It may be instantiated directly, or subclassed.
The :None:None:`set_locs` method must be called to enable the subsetting logic controlled by the minor_thresholds
parameter.
In some cases such as the colorbar, there is no distinction between major and minor ticks; the tick locations might be set manually, or by a locator that puts ticks at integer powers of base and at intermediate locations. For this situation, disable the minor_thresholds logic by using minor_thresholds=(np.inf, np.inf)
, so that all ticks will be labeled.
To disable labeling of minor ticks when 'labelOnlyBase' is False, use minor_thresholds=(0, 0)
. This is the default for the "classic" style.
Base of the logarithm used in all calculations.
If True, label ticks only at integer powers of base. This is normally True for major ticks and False for minor ticks.
If labelOnlyBase is False, these two numbers control the labeling of ticks that are not at integer powers of base; normally these are the minor ticks. The controlling parameter is the log of the axis data range. In the typical case where base is 10 it is the number of decades spanned by the axis, so we can call it 'numdec'. If numdec <= all
, all minor ticks will be labeled. If all < numdec <= subset
, then only a subset of minor ticks will be labeled, so as to avoid crowding. If numdec > subset
then no minor ticks will be labeled.
If a symmetric log scale is in use, its linthresh
parameter must be supplied here.
Base class for formatting ticks on a log or symlog scale.
To label a subset of minor ticks when the view limits span up to 2 decades, and all of the ticks when zoomed in to 0.5 decades or less, use minor_thresholds=(2, 0.5)
.
To label all minor ticks when the view limits span up to 1.5 decades, use minor_thresholds=(1.5, 1.5)
.
The following pages refer to to this document either explicitly or contain code examples using this.
matplotlib.ticker
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