示例#1
0
    def compute(self, data, view=None):
        """For a given data set, compute the component comp_to given
        the data associated with each comp_from and the ``using``
        function

        :param data: The data set to use
        :param view: Optional view (e.g. slice) through the data to use


        *Returns*:

            The data associated with comp_to component

        *Raises*:

            InvalidAttribute, if the data set doesn't have all the
            ComponentIDs needed for the transformation
        """
        logger = logging.getLogger(__name__)
        args = [data[join_component_view(f, view)] for f in self._from]
        logger.debug("shape of first argument: %s", args[0].shape)
        result = self._using(*args)
        logger.debug("shape of result: %s", result.shape)
        if result.shape != args[0].shape:
            logger.warn("ComponentLink function %s changed shape. Fixing", self._using.__name__)
            result.shape = args[0].shape
        return result
示例#2
0
    def compute(self, data, view=None):
        """For a given data set, compute the component comp_to given
        the data associated with each comp_from and the ``using``
        function

        :param data: The data set to use
        :param view: Optional view (e.g. slice) through the data to use


        *Returns*:

            The data associated with comp_to component

        *Raises*:

            InvalidAttribute, if the data set doesn't have all the
            ComponentIDs needed for the transformation
        """
        logger = logging.getLogger(__name__)
        args = [data[join_component_view(f, view)] for f in self._from]
        logger.debug("shape of first argument: %s", args[0].shape)
        result = self._using(*args)
        logger.debug("shape of result: %s", result.shape)
        if result.shape != args[0].shape:
            logger.warn("ComponentLink function %s changed shape. Fixing",
                        self._using.__name__)
            result.shape = args[0].shape
        return result
示例#3
0
    def compute(self, data, view=None):
        """
        For a given data set, compute the component comp_to given the data
        associated with each comp_from and the ``using`` function

        This raises an :class:`glue.core.exceptions.IncompatibleAttribute` if the
        data set doesn't have all the ComponentIDs needed for the transformation

        Parameters
        ----------
        data : `~glue.core.data.Data`
            The data set to use
        view : `None` or `slice` or `tuple`
            Optional view (e.g. slice) through the data to use

        Returns
        -------
        result
            The data associated with comp_to component
        """

        # First we get the values of all the 'from' components.
        args = [data[join_component_view(f, view)] for f in self._from]

        # We keep track of the original shape of the arguments
        original_shape = args[0].shape
        logger.debug("shape of first argument: %s", original_shape)

        # We now unbroadcast the arrays to only compute the link with the
        # smallest number of values we can. This can help for cases where
        # the link depends only on e.g. pixel components or world coordinates
        # that themselves only depend on a subset of pixel components.
        # Unbroadcasting is the act of returning the smallest array that
        # contains all the information needed to be broadcasted back to its
        # full value
        args = [unbroadcast(arg) for arg in args]

        # We now broadcast these to the smallest common shape in case the
        # linking functions don't know how to broadcast arrays with different
        # shapes.
        args = np.broadcast_arrays(*args)

        # We call the actual linking function
        result = self._using(*args)

        # We call asarray since link functions may return Python scalars in some cases
        result = np.asarray(result)

        # In some cases, linking functions return ravelled arrays, so we
        # fix this here.
        logger.debug("shape of result: %s", result.shape)
        if result.shape != args[0].shape:
            logger.debug("ComponentLink function %s changed shape. Fixing",
                         self._using.__name__)
            result.shape = args[0].shape

        # Finally we broadcast the final result to desired shape
        result = broadcast_to(result, original_shape)

        return result
示例#4
0
    def compute(self, data, view=None):
        """
        For a given data set, compute the component comp_to given the data
        associated with each comp_from and the ``using`` function

        This raises an :class:`glue.core.exceptions.IncompatibleAttribute` if the
        data set doesn't have all the ComponentIDs needed for the transformation

        Parameters
        ----------
        data : `~glue.core.data.Data`
            The data set to use
        view : `None` or `slice` or `tuple`
            Optional view (e.g. slice) through the data to use

        Returns
        -------
        result
            The data associated with comp_to component
        """

        # First we get the values of all the 'from' components.
        args = [data[join_component_view(f, view)] for f in self._from]

        # We keep track of the original shape of the arguments
        original_shape = args[0].shape
        logger.debug("shape of first argument: %s", original_shape)

        # We now unbroadcast the arrays to only compute the link with the
        # smallest number of values we can. This can help for cases where
        # the link depends only on e.g. pixel components or world coordinates
        # that themselves only depend on a subset of pixel components.
        # Unbroadcasting is the act of returning the smallest array that
        # contains all the information needed to be broadcasted back to its
        # full value
        args = [unbroadcast(arg) for arg in args]

        # We now broadcast these to the smallest common shape in case the
        # linking functions don't know how to broadcast arrays with different
        # shapes.
        args = np.broadcast_arrays(*args)

        # We call the actual linking function
        result = self._using(*args)

        # We call asarray since link functions may return Python scalars in some cases
        result = np.asarray(result)

        # In some cases, linking functions return ravelled arrays, so we
        # fix this here.
        logger.debug("shape of result: %s", result.shape)
        if result.shape != args[0].shape:
            logger.debug("ComponentLink function %s changed shape. Fixing",
                         self._using.__name__)
            result.shape = args[0].shape

        # Finally we broadcast the final result to desired shape
        result = broadcast_to(result, original_shape)

        return result