使用示例

import paperplotlib as ppl
import numpy as np

# 设定数组的行数a和列数b
a = 6
b = 4
y = np.random.randint(10, 100, size=(a, b))

group_names = ["Canneal", "Memcached", "XSBench", "Graph500", "HashJoin", "BTree"]
column_names = [f"socket {i}" for i in range(b)]

graph = ppl.BarGraph()
graph.plot_2d(y, group_names, column_names)
graph.y_lim = (0, 100)
graph.save()

import paperplotlib as ppl
import numpy as np

# 设定数组的行数a和列数b
a = 5
b = 5
y = np.random.rand(a,b)

group_names = ["A", "B", "C", "D", "F"]
column_names = ["DDR5:CXL-A = 100:0", "75:25", "50:50", "25:75", "0:100"]

graph = ppl.BarGraph()
graph.plot_2d(y, group_names, column_names)
graph.x_label = "Workload"
graph.y_label = "Max QPS\nNormalized DDR 100%"
graph.y_lim = (0, 1.2)
graph.save()

让某一列突出

import paperplotlib as ppl
import numpy as np

# 设定数组的行数a和列数b
a = 5
b = 5
y = np.random.rand(a,b)

group_names = ["A", "B", "C", "D", "F"]
column_names = ["DDR5:CXL-A = 100:0", "75:25", "50:50", "25:75", "0:100"]

graph = ppl.BarGraph()
- graph.plot_2d(y, group_names, column_names)
+ graph.plot_2d(y, group_names, column_names, emphasize_index=0)
graph.x_label = "Workload"
graph.y_label = "Max QPS\nNormalized DDR 100%"
graph.y_lim = (0, 1.2)
graph.save()

宽图, 适用于多组数据, 双栏

import paperplotlib as ppl
import numpy as np

# 设定数组的行数a和列数b
a = 8
b = 6
y = np.random.randint(10, 100, size=(a, b))

group_names = [f"group {i}" for i in range(a)]
column_names = [f"column {i}" for i in range(b)]

graph = ppl.BarGraph()
graph.plot_2d(y, group_names, column_names)
graph.x_label = "The number of data"
graph.y_label = "Throughput (Mbps)"
graph.width_picture = True
graph.save()