python-chaco 4.4.1-1.2 / usr / lib / python2.7 / dist-packages / chaco / subdivision_cells.py

""" Defines cell-related classes and functions.
"""
from numpy import take, array, concatenate, nonzero

from traits.api import HasStrictTraits, Instance, Delegate, Array, List, \
                             Tuple, Property, Trait, Any, Disallow

from datamapper import AbstractDataMapper, right_shift, left_shift, sort_points


def find_runs(int_array, order='ascending'):
    """
    find_runs(int_array, order=<'ascending'|'flat'|'descending'>) -> list_of_int_arrays

    Given an integer array sorted in ascending, descending, or flat order, this
    function returns a list of continuous runs of integers inside the list.
    For example::

        find_runs([1,2,3,6,7,8,9,10,11,15])

    returns [ [1,2,3], [6,7,8,9,10,11], [15] ]
    and::

        find_runs([0,0,0,1,1,1,1,0,0,0,0])

    returns [ [0,0,0], [1,1,1,1], [0,0,0,0] ]
    """
    ranges = arg_find_runs(int_array, order)
    if ranges:
        return [int_array[i:j] for (i,j) in ranges]
    else:
        return []

def arg_find_runs(int_array, order='ascending'):
    """
    This function is like find_runs(), but it returns a list of tuples
    indicating the start and end indices of runs in the input *int_array*.
    """
    if len(int_array) == 0:
        return []
    assert len(int_array.shape)==1, "find_runs() requires a 1D integer array."
    if order == 'ascending':
        increment = 1
    elif order == 'descending':
        increment = -1
    else:
        increment = 0
    rshifted = right_shift(int_array, int_array[0]-increment)
    start_indices = concatenate([[0], nonzero(int_array - (rshifted+increment))[0]])
    end_indices = left_shift(start_indices, len(int_array))
    return zip(start_indices, end_indices)


class AbstractCell(HasStrictTraits):
    """ Abstract class for grid cells in a uniform subdivision.

    Individual subclasses store points in different, possibly optimized
    fashion, and performance may be drastically different between different
    cell subclasses for a given set of data.
    """
    # The parent of this cell.
    parent = Instance(AbstractDataMapper)

    # The sort traits characterizes the internal points list.
    _sort_order = Delegate('parent')

    # The point array for this cell. This attribute delegates to parent._data,
    # which references the actual point array. For the sake of simplicity,
    # cells assume that _data is sorted in fashion indicated by **_sort_order**.
    # If this doesn't hold, then each cell needs to have its own duplicate
    # copy of the sorted data.
    data = Delegate('parent', '_data')

    # A list of indices into **data** that reflect the points inside this cell.
    indices = Property

    # Shadow trait for **indices**.
    _indices = Any

    def add_indices(self, indices):
        """ Adds a list of integer indices to the existing list of indices.
        """
        raise NotImplementedError

    def get_points(self):
        """ Returns a list of points that was previously set.

        This operation might be large and expensive; in general, use
        _get_indices() instead.
        """
        raise NotImplementedError

    def reverse_indices(self):
        """ Tells the cell to manipulate its indices so that they index to the
        same values in a reversed data array.

        Generally this method handles the situation when the parent's _data
        array has been flipped due to a sort order change.

        The length of _data must not have changed; otherwise there is no way to
        know the proper way to manipulate indices.
        """
        raise NotImplementedError

    def _set_indices(self, indices):
        raise NotImplementedError

    def _get_indices(self):
        """  Returns the list of indices into _data that reflect the points
        inside this cell.
        """
        raise NotImplementedError


class Cell(AbstractCell):
    """
    A basic cell that stores its point indices as an array of integers.
    """
    # A list of indices into **data** that reflect the points inside this cell
    # (overrides AbstractCell).
    indices = Property(Array)

    # A 1-D array of indices into _data.
    _indices = Array

    def __init__(self, **kw):
        self._indices = array([])
        super(AbstractCell, self).__init__(**kw)

    def add_indices(self, indices):
        """ Adds a list of integer indices to the existing list of indices.

        Implements AbstractCell.
        """
        self._indices = concatenate([self._indices, indices])
        return

    def get_points(self):
        """ Returns a list of points that was previously set.

        Implements AbstractCell.
        """
        return take(self.data, self._indices)

    def reverse_indices(self):
        """ Tells the cell to manipulate its indices so that they index to the
        same values in a reversed data array.

        Implements AbstractCell.
        """
        length = len(self.data)
        self._indices = [length-i-1 for i in self._indices]
        return

    def _set_indices(self, indices):
        self._indices = indices
        return

    def _get_indices(self):
        return self._indices



class RangedCell(AbstractCell):
    """ A cell optimized for storing lists of continuous points.

    Rather than storing each individual point index as an element in an array,
    RangedCell stores a list of index ranges; each range is a (start,end) tuple).
    """

    # A list of indices into **data** that reflect the points inside this cell
    # (overrides AbstractCell).
    indices = Property

    # Don't use the _indices shadow trait; rather, the getters and setters
    # for 'index' procedurally generate indices from **ranges**.
    _indices = Disallow

    # Ranges are an additional interface on RangedCells.
    ranges = Property(List(Tuple))

    # Shadow trait for ranges.
    _ranges = List(Tuple)

    #---------------------------------------------------------------------
    # AbstractCell methods
    #---------------------------------------------------------------------

    def add_indices(self, indices):
        """ Adds a list of integer indices to the existing list of indices.

        Implements AbstractCell.
        """
        self.add_ranges(find_runs(indices))
        return

    def get_points(self):
        """ Returns a list of points that was previously set.

        Implements AbstractCell.
        """
        return take(self.data, self.indices)

    def reverse_indices(self):
        """ Tells the cell to manipulate its indices so that they index to the
        same values in a reversed data array.

        Implements AbstractCell.
        """
        length = len(self.data)
        self._ranges = [(length-end-1, length-start-1) for (start,end) in self._ranges]
        return

    def _set_indices(self, indices):
        self._ranges = find_runs(indices)
        return

    def _get_indices(self):
        list_of_indices = [range(i,j) for (i,j) in self._ranges]
        return sum(list_of_indices, [])


    #---------------------------------------------------------------------
    # additional RangedCell methods
    #---------------------------------------------------------------------

    def get_ranges(self):
        """ Returns a list of tuples representing the (start,end) indices of
        continuous ranges of points in self._data.
        """
        return self._ranges()

    def add_ranges(self, ranges):
        """ Adds a list of ranges ((start,end) tuples) to the current list.

        This method doesn't check for duplicate or overlapping ranges.
        """
        if self._ranges:
            self._ranges.extend(ranges)
        else:
            self._ranges = ranges
        return
#EOF