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Commit 7f7c0a0

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Add a catalogue to matplotlibrc.template file.
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‎matplotlibrc.template

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+59-9Lines changed: 59 additions & 9 deletions
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@@ -27,9 +27,37 @@
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## - a hex string, such as ff00ff
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## - a scalar grayscale intensity such as 0.75
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## - a legal html color name, e.g., red, blue, darkslategray
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##
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## Configurations are currently divided into following parts:
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## - BACKENDS
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## - LINES
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## - PATCHES
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## - HATCHES
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## - BOXPLOT
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## - FONT
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## - TEXT
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## - LaTeX
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## - AXES
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## - DATES
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## - TICKS
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## - GRIDS
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## - LEGEND
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## - FIGURE
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## - IMAGES
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## - CONTOUR PLOTS
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## - ERRORBAR PLOTS
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## - HISTOGRAM PLOTS
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## - SCATTER PLOTS
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## - AGG RENDERING
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## - PATHS
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## - SAVING FIGURES
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## - INTERACTIVE KEYMAPS
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## - ANIMATION
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##### CONFIGURATION BEGINS HERE
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#### BACKENDS
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## The default backend. If you omit this parameter, the first
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## working backend from the following list is used:
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## MacOSX Qt5Agg Qt4Agg Gtk3Agg TkAgg WxAgg Agg
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## When True, open the webbrowser to the plot that is shown
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#webagg.open_in_browser : True
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## if you are running pyplot inside a GUI and your backend choice
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## If you are running pyplot inside a GUI and your backend choice
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## conflicts, we will automatically try to find a compatible one for
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## you if backend_fallback is True
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#backend_fallback: True
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#markers.fillstyle: full ## full|left|right|bottom|top|none
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#### PATCHES
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## Patches are graphical objects that fill 2D space, like polygons or circles.
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## See https://matplotlib.org/api/artist_api.html#module-matplotlib.patches
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#patch.force_edgecolor : False ## True to always use edgecolor
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#patch.antialiased : True ## render patches in antialiased (no jaggies)
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#### HATCHES
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#hatch.color : black
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#hatch.linewidth : 1.0
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#### Boxplot
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#### BOXPLOT
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#boxplot.notch : False
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#boxplot.vertical : True
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#boxplot.whiskers : 1.5
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#font.fantasy : Comic Sans MS, Chicago, Charcoal, ImpactWestern, Humor Sans, xkcd, fantasy
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#font.monospace : DejaVu Sans Mono, Bitstream Vera Sans Mono, Computer Modern Typewriter, Andale Mono, Nimbus Mono L, Courier New, Courier, Fixed, Terminal, monospace
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#### TEXT
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## The text properties used by `text.Text`.
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## See https://matplotlib.org/api/artist_api.html#module-matplotlib.text
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## for more information on text properties
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#text.color : black
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#### LaTeX
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## See following links for more information on LaTex properties:
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## https://matplotlib.org/tutorials/text/usetex.html
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## the special name "regular" for the same font
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## used in regular text.
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#### AXES
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## Following are default face and edge colors, default tick sizes,
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## default fontsizes for ticklabels, and so on. See
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#polaraxes.grid : True ## display grid on polar axes
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#axes3d.grid : True ## display grid on 3d axes
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#### DATES
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## These control the default format strings used in AutoDateFormatter.
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## Any valid format datetime format string can be used (see the python
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#date.autoformatter.second : %H:%M:%S
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#date.autoformatter.microsecond : %M:%S.%f
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#### TICKS
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## See https://matplotlib.org/api/axis_api.html#matplotlib.axis.Tick
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#xtick.top : False ## draw ticks on the top side
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#ytick.minor.right : True ## draw y axis right minor ticks
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#ytick.alignment : center_baseline ## alignment of yticks
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#### GRIDS
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#grid.color : b0b0b0 ## grid color
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#grid.linestyle : - ## solid
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#grid.linewidth : 0.8 ## in points
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#grid.alpha : 1.0 ## transparency, between 0.0 and 1.0
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#### Legend
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#### LEGEND
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#legend.loc : best
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#legend.frameon : True ## if True, draw the legend on a background patch
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#legend.framealpha : 0.8 ## legend patch transparency
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#legend.borderaxespad : 0.5 ## the border between the axes and legend edge
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#legend.columnspacing : 2.0 ## column separation
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#### FIGURE
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## See https://matplotlib.org/api/figure_api.html#matplotlib.figure.Figure
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#figure.titlesize : large ## size of the figure title (Figure.suptitle())
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#figure.constrained_layout.hspace : 0.02 ## Space between subplot groups. Float representing
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#figure.constrained_layout.wspace : 0.02 ## a fraction of the subplot widths being separated.
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#### IMAGES
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#image.aspect : equal ## equal | auto | a number
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#image.interpolation : nearest ## see help(imshow) for options
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## saving a figure as a vector graphics file,
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## such as a PDF.
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#### CONTOUR PLOTS
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#contour.negative_linestyle : dashed ## string or on-off ink sequence
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#contour.corner_mask : True ## True | False | legacy
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#### ERRORBAR PLOTS
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#errorbar.capsize : 0 ## length of end cap on error bars in pixels
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#### HISTOGRAM PLOTS
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#hist.bins : 10 ## The default number of histogram bins.
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## If Numpy 1.11 or later is
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#scatter.marker : o ## The default marker type for scatter plots.
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#scatter.edgecolors : face ## The default edgecolors for scatter plots.
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#### Agg rendering
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#### Warning: experimental, 2008/10/10
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#### AGG RENDERING
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## Warning: experimental, 2008/10/10
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#agg.path.chunksize : 0 ## 0 to disable; values in the range
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## 10000 to 100000 can improve speed slightly
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## and prevent an Agg rendering failure
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## It may cause minor artifacts, though.
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## A value of 20000 is probably a good
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## starting point.
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#### PATHS
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#path.simplify : True ## When True, simplify paths by removing "invisible"
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## points to reduce file size and increase rendering
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## the length is randomly scaled.
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#path.effects : [] ##
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#### SAVING FIGURES
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## the default savefig params can be different from the display params
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## The default savefig params can be different from the display params
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## e.g., you may want a higher resolution, or to make the figure
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## background white
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#savefig.dpi : figure ## figure dots per inch or 'figure'
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#ps.distiller.res : 6000 ## dpi
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#ps.fonttype : 3 ## Output Type 3 (Type3) or Type 42 (TrueType)
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### pdf backend params
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### PDF backend params
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#pdf.compression : 6 ## integer from 0 to 9
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## 0 disables compression (good for debugging)
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#pdf.fonttype : 3 ## Output Type 3 (Type3) or Type 42 (TrueType)
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#pdf.use14corefonts : False
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#pdf.inheritcolor : False
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### svg backend params
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### SVG backend params
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#svg.image_inline : True ## write raster image data directly into the svg file
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#svg.fonttype : path ## How to handle SVG fonts:
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## none: Assume fonts are installed on the machine where the SVG will be viewed.
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### docstring params
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##docstring.hardcopy = False ## set this when you want to generate hardcopy docstring
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#### INTERACTIVE KEYMAPS
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## Event keys to interact with figures/plots via keyboard.
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## See https://matplotlib.org/users/navigation_toolbar.html for more details on
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## interactive navigation. Customize these settings according to your needs.
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#keymap.all_axes : a ## enable all axes
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#keymap.copy : ctrl+c, cmd+c ## Copy figure to clipboard
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###ANIMATION settings
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#### ANIMATION
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#animation.html : none ## How to display the animation as HTML in
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## the IPython notebook. 'html5' uses
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## HTML5 video tag; 'jshtml' creates a

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