- Matplotlib Basics
- Matplotlib - Home
- Matplotlib - Introduction
- Matplotlib - Vs Seaborn
- Matplotlib - Environment Setup
- Matplotlib - Anaconda distribution
- Matplotlib - Jupyter Notebook
- Matplotlib - Pyplot API
- Matplotlib - Simple Plot
- Matplotlib - Saving Figures
- Matplotlib - Markers
- Matplotlib - Figures
- Matplotlib - Styles
- Matplotlib - Legends
- Matplotlib - Colors
- Matplotlib - Colormaps
- Matplotlib - Colormap Normalization
- Matplotlib - Choosing Colormaps
- Matplotlib - Colorbars
- Matplotlib - Working With Text
- Matplotlib - Text properties
- Matplotlib - Subplot Titles
- Matplotlib - Images
- Matplotlib - Image Masking
- Matplotlib - Annotations
- Matplotlib - Arrows
- Matplotlib - Fonts
- Matplotlib - Font Indexing
- Matplotlib - Font Properties
- Matplotlib - Scales
- Matplotlib - LaTeX
- Matplotlib - LaTeX Text Formatting in Annotations
- Matplotlib - PostScript
- Matplotlib - Mathematical Expressions
- Matplotlib - Animations
- Matplotlib - Celluloid Library
- Matplotlib - Blitting
- Matplotlib - Toolkits
- Matplotlib - Artists
- Matplotlib - Styling with Cycler
- Matplotlib - Paths
- Matplotlib - Path Effects
- Matplotlib - Transforms
- Matplotlib - Ticks and Tick Labels
- Matplotlib - Radian Ticks
- Matplotlib - Dateticks
- Matplotlib - Tick Formatters
- Matplotlib - Tick Locators
- Matplotlib - Basic Units
- Matplotlib - Autoscaling
- Matplotlib - Reverse Axes
- Matplotlib - Logarithmic Axes
- Matplotlib - Symlog
- Matplotlib - Unit Handling
- Matplotlib - Ellipse with Units
- Matplotlib - Spines
- Matplotlib - Axis Ranges
- Matplotlib - Axis Scales
- Matplotlib - Axis Ticks
- Matplotlib - Formatting Axes
- Matplotlib - Axes Class
- Matplotlib - Twin Axes
- Matplotlib - Figure Class
- Matplotlib - Multiplots
- Matplotlib - Grids
- Matplotlib - Object-oriented Interface
- Matplotlib - PyLab module
- Matplotlib - Subplots() Function
- Matplotlib - Subplot2grid() Function
- Matplotlib - Anchored Artists
- Matplotlib - Manual Contour
- Matplotlib - Coords Report
- Matplotlib - AGG filter
- Matplotlib - Ribbon Box
- Matplotlib - Fill Spiral
- Matplotlib - Findobj Demo
- Matplotlib - Hyperlinks
- Matplotlib - Image Thumbnail
- Matplotlib - Plotting with Keywords
- Matplotlib - Create Logo
- Matplotlib - Multipage PDF
- Matplotlib - Multiprocessing
- Matplotlib - Print Stdout
- Matplotlib - Compound Path
- Matplotlib - Sankey Class
- Matplotlib - MRI with EEG
- Matplotlib - Stylesheets
- Matplotlib - Background Colors
- Matplotlib - Basemap
- Matplotlib Event Handling
- Matplotlib - Event Handling
- Matplotlib - Close Event
- Matplotlib - Mouse Move
- Matplotlib - Click Events
- Matplotlib - Scroll Event
- Matplotlib - Keypress Event
- Matplotlib - Pick Event
- Matplotlib - Looking Glass
- Matplotlib - Path Editor
- Matplotlib - Poly Editor
- Matplotlib - Timers
- Matplotlib - Viewlims
- Matplotlib - Zoom Window
- Matplotlib Widgets
- Matplotlib - Cursor Widget
- Matplotlib - Annotated Cursor
- Matplotlib - Buttons Widget
- Matplotlib - Check Buttons
- Matplotlib - Lasso Selector
- Matplotlib - Menu Widget
- Matplotlib - Mouse Cursor
- Matplotlib - Multicursor
- Matplotlib - Polygon Selector
- Matplotlib - Radio Buttons
- Matplotlib - RangeSlider
- Matplotlib - Rectangle Selector
- Matplotlib - Ellipse Selector
- Matplotlib - Slider Widget
- Matplotlib - Span Selector
- Matplotlib - Textbox
- Matplotlib Plotting
- Matplotlib - Line Plots
- Matplotlib - Area Plots
- Matplotlib - Bar Graphs
- Matplotlib - Histogram
- Matplotlib - Pie Chart
- Matplotlib - Scatter Plot
- Matplotlib - Box Plot
- Matplotlib - Arrow Demo
- Matplotlib - Fancy Boxes
- Matplotlib - Zorder Demo
- Matplotlib - Hatch Demo
- Matplotlib - Mmh Donuts
- Matplotlib - Ellipse Demo
- Matplotlib - Bezier Curve
- Matplotlib - Bubble Plots
- Matplotlib - Stacked Plots
- Matplotlib - Table Charts
- Matplotlib - Polar Charts
- Matplotlib - Hexagonal bin Plots
- Matplotlib - Violin Plot
- Matplotlib - Event Plot
- Matplotlib - Heatmap
- Matplotlib - Stairs Plots
- Matplotlib - Errorbar
- Matplotlib - Hinton Diagram
- Matplotlib - Contour Plot
- Matplotlib - Wireframe Plots
- Matplotlib - Surface Plots
- Matplotlib - Triangulations
- Matplotlib - Stream plot
- Matplotlib - Ishikawa Diagram
- Matplotlib - 3D Plotting
- Matplotlib - 3D Lines
- Matplotlib - 3D Scatter Plots
- Matplotlib - 3D Contour Plot
- Matplotlib - 3D Bar Plots
- Matplotlib - 3D Wireframe Plot
- Matplotlib - 3D Surface Plot
- Matplotlib - 3D Vignettes
- Matplotlib - 3D Volumes
- Matplotlib - 3D Voxels
- Matplotlib - Time Plots and Signals
- Matplotlib - Filled Plots
- Matplotlib - Step Plots
- Matplotlib - XKCD Style
- Matplotlib - Quiver Plot
- Matplotlib - Stem Plots
- Matplotlib - Visualizing Vectors
- Matplotlib - Audio Visualization
- Matplotlib - Audio Processing
- Matplotlib Useful Resources
- Matplotlib - Quick Guide
- Matplotlib - Useful Resources
- Matplotlib - Discussion
Matplotlib - Poly Editor
Poly Editor is short for Polygon Editor is an application that allows users to interactively edit and manipulate vertices of a polygon in a graphical environment.
In the context of Matplotlib, a Poly Editor typically refers to a cross-GUI application that allows users to interactively modify polygons displayed on a canvas. This application provides features such as adding, deleting, and moving vertices of a polygon, as well as adjusting its shape and position using mouse clicks and keybindings.
This tutorial will demonstrate how to create a polygon editor using Matplotlib's event handling capabilities.
Creating the Polygon Interactor Class
To create the Poly Editor, define a Python class called PolygonInteractor, which handles interactions with the polygon vertices. This class implements event handling methods to respond to user interactions −
on_draw − Handles the drawing of the polygon and its vertices.
on_button_press − Responds to mouse button presses to select vertices.
on_button_release − Handles mouse button releases.
on_key_press − Handles key presses to toggle vertex markers(using the 't' key), delete vertices(using the ‘d’ key), or insert new vertices(using the 'i' key).
on_mouse_move − Handles mouse movements to drag vertices and update the polygon.
Below is the implementation of the PolygonInteractor class −
class PolygonInteractor:
showverts = True
epsilon = 3
def __init__(self, ax, poly):
if poly.figure is None:
raise RuntimeError('You must first add the polygon to a figure '
'or canvas before defining the interactor')
self.ax = ax
canvas = poly.figure.canvas
self.poly = poly
x, y = zip(*self.poly.xy)
self.line = Line2D(x, y,
marker='o', markerfacecolor='r',
animated=True)
self.ax.add_line(self.line)
self.cid = self.poly.add_callback(self.poly_changed)
self._ind = None # the active vert
canvas.mpl_connect('draw_event', self.on_draw)
canvas.mpl_connect('button_press_event', self.on_button_press)
canvas.mpl_connect('key_press_event', self.on_key_press)
canvas.mpl_connect('button_release_event', self.on_button_release)
canvas.mpl_connect('motion_notify_event', self.on_mouse_move)
self.canvas = canvas
def on_draw(self, event):
self.background = self.canvas.copy_from_bbox(self.ax.bbox)
self.ax.draw_artist(self.poly)
self.ax.draw_artist(self.line)
def poly_changed(self, poly):
vis = self.line.get_visible()
Artist.update_from(self.line, poly)
self.line.set_visible(vis) # don't use the poly visibility state
def get_ind_under_point(self, event):
xy = np.asarray(self.poly.xy)
xyt = self.poly.get_transform().transform(xy)
xt, yt = xyt[:, 0], xyt[:, 1]
d = np.hypot(xt - event.x, yt - event.y)
indseq, = np.nonzero(d == d.min())
ind = indseq[0]
if d[ind] >= self.epsilon:
ind = None
return ind
def on_button_press(self, event):
if not self.showverts:
return
if event.inaxes is None:
return
if event.button != 1:
return
self._ind = self.get_ind_under_point(event)
def on_button_release(self, event):
if not self.showverts:
return
if event.button != 1:
return
self._ind = None
def on_key_press(self, event):
if not event.inaxes:
return
if event.key == 't':
self.showverts = not self.showverts
self.line.set_visible(self.showverts)
if not self.showverts:
self._ind = None
elif event.key == 'd':
ind = self.get_ind_under_point(event)
if ind is not None:
self.poly.xy = np.delete(self.poly.xy,
ind, axis=0)
self.line.set_data(zip(*self.poly.xy))
elif event.key == 'i':
xys = self.poly.get_transform().transform(self.poly.xy)
p = event.x, event.y # display coords
for i in range(len(xys) - 1):
s0 = xys[i]
s1 = xys[i + 1]
d = dist_point_to_segment(p, s0, s1)
if d <= self.epsilon:
self.poly.xy = np.insert(
self.poly.xy, i+1,
[event.xdata, event.ydata],
axis=0)
self.line.set_data(zip(*self.poly.xy))
break
if self.line.stale:
self.canvas.draw_idle()
def on_mouse_move(self, event):
if not self.showverts:
return
if self._ind is None:
return
if event.inaxes is None:
return
if event.button != 1:
return
x, y = event.xdata, event.ydata
self.poly.xy[self._ind] = x, y
if self._ind == 0:
self.poly.xy[-1] = x, y
elif self._ind == len(self.poly.xy) - 1:
self.poly.xy[0] = x, y
self.line.set_data(zip(*self.poly.xy))
self.canvas.restore_region(self.background)
self.ax.draw_artist(self.poly)
self.ax.draw_artist(self.line)
self.canvas.blit(self.ax.bbox)
Defining Utility Function
Define a utility function dist_point_to_segment to calculate the distance between a point and a line segment. This function is used to determine which vertex is closest to the mouse cursor during interaction.
def dist_point_to_segment(p, s0, s1):
s01 = s1 - s0
s0p = p - s0
if (s01 == 0).all():
return np.hypot(*s0p)
p1 = s0 + np.clip((s0p @ s01) / (s01 @ s01), 0, 1) * s01
return np.hypot(*(p - p1))
Initializing the Polygon Editor
To initialize the polygon editor, we need to create an instance of the PolygonInteractor class and pass it the axis object and the polygon object:
if __name__ == '__main__':
import matplotlib.pyplot as plt
from matplotlib.patches import Polygon
theta = np.arange(0, 2*np.pi, 0.2)
r = 1.5
xs = r * np.cos(theta)
ys = r * np.sin(theta)
poly = Polygon(np.column_stack([xs, ys]), animated=True)
fig, ax = plt.subplots()
ax.add_patch(poly)
p = PolygonInteractor(ax, poly)
ax.set_title('Click and drag a point to move it')
ax.set_xlim((-2, 2))
ax.set_ylim((-2, 2))
plt.show()
Running the Poly Editor
By executing the complete code provided below, we will get a Matplotlib window displaying a plot with a polygon. We can interact with the polygon by clicking and dragging its vertices, toggling vertex markers by pressing the ‘t’ key, pressing the 'd' key to delete vertices, and pressing the 'i' key to insert new vertices.
Example
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.backend_bases import MouseButton
from matplotlib.patches import PathPatch
from matplotlib.path import Path
class PathInteractor:
showverts = True
# max pixel distance to count as a vertex hit
epsilon = 5
def __init__(self, pathpatch):
# Initialization and event connections
self.ax = pathpatch.axes
canvas = self.ax.figure.canvas
self.pathpatch = pathpatch
self.pathpatch.set_animated(True)
x, y = zip(*self.pathpatch.get_path().vertices)
self.line, = ax.plot(
x, y, marker='o', markerfacecolor='r', animated=True)
self._ind = None # the active vertex
canvas.mpl_connect('draw_event', self.on_draw)
canvas.mpl_connect('button_press_event', self.on_button_press)
canvas.mpl_connect('key_press_event', self.on_key_press)
canvas.mpl_connect('button_release_event', self.on_button_release)
canvas.mpl_connect('motion_notify_event', self.on_mouse_move)
self.canvas = canvas
def get_ind_under_point(self, event):
# Return the index of the point closest to the event position or None
xy = self.pathpatch.get_path().vertices
xyt = self.pathpatch.get_transform().transform(xy) # to display coords
xt, yt = xyt[:, 0], xyt[:, 1]
d = np.sqrt((xt - event.x)**2 + (yt - event.y)**2)
ind = d.argmin()
return ind if d[ind] < self.epsilon else None
def on_draw(self, event):
# Callback for draws.
self.background = self.canvas.copy_from_bbox(self.ax.bbox)
self.ax.draw_artist(self.pathpatch)
self.ax.draw_artist(self.line)
self.canvas.blit(self.ax.bbox)
def on_button_press(self, event):
# Callback for mouse button presses
if (event.inaxes is None
or event.button != MouseButton.LEFT
or not self.showverts):
return
self._ind = self.get_ind_under_point(event)
def on_button_release(self, event):
# Callback for mouse button releases
if (event.button != MouseButton.LEFT
or not self.showverts):
return
self._ind = None
def on_key_press(self, event):
# Callback for key presses
if not event.inaxes:
return
if event.key == 't':
self.showverts = not self.showverts
self.line.set_visible(self.showverts)
if not self.showverts:
self._ind = None
self.canvas.draw()
def on_mouse_move(self, event):
# Callback for mouse movements
if (self._ind is None
or event.inaxes is None
or event.button != MouseButton.LEFT
or not self.showverts):
return
vertices = self.pathpatch.get_path().vertices
vertices[self._ind] = event.xdata, event.ydata
self.line.set_data(zip(*vertices))
self.canvas.restore_region(self.background)
self.ax.draw_artist(self.pathpatch)
self.ax.draw_artist(self.line)
self.canvas.blit(self.ax.bbox)
fig, ax = plt.subplots()
pathdata = [
(Path.MOVETO, (1.58, -2.57)),
(Path.CURVE4, (0.35, -1.1)),
(Path.CURVE4, (-1.75, 2.0)),
(Path.CURVE4, (0.375, 2.0)),
(Path.LINETO, (0.85, 1.15)),
(Path.CURVE4, (2.2, 3.2)),
(Path.CURVE4, (3, 0.05)),
(Path.CURVE4, (2.0, -0.5)),
(Path.CLOSEPOLY, (1.58, -2.57)),
]
codes, verts = zip(*pathdata)
path = Path(verts, codes)
patch = PathPatch(
path, facecolor='green', edgecolor='yellow', alpha=0.5)
ax.add_patch(patch)
interactor = PathInteractor(patch)
ax.set_title('drag vertices to update path')
ax.set_xlim(-3, 4)
ax.set_ylim(-3, 4)
plt.show()
Output
On executing the above code we will get the following output −
Watch the video below to observe the works of this application −