[Numpy-discussion] Addressing arrays
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 ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Addressing arrays
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), can I look at the values of z given particular values for x and y? Thanks, Ted ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion -- *** Chao YUE Laboratoire des Sciences du Climat et de l'Environnement (LSCE-IPSL) UMR 1572 CEA-CNRS-UVSQ Batiment 712 - Pe 119 91191 GIF Sur YVETTE Cedex Tel: (33) 01 69 08 29 02; Fax:01.69.08.77.16 ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Addressing arrays
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? a[x, y, :] should get you what you want I believe.. Malcolm ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Addressing arrays
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 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 ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Addressing arrays
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: 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 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 ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion -- *** Chao YUE Laboratoire des Sciences du Climat et de l'Environnement (LSCE-IPSL) UMR 1572 CEA-CNRS-UVSQ Batiment 712 - Pe 119 91191 GIF Sur YVETTE Cedex Tel: (33) 01 69 08 29 02; Fax:01.69.08.77.16 ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Addressing arrays
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 values are scalars in this case, and indices are (x,y,z) triples, it seems likely that looking for values of z given an (x,y) pair is an slicing-by-index question, no? For indexing-by-value, fancy indexing with boolean masks is usually the way to go... again, Ted (or Chao), if you can describe your indexing needs in a bit more detail, it's often easy to find a compact slicing and/or fancy-indexing strategy that works well and reasonably efficiently. Zach On Jan 30, 2012, at 10:33 AM, Chao YUE wrote: 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: 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 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 ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion -- *** Chao YUE Laboratoire des Sciences du Climat et de l'Environnement (LSCE-IPSL) UMR 1572 CEA-CNRS-UVSQ Batiment 712 - Pe 119 91191 GIF Sur YVETTE Cedex Tel: (33) 01 69 08 29 02; Fax:01.69.08.77.16 ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Addressing arrays
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 the first three dimensions. Many thanks, Ted On 01/30/2012 10:50 AM, Zachary Pincus wrote: 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 values are scalars in this case, and indices are (x,y,z) triples, it seems likely that looking for values of z given an (x,y) pair is an slicing-by-index question, no? For indexing-by-value, fancy indexing with boolean masks is usually the way to go... again, Ted (or Chao), if you can describe your indexing needs in a bit more detail, it's often easy to find a compact slicing and/or fancy-indexing strategy that works well and reasonably efficiently. Zach On Jan 30, 2012, at 10:33 AM, Chao YUE wrote: 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: 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 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 ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion -- *** Chao YUE Laboratoire des Sciences du Climat et de l'Environnement (LSCE-IPSL) UMR 1572 CEA-CNRS-UVSQ Batiment 712 - Pe 119 91191 GIF Sur YVETTE Cedex Tel: (33) 01 69 08 29 02; Fax:01.69.08.77.16 ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Addressing arrays
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 dimensional array and I'd like to look at the contents using one or more of the first three dimensions. Many thanks, Ted Couldn't you just do something like this with boolean indexing: In [1]: import numpy as np In [2]: a = np.array([(1,2),(2,3),(3,4)]) In [3]: a Out[3]: array([[1, 2], [2, 3], [3, 4]]) In [4]: mask = a[:,0] == 2 In [5]: mask Out[5]: array([False, True, False], dtype=bool) In [6]: a[mask,1] Out[6]: array([3]) ~Brett ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Addressing arrays
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 time==2. My actual application has a six dimensional array and I'd like to look at the contents using one or more of the first three dimensions. Many thanks, Ted Couldn't you just do something like this with boolean indexing: In [1]: import numpy as np In [2]: a = np.array([(1,2),(2,3),(3,4)]) In [3]: a Out[3]: array([[1, 2], [2, 3], [3, 4]]) In [4]: mask = a[:,0] == 2 In [5]: mask Out[5]: array([False, True, False], dtype=bool) In [6]: a[mask,1] Out[6]: array([3]) ~Brett 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 a[['month','year']]==(1,1960) produces False. I'm sure I simply don't know the proper syntax and I apologize for that -- I'm kind of new to numpy. Ted ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Addressing arrays
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 a[['month','year']]==(1,1960) produces False. I'm sure I simply don't know the proper syntax and I apologize for that -- I'm kind of new to numpy. I think that your best bet is to form the boolean masks independently and then logical-and them together: mask = (a['month'] == 1) (a['year'] == 1960) jan_60 = a[mask] Someone might have more insight here. Though I should note that if you have large data and are doing lots of queries like this, a more database-ish approach might be better. Something like sqlite's python bindings, or PyTables. Alternately, if your data are all time-series based things, PANDAS might be worth looking at. But the above approach should be just fine for non-huge datasets... Zach ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Addressing arrays
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 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 the first three dimensions. Many thanks, Ted Couldn't you just do something like this with boolean indexing: In [1]: import numpy as np In [2]: a = np.array([(1,2),(2,3),(3,4)]) In [3]: a Out[3]: array([[1, 2], [2, 3], [3, 4]]) In [4]: mask = a[:,0] == 2 In [5]: mask Out[5]: array([False, True, False], dtype=bool) In [6]: a[mask,1] Out[6]: array([3]) ~Brett 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 a[['month','year']]==(1,1960) produces False. I'm sure I simply don't know the proper syntax and I apologize for that -- I'm kind of new to numpy. Ted 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 operators and if you leave the parens out, it will try to bitwise-and 1 and a[:,1] and throw an error. If you've got a ton of parameters, you can combine these more aesthetically with: mask = (a[:,[0,1]] == [1, 1960]).all(axis=1) ~Brett ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Addressing arrays
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 operators and if you leave the parens out, it will try to bitwise-and 1 and a[:,1] and throw an error. If you've got a ton of parameters, you can combine these more aesthetically with: mask = (a[:,[0,1]] == [1, 1960]).all(axis=1) ~Brett Zach and Brett, Many thanks -- that is exactly what I need. Cheers, Ted ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
