René's URL Explorer Experiment

Title: Add asinh axis scaling (*smooth* symmetric logscale) by rwpenney · Pull Request #21178 · matplotlib/matplotlib · GitHub

Open Graph Title: Add asinh axis scaling (*smooth* symmetric logscale) by rwpenney · Pull Request #21178 · matplotlib/matplotlib

X Title: Add asinh axis scaling (*smooth* symmetric logscale) by rwpenney · Pull Request #21178 · matplotlib/matplotlib

Description: Summary When plotting quantities that span many orders of magnitude, it is standard practice to apply log-scaling, and Matplotlib already provides the symlog scaling which allows log-scaling to be applied to quantities that are both positive and negative. However, symlog introduces discontinuous gradients in its transformation because it involves grafting together separate linear and logarithmic transformations. This pull-request proposes a new transformation, based on numpy.arcsinh, which is a smooth transformation that is asymptotically logarithmic for large sample values and has a quasi-linear region of controllable width near the origin. This pull-request introduces a new asinh option to Axis.set_yscale which applies an inverse hyperbolic sine transformation and also generates tick locations that are roughly uniformly spaced over the given axis, while being rounded sensibly on a base-10 scale. The plot below shows how this behaves when plotting y=m*x with different settings of the scale parameter a0 (which sets the width of the linear region near y=0). A previous pull request (#16639) had proposed changing the behaviour of symlog itself. This P/R sits alongside symlog and should have no impact on code currently dependent on the behaviour of symlog. As a simple example of use of the new asinh scaling: import numpy import matplotlib.pyplot as plt # Prepare sample values for variations on y=x graph: x = numpy.linspace(-3, 6, 100) # Compare "symlog" and "asinh" behaviour on sample y=x graph: fig1 = plt.figure() ax0, ax1 = fig1.subplots(1, 2, sharex=True) ax0.plot(x, x) ax0.set_yscale('symlog') ax0.grid() ax0.set_title('symlog') ax1.plot(x, x) ax1.set_yscale('asinh') ax1.grid() ax1.set_title(r'$sinh^{-1}$') PR Checklist [N/A] Has pytest style unit tests (and pytest passes). [*] Is Flake 8 compliant (run flake8 on changed files to check). [*] New features are documented, with examples if plot related. [*] Documentation is sphinx and numpydoc compliant (the docs should build without error). [*] Conforms to Matplotlib style conventions (install flake8-docstrings and run flake8 --docstring-convention=all). [*] New features have an entry in doc/users/next_whats_new/ (follow instructions in README.rst there). [N/A] API changes documented in doc/api/next_api_changes/ (follow instructions in README.rst there).

Open Graph Description: Summary When plotting quantities that span many orders of magnitude, it is standard practice to apply log-scaling, and Matplotlib already provides the symlog scaling which allows log-scaling to be ...

X Description: Summary When plotting quantities that span many orders of magnitude, it is standard practice to apply log-scaling, and Matplotlib already provides the symlog scaling which allows log-scaling to be ...

Opengraph URL: https://github.com/matplotlib/matplotlib/pull/21178

X: @github

direct link

Domain: github.com

Links:

Viewport: width=device-width