""" Drawing and plotting routines for igraph. IGraph has two stable plotting backends at the moment: Cairo and Matplotlib. It also has experimental support for plotly. The Cairo backend is dependent on the C{pycairo} or C{cairocffi} libraries that provide Python bindings to the popular U{Cairo library}. This means that if you don't have U{pycairo} or U{cairocffi} installed, you won't be able to use the Cairo plotting backend. Whenever the documentation refers to the C{pycairo} library, you can safely replace it with C{cairocffi} as the two are API-compatible. The Matplotlib backend uses the U{Matplotlib library}. You will need to install it from PyPI if you want to use the Matplotlib plotting backend. Many of our gallery examples use the matplotlib backend. The plotly backend uses the U{plotly library } and, like matplotlib, requires installation from PyPI. If you do not want to (or cannot) install any of the dependencies outlined above, you can still save the graph to an SVG file and view it from U{Mozilla Firefox} (free) or edit it in U{Inkscape} (free), U{Skencil} (formerly known as Sketch, also free) or Adobe Illustrator. """ from pathlib import Path from warnings import warn from igraph.configuration import Configuration from igraph.drawing.cairo.utils import find_cairo from igraph.drawing.matplotlib.utils import find_matplotlib from igraph.drawing.plotly.utils import find_plotly from igraph.drawing.cairo.plot import CairoPlot from igraph.drawing.colors import Palette, palettes from igraph.drawing.cairo.graph import CairoGraphDrawer from igraph.drawing.cairo.matrix import CairoMatrixDrawer from igraph.drawing.cairo.histogram import CairoHistogramDrawer from igraph.drawing.cairo.palette import CairoPaletteDrawer from igraph.drawing.matplotlib.graph import MatplotlibGraphDrawer from igraph.drawing.matplotlib.matrix import MatplotlibMatrixDrawer from igraph.drawing.matplotlib.histogram import MatplotlibHistogramDrawer from igraph.drawing.matplotlib.palette import MatplotlibPaletteDrawer from igraph.drawing.plotly.graph import PlotlyGraphDrawer from igraph.drawing.utils import BoundingBox, Point, Rectangle from igraph.utils import _is_running_in_ipython __all__ = ( "BoundingBox", "CairoGraphDrawer", "MatplotlibGraphDrawer", "DefaultGraphDrawer", "Plot", "Point", "Rectangle", "plot", "DrawerDirectory", ) # TODO: deprecate Plot = CairoPlot # TODO: deprecate DefaultGraphDrawer = CairoGraphDrawer class DrawerDirectory: """Static class that finds the object/backend drawer This directory is used by the __plot__ functions. """ valid_backends = ("cairo", "matplotlib") valid_objects = ( "Graph", "Matrix", "Histogram", "Palette", ) known_drawers = { "cairo": { "Graph": CairoGraphDrawer, "Matrix": CairoMatrixDrawer, "Histogram": CairoHistogramDrawer, "Palette": CairoPaletteDrawer, }, "matplotlib": { "Graph": MatplotlibGraphDrawer, "Matrix": MatplotlibMatrixDrawer, "Histogram": MatplotlibHistogramDrawer, "Palette": MatplotlibPaletteDrawer, }, "plotly": { "Graph": PlotlyGraphDrawer, }, } @classmethod def resolve(cls, obj, backend): """Given a shape name, returns the corresponding shape drawer class @param cls: the class to resolve @param obj: an instance of the object to plot @param backend: the name of the backend @return: the corresponding shape drawer class @raise ValueError: if no drawer is available for this backend/object """ object_name = str(obj.__class__).split(".")[-1].strip("<'>") try: return cls.known_drawers[backend][object_name] except KeyError: raise ValueError( f"unknown drawer for {object_name} and backend {backend}", ) def plot(obj, target=None, bbox=(0, 0, 600, 600), *args, **kwds): """Plots the given object to the given target. Positional and keyword arguments not explicitly mentioned here will be passed down to the C{__plot__} method of the object being plotted. Since you are most likely interested in the keyword arguments available for graph plots, see L{Graph.__plot__} as well. @param obj: the object to be plotted @param target: the target where the object should be plotted. It can be one of the following types: - C{matplotib.axes.Axes} -- a matplotlib/pyplot axes in which the graph will be plotted. Drawing is delegated to the chosen matplotlib backend, and you can use interactive backends and matplotlib functions to save to file as well. - C{string} -- a file with the given name will be created and the plot will be stored there. If you are using the Cairo backend, an appropriate Cairo surface will be attached to the file. If you are using the matplotlib backend, the Figure will be saved to that file using Figure.savefig with default parameters. The supported image formats for Cairo are: PNG, PDF, SVG and PostScript; matplotlib might support additional formats. - C{cairo.Surface} -- the given Cairo surface will be used. This can refer to a PNG image, an arbitrary window, an SVG file, anything that Cairo can handle. - C{None} -- If you are using the Cairo backend, no plotting will be performed; igraph simply returns a CairoPlot_ object that you can use to manipulate the plot and save it to a file later. If you are using the matplotlib backend, a Figure objet and an Axes are created and the Axes is returned so you can manipulate it further. Similarly, if you are using the plotly backend, a Figure object is returned. @param bbox: the bounding box of the plot. It must be a tuple with either two or four integers, or a L{BoundingBox} object. If this is a tuple with two integers, it is interpreted as the width and height of the plot (in pixels for PNG images and on-screen plots, or in points for PDF, SVG and PostScript plots, where 72 pt = 1 inch = 2.54 cm). If this is a tuple with four integers, the first two denotes the X and Y coordinates of a corner and the latter two denoting the X and Y coordinates of the opposite corner. Ignored for Matplotlib plots. @keyword opacity: the opacity of the object being plotted. It can be used to overlap several plots of the same graph if you use the same layout for them -- for instance, you might plot a graph with opacity 0.5 and then plot its spanning tree over it with opacity 0.1. To achieve this, you'll need to modify the L{Plot} object returned with L{Plot.add}. Ignored for Matplotlib plots. @keyword palette: the palette primarily used on the plot if the added objects do not specify a private palette. Must be either an L{igraph.drawing.colors.Palette} object or a string referring to a valid key of C{igraph.drawing.colors.palettes} (see module L{igraph.drawing.colors}) or C{None}. In the latter case, the default palette given by the configuration key C{plotting.palette} is used. @keyword margin: the top, right, bottom, left margins as a 4-tuple. If it has less than 4 elements or is a single float, the elements will be re-used until the length is at least 4. The default margin is 20 units on each side. Ignored for Matplotlib plots. @keyword inline: whether to try and show the plot object inline in the current IPython notebook. Passing C{None} here or omitting this keyword argument will look up the preferred behaviour from the C{shell.ipython.inlining.Plot} configuration key. Note that this keyword argument has an effect only if igraph is run inside IPython and C{target} is C{None}. @return: an appropriate L{CairoPlot} object for the Cairo backend, the Matplotlib C{Axes} object for the Matplotlib backend, and the C{Figure} object for the plotly backend. @see: Graph.__plot__ """ VALID_BACKENDS = ("cairo", "matplotlib", "plotly") _, plt = find_matplotlib() cairo = find_cairo() plotly = find_plotly() # Switch backend based on target (first) and config (second) if hasattr(plt, "Axes") and isinstance(target, plt.Axes): backend = "matplotlib" elif hasattr(plotly, "graph_objects") and isinstance( target, plotly.graph_objects.Figure ): backend = "plotly" elif hasattr(cairo, "Surface") and isinstance(target, cairo.Surface): backend = "cairo" else: backend = Configuration.instance()["plotting.backend"] if backend not in VALID_BACKENDS: raise ValueError("unknown plotting backend: {0!r}".format(backend)) if backend in ("matplotlib", "plotly"): # Choose palette # If explicit, use it. If not or None, ask the object: None is an # acceptable response from the object (e.g. for clusterings), it means # the palette is handled internally. If no response, default to config. palette = kwds.pop("palette", None) if palette is None: palette = getattr( obj, "_default_palette", Configuration.instance()["plotting.palette"], ) if palette is not None and not isinstance(palette, Palette): palette = palettes[palette] if isinstance(target, (str, Path)): save_path = str(target) target = None else: save_path = None if target is None: if backend == "matplotlib": # Create a new axes if needed _, target = plt.subplots() elif backend == "plotly": # Create a new figure if needed target = plotly.graph_objects.Figure() # Get the plotting function from the object plotter = getattr(obj, "__plot__", None) if plotter is None: warn("%s does not support plotting" % (obj,)) return else: plotter( backend, target, palette=palette, *args, **kwds, ) if save_path is not None: if backend == "matplotlib": target.figure.savefig(save_path) elif backend == "plotly": target.write_image(save_path) return target # Cairo backend inline = False if target is None and _is_running_in_ipython(): inline = kwds.get("inline") if inline is None: inline = Configuration.instance()["shell.ipython.inlining.Plot"] palette = kwds.pop("palette", None) background = kwds.pop("background", "white") margin = float(kwds.pop("margin", 20)) result = CairoPlot( target=target, bbox=bbox, palette=palette, background=background, ) item_bbox = result.bbox.contract(margin) result.add(obj, item_bbox, *args, **kwds) # If we requested an inline plot, just return the result and IPython will # call its _repr_svg_ method. If we requested a non-inline plot, show the # plot in a separate window and return nothing if inline: return result # We are either not in IPython or the user specified an explicit plot target, # so just show or save the result if isinstance(target, (str, Path)): # save result.save() # Also return the plot itself return result