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文章目录前言Matplotlib 折线图格式调整
标签线条颜色线条形状折点样式线条透明度
前言看到有些论文插图十分简洁美观，于是便摸索一下如何美化一下折线图绘图。本文将在前文Python数据分析-数据可视化的基础上，介绍折线图格式的调整。
本文使用的画图工具为matplotlib，相关API可访问python matplotlib文档。
Matplotlib 折线图格式调整首先，贴一下文档中折线图绘制的附加参数表：
| Property | Description |
|---|---|
| agg_filter | a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array |
| alpha | scalar or None |
| animated | bool |
| antialiased or aa | bool |
| clip_box | Bbox |
| clip_on | bool |
| clip_path | Patch or (Path, Transform) or None |
| color or c | color |
| dash_capstyle | CapStyle or {‘butt’, ‘projecting’, ‘round’} |
| dash_joinstyle | JoinStyle or {‘miter’, ‘round’, ‘bevel’} |
| dashes | sequence of floats (on/off ink in points) or (None, None) |
| data | (2, N) array or two 1D arrays |
| drawstyle or ds | {‘default’, ‘steps’, ‘steps-pre’, ‘steps-mid’, ‘steps-post’}, default: ‘default’ |
| figure | Figure |
| fillstyle | {‘full’, ‘left’, ‘right’, ‘bottom’, ‘top’, ‘none’} |
| gid | str |
| in_layout | bool |
| label | object |
| linestyle or ls | {’-’, ‘–’, ‘-.’, ‘:’, ‘’, (offset, on-off-seq), …} |
| linewidth or lw | float |
| marker | marker style string, Path or MarkerStyle |
| markeredgecolor or mec | color |
| markeredgewidth or mew | float |
| markerfacecolor or mfc | color |
| markerfacecoloralt or mfcalt | color |
| markersize or ms | float |
| markevery | None or int or (int, int) or slice or list[int] or float or (float, float) or list[bool] |
| path_effects | AbstractPathEffect |
| picker | float or callable[[Artist, Event], tuple[bool, dict]] |
| pickradius | float |
| rasterized | bool |
| sketch_params | (scale: float, length: float, randomness: float) |
| snap | bool or None |
| solid_capstyle | CapStyle or {‘butt’, ‘projecting’, ‘round’} |
| solid_joinstyle | JoinStyle or {‘miter’, ‘round’, ‘bevel’} |
| transform | unknown |
| url | str |
| visible | bool |
| xdata | 1D array |
| ydata | 1D array |
| zorder | float |
接下来，我将挑选几个常用的附加参数介绍使用方式与效果。
标签- 附加参数名：label功能：为绘制曲线命名，该名称会在图例显示使用方式：plt.plot(x,y,label=‘example’)
import random import matplotlib.pyplot as plt x = range(10) y = [random.random() for _ in range(10)] plt.figure() plt.plot(x, y, label='example') plt.legend() plt.show()线条颜色
- 附加参数名：color功能：选择绘制线条的颜色使用方式：plt.plot(x,y,color=‘r’)颜色选取方式分为三种：
用全名或简称 ，如blue或b16进制 ，如FF00FF(r, g, b) 或 (r, g, b, a)，如（1,0,1,1） ，其中 r g b a 取均为[0, 1]之间，[0, 1]之间的浮点数的字符串形式，表示灰度值。0表示黑色，1表示白色
import random import matplotlib.pyplot as plt x = range(10) y = [random.random() for _ in range(10)] y2 = [random.random() for _ in range(10)] y3 = [random.random() for _ in range(10)] y4 = [random.random() for _ in range(10)] plt.figure() plt.plot(x, y, label='example1', color='blue') plt.plot(x, y2, label='example2', color='r') plt.plot(x, y3, label='example3', color='#00FFFF') plt.plot(x, y4, label='example4', color=(0.4, 0.5, 0.6)) plt.legend() plt.show()线条形状
- 附加参数名：linestyle(或ls)功能：选择绘制线条的形状使用方式：plt.plot(x,y,linestyle=’:’)或者plt.plot(x,y,ls=’:’)常用形状：
- 实线(solid)– 短线(dashed)-. 短点相间线(dashdot)： 虚点线(dotted)‘’, ’ ', None
import random import matplotlib.pyplot as plt x = range(10) y = [random.random() for _ in range(10)] y2 = [random.random() for _ in range(10)] y3 = [random.random() for _ in range(10)] y4 = [random.random() for _ in range(10)] plt.figure() plt.plot(x, y, label='example1', color='blue', linestyle='-') plt.plot(x, y2, label='example2', color='r', ls='--') plt.plot(x, y3, label='example3', color='#00FFFF', ls=':') plt.plot(x, y4, label='example4', color=(0.4, 0.5, 0.6), ls='') plt.legend() plt.show()折点样式
- 附加参数名：
(1)marker – 折点形状
(2)markeredgecolor 或 mec – 折点外边颜色
(3)markeredgewidth 或 mew – 折点线宽
(4)markerfacecolor 或 mfc --折点实心颜色
(5)markerfacecoloralt 或 mfcalt
(6)markersize 或 ms --折点大小
折点形状选择如下表:
| character | description |
|---|---|
| '-' | solid line style |
| '--' | dashed line style |
| '-.' | dash-dot line style |
| ':' | dotted line style |
| '.' | 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 |
| ``’ | '`` |
| '_' | hline marker |
import random import matplotlib.pyplot as plt x = range(10) y = [random.random() for _ in range(10)] y2 = [random.random() for _ in range(10)] y3 = [random.random() for _ in range(10)] y4 = [random.random() for _ in range(10)] plt.figure() plt.plot(x, y, label='example1', color='blue', linestyle='-', marker='o') plt.plot(x, y2, label='example2', color='r', ls='--', marker='1') plt.plot(x, y3, label='example3', color='#00FFFF', ls=':', marker='2') plt.plot(x, y4, label='example4', color=(0.4, 0.5, 0.6), marker='3') plt.legend() plt.show()线条透明度
- 附加参数名：alpha,值在[0,1]之间功能：选择绘制线条的透明度使用方式：plt.plot(x,y,alpha=‘0.9’)
import random import matplotlib.pyplot as plt x = range(10) y = [random.random() for _ in range(10)] y2 = [random.random() for _ in range(10)] y3 = [random.random() for _ in range(10)] y4 = [random.random() for _ in range(10)] plt.figure() plt.plot(x, y, label='example1', color='blue', linestyle='-', alpha=0.3) plt.plot(x, y2, label='example2', color='r', ls='--', alpha=0.1) plt.plot(x, y3, label='example3', color='#00FFFF', ls=':', alpha=0.5) plt.plot(x, y4, label='example4', color=(0.4, 0.5, 0.6), ls='') plt.legend() plt.show()
