Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack.
Matplotlib.patches.Arrow
The matplotlib.patches.Arrow class is used to for patching an arrow in the plot. it draws arrow from (x, y) to (x + dx, y + dy) and its width is scaled using the width argument.
Syntax: class matplotlib.patches.Arrow(x, y, dx, dy, width=1.0, **kwargs)
Parameters:
- x: It represents the x coordinate of the arrow tail.
- y: It represents the y coordinate of the arrow tail.
- dx: It represents arrow length in the x direction.
- dy: It represents arrow length in the y direction.
- width: It is an optional parameter and has default value as 1. it is the scale factor for the width of the arrow. In default value the tail width is 0.2 and the head width is 0.6.
- **kwargs: These are the patch properties mentioned below in the table;
| Property | Description |
|---|---|
| agg_filter | a filter function that takes a (m, n, 3) float array and a dpi value that returns a (m, n, 3) array |
| alpha | float or None |
| animated | bool |
| antialiased or aa | unknown |
| capstyle | {‘butt’, ’round’, ‘projecting’} |
| clip_box | Bbox |
| clip_on | bool |
| clip_path | [(Path, Transform)|Patch|None] |
| color | color or sequence of rgba tuples |
| contains | callable |
| edgecolor or ec or edgecolors | color or None or ‘auto’ |
| facecolor or fc or facecolors | color or None |
| figure | figure |
| fill | bool |
| gid | str |
| hatch | {‘/’, ‘\’, ‘|’, ‘-‘, ‘+’, ‘x’, ‘o’, ‘O’, ‘.’, ‘*’} |
| in_layout | bool |
| joinstyle | {‘miter’, ’round’, ‘bevel’} |
| linestyle or ls | {‘-‘, ‘–‘, ‘-.’, ‘:’, ”, (offset, on-off-seq), …} |
| linewidth or linewidths or lw | float or None |
| path_effects | AbstractPathEffect |
| picker | None or bool or float or callable |
| path_effects | AbstractPathEffect |
| picker | float or callable[[Artist, Event], Tuple[bool, dict]] |
| rasterized | bool or None |
| sketch_params | (scale: float, length: float, randomness: float) |
| snap | bool or None |
| transform | matplotlib.transforms.Transform |
| url | str | visible | bool |
| zorder | float |
Example 1:
import matplotlib.pyplot as plt import numpy as np import matplotlib.path as mpath import matplotlib.lines as mlines import matplotlib.patches as mpatches from matplotlib.collections import PatchCollection def label(xy, text): # shift y-value for label so that # it's below the artist y = xy[1] - 0.15 plt.text(xy[0], y, text, ha ="center", family ='sans-serif', size = 14) fig, ax = plt.subplots() # create 3x3 grid to plot # the artists grid = np.mgrid[0.2:0.8:3j, 0.2:0.8:3j].reshape(2, -1).T patches = [] # add an arrow arrow = mpatches.Arrow(grid[5, 0] - 0.05, grid[5, 1] - 0.05, 0.1, 0.1, width = 0.1) patches.append(arrow) label(grid[5], " Sample Arrow") colors = np.linspace(0, 1, len(patches)) collection = PatchCollection(patches, cmap = plt.cm.hsv, alpha = 0.3) collection.set_array(np.array(colors)) ax.add_collection(collection) plt.axis('equal') plt.axis('off') plt.tight_layout() plt.show() |
Output:
Example 2:
from matplotlib import pyplot as plt from matplotlib.patches import Rectangle, Arrow import numpy as np nmax = 9xdata = range(nmax) ydata = np.random.random(nmax) plt.ion() fig, ax = plt.subplots() ax.set_aspect("equal") ax.plot(xdata, ydata, 'o-') ax.set_xlim(-1, 10) ax.set_ylim(-1, 4) rect = Rectangle((0, 0), nmax, 1, zorder = 10) ax.add_patch(rect) x0, y0 = 5, 3arrow = Arrow(1, 1, x0-1, y0-1, color ="# aa0088") a = ax.add_patch(arrow) plt.draw() for i in range(nmax): rect.set_x(i) rect.set_width(nmax - i) a.remove() arrow = Arrow(1 + i, 1, x0-i + 1, y0-1, color ="# aa0088") a = ax.add_patch(arrow) fig.canvas.draw_idle() plt.pause(0.4) plt.waitforbuttonpress() plt.show() |
Output:
