Honestly, I can't even remember why it is wrapped. I think this is just a
relic of some old example that I had lying around. Serves me right for just
copying and pasting without thinking :P . A straight call to
itertools.cycle is definitely much cleaner. Also, is there an example of
this in the docs? If not, it would be a useful addition. Seems like a
common feature to address.
Cheers,
Aman
On Mon, Nov 8, 2010 at 10:41 PM, Ryan May <rma...@gmail.com> wrote:
> On Fri, Nov 5, 2010 at 8:07 AM, Aman Thakral <aman.thak...@gmail.com>
> wrote:
> > Hi,
> >
> > The best way to do this is to use a generator:
> >
> > import itertools
> > import matplotlib.pyplot as plt
> > import numpy as np
> >
> > def _ncycle(iterable,n):
> > """
> > Method to create a generator from an iterable. It keeps the
> > current position of the iterable in memory. Each time the
> > next() method for the iterable is called, it will return the
> > next item. If there are no more items, it will cycle to the
> > first item.
> > """
> >
> > for item in itertools.cycle(iterable):
> > yield item
> >
> > colors = _ncycle(('r','g','b','c','y','m','k'),1)
> > markers = _ncycle(('o','s','v'),1)
>
> I like the thought, but I'm not sure why you're making it so
> complicated by wrapping it. itertools.cycle by itself is perfect, and
> there's no reason to prime it by calling next() before the plot. The
> following is a bit more succint IMO:
>
> import itertools
> import matplotlib.pyplot as plt
> import numpy as np
>
> colors = itertools.cycle(['r','g','b','c','y','m','k'])
> markers = itertools.cycle(['o','s','v'])
>
> fig = plt.figure()
> ax = fig.add_subplot(111)
> for i in range(10):
> x = np.linspace(0, 2*np.pi)
> y = np.sin(x) + np.random.randn(*x.shape)
> ax.plot(x, y, c=colors.next(), marker=markers.next())
>
> plt.show()
>
> Also, you can avoid calling colors.next() and markers.next() if you
> put them in a zip command along with range().
>
> Ryan
>
> --
> Ryan May
> Graduate Research Assistant
> School of Meteorology
> University of Oklahoma
>
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