Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. Pyplot is a state-based interface to a Matplotlib module which provides a MATLAB-like interface.
matplotlib.pyplot.annotate() Function
The annotate() function in pyplot module of matplotlib library is used to annotate the point xy with text s.
Syntax: angle_spectrum(x, Fs=2, Fc=0, window=mlab.window_hanning, pad_to=None, sides=’default’, **kwargs)
Parameters: This method accept the following parameters that are described below:
- s: This parameter is the text of the annotation.
- xy: This parameter is the point (x, y) to annotate.
- xytext: This parameter is an optional parameter. It is The position (x, y) to place the text at.
- xycoords: This parameter is also an optional parameter and contains the string value.
- textcoords: This parameter contains the string value.Coordinate system that xytext is given, which may be different than the coordinate system used for xy
- arrowprops : This parameter is also an optional parameter and contains dict type.Its default value is None.
- annotation_clip : This parameter is also an optional parameter and contains boolean value.Its default value is None which behaves as True.
Returns: This method returns the annotation.
Below examples illustrate the matplotlib.pyplot.annotate() function in matplotlib.pyplot:
Example #1:
# Implementation of matplotlib.pyplot.annotate()# function import matplotlib.pyplot as pltimport numpy as np fig, geeeks = plt.subplots() t = np.arange(0.0, 5.0, 0.001)s = np.cos(3 * np.pi * t)line = geeeks.plot(t, s, lw = 2) # Annotationgeeeks.annotate('Local Max', xy =(3.3, 1), xytext =(3, 1.8), arrowprops = dict(facecolor ='green', shrink = 0.05),) geeeks.set_ylim(-2, 2) # Plot the Annotation in the graphplt.show() |
Output:
Example #2:
# Implementation of matplotlib.pyplot.annotate()# function import numpy as npimport matplotlib.pyplot as plt x = np.arange(0, 10, 0.005)y = np.exp(-x / 3.) * np.sin(3 * np.pi * x) fig, ax = plt.subplots()ax.plot(x, y)ax.set_xlim(0, 10)ax.set_ylim(-1, 1) # Setting up the parametersxdata, ydata = 5, 0xdisplay, ydisplay = ax.transData.transform((xdata, ydata)) bbox = dict(boxstyle ="round", fc ="0.8")arrowprops = dict( arrowstyle = "->", connectionstyle = "angle, angleA = 0, angleB = 90,\ rad = 10") offset = 72 # Annotationax.annotate('data = (%.1f, %.1f)'%(xdata, ydata), (xdata, ydata), xytext =(-2 * offset, offset), textcoords ='offset points', bbox = bbox, arrowprops = arrowprops) disp = ax.annotate('display = (%.1f, %.1f)'%(xdisplay, ydisplay), (xdisplay, ydisplay), xytext =(0.5 * offset, -offset), xycoords ='figure pixels', textcoords ='offset points', bbox = bbox, arrowprops = arrowprops) # To display the annotationplt.show() |
Output:
