Python matplotlib.patches() Examples

def test_arc_ellipse():
    from matplotlib import patches
    xcenter, ycenter = 0.38, 0.52
    width, height = 1e-1, 3e-1
    angle = -30

    theta = np.deg2rad(np.arange(360))
    x = width / 2. * np.cos(theta)
    y = height / 2. * np.sin(theta)

    rtheta = np.deg2rad(angle)
    R = np.array([
        [np.cos(rtheta), -np.sin(rtheta)],
        [np.sin(rtheta), np.cos(rtheta)]])

    x, y = np.dot(R, np.array([x, y]))
    x += xcenter
    y += ycenter

    fig = plt.figure()
    ax = fig.add_subplot(211, aspect='auto')
    ax.fill(x, y, alpha=0.2, facecolor='yellow', edgecolor='yellow',
            linewidth=1, zorder=1)

    e1 = patches.Arc((xcenter, ycenter), width, height,
                     angle=angle, linewidth=2, fill=False, zorder=2)

    ax.add_patch(e1)

    ax = fig.add_subplot(212, aspect='equal')
    ax.fill(x, y, alpha=0.2, facecolor='green', edgecolor='green', zorder=1)
    e2 = patches.Arc((xcenter, ycenter), width, height,
                     angle=angle, linewidth=2, fill=False, zorder=2)

    ax.add_patch(e2) 

def plot_cloud(self, Y, facecolor='0.8', edgecolor='0.8', alpha=0.5, edgelinestyle='-'):
		### create patches:
		y0,y1       = Y
		x,y0,y1     = self.x.tolist(), y0.tolist(), y1.tolist()
		x           = [x[0]]  + x  + [x[-1]]
		y0          = [y0[0]] + y0 + [y0[-1]]
		y1          = [y1[0]] + y1 + [y1[-1]]
		y1.reverse()
		### concatenate:
		x1          = np.copy(x).tolist()
		x1.reverse()
		x,y         = x + x1, y0 + y1
		patches     = PatchCollection(   [  Polygon(  np.array([x,y]).T  )  ], edgecolors=None)
		### plot:
		self.ax.add_collection(patches)
		pyplot.setp(patches, facecolor=facecolor, edgecolor=edgecolor, alpha=alpha, linestyle=edgelinestyle)
		return patches 

def plot_filled_polygons(self,polygons, facecolour='green', edgecolour='black', linewidth=1, alpha=0.5):
        """
        This function plots a series of shapely polygons but fills them in

        Args:
            ax_list: list of axes
            polygons: list of shapely polygons

        Author: FJC
        """
        from shapely.geometry import Polygon
        from descartes import PolygonPatch
        from matplotlib.collections import PatchCollection

        print('Plotting the polygons...')

        #patches = []
        for key, poly in polygons.items():
            this_patch = PolygonPatch(poly, fc=facecolour, ec=edgecolour, alpha=alpha)
            self.ax_list[0].add_patch(this_patch) 

def relim(self, visible_only=False):
        """
        Recompute the data limits based on current artists. If you want to
        exclude invisible artists from the calculation, set
        ``visible_only=True``

        At present, :class:`~matplotlib.collections.Collection`
        instances are not supported.
        """
        # Collections are deliberately not supported (yet); see
        # the TODO note in artists.py.
        self.dataLim.ignore(True)
        self.dataLim.set_points(mtransforms.Bbox.null().get_points())
        self.ignore_existing_data_limits = True

        for line in self.lines:
            if not visible_only or line.get_visible():
                self._update_line_limits(line)

        for p in self.patches:
            if not visible_only or p.get_visible():
                self._update_patch_limits(p) 

def _update_patch_limits(self, patch):
        """update the data limits for patch *p*"""
        # hist can add zero height Rectangles, which is useful to keep
        # the bins, counts and patches lined up, but it throws off log
        # scaling.  We'll ignore rects with zero height or width in
        # the auto-scaling

        # cannot check for '==0' since unitized data may not compare to zero
        # issue #2150 - we update the limits if patch has non zero width
        # or height.
        if (isinstance(patch, mpatches.Rectangle) and
                ((not patch.get_width()) and (not patch.get_height()))):
            return
        vertices = patch.get_path().vertices
        if vertices.size > 0:
            xys = patch.get_patch_transform().transform(vertices)
            if patch.get_data_transform() != self.transData:
                patch_to_data = (patch.get_data_transform() -
                                    self.transData)
                xys = patch_to_data.transform(xys)

            updatex, updatey = patch.get_transform().\
                contains_branch_seperately(self.transData)
            self.update_datalim(xys, updatex=updatex,
                                updatey=updatey) 

def read_JSON_file(f):
    
    with open(f, 'r') as g:
        d = json.loads(g.read())
    
    img_paths = [x['file_name'] for x in d['images']]
    
    rects = [{'bbox': x['segmentation'][0], 'class': x['category_id'], 'image_id': x['image_id']} for x in d['annotations']]
    
    annotations = defaultdict(list)
    
    for rect in rects:
        r = rect['bbox']
        x0, y0 = min(r[0], r[2], r[4], r[6]), min(r[1], r[3], r[5], r[7])
        x1, y1 = max(r[0], r[2], r[4], r[6]), max(r[1], r[3], r[5], r[7])
        
        r = patches.Rectangle((x0,y0),x1-x0,y1-y0,linewidth=1,edgecolor='g',facecolor='g', alpha=0.4)        
        
        annotations[img_paths[rect['image_id']]].append({'bbox': r, 'cls': d['classes'][rect['class']-1]})
        
    return d['classes'], img_paths, annotations 

def add_patch(self, p):
        """
        Add a :class:`~matplotlib.patches.Patch` *p* to the list of
        axes patches; the clipbox will be set to the Axes clipping
        box.  If the transform is not set, it will be set to
        :attr:`transData`.

        Returns the patch.
        """

        self._set_artist_props(p)
        if p.get_clip_path() is None:
            p.set_clip_path(self.patch)
        self._update_patch_limits(p)
        self.patches.append(p)
        p._remove_method = lambda h: self.patches.remove(h)
        return p 

def add_patch(self, p):
        """
        Add a :class:`~matplotlib.patches.Patch` *p* to the list of
        axes patches; the clipbox will be set to the Axes clipping
        box.  If the transform is not set, it will be set to
        :attr:`transData`.

        Returns the patch.
        """

        self._set_artist_props(p)
        if p.get_clip_path() is None:
            p.set_clip_path(self.patch)
        self._update_patch_limits(p)
        self.patches.append(p)
        p._remove_method = lambda h: self.patches.remove(h)
        return p 

def _update_patch_limits(self, patch):
        """update the data limits for patch *p*"""
        # hist can add zero height Rectangles, which is useful to keep
        # the bins, counts and patches lined up, but it throws off log
        # scaling.  We'll ignore rects with zero height or width in
        # the auto-scaling

        # cannot check for '==0' since unitized data may not compare to zero
        # issue #2150 - we update the limits if patch has non zero width
        # or height.
        if (isinstance(patch, mpatches.Rectangle) and
                ((not patch.get_width()) and (not patch.get_height()))):
            return
        vertices = patch.get_path().vertices
        if vertices.size > 0:
            xys = patch.get_patch_transform().transform(vertices)
            if patch.get_data_transform() != self.transData:
                patch_to_data = (patch.get_data_transform() -
                                    self.transData)
                xys = patch_to_data.transform(xys)

            updatex, updatey = patch.get_transform().\
                contains_branch_seperately(self.transData)
            self.update_datalim(xys, updatex=updatex,
                                updatey=updatey) 

def test_arc_ellipse():
    from matplotlib import patches
    xcenter, ycenter = 0.38, 0.52
    width, height = 1e-1, 3e-1
    angle = -30

    theta = np.arange(0.0, 360.0, 1.0)*np.pi/180.0
    x = width/2. * np.cos(theta)
    y = height/2. * np.sin(theta)

    rtheta = angle*np.pi/180.
    R = np.array([
        [np.cos(rtheta),  -np.sin(rtheta)],
        [np.sin(rtheta), np.cos(rtheta)],
        ])

    x, y = np.dot(R, np.array([x, y]))
    x += xcenter
    y += ycenter

    fig = plt.figure()
    ax = fig.add_subplot(211, aspect='auto')
    ax.fill(x, y, alpha=0.2, facecolor='yellow', edgecolor='yellow', linewidth=1, zorder=1)

    e1 = patches.Arc((xcenter, ycenter), width, height,
                     angle=angle, linewidth=2, fill=False, zorder=2)

    ax.add_patch(e1)

    ax = fig.add_subplot(212, aspect='equal')
    ax.fill(x, y, alpha=0.2, facecolor='green', edgecolor='green', zorder=1)
    e2 = patches.Arc((xcenter, ycenter), width, height,
                     angle=angle, linewidth=2, fill=False, zorder=2)

    ax.add_patch(e2) 

def lasso_onselect(self, verts):
        self.pathlasso = path.Path(verts)
        patch = patches.PathPatch(self.pathlasso, fill=True, alpha=.2, edgecolor=None)
        self.ax1.add_patch(patch)
        self.figure.canvas.draw()
        if self.mode == 1 or self.mode == 4 or self.mode == 7:
            onslice = 'Z %s' % (self.ind + 1)
        elif self.mode == 2 or self.mode == 5 or self.mode == 8:
            onslice = 'X %s' % (self.ind + 1)
        elif self.mode == 3 or self.mode == 6 or self.mode == 9:
            onslice = 'Y %s' % (self.ind + 1)
        self.df = pandas.read_csv('Markings/marking_records.csv')
        df_size = pandas.DataFrame.count(self.df)
        df_rows = df_size['artist']
        self.df.loc[df_rows, 'artist'] = patch
        plist = np.ndarray.tolist(self.pathlasso.vertices)
        plist = ', '.join(str(x) for x in plist)
        self.df.loc[df_rows, 'labelshape'] = 'lasso'
        self.df.loc[df_rows, 'slice'] = onslice
        self.df.loc[df_rows, 'path'] = plist
        self.df.loc[df_rows, 'status'] = 0
        self.df.to_csv('Markings/marking_records.csv', index=False) 

def add_patch(self, p):
        """
        Add a :class:`~matplotlib.patches.Patch` *p* to the list of
        axes patches; the clipbox will be set to the Axes clipping
        box.  If the transform is not set, it will be set to
        :attr:`transData`.

        Returns the patch.
        """

        self._set_artist_props(p)
        if p.get_clip_path() is None:
            p.set_clip_path(self.patch)
        self._update_patch_limits(p)
        self.patches.append(p)
        p._remove_method = self.patches.remove
        return p 

def relim(self, visible_only=False):
        """
        Recompute the data limits based on current artists. If you want to
        exclude invisible artists from the calculation, set
        ``visible_only=True``

        At present, :class:`~matplotlib.collections.Collection`
        instances are not supported.
        """
        # Collections are deliberately not supported (yet); see
        # the TODO note in artists.py.
        self.dataLim.ignore(True)
        self.dataLim.set_points(mtransforms.Bbox.null().get_points())
        self.ignore_existing_data_limits = True

        for line in self.lines:
            if not visible_only or line.get_visible():
                self._update_line_limits(line)

        for p in self.patches:
            if not visible_only or p.get_visible():
                self._update_patch_limits(p) 

def test_arc_angles():
    from matplotlib import patches
    # Ellipse parameters
    w = 2
    h = 1
    centre = (0.2, 0.5)
    scale = 2

    fig, axs = plt.subplots(3, 3)
    for i, ax in enumerate(axs.flat):
        theta2 = i * 360 / 9
        theta1 = theta2 - 45

        ax.add_patch(patches.Ellipse(centre, w, h, alpha=0.3))
        ax.add_patch(patches.Arc(centre, w, h, theta1=theta1, theta2=theta2))
        # Straight lines intersecting start and end of arc
        ax.plot([scale * np.cos(np.deg2rad(theta1)) + centre[0],
                 centre[0],
                 scale * np.cos(np.deg2rad(theta2)) + centre[0]],
                [scale * np.sin(np.deg2rad(theta1)) + centre[1],
                 centre[1],
                 scale * np.sin(np.deg2rad(theta2)) + centre[1]])

        ax.set_xlim(-scale, scale)
        ax.set_ylim(-scale, scale)

        # This looks the same, but it triggers a different code path when it
        # gets large enough.
        w *= 10
        h *= 10
        centre = (centre[0] * 10, centre[1] * 10)
        scale *= 10 

def test_hist_step_filled():
    np.random.seed(0)
    x = np.random.randn(1000, 3)
    n_bins = 10

    kwargs = [{'fill': True}, {'fill': False}, {'fill': None}, {}]*2
    types = ['step']*4+['stepfilled']*4
    fig, axes = plt.subplots(nrows=2, ncols=4)
    axes = axes.flatten()

    for kg, _type, ax in zip(kwargs, types, axes):
        ax.hist(x, n_bins, histtype=_type, stacked=True, **kg)
        ax.set_title('%s/%s' % (kg, _type))
        ax.set_ylim(bottom=-50)

    patches = axes[0].patches
    assert all(p.get_facecolor() == p.get_edgecolor() for p in patches) 

def construct_ball_trajectory(var, r=1., cmap='Blues', start_color=0.4, shape='c'):
    # https://matplotlib.org/examples/color/colormaps_reference.html
    patches = []
    for pos in var:
        if shape == 'c':
            patches.append(mpatches.Circle(pos, r))
        elif shape == 'r':
            patches.append(mpatches.RegularPolygon(pos, 4, r))
        elif shape == 's':
            patches.append(mpatches.RegularPolygon(pos, 6, r))

    colors = np.linspace(start_color, .9, len(patches))
    collection = PatchCollection(patches, cmap=cm.get_cmap(cmap), alpha=1.)
    collection.set_array(np.array(colors))
    collection.set_clim(0, 1)
    return collection 

def _update_patch_limits(self, patch):
        """update the data limits for patch *p*"""
        # hist can add zero height Rectangles, which is useful to keep
        # the bins, counts and patches lined up, but it throws off log
        # scaling.  We'll ignore rects with zero height or width in
        # the auto-scaling

        # cannot check for '==0' since unitized data may not compare to zero
        # issue #2150 - we update the limits if patch has non zero width
        # or height.
        if (isinstance(patch, mpatches.Rectangle) and
                ((not patch.get_width()) and (not patch.get_height()))):
            return
        vertices = patch.get_path().vertices
        if vertices.size > 0:
            xys = patch.get_patch_transform().transform(vertices)
            if patch.get_data_transform() != self.transData:
                patch_to_data = (patch.get_data_transform() -
                                 self.transData)
                xys = patch_to_data.transform(xys)

            updatex, updatey = patch.get_transform().\
                contains_branch_seperately(self.transData)
            self.update_datalim(xys, updatex=updatex,
                                updatey=updatey) 

def add_patch(self, p):
        """
        Add a :class:`~matplotlib.patches.Patch` *p* to the list of
        axes patches; the clipbox will be set to the Axes clipping
        box.  If the transform is not set, it will be set to
        :attr:`transData`.

        Returns the patch.
        """

        self._set_artist_props(p)
        if p.get_clip_path() is None:
            p.set_clip_path(self.patch)
        self._update_patch_limits(p)
        self.patches.append(p)
        p._remove_method = self.patches.remove
        return p 

def get_children(self):
        """return a list of child artists"""
        children = []
        children.extend(self.collections)
        children.extend(self.patches)
        children.extend(self.lines)
        children.extend(self.texts)
        children.extend(self.artists)
        children.extend(self.spines.values())
        children.append(self.xaxis)
        children.append(self.yaxis)
        children.append(self.title)
        children.append(self._left_title)
        children.append(self._right_title)
        children.extend(self.tables)
        children.extend(self.images)
        children.extend(self.child_axes)

        if self.legend_ is not None:
            children.append(self.legend_)
        children.append(self.patch)

        return children 

def _update_patch_limits(self, patch):
        """update the data limits for patch *p*"""
        # hist can add zero height Rectangles, which is useful to keep
        # the bins, counts and patches lined up, but it throws off log
        # scaling.  We'll ignore rects with zero height or width in
        # the auto-scaling

        # cannot check for '==0' since unitized data may not compare to zero
        # issue #2150 - we update the limits if patch has non zero width
        # or height.
        if (isinstance(patch, mpatches.Rectangle) and
                ((not patch.get_width()) and (not patch.get_height()))):
            return
        vertices = patch.get_path().vertices
        if vertices.size > 0:
            xys = patch.get_patch_transform().transform(vertices)
            if patch.get_data_transform() != self.transData:
                patch_to_data = (patch.get_data_transform() -
                                 self.transData)
                xys = patch_to_data.transform(xys)

            updatex, updatey = patch.get_transform().\
                contains_branch_seperately(self.transData)
            self.update_datalim(xys, updatex=updatex,
                                updatey=updatey) 

def add_heatmap(self, title, x, tensor, drawbox=None):
        assert tensor.dim() == 3

        def plot_heatmap(ax, tensor, drawbox=None):
            ax.imshow(tensor.detach().cpu().numpy())
            ax.invert_yaxis()
            ax.label_outer()
            if drawbox is not None:
                rect = patches.Rectangle((0, 0), *drawbox.tolist(), linewidth=1, edgecolor='b', facecolor='none')
                ax.add_patch(rect)

        if tensor.size(0) == 1:
            fig, ax = plt.subplots()
            plot_heatmap(ax, tensor[0], drawbox)
        else:
            fig, axs = plt.subplots(tensor.size(0), sharex=True)
            for i, ax in enumerate(axs):
                plot_heatmap(ax, tensor[i], drawbox)
            fig.subplots_adjust(hspace=2)

        fig.patch.set_color('white')
        fig.tight_layout()
        self.writer.add_figure(title, fig, x) 

def plot_polys(plist,scale=500.0):
        fig, ax = plt.subplots()
        patches = []
        for p in plist:
            poly = Polygon(np.array(p)/scale, True)
            patches.append(poly) 

def plot(self, img):
        """
        Plots and call auxfun_drag class for moving and removing points.
        """
        self.drs = []
        self.updatedCoords = []
        for bpindex, bp in enumerate(self.bodyparts):
            color = self.colormap(self.norm(self.colorIndex[bpindex]))
            self.points = [
                self.dataFrame[self.scorer][bp]["x"].values[self.iter],
                self.dataFrame[self.scorer][bp]["y"].values[self.iter],
            ]
            circle = [
                patches.Circle(
                    (self.points[0], self.points[1]),
                    radius=self.markerSize,
                    fc=color,
                    alpha=self.alpha,
                )
            ]
            self.axes.add_patch(circle[0])
            self.dr = auxfun_drag_label.DraggablePoint(
                circle[0], self.bodyparts[bpindex]
            )
            self.dr.connect()
            self.dr.coords = MainFrame.getLabels(self, self.iter)[bpindex]
            self.drs.append(self.dr)
            self.updatedCoords.append(self.dr.coords)
            if np.isnan(self.points)[0] == False:
                self.buttonCounter.append(bpindex)
        self.figure.canvas.draw()

        return self.buttonCounter 

def polygons_to_path_patches(element):
    """
    Converts Polygons into list of lists of matplotlib.patches.PathPatch
    objects including any specified holes. Each list represents one
    (multi-)polygon.
    """
    paths = element.split(datatype='array', dimensions=element.kdims)
    has_holes = isinstance(element, Polygons) and element.interface.has_holes(element)
    holes = element.interface.holes(element) if has_holes else None
    mpl_paths = []
    for i, path in enumerate(paths):
        splits = np.where(np.isnan(path[:, :2].astype('float')).sum(axis=1))[0]
        arrays = np.split(path, splits+1) if len(splits) else [path]
        subpath = []
        for j, array in enumerate(arrays):
            if j != (len(arrays)-1):
                array = array[:-1]
            if (array[0] != array[-1]).any():
                array = np.append(array, array[:1], axis=0)
            interiors = []
            for interior in (holes[i][j] if has_holes else []):
                if (interior[0] != interior[-1]).any():
                    interior = np.append(interior, interior[:1], axis=0)
                interiors.append(interior)
            vertices = np.concatenate([array]+interiors)
            codes = np.concatenate([ring_coding(array)]+
                                   [ring_coding(h) for h in interiors])
            subpath.append(PathPatch(Path(vertices, codes)))
        mpl_paths.append(subpath)
    return mpl_paths 

def plotConvertedBlock(self):
        """Render an image of the converted block."""
        figName = self._sourceBlock.name + "_1D_cylinder.svg"
        runLog.extra(
            "Plotting equivalent cylindrical block of {} as {}".format(
                self._sourceBlock, figName
            )
        )
        fig, ax = plt.subplots()
        fig.patch.set_visible(False)
        ax.patch.set_visible(False)
        ax.axis("off")
        patches = []
        colors = []
        for circleComp in self.convertedBlock:
            innerR, outerR = (
                circleComp.getDimension("id") / 2.0,
                circleComp.getDimension("od") / 2.0,
            )
            runLog.debug(
                "Plotting {:40s} with {:10.3f} {:10.3f} ".format(
                    circleComp, innerR, outerR
                )
            )
            circle = Wedge((0.0, 0.0), outerR, 0, 360.0, outerR - innerR)
            patches.append(circle)
            colors.append(circleComp.density())
        colorMap = matplotlib.cm
        p = PatchCollection(patches, alpha=1.0, linewidths=0.1, cmap=colorMap.rainbow)
        p.set_array(numpy.array(colors))
        p.set_clim(0, 20)
        ax.add_collection(p)
        ax.autoscale_view(True, True, True)
        plt.savefig(figName)
        return figName 

def __init__(self, proj, ax=None, interactive=True, **kwargs):
        """Create Map with a given projection.

        A `skymapper.Map` holds a predefined projection and `matplotlib` axes
        and figures to enable plotting on the sphere with proper labeling
        and inter/extrapolations.

        It also allows for interactive and exploratory work by updateing the
        maps after pan/zoom events.

        Most of the methods are wrappers of `matplotlib` functions by the same
        names, so that one can mostly interact with a `Map` instance as one
        would do with a `matplotlib.axes`.

        For plotting purposes, it is recommended to switch `interactive` off.

        Args:
            proj: `skymapper.Projection` instance
            ax: `matplotlib.axes` instance, will be created otherwise
            interactive: if pan/zoom is enabled for map updates
            **kwargs: styling of the `matplotlib.patches.Polygon` that shows
                the outline of the map.
        """
        # store arguments to regenerate the map
        self._config = {'__init__': _parseArgs(locals())}
        self.proj = proj
        self._setFigureAx(ax, interactive=interactive)
        self._resolution = 75 # for graticules
        self._setEdge(**kwargs)
        self.ax.relim()
        self.ax.autoscale_view()
        self._setFrame() 

def test_bar_uint8():
    xs = [0, 1, 2, 3]
    b = plt.bar(np.array(xs, dtype=np.uint8), [2, 3, 4, 5], align="edge")
    for (patch, x) in zip(b.patches, xs):
        assert patch.xy[0] == x 

def clear_plot(self, event):
        MainFrame.saveEachImage(self)
        self.figure.delaxes(self.figure.axes[1])
        [p.remove() for p in reversed(self.axes.patches)]
        self.plot(self.img) 

def clear_plot(self, event):
        self.figure.delaxes(self.figure.axes[1])
        [p.remove() for p in reversed(self.axes.patches)]
        self.plot_labels() 

def figlegend(*args, **kwargs):
    """
    Place a legend in the figure.

    *labels*
      a sequence of strings

    *handles*
      a sequence of :class:`~matplotlib.lines.Line2D` or
      :class:`~matplotlib.patches.Patch` instances

    *loc*
      can be a string or an integer specifying the legend
      location

    A :class:`matplotlib.legend.Legend` instance is returned.

    Examples
    --------

    To make a legend from existing artists on every axes::

      figlegend()

    To make a legend for a list of lines and labels::

      figlegend( (line1, line2, line3),
                 ('label1', 'label2', 'label3'),
                 'upper right' )

    .. seealso::

       :func:`~matplotlib.pyplot.legend`

    """
    return gcf().legend(*args, **kwargs)


## Axes ##