Default Formatter¶

The default formatter identifies when the x-data beingplotted is a small range on top of a large off set. Toreduce the chances that the ticklabels overlap the ticksare 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 thisis not desired turn off the use of the offset on the defaultformatter:

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

set the rcParamaxes.formatter.useoffset=False to turn it offglobally, or set a different formatter.

Tick locating¶

The Locator class is the base class for all tick locators. The locatorshandle autoscaling of the view limits based on the data limits, and thechoosing of tick locations. A useful semi-automatic tick locator isMultipleLocator. You initialize this with a base, e.g., 10, and itpicks 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 theLogLocator for the part outside of the threshold and add 0 ifinside the limits

MultipleLocator

ticks and range are a multiple of base;

either integer or float

OldAutoLocator

choose a MultipleLocator and dyamically reassign it forintelligent ticking during navigation

MaxNLocator

finds up to a max number of ticks at nice locations

AutoLocator

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

AutoMinorLocator

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

LogitLocator

Locator for logit scaling.

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

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

If you want to override the default locator, use one of the above or acustom locator and pass it to the x or y axis instance. The relevantmethods 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 bydefault.

Tick formatting¶

Tick formatting is controlled by classes derived from Formatter. Theformatter operates on a single tick value and returns a string to theaxis.

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 stringformat method

FormatStrFormatter

Use an old-style sprintf format string

ScalarFormatter

Default formatter for scalars: autopick the format string

LogFormatter

Formatter for log axes

LogFormatterExponent

Format values for log axis usingexponent=log_base(value).

LogFormatterMathtext

Format values for log axis usingexponent=log_base(value)using Math text.

LogFormatterSciNotation

Format values for log axis using scientific notation.

LogitFormatter

Probability formatter.

You can derive your own formatter from the Formatter base class bysimply overriding the__call__ method. The formatter class hasaccess to the axis view and data limits.

To control the major and minor tick label formats, use one of thefollowing 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)

Seepylab_examples example code: major_minor_demo1.py for an example of settingmajor and minor ticks. See thematplotlib.dates module formore information and examples of using date locators and formatters.

classmatplotlib.ticker.TickHelper¶

Bases:object

axis = None¶

create_dummy_axis(**kwargs)¶

set_axis(axis)¶

set_bounds(vmin,vmax)¶

set_data_interval(vmin,vmax)¶

set_view_interval(vmin,vmax)¶

classmatplotlib.ticker.Formatter¶

Bases:matplotlib.ticker.TickHelper

Create a string based on a tick value and location.

fix_minus(s)¶

Some classes may want to replace a hyphen for minus with theproper unicode symbol (U+2212) for typographical correctness.The default is to not replace it.

Note, if you use this method, e.g., informat_data() orcall, you probably don’t want to use it forformat_data_short() since the toolbar uses this forinteractive coord reporting and I doubt we can expect GUIsacross platforms will handle the unicode correctly. So fornow the classes that overridefix_minus() should have anexplicitformat_data_short() method

format_data(value)¶

Returns the full string representation of the value with theposition unspecified.

format_data_short(value)¶

Return a short string version of the tick value.

Defaults to the position-independent long value.

get_offset()¶

locs = []¶

set_locs(locs)¶

classmatplotlib.ticker.FixedFormatter(seq)¶

Bases:matplotlib.ticker.Formatter

Return fixed strings for tick labels based only on position, notvalue.

Set the sequence of strings that will be used for labels.

get_offset()¶

set_offset_string(ofs)¶

classmatplotlib.ticker.NullFormatter¶

Bases:matplotlib.ticker.Formatter

Always return the empty string.

classmatplotlib.ticker.FuncFormatter(func)¶

Bases:matplotlib.ticker.Formatter

Use a user-defined function for formatting.

The function should take in two inputs (a tick valuex and apositionpos), and return a string containing the correspondingtick label.

classmatplotlib.ticker.FormatStrFormatter(fmt)¶

Bases:matplotlib.ticker.Formatter

Use an old-style (‘%’ operator) format string to format the tick.

The format string should have a single variable format (%) in it.It will be applied to the value (not the position) of the tick.

classmatplotlib.ticker.StrMethodFormatter(fmt)¶

Bases:matplotlib.ticker.Formatter

Use a new-style format string (as used bystr.format())to format the tick.

The field used for the value must be labeledx and the field usedfor the position must be labeledpos.

classmatplotlib.ticker.ScalarFormatter(useOffset=None,useMathText=None,useLocale=None)¶

Bases:matplotlib.ticker.Formatter

Format tick values as a number.

Tick value is interpreted as a plain old number. IfuseOffset==True and the data range is much smaller than the dataaverage, then an offset will be determined such that the tick labelsare meaningful. Scientific notation is used fordata<10^-n ordata>=10^m, wheren andm are the power limits setusingset_powerlimits((n,m)). The defaults for these arecontrolled by theaxes.formatter.limits rc parameter.

fix_minus(s)¶

Replace hyphens with a unicode minus.

format_data(value)¶

Return a formatted string representation of a number.

format_data_short(value)¶

Return a short formatted string representation of a number.

get_offset()¶

Return scientific notation, plus offset.

get_useLocale()¶

get_useOffset()¶

pprint_val(x)¶

set_locs(locs)¶

Set the locations of the ticks.

set_powerlimits(lims)¶

Sets size thresholds for scientific notation.

lims is a two-element sequence containing the powers of 10that determine the switchover threshold. Numbers below10**lims[0] and above10**lims[1] will be displayed inscientific notation.

For example,formatter.set_powerlimits((-3,4)) sets thepre-2007 default in which scientific notation is used fornumbers less than 1e-3 or greater than 1e4.

See also

Methodset_scientific()

set_scientific(b)¶

Turn scientific notation on or off.

See also

Methodset_powerlimits()

set_useLocale(val)¶

set_useOffset(val)¶

useLocale¶

useOffset¶

classmatplotlib.ticker.LogFormatter(base=10.0,labelOnlyBase=False,minor_thresholds=None,linthresh=None)¶

Bases:matplotlib.ticker.Formatter

Base class for formatting ticks on a log or symlog scale.

It may be instantiated directly, or subclassed.

Parameters:

base : float, optional, default: 10. Base of the logarithm used in all calculations. labelOnlyBase : bool, optional, default: False If True, label ticks only at integer powers of base.This is normally True for major ticks and False forminor ticks. minor_thresholds : (subset, all), optional, default: (1, 0.4) If labelOnlyBase is False, these two numbers controlthe labeling of ticks that are not at integer powers ofbase; normally these are the minor ticks. The controllingparameter is the log of the axis data range. In the typicalcase where base is 10 it is the number of decades spannedby the axis, so we can call it ‘numdec’. Ifnumdec<=all,all minor ticks will be labeled. Ifall<numdec<=subset,then only a subset of minor ticks will be labeled, so as toavoid crowding. Ifnumdec>subset then no minor ticks willbe labeled. linthresh : None or float, optional, default: None If a symmetric log scale is in use, itslinthreshparameter must be supplied here.

Notes

Theset_locs method must be called to enable the subsettinglogic controlled by theminor_thresholds parameter.

In some cases such as the colorbar, there is no distinction betweenmajor and minor ticks; the tick locations might be set manually,or by a locator that puts ticks at integer powers of base andat intermediate locations. For this situation, disable theminor_thresholds logic by usingminor_thresholds=(np.inf,np.inf),so that all ticks will be labeled.

To disable labeling of minor ticks when ‘labelOnlyBase’ is False,useminor_thresholds=(0,0). This is the default for the“classic” style.

Examples

To label a subset of minor ticks when the view limits span upto 2 decades, and all of the ticks when zoomed in to 0.5 decadesor less, useminor_thresholds=(2,0.5).

To label all minor ticks when the view limits span up to 1.5decades, useminor_thresholds=(1.5,1.5).

base(base)¶

change thebase for labeling.

Warning

Should always match the base used forLogLocator

format_data(value)¶

format_data_short(value)¶

Return a short formatted string representation of a number.

label_minor(labelOnlyBase)¶

Switch minor tick labeling on or off.

Parameters:	labelOnlyBase : bool If True, label ticks only at integer powers of base.

pprint_val(x,d)¶

set_locs(locs=None)¶

Use axis view limits to control which ticks are labeled.

Thelocs parameter is ignored in the present algorithm.

classmatplotlib.ticker.LogFormatterExponent(base=10.0,labelOnlyBase=False,minor_thresholds=None,linthresh=None)¶

Bases:matplotlib.ticker.LogFormatter

Format values for log axis usingexponent=log_base(value).

classmatplotlib.ticker.LogFormatterMathtext(base=10.0,labelOnlyBase=False,minor_thresholds=None,linthresh=None)¶

Bases:matplotlib.ticker.LogFormatter

Format values for log axis usingexponent=log_base(value).

classmatplotlib.ticker.Locator¶

Bases:matplotlib.ticker.TickHelper

Determine the tick locations;

Note, you should not use the same locator between differentAxis because the locator stores references tothe Axis data and view limits

MAXTICKS = 1000¶

autoscale()¶

autoscale the view limits

pan(numsteps)¶

Pan numticks (can be positive or negative)

raise_if_exceeds(locs)¶

raise a RuntimeError if Locator attempts to create more thanMAXTICKS locs

refresh()¶

refresh internal information based on current lim

set_params(**kwargs)¶

Do nothing, and rase a warning. Any locator class not supporting theset_params() function will call this.

tick_values(vmin,vmax)¶

Return the values of the located ticks givenvmin andvmax.

Note

To get tick locations with the vmin and vmax values definedautomatically for the associatedaxis simply callthe Locator instance:

>>>print((type(loc)))<type 'Locator'>>>>print((loc()))[1, 2, 3, 4]

view_limits(vmin,vmax)¶

select a scale for the range from vmin to vmax

Normally this method is overridden by subclasses tochange locator behaviour.

zoom(direction)¶

Zoom in/out on axis; if direction is >0 zoom in, else zoom out

classmatplotlib.ticker.IndexLocator(base,offset)¶

Bases:matplotlib.ticker.Locator

Place a tick on every multiple of some base number of pointsplotted, e.g., on every 5th point. It is assumed that you are doingindex plotting; i.e., the axis is 0, len(data). This is mainlyuseful for x ticks.

place ticks on the i-th data points where (i-offset)%base==0

set_params(base=None,offset=None)¶

Set parameters within this locator

tick_values(vmin,vmax)¶

classmatplotlib.ticker.FixedLocator(locs,nbins=None)¶

Bases:matplotlib.ticker.Locator

Tick locations are fixed. If nbins is not None,the array of possible positions will be subsampled tokeep the number of ticks <= nbins +1.The subsampling will be done so as to include the smallestabsolute value; for example, if zero is included in thearray of possibilities, then it is guaranteed to be one ofthe chosen ticks.

set_params(nbins=None)¶

Set parameters within this locator.

tick_values(vmin,vmax)¶

”Return the locations of the ticks.

Note

Because the values are fixed, vmin and vmax are not used in thismethod.

classmatplotlib.ticker.NullLocator¶

Bases:matplotlib.ticker.Locator

No ticks

tick_values(vmin,vmax)¶

”Return the locations of the ticks.

Note

Because the values are Null, vmin and vmax are not used in thismethod.

classmatplotlib.ticker.LinearLocator(numticks=None,presets=None)¶

Bases:matplotlib.ticker.Locator

Determine the tick locations

The first time this function is called it will try to set thenumber of ticks to make a nice tick partitioning. Thereafter thenumber of ticks will be fixed so that interactive navigation willbe nice

Use presets to set locs based on lom. A dict mapping vmin, vmax->locs

set_params(numticks=None,presets=None)¶

Set parameters within this locator.

tick_values(vmin,vmax)¶

view_limits(vmin,vmax)¶

Try to choose the view limits intelligently

classmatplotlib.ticker.LogLocator(base=10.0,subs=(1.0,),numdecs=4,numticks=None)¶

Bases:matplotlib.ticker.Locator

Determine the tick locations for log axes

Place ticks on the locations : subs[j] * base**i

Parameters:

subs : None, string, or sequence of float, optional, default (1.0,) Gives the multiples of integer powers of the base at whichto place ticks. The default places ticks only atinteger powers of the base.The permitted string values are'auto' and'all',both of which use an algorithm based on the axis viewlimits to determine whether and how to put ticks betweeninteger powers of the base. With'auto', ticks areplaced only between integer powers; with'all', theinteger powers are included. A value of None isequivalent to'auto'.

base(base)¶

set the base of the log scaling (major tick every base**i, i integer)

nonsingular(vmin,vmax)¶

set_params(base=None,subs=None,numdecs=None,numticks=None)¶

Set parameters within this locator.

subs(subs)¶

set the minor ticks for the log scaling every base**i*subs[j]

tick_values(vmin,vmax)¶

view_limits(vmin,vmax)¶

Try to choose the view limits intelligently

classmatplotlib.ticker.AutoLocator¶

Bases:matplotlib.ticker.MaxNLocator

classmatplotlib.ticker.MultipleLocator(base=1.0)¶

Bases:matplotlib.ticker.Locator

Set a tick on every integer that is multiple of base in theview interval

set_params(base)¶

Set parameters within this locator.

tick_values(vmin,vmax)¶

view_limits(dmin,dmax)¶

Set the view limits to the nearest multiples of base thatcontain the data

classmatplotlib.ticker.MaxNLocator(*args,**kwargs)¶

Bases:matplotlib.ticker.Locator

Select no more than N intervals at nice locations.

Keyword args:

nbins

Maximum number of intervals; one less than max number ofticks. If the string'auto', the number of bins will beautomatically determined based on the length of the axis.

steps

Sequence of nice numbers starting with 1 and ending with 10;e.g., [1, 2, 4, 5, 10]

integer

If True, ticks will take only integer values, providedat leastmin_n_ticks integers are found within theview limits.

symmetric

If True, autoscaling will result in a range symmetricabout zero.

prune

[‘lower’ | ‘upper’ | ‘both’ | None]Remove edge ticks – useful for stacked or ganged plotswhere the upper tick of one axes overlaps with the lowertick of the axes above it, primarily whenrcParams['axes.autolimit_mode'] is'round_numbers'.Ifprune=='lower', the smallest tick willbe removed. Ifprune=='upper', the largest tick will beremoved. Ifprune=='both', the largest and smallest tickswill be removed. Ifprune==None, no ticks will be removed.

min_n_ticks

Relaxnbins andinteger constraints if necessary toobtain this minimum number of ticks.

bin_boundaries(vmin,vmax)¶

Deprecated since version 2.0:The bin_boundaries function was deprecated in version 2.0.

default_params = {'nbins': 10, 'steps': None, 'integer': False, 'symmetric': False, 'prune': None, 'min_n_ticks': 2}¶

set_params(**kwargs)¶

Set parameters within this locator.

tick_values(vmin,vmax)¶

view_limits(dmin,dmax)¶

classmatplotlib.ticker.AutoMinorLocator(n=None)¶

Bases:matplotlib.ticker.Locator

Dynamically find minor tick positions based on the positions ofmajor ticks. Assumes the scale is linear and major ticks areevenly spaced.

n is the number of subdivisions of the interval betweenmajor ticks; e.g., n=2 will place a single minor tick midwaybetween major ticks.

Ifn is omitted or None, it will be set to 5 or 4.

tick_values(vmin,vmax)¶

classmatplotlib.ticker.SymmetricalLogLocator(transform=None,subs=None,linthresh=None,base=None)¶

Bases:matplotlib.ticker.Locator

Determine the tick locations for symmetric log axes

place ticks on the location= base**i*subs[j]

set_params(subs=None,numticks=None)¶

Set parameters within this locator.

tick_values(vmin,vmax)¶

view_limits(vmin,vmax)¶

Try to choose the view limits intelligently