acc_eps_multiclass.py

import matplotlib.pyplot as plt
import seaborn as sns
import matplotlib.gridspec as gridspec
import matplotlib
import numpy as np
import pandas as pd


MARKERS = ['x', 'o', '^', 'v', 'D', '<', '>']

titles = ['fgsm', 'bim', 'pgd', 'cw-li']

for i in range(4):
    sns.set_style("whitegrid")
    fig = plt.figure(figsize=(5, 5))
    # gs = gridspec.GridSpec(1, 3, wspace=0.2, hspace=0.)
    ax = fig.gca() # ax = fig.add_subplot(gs[0, i])
    df = pd.read_csv('vis/acc_eps_multiclass/%s.csv' % titles[i])
    ax.plot(df['epsilon'], 100 * df['CXR-2'], marker=MARKERS[0], markersize=5, linewidth=1, label='CXR-2')
    ax.plot(df['epsilon'], 100 * df['CXR-3'], marker=MARKERS[1], markersize=5, linewidth=1, label='CXR-3')
    ax.plot(df['epsilon'], 100 * df['CXR-4'], marker=MARKERS[2], markersize=5, linewidth=1, label='CXR-4')
    ax.set_xlabel(r"Perturbation size epsilon ($\epsilon$)", fontsize=20)
    fig.gca().xaxis.set_ticks(np.arange(0, 1.1, 0.2))
    fig.gca().xaxis.set_major_formatter(matplotlib.ticker.FormatStrFormatter('%.1f/255'))
    ax.set_xlim(0, 0.8 if titles[i] == 'fgsm' else 0.6)
    ax.set_ylabel("Accuracy (%)", fontsize=20)
    # ax.title("CIFAR-10 with clean labels", fontsize=16)
    ax.legend(loc='upper right', ncol=1, fontsize=20)  # lower/center right
    ax.set_ylim(bottom=-0.1, top=100.0)
    plt.xticks(size=15)
    plt.yticks(size=15)
    plt.tight_layout()
    plt.savefig('vis/acc_eps_multiclass/acc_eps_mul_%s.pdf' % titles[i], dpi=300)
    plt.show()

def plot_test_acc_curve(models, model_names):
    sns.set_style("whitegrid")

    # plot initialization
    fig = plt.figure(figsize=(15, 6))
    gs = gridspec.GridSpec(1, 2, wspace=0.2, hspace=0.)

    ax1 = fig.add_subplot(gs[0, 0])
    ax2 = fig.add_subplot(gs[0, 1])
    for i, model in enumerate(models):
        acc = np.load('log/acc_%s_cifar-10_0.npy' % model)
        acc = acc[1]
        xnew = np.arange(0, len(acc), 5)
        acc = acc[xnew]
        ax1.plot(xnew, acc, marker=MARKERS[i], markersize=5, linewidth=1, label='%s' % model_names[i])
        acc = np.load('log/acc_%s_cifar-10_40.npy' % model)
        acc = acc[1]
        acc = acc[xnew]
        ax2.plot(xnew, acc, marker=MARKERS[i], markersize=5, linewidth=1, label='%s' % model_names[i])

    ax1.set_xlabel("Epoch", fontsize=15)
    # ax1.xaxis.set_ticks(np.arange(0, 10, 1))
    ax1.set_ylabel("Test accuracy", fontsize=15)
    ax1.set_title("CIFAR-10 with clean labels", fontsize=16)
    ax1.legend(loc='lower right', ncol=2, fontsize=13)  # lower/center right
    ax1.set_ylim(bottom=0.0, top=1.0)

    ax2.set_xlabel("Epoch", fontsize=15)
    # ax2.xaxis.set_ticks(np.arange(0, 10, 1))
    ax2.set_ylabel("Test accuracy", fontsize=15)
    ax2.set_title("CIFAR-10 with 40% symmetric noisy labels", fontsize=16)
    ax2.legend(loc='lower right', ncol=2, fontsize=13)  # lower/center right
    ax2.set_ylim(bottom=0.0, top=1.0)


    fig.savefig("plots/test_acc_curve.png", dpi=300)
    plt.show()