# -*- coding: utf-8 -*-"""Created on Wed Nov 05 15:18:17 2014@author: dell"""import pandas as pdimport numpy as npimport datetimeimport matplotlib.pyplot as pltimport matplotlib.dates as mdatesif __name__ == ‘__main__‘:    df = pd.read_table(‘carbon.dioxide.txt‘, header = None)    data = np.array(list(df[0].values))        fig = plt.figure()    ax = fig.add_subplot(331)    ax.plot(data)        x = np.linspace(1, len(data), len(data))    ax1 = fig.add_subplot(332)    ax1.plot(data-315)    ax1.plot(((x/350)**2)*35,‘--‘)        ax3 = fig.add_subplot(333)    ax3.plot(data-315)    ax3.plot(((x/350)**1.35)*35, ‘--‘)        ax4 = fig.add_subplot(334)    myres = data-315-((x/350)**1.35)*35    ax4.plot(myres)    ax1 = fig.add_subplot(335)    from scipy.interpolate import UnivariateSpline    #xs = np.linspace(1, len(data), len(data)*100)    xs = np.linspace(1, len(data), 1000)    s = UnivariateSpline(x, myres)    ys = s(xs)    ax1.plot(xs, ys)    ax1.plot(myres)        ax2 = fig.add_subplot(336)    ax2.plot(myres)    ax2.plot(3*np.sin(2*np.pi*x/12))        ax3 = fig.add_subplot(337)    myres1 = myres - 3*np.sin(2*np.pi*x/12)     #myres2 = data - 315-35*(x/350)**1.35 - 3*np.sin(np.pi*2*x/12)    s1 = UnivariateSpline(x, myres1, s = 850)    ys1 = s1(xs)    ax3.plot(xs, ys1)    ax3.plot(myres1)    ax3.axhline(y = 1, ls = ‘--‘)    ax3.axhline(y = -1, ls = ‘:‘)        ax8 = fig.add_subplot(338)    myfun = 315 + (x/350)**1.35*35 + 3*np.sin(2*np.pi*x/12) + 0.75*np.sin(2*np.pi*x/6) + 0.1    ax8.plot(myfun, ls=‘:‘)    ax8.plot(data)        ax9 = fig.add_subplot(339)    x = np.linspace(1, 800, 800)    myfun = 315 + (x/350)**1.35*35 + 3*np.sin(2*np.pi*x/12) + 0.75*np.sin(2*np.pi*x/6) + 0.1    ax9.plot(myfun, ls=‘:‘)    ax9.plot(data)    ax9.set_xlim(1, 800)        plt.show()