Example #1
0
def tree(tr, plane='xy', new_fig=True, subplot=False, **kwargs):
    '''Generates a 2d figure of the tree.

    Parameters:
        tr: Tree \
            neurom.Tree object

    Options:
        plane: str \
            Accepted values: Any pair of of xyz \
            Default value is 'xy'.treecolor
        linewidth: float \
            Defines the linewidth of the tree, \
            if diameter is set to False. \
            Default value is 1.2.
        alpha: float \
            Defines throughe transparency of the tree. \
            0.0 transparent through 1.0 opaque. \
            Default value is 0.8.
        treecolor: str or None \
            Defines the color of the tree. \
            If None the default values will be used, \
            depending on the type of tree: \
            Basal dendrite: "red" \
            Axon : "blue" \
            Apical dendrite: "purple" \
            Undefined tree: "black" \
            Default value is None.
        new_fig: boolean \
            Defines if the tree will be plotted \
            in the current figure (False) \
            or in a new figure (True) \
            Default value is True.
        subplot: matplotlib subplot value or False \
            If False the default subplot 111 will be used. \
            For any other value a matplotlib subplot \
            will be generated. \
            Default value is False.
        diameter: boolean
            If True the diameter, scaled with diameter_scale factor, \
            will define the width of the tree lines. \
            If False use linewidth to select the width of the tree lines. \
            Default value is True.
        diameter_scale: float \
            Defines the scale factor that will be multiplied \
            with the diameter to define the width of the tree line. \
            Default value is 1.
        limits: list or boolean \
            List of type: [[xmin, ymin, zmin], [xmax, ymax, zmax]] \
            If False the figure will not be scaled. \
            If True the figure will be scaled according to tree limits. \
            Default value is False.
        white_space: float \
            Defines the white space around \
            the boundary box of the morphology. \
            Default value is 1.

    Returns:
        A 2D matplotlib figure with a tree view, at the selected plane.
    '''
    if plane not in ('xy', 'yx', 'xz', 'zx', 'yz', 'zy'):
        return None, 'No such plane found! Please select one of: xy, xz, yx, yz, zx, zy.'

    # Initialization of matplotlib figure and axes.
    fig, ax = common.get_figure(new_fig=new_fig, subplot=subplot)

    # Data needed for the viewer: x,y,z,r
    bounding_box = get_bounding_box(tr)

    def _seg_2d(seg):
        '''2d coordinates needed for the plotting of a segment'''
        horz = getattr(COLS, plane[0].capitalize())
        vert = getattr(COLS, plane[1].capitalize())
        parent_point = seg[0]
        child_point = seg[1]
        horz1 = parent_point[horz]
        horz2 = child_point[horz]
        vert1 = parent_point[vert]
        vert2 = child_point[vert]
        return ((horz1, vert1), (horz2, vert2))

    segs = [_seg_2d(seg) for seg in val_iter(isegment(tr))]

    linewidth = get_default('linewidth', **kwargs)
    # Definition of the linewidth according to diameter, if diameter is True.
    if get_default('diameter', **kwargs):
        scale = get_default('diameter_scale', **kwargs)
        # TODO: This was originally a numpy array. Did it have to be one?
        linewidth = [2 * d * scale for d in i_segment_radius(tr)]

    # Plot the collection of lines.
    collection = LineCollection(segs,
                                color=common.get_color(get_default('treecolor', **kwargs),
                                                       get_tree_type(tr)),
                                linewidth=linewidth, alpha=get_default('alpha', **kwargs))

    ax.add_collection(collection)

    kwargs['title'] = kwargs.get('title', 'Tree view')
    kwargs['xlabel'] = kwargs.get('xlabel', plane[0])
    kwargs['ylabel'] = kwargs.get('ylabel', plane[1])
    kwargs['xlim'] = kwargs.get('xlim', [bounding_box[0][getattr(COLS, plane[0].capitalize())] -
                                         get_default('white_space', **kwargs),
                                         bounding_box[1][getattr(COLS, plane[0].capitalize())] +
                                         get_default('white_space', **kwargs)])
    kwargs['ylim'] = kwargs.get('ylim', [bounding_box[0][getattr(COLS, plane[1].capitalize())] -
                                         get_default('white_space', **kwargs),
                                         bounding_box[1][getattr(COLS, plane[1].capitalize())] +
                                         get_default('white_space', **kwargs)])

    return common.plot_style(fig=fig, ax=ax, **kwargs)
Example #2
0
def tree3d(tr, new_fig=True, new_axes=True, subplot=False, **kwargs):
    '''Generates a figure of the tree in 3d.

    Parameters:
        tr: Tree
        neurom.Tree object

    Options:
        linewidth: float \
            Defines the linewidth of the tree, \
            if diameter is set to False. \
            Default value is 1.2.
        alpha: float \
            Defines throughe transparency of the tree. \
            0.0 transparent through 1.0 opaque. \
            Default value is 0.8.
        treecolor: str or None \
            Defines the color of the tree. \
            If None the default values will be used, \
            depending on the type of tree: \
            Basal dendrite: "red" \
            Axon : "blue" \
            Apical dendrite: "purple" \
            Undefined tree: "black" \
            Default value is None.
        new_fig: boolean \
            Defines if the tree will be plotted \
            in the current figure (False) \
            or in a new figure (True) \
            Default value is True.
        subplot: matplotlib subplot value or False \
            If False the default subplot 111 will be used. \
            For any other value a matplotlib subplot \
            will be generated. \
            Default value is False.
        diameter: boolean
            If True the diameter, scaled with diameter_scale factor, \
            will define the width of the tree lines. \
            If False use linewidth to select the width of the tree lines. \
            Default value is True.
        diameter_scale: float \
            Defines the scale factor that will be multiplied \
            with the diameter to define the width of the tree line. \
            Default value is 1.
        white_space: float \
            Defines the white space around \
            the boundary box of the morphology. \
            Default value is 1.

    Returns:
        A 3D matplotlib figure with a tree view.
    '''
    from mpl_toolkits.mplot3d.art3d import Line3DCollection

    # Initialization of matplotlib figure and axes.
    fig, ax = common.get_figure(new_fig=new_fig, new_axes=new_axes,
                                subplot=subplot, params={'projection': '3d'})

    # Data needed for the viewer: x,y,z,r
    bounding_box = get_bounding_box(tr)

    def _seg_3d(seg):
        '''2d coordinates needed for the plotting of a segment'''
        horz = getattr(COLS, 'X')
        vert = getattr(COLS, 'Y')
        depth = getattr(COLS, 'Z')
        parent_point = seg[0]
        child_point = seg[1]
        horz1 = parent_point[horz]
        horz2 = child_point[horz]
        vert1 = parent_point[vert]
        vert2 = child_point[vert]
        depth1 = parent_point[depth]
        depth2 = child_point[depth]
        return ((horz1, vert1, depth1), (horz2, vert2, depth2))

    segs = [_seg_3d(seg) for seg in val_iter(isegment(tr))]

    linewidth = get_default('linewidth', **kwargs)

    # Definition of the linewidth according to diameter, if diameter is True.
    if get_default('diameter', **kwargs):
        # TODO: This was originally a numpy array. Did it have to be one?
        linewidth = [2 * d * get_default('diameter_scale', **kwargs) for d in i_segment_radius(tr)]

    # Plot the collection of lines.
    collection = Line3DCollection(segs,
                                  color=common.get_color(get_default('treecolor', **kwargs),
                                                         get_tree_type(tr)),
                                  linewidth=linewidth, alpha=get_default('alpha', **kwargs))

    ax.add_collection3d(collection)

    kwargs['title'] = kwargs.get('title', 'Tree 3d-view')
    kwargs['xlabel'] = kwargs.get('xlabel', 'X')
    kwargs['ylabel'] = kwargs.get('ylabel', 'Y')
    kwargs['zlabel'] = kwargs.get('zlabel', 'Z')
    kwargs['xlim'] = kwargs.get('xlim', [bounding_box[0][0] - get_default('white_space', **kwargs),
                                         bounding_box[1][0] + get_default('white_space', **kwargs)])
    kwargs['ylim'] = kwargs.get('ylim', [bounding_box[0][1] - get_default('white_space', **kwargs),
                                         bounding_box[1][1] + get_default('white_space', **kwargs)])
    kwargs['zlim'] = kwargs.get('zlim', [bounding_box[0][2] - get_default('white_space', **kwargs),
                                         bounding_box[1][2] + get_default('white_space', **kwargs)])

    return common.plot_style(fig=fig, ax=ax, **kwargs)
Example #3
0
def neuron3d(nrn, new_fig=True, new_axes=True, subplot=False, **kwargs):
    '''Generates a figure of the neuron,
       that contains a soma and a list of trees.

    Parameters:
        neuron: Neuron
        neurom.Neuron object

    Options:
        linewidth: float \
            Defines the linewidth of the tree, \
            if diameter is set to False. \
            Default value is 1.2.
        alpha: float \
            Defines throughe transparency of the tree. \
            0.0 transparent through 1.0 opaque. \
            Default value is 0.8.
        treecolor: str or None \
            Defines the color of the tree. \
            If None the default values will be used, \
            depending on the type of tree: \
            Basal dendrite: "red" \
            Axon : "blue" \
            Apical dendrite: "purple" \
            Undefined tree: "black" \
            Default value is None.
        new_fig: boolean \
            Defines if the tree will be plotted \
            in the current figure (False) \
            or in a new figure (True) \
            Default value is True.
        subplot: matplotlib subplot value or False \
            If False the default subplot 111 will be used. \
            For any other value a matplotlib subplot \
            will be generated. \
            Default value is False.
        diameter: boolean
            If True the diameter, scaled with diameter_scale factor, \
            will define the width of the tree lines. \
            If False use linewidth to select the width of the tree lines. \
            Default value is True.
        diameter_scale: float \
            Defines the scale factor that will be multiplied \
            with the diameter to define the width of the tree line. \
            Default value is 1.

    Returns:
        A 3D matplotlib figure with a neuron view.
    '''
    # Initialization of matplotlib figure and axes.
    fig, ax = common.get_figure(new_fig=new_fig, new_axes=new_axes,
                                subplot=subplot, params={'projection': '3d'})

    kwargs['new_fig'] = False
    kwargs['subplot'] = subplot
    kwargs['new_axes'] = False
    kwargs['title'] = kwargs.get('title', 'Neuron view')

    soma3d(nrn.soma, **kwargs)

    h = []
    v = []
    d = []

    for temp_tree in nrn.neurites:

        bounding_box = get_bounding_box(temp_tree)

        h.append([bounding_box[0][getattr(COLS, 'X')],
                  bounding_box[1][getattr(COLS, 'X')]])
        v.append([bounding_box[0][getattr(COLS, 'Y')],
                  bounding_box[1][getattr(COLS, 'Y')]])
        d.append([bounding_box[0][getattr(COLS, 'Z')],
                  bounding_box[1][getattr(COLS, 'Z')]])

        tree3d(temp_tree, **kwargs)

    if h:
        kwargs['xlim'] = kwargs.get('xlim', [np.min(h) - get_default('white_space', **kwargs),
                                             np.max(h) + get_default('white_space', **kwargs)])
    if v:
        kwargs['ylim'] = kwargs.get('ylim', [np.min(v) - get_default('white_space', **kwargs),
                                             np.max(v) + get_default('white_space', **kwargs)])
    if d:
        kwargs['zlim'] = kwargs.get('zlim', [np.min(d) - get_default('white_space', **kwargs),
                                             np.max(d) + get_default('white_space', **kwargs)])

    return common.plot_style(fig=fig, ax=ax, **kwargs)
Example #4
0
def test_get_bounding_box():
    box = np.array([[-33.25305769, -57.600172  ,   0.        ],
                    [  0.        ,   0.        ,  49.70137991]])
    bb = get_bounding_box(tree0)
    nt.ok_(np.allclose(bb, box))
Example #5
0
def neuron(nrn, plane='xy', new_fig=True, subplot=False, **kwargs):
    '''Generates a 2d figure of the neuron,
       that contains a soma and a list of trees.

    Parameters:
        neuron: Neuron
        neurom.Neuron object

    Options:
        plane: str \
            Accepted values: Any pair of of xyz \
            Default value is 'xy'.treecolor
        linewidth: float \
            Defines the linewidth of the tree, \
            if diameter is set to False. \
            Default value is 1.2.
        alpha: float \
            Defines throughe transparency of the tree. \
            0.0 transparent through 1.0 opaque. \
            Default value is 0.8.
        treecolor: str or None \
            Defines the color of the tree. \
            If None the default values will be used, \
            depending on the type of tree: \
            Basal dendrite: "red" \
            Axon : "blue" \
            Apical dendrite: "purple" \
            Undefined tree: "black" \
            Default value is None.
        new_fig: boolean \
            Defines if the tree will be plotted \
            in the current figure (False) \
            or in a new figure (True) \
            Default value is True.
        subplot: matplotlib subplot value or False \
            If False the default subplot 111 will be used. \
            For any other value a matplotlib subplot \
            will be generated. \
            Default value is False.
        diameter: boolean
            If True the diameter, scaled with diameter_scale factor, \
            will define the width of the tree lines. \
            If False use linewidth to select the width of the tree lines. \
            Default value is True.
        diameter_scale: float \
            Defines the scale factor that will be multiplied \
            with the diameter to define the width of the tree line. \
            Default value is 1.
        limits: list or boolean \
            List of type: [[xmin, ymin, zmin], [xmax, ymax, zmax]] \
            If False the figure will not be scaled. \
            If True the figure will be scaled according to tree limits. \
            Default value is False.

    Returns:
        A 3D matplotlib figure with a tree view, at the selected plane.
    '''
    if plane not in ('xy', 'yx', 'xz', 'zx', 'yz', 'zy'):
        return None, 'No such plane found! Please select one of: xy, xz, yx, yz, zx, zy.'

    # Initialization of matplotlib figure and axes.
    fig, ax = common.get_figure(new_fig=new_fig, subplot=subplot)

    kwargs['new_fig'] = False
    kwargs['subplot'] = subplot

    soma(nrn.soma, plane=plane, **kwargs)

    kwargs['title'] = kwargs.get('title', 'Neuron view')
    kwargs['xlabel'] = kwargs.get('xlabel', plane[0])
    kwargs['ylabel'] = kwargs.get('ylabel', plane[1])

    h = []
    v = []

    for temp_tree in nrn.neurites:

        bounding_box = get_bounding_box(temp_tree)

        h.append([bounding_box[0][getattr(COLS, plane[0].capitalize())],
                  bounding_box[1][getattr(COLS, plane[0].capitalize())]])
        v.append([bounding_box[0][getattr(COLS, plane[1].capitalize())],
                  bounding_box[1][getattr(COLS, plane[1].capitalize())]])

        tree(temp_tree, plane=plane, **kwargs)

    if h:
        kwargs['xlim'] = kwargs.get('xlim', [np.min(h) - get_default('white_space', **kwargs),
                                             np.max(h) + get_default('white_space', **kwargs)])
    if v:
        kwargs['ylim'] = kwargs.get('ylim', [np.min(v) - get_default('white_space', **kwargs),
                                             np.max(v) + get_default('white_space', **kwargs)])

    return common.plot_style(fig=fig, ax=ax, **kwargs)
Example #6
0
def tree(tr, plane='xy', new_fig=True, subplot=False, **kwargs):
    '''
    Generates a 2d figure of the tree's segments. \
    If the tree contains one single point the plot will be empty \
    since no segments can be constructed.

    Parameters:
        tr: Tree \
            neurom.Tree object
        plane: str \
            Accepted values: Any pair of of xyz \
            Default value is 'xy'.treecolor
        linewidth: float \
            Defines the linewidth of the tree, \
            if diameter is set to False. \
            Default value is 1.2.
        alpha: float \
            Defines throughe transparency of the tree. \
            0.0 transparent through 1.0 opaque. \
            Default value is 0.8.
        treecolor: str or None \
            Defines the color of the tree. \
            If None the default values will be used, \
            depending on the type of tree: \
            Basal dendrite: "red" \
            Axon : "blue" \
            Apical dendrite: "purple" \
            Undefined tree: "black" \
            Default value is None.
        new_fig: boolean \
            Defines if the tree will be plotted \
            in the current figure (False) \
            or in a new figure (True) \
            Default value is True.
        subplot: matplotlib subplot value or False \
            If False the default subplot 111 will be used. \
            For any other value a matplotlib subplot \
            will be generated. \
            Default value is False.
        diameter: boolean
            If True the diameter, scaled with diameter_scale factor, \
            will define the width of the tree lines. \
            If False use linewidth to select the width of the tree lines. \
            Default value is True.
        diameter_scale: float \
            Defines the scale factor that will be multiplied \
            with the diameter to define the width of the tree line. \
            Default value is 1.
        limits: list or boolean \
            List of type: [[xmin, ymin, zmin], [xmax, ymax, zmax]] \
            If False the figure will not be scaled. \
            If True the figure will be scaled according to tree limits. \
            Default value is False.
        white_space: float \
            Defines the white space around \
            the boundary box of the morphology. \
            Default value is 1.

    Returns:
        A 2D matplotlib figure with a tree view, at the selected plane.
    '''
    if plane not in ('xy', 'yx', 'xz', 'zx', 'yz', 'zy'):
        return None, 'No such plane found! Please select one of: xy, xz, yx, yz, zx, zy.'

    # Initialization of matplotlib figure and axes.
    fig, ax = common.get_figure(new_fig=new_fig, subplot=subplot)

    # Data needed for the viewer: x,y,z,r
    bounding_box = get_bounding_box(tr)

    def _seg_2d(seg):
        '''2d coordinates needed for the plotting of a segment'''
        horz = getattr(COLS, plane[0].capitalize())
        vert = getattr(COLS, plane[1].capitalize())
        parent_point = seg[0]
        child_point = seg[1]
        horz1 = parent_point[horz]
        horz2 = child_point[horz]
        vert1 = parent_point[vert]
        vert2 = child_point[vert]
        return ((horz1, vert1), (horz2, vert2))

    segs = [_seg_2d(seg) for seg in val_iter(isegment(tr))]

    linewidth = get_default('linewidth', **kwargs)
    # Definition of the linewidth according to diameter, if diameter is True.
    if get_default('diameter', **kwargs):
        scale = get_default('diameter_scale', **kwargs)
        # TODO: This was originally a numpy array. Did it have to be one?
        linewidth = [2 * d * scale for d in iter_neurites(tr, segment_radius)]
        if len(linewidth) == 0:
            linewidth = get_default('linewidth', **kwargs)

    # Plot the collection of lines.
    collection = LineCollection(segs,
                                color=common.get_color(get_default('treecolor', **kwargs),
                                                       get_tree_type(tr)),
                                linewidth=linewidth, alpha=get_default('alpha', **kwargs))

    ax.add_collection(collection)

    kwargs['title'] = kwargs.get('title', 'Tree view')
    kwargs['xlabel'] = kwargs.get('xlabel', plane[0])
    kwargs['ylabel'] = kwargs.get('ylabel', plane[1])
    kwargs['xlim'] = kwargs.get('xlim', [bounding_box[0][getattr(COLS, plane[0].capitalize())] -
                                         get_default('white_space', **kwargs),
                                         bounding_box[1][getattr(COLS, plane[0].capitalize())] +
                                         get_default('white_space', **kwargs)])
    kwargs['ylim'] = kwargs.get('ylim', [bounding_box[0][getattr(COLS, plane[1].capitalize())] -
                                         get_default('white_space', **kwargs),
                                         bounding_box[1][getattr(COLS, plane[1].capitalize())] +
                                         get_default('white_space', **kwargs)])

    return common.plot_style(fig=fig, ax=ax, **kwargs)
Example #7
0
def neuron3d(nrn, new_fig=True, new_axes=True, subplot=False, **kwargs):
    '''
    Generates a figure of the neuron,
    that contains a soma and a list of trees.

    Parameters:
        neuron: Neuron \
        neurom.Neuron object
        linewidth: float \
            Defines the linewidth of the tree, \
            if diameter is set to False. \
            Default value is 1.2.
        alpha: float \
            Defines throughe transparency of the tree. \
            0.0 transparent through 1.0 opaque. \
            Default value is 0.8.
        treecolor: str or None \
            Defines the color of the tree. \
            If None the default values will be used, \
            depending on the type of tree: \
            Basal dendrite: "red" \
            Axon : "blue" \
            Apical dendrite: "purple" \
            Undefined tree: "black" \
            Default value is None.
        new_fig: boolean \
            Defines if the tree will be plotted \
            in the current figure (False) \
            or in a new figure (True) \
            Default value is True.
        subplot: matplotlib subplot value or False \
            If False the default subplot 111 will be used. \
            For any other value a matplotlib subplot \
            will be generated. \
            Default value is False.
        diameter: boolean
            If True the diameter, scaled with diameter_scale factor, \
            will define the width of the tree lines. \
            If False use linewidth to select the width of the tree lines. \
            Default value is True.
        diameter_scale: float \
            Defines the scale factor that will be multiplied \
            with the diameter to define the width of the tree line. \
            Default value is 1.

    Returns:
        A 3D matplotlib figure with a neuron view.
    '''
    # Initialization of matplotlib figure and axes.
    fig, ax = common.get_figure(new_fig=new_fig, new_axes=new_axes,
                                subplot=subplot, params={'projection': '3d'})

    kwargs['new_fig'] = False
    kwargs['subplot'] = subplot
    kwargs['new_axes'] = False
    kwargs['title'] = kwargs.get('title', 'Neuron view')

    soma3d(nrn.soma, **kwargs)

    h = []
    v = []
    d = []

    for temp_tree in nrn.neurites:

        bounding_box = get_bounding_box(temp_tree)

        h.append([bounding_box[0][getattr(COLS, 'X')],
                  bounding_box[1][getattr(COLS, 'X')]])
        v.append([bounding_box[0][getattr(COLS, 'Y')],
                  bounding_box[1][getattr(COLS, 'Y')]])
        d.append([bounding_box[0][getattr(COLS, 'Z')],
                  bounding_box[1][getattr(COLS, 'Z')]])

        tree3d(temp_tree, **kwargs)

    if h:
        kwargs['xlim'] = kwargs.get('xlim', [np.min(h) - get_default('white_space', **kwargs),
                                             np.max(h) + get_default('white_space', **kwargs)])
    if v:
        kwargs['ylim'] = kwargs.get('ylim', [np.min(v) - get_default('white_space', **kwargs),
                                             np.max(v) + get_default('white_space', **kwargs)])
    if d:
        kwargs['zlim'] = kwargs.get('zlim', [np.min(d) - get_default('white_space', **kwargs),
                                             np.max(d) + get_default('white_space', **kwargs)])

    return common.plot_style(fig=fig, ax=ax, **kwargs)
Example #8
0
def tree3d(tr, new_fig=True, new_axes=True, subplot=False, **kwargs):
    '''
    Generates a figure of the tree in 3d.
    If the tree contains one single point the plot will be empty \
    since no segments can be constructed.


    Parameters:
        tr: Tree \
        neurom.Tree object
        linewidth: float \
            Defines the linewidth of the tree, \
            if diameter is set to False. \
            Default value is 1.2.
        alpha: float \
            Defines throughe transparency of the tree. \
            0.0 transparent through 1.0 opaque. \
            Default value is 0.8.
        treecolor: str or None \
            Defines the color of the tree. \
            If None the default values will be used, \
            depending on the type of tree: \
            Basal dendrite: "red" \
            Axon : "blue" \
            Apical dendrite: "purple" \
            Undefined tree: "black" \
            Default value is None.
        new_fig: boolean \
            Defines if the tree will be plotted \
            in the current figure (False) \
            or in a new figure (True) \
            Default value is True.
        subplot: matplotlib subplot value or False \
            If False the default subplot 111 will be used. \
            For any other value a matplotlib subplot \
            will be generated. \
            Default value is False.
        diameter: boolean \
            If True the diameter, scaled with diameter_scale factor, \
            will define the width of the tree lines. \
            If False use linewidth to select the width of the tree lines. \
            Default value is True.
        diameter_scale: float \
            Defines the scale factor that will be multiplied \
            with the diameter to define the width of the tree line. \
            Default value is 1.
        white_space: float \
            Defines the white space around \
            the boundary box of the morphology. \
            Default value is 1.

    Returns:
        A 3D matplotlib figure with a tree view.
    '''
    from mpl_toolkits.mplot3d.art3d import Line3DCollection

    # Initialization of matplotlib figure and axes.
    fig, ax = common.get_figure(new_fig=new_fig, new_axes=new_axes,
                                subplot=subplot, params={'projection': '3d'})

    # Data needed for the viewer: x,y,z,r
    bounding_box = get_bounding_box(tr)

    def _seg_3d(seg):
        '''2d coordinates needed for the plotting of a segment'''
        horz = getattr(COLS, 'X')
        vert = getattr(COLS, 'Y')
        depth = getattr(COLS, 'Z')
        parent_point = seg[0]
        child_point = seg[1]
        horz1 = parent_point[horz]
        horz2 = child_point[horz]
        vert1 = parent_point[vert]
        vert2 = child_point[vert]
        depth1 = parent_point[depth]
        depth2 = child_point[depth]
        return ((horz1, vert1, depth1), (horz2, vert2, depth2))

    segs = [_seg_3d(seg) for seg in val_iter(isegment(tr))]

    linewidth = get_default('linewidth', **kwargs)

    # Definition of the linewidth according to diameter, if diameter is True.
    if get_default('diameter', **kwargs):
        # TODO: This was originally a numpy array. Did it have to be one?
        linewidth = [2 * d * get_default('diameter_scale', **kwargs)
                     for d in iter_neurites(tr, segment_radius)]
        if len(linewidth) == 0:
            linewidth = get_default('linewidth', **kwargs)

    # Plot the collection of lines.
    collection = Line3DCollection(segs,
                                  color=common.get_color(get_default('treecolor', **kwargs),
                                                         get_tree_type(tr)),
                                  linewidth=linewidth, alpha=get_default('alpha', **kwargs))

    ax.add_collection3d(collection)

    kwargs['title'] = kwargs.get('title', 'Tree 3d-view')
    kwargs['xlabel'] = kwargs.get('xlabel', 'X')
    kwargs['ylabel'] = kwargs.get('ylabel', 'Y')
    kwargs['zlabel'] = kwargs.get('zlabel', 'Z')
    kwargs['xlim'] = kwargs.get('xlim', [bounding_box[0][0] - get_default('white_space', **kwargs),
                                         bounding_box[1][0] + get_default('white_space', **kwargs)])
    kwargs['ylim'] = kwargs.get('ylim', [bounding_box[0][1] - get_default('white_space', **kwargs),
                                         bounding_box[1][1] + get_default('white_space', **kwargs)])
    kwargs['zlim'] = kwargs.get('zlim', [bounding_box[0][2] - get_default('white_space', **kwargs),
                                         bounding_box[1][2] + get_default('white_space', **kwargs)])

    return common.plot_style(fig=fig, ax=ax, **kwargs)
Example #9
0
def neuron(nrn, plane='xy', new_fig=True, subplot=False, **kwargs):
    '''
    Generates a 2d figure of the neuron, \
    that contains a soma and a list of trees.

    Parameters:
        neuron: Neuron \
        neurom.Neuron object
        plane: str \
            Accepted values: Any pair of of xyz \
            Default value is 'xy'.treecolor
        linewidth: float \
            Defines the linewidth of the tree, \
            if diameter is set to False. \
            Default value is 1.2.
        alpha: float \
            Defines throughe transparency of the tree. \
            0.0 transparent through 1.0 opaque. \
            Default value is 0.8.
        treecolor: str or None \
            Defines the color of the tree. \
            If None the default values will be used, \
            depending on the type of tree: \
            Basal dendrite: "red" \
            Axon : "blue" \
            Apical dendrite: "purple" \
            Undefined tree: "black" \
            Default value is None.
        new_fig: boolean \
            Defines if the tree will be plotted \
            in the current figure (False) \
            or in a new figure (True) \
            Default value is True.
        subplot: matplotlib subplot value or False \
            If False the default subplot 111 will be used. \
            For any other value a matplotlib subplot \
            will be generated. \
            Default value is False.
        diameter: boolean
            If True the diameter, scaled with diameter_scale factor, \
            will define the width of the tree lines. \
            If False use linewidth to select the width of the tree lines. \
            Default value is True.
        diameter_scale: float \
            Defines the scale factor that will be multiplied \
            with the diameter to define the width of the tree line. \
            Default value is 1.
        limits: list or boolean \
            List of type: [[xmin, ymin, zmin], [xmax, ymax, zmax]] \
            If False the figure will not be scaled. \
            If True the figure will be scaled according to tree limits. \
            Default value is False.

    Returns:
        A 3D matplotlib figure with a tree view, at the selected plane.
    '''
    if plane not in ('xy', 'yx', 'xz', 'zx', 'yz', 'zy'):
        return None, 'No such plane found! Please select one of: xy, xz, yx, yz, zx, zy.'

    # Initialization of matplotlib figure and axes.
    fig, ax = common.get_figure(new_fig=new_fig, subplot=subplot)

    kwargs['new_fig'] = False
    kwargs['subplot'] = subplot

    soma(nrn.soma, plane=plane, **kwargs)

    kwargs['title'] = kwargs.get('title', 'Neuron view')
    kwargs['xlabel'] = kwargs.get('xlabel', plane[0])
    kwargs['ylabel'] = kwargs.get('ylabel', plane[1])

    h = []
    v = []

    for temp_tree in nrn.neurites:

        bounding_box = get_bounding_box(temp_tree)

        h.append([bounding_box[0][getattr(COLS, plane[0].capitalize())],
                  bounding_box[1][getattr(COLS, plane[0].capitalize())]])
        v.append([bounding_box[0][getattr(COLS, plane[1].capitalize())],
                  bounding_box[1][getattr(COLS, plane[1].capitalize())]])

        tree(temp_tree, plane=plane, **kwargs)

    if h:
        kwargs['xlim'] = kwargs.get('xlim', [np.min(h) - get_default('white_space', **kwargs),
                                             np.max(h) + get_default('white_space', **kwargs)])
    if v:
        kwargs['ylim'] = kwargs.get('ylim', [np.min(v) - get_default('white_space', **kwargs),
                                             np.max(v) + get_default('white_space', **kwargs)])

    return common.plot_style(fig=fig, ax=ax, **kwargs)
Example #10
0
def tree3d(tr, new_fig=True, new_axes=True, subplot=False, **kwargs):
    """Generates a figure of the tree in 3d.

    Parameters:
        tr: Tree
        neurom.Tree object

    Options:
        linewidth: float \
            Defines the linewidth of the tree, \
            if diameter is set to False. \
            Default value is 1.2.
        alpha: float \
            Defines throughe transparency of the tree. \
            0.0 transparent through 1.0 opaque. \
            Default value is 0.8.
        treecolor: str or None \
            Defines the color of the tree. \
            If None the default values will be used, \
            depending on the type of tree: \
            Basal dendrite: "red" \
            Axon : "blue" \
            Apical dendrite: "purple" \
            Undefined tree: "black" \
            Default value is None.
        new_fig: boolean \
            Defines if the tree will be plotted \
            in the current figure (False) \
            or in a new figure (True) \
            Default value is True.
        subplot: matplotlib subplot value or False \
            If False the default subplot 111 will be used. \
            For any other value a matplotlib subplot \
            will be generated. \
            Default value is False.
        diameter: boolean
            If True the diameter, scaled with diameter_scale factor, \
            will define the width of the tree lines. \
            If False use linewidth to select the width of the tree lines. \
            Default value is True.
        diameter_scale: float \
            Defines the scale factor that will be multiplied \
            with the diameter to define the width of the tree line. \
            Default value is 1.
        white_space: float \
            Defines the white space around \
            the boundary box of the morphology. \
            Default value is 1.

    Returns:
        A 3D matplotlib figure with a tree view.
    """
    from mpl_toolkits.mplot3d.art3d import Line3DCollection

    # Initialization of matplotlib figure and axes.
    fig, ax = common.get_figure(new_fig=new_fig, new_axes=new_axes, subplot=subplot, params={"projection": "3d"})

    # Data needed for the viewer: x,y,z,r
    bounding_box = get_bounding_box(tr)

    def _seg_3d(seg):
        """2d coordinates needed for the plotting of a segment"""
        horz = getattr(COLS, "X")
        vert = getattr(COLS, "Y")
        depth = getattr(COLS, "Z")
        parent_point = seg[0]
        child_point = seg[1]
        horz1 = parent_point[horz]
        horz2 = child_point[horz]
        vert1 = parent_point[vert]
        vert2 = child_point[vert]
        depth1 = parent_point[depth]
        depth2 = child_point[depth]
        return ((horz1, vert1, depth1), (horz2, vert2, depth2))

    segs = [_seg_3d(seg) for seg in val_iter(isegment(tr))]

    linewidth = get_default("linewidth", **kwargs)

    # Definition of the linewidth according to diameter, if diameter is True.
    if get_default("diameter", **kwargs):
        # TODO: This was originally a numpy array. Did it have to be one?
        linewidth = [2 * d * get_default("diameter_scale", **kwargs) for d in i_segment_radius(tr)]

    # Plot the collection of lines.
    collection = Line3DCollection(
        segs,
        color=common.get_color(get_default("treecolor", **kwargs), get_tree_type(tr)),
        linewidth=linewidth,
        alpha=get_default("alpha", **kwargs),
    )

    ax.add_collection3d(collection)

    kwargs["title"] = kwargs.get("title", "Tree 3d-view")
    kwargs["xlabel"] = kwargs.get("xlabel", "X")
    kwargs["ylabel"] = kwargs.get("ylabel", "Y")
    kwargs["zlabel"] = kwargs.get("zlabel", "Z")
    kwargs["xlim"] = kwargs.get(
        "xlim",
        [
            bounding_box[0][0] - get_default("white_space", **kwargs),
            bounding_box[1][0] + get_default("white_space", **kwargs),
        ],
    )
    kwargs["ylim"] = kwargs.get(
        "ylim",
        [
            bounding_box[0][1] - get_default("white_space", **kwargs),
            bounding_box[1][1] + get_default("white_space", **kwargs),
        ],
    )
    kwargs["zlim"] = kwargs.get(
        "zlim",
        [
            bounding_box[0][2] - get_default("white_space", **kwargs),
            bounding_box[1][2] + get_default("white_space", **kwargs),
        ],
    )

    return common.plot_style(fig=fig, ax=ax, **kwargs)