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plots.py
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plots.py
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# -*- coding: utf-8 -*-
# @Time : 2020/9/5 23:04
# @Author : Hui Wang
import numpy as np
import matplotlib
matplotlib.rcParams['pdf.fonttype'] = 42
matplotlib.rcParams['ps.fonttype'] = 42
import matplotlib.pyplot as plt
plt.rcParams["font.family"] = "Times New Roman"
def plot_bar():
result1 = [0.0714, 0.0840, 0.0784, 0.0709]
# Arial
# plt.rcParams['font.sans-serif'] = ['Times New Roman'] # 如果要显示中文字体,则在此处设为：SimHei
# plt.rcParams['axes.unicode_minus'] = False # 显示负号
plt.figure(figsize=(5, 4))
plt.ylim(0.067, 0.088)
labels = ['1', '2', '3', '4']
# from matplotlib.font_manager import FontProperties
# myfont = FontProperties(fname='times.ttf', size=25)
plt.xticks(fontsize=15)
plt.yticks(fontsize=15)
colors = ['tomato'] * 4
# /, \, |, -, +, x, o, O,., * 。
plt.bar(np.arange(len(result1)), result1, ec='b', hatch=2 * '.', width=0.5,
tick_label=labels,
color=colors)
plt.tight_layout()
plt.savefig(f'pics/bar.png', format='png') # 建议保存为svg格式,再用inkscape转为矢量图emf后插入word中
plt.show()
def plot_line():
x = np.array([1, 2, 3, 4, 5])
model1 = np.array([0.2160, 0.1925, 0.1854, 0.1513, 0.1132])
Ours = np.array([0.2416, 0.2331, 0.2165, 0.1943, 0.1715])
# label在图示(legend)中显示。若为数学公式,则最好在字符串前后添加"$"符号
# color：b:blue、g:green、r:red、c:cyan、m:magenta、y:yellow、k:black、w:white、、、
# 线型：- -- -. : ,
# marker：. , o v < * + 1
plt.figure(figsize=(5, 4))
# linestyle = "-"
plt.grid(linestyle="-.") # 设置背景网格线为虚线
ax = plt.gca()
# ax.spines['top'].set_visible(False) # 去掉上边框
# ax.spines['right'].set_visible(False) # 去掉右边框
linewidth = 2.0
markersize = 7
plt.plot(x, model1, marker='s', markersize=markersize, color="blue", label="Model1", linewidth=linewidth)
plt.plot(x, Ours, marker='X', markersize=markersize, color="tomato", label="Ours", linewidth=linewidth)
group_labels = ['-', '20%', '40%', '60%', '80%']
plt.xticks(x, group_labels, fontsize=15) # 默认字体大小为10
y_ticks = [0.10, 0.15, 0.20, 0.25, 0.30]
y_lables = ['0.10', '0.15', '0.20', '0.25', '0.30']
plt.yticks(np.array(y_ticks), y_lables, fontsize=15)
# plt.title("example", fontsize=12, fontweight='bold') # 默认字体大小为12
# plt.text(1, label_position, dataset,fontsize=25, fontweight='bold')
# plt.xlabel("Edge Miss Rate", fontsize=15)
plt.ylabel(f"HR@20", fontsize=15)
plt.xlim(0.5, 5.5) # 设置x轴的范围
plt.ylim(0.08, 0.30)
# plt.legend()
# 显示各曲线的图例 loc=3 lower left
plt.legend(loc=0, numpoints=1, ncol=2)
leg = plt.gca().get_legend()
ltext = leg.get_texts()
plt.setp(ltext, fontsize=15)
# plt.setp(ltext, fontsize=25, fontweight='bold') # 设置图例字体的大小和粗细
plt.tight_layout()
plt.savefig(f'pics/line.png', format='png') # 建议保存为svg格式,再用inkscape转为矢量图emf后插入word中
plt.show()
def plot_multi_bar():
model1 = np.array([0.0409, 0.0543, 0.0943, 0.1115, 0.1363])
model2 = np.array([0.0351, 0.0557, 0.0916, 0.1315, 0.1860])
model3 = np.array([0.0586, 0.0865, 0.1046, 0.1476, 0.2160])
Ours = np.array([0.1043, 0.1344, 0.1638, 0.2035, 0.2446])
# label在图示(legend)中显示。若为数学公式,则最好在字符串前后添加"$"符号
# color：b:blue、g:green、r:red、c:cyan、m:magenta、y:yellow、k:black、w:white、、、
# 线型：- -- -. : ,
# marker：. , o v < * + 1
plt.figure(figsize=(7, 4))
# linestyle = "-"
x = np.arange(5)
# n 为有几个柱子
total_width, n = 0.8, 4
width = total_width / n
x = x - (total_width - width) / n
# low = 0.05
# up = 0.44
low = 0.02
up = 0.27
plt.ylim(low, up)
# plt.xlabel("Amount of Data", fontsize=15)
plt.ylabel(f"HR@20", fontsize=20)
labels = ['Model1', 'Model2', 'Model3', 'Ours']
# 'tomato', 'blue', 'orange', 'green', 'purple', 'deepskyblue'
plt.bar(x, model1, width=width, color='blue', edgecolor='w') # , edgecolor='k',)
plt.bar(x + width, model2, width=width, color='green', edgecolor='w') # , edgecolor='k',)
plt.bar(x + 2*width, model3, width=width, color='orange', edgecolor='w') # , edgecolor='k',)
plt.bar(x + 3*width, Ours, width=width, color='tomato', edgecolor='w') # , edgecolor='k',)
plt.xticks(x +1.5*width, labels=['20%', '40%', '60%', '80%', '100%'], fontsize=20)
y_lables = ['0.02', '0.08', '0.14', '0.20', '0.26']
y_ticks = [float(i) for i in y_lables]
# plt.yscale('linear')
# y_ticks = [0.25, 0.30, 0.35, 0.40, 0.45]
# y_lables = ['0.25', '0.30', '0.35', '0.40', '0.45']
plt.yticks(np.array(y_ticks), y_lables, fontsize=20)#bbox_to_anchor=(0.30, 1)
plt.legend(labels=labels, ncol=2,
prop={'size': 14})
plt.tight_layout()
plt.savefig('./pics/multi_bar.png', format='png')
plt.show()
# 建议保存为svg格式,再用inkscape转为矢量图emf后插入word中
def plot_bar_and_line():
fontsize=20
result1 = [0.1967, 0.2103, 0.2398, 0.2446, 0.2387]
l = [i for i in range(5)]
lx = ['2', '3', '4', '5', '6']
fig = plt.figure()
ax1 = fig.add_subplot(111)
plt.bar(l, result1, alpha=0.3, color='blue', label='HR@20')
# left_axis.set_ylim(0.80, 0.96)
# left_axis.set_yticks(np.arange(0.80, 0.97, 0.04))
ax1.set_ylim([0.18, 0.26])
ax1.set_yticks(np.arange(0.18, 0.26, 0.015))
# ax1.set_ylabel('AUC', fontsize=fontsize)
plt.legend(loc="upper left", prop={'size': 15})
plt.xticks(l, lx, fontsize=fontsize)
plt.yticks(fontsize=fontsize)
result2 = [0.0823, 0.0976, 0.1054, 0.1185, 0.1045]
ax2 = ax1.twinx() # this is the important function
ax2.plot(l, result2, 'or-', label='NDCG@20', color='green')
ax2.legend(loc=2)
ax2.set_ylim([0.07, 0.13])
ax2.set_yticks(np.arange(0.07, 0.13, 0.01))
# ax2.set_ylabel('Log-loss', fontsize=fontsize)
plt.text(1.5, 0.06, "Num", fontsize=20)
plt.legend(loc="upper right", prop={'size': 15})
plt.yticks(fontsize=fontsize)
plt.tight_layout()
# , bbox_inches='tight', pad_inches=0.05, dpi=100
plt.savefig('pics/bar_and_line.png', format='png')
plt.show()
def plot_scatters():
# label在图示(legend)中显示。若为数学公式,则最好在字符串前后添加"$"符号
# color：b:blue、g:green、r:red、c:cyan、m:magenta、y:yellow、k:black、w:white、、、
# 线型：- -- -. : ,
# marker：. , o v < * + 1
plt.figure(figsize=(5, 4))
# linestyle = "-"
# plt.grid(linestyle = "-.") # 设置背景网格线为虚线
ax = plt.gca()
# ax.spines['top'].set_visible(False) # 去掉上边框
# ax.spines['right'].set_visible(False) # 去掉右边框
linewidth = 2.0
markersize = 25
plt.scatter(np.array([0.1394]), np.array([2.4]), marker='o', s=markersize, color="tomato", label="Model1")
plt.scatter(np.array([0.1353]), np.array([3.7]), marker='d', s=markersize, color="orange", label="Model2")
plt.scatter(np.array([0.1860]), np.array([8.7]), marker='+', s=markersize, color="gray", label="Model3")
plt.scatter(np.array([0.1478]), np.array([60]), marker='<', s=markersize, color="purple", label="Model4")
plt.scatter(np.array([0.1363]), np.array([6.7]), marker='^', s=markersize, color="peru", label="Model5")
plt.scatter(np.array([0.1683]), np.array([16]), marker='p', s=markersize, color="maroon", label="Model6")
plt.scatter(np.array([0.1922]), np.array([9.8]), marker='s', s=markersize, color="blue", label="Model7")
plt.scatter(np.array([0.1823]), np.array([90]), marker='>', s=markersize, color="lime", label="Model8")
plt.scatter(np.array([0.1875]), np.array([100.54]), marker='x', s=markersize, color="green", label="Model9")
plt.scatter(np.array([0.2160]), np.array([228]), marker='d', s=markersize, color="blue", label="Model10")
plt.scatter(np.array([0.2446]), np.array([66.02]), marker='*', s=markersize, color="red", label="Ours")
x_labels = ['0.11', '0.15', '0.19', '0.23', '0.27']
x_ticks = [float(i) for i in x_labels]
plt.xticks(np.array(x_ticks), x_labels, fontsize=15)
plt.xlabel("HR@20", fontsize=15)
plt.ylabel(f"Inference Time", fontsize=15)
plt.xlim(0.11, 0.27) # 设置x轴的范围
plt.ylim(0, 250)
y_labels = ['0', '50', '100', '150', '200', '250']
y_ticks = [int(i) for i in y_labels]
plt.yticks(np.array(y_ticks), y_labels, fontsize=15)
# plt.legend() #显示各曲线的图例
plt.legend(loc=0, numpoints=1, ncol=1, bbox_to_anchor=(1.05, 1.0), borderaxespad=0.)
leg = plt.gca().get_legend()
ltext = leg.get_texts()
plt.setp(ltext, fontsize=10) # 设置图例字体的大小和粗细
plt.tight_layout()
plt.savefig(f'./pics/scatter.png', format='png') # 建议保存为svg格式,再用inkscape转为矢量图emf后插入word中
plt.show()
def plot_hetmap():
import seaborn as sns
import numpy as np
x = np.array(
[[0.3761, 0.3704, 0.3674],
[0.3568, 0.3318, 0.3319],
[0.3461, 0.3335, 0.3182]]
)
# x = x.T
plt.figure(figsize=(5, 4))
ax = sns.heatmap(x, annot=True, fmt=".4f", annot_kws={'size': 15, 'color': 'black'}, # 'weight': 'bold'
linewidths=0.5, cmap='YlOrRd', square=True)
x_lables = ['Model1', 'Model2', 'Model3']
ax.set_yticklabels(ax.get_yticklabels(), rotation=0)
ax.set_xticklabels(ax.get_xticklabels(), rotation=0)
ax.xaxis.tick_top()
# plt.title('Target Model', fontsize=15)
plt.xlabel('Target Model', fontsize=15)
plt.ylabel('Complementary Model', fontsize=15)
plt.xticks([0.5, 1.5, 2.5], x_lables, fontsize=15) # 默认字体大小为10
plt.yticks([0.5, 1.5, 2.5], x_lables, fontsize=15) # 默认字体大小为10
cax = plt.gcf().axes[-1]
cax.tick_params(labelsize=15)
plt.tight_layout()
plt.savefig('./pics/heatmap.png', format='png')
plt.show()
# text的位置确认有点拉
def plot_ablation_bar_in_one():
models = ['Base', '$\\neg$ A', '$\\neg$ B', '$\\neg$ C', "Ours"]
x_label_size = 35
rotation = 0
# 从这里开始选择数据
labels = models
# plt.rcParams['font.sans-serif'] = ['Times New Roman'] # 如果要显示中文字体,则在此处设为：SimHei
# plt.rcParams['axes.unicode_minus'] = False # 显示负号
# # plt.rcParams['savefig.dpi'] = 300 # 图片像素
# plt.rcParams['figure.dpi'] = 300 # 分辨率
plt.figure(figsize=(40, 7))
colors = ['blue', 'green', 'red']
low = 0.34
up = 0.391
Beauty = [0.3488, 0.3687, 0.3688, 0.3546, 0.3761]
data=Beauty
plt.subplot(141)
plt.ylim(low, up)
position = (up - low) * 0.9 + low
plt.text(1.4, position, 'Beauty', fontsize=40)
plt.xticks(fontsize=x_label_size, rotation=rotation)
my_y_ticks = np.arange(low, up, 0.01)
plt.yticks(my_y_ticks, fontsize=40)
# plt.xlabel("Meituan", fontsize=20, fontweight='bold')
# hatches = ["\\"] + ["."] * 4 + ["/"]
# /, \, |, -, +, x, o, O,., * 。
plt.bar([0], data[0], width=0.5, color=colors[0], hatch=".", edgecolor='w')
plt.bar([1, 2, 3], data[1:4], width=0.5, color=colors[1], hatch=".", edgecolor='w')
plt.bar([4], data[4], width=0.5, color=colors[2], hatch=".", edgecolor='w')
plt.xticks([0, 1, 2, 3, 4], labels)
# plt.bar(np.arange(len(data)), data, width=0.5, tick_label=labels, color=colors, hatches=hatches)
low = 0.32
up = 0.361
Sport = [0.328, 0.3385, 0.3346, 0.3335, 0.3473]
data = Sport
plt.subplot(142)
plt.ylim(low, up)
position = (up - low) * 0.9 + low
plt.text(1.4, position, 'Sports', fontsize=40)
plt.xticks(fontsize=x_label_size, rotation=rotation)
my_y_ticks = np.arange(low, up, 0.01)
plt.yticks(my_y_ticks, fontsize=40)
# plt.xlabel("Beauty", fontsize=20, fontweight='bold')
# colors = ['darkorange'] * 1 + ['royalblue'] * 4 + ['red']
# /, \, |, -, +, x, o, O,., * 。
# plt.bar(np.arange(len(data)), data, hatch=2 * '.', width=0.5,
# tick_label=labels, color=colors,
# # edgecolor='k'
# )
plt.bar([0], data[0], width=0.5, color=colors[0], hatch="\\", edgecolor='w')
plt.bar([1, 2, 3], data[1:4], width=0.5, color=colors[1], hatch=".", edgecolor='w')
plt.bar([4], data[4], width=0.5, color=colors[2], hatch="/", edgecolor='w')
plt.xticks([0, 1, 2, 3, 4], labels)
low = 0.34
up = 0.391
Toys = [0.3455, 0.3671, 0.3588, 0.3611, 0.3749]
data = Toys
plt.subplot(143)
plt.ylim(low, up)
position = (up - low) * 0.9 + low
plt.text(1.4, position, 'Toys', fontsize=40)
plt.xticks(fontsize=x_label_size, rotation=rotation)
my_y_ticks = np.arange(low, up, 0.01)
plt.yticks(my_y_ticks, fontsize=40)
# plt.xlabel("Sports", fontsize=20, fontweight='bold')
# colors = ['darkorange'] * 1 + ['royalblue'] * 4 + ['red']
# /, \, |, -, +, x, o, O,., * 。
# plt.bar(np.arange(len(data)), data, hatch=2 * '.', width=0.5,
# tick_label=labels, color=colors,
# # edgecolor='k'
# )
plt.bar([0], data[0], width=0.5, color=colors[0], hatch="\\", edgecolor='w')
plt.bar([1, 2, 3], data[1:4], width=0.5, color=colors[1], hatch=".", edgecolor='w')
plt.bar([4], data[4], width=0.5, color=colors[2], hatch="/", edgecolor='w')
plt.xticks([0, 1, 2, 3, 4], labels)
low = 0.49
up = 0.54
Yelp = [0.496, 0.523, 0.5231, 0.5167, 0.53]
data = Yelp
plt.subplot(144)
plt.ylim(low, up)
position = (up - low) * 0.9 + low
plt.text(1.6, position, 'Yelp', fontsize=40)
plt.xticks(fontsize=x_label_size, rotation=rotation)
my_y_ticks = np.arange(low, up, 0.01)
plt.yticks(my_y_ticks, fontsize=40)
# plt.xlabel("Toys", fontsize=20, fontweight='bold')
# colors = ['darkorange'] * 1 + ['royalblue'] * 4 + ['red']
# /, \, |, -, +, x, o, O,., * 。
# plt.bar(np.arange(len(data)), data, hatch=2 * '.', width=0.5,
# tick_label=labels, color=colors,
# # edgecolor='k'
# )
plt.bar([0], data[0], width=0.5, color=colors[0], hatch="\\", edgecolor='w')
plt.bar([1, 2, 3], data[1:4], width=0.5, color=colors[1], hatch=".", edgecolor='w')
plt.bar([4], data[4], width=0.5, color=colors[2], hatch="/", edgecolor='w')
plt.xticks([0, 1, 2, 3, 4], labels)
plt.tight_layout()
plt.subplots_adjust(wspace=0.3, hspace=0)
# 建议保存为svg格式,再用inkscape转为矢量图emf后插入word中
plt.savefig('./pics/ablation.png', format='png')
plt.show()
import matplotlib.patches as mpatches
# 上下对齐的两个子图
def plot_two_bar_in_one():
beauty_base = [0.14, 0.16, 0.23, 0.25, 0.27, 0.30, 0.33, 0.34]
beauty_grow = [0.15, 0.17, 0.24, 0.26, 0.28, 0.31, 0.34, 0.35]
toys_base = [0.14, 0.16, 0.23, 0.25, 0.27, 0.30, 0.33, 0.34]
toys_grow = [0.15, 0.17, 0.24, 0.26, 0.28, 0.31, 0.34, 0.35]
# plt.xlabel("Extend", fontsize=20, fontweight='bold')
# plt.ylabel("NDCG@10", fontsize=25)
# plt.text(0.1, 0.55, data_name, fontsize=20, fontweight='bold')
x = np.arange(8)
total_width, n = 0.8, 2
width = total_width / n
x = x - (total_width - width) / n
lables = ['Model1', 'Model2', 'Model3', 'Model4',
'Model5', 'Model6', 'Model7', 'Model8']
# plt.rcParams['font.sans-serif'] = ['Times New Roman'] # 如果要显示中文字体,则在此处设为：SimHei
# plt.rcParams['axes.unicode_minus'] = False # 显示负号
# # from matplotlib.font_manager import FontProperties
# myfont = FontProperties(fname='times.ttf', size=25)
fig, (ax1, ax2) = plt.subplots(
2, 1, sharex=True, figsize=(20, 16), dpi=100)
beauty_base = np.array(beauty_base)
beauty_grow = np.array(beauty_grow)
low = 0.13
up = 0.41
ax1.set_ylim(low, up)
ax1.bar(x, beauty_base, width=width, color='royalblue', hatch=".", edgecolor='w') # , edgecolor='k',)
ax1.bar(x + width, beauty_grow, width=width, color='tomato', hatch="/", edgecolor='w') # , edgecolor='k',)
position = (up - low) * 0.9 + low
ax1.text(2.6, position, 'Beauty', fontsize=40)
y_ticks = [0.15, 0.20, 0.25, 0.30, 0.35, 0.40]
y_lables = ['0.15', '0.20', '0.25', '0.30', '0.35', '0.40']
ax1.set_yticks(np.array(y_ticks))
ax1.set_yticklabels(y_lables, fontsize=40)
toys_base = np.array(toys_base)
toys_grow = np.array(toys_grow)
low = 0.11
up = 0.41
ax2.set_ylim(low, up)
ax2.bar(x, toys_base, width=width, color='royalblue', hatch=".", edgecolor='w')
ax2.bar(x + width, toys_grow, width=width, color='tomato', hatch="/", edgecolor='w')
position = (up - low) * 0.9 + low
ax2.text(2.7, position, 'Toys', fontsize=40)
ax2.set_xticks(x + (width / 2))
ax2.set_xticklabels(lables, fontsize=40, rotation=20)
y_ticks = [0.15, 0.20, 0.25, 0.30, 0.35, 0.40]
y_lables = ['0.15', '0.20', '0.25', '0.30', '0.35', '0.40']
ax2.set_yticks(np.array(y_ticks))
ax2.set_yticklabels(y_lables, fontsize=40)
leg1 = mpatches.Patch(color='royalblue', hatch='.')
leg2 = mpatches.Patch(color='tomato', hatch='/')
labels = ['Original', 'Final']
fig.legend(handles=[leg1, leg2], labels=labels, loc='upper center', bbox_to_anchor=(0.2, 1), ncol=1, prop={'size': 40})
fig.tight_layout()
fig.show()
# 建议保存为svg格式,再用inkscape转为矢量图emf后插入word中
fig.savefig('./pics/two_bars.png', format='png')
plot_bar()
plot_line()
plot_multi_bar()
plot_bar_and_line()
plot_scatters()
plot_hetmap()
plot_ablation_bar_in_one()
plot_two_bar_in_one()