Find positions of elements in sorted array
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Suppose I have some numpy array (all elements are unique) that I want to sort in descending order. I need to find out which positions elements of initial array will take in sorted array.
Example.
In1: [1, 2, 3] # Input
Out1: [2, 1, 0] # Expected output
In2: [1, -2, 2] # Input
Out2: [1, 2, 0] # Expected output
I tried this one:
def find_positions(A):
A = np.array(A)
A_sorted = np.sort(A)[::-1]
return np.argwhere(A[:, None] == A_sorted[None, :])[:, 1]
But it doesn't work when the input array is very large (len > 100000). What I did wrong and how can I resolve it?
python numpy
edited Nov 23 '18 at 8:02
Divakar
160k1494187
asked Nov 23 '18 at 7:51
M.SidorenkoM.Sidorenko
194
add a comment |
Suppose I have some numpy array (all elements are unique) that I want to sort in descending order. I need to find out which positions elements of initial array will take in sorted array.
Example.
In1: [1, 2, 3] # Input
Out1: [2, 1, 0] # Expected output
In2: [1, -2, 2] # Input
Out2: [1, 2, 0] # Expected output
I tried this one:
def find_positions(A):
A = np.array(A)
A_sorted = np.sort(A)[::-1]
return np.argwhere(A[:, None] == A_sorted[None, :])[:, 1]
But it doesn't work when the input array is very large (len > 100000). What I did wrong and how can I resolve it?
python numpy
edited Nov 23 '18 at 8:02
Divakar
160k1494187
asked Nov 23 '18 at 7:51
M.SidorenkoM.Sidorenko
194
2
Possible duplicate of Get original indices of a sorted Numpy array
– Rahul Agarwal
Nov 23 '18 at 7:59
@RahulAgarwal Not a duplicate because we are trying to trace back the index positions in the sorted array against the original order. Simply using argsort as suggested in the linked dup target won't work here.
– Divakar
Nov 23 '18 at 8:04
add a comment |
Suppose I have some numpy array (all elements are unique) that I want to sort in descending order. I need to find out which positions elements of initial array will take in sorted array.
Example.
In1: [1, 2, 3] # Input
Out1: [2, 1, 0] # Expected output
In2: [1, -2, 2] # Input
Out2: [1, 2, 0] # Expected output
I tried this one:
def find_positions(A):
A = np.array(A)
A_sorted = np.sort(A)[::-1]
return np.argwhere(A[:, None] == A_sorted[None, :])[:, 1]
But it doesn't work when the input array is very large (len > 100000). What I did wrong and how can I resolve it?
python numpy
edited Nov 23 '18 at 8:02
Divakar
160k1494187
asked Nov 23 '18 at 7:51
M.SidorenkoM.Sidorenko
194
Suppose I have some numpy array (all elements are unique) that I want to sort in descending order. I need to find out which positions elements of initial array will take in sorted array.
Example.
In1: [1, 2, 3] # Input
Out1: [2, 1, 0] # Expected output
In2: [1, -2, 2] # Input
Out2: [1, 2, 0] # Expected output
I tried this one:
def find_positions(A):
A = np.array(A)
A_sorted = np.sort(A)[::-1]
return np.argwhere(A[:, None] == A_sorted[None, :])[:, 1]
But it doesn't work when the input array is very large (len > 100000). What I did wrong and how can I resolve it?
python numpy
python numpy
edited Nov 23 '18 at 8:02
Divakar
160k1494187
asked Nov 23 '18 at 7:51
M.SidorenkoM.Sidorenko
194
edited Nov 23 '18 at 8:02
Divakar
160k1494187
asked Nov 23 '18 at 7:51
M.SidorenkoM.Sidorenko
194
edited Nov 23 '18 at 8:02
Divakar
160k1494187
edited Nov 23 '18 at 8:02
Divakar
160k1494187
edited Nov 23 '18 at 8:02
Divakar
160k1494187
160k1494187
asked Nov 23 '18 at 7:51
M.SidorenkoM.Sidorenko
194
asked Nov 23 '18 at 7:51
M.SidorenkoM.Sidorenko
194
asked Nov 23 '18 at 7:51
M.SidorenkoM.Sidorenko
194
194
2
Possible duplicate of Get original indices of a sorted Numpy array
– Rahul Agarwal
Nov 23 '18 at 7:59
@RahulAgarwal Not a duplicate because we are trying to trace back the index positions in the sorted array against the original order. Simply using argsort as suggested in the linked dup target won't work here.
– Divakar
Nov 23 '18 at 8:04
add a comment |
2
Possible duplicate of Get original indices of a sorted Numpy array
– Rahul Agarwal
Nov 23 '18 at 7:59
@RahulAgarwal Not a duplicate because we are trying to trace back the index positions in the sorted array against the original order. Simply using argsort as suggested in the linked dup target won't work here.
– Divakar
Nov 23 '18 at 8:04
2
2
Possible duplicate of Get original indices of a sorted Numpy array
– Rahul Agarwal
Nov 23 '18 at 7:59
Possible duplicate of Get original indices of a sorted Numpy array
– Rahul Agarwal
Nov 23 '18 at 7:59
@RahulAgarwal Not a duplicate because we are trying to trace back the index positions in the sorted array against the original order. Simply using argsort as suggested in the linked dup target won't work here.
– Divakar
Nov 23 '18 at 8:04
@RahulAgarwal Not a duplicate because we are trying to trace back the index positions in the sorted array against the original order. Simply using argsort as suggested in the linked dup target won't work here.
– Divakar
Nov 23 '18 at 8:04
add a comment |
2 Answers
2
active
oldest
votes
Approach #1
We could use double argsort -
np.argsort(a)[::-1].argsort() # a is input array/list
Approach #2
We could use one argsort and then array-assignment -
# https://stackoverflow.com/a/41242285/ @Andras Deak
def argsort_unique(idx):
n = idx.size
sidx = np.empty(n,dtype=int)
sidx[idx] = np.arange(n)
return sidx
out = argsort_unique(np.argsort(a)[::-1])
answered Nov 23 '18 at 7:58
DivakarDivakar
160k1494187
add a comment |
Take a look at numpy.argsort(...) function:
Returns the indices that would sort an array.
Perform an indirect sort along the given axis using the algorithm specified by the kind keyword. It returns an array of indices of the same shape as a that index data along the given axis in sorted order.
Here is the reference from the documentation, and the following is a simple example:
import numpy
arr = numpy.random.rand(100000)
indexes = numpy.argsort(arr)
the indexes array will contain all the indexes in the order in which the array arr would be sorted
answered Nov 23 '18 at 8:04
DLMDLM
684
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
Approach #1
We could use double argsort -
np.argsort(a)[::-1].argsort() # a is input array/list
Approach #2
We could use one argsort and then array-assignment -
# https://stackoverflow.com/a/41242285/ @Andras Deak
def argsort_unique(idx):
n = idx.size
sidx = np.empty(n,dtype=int)
sidx[idx] = np.arange(n)
return sidx
out = argsort_unique(np.argsort(a)[::-1])
answered Nov 23 '18 at 7:58
DivakarDivakar
160k1494187
add a comment |
Approach #1
We could use double argsort -
np.argsort(a)[::-1].argsort() # a is input array/list
Approach #2
We could use one argsort and then array-assignment -
# https://stackoverflow.com/a/41242285/ @Andras Deak
def argsort_unique(idx):
n = idx.size
sidx = np.empty(n,dtype=int)
sidx[idx] = np.arange(n)
return sidx
out = argsort_unique(np.argsort(a)[::-1])
answered Nov 23 '18 at 7:58
DivakarDivakar
160k1494187
add a comment |
Approach #1
We could use double argsort -
np.argsort(a)[::-1].argsort() # a is input array/list
Approach #2
We could use one argsort and then array-assignment -
# https://stackoverflow.com/a/41242285/ @Andras Deak
def argsort_unique(idx):
n = idx.size
sidx = np.empty(n,dtype=int)
sidx[idx] = np.arange(n)
return sidx
out = argsort_unique(np.argsort(a)[::-1])
answered Nov 23 '18 at 7:58
DivakarDivakar
160k1494187
Approach #1
We could use double argsort -
np.argsort(a)[::-1].argsort() # a is input array/list
Approach #2
We could use one argsort and then array-assignment -
# https://stackoverflow.com/a/41242285/ @Andras Deak
def argsort_unique(idx):
n = idx.size
sidx = np.empty(n,dtype=int)
sidx[idx] = np.arange(n)
return sidx
out = argsort_unique(np.argsort(a)[::-1])
answered Nov 23 '18 at 7:58
DivakarDivakar
160k1494187
answered Nov 23 '18 at 7:58
DivakarDivakar
160k1494187
answered Nov 23 '18 at 7:58
DivakarDivakar
160k1494187
answered Nov 23 '18 at 7:58
DivakarDivakar
160k1494187
160k1494187
add a comment |
add a comment |
Take a look at numpy.argsort(...) function:
Returns the indices that would sort an array.
Perform an indirect sort along the given axis using the algorithm specified by the kind keyword. It returns an array of indices of the same shape as a that index data along the given axis in sorted order.
Here is the reference from the documentation, and the following is a simple example:
import numpy
arr = numpy.random.rand(100000)
indexes = numpy.argsort(arr)
the indexes array will contain all the indexes in the order in which the array arr would be sorted
answered Nov 23 '18 at 8:04
DLMDLM
684
add a comment |
Take a look at numpy.argsort(...) function:
Returns the indices that would sort an array.
Perform an indirect sort along the given axis using the algorithm specified by the kind keyword. It returns an array of indices of the same shape as a that index data along the given axis in sorted order.
Here is the reference from the documentation, and the following is a simple example:
import numpy
arr = numpy.random.rand(100000)
indexes = numpy.argsort(arr)
the indexes array will contain all the indexes in the order in which the array arr would be sorted
answered Nov 23 '18 at 8:04
DLMDLM
684
add a comment |
Take a look at numpy.argsort(...) function:
Returns the indices that would sort an array.
Perform an indirect sort along the given axis using the algorithm specified by the kind keyword. It returns an array of indices of the same shape as a that index data along the given axis in sorted order.
Here is the reference from the documentation, and the following is a simple example:
import numpy
arr = numpy.random.rand(100000)
indexes = numpy.argsort(arr)
the indexes array will contain all the indexes in the order in which the array arr would be sorted
answered Nov 23 '18 at 8:04
DLMDLM
684
Take a look at numpy.argsort(...) function:
Returns the indices that would sort an array.
Perform an indirect sort along the given axis using the algorithm specified by the kind keyword. It returns an array of indices of the same shape as a that index data along the given axis in sorted order.
Here is the reference from the documentation, and the following is a simple example:
import numpy
arr = numpy.random.rand(100000)
indexes = numpy.argsort(arr)
the indexes array will contain all the indexes in the order in which the array arr would be sorted
answered Nov 23 '18 at 8:04
DLMDLM
684
answered Nov 23 '18 at 8:04
DLMDLM
684
answered Nov 23 '18 at 8:04
DLMDLM
684
answered Nov 23 '18 at 8:04
DLMDLM
684
684
add a comment |
add a comment |
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2
Possible duplicate of Get original indices of a sorted Numpy array
– Rahul Agarwal
Nov 23 '18 at 7:59
@RahulAgarwal Not a duplicate because we are trying to trace back the index positions in the sorted array against the original order. Simply using argsort as suggested in the linked dup target won't work here.
– Divakar
Nov 23 '18 at 8:04