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. There are various plots which can be used in Pyplot are Line Plot, Contour, Histogram, Scatter, 3D Plot, etc.
matplotlib.pyplot.figure() Function:
The figure() function in pyplot module of matplotlib library is used to create a new figure.
Syntax: matplotlib.pyplot.figure(num=None, figsize=None, dpi=None, facecolor=None, edgecolor=None, frameon=True, FigureClass=, clear=False, **kwargs)
Parameters: This method accept the following parameters that are described below:
- num : This parameter is provided, and a figure with this id already exists.
- figsize(float, float): These parameter are the width, height in inches.
- dpi : This parameter is the resolution of the figure.
- facecolor : This parameter is the background color.
- edgecolor : This parameter is the border color.
- frameon : This parameter suppress drawing the figure frame.
- FigureClass : This parameter use a custom Figure instance.
- clear : This parameter if True and the figure already exists, then it is cleared.
Return value: This method returns the following values:
- figure : This returns the Figure instance returned will also be passed to new_figure_manager in the backends.
Below examples illustrate the matplotlib.pyplot.figure() function in matplotlib.axes:
Example #1:
# Implementation of matplotlib functionimport matplotlib.pyplot as pltimport matplotlib.lines as lines fig = plt.figure()fig.add_artist(lines.Line2D([0, 1, 0.5], [0, 1, 0.3]))fig.add_artist(lines.Line2D([0, 1, 0.5], [1, 0, 0.2])) plt.title('matplotlib.pyplot.figure() Example\n', fontsize = 14, fontweight ='bold') plt.show() |
Output:
Example #2:
# Implementation of matplotlib functionimport matplotlib.pyplot as pltfrom mpl_toolkits.axisartist.axislines import Subplot fig = plt.figure(figsize =(4, 4)) ax = Subplot(fig, 111)fig.add_subplot(ax) ax.axis["left"].set_visible(False)ax.axis["bottom"].set_visible(False) plt.title('matplotlib.pyplot.figure() Example\n', fontsize = 14, fontweight ='bold') plt.show() |
Output:
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