python中matplotlib的顏色及線條控制的示例

更新時(shí)間：2018年03月16日 13:40:18 作者：Purogram

這篇文章主要介紹了python中matplotlib的顏色及線條控制的示例，小編覺得挺不錯(cuò)的，現(xiàn)在分享給大家，也給大家做個(gè)參考。一起跟隨小編過來看看吧

下次用python畫圖的時(shí)候選色選點(diǎn)都可以直接參考這邊，牛逼！分享給大家，也給自己留個(gè)筆記。

參考網(wǎng)址：

http://stackoverflow.com/questions/22408237/named-colors-in-matplotlib

http://stackoverflow.com/questions/8409095/matplotlib-set-markers-for-individual-points-on-a-line

第二個(gè)參考網(wǎng)址給出了linestyle可選參數(shù)：

'-'  solid line style 
'--'  dashed line style 
'-.'  dash-dot line style 
':'  dotted line style

第二個(gè)參考網(wǎng)址給出了marker可選參數(shù)：

'.'  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

第一個(gè)參考網(wǎng)址給出了matplotlib中color可用的顏色：

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'}

上面對(duì)應(yīng)的顏色：

另外的顯示方式：

另附上我簡(jiǎn)單的畫折線圖代碼和圖：

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()