MplRegion#
- class discretisedfield.plotting.MplRegion(region)#
Methods
matplotlib
plot.__dir__
Default dir() implementation.
__eq__
Return self==value.
__repr__
Return repr(self).
- __call__(*, ax=None, figsize=None, multiplier=None, color='#4c72b0', box_aspect='auto', filename=None, **kwargs)#
matplotlib
plot.If
ax
is not passed,matplotlib.axes.Axes
object is created automatically and the size of a figure can be specified usingfigsize
. The colour of lines depicting the region can be specified usingcolor
argument, which must be a validmatplotlib
color. The plot is saved in PDF-format iffilename
is passed.It is often the case that the object size is either small (e.g. on a nanoscale) or very large (e.g. in units of kilometers). Accordingly,
multiplier
can be passed as \(10^{n}\), where \(n\) is a multiple of 3 (…, -6, -3, 0, 3, 6,…). According to that value, the axes will be scaled and appropriate units shown. For instance, ifmultiplier=1e-9
is passed, all axes will be divided by \(1\,\text{nm}\) and \(\text{nm}\) units will be used as axis labels. Ifmultiplier
is not passed, the best one is calculated internally.This method is based on
matplotlib.pyplot.plot
, so any keyword arguments accepted by it can be passed (for instance,linewidth
,linestyle
, etc.).- Parameters:
ax (matplotlib.axes.Axes, optional) – Axes to which the plot is added. Defaults to
None
- axes are created internally.figsize ((2,) tuple, optional) – The size of a created figure if
ax
is not passed. Defaults toNone
.color (int, str, tuple, optional) – A valid
matplotlib
color for lines depicting the region. Defaults to the default color palette.multiplier (numbers.Real, optional) – Axes multiplier. Defaults to
None
.box_aspect (str, array_like (3), optional) – Set the aspect-ratio of the plot. If set to ‘auto’ the aspect ratio is determined from the edge lengths of the region. To set different aspect ratios a tuple can be passed. Defaults to
'auto'
.filename (str, optional) – If filename is passed, the plot is saved. Defaults to
None
.
Examples
Visualising the region using
matplotlib
.
>>> import discretisedfield as df ... >>> p1 = (-50e-9, -50e-9, 0) >>> p2 = (50e-9, 50e-9, 10e-9) >>> region = df.Region(p1=p1, p2=p2) >>> region.mpl()