Re: [Matplotlib-users] x axis non-uniform labeling (KURT PETERS)

[Benjamin R. <ben...@ou...>]

On Tue, Oct 1, 2013 at 1:55 PM, KURT PETERS <pet...@ms...> wrote:

>
>
> > Date: Tue, 1 Oct 2013 19:35:39 +0200
>
> > Subject: Re: [Matplotlib-users] x axis non-uniform labeling (KURT PETERS)
> > From: goy...@gm...
> > To: pet...@ms...
> > CC: pmh...@gm...; mat...@li...
>
> >
> > 2013/10/1 KURT PETERS <pet...@ms...>:
> > > here's what SHOULD be happening
> > >
> > > | 0 1 5 9 13 18 21 24 25 28
> > > 3 | x
> > > | x x
> > > | x x
> > > | x x
> > > -1|_x__________________x_____
> > > 1 2 3 4 5 6 7 8 9 10
> > >
> > > How can I make that happen? Instead, MPL is autoranging the top axis. I
> > > don't want that I just want the actual labels to occur up there.
> >
> > Then just set the ticks and the tick labels of the axis:
> >
> > import numpy as np
> > import matplotlib.pyplot as plt
> > xdat=np.arange(1,11)
> > simtimedata = np.array([0, 1, 5, 9, 13, 18, 21, 24, 25, 28])
> > idatanp = np.array([-1,0, 1, 2, 3, 2, 1, 0, -1, -2])
> > ax1 = plt.subplot(111)
> > ax1.plot(xdat,idatanp)
> > ax2 = ax1.twiny()
> > ax2.set_xticks(range(len(xdat)))
> > ax2.set_xticklabels(simtimedata)
> > plt.show()
> >
> > Goyo
>
> Goyo,
>   Thanks, the code below seems to work.  The problem is that with
> "REAL/actual" data, I have SO many data points that each point is now
> labeled and it takes forever to render.  And when it does render, I cannot
> read the axis because there are too many there.  Is there a way to
> judiciously have it only display a certain number of values?  Such as every
> 100th value?
> Kurt
> xdat=np.arange(1,11)
> simtimedata = np.array([0, 1, 5, 9, 13, 18, 21, 24, 25, 28])
> idatanp = np.array([-1,0, 1, 2, 3, 2, 1, 0, -1, -2])
> print idatanp.shape
> print simtimedata.shape
> print xdat.shape
> fig = plt.figure()
>
> ax1 = fig.add_subplot(211)
> ax1.plot(xdat,idatanp)
> ax1.grid(True)
> ax2 = fig.add_subplot(212)
> ax2.plot(xdat, idatanp.real,'k-o')
> ax2.set_xticks(xdat)
> ax2.set_xticklabels(simtimedata)
> #ax2.set_title("time domain")
> ax2.grid(True)
> plt.show()
>

The philosophy of matplotlib is to have smart defaults, but always allow
the user to override.  Perhaps you are looking for a particular "ticker"?

http://matplotlib.org/api/ticker_api.html

I hope this helps!
Ben Root