Can we turn this for loop into a more elegant Mathematica code?
$begingroup$
I am coding stuff manipulating indirection arrays and I have some code like:
createDupInvIndir[indirection_?VectorQ,duplicate_?VectorQ]:=
Block[{n,dupInvIndir},
n=Length[indirection];
Assert[n==Length[duplicate]];
dupInvIndir=ConstantArray[0,n];
For[i=1,i<=n,i++,
dupInvIndir[[indirection[[i]]]]=duplicate[[i]];
];
Return[dupInvIndir];
];
We agree that this is not a good functional / Mathematica coding style. However, for the moment I have no idea to get an elegant/efficient way to remove the loop (using functions like Map, Scan...). Any suggestion/idea?
to check it works:
ind={3,5,4,2,1,6}
dup={1,2,2,3,3,3}
createDupInvIndir[ind,dup]
Output:
{3,3,1,2,2,3}
More context:
indirection
: is an indirection array got fromSortBy
function used with Range[1,n] to sort another array.
duplicate
: count different successive elements to detect duplicates
The array dupInvIndir
that satisfies the relation:
dupInvIndir[[indirection[[i]]]]=duplicate[[i]]
is used to get the positions (taking into account the duplicate) of the sorted data without explictely reordering the data.
Here is a complete working example:
createDupInvIndir[indirection_?VectorQ,duplicate_?VectorQ]:=
Block[{n,dupInvIndir},
n=Length[indirection];
Assert[n==Length[duplicate]];
dupInvIndir=ConstantArray[0,n];
For[i=1,i<=n,i++,
dupInvIndir[[indirection[[i]]]]=duplicate[[i]];
];
Return[dupInvIndir];
];
createDuplicate[data_List,indirection_?VectorQ]:=
Block[{dup},
dup=Tally[Range[Length[indirection]],(data[[indirection[[#1]]]]==data[[indirection[[#2]]]])&];
dup=Flatten[MapThread[ConstantArray[#1,#2]&,{Range[Length[dup]],Part[dup,All,2]}]];
Return[dup];
];
data={{3,4},{3,5},{1,2},{1,2},{2,3},{3,6},{5,6}}
indirection=SortBy[Range[Length[data]],data[[#]]&] (* {3,4,5,1,2,6,7} *)
duplicate=createDuplicate[data,indirection] (* {1,1,2,3,4,5,6} *)
dupInvIndir=createDupInvIndir[indirection,duplicate] (* {3,4,1,1,2,5,6} <- Final result *)
(* same stuff with *explicit* sort: data components are moved *)
DeleteDuplicates[Sort[data]] (* {{1,2},{2,3},{3,4},{3,5},{3,6},{5,6}} *)
Take the first element of dupInvIndir
, 3, it means that the first element of the (implicitely) sorted data array is data[[3]]
, ( -> {1,2}
).
This can be compared to the explicit DeleteDuplicate[Sort[data]]
performance-tuning vector permutation coding-style
$endgroup$
add a comment |
$begingroup$
I am coding stuff manipulating indirection arrays and I have some code like:
createDupInvIndir[indirection_?VectorQ,duplicate_?VectorQ]:=
Block[{n,dupInvIndir},
n=Length[indirection];
Assert[n==Length[duplicate]];
dupInvIndir=ConstantArray[0,n];
For[i=1,i<=n,i++,
dupInvIndir[[indirection[[i]]]]=duplicate[[i]];
];
Return[dupInvIndir];
];
We agree that this is not a good functional / Mathematica coding style. However, for the moment I have no idea to get an elegant/efficient way to remove the loop (using functions like Map, Scan...). Any suggestion/idea?
to check it works:
ind={3,5,4,2,1,6}
dup={1,2,2,3,3,3}
createDupInvIndir[ind,dup]
Output:
{3,3,1,2,2,3}
More context:
indirection
: is an indirection array got fromSortBy
function used with Range[1,n] to sort another array.
duplicate
: count different successive elements to detect duplicates
The array dupInvIndir
that satisfies the relation:
dupInvIndir[[indirection[[i]]]]=duplicate[[i]]
is used to get the positions (taking into account the duplicate) of the sorted data without explictely reordering the data.
Here is a complete working example:
createDupInvIndir[indirection_?VectorQ,duplicate_?VectorQ]:=
Block[{n,dupInvIndir},
n=Length[indirection];
Assert[n==Length[duplicate]];
dupInvIndir=ConstantArray[0,n];
For[i=1,i<=n,i++,
dupInvIndir[[indirection[[i]]]]=duplicate[[i]];
];
Return[dupInvIndir];
];
createDuplicate[data_List,indirection_?VectorQ]:=
Block[{dup},
dup=Tally[Range[Length[indirection]],(data[[indirection[[#1]]]]==data[[indirection[[#2]]]])&];
dup=Flatten[MapThread[ConstantArray[#1,#2]&,{Range[Length[dup]],Part[dup,All,2]}]];
Return[dup];
];
data={{3,4},{3,5},{1,2},{1,2},{2,3},{3,6},{5,6}}
indirection=SortBy[Range[Length[data]],data[[#]]&] (* {3,4,5,1,2,6,7} *)
duplicate=createDuplicate[data,indirection] (* {1,1,2,3,4,5,6} *)
dupInvIndir=createDupInvIndir[indirection,duplicate] (* {3,4,1,1,2,5,6} <- Final result *)
(* same stuff with *explicit* sort: data components are moved *)
DeleteDuplicates[Sort[data]] (* {{1,2},{2,3},{3,4},{3,5},{3,6},{5,6}} *)
Take the first element of dupInvIndir
, 3, it means that the first element of the (implicitely) sorted data array is data[[3]]
, ( -> {1,2}
).
This can be compared to the explicit DeleteDuplicate[Sort[data]]
performance-tuning vector permutation coding-style
$endgroup$
3
$begingroup$
It would be somewhat easier with some context on what you actually try to achieve there...
$endgroup$
– Henrik Schumacher
yesterday
$begingroup$
@HenrikSchumacher please holds on, I will add more context
$endgroup$
– Picaud Vincent
yesterday
add a comment |
$begingroup$
I am coding stuff manipulating indirection arrays and I have some code like:
createDupInvIndir[indirection_?VectorQ,duplicate_?VectorQ]:=
Block[{n,dupInvIndir},
n=Length[indirection];
Assert[n==Length[duplicate]];
dupInvIndir=ConstantArray[0,n];
For[i=1,i<=n,i++,
dupInvIndir[[indirection[[i]]]]=duplicate[[i]];
];
Return[dupInvIndir];
];
We agree that this is not a good functional / Mathematica coding style. However, for the moment I have no idea to get an elegant/efficient way to remove the loop (using functions like Map, Scan...). Any suggestion/idea?
to check it works:
ind={3,5,4,2,1,6}
dup={1,2,2,3,3,3}
createDupInvIndir[ind,dup]
Output:
{3,3,1,2,2,3}
More context:
indirection
: is an indirection array got fromSortBy
function used with Range[1,n] to sort another array.
duplicate
: count different successive elements to detect duplicates
The array dupInvIndir
that satisfies the relation:
dupInvIndir[[indirection[[i]]]]=duplicate[[i]]
is used to get the positions (taking into account the duplicate) of the sorted data without explictely reordering the data.
Here is a complete working example:
createDupInvIndir[indirection_?VectorQ,duplicate_?VectorQ]:=
Block[{n,dupInvIndir},
n=Length[indirection];
Assert[n==Length[duplicate]];
dupInvIndir=ConstantArray[0,n];
For[i=1,i<=n,i++,
dupInvIndir[[indirection[[i]]]]=duplicate[[i]];
];
Return[dupInvIndir];
];
createDuplicate[data_List,indirection_?VectorQ]:=
Block[{dup},
dup=Tally[Range[Length[indirection]],(data[[indirection[[#1]]]]==data[[indirection[[#2]]]])&];
dup=Flatten[MapThread[ConstantArray[#1,#2]&,{Range[Length[dup]],Part[dup,All,2]}]];
Return[dup];
];
data={{3,4},{3,5},{1,2},{1,2},{2,3},{3,6},{5,6}}
indirection=SortBy[Range[Length[data]],data[[#]]&] (* {3,4,5,1,2,6,7} *)
duplicate=createDuplicate[data,indirection] (* {1,1,2,3,4,5,6} *)
dupInvIndir=createDupInvIndir[indirection,duplicate] (* {3,4,1,1,2,5,6} <- Final result *)
(* same stuff with *explicit* sort: data components are moved *)
DeleteDuplicates[Sort[data]] (* {{1,2},{2,3},{3,4},{3,5},{3,6},{5,6}} *)
Take the first element of dupInvIndir
, 3, it means that the first element of the (implicitely) sorted data array is data[[3]]
, ( -> {1,2}
).
This can be compared to the explicit DeleteDuplicate[Sort[data]]
performance-tuning vector permutation coding-style
$endgroup$
I am coding stuff manipulating indirection arrays and I have some code like:
createDupInvIndir[indirection_?VectorQ,duplicate_?VectorQ]:=
Block[{n,dupInvIndir},
n=Length[indirection];
Assert[n==Length[duplicate]];
dupInvIndir=ConstantArray[0,n];
For[i=1,i<=n,i++,
dupInvIndir[[indirection[[i]]]]=duplicate[[i]];
];
Return[dupInvIndir];
];
We agree that this is not a good functional / Mathematica coding style. However, for the moment I have no idea to get an elegant/efficient way to remove the loop (using functions like Map, Scan...). Any suggestion/idea?
to check it works:
ind={3,5,4,2,1,6}
dup={1,2,2,3,3,3}
createDupInvIndir[ind,dup]
Output:
{3,3,1,2,2,3}
More context:
indirection
: is an indirection array got fromSortBy
function used with Range[1,n] to sort another array.
duplicate
: count different successive elements to detect duplicates
The array dupInvIndir
that satisfies the relation:
dupInvIndir[[indirection[[i]]]]=duplicate[[i]]
is used to get the positions (taking into account the duplicate) of the sorted data without explictely reordering the data.
Here is a complete working example:
createDupInvIndir[indirection_?VectorQ,duplicate_?VectorQ]:=
Block[{n,dupInvIndir},
n=Length[indirection];
Assert[n==Length[duplicate]];
dupInvIndir=ConstantArray[0,n];
For[i=1,i<=n,i++,
dupInvIndir[[indirection[[i]]]]=duplicate[[i]];
];
Return[dupInvIndir];
];
createDuplicate[data_List,indirection_?VectorQ]:=
Block[{dup},
dup=Tally[Range[Length[indirection]],(data[[indirection[[#1]]]]==data[[indirection[[#2]]]])&];
dup=Flatten[MapThread[ConstantArray[#1,#2]&,{Range[Length[dup]],Part[dup,All,2]}]];
Return[dup];
];
data={{3,4},{3,5},{1,2},{1,2},{2,3},{3,6},{5,6}}
indirection=SortBy[Range[Length[data]],data[[#]]&] (* {3,4,5,1,2,6,7} *)
duplicate=createDuplicate[data,indirection] (* {1,1,2,3,4,5,6} *)
dupInvIndir=createDupInvIndir[indirection,duplicate] (* {3,4,1,1,2,5,6} <- Final result *)
(* same stuff with *explicit* sort: data components are moved *)
DeleteDuplicates[Sort[data]] (* {{1,2},{2,3},{3,4},{3,5},{3,6},{5,6}} *)
Take the first element of dupInvIndir
, 3, it means that the first element of the (implicitely) sorted data array is data[[3]]
, ( -> {1,2}
).
This can be compared to the explicit DeleteDuplicate[Sort[data]]
performance-tuning vector permutation coding-style
performance-tuning vector permutation coding-style
edited yesterday
Picaud Vincent
asked yesterday
Picaud VincentPicaud Vincent
1,065517
1,065517
3
$begingroup$
It would be somewhat easier with some context on what you actually try to achieve there...
$endgroup$
– Henrik Schumacher
yesterday
$begingroup$
@HenrikSchumacher please holds on, I will add more context
$endgroup$
– Picaud Vincent
yesterday
add a comment |
3
$begingroup$
It would be somewhat easier with some context on what you actually try to achieve there...
$endgroup$
– Henrik Schumacher
yesterday
$begingroup$
@HenrikSchumacher please holds on, I will add more context
$endgroup$
– Picaud Vincent
yesterday
3
3
$begingroup$
It would be somewhat easier with some context on what you actually try to achieve there...
$endgroup$
– Henrik Schumacher
yesterday
$begingroup$
It would be somewhat easier with some context on what you actually try to achieve there...
$endgroup$
– Henrik Schumacher
yesterday
$begingroup$
@HenrikSchumacher please holds on, I will add more context
$endgroup$
– Picaud Vincent
yesterday
$begingroup$
@HenrikSchumacher please holds on, I will add more context
$endgroup$
– Picaud Vincent
yesterday
add a comment |
1 Answer
1
active
oldest
votes
$begingroup$
Apparently, you try to apply a permutation given by list indirection
to a vector duplicate
.
Here are several ways to do it, each along with its timing:
n = 1000000;
indirection = RandomSample[Range[n], n];
duplicate = RandomInteger[{-n, n}, n];
First@RepeatedTiming[
result0 = createDupInvIndir[indirection, duplicate];
]
First@RepeatedTiming[
result1 = ConstantArray[0, Length[duplicate]];
result1[[indirection]] = duplicate;
]
First@RepeatedTiming[
result2 =
Normal@SparseArray[Partition[indirection, 1] -> duplicate,Length[duplicate]];
]
First@RepeatedTiming[
result3 = duplicate[[InversePermutation@indirection]];
]
result0 == result1 == result2 == result3
1.799
0.012
0.016
0.015
True
This is another one of the many examples that highlights why For
should not be used (in uncompiled code).
$endgroup$
$begingroup$
Thanks for this quick answer, I already had the Normal @ SparseArray solution in mind but I eliminated it because I had the feeling it was not optimal concerning efficiency (a lot of manupilation, rules, array etc..). I did not know about the ToPackedArray package, thanks! (and yes indirection is a permutation of [1..Length[duplicate]])
$endgroup$
– Picaud Vincent
yesterday
$begingroup$
The benchmark you just added confirms my feeling about perfs. Thanks a lot
$endgroup$
– Picaud Vincent
yesterday
1
$begingroup$
You're welcome.Developer`ToPackedArray
is useful if you handle unpacked arrays that could be packed (with pure machine integers or machine precision numbers (real or complex)). Of course, it is always better never to produce any unpacked arrays.Developer`PackedArrayQ
lets you check whether an array is packed or not. I removed the use ofDeveloper`ToPackedArray
in my answer sinceRandomSample
andRandomInteger
are guaranteed to produce packed arrays (if the occurring integers are not too large).
$endgroup$
– Henrik Schumacher
yesterday
1
$begingroup$
For
and the like can be quite useful. They are no substitute when alternatives exist that are vectorized though.
$endgroup$
– Daniel Lichtblau
yesterday
$begingroup$
It might be worth nothing that replacing theFor
loop with aDo
loop directly gives you a 25% speedup, without doing anything fancy. Also, it seems you've accidentally deleted the definition ofToPack
from your answer...
$endgroup$
– Lukas Lang
yesterday
|
show 1 more comment
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
Apparently, you try to apply a permutation given by list indirection
to a vector duplicate
.
Here are several ways to do it, each along with its timing:
n = 1000000;
indirection = RandomSample[Range[n], n];
duplicate = RandomInteger[{-n, n}, n];
First@RepeatedTiming[
result0 = createDupInvIndir[indirection, duplicate];
]
First@RepeatedTiming[
result1 = ConstantArray[0, Length[duplicate]];
result1[[indirection]] = duplicate;
]
First@RepeatedTiming[
result2 =
Normal@SparseArray[Partition[indirection, 1] -> duplicate,Length[duplicate]];
]
First@RepeatedTiming[
result3 = duplicate[[InversePermutation@indirection]];
]
result0 == result1 == result2 == result3
1.799
0.012
0.016
0.015
True
This is another one of the many examples that highlights why For
should not be used (in uncompiled code).
$endgroup$
$begingroup$
Thanks for this quick answer, I already had the Normal @ SparseArray solution in mind but I eliminated it because I had the feeling it was not optimal concerning efficiency (a lot of manupilation, rules, array etc..). I did not know about the ToPackedArray package, thanks! (and yes indirection is a permutation of [1..Length[duplicate]])
$endgroup$
– Picaud Vincent
yesterday
$begingroup$
The benchmark you just added confirms my feeling about perfs. Thanks a lot
$endgroup$
– Picaud Vincent
yesterday
1
$begingroup$
You're welcome.Developer`ToPackedArray
is useful if you handle unpacked arrays that could be packed (with pure machine integers or machine precision numbers (real or complex)). Of course, it is always better never to produce any unpacked arrays.Developer`PackedArrayQ
lets you check whether an array is packed or not. I removed the use ofDeveloper`ToPackedArray
in my answer sinceRandomSample
andRandomInteger
are guaranteed to produce packed arrays (if the occurring integers are not too large).
$endgroup$
– Henrik Schumacher
yesterday
1
$begingroup$
For
and the like can be quite useful. They are no substitute when alternatives exist that are vectorized though.
$endgroup$
– Daniel Lichtblau
yesterday
$begingroup$
It might be worth nothing that replacing theFor
loop with aDo
loop directly gives you a 25% speedup, without doing anything fancy. Also, it seems you've accidentally deleted the definition ofToPack
from your answer...
$endgroup$
– Lukas Lang
yesterday
|
show 1 more comment
$begingroup$
Apparently, you try to apply a permutation given by list indirection
to a vector duplicate
.
Here are several ways to do it, each along with its timing:
n = 1000000;
indirection = RandomSample[Range[n], n];
duplicate = RandomInteger[{-n, n}, n];
First@RepeatedTiming[
result0 = createDupInvIndir[indirection, duplicate];
]
First@RepeatedTiming[
result1 = ConstantArray[0, Length[duplicate]];
result1[[indirection]] = duplicate;
]
First@RepeatedTiming[
result2 =
Normal@SparseArray[Partition[indirection, 1] -> duplicate,Length[duplicate]];
]
First@RepeatedTiming[
result3 = duplicate[[InversePermutation@indirection]];
]
result0 == result1 == result2 == result3
1.799
0.012
0.016
0.015
True
This is another one of the many examples that highlights why For
should not be used (in uncompiled code).
$endgroup$
$begingroup$
Thanks for this quick answer, I already had the Normal @ SparseArray solution in mind but I eliminated it because I had the feeling it was not optimal concerning efficiency (a lot of manupilation, rules, array etc..). I did not know about the ToPackedArray package, thanks! (and yes indirection is a permutation of [1..Length[duplicate]])
$endgroup$
– Picaud Vincent
yesterday
$begingroup$
The benchmark you just added confirms my feeling about perfs. Thanks a lot
$endgroup$
– Picaud Vincent
yesterday
1
$begingroup$
You're welcome.Developer`ToPackedArray
is useful if you handle unpacked arrays that could be packed (with pure machine integers or machine precision numbers (real or complex)). Of course, it is always better never to produce any unpacked arrays.Developer`PackedArrayQ
lets you check whether an array is packed or not. I removed the use ofDeveloper`ToPackedArray
in my answer sinceRandomSample
andRandomInteger
are guaranteed to produce packed arrays (if the occurring integers are not too large).
$endgroup$
– Henrik Schumacher
yesterday
1
$begingroup$
For
and the like can be quite useful. They are no substitute when alternatives exist that are vectorized though.
$endgroup$
– Daniel Lichtblau
yesterday
$begingroup$
It might be worth nothing that replacing theFor
loop with aDo
loop directly gives you a 25% speedup, without doing anything fancy. Also, it seems you've accidentally deleted the definition ofToPack
from your answer...
$endgroup$
– Lukas Lang
yesterday
|
show 1 more comment
$begingroup$
Apparently, you try to apply a permutation given by list indirection
to a vector duplicate
.
Here are several ways to do it, each along with its timing:
n = 1000000;
indirection = RandomSample[Range[n], n];
duplicate = RandomInteger[{-n, n}, n];
First@RepeatedTiming[
result0 = createDupInvIndir[indirection, duplicate];
]
First@RepeatedTiming[
result1 = ConstantArray[0, Length[duplicate]];
result1[[indirection]] = duplicate;
]
First@RepeatedTiming[
result2 =
Normal@SparseArray[Partition[indirection, 1] -> duplicate,Length[duplicate]];
]
First@RepeatedTiming[
result3 = duplicate[[InversePermutation@indirection]];
]
result0 == result1 == result2 == result3
1.799
0.012
0.016
0.015
True
This is another one of the many examples that highlights why For
should not be used (in uncompiled code).
$endgroup$
Apparently, you try to apply a permutation given by list indirection
to a vector duplicate
.
Here are several ways to do it, each along with its timing:
n = 1000000;
indirection = RandomSample[Range[n], n];
duplicate = RandomInteger[{-n, n}, n];
First@RepeatedTiming[
result0 = createDupInvIndir[indirection, duplicate];
]
First@RepeatedTiming[
result1 = ConstantArray[0, Length[duplicate]];
result1[[indirection]] = duplicate;
]
First@RepeatedTiming[
result2 =
Normal@SparseArray[Partition[indirection, 1] -> duplicate,Length[duplicate]];
]
First@RepeatedTiming[
result3 = duplicate[[InversePermutation@indirection]];
]
result0 == result1 == result2 == result3
1.799
0.012
0.016
0.015
True
This is another one of the many examples that highlights why For
should not be used (in uncompiled code).
edited yesterday
answered yesterday
Henrik SchumacherHenrik Schumacher
51.9k469146
51.9k469146
$begingroup$
Thanks for this quick answer, I already had the Normal @ SparseArray solution in mind but I eliminated it because I had the feeling it was not optimal concerning efficiency (a lot of manupilation, rules, array etc..). I did not know about the ToPackedArray package, thanks! (and yes indirection is a permutation of [1..Length[duplicate]])
$endgroup$
– Picaud Vincent
yesterday
$begingroup$
The benchmark you just added confirms my feeling about perfs. Thanks a lot
$endgroup$
– Picaud Vincent
yesterday
1
$begingroup$
You're welcome.Developer`ToPackedArray
is useful if you handle unpacked arrays that could be packed (with pure machine integers or machine precision numbers (real or complex)). Of course, it is always better never to produce any unpacked arrays.Developer`PackedArrayQ
lets you check whether an array is packed or not. I removed the use ofDeveloper`ToPackedArray
in my answer sinceRandomSample
andRandomInteger
are guaranteed to produce packed arrays (if the occurring integers are not too large).
$endgroup$
– Henrik Schumacher
yesterday
1
$begingroup$
For
and the like can be quite useful. They are no substitute when alternatives exist that are vectorized though.
$endgroup$
– Daniel Lichtblau
yesterday
$begingroup$
It might be worth nothing that replacing theFor
loop with aDo
loop directly gives you a 25% speedup, without doing anything fancy. Also, it seems you've accidentally deleted the definition ofToPack
from your answer...
$endgroup$
– Lukas Lang
yesterday
|
show 1 more comment
$begingroup$
Thanks for this quick answer, I already had the Normal @ SparseArray solution in mind but I eliminated it because I had the feeling it was not optimal concerning efficiency (a lot of manupilation, rules, array etc..). I did not know about the ToPackedArray package, thanks! (and yes indirection is a permutation of [1..Length[duplicate]])
$endgroup$
– Picaud Vincent
yesterday
$begingroup$
The benchmark you just added confirms my feeling about perfs. Thanks a lot
$endgroup$
– Picaud Vincent
yesterday
1
$begingroup$
You're welcome.Developer`ToPackedArray
is useful if you handle unpacked arrays that could be packed (with pure machine integers or machine precision numbers (real or complex)). Of course, it is always better never to produce any unpacked arrays.Developer`PackedArrayQ
lets you check whether an array is packed or not. I removed the use ofDeveloper`ToPackedArray
in my answer sinceRandomSample
andRandomInteger
are guaranteed to produce packed arrays (if the occurring integers are not too large).
$endgroup$
– Henrik Schumacher
yesterday
1
$begingroup$
For
and the like can be quite useful. They are no substitute when alternatives exist that are vectorized though.
$endgroup$
– Daniel Lichtblau
yesterday
$begingroup$
It might be worth nothing that replacing theFor
loop with aDo
loop directly gives you a 25% speedup, without doing anything fancy. Also, it seems you've accidentally deleted the definition ofToPack
from your answer...
$endgroup$
– Lukas Lang
yesterday
$begingroup$
Thanks for this quick answer, I already had the Normal @ SparseArray solution in mind but I eliminated it because I had the feeling it was not optimal concerning efficiency (a lot of manupilation, rules, array etc..). I did not know about the ToPackedArray package, thanks! (and yes indirection is a permutation of [1..Length[duplicate]])
$endgroup$
– Picaud Vincent
yesterday
$begingroup$
Thanks for this quick answer, I already had the Normal @ SparseArray solution in mind but I eliminated it because I had the feeling it was not optimal concerning efficiency (a lot of manupilation, rules, array etc..). I did not know about the ToPackedArray package, thanks! (and yes indirection is a permutation of [1..Length[duplicate]])
$endgroup$
– Picaud Vincent
yesterday
$begingroup$
The benchmark you just added confirms my feeling about perfs. Thanks a lot
$endgroup$
– Picaud Vincent
yesterday
$begingroup$
The benchmark you just added confirms my feeling about perfs. Thanks a lot
$endgroup$
– Picaud Vincent
yesterday
1
1
$begingroup$
You're welcome.
Developer`ToPackedArray
is useful if you handle unpacked arrays that could be packed (with pure machine integers or machine precision numbers (real or complex)). Of course, it is always better never to produce any unpacked arrays. Developer`PackedArrayQ
lets you check whether an array is packed or not. I removed the use of Developer`ToPackedArray
in my answer since RandomSample
and RandomInteger
are guaranteed to produce packed arrays (if the occurring integers are not too large).$endgroup$
– Henrik Schumacher
yesterday
$begingroup$
You're welcome.
Developer`ToPackedArray
is useful if you handle unpacked arrays that could be packed (with pure machine integers or machine precision numbers (real or complex)). Of course, it is always better never to produce any unpacked arrays. Developer`PackedArrayQ
lets you check whether an array is packed or not. I removed the use of Developer`ToPackedArray
in my answer since RandomSample
and RandomInteger
are guaranteed to produce packed arrays (if the occurring integers are not too large).$endgroup$
– Henrik Schumacher
yesterday
1
1
$begingroup$
For
and the like can be quite useful. They are no substitute when alternatives exist that are vectorized though.$endgroup$
– Daniel Lichtblau
yesterday
$begingroup$
For
and the like can be quite useful. They are no substitute when alternatives exist that are vectorized though.$endgroup$
– Daniel Lichtblau
yesterday
$begingroup$
It might be worth nothing that replacing the
For
loop with a Do
loop directly gives you a 25% speedup, without doing anything fancy. Also, it seems you've accidentally deleted the definition of ToPack
from your answer...$endgroup$
– Lukas Lang
yesterday
$begingroup$
It might be worth nothing that replacing the
For
loop with a Do
loop directly gives you a 25% speedup, without doing anything fancy. Also, it seems you've accidentally deleted the definition of ToPack
from your answer...$endgroup$
– Lukas Lang
yesterday
|
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$begingroup$
It would be somewhat easier with some context on what you actually try to achieve there...
$endgroup$
– Henrik Schumacher
yesterday
$begingroup$
@HenrikSchumacher please holds on, I will add more context
$endgroup$
– Picaud Vincent
yesterday