).value
else:
_logger.debug(
'The errors differ: The error of the second argument is none, while the error of the first argument is %s.'
% error)
return False
if not numpy.allclose(scaledError, otherScaledError, rtol,
atol):
_logger.debug('The normed errors differ: %s\n%s' %
(scaledError, otherScaledError))
return False
else:
if not data.dtype.char in ['S', 'U']:
try:
scaledData = data * self.unit
scaledOtherData = otherData * other.unit
if not numpy.allclose(scaledData, scaledOtherData, rtol,
atol):
_logger.debug('The scaled fields differ: %s\n%s' %
(scaledData, scaledOtherData))
return False
except ValueError:
_logger.debug('Shape mismatch: %s != %s' %
(self.data.shape, other.data.shape))
return False
if error == None:
if not (otherError == None):
_logger.debug(
'The errors differ: Error of first argument is None, but the error of the second argument is not None.'
)
return False
else:
scaledError = error * self.unit
otherScaledError = otherError * other.unit
if not numpy.allclose(scaledError, otherScaledError, rtol,
atol):
_logger.debug('The errors differ: %s\n%s' %
(scaledError, otherScaledError))
return False
if not self.attributes == other.attributes:
_logger.debug('The attribute dictionary differs.')
return False
for dimSelf, dimOther in zip(self._dimensions, other.dimensions):
if dimSelf != dimOther:
_logger.debug('Different dimensions: %s, %s' %
(dimSelf, dimOther))
return False
return True
