Re: [Numpy-discussion] Unrealistic expectations of class Polynomial or a bug?

2012-01-30 Thread eat
On Sat, Jan 28, 2012 at 11:14 PM, Charles R Harris charlesr.har...@gmail.com wrote: On Sat, Jan 28, 2012 at 11:15 AM, eat e.antero.ta...@gmail.com wrote: Hi, Short demonstration of the issue: In []: sys.version Out[]: '2.7.2 (default, Jun 12 2011, 15:08:59) [MSC v.1500 32 bit (Intel)]'

[Numpy-discussion] Addressing arrays

2012-01-30 Thread Ted To
Hi, Is there some straightforward way to access an array by values across a subset of its dimensions? For example, if I have a three dimensional array a=(x,y,z), can I look at the values of z given particular values for x and y? Thanks, Ted ___

Re: [Numpy-discussion] Addressing arrays

2012-01-30 Thread Chao YUE
I am afraid you have to write index inquire function by yourself. I did like this. chao 2012/1/30 Ted To rainexpec...@theo.to Hi, Is there some straightforward way to access an array by values across a subset of its dimensions? For example, if I have a three dimensional array a=(x,y,z),

Re: [Numpy-discussion] Addressing arrays

2012-01-30 Thread Malcolm Reynolds
On Mon, Jan 30, 2012 at 3:25 PM, Ted To rainexpec...@theo.to wrote: Is there some straightforward way to access an array by values across a subset of its dimensions?  For example, if I have a three dimensional array a=(x,y,z), can I look at the values of z given particular values for x and y?

Re: [Numpy-discussion] Addressing arrays

2012-01-30 Thread Zachary Pincus
a[x,y,:] Read the slicing part of the tutorial: http://www.scipy.org/Tentative_NumPy_Tutorial (section 1.6) And the documentation: http://docs.scipy.org/doc/numpy/reference/arrays.indexing.html On Jan 30, 2012, at 10:25 AM, Ted To wrote: Hi, Is there some straightforward way to access

Re: [Numpy-discussion] Addressing arrays

2012-01-30 Thread Chao YUE
he is not asking for slicing. he is asking for how to index array by element value but not element index. 2012/1/30 Zachary Pincus zachary.pin...@yale.edu a[x,y,:] Read the slicing part of the tutorial: http://www.scipy.org/Tentative_NumPy_Tutorial (section 1.6) And the documentation:

Re: [Numpy-discussion] Addressing arrays

2012-01-30 Thread Zachary Pincus
Ted, can you clarify what you're asking for? Maybe give a trivial example of an array and the desired output? I'm pretty sure this is a slicing question though: If I have a three dimensional array a=(x,y,z), can I look at the values of z given particular values for x and y? Given that element

Re: [Numpy-discussion] Addressing arrays

2012-01-30 Thread Ted To
Sure thing. To keep it simple suppose I have just a two dimensional array (time,output): [(1,2),(2,3),(3,4)] I would like to look at all values of output for which, for example time==2. My actual application has a six dimensional array and I'd like to look at the contents using one or more of

Re: [Numpy-discussion] Addressing arrays

2012-01-30 Thread Brett Olsen
On Mon, Jan 30, 2012 at 10:57 AM, Ted To rainexpec...@theo.to wrote: Sure thing.  To keep it simple suppose I have just a two dimensional array (time,output): [(1,2),(2,3),(3,4)] I would like to look at all values of output for which, for example time==2. My actual application has a six

Re: [Numpy-discussion] Addressing arrays

2012-01-30 Thread Ted To
On 01/30/2012 12:13 PM, Brett Olsen wrote: On Mon, Jan 30, 2012 at 10:57 AM, Ted To rainexpec...@theo.to wrote: Sure thing. To keep it simple suppose I have just a two dimensional array (time,output): [(1,2),(2,3),(3,4)] I would like to look at all values of output for which, for example

Re: [Numpy-discussion] Addressing arrays

2012-01-30 Thread Zachary Pincus
Thanks! That works great if I only want to search over one index but I can't quite figure out what to do with more than a single index. So suppose I have a labeled, multidimensional array with labels 'month', 'year' and 'quantity'. a[['month','year']] gives me an array of indices but

Re: [Numpy-discussion] Addressing arrays

2012-01-30 Thread Brett Olsen
On Mon, Jan 30, 2012 at 11:31 AM, Ted To rainexpec...@theo.to wrote: On 01/30/2012 12:13 PM, Brett Olsen wrote: On Mon, Jan 30, 2012 at 10:57 AM, Ted To rainexpec...@theo.to wrote: Sure thing.  To keep it simple suppose I have just a two dimensional array (time,output): [(1,2),(2,3),(3,4)] I

Re: [Numpy-discussion] Addressing arrays

2012-01-30 Thread Ted To
You'd want to update your mask appropriately to get everything you want to select, one criteria at a time e.g.: mask = a[:,0] == 1 mask = a[:,1] == 1960 Alternatively: mask = (a[:,0] == 1) (a[:,1] == 1960) but be careful with the parens, and | are normally high-priority bitwise

Re: [Numpy-discussion] condense array along one dimension

2012-01-30 Thread Ruby Stevenson
I think this is exactly what I need. Thanks for your help, Olivier. Ruby On Fri, Jan 20, 2012 at 9:50 AM, Olivier Delalleau sh...@keba.be wrote: What do you mean by summarize? If for instance you want to sum along Y, just do   my_array.sum(axis=1) -=- Olivier 2012/1/20 Ruby Stevenson

Re: [Numpy-discussion] histogram help

2012-01-30 Thread Ruby Stevenson
Sorry, I realize I didn't describe the problem completely clear or correct. the (x,y) in this case is just many co-ordinates, and each coordinate has a list of values (Z value) associated with it. The bins are allocated for the Z. I hope this clarify things a little. Thanks again. Ruby On

Re: [Numpy-discussion] histogram help

2012-01-30 Thread Samuel John
Hi Ruby, I still do not fully understand your question but what I do in such cases is to construct a very simple array and test the functions. The help of numpy.histogram2d or numpy.histogramdd (for more than two dims) might help here. So I guess, basically you want to ignore the x,y positions

Re: [Numpy-discussion] preferred way of testing empty arrays

2012-01-30 Thread Chris Barker
On Fri, Jan 27, 2012 at 1:29 PM, Robert Kern robert.k...@gmail.com wrote: Well, if you really need to do this in more than one place, define a utility function and call it a day. def should_not_plot(x):    if x is None:        return True    elif isinstance(x, np.ndarray):        return