matplotlib實現自定義散點形狀marker的3種方法 python 程式碼

目錄

• 無填充形狀和填充形狀
• Tex形狀
• Path對象
• 使用Path模塊中的Path對象
• 自定義Path對象
• 從svg格式轉化為Path對象
• 參考

matplotlib中marker支援的數據類型

marker有4種類型，分別是：

• Unfilled markers: 無填充形狀
• Filled markers: 填充形狀
• markers created from Tex symbols: 即用tex字符串定義的形狀
• created from paths：自定義的matplotlib中的Path對象即路徑。

4種類型中前兩種即無填充類型和填充類型都是matplotlib本身就有的，沒有可擴充性。第三種tex字符串也隻能表現一些特殊的形狀，可擴充性也不是很強。最後一種Path對象可以自己定義形狀，可擴充性比較強。

無填充形狀和填充形狀

使用這種形狀隻需給marker指定一個字符或者一個數字即可

Tex形狀

通過自定義一個符合Latex格式的字符串復制給marker即可,因此如果想讓makrer為一個數字或者單詞字母或者特殊的符號便可以定義這樣一個字符串

import matplotlib.pyplot as plt 
import numpy as np 

data = np.random.rand(3,2)
fig = plt.figure() 
ax = fig.add_subplot(111) 
markers = ["$\u266B$", r"$\frac{1}{2}$", "$\heartsuit$"]
for i in range(data.shape[0]):
    ax.scatter(data[i,0], data[i,1], marker=markers[i], s=400) 
plt.show()

Path對象

matplotlib中Path類的定義參考瞭圖片格式svg格式的定義,具體不做闡述,可自行百度。Path對象給定制marker提供瞭極大的便利，可以使用Path模塊中已經定義好的一些Path類供用戶組合，用戶也可以自定義Path類

使用Path模塊中的Path對象

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

star = mpath.Path.unit_regular_star(6)  # 星型Path
circle = mpath.Path.unit_circle()  # 圓形Path 
# 整合兩個路徑對象的點
verts = np.concatenate([circle.vertices, star.vertices[::-1, ...]])
# 整合兩個路徑對象點的類型
codes = np.concatenate([circle.codes, star.codes])

# 根據路徑點和點的類型重新生成一個新的Path對象 
cut_star = mpath.Path(verts, codes)

plt.plot(np.arange(10)**2, '--r', marker=cut_star, markersize=15)

plt.show()

自定義Path對象

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

circle = mpath.Path.unit_circle()  # 獲得一個圓 
verts_part= circle.wedge(340,220).vertices  # 按逆時針從340度到220度部分圓的路徑點
codes_part = circle.wedge(340,220).codes  # 點類型 
verts_part = verts_part[1:-2]  # 去除第一個點和最後兩個點 
codes_part = codes_part[1:-2] 
# 整合新的點 
verts = np.concatenate([np.array([[0,-2]]), verts_part, np.array([[0,-2]])]) 
codes = [mpath.Path.MOVETO] + codes_part.tolist() +  [mpath.Path.CLOSEPOLY] 

icon = mpath.Path(vertices=verts, codes=codes)

plt.plot(verts[:,0], verts[:,1]) 
plt.show() 

plt.scatter(data[:,0], data[:,1], marker=icon, s=300, facecolor="none",edgecolors="black")
plt.show()

從svg格式轉化為Path對象

既然Path類的定義起源於svg，那麼引申出一個問題，能否將svg格式的圖片轉化為Path對象？這樣我們就不用費力自己定義Path對象，而是可以用別人已經定義好的svg格式的圖片轉換為Path對象

答案是可以的，可以用svgpath2mpl庫解析svg轉化為matplotlib的Path對象

import matplotlib as mpl 
from svgpath2mpl import parse_path
import xml.etree.ElementTree as etree 
from six import StringIO 
import re 

# svg格式圖片的svg程式碼
svg = """<svg t="1616741322150" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="8787" width="200" height="200"><path d="M292.306 214.793c40.673-59.469 98.47-89.114 123.74-99.877-50.841 19.771-94.015 54.996-123.74 99.877zM317.249 549.7l-0.009-0.017a0.095 0.095 0 0 1 0.009 0.017zM330.252 573.425l-0.889-1.589 0.889 1.589zM314.714 544.938zM312.366 540.488c-16.983-32.365-32.057-64.58-43.611-95.073 10.481 27.982 25.067 59.78 43.611 95.073z" fill="#8BF268" p-id="8788"></path><path d="M276.744 382.688C295.187 506.384 510.593 843.49 510.593 843.49S409.26 713.734 331.798 576.177c15.768 28.036 33.713 57.96 53.791 89.654 50.524 79.755 101.501 149.919 125.003 181.547a2836.34 2836.34 0 0 0 13.718-18.628c41.494-66.235 208.413-337.835 224.549-446.063 27.402-152.126-70.696-229.04-122.257-258.284-34.982-17.378-74.37-27.171-116.009-27.171-30.64 0-60.058 5.311-87.405 15.032-30.816 13.288-179.4 87.46-146.444 270.424z m233.849-157.864c78.389 0 142.163 63.774 142.163 142.163S588.982 509.15 510.593 509.15 368.43 445.376 368.43 366.987s63.773-142.163 142.163-142.163z" fill="#8BF268" p-id="8789"></path><path d="M497.201 885.762l13.392 17.442 13.392-17.442c0.701-0.913 70.898-92.56 140.138-201.86C758.272 535.28 806.01 425.928 806.01 358.882c0-39.874-7.813-78.564-23.222-114.995-14.88-35.18-36.178-66.772-63.303-93.897s-58.716-48.423-93.896-63.303c-36.432-15.409-75.121-23.222-114.995-23.222s-78.563 7.813-114.995 23.222c-35.18 14.88-66.772 36.178-93.897 63.303s-48.423 58.717-63.303 93.897c-15.409 36.431-23.222 75.121-23.222 114.995 0 67.046 47.738 176.399 141.888 325.02 69.238 109.3 139.435 200.947 140.136 201.86z m-68.507-775.74s-1.986 0.725-5.507 2.243c27.347-9.721 56.765-15.032 87.405-15.032 41.638 0 81.026 9.793 116.009 27.171-17.536-9.946-29.693-14.382-29.693-14.382s187.827 60.358 180.229 265.49C746.326 547.301 515.01 843.49 515.01 843.49s3.369-5.272 9.299-14.739a2790.949 2790.949 0 0 1-13.718 18.628c-23.502-31.628-74.479-101.792-125.003-181.547-20.078-31.694-38.022-61.618-53.791-89.654a1069.523 1069.523 0 0 1-2.435-4.341 1399.816 1399.816 0 0 1-12.114-22.136l-0.009-0.017c-0.847-1.582-1.689-3.164-2.527-4.745-0.685-1.291-1.36-2.574-2.035-3.855l-0.313-0.595c-18.543-35.293-33.13-67.091-43.611-95.073-9.363-24.711-16.414-48.291-20.29-69.902-2.548-68.796 16.885-121.307 43.842-160.72 29.725-44.881 72.899-80.106 123.74-99.877 7.92-3.374 12.649-4.895 12.649-4.895z" fill="" p-id="8790"></path><path d="M510.593 509.151c78.389 0 142.163-63.774 142.163-142.163s-63.774-142.163-142.163-142.163S368.43 288.599 368.43 366.988s63.773 142.163 142.163 142.163z m108.395-142.164c0 59.769-48.626 108.395-108.395 108.395s-108.395-48.626-108.395-108.395 48.626-108.395 108.395-108.395 108.395 48.627 108.395 108.395zM736.383 836.927c-20.041-9.489-47.483-17.342-81.565-23.342l-0.655 3.723a12.318 12.318 0 0 0-1.116-0.194c-6.864-0.816-13.127 4.408-13.99 11.668-0.849 7.137 3.843 13.572 10.522 14.564l-0.615 3.496c29.133 5.128 53.509 11.86 70.496 19.466 18.638 8.346 21.571 14.609 21.86 15.365-0.868 3.232-13.707 16.8-63.714 28.875-45.006 10.868-104.318 16.853-167.012 16.853s-122.007-5.985-167.013-16.853c-50.105-12.099-62.896-25.697-63.719-28.894 1.082-4.274 21.574-23.326 99.529-36.026l-0.62-3.806c6.158-1.477 10.323-7.675 9.466-14.463-0.899-7.125-6.996-12.235-13.711-11.594l-0.565-3.466c-35.641 5.806-65.645 13.94-86.77 23.521-27.28 12.374-41.112 27.795-41.112 45.835 0 14.81 9.313 27.887 27.679 38.869 13.882 8.302 33.26 15.631 57.594 21.786 48.085 12.162 111.741 18.86 179.241 18.86s131.155-6.698 179.241-18.86c24.334-6.155 43.712-13.484 57.594-21.786 18.366-10.982 27.679-24.06 27.679-38.869 0-17.513-13.029-32.562-38.724-44.728z" fill="" p-id="8791"></path><path d="M292.306 214.793c-26.956 39.413-46.389 91.924-43.842 160.72 3.876 21.611 10.928 45.191 20.29 69.902 11.553 30.493 26.628 62.708 43.611 95.073l0.313 0.595a1193.743 1193.743 0 0 0 4.562 8.6l0.009 0.017a1395.399 1395.399 0 0 0 14.549 26.477C409.26 713.734 510.593 843.49 510.593 843.49S295.187 506.384 276.744 382.688c-32.956-182.964 115.628-257.137 146.443-270.423 3.52-1.518 5.507-2.243 5.507-2.243s-4.729 1.521-12.649 4.894c-25.269 10.762-83.066 40.407-123.739 99.877z" fill="#FFFFFF" p-id="8792"></path><path d="M748.858 382.688c-16.136 108.228-183.054 379.827-224.549 446.063-5.93 9.467-9.299 14.739-9.299 14.739s231.316-296.189 262.128-467.977c7.597-205.132-180.229-265.49-180.229-265.49s12.156 4.435 29.693 14.382c51.56 29.243 149.658 106.157 122.256 258.283z" fill="#2FBC3C" p-id="8793"></path></svg>"""
# 解析程式碼 
tree = etree.parse(StringIO(svg)) 
root = tree.getroot() 
width = int(re.match(r'\d+', root.attrib['width']).group())
height = int(re.match(r'\d+', root.attrib['height']).group())
path_elems = root.findall('.//{http://www.w3.org/2000/svg}path') 

# 解析出每個Path對象
paths = [parse_path(elem.attrib['d']) for elem in path_elems] 
facecolors = [elem.attrib.get('fill', 'none') for elem in path_elems] 
facecolors = [c if c !="" else "none" for c in facecolors]
edgecolors = [elem.attrib.get('stroke', 'none') for elem in path_elems]
linewidths = [elem.attrib.get('stroke_width', 1) for elem in path_elems]

#定義旋轉矩陣
def rot(verts, az):
    #順時針旋轉
    rad = az / 180 * np.pi
    verts = np.array(verts)
    rotMat = np.array([[np.cos(rad), -np.sin(rad)], [np.sin(rad), np.cos(rad)]])
    transVerts = verts.dot(rotMat)
    return transVerts

# 合並每個Path對象
verts = paths[0].vertices 
codes = paths[0].codes 
for i in range(1,len(paths)): 
    verts = np.concatenate([verts, paths[i].vertices])
    codes = np.concatenate([codes, paths[i].codes])
verts = rot(verts, 180) 
fig = plt.figure() 
ax = fig.add_subplot(111) 
ax.plot(verts[:,0], verts[:,1]  , color="red")  
plt.show() 

# 定義解析函數 
def svg2path(svg):
    # 解析程式碼 
    tree = etree.parse(StringIO(svg)) 
    root = tree.getroot() 
    path_elems = root.findall('.//{http://www.w3.org/2000/svg}path') 

    # 解析出每個Path對象
    paths = [parse_path(elem.attrib['d']) for elem in path_elems] 
    
    # 合並path對象
    verts = paths[0].vertices 
    codes = paths[0].codes 
    for i in range(1, len(paths)): 
        verts = np.concatenate([verts, paths[i].vertices])
        codes = np.concatenate([codes, paths[i].codes])
    # 復原為原來的形狀
    verts = rot(verts, 270) 
    verts = np.fliplr(verts)  # 水平翻轉，鏡像
    #verts = (verts - verts.min(0)) / (verts.max(0) - verts.min(0)) 
    icon = mpath.Path(vertices=verts, codes=codes)
    return icon 

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icons = []
for s in svg:
    icons.append(svg2path(s)) 

fig = plt.figure() 
ax = fig.add_subplot(111) 
for i in range(data.shape[0]):
    ax.scatter(data[i,0], data[i,1], marker=icons[i], s=3000)
plt.show()

參考

https://matplotlib.org/stable/gallery/lines_bars_and_markers/marker_reference.html#sphx-glr-gallery-lines-bars-and-markers-marker-reference-py

https://nbviewer.jupyter.org/github/nvictus/svgpath2mpl/blob/master/examples/homer.ipynb

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