在上一篇 python matplotlib入門（二） Matplotlib 作圖生命週期 中，其中一個重要環節是 自定義圖像（Customizing Matplotlib)，從某種角度來講，其實這幾乎包括了我們繪圖80%的工作，這篇博客就來探討如何DIY我們的圖像。
rcParams
可以在python腳本中動態更改默認的rc設置，或者從python shell以交互方式更改。所有rc設置都存儲在一個名爲matplotlib.rcParams的類字典變量中，該變量對於matplotlib包是全局的, 其本質是從本地文件matplotlibrc讀取數據 。
import matplotlib as mpl
# 修改方式一
mpl.rcParams['lines.linewidth'] = 2
mpl.rcParams['lines.color'] = 'r'
# 修改方式二
mpl.rc('lines', linewidth=4, color='g')
# 恢復默認參數
mpl.rcdefaults() 上面我提到一句話， 其本質是從本地文件matplotlibrc讀取數據 ， 所以接下來我們找到根源，深入探索。
matplotlib使用matplotlibrc配置文件來自定義各種屬性，我們稱之爲rc settings或rc params, 它可以控制matplotlib中幾乎每個屬性的默認值：圖形大小，dpi，線寬，顏色和樣式，軸，軸和網格屬性，文本和字體屬性等。 matplotlib按以下順序在四個位置查找matplotlibrc：
matplotlibrcin the current working directory, usually used for specific customizations that you do not want to apply elsewhere.$MATPLOTLIBRCif it is a file, else$MATPLOTLIBRC/matplotlibrc.It next looks in a user-specific place, depending on your platform:
- On Linux and FreeBSD, it looks in
.config/matplotlib/matplotlibrc(or$XDG_CONFIG_HOME/matplotlib/matplotlibrc) if you’ve customized your environment. - On other platforms, it looks in
.matplotlib/matplotlibrc.
- On Linux and FreeBSD, it looks in
*INSTALL*/matplotlib/mpl-data/matplotlibrc, where*INSTALL*is something like/usr/lib/python3.5/site-packageson Linux, and maybeC:\Python35\Lib\site-packageson Windows. Every time you install matplotlib, this file will be overwritten, so if you want your customizations to be saved, please move this file to your user-specific matplotlib directory.# 查找文件位置 >>> import matplotlib >>> matplotlib.matplotlib_fname() '/home/foo/.config/matplotlib/matplotlibrc'
在我電腦中，只有第四個路徑匹配項，即在安裝包的時候生成的，部分內容如下:
# 路徑 D:\Python\Lib\site-packages\matplotlib\mpl-data
#### MATPLOTLIBRC FORMAT
## This is a sample matplotlib configuration file - you can find a copy
## of it on your system in
## site-packages/matplotlib/mpl-data/matplotlibrc. If you edit it
## there, please note that it will be overwritten in your next install.
## If you want to keep a permanent local copy that will not be
## overwritten, place it in the following location:
## unix/linux:
## $HOME/.config/matplotlib/matplotlibrc or
## $XDG_CONFIG_HOME/matplotlib/matplotlibrc (if $XDG_CONFIG_HOME is set)
## other platforms:
## $HOME/.matplotlib/matplotlibrc
##
## See http://matplotlib.org/users/customizing.html#the-matplotlibrc-file for
## more details on the paths which are checked for the configuration file.
##
## This file is best viewed in a editor which supports python mode
## syntax highlighting. Blank lines, or lines starting with a comment
## symbol, are ignored, as are trailing comments. Other lines must
## have the format
## key : val ## optional comment
##
## Colors: for the color values below, you can either use - a
## matplotlib color string, such as r, k, or b - an rgb tuple, such as
## (1.0, 0.5, 0.0) - a hex string, such as ff00ff - a scalar
## grayscale intensity such as 0.75 - a legal html color name, e.g., red,
## blue, darkslategray
##### CONFIGURATION BEGINS HERE
## The default backend; one of GTK GTKAgg GTKCairo GTK3Agg GTK3Cairo
## MacOSX Qt4Agg Qt5Agg TkAgg WX WXAgg Agg Cairo GDK PS PDF SVG
## Template.
## You can also deploy your own backend outside of matplotlib by
## referring to the module name (which must be in the PYTHONPATH) as
## 'module://my_backend'.
##
## If you omit this parameter, it will always default to "Agg", which is a
## non-interactive backend.
backend : TkAgg
## Note that this can be overridden by the environment variable
## QT_API used by Enthought Tool Suite (ETS); valid values are
## "pyqt" and "pyside". The "pyqt" setting has the side effect of
## forcing the use of Version 2 API for QString and QVariant.
## The port to use for the web server in the WebAgg backend.
#webagg.port : 8988
## The address on which the WebAgg web server should be reachable
#webagg.address : 127.0.0.1
## If webagg.port is unavailable, a number of other random ports will
## be tried until one that is available is found.
#webagg.port_retries : 50
## When True, open the webbrowser to the plot that is shown
#webagg.open_in_browser : True
## if you are running pyplot inside a GUI and your backend choice
## conflicts, we will automatically try to find a compatible one for
## you if backend_fallback is True
#backend_fallback: True
#interactive : False
#toolbar : toolbar2 ## None | toolbar2 ("classic" is deprecated)
#timezone : UTC ## a pytz timezone string, e.g., US/Central or Europe/Paris
## Where your matplotlib data lives if you installed to a non-default
## location. This is where the matplotlib fonts, bitmaps, etc reside
#datapath : /home/jdhunter/mpldata
#### LINES
## See http://matplotlib.org/api/artist_api.html#module-matplotlib.lines for more
## information on line properties.
#lines.linewidth : 1.5 ## line width in points
#lines.linestyle : - ## solid line
#lines.color : C0 ## has no affect on plot(); see axes.prop_cycle
#lines.marker : None ## the default marker
#lines.markeredgewidth : 1.0 ## the line width around the marker symbol
#lines.markersize : 6 ## markersize, in points
#lines.dash_joinstyle : round ## miter|round|bevel
#lines.dash_capstyle : butt ## butt|round|projecting
#lines.solid_joinstyle : round ## miter|round|bevel
#lines.solid_capstyle : projecting ## butt|round|projecting
#lines.antialiased : True ## render lines in antialiased (no jaggies)樣式表
rcParams是自定義控制樣式最全面也是最細緻的方法，但不見得是最佳的方法。因爲我們很多時候並不想花費這麼多的時間去設置一堆堆參數，於是會想到能不能使用模板呢？呵，聰明又懶惰的人類！怎麼可能沒有呢！使用樣式模板很簡單：
plt.style.use('ggplot') # ggplot是其中一種預設樣式,會使用R的同學應該非常熟悉
print(plt.style.available) # 查看所有預設樣式
自定義樣式
可以通過調用style.use以及樣式表的路徑或URL來創建自定義樣式並使用它們。此外，如果將 .mplstyle文件添加到mpl_configdir / stylelib，則可以通過調用style.use（<style-name> ）重用自定義樣式表。默認情況下，mpl_configdir應爲〜/ .config / matplotlib，但你可以使用matplotlib.get_configdir（）查看你的位置，你可能需要創建此目錄。
組合樣式
即使用多種樣式
>>> import matplotlib.pyplot as plt
>>> plt.style.use(['dark_background', 'presentation'])臨時樣式
# 臨時樣式通過這種上下文的方式實現，在python中非常常見
# ps:在R語言中也有類似的用法
with plt.style.context(('dark_background')):
plt.plot(np.sin(np.linspace(0, 2 * np.pi)), 'r-o')
plt.show()