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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