matplotlib.backends.backend_ps

A PostScript backend, which can produce both PostScript .ps and .eps.

matplotlib.backends.backend_ps.FigureCanvas

alias of matplotlib.backends.backend_ps.FigureCanvasPS

class matplotlib.backends.backend_ps.FigureCanvasPS(figure) [source]

Bases: matplotlib.backend_bases.FigureCanvasBase

draw() [source]

Render the Figure.

filetypes = {'eps': 'Encapsulated Postscript', 'ps': 'Postscript'}

fixed_dpi = 72

get_default_filetype() [source]

Get the default savefig file format as specified in rcParam savefig.format. Returned string excludes period. Overridden in backends that only support a single file type.

print_eps(outfile, *args, **kwargs) [source]

print_ps(outfile, *args, **kwargs) [source]

class matplotlib.backends.backend_ps.GraphicsContextPS [source]

Bases: matplotlib.backend_bases.GraphicsContextBase

get_capstyle() [source]

Return the capstyle as a string in ('butt', 'round', 'projecting')

get_joinstyle() [source]

Return the line join style as one of ('miter', 'round', 'bevel')

shouldstroke() [source]

class matplotlib.backends.backend_ps.PsBackendHelper [source]

Bases: object

gs_exe

executable name of ghostscript.

gs_version

version of ghostscript.

supports_ps2write

True if the installed ghostscript supports ps2write device.

class matplotlib.backends.backend_ps.RendererPS(width, height, pswriter, imagedpi=72) [source]

Bases: matplotlib.backend_bases.RendererBase

The renderer handles all the drawing primitives using a graphics context instance that controls the colors/styles.

Although postscript itself is dpi independent, we need to imform the image code about a requested dpi to generate high res images and them scale them before embeddin them

afmfontd = {}

create_hatch(hatch) [source]

draw_gouraud_triangle(gc, points, colors, trans) [source]

Draw a Gouraud-shaded triangle.

Parameters:	points : array_like, shape=(3, 2) Array of (x, y) points for the triangle. colors : array_like, shape=(3, 4) RGBA colors for each point of the triangle. transform : matplotlib.transforms.Transform An affine transform to apply to the points.

draw_gouraud_triangles(gc, points, colors, trans) [source]

Draws a series of Gouraud triangles.

Parameters:	points : array_like, shape=(N, 3, 2) Array of N (x, y) points for the triangles. colors : array_like, shape=(N, 3, 4) Array of N RGBA colors for each point of the triangles. transform : matplotlib.transforms.Transform An affine transform to apply to the points.

draw_image(gc, x, y, im, transform=None) [source]

Draw the Image instance into the current axes; x is the distance in pixels from the left hand side of the canvas and y is the distance from bottom

draw_markers(gc, marker_path, marker_trans, path, trans, rgbFace=None) [source]

Draw the markers defined by path at each of the positions in x and y. path coordinates are points, x and y coords will be transformed by the transform

draw_mathtext(gc, x, y, s, prop, angle) [source]

Draw the math text using matplotlib.mathtext

draw_path(gc, path, transform, rgbFace=None) [source]

Draws a Path instance using the given affine transform.

draw_path_collection(gc, master_transform, paths, all_transforms, offsets, offsetTrans, facecolors, edgecolors, linewidths, linestyles, antialiaseds, urls, offset_position) [source]

Draws a collection of paths selecting drawing properties from the lists facecolors, edgecolors, linewidths, linestyles and antialiaseds. offsets is a list of offsets to apply to each of the paths. The offsets in offsets are first transformed by offsetTrans before being applied. offset_position may be either "screen" or "data" depending on the space that the offsets are in.

This provides a fallback implementation of draw_path_collection() that makes multiple calls to draw_path(). Some backends may want to override this in order to render each set of path data only once, and then reference that path multiple times with the different offsets, colors, styles etc. The generator methods _iter_collection_raw_paths() and _iter_collection() are provided to help with (and standardize) the implementation across backends. It is highly recommended to use those generators, so that changes to the behavior of draw_path_collection() can be made globally.

draw_tex(gc, x, y, s, prop, angle, ismath='TeX!', mtext=None) [source]

draw a Text instance

draw_text(gc, x, y, s, prop, angle, ismath=False, mtext=None) [source]

Draw a Text instance.

flipy() [source]

return true if small y numbers are top for renderer

get_canvas_width_height() [source]

return the canvas width and height in display coords

get_image_magnification() [source]

Get the factor by which to magnify images passed to draw_image. Allows a backend to have images at a different resolution to other artists.

get_text_width_height_descent(s, prop, ismath) [source]

get the width and height in display coords of the string s with FontPropertry prop

merge_used_characters(other) [source]

new_gc() [source]

Return an instance of a GraphicsContextBase

option_image_nocomposite() [source]

return whether to generate a composite image from multiple images on a set of axes

option_scale_image() [source]

ps backend support arbitrary scaling of image.

set_color(r, g, b, store=1) [source]

set_font(fontname, fontsize, store=1) [source]

set_linecap(linecap, store=1) [source]

set_linedash(offset, seq, store=1) [source]

set_linejoin(linejoin, store=1) [source]

set_linewidth(linewidth, store=1) [source]

track_characters(font, s) [source]

Keeps track of which characters are required from each font.

matplotlib.backends.backend_ps.convert_psfrags(tmpfile, psfrags, font_preamble, custom_preamble, paperWidth, paperHeight, orientation) [source]

When we want to use the LaTeX backend with postscript, we write PSFrag tags to a temporary postscript file, each one marking a position for LaTeX to render some text. convert_psfrags generates a LaTeX document containing the commands to convert those tags to text. LaTeX/dvips produces the postscript file that includes the actual text.

matplotlib.backends.backend_ps.get_bbox(tmpfile, bbox) [source]

Deprecated since version 3.0: The get_bbox function was deprecated in Matplotlib 3.0 and will be removed in 3.2.

Use ghostscript's bbox device to find the center of the bounding box. Return an appropriately sized bbox centered around that point. A bit of a hack.

matplotlib.backends.backend_ps.get_bbox_header(lbrt, rotated=False) [source]

return a postscript header stringfor the given bbox lbrt=(l, b, r, t). Optionally, return rotate command.

matplotlib.backends.backend_ps.gs_distill(tmpfile, eps=False, ptype='letter', bbox=None, rotated=False) [source]

Use ghostscript's pswrite or epswrite device to distill a file. This yields smaller files without illegal encapsulated postscript operators. The output is low-level, converting text to outlines.

matplotlib.backends.backend_ps.pstoeps(tmpfile, bbox=None, rotated=False) [source]

Convert the postscript to encapsulated postscript. The bbox of the eps file will be replaced with the given bbox argument. If None, original bbox will be used.

matplotlib.backends.backend_ps.quote_ps_string(s) [source]

Quote dangerous characters of S for use in a PostScript string constant.

matplotlib.backends.backend_ps.xpdf_distill(tmpfile, eps=False, ptype='letter', bbox=None, rotated=False) [source]

Use ghostscript's ps2pdf and xpdf's/poppler's pdftops to distill a file. This yields smaller files without illegal encapsulated postscript operators. This distiller is preferred, generating high-level postscript output that treats text as text.