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pyplot.plot(a, color='blue', lw=2) pyplot.yscale('log') pyplot.show() The relevant function is pyplot.yscale(). If you use the object-oriented version, replace it by the method Axes.set_yscale(). Remember that you can also change the scale of X axis, using pyplot.xscale() (or Axes.set_xscale()).
1 Ιαν 2021 · Syntax : matplotlib.pyplot.xscale (value, **kwargs) Parameters: Value = { “linear”, “log”, “symlog”, “logit”, …. **kwargs = Different keyword arguments are accepted, depending on the scale (matplotlib.scale.LinearScale, LogScale, SymmetricalLogScale, LogitScale) Returns : Converts the x-axes to the given scale type.
Axis scales# By default Matplotlib displays data on the axis using a linear scale. Matplotlib also supports logarithmic scales, and other less common scales as well. Usually this can be done directly by using the set_xscale or set_yscale methods.
Make a plot with log scaling on both the x- and y-axis. Call signatures: loglog([x], y, [fmt], data=None, **kwargs) loglog([x], y, [fmt], [x2], y2, [fmt2], ..., **kwargs) This is just a thin wrapper around plot which additionally changes both the x-axis and the y-axis to log scaling.
When you want to focus on how to plot logarithmic axes in Matplotlib for just the x-axis, you can use the semilogx () function. This is particularly useful when your x-axis data spans several orders of magnitude, but your y-axis data is better represented on a linear scale.
11 Φεβ 2022 · Additionally, we will showcase how to plot figures with logarithmic axes using Python and matplotlib package and understand which method to use depending on whether you are using the Pyplot or Object-oriented interface.
2 Φεβ 2024 · The semilogx() function creates plot with log scaling along X-axis while semilogy() function creates plot with log scaling along Y-axis. The default base of logarithm is 10 while base can set with basex and basey parameters for the function semilogx() and semilogy() respectively.
