Matplotlib Snippets

import matplotlib
import matplotlib.pyplot as plt
import numpy as np

dataset = ["Dataset 1", "Dataset 2"]
data = {"A": np.array([...]),
        "B": np.array([...]),
        "C": np.array([...]),
        "D": np.array([...])}
best = "A"
# normalize(data)

x = np.arange(0,len(dataset)*3,3)
width = 0.15

fig, ax = plt.subplots(1,1,figsize=(6.5,3.5))

def normalize(data):
    for key in data:
        data[key] /= data[best]

def draw_bar(ax,title):
    interval = np.arange(-len(data)+1,len(data),2)
    for i, key in enumerate(data):
        ax.bar(x + interval[i] * width, data[key], width*2, alpha=0.9, label=key)
    ax.set_xticks(x)
    ax.set_xticklabels(dataset)
    # ax.set_yticks(np.arange(0, 8.5, 1.0))
    ax.set_xlabel("Dataset")
    ax.set_ylabel("Normalized execution time")
    # for i, v in enumerate(baseline/best):
    #     ax.text(i, v, str(v), color='black', fontweight='bold')
    ax.set_axisbelow(True)
    ax.legend(loc=1,prop={"size":8})
    ax.grid(axis='y')
    if title != None:
        ax.set_title(title)

draw_bar(ax)

# handles, labels = ax.get_legend_handles_labels()
# lgd = fig.legend(handles, labels, loc='upper center', mode="expand",ncol=3,columnspacing=0,bbox_to_anchor=(0.15, 0.62, 0.8, 0.5))
# fig.tight_layout()
plt.savefig(r"results.png",format="png",dpi=200,bbox_inches='tight')
plt.show()

import matplotlib
import matplotlib.pyplot as plt
import matplotlib.ticker as mtick
import numpy as np

fig, ax = plt.subplots(1,2,figsize=(8,3))
data = {"A": np.array([...]),
        "B": np.array([...]),
        "C": np.array([...])}
x = np.array((1,2,4,8,16,32,48))
colors = ["red", "#91cf60", "#4575b4"]
ticks = ["x", "o", "^"]

def draw_line(ax,title=None):
    for i, key in enumerate(data):
        ax.plot(x, data[key], color=colors[i])
        ax.plot(x, data[key], ticks[i], color=colors[i], label=key)
    ax.set_xscale('log',basex=2)
    ax.get_xaxis().set_major_formatter(matplotlib.ticker.ScalarFormatter())
    ax.get_xaxis().get_major_formatter().labelOnlyBase = False
    fmt = '%d' # Format you want the ticks, e.g. '40%'
    xticks = mtick.FormatStrFormatter(fmt)
    ax.xaxis.set_major_formatter(xticks)
    ax.set_ylabel("Normalized execution time")
    ax.set_xlabel("# of cores")
    if title != None:
        ax.set_title(title)
    ax.legend()

draw_line(ax[0])

plt.tight_layout()
plt.savefig(r"fig/scale.pdf",format="pdf")
plt.show()