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Diffstat (limited to 'Monitoring/MonitoringService/DataProcessing/DataHeaderCell.py')
| -rw-r--r-- | Monitoring/MonitoringService/DataProcessing/DataHeaderCell.py | 180 |
1 files changed, 180 insertions, 0 deletions
diff --git a/Monitoring/MonitoringService/DataProcessing/DataHeaderCell.py b/Monitoring/MonitoringService/DataProcessing/DataHeaderCell.py new file mode 100644 index 0000000..f3bdb16 --- /dev/null +++ b/Monitoring/MonitoringService/DataProcessing/DataHeaderCell.py @@ -0,0 +1,180 @@ +''' +Created on Dec 20, 2012 + +@author: steger, jozsef +@organization: ELTE +@contact: steger@complex.elte.hu +''' + +from DataProcessing.Dimension import DimensionManager +from DataProcessing.DataError import DataError +from DataProcessing.Unit import UnitManager + +class Cell(object): + ''' + @summary: This class is a skeleton to represent the meta information of a single table column. + It combines the following information: + - the name of the cell, + - the feature associated to the underlying data, + - the dimension of the underlying data, + - the unit of the underlying data, + @ivar name: the name of the cell + @type name: str + @ivar dimension: the dimension of the cell + @type dimension: L{Dimension} + @ivar unit: the unit of a cell, if not set, the default unit of the dimension is applied + @type unit: L{Unit} + @ivar feature: the metric of the column + @type feature: str + ''' + def __init__(self): + self._name = None + self._dimension = None + self._unit = None + self._feature = None + + @property + def name(self): + if self._name is None: + raise DataError("name property is not set") + return self._name + @name.setter + def name(self, name): + if not isinstance(name, basestring): + raise DataError("name is not a string") + if name.count('.'): + raise DataError("name must not contain any periods (%s)" % name) + if self._name is not None and self._name != name: + raise DataError("name property cannot be modified") + self._name = name + + @property + def dimension(self): + if not self._dimension: + raise DataError("dimension property is not set") + return self._dimension + @dimension.setter + def dimension(self, dimension): + if not isinstance(dimension, DimensionManager.Dimension): + raise DataError("dimension is invalid") + if self._unit is not None: + if not dimension.containsUnit(self._unit): + raise DataError("unit %s is not in the basin of dimension %s" % (self.unit, dimension)) + self._dimension = dimension + + @property + def unit(self): + if self._unit is None: + return self.dimension.unit + else: + return self._unit + @unit.setter + def unit(self, unit): + if not isinstance(unit, UnitManager.Unit): + raise DataError("unit is invalid") + if self._dimension is not None: + if not self.dimension.containsUnit(unit): + raise DataError("unit %s is not in the basin of dimension %s" % (unit, self.dimension)) + self._unit = unit + + @property + def feature(self): + if self._feature is None: + raise DataError("feature property is not set") + return self._feature + @feature.setter + def feature(self, feature): + if self._feature is not None and self._feature != feature: + raise DataError("feature property cannot be modified") + self._feature = feature + + def __eq__(self, cell): + ''' + @summary: comparison operator of two columns' meta + @return: True if column names, features, units and dimensions match + @rtype: bool + ''' + if not isinstance(cell, Cell): + raise DataError("type error expecting Cell for comparison") + return self._name == cell._name and self._feature == cell._feature and self._unit == cell._unit and self._dimension == cell._dimension + + def __ne__(self, cell): + ''' + @summary: comparison operator of two columns' meta + @return: True if column names or their units differ + @rtype: bool + ''' + return not self.__eq__(cell) + +class DataHeaderCell(Cell): + ''' + @summary: represents meta information of a single column + ''' + def __init__(self, name, dimension, feature = None, unit = None): + ''' + @summary: constructor + @param name: the nema of the cell + @type name: str + @param dimension: the dimension of the cell + @type dimension: L{Dimension} + @param feature: pointer if it is a monitoring feature + @param unit: indicates the unit of a column if it is different from the default + @type unit: L{Unit} + ''' + Cell.__init__(self) + self.name = name + self.dimension = dimension + if unit is not None and unit != dimension.unit: + self.unit = unit + if feature is not None: + self.feature = feature + +class CellRequest(Cell): + ''' + @summary: skeleton, which is used to search the among meta information. It is basically a cell with missing certain details + ''' + pass + +class CellRequestByName(CellRequest): + ''' + @summary: This class represents the user request for a data column matching the name of the column. + One can specify the requested unit. + ''' + def __init__(self, name, unit = None): + ''' + @summary: Constructor + @param name: the name of the requested column + @type name: str + @param unit: the requested unit, default is None, which means no conversion request + @type unit: L{Unit} or None + ''' + Cell.__init__(self) + self.name = name + if unit is not None: + self.unit = unit + + def __eq__(self, cell): + return self.name == cell.name + +class CellRequestByFeature(CellRequest): + ''' + @author: steger, jozsef + @summary: + This class represents the user request for a data column(s) matching the feature of the column. + One can also specify the requested unit. + ''' + def __init__(self, feature, unit = None): + ''' + @summary: Constructor + @param feature: the feature of the requested column + @type feature: str + @param unit: the requested unit, default is None, which means no conversion request + @type unit: L{Unit} or None + ''' + Cell.__init__(self) + self.feature = feature + if unit is not None: + self.unit = unit + + def __eq__(self, cell): + return self.feature == cell.feature |