下次用python画图的时候选色选点都可以直接参考这边,牛逼!分享给大家,也给自己留个笔记。
参考网址:
http://*.com/questions/22408237/named-colors-in-matplotlib
http://*.com/questions/8409095/matplotlib-set-markers-for-individual-points-on-a-line
第二个参考网址给出了linestyle可选参数:
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'-' solid line style
'--' dashed line style
'-.' dash - dot line style
':' dotted line style
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第二个参考网址给出了marker可选参数:
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'.' point marker
',' pixel marker
'o' circle marker
'v' triangle_down marker
'^' triangle_up marker
'<' triangle_left marker
'>' triangle_right marker
'1' tri_down marker
'2' tri_up marker
'3' tri_left marker
'4' tri_right marker
's' square marker
'p' pentagon marker
'*' star marker
'h' hexagon1 marker
'h' hexagon2 marker
'+' plus marker
'x' x marker
'd' diamond marker
'd' thin_diamond marker
'|' vline marker
'_' hline marker
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第一个参考网址给出了matplotlib中color可用的颜色:
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cnames = {
'aliceblue' : '#f0f8ff' ,
'antiquewhite' : '#faebd7' ,
'aqua' : '#00ffff' ,
'aquamarine' : '#7fffd4' ,
'azure' : '#f0ffff' ,
'beige' : '#f5f5dc' ,
'bisque' : '#ffe4c4' ,
'black' : '#000000' ,
'blanchedalmond' : '#ffebcd' ,
'blue' : '#0000ff' ,
'blueviolet' : '#8a2be2' ,
'brown' : '#a52a2a' ,
'burlywood' : '#deb887' ,
'cadetblue' : '#5f9ea0' ,
'chartreuse' : '#7fff00' ,
'chocolate' : '#d2691e' ,
'coral' : '#ff7f50' ,
'cornflowerblue' : '#6495ed' ,
'cornsilk' : '#fff8dc' ,
'crimson' : '#dc143c' ,
'cyan' : '#00ffff' ,
'darkblue' : '#00008b' ,
'darkcyan' : '#008b8b' ,
'darkgoldenrod' : '#b8860b' ,
'darkgray' : '#a9a9a9' ,
'darkgreen' : '#006400' ,
'darkkhaki' : '#bdb76b' ,
'darkmagenta' : '#8b008b' ,
'darkolivegreen' : '#556b2f' ,
'darkorange' : '#ff8c00' ,
'darkorchid' : '#9932cc' ,
'darkred' : '#8b0000' ,
'darksalmon' : '#e9967a' ,
'darkseagreen' : '#8fbc8f' ,
'darkslateblue' : '#483d8b' ,
'darkslategray' : '#2f4f4f' ,
'darkturquoise' : '#00ced1' ,
'darkviolet' : '#9400d3' ,
'deeppink' : '#ff1493' ,
'deepskyblue' : '#00bfff' ,
'dimgray' : '#696969' ,
'dodgerblue' : '#1e90ff' ,
'firebrick' : '#b22222' ,
'floralwhite' : '#fffaf0' ,
'forestgreen' : '#228b22' ,
'fuchsia' : '#ff00ff' ,
'gainsboro' : '#dcdcdc' ,
'ghostwhite' : '#f8f8ff' ,
'gold' : '#ffd700' ,
'goldenrod' : '#daa520' ,
'gray' : '#808080' ,
'green' : '#008000' ,
'greenyellow' : '#adff2f' ,
'honeydew' : '#f0fff0' ,
'hotpink' : '#ff69b4' ,
'indianred' : '#cd5c5c' ,
'indigo' : '#4b0082' ,
'ivory' : '#fffff0' ,
'khaki' : '#f0e68c' ,
'lavender' : '#e6e6fa' ,
'lavenderblush' : '#fff0f5' ,
'lawngreen' : '#7cfc00' ,
'lemonchiffon' : '#fffacd' ,
'lightblue' : '#add8e6' ,
'lightcoral' : '#f08080' ,
'lightcyan' : '#e0ffff' ,
'lightgoldenrodyellow' : '#fafad2' ,
'lightgreen' : '#90ee90' ,
'lightgray' : '#d3d3d3' ,
'lightpink' : '#ffb6c1' ,
'lightsalmon' : '#ffa07a' ,
'lightseagreen' : '#20b2aa' ,
'lightskyblue' : '#87cefa' ,
'lightslategray' : '#778899' ,
'lightsteelblue' : '#b0c4de' ,
'lightyellow' : '#ffffe0' ,
'lime' : '#00ff00' ,
'limegreen' : '#32cd32' ,
'linen' : '#faf0e6' ,
'magenta' : '#ff00ff' ,
'maroon' : '#800000' ,
'mediumaquamarine' : '#66cdaa' ,
'mediumblue' : '#0000cd' ,
'mediumorchid' : '#ba55d3' ,
'mediumpurple' : '#9370db' ,
'mediumseagreen' : '#3cb371' ,
'mediumslateblue' : '#7b68ee' ,
'mediumspringgreen' : '#00fa9a' ,
'mediumturquoise' : '#48d1cc' ,
'mediumvioletred' : '#c71585' ,
'midnightblue' : '#191970' ,
'mintcream' : '#f5fffa' ,
'mistyrose' : '#ffe4e1' ,
'moccasin' : '#ffe4b5' ,
'navajowhite' : '#ffdead' ,
'navy' : '#000080' ,
'oldlace' : '#fdf5e6' ,
'olive' : '#808000' ,
'olivedrab' : '#6b8e23' ,
'orange' : '#ffa500' ,
'orangered' : '#ff4500' ,
'orchid' : '#da70d6' ,
'palegoldenrod' : '#eee8aa' ,
'palegreen' : '#98fb98' ,
'paleturquoise' : '#afeeee' ,
'palevioletred' : '#db7093' ,
'papayawhip' : '#ffefd5' ,
'peachpuff' : '#ffdab9' ,
'peru' : '#cd853f' ,
'pink' : '#ffc0cb' ,
'plum' : '#dda0dd' ,
'powderblue' : '#b0e0e6' ,
'purple' : '#800080' ,
'red' : '#ff0000' ,
'rosybrown' : '#bc8f8f' ,
'royalblue' : '#4169e1' ,
'saddlebrown' : '#8b4513' ,
'salmon' : '#fa8072' ,
'sandybrown' : '#faa460' ,
'seagreen' : '#2e8b57' ,
'seashell' : '#fff5ee' ,
'sienna' : '#a0522d' ,
'silver' : '#c0c0c0' ,
'skyblue' : '#87ceeb' ,
'slateblue' : '#6a5acd' ,
'slategray' : '#708090' ,
'snow' : '#fffafa' ,
'springgreen' : '#00ff7f' ,
'steelblue' : '#4682b4' ,
'tan' : '#d2b48c' ,
'teal' : '#008080' ,
'thistle' : '#d8bfd8' ,
'tomato' : '#ff6347' ,
'turquoise' : '#40e0d0' ,
'violet' : '#ee82ee' ,
'wheat' : '#f5deb3' ,
'white' : '#ffffff' ,
'whitesmoke' : '#f5f5f5' ,
'yellow' : '#ffff00' ,
'yellowgreen' : '#9acd32' }
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上面对应的颜色:
另外的显示方式:
另附上我简单的画折线图代码和图:
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import matplotlib.pyplot as plt
if __name__ = = '__main__' :
x = [ 20 , 50 , 100 , 150 , 200 , 300 , 400 , 600 , 1000 ]
y1 = [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 ]
plt.figure(figsize = ( 8 , 4.9 ))
plt.plot(x,y1,label = "$example$" ,color = 'r' ,marker = "+" ,linewidth = 1 )
plt.xlabel( "number" )
plt.ylabel( "time" )
plt.title( "-" )
plt.legend()
plt.show()
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以上就是本文的全部内容,希望对大家的学习有所帮助,也希望大家多多支持服务器之家。
原文链接:http://blog.csdn.net/qq_26376175/article/details/67637151