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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.
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.
This tutorial covered how to create plots with logarithmic axes using semilogy, semilogx, loglog, and errorbars plots. By using these types of plots, you can effectively visualize data that has a large range of values.
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.
Detailed examples of Log Plots including changing color, size, log axes, and more in Python.
