I don't understand why sometimes a direct assignment of a new dtype is
possible (but messes up the values), and why at other times a seemingly
harmless upcast (in my potentially ignorant point of view) is not
possible.
So, maybe a direct assignment of a new dtype is actually never a good
idea?
On 2013-04-19 01:02:59 +, Benjamin Root said:
On Thu, Apr 18, 2013 at 7:31 PM, K.-Michael Aye kmichael@gmail.com
wrote:
I don't understand why sometimes a direct assignment of a new dtype is
possible (but messes up the values), and why at other times a seemingly
harmless
I know I know, that's pretty outrageous to even suggest, but please
bear with me, I am stumped as you may be:
2-D data file here:
http://dl.dropbox.com/u/139035/data.npy
Then:
In [3]: data.mean()
Out[3]: 3067.024383998
In [4]: data.max()
Out[4]: 3052.4343
In [5]: data.shape
Out[5]: (1000,
do not want to convert to float64 you can add
the result of the previous line to the bad mean:
bad_mean = data.mean()
good_mean = bad_mean + np.mean(data - bad_mean)
Val
On Tue, Jan 24, 2012 at 12:33 PM, K.-Michael Aye
kmichael@gmail.com wrote:
I know I know, that's pretty outrageous
Dear all,
I can't wrap my head around this. Mathematically it's not hard, I just
don't know how to store and access it without many loops.
I have a function f(x,y).
I would like to calculate it at x = arange(20,101,20) and y = arange(2,30,2)
How do I store that in a multi-dimensional array
Dear all,
I'm a bit puzzled that there seems just no way to cleanly code an
interval with evenly spaced numbers that includes the stop point given?
linspace offers to include the stop point, but arange does not?
Am I missing something? (I am aware, that I could do
arange(9,15.0001,0.1) but
On 2010-12-30 16:43:12 +0200, josef.p...@gmail.com said:
Since linspace exists, I don't see much point in adding the stop point
in arange. I use arange mainly for integers as numpy equivalent of
python's range. And I often need arange(n+1) which is less writing
than arange(n,
Dear numpy hackers,
I can't find the syntax for unpacking the 3 dimensions of a rgb array.
so i have a MxNx3 image array 'img' and would like to do:
red, green, blue = img[magical_slicing]
Which slicing magic do I need to apply?
Thanks for your help!
BR,
Michael
