mpl.ticker¶

Default Formatter¶

The default formatter identifies when the x-data being plotted is a small range on top of a large off set. To reduce the chances that the ticklabels overlap the ticks are labeled as deltas from a fixed offset. For example:

ax.plot(np.arange(2000, 2010), range(10))

will have tick of 0-9 with an offset of +2e3. If this is not desired turn off the use of the offset on the default formatter:

ax.get_xaxis().get_major_formatter().set_useOffset(False)

set the rcParam axes.formatter.useoffset=False to turn it off globally, or set a different formatter.

Tick locating¶

The Locator class is the base class for all tick locators. The locators handle autoscaling of the view limits based on the data limits, and the choosing of tick locations. A useful semi-automatic tick locator is MultipleLocator. You initialize this with a base, e.g., 10, and it picks axis limits and ticks that are multiples of your base.

The Locator subclasses defined here are

NullLocator

No ticks

FixedLocator

Tick locations are fixed

IndexLocator

locator for index plots (e.g., where x = range(len(y)))

LinearLocator

evenly spaced ticks from min to max

LogLocator

logarithmically ticks from min to max

SymmetricalLogLocator

locator for use with with the symlog norm, works like the LogLocator for the part outside of the threshold and add 0 if inside the limits

MultipleLocator

ticks and range are a multiple of base;

either integer or float

OldAutoLocator

choose a MultipleLocator and dyamically reassign it for intelligent ticking during navigation

MaxNLocator

finds up to a max number of ticks at nice locations

AutoLocator

MaxNLocator with simple defaults. This is the default tick locator for most plotting.

AutoMinorLocator

locator for minor ticks when the axis is linear and the major ticks are uniformly spaced. It subdivides the major tick interval into a specified number of minor intervals, defaulting to 4 or 5 depending on the major interval.

There are a number of locators specialized for date locations - see the dates module

You can define your own locator by deriving from Locator. You must override the __call__ method, which returns a sequence of locations, and you will probably want to override the autoscale method to set the view limits from the data limits.

If you want to override the default locator, use one of the above or a custom locator and pass it to the x or y axis instance. The relevant methods are:

ax.xaxis.set_major_locator( xmajorLocator )
ax.xaxis.set_minor_locator( xminorLocator )
ax.yaxis.set_major_locator( ymajorLocator )
ax.yaxis.set_minor_locator( yminorLocator )

The default minor locator is the NullLocator, e.g., no minor ticks on by default.

Tick formatting¶

Tick formatting is controlled by classes derived from Formatter. The formatter operates on a single tick value and returns a string to the axis.

NullFormatter

no labels on the ticks

IndexFormatter

set the strings from a list of labels

FixedFormatter

set the strings manually for the labels

FuncFormatter

user defined function sets the labels

StrMethodFormatter

Use string format method

FormatStrFormatter

use a sprintf format string

ScalarFormatter

default formatter for scalars; autopick the fmt string

LogFormatter

formatter for log axes

You can derive your own formatter from the Formatter base class by simply overriding the __call__ method. The formatter class has access to the axis view and data limits.

To control the major and minor tick label formats, use one of the following methods:

ax.xaxis.set_major_formatter( xmajorFormatter )
ax.xaxis.set_minor_formatter( xminorFormatter )
ax.yaxis.set_major_formatter( ymajorFormatter )
ax.yaxis.set_minor_formatter( yminorFormatter )

See pylab_examples-major_minor_demo1 for an example of setting major and minor ticks. See the matplotlib.dates module for more information and examples of using date locators and formatters.

Functions¶

Classes¶