一致点/重複するアノテーションを含むPyplot Label散布図

Question

この質問は、thisの続きです。ラベル付きの点が正確に一致していたり​​、ほぼ一致していても、注釈を読み込み可能にするにはどうすればよいですか？私はプログラム的な解決策が必要です、手を調整する手はオプションではありません。醜いラベル付きサンプル：

import numpy as np 
import matplotlib.pyplot as plt 

np.random.seed(0) 
N = 10 
data = np.random.random((N, 4)) 
data[1, :2] = data[0, :2] 
data[-1, :2] = data[-2, :2] + .01 
labels = ['point{0}'.format(i) for i in range(N)] 
plt.subplots_adjust(bottom = 0.1) 
plt.scatter(
    data[:, 0], data[:, 1], marker = 'o', c = data[:, 2], s = data[:, 3]*1500, 
    cmap = plt.get_cmap('Spectral')) 
for label, x, y in zip(labels, data[:, 0], data[:, 1]): 
    plt.annotate(
     label, 
     xy = (x, y), xytext = (-20, 20), 
     textcoords = 'offset points', ha = 'right', va = 'bottom', 
     bbox = dict(boxstyle = 'round,pad=0.5', fc = 'yellow', alpha = 0.5), 
     arrowprops = dict(arrowstyle = '->', connectionstyle = 'arc3,rad=0')) 

plt.show() 

Answer 1

が最後の点の間の距離を取り、閾値ホールドを設定し、それに応じてX、Y、テキストを反転。下記参照。その結果

import numpy as np 
import matplotlib.pyplot as plt 

np.random.seed(0) 
N = 10 
data = np.random.random((N, 4)) 
data[1, :2] = data[0, :2] 
data[-1, :2] = data[-2, :2] + .01 
labels = ['point{0}'.format(i) for i in range(N)] 
plt.subplots_adjust(bottom = 0.1) 
plt.scatter(
    data[:, 0], data[:, 1], marker = 'o', c = data[:, 2], s = data[:, 3]*1500, 
    cmap = plt.get_cmap('Spectral')) 

old_x = old_y = 1e9 # make an impossibly large initial offset 
thresh = .1 #make a distance threshold 

for label, x, y in zip(labels, data[:, 0], data[:, 1]): 
    #calculate distance 
    d = ((x-old_x)**2+(y-old_y)**2)**(.5) 

    #if distance less than thresh then flip the arrow 
    flip = 1 
    if d < .1: flip=-2 

    plt.annotate(
     label, 
     xy = (x, y), xytext = (-20*flip, 20*flip), 
     textcoords = 'offset points', ha = 'right', va = 'bottom', 
     bbox = dict(boxstyle = 'round,pad=0.5', fc = 'yellow', alpha = 0.5), 
     arrowprops = dict(arrowstyle = '->', connectionstyle = 'arc3,rad=0')) 
    old_x = x 
    old_y = y 

plt.show() 

：

Answer 2

は、ここで私がなってしまったものです。すべての状況には完璧ではなく、このサンプルの問題ではうまく機能しませんが、私のニーズには十分だと思います。あなたの答えが正しい方向に私を指してくれてありがとうダン。

import numpy as np 
import matplotlib.pyplot as plt 
from scipy.spatial import cKDTree 


def get_label_xy(tree, thresh, data, i): 
    neighbors = tree.query_ball_point([data[i, 0], data[i, 1]], thresh) 
    if len(neighbors) == 1: 
     xy = (-30, 30) 
    else: 
     mean = np.mean(data[:, :2][neighbors], axis=0) 

     if mean[0] == data[i, 0] and mean[1] == data[i, 1]: 
      if i < np.max(neighbors): 
       xy = (-30, 30) 
      else: 
       xy = (30, -30) 
     else: 
      angle = np.arctan2(data[i, 1] - mean[1], data[i, 0] - mean[0]) 

      if angle > np.pi/2: 
       xy = (-30, 30) 
      elif angle > 0: 
       xy = (30, 30) 
      elif angle > -np.pi/2: 
       xy = (30, -30) 
      else: 
       xy = (-30, -30) 
    return xy 


def labeled_scatter_plot(data, labels): 
    plt.subplots_adjust(bottom = 0.1) 
    plt.scatter(
     data[:, 0], data[:, 1], marker = 'o', c = data[:, 2], s = data[:, 3]*1500, 
     cmap = plt.get_cmap('Spectral')) 

    tree = cKDTree(data[:, :2]) 
    thresh = .1 

    for i in range(data.shape[0]): 
     xy = get_label_xy(tree, thresh, data, i) 

     plt.annotate(
      labels[i], 
      xy = data[i, :2], xytext = xy, 
      textcoords = 'offset points', ha = 'center', va = 'center', 
      bbox = dict(boxstyle = 'round,pad=0.5', fc = 'yellow', alpha = 0.5), 
      arrowprops = dict(arrowstyle = '->', connectionstyle = 'arc3,rad=0')) 


np.random.seed(0) 
N = 10 
data = np.random.random((N, 4)) 
data[1, :2] = data[0, :2] 
data[-1, :2] = data[-2, :2] + .01 
data[5, :2] = data[4, :2] + [.05, 0] 
data[6, :2] = data[4, :2] + [.05, .05] 
data[7, :2] = data[4, :2] + [0, .05] 
labels = ['point{0}'.format(i) for i in range(N)] 

labeled_scatter_plot(data, labels) 

plt.show()