# (C) Copyright 2005-2021 Enthought, Inc., Austin, TX
# All rights reserved.
#
# This software is provided without warranty under the terms of the BSD
# license included in LICENSE.txt and may be redistributed only under
# the conditions described in the aforementioned license. The license
# is also available online at http://www.enthought.com/licenses/BSD.txt
#
# Thanks for using Enthought open source!

""" Defines the Base1DMapper class.
"""
# Enthought library imports
from traits.api import Bool, Instance, Float, Property

# Local relative imports
from .abstract_mapper import AbstractMapper
from .data_range_1d import DataRange1D


class Base1DMapper(AbstractMapper):
    """Defines an abstract mapping from a 1-D region in input space to a 1-D
    region in output space.
    """

    #: The data-space bounds of the mapper.
    range = Instance(DataRange1D)

    #: The screen space position of the lower bound of the data space.
    low_pos = Float(0.0)

    #: The screen space position of the upper bound of the data space.
    high_pos = Float(1.0)

    #: Convenience property to get low and high positions in one structure.
    #: Must be a tuple (low_pos, high_pos).
    screen_bounds = Property

    #: Should the mapper stretch the dataspace when its screen space bounds are
    #: modified (default), or should it preserve the screen-to-data ratio and
    #: resize the data bounds?  If the latter, it will only try to preserve
    #: the ratio if both screen and data space extents are non-zero.
    stretch_data = Bool(True)

    #: The sign of the mapping: 1 if deltas match sign, -1 if opposite sign
    sign = Property

    # If the subclass uses a cache, _cache_valid is maintained to
    # monitor its status
    _cache_valid = Bool(False, transient=True)

    # Indicates whether or not the bounds have been set at all, or if they
    # are at their initial default values.
    _low_bound_initialized = Bool(False)
    _high_bound_initialized = Bool(False)

    # ------------------------------------------------------------------------
    # Event handlers
    # ------------------------------------------------------------------------

    def _low_pos_changed(self, old, new):
        self._cache_valid = False
        if not self.stretch_data:
            self._adjust_range((old, self.high_pos), (new, self.high_pos))
        self._low_bound_initialized = True
        self.updated = True

    def _high_pos_changed(self, old, new):
        self._cache_valid = False
        if not self.stretch_data:
            self._adjust_range((self.low_pos, old), (self.low_pos, new))
        self._high_bound_initialized = True
        self.updated = True

    def _range_changed(self, old, new):
        if old is not None:
            old.observe(self._range_change_handler, "updated", remove=True)
        if new is not None:
            new.observe(self._range_change_handler, "updated")

        self._cache_valid = False
        self.updated = new

    def _range_change_handler(self, event):
        "Handles the range changing; dynamically attached to our ranges"
        self._cache_valid = False
        self.updated = event.object

    def _get_screen_bounds(self):
        return (self.low_pos, self.high_pos)

    def _get_sign(self):
        delta_screen = self.high_pos - self.low_pos
        delta_data = self.range.high - self.range.low
        if delta_screen == 0 or delta_data == 0:
            return 0
        elif delta_screen / float(delta_data) < 0:
            return -1
        else:
            return 1

    def _set_screen_bounds(self, new_bounds):
        if new_bounds[0] == self.low_pos and new_bounds[1] == self.high_pos:
            return
        if not self.stretch_data:
            self._adjust_range((self.low_pos, self.high_pos), new_bounds)
        self.trait_setq(low_pos=new_bounds[0])
        self.trait_setq(high_pos=new_bounds[1])
        self._cache_valid = False
        self._low_bound_initialized = True
        self._high_bound_initialized = True
        self.updated = True

    def _adjust_range(self, old_bounds, new_bounds):
        initialized = (
            self._low_bound_initialized and self._high_bound_initialized
        )
        if self.range is not None and initialized:
            rangelow = self.range.low
            rangehigh = self.range.high
            d_data = rangehigh - rangelow
            old_d_screen = old_bounds[1] - old_bounds[0]
            if d_data != 0 and old_d_screen != 0:
                new_data_extent = (
                    d_data / old_d_screen * (new_bounds[1] - new_bounds[0])
                )
                self.range.set_bounds(rangelow, rangelow + new_data_extent)