Use the code here to implement custom log scale in a clean way in plot_graphs script. Right now its only experimental.
As of right now uncommenting this hunk would toggle a fixed custom log scale. It should be implemented in the plot.yml as a parameter.
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# from matplotlib.ticker import MaxNLocator, LogLocator,FormatStrFormatter,ScalarFormatter |
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# import numpy as np |
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# plt.gca().yaxis.set_major_locator(LogLocator(base=10, subs=np.arange(0.1, 1, 0.1), numticks=10)) |
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# # plt.gca().yaxis.set_major_formatter(FormatStrFormatter('')) |
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# plt.gca().yaxis.set_major_formatter(ScalarFormatter()) |
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# plt.gca().yaxis.set_minor_formatter(ScalarFormatter()) |
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# plt.tick_params(axis='y', labelsize=8) # Adjust the label size here (e.g., 8) |
Use the code here to implement custom log scale in a clean way in
plot_graphsscript. Right now its only experimental.As of right now uncommenting this hunk would toggle a fixed custom log scale. It should be implemented in the
plot.ymlas a parameter.atom/atom_batch_execution/scripts/plot_graphs
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