Hello, I've started to use the convention of making dictionaries to hold my
datasets. But I haven't settled on an approach yet, and would like input
from people for how they a) handle their arrays of data, and b) how to
create pylab arrays from lists of lists, etc.
What I generally have is:
Okay??
That does seem to work... I guess I'd better go read up on index_tricks.py ?
Thanks.
Alan G Isaac wrote:
x1,y1,x2,y2 =np.random.random((4,20))
data = dict(var1=(x1,y1), var2=(x2,y2))
a = np.c_[[d for xy in data.values() for d in xy]]
a
array([[ 0.66613738, 0.39154179,
Hello, I've defined the following function to dynamically define map extents
based on lon,lat input data. It is not very elegant or robust, but it does
seem to work. One issue, however, and it probably is related to something
else further down the chain... but every plot ends up being a different
Hello all,
I'm trying to create a plot in each element in my x,y array have a
slightly different color - using spectral for example.
My data is a time series, but I am not plotting the time series. I
want the older data to show up in a different color from the latest
data.
What I have so far
Trying again, a little more detail:
I am trying to use the color setting feature of SCATTER:
colors=cm.spectral(linespace(0,100,len(x))
then, plotting:
scatter(x,y,c=colors)
I get the error:
TypeError: c must be a matplotlib color arg or a sequence of them
But I don't understand.
x.shape
Eric,
Exactly. Thanks for your post. I finally figured it out, and wanted to
post here for completeness in case no one followed up, but I'm glad
that you did. So yes, the following:
scatter(x, y, c=arange(len(x)), cmap=cm.spectral)
is exactly what I wanted... except that for my data I had:
