<jupyter_start><jupyter_text>Best<jupyter_code>import matplotlib.colors as colors
ma1, ma2, ma4, maS = data[weights == weights.max()][0]
best = [ma1, ma2, ma4, maS]
truth = [a1, a2, a4, S]
labels = [r'$\alpha_1$', r'$\alpha_2$', r'$\alpha_4$', r'$S$']
for i in xrange(4):
    for j in xrange(4):
        plt.subplot(4,4,i*4+j+1)
        plt.scatter(data[:100,i], data[:100,j], alpha=.6)
        plt.scatter(best[i], best[j], color='gold')
        plt.scatter(truth[i], truth[j], color='red')
        plt.xlabel(labels[i])
        plt.ylabel(labels[j])
plt.gcf().set_size_inches((12,12))
plt.tight_layout()<jupyter_output><empty_output><jupyter_text>Second Best<jupyter_code>ma1, ma2, ma4, maS = data[weights == np.sort(weights)[-2]][0]
best = [ma1, ma2, ma4, maS]
truth = [a1, a2, a4, S]
labels = [r'$\alpha_1$', r'$\alpha_2$', r'$\alpha_4$', r'$S$']
for i in xrange(4):
    for j in xrange(4):
        plt.subplot(4,4,i*4+j+1)
        plt.scatter(data[:100,i], data[:100,j], alpha=.6)
        plt.scatter(best[i], best[j], color='gold')
        plt.scatter(truth[i], truth[j], color='red')
        plt.xlabel(labels[i])
        plt.ylabel(labels[j])
plt.gcf().set_size_inches((12,12))
plt.tight_layout()<jupyter_output><empty_output><jupyter_text>Worst<jupyter_code>ma1, ma2, ma4, maS = data[weights == np.sort(weights)[0]][0]
best = [ma1, ma2, ma4, maS]
truth = [a1, a2, a4, S]
labels = [r'$\alpha_1$', r'$\alpha_2$', r'$\alpha_4$', r'$S$']
for i in xrange(4):
    for j in xrange(4):
        plt.subplot(4,4,i*4+j+1)
        plt.scatter(data[:100,i], data[:100,j], alpha=.6)
        plt.scatter(best[i], best[j], color='gold')
        plt.scatter(truth[i], truth[j], color='red')
        plt.xlabel(labels[i])
        plt.ylabel(labels[j])
plt.gcf().set_size_inches((12,12))
plt.tight_layout()<jupyter_output><empty_output>
StarcoderdataJupyterStructuredCleanDedup