簡(jiǎn)單好用的深度學(xué)習(xí)論文繪圖專用工具包：Science Plot

import numpy as npimport?matplotlib.pyplot?as?pltdef?model(x,?p):????return?x?**?(2?*?p?+?1)?/?(1?+?x?**?(2?*?p))x?=?np.linspace(0.75,?1.25,?201)

fig, ax = plt.subplots()for?p?in?[10,?15,?20,?30,?50,?100]:??????????ax.plot(x,?model(x,?p),?label=p)ax.legend(title='Order')ax.set(xlabel='Voltage?(mV)')ax.set(ylabel='Current?($\mu$A)')ax.autoscale(tight=True)fig.savefig('fig1.jpg',?dpi=300)

with?plt.style.context(['science']):    fig,?ax?=?plt.subplots()????????for?p?in?[10,?15,?20,?30,?50,?100]:???????????????        ax.plot(x,?model(x,?p),?label=p)????????????ax.legend(title='Order')????????????ax.set(xlabel='Voltage?(mV)')????????????ax.set(ylabel='Current?($\mu$A)')????????????ax.autoscale(tight=True)????????????fig.savefig('figures/fig1.pdf')????????????fig.savefig('figures/fig1.jpg',?dpi=300)

with plt.style.context(['science', 'ieee']):    fig, ax = plt.subplots()    for p in [10, 20, 50]:       ????   ax.plot(x,?model(x,?p),?label=p)????????   ax.legend(title='Order')????????ax.set(xlabel='Voltage?(mV)')????????ax.set(ylabel='Current?($\mu$A)')????????ax.autoscale(tight=True)????????fig.savefig('figures/fig2.pdf')????????fig.savefig('figures/fig2.jpg',?dpi=300)

with plt.style.context(['science', 'scatter']):        fig, ax = plt.subplots(figsize=(4,4))        ax.plot([-2, 2], [-2, 2], 'k--')        ax.fill_between([-2, 2], [-2.2, 1.8], [-1.8, 2.2], color='dodgerblue', alpha=0.2, lw=0)    for i in range(7):                x1 = np.random.normal(0, 0.5, 10)                y1 = x1 + np.random.normal(0, 0.2, 10)                ax.plot(x1, y1, label=r"$^\#${}".format(i+1))            ax.legend(title='Sample', loc=2)            ax.set_xlabel(r"$\log_{10}\left(\frac{L_\mathrm{IR}}{\mathrm{L}_\odot}\right)$")            ax.set_ylabel(r"$\log_{10}\left(\frac{L_\mathrm{6.2}}{\mathrm{L}_\odot}\right)$")            ax.set_xlim([-2, 2])            ax.set_ylim([-2, 2])            fig.savefig('figures/fig3.pdf')            fig.savefig('figures/fig3.jpg', dpi=300)