def __fillStatistics__(self, _statistics_base_classes):
        model = self.__table__.model()
        model.removeRows(0, model.rowCount())

        self.__statistics_classes__ = []

        for base_class in _statistics_base_classes:
            for subclass in get_subclasses(base_class):
                self.__statistics_classes__.append(subclass)

        #sort alphabetically
        cmp_stat = lambda x, y: cmp(x.__name__, y.__name__)
        self.__statistics_classes__ = sorted(self.__statistics_classes__,
                                             cmp_stat)

        for statistic_class in self.__statistics_classes__:
            check_column = QStandardItem('%s' % statistic_class.__name__)
            check_column.setCheckState(Qt.Unchecked)
            check_column.setCheckable(True)

            description_column = QStandardItem(str(statistic_class().description)) # @IgnorePep8

            value_column = QStandardItem('')

            model.appendRow([check_column, description_column, value_column])
    def __fillStatistics__(self, _statistics_base_classes):
        model = self.__table__.model()
        model.removeRows(0, model.rowCount())

        self.__statistics_classes__ = []

        for base_class in _statistics_base_classes:
            for subclass in get_subclasses(base_class):
                self.__statistics_classes__.append(subclass)

        #sort alphabetically
        cmp_stat = lambda x, y: cmp(x.__name__, y.__name__)
        self.__statistics_classes__ = sorted(self.__statistics_classes__,
                                             cmp_stat)

        for statistic_class in self.__statistics_classes__:
            check_column = QStandardItem('%s' % statistic_class.__name__)
            check_column.setCheckState(Qt.Unchecked)
            check_column.setCheckable(True)

            description_column = QStandardItem(
                str(statistic_class().description))  # @IgnorePep8

            value_column = QStandardItem('')

            model.appendRow([check_column, description_column, value_column])
Exemplo n.º 3
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def get_unit_by_class_name(_class_name):
    """
    returns unit object based on unit class name
    """
    if _class_name:
        for subclass_unit in get_subclasses(__Unit__):
            if subclass_unit.__name__.endswith(_class_name):
                for unit_type in __UNITS_TYPE_MAP__:
                    for unit in __UNITS_TYPE_MAP__.get(unit_type):
                        if isinstance(unit, subclass_unit):
                            return unit
    return NoneUnit
Exemplo n.º 4
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def get_unit_by_class_name(_class_name):
    """
    returns unit object based on unit class name
    """
    if _class_name:
        for subclass_unit in get_subclasses(__Unit__):
            if subclass_unit.__name__.endswith(_class_name):
                for unit_type in __UNITS_TYPE_MAP__:
                    for unit in __UNITS_TYPE_MAP__.get(unit_type):
                        if isinstance(unit, subclass_unit):
                            return unit
    return NoneUnit
Exemplo n.º 5
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def calculate_tachogram_statistics(**data):
    """
    function to calculate all statistics associated with tachogram plots
    """
    outcomes = {}
    descriptions = {}
    for tachogram_statistic_class in get_subclasses(TachogramStatistic):
        tachogram_statistic = tachogram_statistic_class(**data)
        #remove TachogramStatistic label
        name = tachogram_statistic_class.__name__
        descriptions[name] = tachogram_statistic.description
        outcomes[name] = tachogram_statistic.compute()
    return (outcomes, descriptions, )
Exemplo n.º 6
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def calculate_tachogram_statistics(**data):
    """
    function to calculate all statistics associated with tachogram plots
    """
    outcomes = {}
    descriptions = {}
    for tachogram_statistic_class in get_subclasses(TachogramStatistic):
        tachogram_statistic = tachogram_statistic_class(**data)
        #remove TachogramStatistic label
        name = tachogram_statistic_class.__name__
        descriptions[name] = tachogram_statistic.description
        outcomes[name] = tachogram_statistic.compute()
    return (
        outcomes,
        descriptions,
    )