import matplotlib.pyplot as plt import pandas as pd from nas_201_api import NASBench201API as API # from naswot.score_networks import get_nasbench201_idx_score # from naswot import datasets as dt # from naswot import nasspace # class Args(): # pass # args = Args() # args.trainval = True # args.augtype = 'none' # args.repeat = 1 # args.score = 'hook_logdet' # args.sigma = 0.05 # args.nasspace = 'nasbench201' # args.batch_size = 128 # args.GPU = '0' # args.dataset = 'cifar10' # args.api_loc = '/nfs/data3/hanzhang/nasbenchDiT/graph_dit/NAS-Bench-201-v1_1-096897.pth' # args.data_loc = '../cifardata/' # args.seed = 777 # args.init = '' # args.save_loc = 'results' # args.save_string = 'naswot' # args.dropout = False # args.maxofn = 1 # args.n_samples = 100 # args.n_runs = 500 # args.stem_out_channels = 16 # args.num_stacks = 3 # args.num_modules_per_stack = 3 # args.num_labels = 1 # searchspace = nasspace.get_search_space(args) # train_loader = dt.get_data(args.dataset, args.data_loc, args.trainval, args.batch_size, args.augtype, args.repeat, args) # device = torch.device('cuda:2') source = '/nfs/data3/hanzhang/nasbenchDiT/graph_dit/NAS-Bench-201-v1_1-096897.pth' api = API(source) # 示例百分数列表,精确到小数点后两位 # percentages = [5.12, 15.78, 25.43, 35.22, 45.99, 55.34, 65.12, 75.68, 85.99, 95.25, 23.45, 12.34, 37.89, 58.67, 64.23, 72.15, 81.76, 99.99, 42.11, 61.58, 77.34, 14.56] percentages = [] len_201 = 15625 for i in range(len_201): # percentage = get_nasbench201_idx_score(i, train_loader, searchspace, args, device) results = api.query_by_index(i, 'cifar10') result = results[111].get_eval('ori-test') percentages.append(result) # 定义10%区间 bins = [i for i in range(0, 101, 10)] # 对数据进行分箱,计算每个区间的数据量 hist, bin_edges = pd.cut(percentages, bins=bins, right=False, retbins=True, include_lowest=True) bin_counts = hist.value_counts().sort_index() total_counts = len(percentages) percentages_in_bins = (bin_counts / total_counts) * 100 # 绘制条形图 plt.figure(figsize=(10, 6)) bars = plt.bar(bin_counts.index.astype(str), bin_counts.values, width=0.9, color='skyblue') for bar, percentage in zip(bars, percentages_in_bins): plt.text(bar.get_x() + bar.get_width() / 2, bar.get_height(), f'{percentage:.2f}%', ha='center', va='bottom') # 添加标题和标签 plt.title('Distribution of Percentages in 10% Intervals') plt.xlabel('Percentage Interval') plt.ylabel('Count') # 显示图表 plt.xticks(rotation=45) plt.savefig('barplog.png')