Plot Options

Plot options are given to viscid.plot.vpyplot.plot() as either keyword arguments, or as a string called plot_opts. For the various plot types, what follows should be a comprehensive list of the available options.

Note

For all options, supplying no arguments implies one argument with the value True.

Note

Any options that Viscid does not understand are passed to the matplotlib function that actually plots the data (pyplot.plot, pyplot.pcolormesh, pyplot.contourf, etc).

Multiple arguments are given to keywords as a tuple:

kwargs = {'lin': (-1.0, 1.0), 'gridec': 'k'}

All options can be passed as strings with one of two formats. First, the string can be a list of comma separated options with underscore separated arguments:

plot_opts = "lin_-1.0_1.0, gridec_k"
# also, any '=' will be substituted with a '_' to aid readability
plot_opts = "lin=-1.0_1.0, gridec=k"

If PyYaml is available, plot options can be given between curly brackets using Yaml syntax. Note that the colon must be followed by a space in Yaml syntax.

plot_opts = "{lin: [-1.0, 1.0], gridec: k}"

Known Issues

Since Viscid switched to using image axes by default, it has exposed some undesired behavior in matplotlib. Namely, if you call pyplot.tight_layout(), viscid.plot.vpyplot.tighten(), or viscid.plot.vpyplot.auto_adjust_subplots() more than once for a figure, then some of the subplots dissapear. The solution is to only call these functions once per figure.

Universal

Option	Arguments	Description
clim	vmin, [vmax]	Set min and max values for the data scale
vmin	int	Minimum value for the data range
vmax	int	Maximum value for the data range
lin	[vmin, [vmax]]	Shorthand for clim and logscale=0. Min/Max values that aren’t given are found from the data.
log	[vmin, [vmax]]	Shorthand for clim and logscale=1. Min/Max values that aren’t given are found from the data.
loglog	[vmin, [vmax]]	Same as log, but also use a logscale for the coordinates
logscale	[bool]	Use a logarithmic scale for the data
symmetric	[bool]	Make the data scale symmetric around 0
norescale	[bool]	Do not set limit of the data axis explicitly
x	min, max	Set axis limits using pyplot.set_xlim()
y	min, max	Set axis limits using pyplot.set_ylim()
axis	str	Arguments for pyplot.axis(). In viscid, this defaults to ‘image’ but can be anything accepted by matplotlib.pyplot.axis() or ‘none’ for no call to pyplot.axis(). See matplotlib docs for more info. This option can be used to force a 1:1 aspect ratio.
scale	float	Scale data by some scalar value
masknan	[bool or color]	Mask out NaN values in data with a given color (default: ‘y’ for yellow)
flipplot	[bool]	Alias for flip_plot
flip_plot	[bool]	Flip the horizontal and vertical axes
nolabels	[bool]	Skip applying labels to x/y/cbar axes
xlabel	str	Specific label for the x axis
ylabel	str	Specific label for the y axis
majorfmt	ticker.Formatter	Formatter for major axes (x and y)
minorfmt	ticker.Formatter	Formatter for minor axes (x and y)
majorloc	ticker.Locater	Locater for major axes (x and y)
minorloc	ticker.Locater	Locater for minor axes (x and y)
datefmt	str	date format string in the datetime.strftime format
timefmt	str	time format string in the datetime.strftime format (used for timedeltas)
autofmt_xdate	[bool]	auto-rotate date labels on the x-axis
autofmtxdate	[bool]	alias for autofmt_xdate
show	[bool]	Call pyplot.show() before returning

Note

When using lin, if vmin == 0 and vmax is not given, the scale will be symmetric about 0. This is a shorthand for the symmetric keyword argument.

2-D Plots

Option	Arguments	Description
style	str	One of (pcolormesh, pcolor, contour, contourf)
tightlim	bool	If True, then set axes limits to data limits
levels	[int or list]	Number of contours, or list of specific contour values (contours only)
g	[bool or color]	Alias for gridec=k or gridec=color
gridec	color	Color for grid lines (pcolormesh only)
gridlw	number	Line width for grid lines (pcolormesh only)
gridaa	[bool]	Antialias grid lines (default: True)
p	[bool or color]	Alias for patchec=k or patchec=color
patchec	color	Color for patch boundaries
patchlw	number	Line width for patch boundaries
patchaa	[bool]	Antialias patch boundaries (default: True)
mod	modx, mody	Scale coordinates by some scalar value
colorbar	bool	Automatically add a colorbar? Default is True
cax	mpl Axis	Explicit axis for colorbar, if drawn
cbar_kwargs	dict	keyword options for pyplot.colorbar. Handles the additional arguments ‘use_grid1’ for nicer cax creation, and ‘position’ which can be ‘left’, ‘right’, ‘top’ or ‘bottom’.
title	bool or str	Put a specific title on the plot, or if true, use field’s pretty_name (suppresses cbarlabel if both would default to pretty_name)
cbarlabel	str	Specific label for the color bar
earth	[bool]	Plot a black and white circle for Earth

2-D Map Plots

All options for normal 2-D plots work for map plots too.

Option	Arguments	Description
projection	str	‘polar’ or Basemap projection to use
hemisphere	str	‘north’ or ‘south’
drawcoastlines	[bool]	If projection is a basemap projection, then draw coastlines. Pretty cool, but not actually useful. Coastlines do NOT reflect UT time; London is always at midnight.
lon0	float	Center longitude (basemap projections only)
lat0	float	Center latitude (basemap projections only)
boundinglat	float	Bounding latitude in degrees from the nearest pole (not for all projections)
title	bool or str	Put a specific title on the plot, or if true, use field’s pretty_name
axgridec	color	Color for patch boundaries (use empty string or False to turn off axes)
axgridlw	number	Line width for patch boundaries
axgridls	str	Line style for patch boundaries
labellat	[bool or str]	Alias for label_lat
label_lat	[bool or str]	Label latitudes at 80, 70, 60 degrees with sign indicating northern / southern hemisphere. If label_lat is ‘from_pole’, then the labels are 10, 20, 30 for both hemispheres. Note that basemap projections won’t label latitudes unless they hit the edge of the plot.
label_mlt	[bool]	label magnetic local time

2-D Iono Plots

All options for normal 2-D and map plots apply too.

Option	Arguments	Description
annotations	str	‘pot’ annotates min/max/cpcp, others may be added in the future
units	str	units for annotations / title etc
fontsize	int	font size in points
titlescale	float	now much larger to make the title as a fraction (1.5 is 50% larger than annotations)

1-D Color Plots

Option	Arguments	Description
legend	[loc]	call pyplot.legend()
label	str	Label for the data series
mod	modx	Scale coordinates by some scalar value