如何修复重叠的注释/文本

我试图阻止注释文本在我的图中重叠。在 Matplotlib 重叠注释的公认答案中建议的方法看起来非常有前途,但是对于条形图而言。我有麻烦转换“轴”方法到我想做的事情,我不明白如何文本行。

import sys
import matplotlib.pyplot as plt




# start new plot
plt.clf()
plt.xlabel("Proportional Euclidean Distance")
plt.ylabel("Percentage Timewindows Attended")
plt.title("Test plot")


together = [(0, 1.0, 0.4), (25, 1.0127692669427917, 0.41), (50, 1.016404709797609, 0.41), (75, 1.1043426359673716, 0.42), (100, 1.1610446924342996, 0.44), (125, 1.1685687930691457, 0.43), (150, 1.3486407784550272, 0.45), (250, 1.4013999168008104, 0.45)]
together.sort()


for x,y,z in together:
plt.annotate(str(x), xy=(y, z), size=8)


eucs = [y for (x,y,z) in together]
covers = [z for (x,y,z) in together]


p1 = plt.plot(eucs,covers,color="black", alpha=0.5)


plt.savefig("test.png")

图像(如果这个工作)可以找到 给你(这个代码) :

image1

给你(更复杂) :

image2

84831 次浏览

经过大量的练习,我终于弄明白了。同样,原始解决方案的功劳归于 Matplotlib 重叠注释的答案。

然而,我不知道如何找到文本的确切宽度和高度。如果有人知道,请发布一个改进(或添加评论与方法)。

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


def get_text_positions(text, x_data, y_data, txt_width, txt_height):
a = zip(y_data, x_data)
text_positions = list(y_data)
for index, (y, x) in enumerate(a):
local_text_positions = [i for i in a if i[0] > (y - txt_height)
and (abs(i[1] - x) < txt_width * 2) and i != (y,x)]
if local_text_positions:
sorted_ltp = sorted(local_text_positions)
if abs(sorted_ltp[0][0] - y) < txt_height: #True == collision
differ = np.diff(sorted_ltp, axis=0)
a[index] = (sorted_ltp[-1][0] + txt_height, a[index][1])
text_positions[index] = sorted_ltp[-1][0] + txt_height*1.01
for k, (j, m) in enumerate(differ):
#j is the vertical distance between words
if j > txt_height * 2: #if True then room to fit a word in
a[index] = (sorted_ltp[k][0] + txt_height, a[index][1])
text_positions[index] = sorted_ltp[k][0] + txt_height
break
return text_positions


def text_plotter(text, x_data, y_data, text_positions, txt_width,txt_height):
for z,x,y,t in zip(text, x_data, y_data, text_positions):
plt.annotate(str(z), xy=(x-txt_width/2, t), size=12)
if y != t:
plt.arrow(x, t,0,y-t, color='red',alpha=0.3, width=txt_width*0.1,
head_width=txt_width, head_length=txt_height*0.5,
zorder=0,length_includes_head=True)


# start new plot
plt.clf()
plt.xlabel("Proportional Euclidean Distance")
plt.ylabel("Percentage Timewindows Attended")
plt.title("Test plot")


together = [(0, 1.0, 0.4), (25, 1.0127692669427917, 0.41), (50, 1.016404709797609, 0.41), (75, 1.1043426359673716, 0.42), (100, 1.1610446924342996, 0.44), (125, 1.1685687930691457, 0.43), (150, 1.3486407784550272, 0.45), (250, 1.4013999168008104, 0.45)]
together.sort()


text = [x for (x,y,z) in together]
eucs = [y for (x,y,z) in together]
covers = [z for (x,y,z) in together]


p1 = plt.plot(eucs,covers,color="black", alpha=0.5)


txt_height = 0.0037*(plt.ylim()[1] - plt.ylim()[0])
txt_width = 0.018*(plt.xlim()[1] - plt.xlim()[0])


text_positions = get_text_positions(text, eucs, covers, txt_width, txt_height)


text_plotter(text, eucs, covers, text_positions, txt_width, txt_height)


plt.savefig("test.png")
plt.show()

创建 < a href = “ https://i.stack.imgur.com/xiTeU.png”rel = “ nofollow norefrer”> http://i.stack.imgur.com/xiteu.png enter image description here

更复杂的图现在是 http://i.stack.imgur.com/KJeYW.png,仍然有点不确定,但是好多了! enter image description here

我只是想在这里发布另一个解决方案,一个我编写的用于实现这类事情的小型 https://github.com/phlya/adjusttext 库: 这个过程的一个例子可以在这里看到: enter image description here

下面是示例图片:

import matplotlib.pyplot as plt
from adjustText import adjust_text
import numpy as np
together = [(0, 1.0, 0.4), (25, 1.0127692669427917, 0.41), (50, 1.016404709797609, 0.41), (75, 1.1043426359673716, 0.42), (100, 1.1610446924342996, 0.44), (125, 1.1685687930691457, 0.43), (150, 1.3486407784550272, 0.45), (250, 1.4013999168008104, 0.45)]
together.sort()


text = [x for (x,y,z) in together]
eucs = [y for (x,y,z) in together]
covers = [z for (x,y,z) in together]


p1 = plt.plot(eucs,covers,color="black", alpha=0.5)
texts = []
for x, y, s in zip(eucs, covers, text):
texts.append(plt.text(x, y, s))


plt.xlabel("Proportional Euclidean Distance")
plt.ylabel("Percentage Timewindows Attended")
plt.title("Test plot")
adjust_text(texts, only_move={'points':'y', 'texts':'y'}, arrowprops=dict(arrowstyle="->", color='r', lw=0.5))
plt.show()

enter image description here

如果你想要一个完美的身材,你可以随便摆弄一下。首先,我们还让文本排斥这些行——为此,我们只需使用 scypy.interpolate.interp1d 沿着它们创建大量虚拟点。

我们希望避免标签沿着 x 轴移动,因为,为什么不为了说明的目的这样做。为此,我们使用参数 only_move={'points':'y', 'text':'y'}。如果我们只想在它们与文本重叠的情况下沿着 x 轴移动它们,那么使用 move_only={'points':'y', 'text':'xy'}。同样在一开始,函数选择文本相对于其原始点的最佳对齐方式,所以我们只希望沿着 y 轴发生这种情况,因此 autoalign='y'。我们还降低了点的排斥力,以避免文本飞得太远,由于我们人为地避免行。所有人一起:

from scipy import interpolate
p1 = plt.plot(eucs,covers,color="black", alpha=0.5)
texts = []
for x, y, s in zip(eucs, covers, text):
texts.append(plt.text(x, y, s))


f = interpolate.interp1d(eucs, covers)
x = np.arange(min(eucs), max(eucs), 0.0005)
y = f(x)
    

plt.xlabel("Proportional Euclidean Distance")
plt.ylabel("Percentage Timewindows Attended")
plt.title("Test plot")
adjust_text(texts, x=x, y=y, autoalign='y',
only_move={'points':'y', 'text':'y'}, force_points=0.15,
arrowprops=dict(arrowstyle="->", color='r', lw=0.5))
plt.show()

enter image description here

简单的解决方案: (针对木星笔记本电脑)

%matplotlib notebook
import mplcursors


plt.plot.scatter(y=YOUR_Y_DATA, x =YOUR_X_DATA)




mplcursors.cursor(multiple = True).connect(
"add", lambda sel: sel.annotation.set_text(
YOUR_ANOTATION_LIST[sel.target.index]
))

右键点击一个点到 表演它的注释。

左键单击对 关门的注释。

右键单击并将注释拖动到 快走

enter image description here

只是想在代码中添加另一个解决方案。

  1. 获取 y 轴的刻度并找出任意2个连续刻度之间的差异(y _ diff)。
  2. 通过将图的每个“ y”元素添加到列表来注释第一行。
  3. 在对第二项进行注释时,检查前一个图(prev _ y)对相同“ x”的注释是否在相同的 y 轴刻度范围内(curr _ y)。
  4. 仅当(prev _ y-curr _ y) > (y _ diff/3)时注释。可以将差异除以图形大小和注释字体大小所需的数字。
 annotation_y_values = []
for i, j in zip(x, df[df.columns[0]]):
annotation_y_values.append(j)
axs.annotate(str(j), xy=(i, j), color="black")
count = 0
y_ticks = axs.get_yticks()
y_diff = y_ticks[-1] - y_ticks[-2]
for i, j in zip(x, df1[df1.columns[0]]):
df_annotate_value = annotation_y_values[count]
current_y_val = j
diff = df_annotate_value - current_y_val
if diff > (y_diff/3):
axs.annotate(str(j), xy=(i, j), color="black", size=8)
count = count + 1


刚刚为这样的问题创建了一个包: 纺织品

下面的示例演示在这种情况下如何使用它。通过一些参数调整,你可以在几分之一秒内生成这样的图:

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


np.random.seed(0)
x_lines = [np.array([0.0, 0.03192317, 0.04101177, 0.26085659, 0.40261173, 0.42142198, 0.87160195, 1.00349979]) + np.random.normal(0,0.03,(8,)) for _ in range(4)]
y_lines = [np.array([0. , 0.2, 0.2, 0.4, 0.8, 0.6, 1. , 1. ]) + np.random.normal(0,0.03,(8,)) for _ in range(4)]
text_lists = [['0', '25', '50', '75', '100', '125', '150', '250'] for _ in range(4)]


texts = []
for tl in text_lists:
texts += tl
fig,ax = plt.subplots(dpi=100)
for x_line,y_line,text_list in zip(x_lines,y_lines,text_lists):
ax.plot(x_line,y_line,color="black",linewidth=0.5)
ta.allocate_text(fig,ax,np.hstack(x_lines),np.hstack(y_lines),
texts,
x_lines=x_lines, y_lines=y_lines,
max_distance=0.1,
min_distance=0.025,
margin=0.0,
linewidth=0.5,
nbr_candidates=400)
plt.show()

enter image description here