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)

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(self)

Get the image as a memoryview to the renderer's buffer.

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:

memoryview

copy_from_bbox(self, bbox)

draw(self)

Draw the figure using the renderer.

get_renderer(self, cleared=False)

print_jpeg(self, filename_or_obj, *args, dryrun=False, pil_kwargs=None, **kwargs)

Write the figure to a JPEG file.

Parameters:

filename_or_obj : str or PathLike or file-like object

The file to write to.

Other Parameters:

quality : int

The image quality, on a scale from 1 (worst) to 100 (best). The default is rcParams["savefig.jpeg_quality"] (default: 95). 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.

pil_kwargs : dict, optional

Additional keyword arguments that are passed to PIL.Image.save when saving the figure. These take precedence over quality, optimize and progressive.

print_jpg(self, filename_or_obj, *args, dryrun=False, pil_kwargs=None, **kwargs)

Write the figure to a JPEG file.

Parameters:

filename_or_obj : str or PathLike or file-like object

The file to write to.

Other Parameters:

quality : int

The image quality, on a scale from 1 (worst) to 100 (best). The default is rcParams["savefig.jpeg_quality"] (default: 95). 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.

pil_kwargs : dict, optional

Additional keyword arguments that are passed to PIL.Image.save when saving the figure. These take precedence over quality, optimize and progressive.

print_png(self, filename_or_obj, *args, metadata=None, pil_kwargs=None, **kwargs)

Write the figure to a PNG file.

Parameters:

filename_or_obj : str or PathLike or file-like object

The file to write to.

metadata : dict, optional

Metadata in the PNG file as key-value pairs of bytes or latin-1 encodable strings. According to the PNG specification, keys must be shorter than 79 chars.

The PNG specification defines some common keywords that may be used as appropriate:

• Title: Short (one line) title or caption for image.
• Author: Name of image's creator.
• Description: Description of image (possibly long).
• Copyright: Copyright notice.
• Creation Time: Time of original image creation (usually RFC 1123 format).
• Software: Software used to create the image.
• Disclaimer: Legal disclaimer.
• Warning: Warning of nature of content.
• Source: Device used to create the image.
• Comment: Miscellaneous comment; conversion from other image format.

Other keywords may be invented for other purposes.

If 'Software' is not given, an autogenerated value for matplotlib will be used.

For more details see the PNG specification.

pil_kwargs : dict, optional

If set to a non-None value, use Pillow to save the figure instead of Matplotlib's builtin PNG support, and pass these keyword arguments to PIL.Image.save.

If the 'pnginfo' key is present, it completely overrides metadata, including the default 'Software' key.

print_raw(self, filename_or_obj, *args, **kwargs)

print_rgba(self, filename_or_obj, *args, **kwargs)

print_tif(self, filename_or_obj, *args, dryrun=False, pil_kwargs=None, **kwargs)

print_tiff(self, filename_or_obj, *args, dryrun=False, pil_kwargs=None, **kwargs)

print_to_buffer(self)

restore_region(self, region, bbox=None, xy=None)

tostring_argb(self)

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(self)

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)

Bases: matplotlib.backend_bases.RendererBase

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

buffer_rgba(self)

clear(self)

draw_mathtext(self, gc, x, y, s, prop, angle)

Draw the math text using matplotlib.mathtext

draw_path(self, gc, path, transform, rgbFace=None)

Draws a Path instance using the given affine transform.

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

draw_text(self, gc, x, y, s, prop, angle, ismath=False, mtext=None)

Draw the text instance.

Parameters:

gc : GraphicsContextBase

The graphics context.

x : scalar

The x location of the text in display coords.

y : scalar

The y location of the text baseline in display coords.

s : str

The text string.

prop : matplotlib.font_manager.FontProperties

The font properties.

angle : scalar

The rotation angle in degrees.

mtext : matplotlib.text.Text

The original text object to be rendered.

Notes

backend implementers note

When you are trying to determine if you have gotten your bounding box right (which is what enables the text layout/alignment to work properly), it helps to change the line in text.py:

if 0: bbox_artist(self, renderer)

to if 1, and then the actual bounding box will be plotted along with your text.

get_canvas_width_height(self)

Return the canvas width and height in display coords.

get_text_width_height_descent(self, s, prop, ismath)

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(self)

Return whether image composition by Matplotlib should be skipped.

Raster backends should usually return False (letting the C-level rasterizer take care of image composition); vector backends should usually return not rcParams["image.composite_image"].

option_scale_image(self)

Return whether arbitrary affine transformations in draw_image() are supported (True for most vector backends).

points_to_pixels(self, points)

Convert points to display units.

You need to override this function (unless your backend doesn't have a dpi, e.g., postscript or svg). Some imaging systems assume some value for pixels per inch:

points to pixels = points * pixels_per_inch/72.0 * dpi/72.0

Parameters:

points : scalar or array_like

a float or a numpy array of float

Returns:

Points converted to pixels

restore_region(self, region, bbox=None, xy=None)

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 pair of floats) 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(self)

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

stop_filter(self, post_processing)

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(self)

tostring_rgb(self)

tostring_rgba_minimized(self)

matplotlib.backends.backend_agg.get_hinting_flag()