import numpy as np import matplotlib as mpl import matplotlib.pyplot as plt x = np.linspace(0,2,100) y = np.power(np.sin(x-2),2)*np.exp((-1)*np.power(x,2)) fig = plt.figure() axes = fig.add_axes([0.1,0.1,0.8,0.8]) axes.plot(x,y) axes.set_xlabel('x') axes.set_ylabel('y') axes.set_xlim((0,2)) axes.set_ylim((0,1)) axes.set_title('Exercise 11.1') plt.show()
>>> import numpy as np >>> import matplotlib as mpl >>> import matplotlib.pyplot as plt >>> X = np.random.rand(20,10) >>> b = np.random.rand(10,1) >>> z = np.random.rand(20,1) >>> y = np.dot(X,b)+z >>> D = np.dot(np.transpose(X),X) >>> d = np.dot(np.transpose(X),y) >>> _b = np.dot(np.linalg.inv(D),d) >>> a = np.linspace(0,9,10) >>> fig,axes = plt.subplots() >>> ax.grid(linestyle='-') Traceback (most recent call last): File "<pyshell#38>", line 1, in <module> ax.grid(linestyle='-') NameError: name 'ax' is not defined >>> axes.grid(linestyle='-') >>> True_Cofficient = axes.plot(a,b,'bo') >>> Estimate_Cofficient = axes.plot(a._b,'r+') Traceback (most recent call last): File "<pyshell#41>", line 1, in <module> Estimate_Cofficient = axes.plot(a._b,'r+') AttributeError: 'numpy.ndarray' object has no attribute '_b' >>> Estimate_Cofficient = axes.plot(a,_b,'r+') >>> plt.legend([True_Cofficient,Estimate_Cofficient],['True cofficients','Estimated cofficients']) >>> axes.set_xlabel('Index') Text(0.5,0,'Index') >>> axes.set_ylabel('Value') Text(0,0.5,'Value') >>> axes.set_xlim((0,10)) (0, 10) >>> axes.set_ylim((-2,2)) (-2, 2) >>> axes.set_title('Exercise 11.2') Text(0.5,1,'Exercise 11.2') >>> plt.show()
import numpy as np import matplotlib.pyplot as plt from scipy import stats import matplotlib z=np.random.randn(10000) figure,axes=plt.subplots() c,d,e=axes.hist(z, bins=25,color='b',density=True) axes.set_title('Exercise 11.3:') plt.setp(e, edgecolor='k') kernel=stats.gaussian_kde(z) x=np.linspace(-4,4,1000) y=kernel.pdf(x) axes.plot(x,y,'k-') plt.show()