Projections are defined as :None:None:`~.axes.Axes` subclasses. They include the following elements:
A transformation from data coordinates into display coordinates.
An inverse of that transformation. This is used, for example, to convert mouse positions from screen space back into data space.
Transformations for the gridlines, ticks and ticklabels. Custom projections will often need to place these elements in special locations, and Matplotlib has a facility to help with doing so.
Setting up default values (overriding :None:None:`~.axes.Axes.cla`), since the defaults for a rectilinear axes may not be appropriate.
Defining the shape of the axes, for example, an elliptical axes, that will be used to draw the background of the plot and for clipping any data elements.
Defining custom locators and formatters for the projection. For example, in a geographic projection, it may be more convenient to display the grid in degrees, even if the data is in radians.
Set up interactive panning and zooming. This is left as an "advanced" feature left to the reader, but there is an example of this for polar plots in matplotlib.projections.polar
.
Any additional methods for additional convenience or features.
Once the projection axes is defined, it can be used in one of two ways:
By defining the class attribute name
, the projection axes can be registered with matplotlib.projections.register_projection
and subsequently simply invoked by name:
fig.add_subplot(projection="my_proj_name")
For more complex, parameterisable projections, a generic "projection" object may be defined which includes the method _as_mpl_axes
. _as_mpl_axes
should take no arguments and return the projection's axes subclass and a dictionary of additional arguments to pass to the subclass' __init__
method. Subsequently a parameterised projection can be initialised with:
fig.add_subplot(projection=MyProjection(param1=param1_value))
where MyProjection is an object which implements a _as_mpl_axes
method.
A full-fledged and heavily annotated example is in /gallery/misc/custom_projection
. The polar plot functionality in matplotlib.projections.polar
may also be of interest.
Non-separable transforms that map from data space to screen space.
Non-separable transforms that map from data space to screen space.
Projections are defined as :None:None:`~.axes.Axes` subclasses. They include the following elements:
A transformation from data coordinates into display coordinates.
An inverse of that transformation. This is used, for example, to convert mouse positions from screen space back into data space.
Transformations for the gridlines, ticks and ticklabels. Custom projections will often need to place these elements in special locations, and Matplotlib has a facility to help with doing so.
Setting up default values (overriding :None:None:`~.axes.Axes.cla`), since the defaults for a rectilinear axes may not be appropriate.
Defining the shape of the axes, for example, an elliptical axes, that will be used to draw the background of the plot and for clipping any data elements.
Defining custom locators and formatters for the projection. For example, in a geographic projection, it may be more convenient to display the grid in degrees, even if the data is in radians.
Set up interactive panning and zooming. This is left as an "advanced" feature left to the reader, but there is an example of this for polar plots in matplotlib.projections.polar
.
Any additional methods for additional convenience or features.
Once the projection axes is defined, it can be used in one of two ways:
By defining the class attribute name
, the projection axes can be registered with matplotlib.projections.register_projection
and subsequently simply invoked by name:
fig.add_subplot(projection="my_proj_name")
For more complex, parameterisable projections, a generic "projection" object may be defined which includes the method _as_mpl_axes
. _as_mpl_axes
should take no arguments and return the projection's axes subclass and a dictionary of additional arguments to pass to the subclass' __init__
method. Subsequently a parameterised projection can be initialised with:
fig.add_subplot(projection=MyProjection(param1=param1_value))
where MyProjection is an object which implements a _as_mpl_axes
method.
A full-fledged and heavily annotated example is in /gallery/misc/custom_projection
. The polar plot functionality in matplotlib.projections.polar
may also be of interest.
The following pages refer to to this document either explicitly or contain code examples using this.
matplotlib.scale
matplotlib.pyplot.axes
matplotlib.figure.FigureBase.add_subplot
matplotlib.figure.FigureBase.add_axes
matplotlib.pyplot.subplot
Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.
Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)
SVG is more flexible but power hungry; and does not scale well to 50 + nodes.
All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them