Visualizing Mathematical Functions with Matplotlib
Discover how to create visually appealing plots of mathematical functions using Matplotlib in Python. From simple sine and cosine curves to more complex exponential functions, learn step-by-step how to generate and customize plots for various mathematical expressions.
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Presentation Transcript
# [-2 , 2 ] >>> import numpy as np >>> import matplotlib as mpl >>> import matplotlib.pyplot as plt >>> x=np.linspace(-2*np.pi, 2*np.pi,100) >>> y=np.sin(x) >>> plt.plot(x,y) >>> plt.show()
>>> import numpy as np >>> import matplotlib as mpl >>> import matplotlib.pyplot as plt >>> x=np.linspace(-2*np.pi, 2*np.pi,100) >>> y=np.sin(x) >>> y1=np.cos(x) >>> fig=plt.figure(figsize=(6,3), facecolor= 0.8 ) >>> fig.suptitle( , [-2 ,2 ] , fontsize=12) >>> ax=fig.add_axes((0.1,0.1,0.8,0.8), facecolor= 0.95 ) >>> ax.plot(x,y, g: , linewidth=3) >>> ax.plot(x,y1, r ,linewidth=2) >>> plt.show()
import numpy as np import matplotlib as mpl import matplotlib.pyplot as plt x=np.linspace(-2*np.pi, 2*np.pi,40) y=np.sin(x) y1=np.cos(x) fig, axs=plt.subplots(nrows=2, ncols=1, figsize=(8,5)) fig.tight_layout(pad=1.5) axs[0].set_facecolor('0.95') axs[1].set_facecolor('0.95') axs[0].plot(x,y,marker='o', markersize=8, markerfacecolor='#FFA500', markeredgewidth=1, markeredgecolor='xkcd:petrol') axs[1].plot(x,y1,'g*--',linewidth=2.0) plt.show()
import numpy as np import matplotlib as mpl import matplotlib.pyplot as plt t=np.linspace(0, 70,500) y=np.exp(-t/10)*np.cos(t) fig, axs=plt.subplots(figsize=(8,5)) axs.plot(t,y) axs.set_xlabel('t->secs', labelpad=6, fontsize=10, fontname='sans serif', style='italic') axs.set_ylabel('y=f(t)', labelpad=6, fontsize=10, fontname='serif') axs.set_title(' ', fontsize=14, fontname='monospace', color='green', loc='center', pad=7.0) plt.show() #y(t)=e^(-t/10)cos(t)
