import matplotlib.pyplot as plt import autograd.numpy as np from autograd import grad def fun(x): curr = x ans = curr for i in xrange(1000): curr = - curr*x**2 / ((2*i+3)*(2*i+2)) ans = ans + curr if np.abs(curr) < 0.2: break return ans d_fun = grad(fun) dd_fun = grad(d_fun) x = np.linspace(-10, 10, 100) plt.plot(x, map(fun, x),x, map(d_fun, x),x, map(dd_fun, x)) plt.show()  import matplotlib.pyplot as plt import autograd.numpy as np from autograd import grad def tanh(x): return (1 - np.exp(-x)) / (1 + np.exp(-x)) d_fun = grad(tanh) # 1st derivative dd_fun = grad(d_fun) # 2nd derivative ddd_fun = grad(dd_fun) # 3rd derivative dddd_fun = grad(ddd_fun) # 4th derivative ddddd_fun = grad(dddd_fun) # 5th derivative dddddd_fun = grad(ddddd_fun) # 6th derivative x = np.linspace(-7, 7, 200) plt.plot(x, map(tanh, x), x, map(d_fun, x), x, map(dd_fun, x), x, map(ddd_fun, x), x, map(dddd_fun, x), x, map(ddddd_fun, x), x, map(dddddd_fun, x)) plt.show()  |
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