matplotlib.backends.backend_agg

An agg http://antigrain.com/ backend

Features that are implemented

• capstyles and join styles
• dashes
• linewidth
• lines, rectangles, ellipses
• clipping to a rectangle
• output to RGBA and PNG, optionally JPEG and TIFF
• alpha blending
• DPI scaling properly - everything scales properly (dashes, linewidths, etc)
• draw polygon
• freetype2 w/ ft2font

TODO:

• integrate screen dpi w/ ppi and text

matplotlib.backends.backend_agg.FigureCanvas

alias of matplotlib.backends.backend_agg.FigureCanvasAgg

class matplotlib.backends.backend_agg.FigureCanvasAgg(figure) [source]

Bases: matplotlib.backend_bases.FigureCanvasBase

The canvas the figure renders into. Calls the draw and print fig methods, creates the renderers, etc...

Attributes:	figure : matplotlib.figure.Figure A high-level Figure instance

buffer_rgba() [source]

Get the image as an RGBA byte string

draw must be called at least once before this function will work and to update the renderer for any subsequent changes to the Figure.

Returns:	bytes

copy_from_bbox(bbox) [source]

draw() [source]

Draw the figure using the renderer

get_renderer(cleared=False) [source]

print_jpeg(filename_or_obj, *args, **kwargs)

Other Parameters:

quality : int The image quality, on a scale from 1 (worst) to 95 (best). The default is 95, if not given in the matplotlibrc file in the savefig.jpeg_quality parameter. Values above 95 should be avoided; 100 completely disables the JPEG quantization stage. optimize : bool If present, indicates that the encoder should make an extra pass over the image in order to select optimal encoder settings. progressive : bool If present, indicates that this image should be stored as a progressive JPEG file.

print_jpg(filename_or_obj, *args, **kwargs) [source]

Other Parameters:

quality : int The image quality, on a scale from 1 (worst) to 95 (best). The default is 95, if not given in the matplotlibrc file in the savefig.jpeg_quality parameter. Values above 95 should be avoided; 100 completely disables the JPEG quantization stage. optimize : bool If present, indicates that the encoder should make an extra pass over the image in order to select optimal encoder settings. progressive : bool If present, indicates that this image should be stored as a progressive JPEG file.

print_png(filename_or_obj, *args, **kwargs) [source]

print_raw(filename_or_obj, *args, **kwargs) [source]

print_rgba(filename_or_obj, *args, **kwargs)

print_tif(filename_or_obj, *args, **kwargs) [source]

print_tiff(filename_or_obj, *args, **kwargs)

print_to_buffer() [source]

restore_region(region, bbox=None, xy=None) [source]

tostring_argb() [source]

Get the image as an ARGB byte string

draw must be called at least once before this function will work and to update the renderer for any subsequent changes to the Figure.

Returns:	bytes

tostring_rgb() [source]

Get the image as an RGB byte string

draw must be called at least once before this function will work and to update the renderer for any subsequent changes to the Figure.

Returns:	bytes

class matplotlib.backends.backend_agg.RendererAgg(width, height, dpi) [source]

Bases: matplotlib.backend_bases.RendererBase

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

buffer_rgba() [source]

clear() [source]

debug

Deprecated since version 2.2: The debug function was deprecated in version 2.2.

draw_markers(*kl, **kw) [source]

Draws a marker at each of the vertices in path. This includes all vertices, including control points on curves. To avoid that behavior, those vertices should be removed before calling this function.

This provides a fallback implementation of draw_markers that makes multiple calls to draw_path(). Some backends may want to override this method in order to draw the marker only once and reuse it multiple times.

Parameters:	gc : GraphicsContextBase The graphics context marker_trans : matplotlib.transforms.Transform An affine transform applied to the marker. trans : matplotlib.transforms.Transform An affine transform applied to the path.

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

Draw the math text using matplotlib.mathtext

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

Draw the path

draw_path_collection(*kl, **kw) [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_text(gc, x, y, s, prop, angle, ismath=False, mtext=None) [source]

Render the text

get_canvas_width_height() [source]

return the canvas width and height in display coords

get_text_width_height_descent(s, prop, ismath) [source]

Get the width, height, and descent (offset from the bottom to the baseline), in display coords, of the string s with FontProperties prop

lock = <unlocked _thread.RLock object owner=0 count=0>

option_image_nocomposite() [source]

override this method for renderers that do not necessarily always want to rescale and composite raster images. (like SVG, PDF, or PS)

option_scale_image() [source]

agg backend doesn't support arbitrary scaling of image.

points_to_pixels(points) [source]

convert point measures to pixes using dpi and the pixels per inch of the display

restore_region(region, bbox=None, xy=None) [source]

Restore the saved region. If bbox (instance of BboxBase, or its extents) is given, only the region specified by the bbox will be restored. xy (a tuple of two floasts) optionally specifies the new position (the LLC of the original region, not the LLC of the bbox) where the region will be restored.

>>> region = renderer.copy_from_bbox()
>>> x1, y1, x2, y2 = region.get_extents()
>>> renderer.restore_region(region, bbox=(x1+dx, y1, x2, y2),
...                         xy=(x1-dx, y1))

start_filter() [source]

Start filtering. It simply create a new canvas (the old one is saved).

stop_filter(post_processing) [source]

Save the plot in the current canvas as a image and apply the post_processing function.

def post_processing(image, dpi):

# ny, nx, depth = image.shape # image (numpy array) has RGBA channels and has a depth of 4. ... # create a new_image (numpy array of 4 channels, size can be # different). The resulting image may have offsets from # lower-left corner of the original image return new_image, offset_x, offset_y

The saved renderer is restored and the returned image from post_processing is plotted (using draw_image) on it.

tostring_argb() [source]

tostring_rgb() [source]

tostring_rgba_minimized() [source]

matplotlib.backends.backend_agg.get_hinting_flag() [source]