[Matplotlib-users] Struggle with ticker.SymmetricalLogLocator()

[superchinchilla]

Thanks for the answer,

I'm actually struggling to set a new major yticks in the case
symlog plot because it's not clear for me how the
  m=matplotlib.ticker.SymmetricallLogLocator(transform,subs=None)
  m.set_params() ... to change ytickfrequency    and I didn't find a proper
  solution to it the internet?
  Do you know how to change it? What is the meaning of transform?

  Thank you very much,:)
  chinchi

||||////||

Am 19.03.2016 um 01:13 schrieb Eric Firing [via matplotlib]:
> On 2016/02/15 12:03 AM, superchinchilla wrote:
>
> > Hi,
> >
> > I want to make a symmetric logarithmic plot, but unfortunately the 
> y-values
> > are overlapping around 0. I don't want to display the first values 
> around 0.
> > I'm not sure how to use the ticker.SymmetricalLogLocator command to 
> change
> > the ticklocations or the tickfrequencies. I searched for a long time 
> but
> > didn't find any proper solution for it besides the examples for the 
> normal
> > Loglocater which didn't work.  I tried to understand how the
> > ticker.SymmetricalLogLocator(transform, subs=None) instance is 
> working on
> > the matplotlib documentation side which is not an easy target for 
> me. I only
> > want that the first ticklabes around zero are not displayed in my plot.
> >
> > I'm using the plt.yscale('symlog') command in order to plot it 
> symmetrically
> > around zero. My picture looks like
> >
> > <http://matplotlib.1069221.n5.nabble.com/file/n46753/heat1_raten1.png>
> > Sorry for my bad English,
> > thanx for any help in advance
>
> I'm sorry for the long delay, but in case you haven't found a solution
> yet, here is an example of one way of handling the situation:
>
>
> import matplotlib.pyplot as plt
> import numpy as np
>
> dt = 0.01
> x = np.arange(-50.0, 50.0, dt)
> y = np.arange(0, 100.0, dt)
>
> fig, ax = plt.subplots()
> ax.plot(y, x)
> ax.set_yscale('symlog')
> ax.set_ylabel('symlogy')
>
> ylabs = ax.yaxis.get_ticklabels()
> i0 = int(len(ylabs) // 2)
>
> for label in ylabs[i0-1:i0+2]:
>      label.set_visible(False)
>
> plt.show()
>
> -----
> Eric
>
> >
> >
> >
> > --
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