如何在每个点上用文本绘制图形上的点（python）

Question

我正在尝试复制这个：我有一个单词列表，每个单词都有一个 x 和 y 坐标。我需要像上面那样绘制它们。做这个的最好方式是什么？我知道我可以做类似...y = [2.56422, 3.77284, 3.52623, 3.51468, 3.02199]z = [0.15, 0.3, 0.45, 0.6, 0.75]n = [hello, xyz, bbb, fasjd, boy]fig, ax = plt.subplots()for i, txt in enumerate(n):    ax.annotate(txt, (z[i], y[i]))但这对于我想做的事情来说似乎不太有效。对于每个单词，我都有一个函数来传递它以找到 x 坐标，然后另一个函数来找到它的 y 坐标。也许只是一个单词列表，然后是一个循环遍历并在遍历列表时绘制每个单词的函数？这可能吗？def plotWords(words):    fig, ax = pyplot.subplots()    for w in words:        ax.annotate(w, code for x coordinate, code for y coordinate)    return ax

Answer 1

我想你可以用zip()它们来循环。

import matplotlib.pyplot as plt

y = [2.56422, 3.77284, 3.52623, 3.51468, 3.02199]

z = [0.15, 0.3, 0.45, 0.6, 0.75]

n = ['hello', 'xyz', 'bbb', 'fasjd', 'boy']

fig = plt.figure(figsize=(4,3),dpi=144)

ax = fig.add_subplot(111)

def plotWords(words,z,y):

    for w,xx,yy in zip(words,z,y):

        ax.annotate(w, xy=(xx,yy))

    ax.set_ylim(0,5)

    plt.show()

    return 

plotWords(n,z,y)

Answer 2

这个图

是运行这个脚本产生的

import matplotlib.pyplot as plt 

import numpy as np 

# determine the sequence of random numbers 

np.random.seed(sum(ord(c) for c in 'gboffi')) 

# initialize the plotting

fig, ax = plt.subplots(figsize=(8,6), constrained_layout=1) 

# a list of long words 

N = 40 

data = '/usr/share/dict/italian' 

long_words = [w.strip() for w in open(data) if len(w)>12 and "'" not in w] 

words = np.random.choice(long_words, N) 

# let's compute the word characteristics

xs = np.random.random(N) + [len(w) for w in words] 

ys = np.random.random(N) + [sum(ord(c) for c in w)/len(w) for w in words] 

# determine the axes limits

xmn = min(xs) ; xmx = max(xs) ; dx = xmx-xmn 

ymn = min(ys) ; ymx = max(ys) ; dy = ymx-ymn 

ax.set_xlim(xmn-0.05*dx, xmx+0.05*dx) ; ax.set_ylim(ymn-0.05*dy, ymx+0.05*dx) 

# label the axes

plt.xlabel('Word Length', size='x-large')

plt.ylabel('Mean Value', size='x-large')

# for every word, plot a red "o" and place the text around it 

for w, x, y in zip(words, xs, ys): 

    ax.plot((x,),(y,), 'o', c='r') 

    ax.annotate(w, (x, y), ha='center', va='center')

# the dashed red lines, the position is a little arbitrary

plt.hlines(ymn+0.5*dy, xmn, xmx, ls='--', color='r') 

plt.vlines(xmn+0.4*dx, ymn, ymx, ls='--', color='r')                                                                

# remove everything except points, red lines and axes' labels

plt.box(False)

plt.tick_params(left=0, top=0, right=0, bottom=0,

                labelleft=0, labeltop=0, labelright=0, labelbottom=0) 

# we are done

plt.show()