Esempio n. 1
0
def test_get_color():
    nt.ok_(get_color(None, TreeType.basal_dendrite) == "red")
    nt.ok_(get_color(None, TreeType.axon) == "blue")
    nt.ok_(get_color(None, TreeType.apical_dendrite) == "purple")
    nt.ok_(get_color(None, TreeType.soma) == "black")
    nt.ok_(get_color(None, TreeType.undefined) == "green")
    nt.ok_(get_color(None, 'wrong') == "green")
    nt.ok_(get_color('blue', 'wrong') == "blue")
    nt.ok_(get_color('yellow', TreeType.axon) == "yellow")
Esempio n. 2
0
def test_get_color():
    nt.ok_(get_color(None, TreeType.basal_dendrite) == "red")
    nt.ok_(get_color(None, TreeType.axon) == "blue")
    nt.ok_(get_color(None, TreeType.apical_dendrite) == "purple")
    nt.ok_(get_color(None, TreeType.soma) == "black")
    nt.ok_(get_color(None, TreeType.undefined) == "green")
    nt.ok_(get_color(None, 'wrong') == "green")
    nt.ok_(get_color('blue', 'wrong') == "blue")
    nt.ok_(get_color('yellow', TreeType.axon) == "yellow")
Esempio n. 3
0
def soma3d(sm, new_fig=True, new_axes=True, subplot=False, **kwargs):
    '''Generates a 3d figure of the soma.

    Parameters:
        soma: Soma
        neurom.Soma object

    Options:
        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 soma. \
            Soma : "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.

    Returns:
        A 3D matplotlib figure with a soma view.
    '''
    treecolor = kwargs.get('treecolor', None)

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

    # Definition of the tree color depending on the tree type.
    treecolor = common.get_color(treecolor, tree_type=TreeType.soma)

    xs = sm.center[0]
    ys = sm.center[1]
    zs = sm.center[2]

    # Plot the soma as a circle.
    fig, ax = common.plot_sphere(fig, ax, center=[xs, ys, zs], radius=sm.radius, color=treecolor,
                                 alpha=get_default('alpha', **kwargs))

    kwargs['title'] = kwargs.get('title', 'Soma view')
    kwargs['xlabel'] = kwargs.get('xlabel', 'X')
    kwargs['ylabel'] = kwargs.get('ylabel', 'Y')
    kwargs['zlabel'] = kwargs.get('zlabel', 'Z')

    return common.plot_style(fig=fig, ax=ax, **kwargs)
Esempio n. 4
0
def soma3d(sm, new_fig=True, new_axes=True, subplot=False, **kwargs):
    """Generates a 3d figure of the soma.

    Parameters:
        soma: Soma
        neurom.Soma object

    Options:
        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 soma. \
            Soma : "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.

    Returns:
        A 3D matplotlib figure with a soma view.
    """
    treecolor = kwargs.get("treecolor", None)

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

    # Definition of the tree color depending on the tree type.
    treecolor = common.get_color(treecolor, tree_type=TreeType.soma)

    xs = sm.center[0]
    ys = sm.center[1]
    zs = sm.center[2]

    # Plot the soma as a circle.
    fig, ax = common.plot_sphere(
        fig, ax, center=[xs, ys, zs], radius=sm.radius, color=treecolor, alpha=get_default("alpha", **kwargs)
    )

    kwargs["title"] = kwargs.get("title", "Soma view")
    kwargs["xlabel"] = kwargs.get("xlabel", "X")
    kwargs["ylabel"] = kwargs.get("ylabel", "Y")
    kwargs["zlabel"] = kwargs.get("zlabel", "Z")

    return common.plot_style(fig=fig, ax=ax, **kwargs)
Esempio n. 5
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)
Esempio n. 6
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)
Esempio n. 7
0
def soma(sm, plane='xy', new_fig=True, subplot=False, **kwargs):
    '''Generates a 2d figure of the soma.

    Parameters:
        soma: Soma
        neurom.Soma 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 soma. \
            Soma: 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.
        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 2D matplotlib figure with a soma view, at the selected plane.
    '''
    treecolor = kwargs.get('treecolor', None)
    outline = kwargs.get('outline', True)

    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)

    # Definition of the tree color depending on the tree type.
    treecolor = common.get_color(treecolor, tree_type=TreeType.soma)

    # Plot the outline of the soma as a circle, is outline is selected.
    if not outline:
        soma_circle = common.plt.Circle(sm.center, sm.radius, color=treecolor,
                                        alpha=get_default('alpha', **kwargs))
        ax.add_artist(soma_circle)
    else:
        horz = []
        vert = []

        for s_point in sm.iter():
            horz.append(s_point[getattr(COLS, plane[0].capitalize())])
            vert.append(s_point[getattr(COLS, plane[1].capitalize())])

        horz.append(horz[0]) # To close the loop for a soma viewer. This might be modified!
        vert.append(vert[0]) # To close the loop for a soma viewer. This might be modified!

        common.plt.plot(horz, vert, color=treecolor,
                        alpha=get_default('alpha', **kwargs),
                        linewidth=get_default('linewidth', **kwargs))

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

    return common.plot_style(fig=fig, ax=ax, **kwargs)
Esempio n. 8
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)
Esempio n. 9
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)
Esempio n. 10
0
def soma(sm, plane='xy', new_fig=True, subplot=False, **kwargs):
    '''
    Generates a 2d figure of the soma.

    Parameters:
        soma: Soma \
        neurom.Soma 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 soma. \
            Soma: 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.
        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 2D matplotlib figure with a soma view, at the selected plane.
    '''
    treecolor = kwargs.get('treecolor', None)
    outline = kwargs.get('outline', True)

    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)

    # Definition of the tree color depending on the tree type.
    treecolor = common.get_color(treecolor, tree_type=TreeType.soma)

    # Plot the outline of the soma as a circle, is outline is selected.
    if not outline:
        soma_circle = common.plt.Circle(sm.center, sm.radius, color=treecolor,
                                        alpha=get_default('alpha', **kwargs))
        ax.add_artist(soma_circle)
    else:
        horz = []
        vert = []

        for s_point in sm.iter():
            horz.append(s_point[getattr(COLS, plane[0].capitalize())])
            vert.append(s_point[getattr(COLS, plane[1].capitalize())])

        horz.append(horz[0]) # To close the loop for a soma viewer. This might be modified!
        vert.append(vert[0]) # To close the loop for a soma viewer. This might be modified!

        common.plt.plot(horz, vert, color=treecolor,
                        alpha=get_default('alpha', **kwargs),
                        linewidth=get_default('linewidth', **kwargs))

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

    return common.plot_style(fig=fig, ax=ax, **kwargs)
Esempio n. 11
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)