matplotlib.axes.Axes.semilogy#

Axes.semilogy(*args,**kwargs)[source]#

Make a plot with log scaling on the y-axis.

Call signatures:

semilogy([x],y,[fmt],data=None,**kwargs)semilogy([x],y,[fmt],[x2],y2,[fmt2],...,**kwargs)

This is just a thin wrapper aroundplot which additionally changesthe y-axis to log scaling. All the concepts and parameters of plot canbe used here as well.

The additional parametersbase,subs, andnonpositive control they-axis properties. They are just forwarded toAxes.set_yscale.

Parameters:

basefloat, default: 10

Base of the y logarithm.

subsarray-like, optional

The location of the minor yticks. IfNone, reasonable locationsare automatically chosen depending on the number of decades in theplot. SeeAxes.set_yscale for details.

nonpositive{'mask', 'clip'}, default: 'clip'

Non-positive values in y can be masked as invalid, or clipped to avery small positive number.

**kwargs

All parameters supported byplot.

Returns:

list ofLine2D

Objects representing the plotted data.

Examples usingmatplotlib.axes.Axes.semilogy#

Log scale

Log scale

SkewT-logP diagram: using transforms and custom projections

SkewT-logP diagram: using transforms and custom projections

Axis scales

Axis scales