matplotlib實(shí)現(xiàn)自定義散點(diǎn)形狀marker的3種方法
更新時(shí)間：2021年10月27日 15:38:42 作者：R人
本文主要介紹了matplotlib實(shí)現(xiàn)自定義散點(diǎn)形狀marker的3種方法，文中通過示例代碼介紹的非常詳細(xì)，具有一定的參考價(jià)值，感興趣的小伙伴們可以參考一下
matplotlib中marker支持的數(shù)據(jù)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(duì)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(kuò)充性。第三種tex字符串也只能表現(xiàn)一些特殊的形狀，可擴(kuò)充性也不是很強(qiáng)。最后一種Path對(duì)象可以自己定義形狀，可擴(kuò)充性比較強(qiáng)。
無填充形狀和填充形狀
使用這種形狀只需給marker指定一個(gè)字符或者一個(gè)數(shù)字即可
Tex形狀
通過自定義一個(gè)符合Latex格式的字符串復(fù)制給marker即可,因此如果想讓makrer為一個(gè)數(shù)字或者單詞字母或者特殊的符號(hào)便可以定義這樣一個(gè)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(duì)象
matplotlib中Path類的定義參考了圖片格式svg格式的定義,具體不做闡述,可自行百度。Path對(duì)象給定制marker提供了極大的便利，可以使用Path模塊中已經(jīng)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(duì)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(gè)路徑對(duì)象的點(diǎn) verts = np.concatenate([circle.vertices, star.vertices[::-1, ...]]) # 整合兩個(gè)路徑對(duì)象點(diǎn)的類型 codes = np.concatenate([circle.codes, star.codes]) # 根據(jù)路徑點(diǎn)和點(diǎn)的類型重新生成一個(gè)新的Path對(duì)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(duì)象
import matplotlib.pyplot as plt import matplotlib.path as mpath import numpy as np circle = mpath.Path.unit_circle() # 獲得一個(gè)圓 verts_part= circle.wedge(340,220).vertices # 按逆時(shí)針從340度到220度部分圓的路徑點(diǎn) codes_part = circle.wedge(340,220).codes # 點(diǎn)類型 verts_part = verts_part[1:-2] # 去除第一個(gè)點(diǎn)和最后兩個(gè)點(diǎn) codes_part = codes_part[1:-2] # 整合新的點(diǎn) 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(zhuǎn)化為Path對(duì)象
既然Path類的定義起源于svg，那么引申出一個(gè)問題，能否將svg格式的圖片轉(zhuǎn)化為Path對(duì)象？這樣我們就不用費(fèi)力自己定義Path對(duì)象，而是可以用別人已經(jīng)定義好的svg格式的圖片轉(zhuǎn)換為Path對(duì)象
答案是可以的，可以用svgpath2mpl庫解析svg轉(zhuǎn)化為matplotlib的Path對(duì)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代碼
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>"""
# 解析代碼
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(gè)Path對(duì)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(zhuǎn)矩陣
def rot(verts, az):
#順時(shí)針旋轉(zhuǎn)
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
# 合并每個(gè)Path對(duì)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(shù)
def svg2path(svg):
# 解析代碼
tree = etree.parse(StringIO(svg))
root = tree.getroot()
path_elems = root.findall('.//{http://www.w3.org/2000/svg}path')
# 解析出每個(gè)Path對(duì)象
paths = [parse_path(elem.attrib['d']) for elem in path_elems]
# 合并path對(duì)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(fù)原為原來的形狀
verts = rot(verts, 270)
verts = np.fliplr(verts) # 水平翻轉(zhuǎn)，鏡像
#verts = (verts - verts.min(0)) / (verts.max(0) - verts.min(0))
icon = mpath.Path(vertices=verts, codes=codes)
return icon
svg = ["""<svg t="1616814589861" class="icon" viewBox="0 0 1151 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="1716" width="200" height="200"><path d="M234.141946 661.465839a30.020373 30.020373 0 0 1-6.190642-0.593624 33.412505 33.412505 0 0 1-22.303271-15.264596 770.692505 770.692505 0 0 0-47.913872-68.690683 33.921325 33.921325 0 0 1 5.851429-47.235445 921.727205 921.727205 0 0 1 569.030228-194.199586c19.759172 0 39.518344 0.593623 59.362319 1.865673a16.960663 16.960663 0 0 1 16.027826 16.960662v135.6853a16.960663 16.960663 0 0 1-18.911139 16.960663 760.770518 760.770518 0 0 0-534.26087 147.557764 33.921325 33.921325 0 0 1-20.692008 6.953872z m-49.016315-105.156108a789.264431 789.264431 0 0 1 49.185922 70.556356 787.822774 787.822774 0 0 1 475.66178-157.818965c21.116025 0 42.401656 0.848033 63.348075 2.5441V370.844886c-13.483727-0.593623-27.13706-0.932836-40.70559-0.932836a887.80588 887.80588 0 0 0-547.490187 186.567287z" p-id="1717"></path><path d="M234.141946 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"""<svg t="1616821022361" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="1865" width="200" height="200"><path d="M799.1 479c-11.7 0-23.1 1.2-34.2 3.3L672.5 205l85.3-42.7c10.8-5.4 15.2-18.6 9.8-29.5-5.4-10.8-18.6-15.2-29.5-9.8l-102.4 51.2c-9.8 4.9-14.5 16.2-11 26.6l40.6 122L524.5 584 384.4 343.8h25.7c12.2 0 22.1-9.8 22.1-22s-9.8-22-22-22H295c-12.2 0-22 9.8-22 22s9.8 22 22 22h38.5l28.5 48.8-55.2 90.7c-22.9-11-48.6-17.2-75.7-17.2-96.8 0-175.5 78.8-175.5 175.6S134.2 817.2 231 817.2c93.7 0 170.4-73.8 175.3-166.3h119c0.5 0 1 0 1.5-0.1 0.2 0 0.5 0 0.7-0.1 0.3 0 0.5 0 0.8-0.1 0.3 0 0.6-0.1 0.9-0.2 0.2 0 0.3-0.1 0.5-0.1 0.4-0.1 0.8-0.2 1.1-0.3 0.1 0 0.2 0 0.2-0.1 3.3-0.9 6.4-2.6 8.9-4.8 0.5-0.4 0.9-0.9 1.3-1.3 0.2-0.2 0.3-0.4 0.5-0.5 0.2-0.2 0.4-0.5 0.6-0.7 1.1-1.3 2-2.8 2.7-4.3L684.4 380l38.7 116.3c-58.9 28.4-99.6 88.6-99.6 158.2 0 96.8 78.7 175.5 175.5 175.5s175.5-78.7 175.5-175.5S895.9 479 799.1 479z m-412-43.3L487 606.9h-83.9c-8-39.7-29.5-74.7-59.4-99.8l43.4-71.4z m-29.3 171.2h-74.9l37.5-61.6c17.7 16.4 30.9 37.7 37.4 61.6zM231 773.1c-72.5 0-131.5-59-131.5-131.5s59-131.5 131.5-131.5c18.7 0 36.5 3.9 52.7 11L225 617.5c-4.1 6.8-4.3 15.3-0.4 22.2 3.9 6.9 11.2 11.2 19.2 11.2h118.4c-4.8 68.2-61.8 122.2-131.2 122.2z m568.1 12.8c-72.5 0-131.5-59-131.5-131.5 0-50.1 28.2-93.8 69.6-116l41 123.1c3.1 9.2 11.7 15 20.9 15 2.3 0 4.6-0.4 7-1.2 11.5-3.8 17.7-16.3 13.9-27.8l-41-123.1c6.6-1 13.3-1.5 20.1-1.5 72.5 0 131.5 59 131.5 131.5s-59 131.5-131.5 131.5z" p-id="1866"></path></svg>""",
"""<svg t="1616821127367" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="2163" width="200" height="200"><path d="M227.3 551.5c-91.3 0-165.6 74.3-165.6 165.6S136 882.7 227.3 882.7s165.6-74.3 165.6-165.6-74.3-165.6-165.6-165.6z m0 287.2c-67.1 0-121.6-54.5-121.6-121.6s54.6-121.6 121.6-121.6S348.9 650 348.9 717.1s-54.5 121.6-121.6 121.6zM631.4 333.8c59.2 0 107.4-48.2 107.5-107.5 0-59.3-48.2-107.5-107.5-107.5S523.9 167 523.9 226.3s48.2 107.5 107.5 107.5z m0-171c35 0 63.4 28.5 63.5 63.5 0 35-28.5 63.5-63.5 63.5s-63.5-28.5-63.5-63.5 28.5-63.5 63.5-63.5zM789.7 563.5c-91.3 0-165.6 74.3-165.6 165.6s74.3 165.6 165.6 165.6 165.6-74.3 165.6-165.6S881 563.5 789.7 563.5z m0 287.2c-67.1 0-121.6-54.5-121.6-121.6s54.6-121.6 121.6-121.6c67.1 0 121.6 54.5 121.6 121.6s-54.5 121.6-121.6 121.6zM615 573.6l-112.1-95.1 26.3-39.2 118.7 61.5c9.1 4.7 18.8 6.9 28.4 6.9 19.9 0 39.4-9.7 51.2-27.3a61.74 61.74 0 0 0 8.6-49.6c-4.4-16.9-15.8-31.3-31.3-39.4L546.7 309c-29.6-15.4-65.8-6.2-84.4 21.5l-85.5 127.3c-18.5 27.6-13.3 64.7 12.1 86.2l99.6 84.1-53.8 80.1c-8.7 12.9-11.8 28.4-8.8 43.6s11.7 28.4 24.6 37c9.6 6.5 20.8 9.9 32.2 9.9 3.8 0 7.6-0.4 11.3-1.2 15.2-3 28.4-11.7 37-24.6l92.5-137.7c13.3-19.8 9.6-46.2-8.5-61.6z m-28 37.1l-92.6 137.7c-4.3 6.4-13.1 8.1-19.5 3.8s-8.1-13.1-3.8-19.5l64.8-96.5c6.2-9.3 4.5-21.9-4.1-29.1l-114.5-96.8c-8.3-7-10-19.1-3.9-28.1l85.5-127.3c6-9 17.8-12 27.3-7l158.1 82.4c4.6 2.4 7.7 6.4 9 11.3s0.4 10-2.4 14.2c-5 7.4-14.8 9.9-22.8 5.8L532 391c-9.9-5.1-22.2-2-28.4 7.3l-48.2 71.9c-6.3 9.3-4.5 21.8 4 29l127.1 108c1 0.9 1.3 2.4 0.5 3.5z" p-id="2164"></path></svg>"""]
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://nbviewer.jupyter.org/github/nvictus/svgpath2mpl/blob/master/examples/homer.ipynb
到此這篇關(guān)于matplotlib實(shí)現(xiàn)自定義散點(diǎn)形狀marker的3種方法的文章就介紹到這了,更多相關(guān)matplotlib 自定義散點(diǎn)形狀marker內(nèi)容請(qǐng)搜索腳本之家以前的文章或繼續(xù)瀏覽下面的相關(guān)文章希望大家以后多多支持腳本之家！
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