I have a 2D array. Say it is 10x10 and I want a 1D Array of 100
elements...
What is the syntax?
oneD = reshape(twoD, (100,1))
or
oneD = reshape(twoD, (1,100))
One I guess is the transpose of the other but both seem to be
arrays of arrays...
help?!
4  12333 
KraftDiner wrote: I have a 2D array. Say it is 10x10 and I want a 1D Array of 100
elements...
What is the syntax?
oneD = reshape(twoD, (100,1))
or
oneD = reshape(twoD, (1,100))
One I guess is the transpose of the other but both seem to be
arrays of arrays...
The mailing list for numpy is nu****************@lists.sourceforge.net, and you
may get faster/better help there. But:
oneD = reshape(twoD, (100,))
--
Robert Kern ro*********@gmail.com
"I have come to believe that the whole world is an enigma, a harmless enigma
that is made terrible by our own mad attempt to interpret it as though it had
an underlying truth."
-- Umberto Eco
KraftDiner wrote: I have a 2D array. Say it is 10x10 and I want a 1D Array of 100
elements...
What is the syntax?
oneD = reshape(twoD, (100,1))
or
oneD = reshape(twoD, (1,100))
One I guess is the transpose of the other but both seem to be
arrays of arrays...
Or
oneD = ravel(twoD)
--
Robert Kern ro*********@gmail.com
"I have come to believe that the whole world is an enigma, a harmless enigma
that is made terrible by our own mad attempt to interpret it as though it had
an underlying truth."
-- Umberto Eco
KraftDiner wrote: I have a 2D array. Say it is 10x10 and I want a 1D Array of 100
elements...
What is the syntax?
oneD = reshape(twoD, (100,1))
or
oneD = reshape(twoD, (1,100))
One I guess is the transpose of the other but both seem to be
arrays of arrays...
help?!
Using pyarray, as mentioned in the previous thread:
#from http://svn.brownspencer.com/pyarray/trunk/ from pyarray import ndlist
source_list = [range(i*10,(i+1)*10) for i in range(10)]
source_array = ndlist(source_list)
source_array
array([[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
[10, 11, 12, 13, 14, 15, 16, 17, 18, 19],
[20, 21, 22, 23, 24, 25, 26, 27, 28, 29],
[30, 31, 32, 33, 34, 35, 36, 37, 38, 39],
[40, 41, 42, 43, 44, 45, 46, 47, 48, 49],
[50, 51, 52, 53, 54, 55, 56, 57, 58, 59],
[60, 61, 62, 63, 64, 65, 66, 67, 68, 69],
[70, 71, 72, 73, 74, 75, 76, 77, 78, 79],
[80, 81, 82, 83, 84, 85, 86, 87, 88, 89],
[90, 91, 92, 93, 94, 95, 96, 97, 98, 99]]) source_array.flat
array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,
18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37,
38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57,
58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77,
78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97,
98, 99]) list(source_array.flat)
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21,
22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41,
42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61,
62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81,
82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99]
In this case, pyarray.ndlist behaves the same as numpy.array
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