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matplot的字体问题,有以下3种方式
一种是从pylab中进行全局管理,可以管理任意实验相关的字体,可以是和matplot无关的实验的字体问题的管理
一种是matplot的配置文件,进行全局管理
一种是.py文件中临时加入配置语句
网上具体的解决方案很多,但是我们会发现拿来用的时候,有时候见效,有时候又不见效,到底咋回事?
注意一点,linux系统支持的中文字体≠matplotlib支持的中文字体。
所以在linux系统中安装好新字体以后,要删除缓存文件:
rm -r ~/.cache/matplotlib
这样再次运行绘图代码时,matplotlib才会重新生成缓存文件,并且更新matplotlib中支持的中文字体,使其与linux系统中支持的中文字体保持一致。
那么“matplotlib支持的字体”怎么知道是哪些呢?见下面代码即可
#-*- coding:utf-8 -*- import sys reload(sys) sys.setdefaultencoding('utf-8') from matplotlib.font_manager import fontManager import os print"os.path=",os.path print"-------------------下面看下matplotlib当前支持哪些中文字体--------------" fonts = [font.name for font in fontManager.ttflist if os.path.exists(font.fname) and os.stat(font.fname).st_size>1e6] for font in fonts: print(font) print"-------------------下面测试matplotlib能否正常显示中文--------------" import matplotlib.pyplot as plt import matplotlib # matplotlib.rcParams['font.sans-serif'] = 'HYQuanTangShiF,Times New Roman' plt.plot((1,2,3),(4,3,-1)) plt.xlabel('横坐标') plt.ylabel(u'纵坐标') plt.show()
结果如下:
好了,没完,有的同学说:
我的不是中文显示为方块,而是中文不显示,这是怎么回事???
可以看到上面的图形中,横坐标居然没有显示中文,咋回事呢?
plt.xlabel(‘横坐标’)
改为:
plt.xlabel(u’横坐标’)
即可
另外,我的配置文件是:
### 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'. backend : TkAgg # If you are using the Qt4Agg backend, you can choose here # to use the PyQt4 bindings or the newer PySide bindings to # the underlying Qt4 toolkit. #backend.qt4 : PyQt4 # PyQt4 | PySide # 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 : 8888 # 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 # When True, the figures rendered in the nbagg backend are created with # a transparent background. # nbagg.transparent : False # 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 : miter # miter|round|bevel #lines.dash_capstyle : butt # butt|round|projecting #lines.solid_joinstyle : miter # miter|round|bevel #lines.solid_capstyle : projecting # butt|round|projecting #lines.antialiased : True # render lines in antialiased (no jaggies) # The three standard dash patterns. These are scaled by the linewidth. #lines.dashed_pattern : 2.8, 1.2 #lines.dashdot_pattern : 4.8, 1.2, 0.8, 1.2 #lines.dotted_pattern : 1.1, 1.1 #lines.scale_dashes : True #markers.fillstyle: full # full|left|right|bottom|top|none ### PATCHES # Patches are graphical objects that fill 2D space, like polygons or # circles. See # http://matplotlib.org/api/artist_api.html#module-matplotlib.patches # information on patch properties #patch.linewidth : 1 # edge width in points. #patch.facecolor : C0 #patch.edgecolor : black # if forced, or patch is not filled #patch.force_edgecolor : False # True to always use edgecolor #patch.antialiased : True # render patches in antialiased (no jaggies) ### HATCHES #hatch.color : k #hatch.linewidth : 1.0 ### Boxplot #boxplot.notch : False #boxplot.vertical : True #boxplot.whiskers : 1.5 #boxplot.bootstrap : None #boxplot.patchartist : False #boxplot.showmeans : False #boxplot.showcaps : True #boxplot.showbox : True #boxplot.showfliers : True #boxplot.meanline : False #boxplot.flierprops.color : 'k' #boxplot.flierprops.marker : 'o' #boxplot.flierprops.markerfacecolor : 'none' #boxplot.flierprops.markeredgecolor : 'k' #boxplot.flierprops.markersize : 6 #boxplot.flierprops.linestyle : 'none' #boxplot.flierprops.linewidth : 1.0 #boxplot.boxprops.color : 'k' #boxplot.boxprops.linewidth : 1.0 #boxplot.boxprops.linestyle : '-' #boxplot.whiskerprops.color : 'k' #boxplot.whiskerprops.linewidth : 1.0 #boxplot.whiskerprops.linestyle : '-' #boxplot.capprops.color : 'k' #boxplot.capprops.linewidth : 1.0 #boxplot.capprops.linestyle : '-' #boxplot.medianprops.color : 'C1' #boxplot.medianprops.linewidth : 1.0 #boxplot.medianprops.linestyle : '-' #boxplot.meanprops.color : 'C2' #boxplot.meanprops.marker : '^' #boxplot.meanprops.markerfacecolor : 'C2' #boxplot.meanprops.markeredgecolor : 'C2' #boxplot.meanprops.markersize : 6 #boxplot.meanprops.linestyle : 'none' #boxplot.meanprops.linewidth : 1.0 ### FONT # # font properties used by text.Text. See # http://matplotlib.org/api/font_manager_api.html for more # information on font properties. The 6 font properties used for font # matching are given below with their default values. # # The font.family property has five values: 'serif' (e.g., Times), # 'sans-serif' (e.g., Helvetica), 'cursive' (e.g., Zapf-Chancery), # 'fantasy' (e.g., Western), and 'monospace' (e.g., Courier). Each of # these font families has a default list of font names in decreasing # order of priority associated with them. When text.usetex is False, # font.family may also be one or more concrete font names. # # The font.style property has three values: normal (or roman), italic # or oblique. The oblique style will be used for italic, if it is not # present. # # The font.variant property has two values: normal or small-caps. For # TrueType fonts, which are scalable fonts, small-caps is equivalent # to using a font size of 'smaller', or about 83%% of the current font # size. # # The font.weight property has effectively 13 values: normal, bold, # bolder, lighter, 100, 200, 300, ..., 900. Normal is the same as # 400, and bold is 700. bolder and lighter are relative values with # respect to the current weight. # # The font.stretch property has 11 values: ultra-condensed, # extra-condensed, condensed, semi-condensed, normal, semi-expanded, # expanded, extra-expanded, ultra-expanded, wider, and narrower. This # property is not currently implemented. # # The font.size property is the default font size for text, given in pts. # 10 pt is the standard value. # font.family : sans-serif font.style : normal font.variant : normal font.weight : medium font.stretch : normal # note that font.size controls default text sizes. To configure # special text sizes tick labels, axes, labels, title, etc, see the rc # settings for axes and ticks. Special text sizes can be defined # relative to font.size, using the following values: xx-small, x-small, # small, medium, large, x-large, xx-large, larger, or smaller #font.size : 10.0 #font.serif : DejaVu Serif, Bitstream Vera Serif, New Century Schoolbook, Century Schoolbook L, Utopia, ITC Bookman, Bookman, Nimbus Roman No9 L, Times New Roman, Times, Palatino, Charter, serif font.sans-serif : HYQuanTangShiF,Times New Roman #font.cursive : Apple Chancery, Textile, Zapf Chancery, Sand, Script MT, Felipa, cursive #font.fantasy : Comic Sans MS, Chicago, Charcoal, Impact, Western, Humor Sans, xkcd, fantasy #font.monospace : DejaVu Sans Mono, Bitstream Vera Sans Mono, Andale Mono, Nimbus Mono L, Courier New, Courier, Fixed, Terminal, monospace ### TEXT # text properties used by text.Text. See # http://matplotlib.org/api/artist_api.html#module-matplotlib.text for more # information on text properties #text.color : black ### LaTeX customizations. See http://wiki.scipy.org/Cookbook/Matplotlib/UsingTex #text.usetex : False # use latex for all text handling. The following fonts # are supported through the usual rc parameter settings: # new century schoolbook, bookman, times, palatino, # zapf chancery, charter, serif, sans-serif, helvetica, # avant garde, courier, monospace, computer modern roman, # computer modern sans serif, computer modern typewriter # If another font is desired which can loaded using the # LaTeX \usepackage command, please inquire at the # matplotlib mailing list #text.latex.unicode : False # use "ucs" and "inputenc" LaTeX packages for handling # unicode strings. #text.latex.preamble : # IMPROPER USE OF THIS FEATURE WILL LEAD TO LATEX FAILURES # AND IS THEREFORE UNSUPPORTED. PLEASE DO NOT ASK FOR HELP # IF THIS FEATURE DOES NOT DO WHAT YOU EXPECT IT TO. # preamble is a comma separated list of LaTeX statements # that are included in the LaTeX document preamble. # An example: # text.latex.preamble : \usepackage{bm},\usepackage{euler} # The following packages are always loaded with usetex, so # beware of package collisions: color, geometry, graphicx, # type1cm, textcomp. Adobe Postscript (PSSNFS) font packages # may also be loaded, depending on your font settings #text.dvipnghack : None # some versions of dvipng don't handle alpha # channel properly. Use True to correct # and flush ~/.matplotlib/tex.cache # before testing and False to force # correction off. None will try and # guess based on your dvipng version #text.hinting : auto # May be one of the following: # 'none': Perform no hinting # 'auto': Use FreeType's autohinter # 'native': Use the hinting information in the # font file, if available, and if your # FreeType library supports it # 'either': Use the native hinting information, # or the autohinter if none is available. # For backward compatibility, this value may also be # True === 'auto' or False === 'none'. #text.hinting_factor : 8 # Specifies the amount of softness for hinting in the # horizontal direction. A value of 1 will hint to full # pixels. A value of 2 will hint to half pixels etc. #text.antialiased : True # If True (default), the text will be antialiased. # This only affects the Agg backend. # The following settings allow you to select the fonts in math mode. # They map from a TeX font name to a fontconfig font pattern. # These settings are only used if mathtext.fontset is 'custom'. # Note that this "custom" mode is unsupported and may go away in the # future. #mathtext.cal : cursive #mathtext.rm : serif #mathtext.tt : monospace #mathtext.it : serif:italic #mathtext.bf : serif:bold #mathtext.sf : sans #mathtext.fontset : dejavusans # Should be 'dejavusans' (default), # 'dejavuserif', 'cm' (Computer Modern), 'stix', # 'stixsans' or 'custom' #mathtext.fallback_to_cm : True # When True, use symbols from the Computer Modern # fonts when a symbol can not be found in one of # the custom math fonts. #mathtext.default : it # The default font to use for math. # Can be any of the LaTeX font names, including # the special name "regular" for the same font # used in regular text. ### AXES # default face and edge color, default tick sizes, # default fontsizes for ticklabels, and so on. See # http://matplotlib.org/api/axes_api.html#module-matplotlib.axes #axes.facecolor : white # axes background color #axes.edgecolor : black # axes edge color #axes.linewidth : 0.8 # edge linewidth #axes.grid : False # display grid or not #axes.titlesize : large # fontsize of the axes title #axes.titlepad : 6.0 # pad between axes and title in points #axes.labelsize : medium # fontsize of the x any y labels #axes.labelpad : 4.0 # space between label and axis #axes.labelweight : normal # weight of the x and y labels #axes.labelcolor : black #axes.axisbelow : 'line' # draw axis gridlines and ticks below # patches (True); above patches but below # lines ('line'); or above all (False) #axes.formatter.limits : -7, 7 # use scientific notation if log10 # of the axis range is smaller than the # first or larger than the second #axes.formatter.use_locale : False # When True, format tick labels # according to the user's locale. # For example, use ',' as a decimal # separator in the fr_FR locale. #axes.formatter.use_mathtext : False # When True, use mathtext for scientific # notation. #axes.formatter.useoffset : True # If True, the tick label formatter # will default to labeling ticks relative # to an offset when the data range is # small compared to the minimum absolute # value of the data. #axes.formatter.offset_threshold : 4 # When useoffset is True, the offset # will be used when it can remove # at least this number of significant # digits from tick labels. # axes.spines.left : True # display axis spines # axes.spines.bottom : True # axes.spines.top : True # axes.spines.right : True #axes.unicode_minus : True # use unicode for the minus symbol # rather than hyphen. See # http://en.wikipedia.org/wiki/Plus_and_minus_signs#Character_codes #axes.prop_cycle : cycler('color', # ['1f77b4', 'ff7f0e', '2ca02c', 'd62728', # '9467bd', '8c564b', 'e377c2', '7f7f7f', # 'bcbd22', '17becf']) # color cycle for plot lines # as list of string colorspecs: # single letter, long name, or # web-style hex #axes.autolimit_mode : data # How to scale axes limits to the data. # Use "data" to use data limits, plus some margin # Use "round_number" move to the nearest "round" number #axes.xmargin : .05 # x margin. See `axes.Axes.margins` #axes.ymargin : .05 # y margin See `axes.Axes.margins` #polaraxes.grid : True # display grid on polar axes #axes3d.grid : True # display grid on 3d axes ### DATES # These control the default format strings used in AutoDateFormatter. # Any valid format datetime format string can be used (see the python # `datetime` for details). For example using '%%x' will use the locale date representation # '%%X' will use the locale time representation and '%%c' will use the full locale datetime # representation. # These values map to the scales: # {'year': 365, 'month': 30, 'day': 1, 'hour': 1/24, 'minute': 1 / (24 * 60)} # date.autoformatter.year : %Y # date.autoformatter.month : %Y-%m # date.autoformatter.day : %Y-%m-%d # date.autoformatter.hour : %m-%d %H # date.autoformatter.minute : %d %H:%M # date.autoformatter.second : %H:%M:%S # date.autoformatter.microsecond : %M:%S.%f ### TICKS # see http://matplotlib.org/api/axis_api.html#matplotlib.axis.Tick #xtick.top : False # draw ticks on the top side #xtick.bottom : True # draw ticks on the bottom side #xtick.major.size : 3.5 # major tick size in points #xtick.minor.size : 2 # minor tick size in points #xtick.major.width : 0.8 # major tick width in points #xtick.minor.width : 0.6 # minor tick width in points #xtick.major.pad : 3.5 # distance to major tick label in points #xtick.minor.pad : 3.4 # distance to the minor tick label in points #xtick.color : k # color of the tick labels #xtick.labelsize : medium # fontsize of the tick labels #xtick.direction : out # direction: in, out, or inout #xtick.minor.visible : False # visibility of minor ticks on x-axis #xtick.major.top : True # draw x axis top major ticks #xtick.major.bottom : True # draw x axis bottom major ticks #xtick.minor.top : True # draw x axis top minor ticks #xtick.minor.bottom : True # draw x axis bottom minor ticks #ytick.left : True # draw ticks on the left side #ytick.right : False # draw ticks on the right side #ytick.major.size : 3.5 # major tick size in points #ytick.minor.size : 2 # minor tick size in points #ytick.major.width : 0.8 # major tick width in points #ytick.minor.width : 0.6 # minor tick width in points #ytick.major.pad : 3.5 # distance to major tick label in points #ytick.minor.pad : 3.4 # distance to the minor tick label in points #ytick.color : k # color of the tick labels #ytick.labelsize : medium # fontsize of the tick labels #ytick.direction : out # direction: in, out, or inout #ytick.minor.visible : False # visibility of minor ticks on y-axis #ytick.major.left : True # draw y axis left major ticks #ytick.major.right : True # draw y axis right major ticks #ytick.minor.left : True # draw y axis left minor ticks #ytick.minor.right : True # draw y axis right minor ticks ### GRIDS #grid.color : b0b0b0 # grid color #grid.linestyle : - # solid #grid.linewidth : 0.8 # in points #grid.alpha : 1.0 # transparency, between 0.0 and 1.0 ### Legend #legend.loc : best #legend.frameon : True # if True, draw the legend on a background patch #legend.framealpha : 0.8 # legend patch transparency #legend.facecolor : inherit # inherit from axes.facecolor; or color spec #legend.edgecolor : 0.8 # background patch boundary color #legend.fancybox : True # if True, use a rounded box for the # legend background, else a rectangle #legend.shadow : False # if True, give background a shadow effect #legend.numpoints : 1 # the number of marker points in the legend line #legend.scatterpoints : 1 # number of scatter points #legend.markerscale : 1.0 # the relative size of legend markers vs. original #legend.fontsize : medium # Dimensions as fraction of fontsize: #legend.borderpad : 0.4 # border whitespace #legend.labelspacing : 0.5 # the vertical space between the legend entries #legend.handlelength : 2.0 # the length of the legend lines #legend.handleheight : 0.7 # the height of the legend handle #legend.handletextpad : 0.8 # the space between the legend line and legend text #legend.borderaxespad : 0.5 # the border between the axes and legend edge #legend.columnspacing : 2.0 # column separation ### FIGURE # See http://matplotlib.org/api/figure_api.html#matplotlib.figure.Figure #figure.titlesize : large # size of the figure title (Figure.suptitle()) #figure.titleweight : normal # weight of the figure title #figure.figsize : 6.4, 4.8 # figure size in inches #figure.dpi : 100 # figure dots per inch #figure.facecolor : white # figure facecolor; 0.75 is scalar gray #figure.edgecolor : white # figure edgecolor #figure.autolayout : False # When True, automatically adjust subplot # parameters to make the plot fit the figure #figure.max_open_warning : 20 # The maximum number of figures to open through # the pyplot interface before emitting a warning. # If less than one this feature is disabled. # The figure subplot parameters. All dimensions are a fraction of the #figure.subplot.left : 0.125 # the left side of the subplots of the figure #figure.subplot.right : 0.9 # the right side of the subplots of the figure #figure.subplot.bottom : 0.11 # the bottom of the subplots of the figure #figure.subplot.top : 0.88 # the top of the subplots of the figure #figure.subplot.wspace : 0.2 # the amount of width reserved for blank space between subplots, # expressed as a fraction of the average axis width #figure.subplot.hspace : 0.2 # the amount of height reserved for white space between subplots, # expressed as a fraction of the average axis height ### IMAGES #image.aspect : equal # equal | auto | a number #image.interpolation : nearest # see help(imshow) for options #image.cmap : viridis # A colormap name, gray etc... #image.lut : 256 # the size of the colormap lookup table #image.origin : upper # lower | upper #image.resample : True #image.composite_image : True # When True, all the images on a set of axes are # combined into a single composite image before # saving a figure as a vector graphics file, # such as a PDF. ### CONTOUR PLOTS #contour.negative_linestyle : dashed # dashed | solid #contour.corner_mask : True # True | False | legacy ### ERRORBAR PLOTS #errorbar.capsize : 0 # length of end cap on error bars in pixels ### HISTOGRAM PLOTS #hist.bins : 10 # The default number of histogram bins. # If Numpy 1.11 or later is # installed, may also be `auto` ### SCATTER PLOTS #scatter.marker : o # The default marker type for scatter plots. ### Agg rendering ### Warning: experimental, 2008/10/10 #agg.path.chunksize : 0 # 0 to disable; values in the range # 10000 to 100000 can improve speed slightly # and prevent an Agg rendering failure # when plotting very large data sets, # especially if they are very gappy. # It may cause minor artifacts, though. # A value of 20000 is probably a good # starting point. ### SAVING FIGURES #path.simplify : True # When True, simplify paths by removing "invisible" # points to reduce file size and increase rendering # speed #path.simplify_threshold : 0.1 # The threshold of similarity below which # vertices will be removed in the simplification # process #path.snap : True # When True, rectilinear axis-aligned paths will be snapped to # the nearest pixel when certain criteria are met. When False, # paths will never be snapped. #path.sketch : None # May be none, or a 3-tuple of the form (scale, length, # randomness). # *scale* is the amplitude of the wiggle # perpendicular to the line (in pixels). *length* # is the length of the wiggle along the line (in # pixels). *randomness* is the factor by which # the length is randomly scaled. # the default savefig params can be different from the display params # e.g., you may want a higher resolution, or to make the figure # background white #savefig.dpi : figure # figure dots per inch or 'figure' #savefig.facecolor : white # figure facecolor when saving #savefig.edgecolor : white # figure edgecolor when saving #savefig.format : png # png, ps, pdf, svg #savefig.bbox : standard # 'tight' or 'standard'. # 'tight' is incompatible with pipe-based animation # backends but will workd with temporary file based ones: # e.g. setting animation.writer to ffmpeg will not work, # use ffmpeg_file instead #savefig.pad_inches : 0.1 # Padding to be used when bbox is set to 'tight' #savefig.jpeg_quality: 95 # when a jpeg is saved, the default quality parameter. #savefig.directory : ~ # default directory in savefig dialog box, # leave empty to always use current working directory #savefig.transparent : False # setting that controls whether figures are saved with a # transparent background by default # tk backend params #tk.window_focus : False # Maintain shell focus for TkAgg # ps backend params #ps.papersize : letter # auto, letter, legal, ledger, A0-A10, B0-B10 #ps.useafm : False # use of afm fonts, results in small files #ps.usedistiller : False # can be: None, ghostscript or xpdf # Experimental: may produce smaller files. # xpdf intended for production of publication quality files, # but requires ghostscript, xpdf and ps2eps #ps.distiller.res : 6000 # dpi #ps.fonttype : 3 # Output Type 3 (Type3) or Type 42 (TrueType) # pdf backend params #pdf.compression : 6 # integer from 0 to 9 # 0 disables compression (good for debugging) #pdf.fonttype : 3 # Output Type 3 (Type3) or Type 42 (TrueType) # svg backend params #svg.image_inline : True # write raster image data directly into the svg file #svg.fonttype : 'path' # How to handle SVG fonts: # 'none': Assume fonts are installed on the machine where the SVG will be viewed. # 'path': Embed characters as paths -- supported by most SVG renderers # 'svgfont': Embed characters as SVG fonts -- supported only by Chrome, # Opera and Safari #svg.hashsalt : None # if not None, use this string as hash salt # instead of uuid4 # docstring params #docstring.hardcopy = False # set this when you want to generate hardcopy docstring # Set the verbose flags. This controls how much information # matplotlib gives you at runtime and where it goes. The verbosity # levels are: silent, helpful, debug, debug-annoying. Any level is # inclusive of all the levels below it. If your setting is "debug", # you'll get all the debug and helpful messages. When submitting # problems to the mailing-list, please set verbose to "helpful" or "debug" # and paste the output into your report. # # The "fileo" gives the destination for any calls to verbose.report. # These objects can a filename, or a filehandle like sys.stdout. # # You can override the rc default verbosity from the command line by # giving the flags --verbose-LEVEL where LEVEL is one of the legal # levels, e.g., --verbose-helpful. # # You can access the verbose instance in your code # from matplotlib import verbose. #verbose.level : silent # one of silent, helpful, debug, debug-annoying #verbose.fileo : sys.stdout # a log filename, sys.stdout or sys.stderr # Event keys to interact with figures/plots via keyboard. # Customize these settings according to your needs. # Leave the field(s) empty if you don't need a key-map. (i.e., fullscreen : '') #keymap.fullscreen : f, ctrl+f # toggling #keymap.home : h, r, home # home or reset mnemonic #keymap.back : left, c, backspace # forward / backward keys to enable #keymap.forward : right, v # left handed quick navigation #keymap.pan : p # pan mnemonic #keymap.zoom : o # zoom mnemonic #keymap.save : s # saving current figure #keymap.quit : ctrl+w, cmd+w # close the current figure #keymap.grid : g # switching on/off a grid in current axes #keymap.yscale : l # toggle scaling of y-axes ('log'/'linear') #keymap.xscale : L, k # toggle scaling of x-axes ('log'/'linear') #keymap.all_axes : a # enable all axes # Control location of examples data files #examples.directory : '' # directory to look in for custom installation ###ANIMATION settings #animation.html : 'none' # How to display the animation as HTML in # the IPython notebook. 'html5' uses # HTML5 video tag. #animation.writer : ffmpeg # MovieWriter 'backend' to use #animation.codec : h264 # Codec to use for writing movie #animation.bitrate: -1 # Controls size/quality tradeoff for movie. # -1 implies let utility auto-determine #animation.frame_format: 'png' # Controls frame format used by temp files #animation.ffmpeg_path: 'ffmpeg' # Path to ffmpeg binary. Without full path # $PATH is searched #animation.ffmpeg_args: '' # Additional arguments to pass to ffmpeg #animation.avconv_path: 'avconv' # Path to avconv binary. Without full path # $PATH is searched #animation.avconv_args: '' # Additional arguments to pass to avconv #animation.mencoder_path: 'mencoder' # Path to mencoder binary. Without full path # $PATH is searched #animation.mencoder_args: '' # Additional arguments to pass to mencoder #animation.convert_path: 'convert' # Path to ImageMagick's convert binary. # On Windows use the full path since convert # is also the name of a system tool.
配置文件的路径是:
~/.virtualenvs/python2.7/lib/python2.7/site-packages/matplotlib/mpl-data
如果是python3,那么上面的路径是
~/.virtualenvs/python3.5/lib/python3.5/site-packages/matplotlib/mpl-data
文件内容不变
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