"""
Brain schematics plotting for glass brain functionality
"""

import json
import os

from matplotlib.path import Path
from matplotlib import patches
from matplotlib import colors
from matplotlib import transforms


def _codes_bezier(pts):
    bezier_num = len(pts)
    # Next two lines are meant to handle both Bezier 3 and 4
    path_attr = 'CURVE{0}'.format(bezier_num)
    codes = [getattr(Path, path_attr)] * (bezier_num - 1)
    return [Path.MOVETO] + codes


def _codes_segment(pts):
    return [Path.MOVETO, Path.LINETO]


def _codes(atype, pts):
    dispatch = {'bezier': _codes_bezier,
                'segment': _codes_segment}

    return dispatch[atype](pts)


def _invert_color(color):
    """Return inverted color

    If color is (R, G, B) it returns (1 - R, 1 - G, 1 - B). If
    'color' can not be converted to a color it is returned
    unmodified.

    """
    try:
        color_converter = colors.ColorConverter()
        color_rgb = color_converter.to_rgb(color)
        return tuple(1 - level for level in color_rgb)
    except ValueError:
        return color


def _get_mpl_patches(json_content, transform=None,
                     invert_color=False, **kwargs):
    """Walks over the json content and builds a list of matplotlib patches
    """
    mpl_patches = []
    kwargs_edgecolor = kwargs.pop('edgecolor', None)
    kwargs_linewidth = kwargs.pop('linewidth', None)
    for path in json_content['paths']:
        if kwargs_edgecolor is not None:
            edgecolor = kwargs_edgecolor
        else:
            edgecolor = path['edgecolor']
            if invert_color:
                edgecolor = _invert_color(edgecolor)
        linewidth = kwargs_linewidth or path['linewidth']
        path_id = path['id']

        for item in path['items']:
            type = item['type']
            pts = item['pts']
            codes = _codes(type, pts)
            path = Path(pts, codes)
            patch = patches.PathPatch(path,
                                      edgecolor=edgecolor,
                                      linewidth=linewidth,
                                      facecolor='none',
                                      gid=path_id,
                                      transform=transform,
                                      **kwargs)

            mpl_patches.append(patch)

    return mpl_patches


def _get_json_and_transform(direction):
    """Returns the json filename and and an affine transform, which has
    been tweaked by hand to fit the MNI template
    """
    direction_to_view_name = {'x': 'side',
                              'y': 'front',
                              'z': 'top',
                              'l': 'side',
                              'r': 'side'}

    direction_to_transform_params = {
        'x': [0.38, 0, 0, 0.38, -108, -70],
        'y': [0.39, 0, 0, 0.39, -72, -73],
        'z': [0.36, 0, 0, 0.37, -71, -107],
        'l': [0.38, 0, 0, 0.38, -108, -70],
        'r': [0.38, 0, 0, 0.38, -108, -70]}

    dirname = os.path.dirname(os.path.abspath(__file__))
    dirname = os.path.join(dirname, 'glass_brain_files')
    direction_to_filename = dict([
        (_direction, os.path.join(
            dirname,
            'brain_schematics_{0}.json'.format(view_name)))
        for _direction, view_name in direction_to_view_name.items()])

    direction_to_transforms = dict([
        (_direction, transforms.Affine2D.from_values(*params))
        for _direction, params in direction_to_transform_params.items()])

    direction_to_json_and_transform = dict([
        (_direction, (direction_to_filename[_direction],
                      direction_to_transforms[_direction]))
        for _direction in direction_to_filename])

    filename_and_transform = direction_to_json_and_transform.get(direction)

    if filename_and_transform is None:
        message = ("No glass brain view associated with direction '{0}'. "
                   "Possible directions are {1}").format(
                       direction,
                       list(direction_to_json_and_transform.keys()))
        raise ValueError(message)

    return filename_and_transform


def _get_object_bounds(json_content, transform):
    xmin, xmax, ymin, ymax = json_content['metadata']['bounds']
    x0, y0 = transform.transform((xmin, ymin))
    x1, y1 = transform.transform((xmax, ymax))

    xmin, xmax = min(x0, x1), max(x0, x1)
    ymin, ymax = min(y0, y1), max(y0, y1)

    # A combination of a proportional factor (fraction of the drawing)
    # and a guestimate of the linewidth
    xmargin = (xmax - xmin) * 0.025 + .1
    ymargin = (ymax - ymin) * 0.025 + .1
    return xmin - xmargin, xmax + xmargin, ymin - ymargin, ymax + ymargin


def plot_brain_schematics(ax, direction, **kwargs):
    """Creates matplotlib patches from a json custom format and plots them
       on a matplotlib Axes.

       Parameters
       ----------
           ax: a MPL axes instance
                The axes in which the plots will be drawn
            direction: {'x', 'y', 'z', 'l', 'r'}
                The directions of the view
            **kwargs:
                Passed to the matplotlib patches constructor

       Returns
       -------
       object_bounds: (xmin, xmax, ymin, ymax) tuple
           Useful for the caller to be able to set axes limits

    """
    black_bg = colors.colorConverter.to_rgba(ax.get_axis_bgcolor()) \
                    == colors.colorConverter.to_rgba('k')

    json_filename, transform = _get_json_and_transform(direction)
    with open(json_filename) as json_file:
        json_content = json.loads(json_file.read())

    mpl_patches = _get_mpl_patches(json_content,
                                   transform=transform + ax.transData,
                                   invert_color=black_bg,
                                   **kwargs)

    for mpl_patch in mpl_patches:
        ax.add_patch(mpl_patch)

    object_bounds = _get_object_bounds(json_content, transform)

    return object_bounds
