Can this be solved even faster?
$begingroup$
So I would like to solve the following set of equation for $m_i$ given a set of ${M_m,N_m}$.
$$
m_1 +m_2 +m_3 +m_4 =M_m \
|m_1| +|m_2| +|m_3| +|m_4| =N_m
$$
All variables are integers.
Also $N_m ge M_m$ and their maximum value can reach up-to 30.
I only need the total number of possible solution not the solutions themselves. So my first trivial attempt was to just use Solve
dimNM1[Nm_, Mm_] :=
Length[(Solve[m1 + m2 + m3 + m4 == Mm &&
Abs[m1] + Abs[m2] + Abs[m3] + Abs[m4] == Nm, {m1, m2, m3, m4}, Integers])]
My second slightly non-trivial attempt is the following:-
dimNM2[Nm_, Mm_] :=
Which[Nm === Mm,
Length[Partition[
Flatten[Permutations /@ IntegerPartitions[Nm, {4}, Range[0, Nm]]],
4]], True,
Module[{res},
res = Partition[
Flatten[Permutations /@ IntegerPartitions[Mm, {4}, Range[-Nm, Nm]]],
4];
Length[
Select[res, (Abs[#[[1]]] + Abs[#[[2]]] + Abs[#[[3]]] +
Abs[#[[4]]]) == Nm &]]]]
The second method is much faster than the first specially for $N_m=M_m$.
But I would like to increase the speed further for $N_mge M_m$ case if possible.
dimNM1[2, 2] // AbsoluteTiming
(*{0.177768, 10}*)
dimNM2[2, 2] // AbsoluteTiming
(*{0.0000899056, 10}*)
So is there any other way to solve these equation faster?
equation-solving performance-tuning
$endgroup$
add a comment |
$begingroup$
So I would like to solve the following set of equation for $m_i$ given a set of ${M_m,N_m}$.
$$
m_1 +m_2 +m_3 +m_4 =M_m \
|m_1| +|m_2| +|m_3| +|m_4| =N_m
$$
All variables are integers.
Also $N_m ge M_m$ and their maximum value can reach up-to 30.
I only need the total number of possible solution not the solutions themselves. So my first trivial attempt was to just use Solve
dimNM1[Nm_, Mm_] :=
Length[(Solve[m1 + m2 + m3 + m4 == Mm &&
Abs[m1] + Abs[m2] + Abs[m3] + Abs[m4] == Nm, {m1, m2, m3, m4}, Integers])]
My second slightly non-trivial attempt is the following:-
dimNM2[Nm_, Mm_] :=
Which[Nm === Mm,
Length[Partition[
Flatten[Permutations /@ IntegerPartitions[Nm, {4}, Range[0, Nm]]],
4]], True,
Module[{res},
res = Partition[
Flatten[Permutations /@ IntegerPartitions[Mm, {4}, Range[-Nm, Nm]]],
4];
Length[
Select[res, (Abs[#[[1]]] + Abs[#[[2]]] + Abs[#[[3]]] +
Abs[#[[4]]]) == Nm &]]]]
The second method is much faster than the first specially for $N_m=M_m$.
But I would like to increase the speed further for $N_mge M_m$ case if possible.
dimNM1[2, 2] // AbsoluteTiming
(*{0.177768, 10}*)
dimNM2[2, 2] // AbsoluteTiming
(*{0.0000899056, 10}*)
So is there any other way to solve these equation faster?
equation-solving performance-tuning
$endgroup$
$begingroup$
Note thatN
has built-in meanings.
$endgroup$
– Αλέξανδρος Ζεγγ
Dec 9 '18 at 12:34
$begingroup$
OK I have changed it.
$endgroup$
– Hubble07
Dec 9 '18 at 12:46
$begingroup$
Nice problem. No need to generate candidates... see my reply.
$endgroup$
– ciao
Dec 10 '18 at 8:13
add a comment |
$begingroup$
So I would like to solve the following set of equation for $m_i$ given a set of ${M_m,N_m}$.
$$
m_1 +m_2 +m_3 +m_4 =M_m \
|m_1| +|m_2| +|m_3| +|m_4| =N_m
$$
All variables are integers.
Also $N_m ge M_m$ and their maximum value can reach up-to 30.
I only need the total number of possible solution not the solutions themselves. So my first trivial attempt was to just use Solve
dimNM1[Nm_, Mm_] :=
Length[(Solve[m1 + m2 + m3 + m4 == Mm &&
Abs[m1] + Abs[m2] + Abs[m3] + Abs[m4] == Nm, {m1, m2, m3, m4}, Integers])]
My second slightly non-trivial attempt is the following:-
dimNM2[Nm_, Mm_] :=
Which[Nm === Mm,
Length[Partition[
Flatten[Permutations /@ IntegerPartitions[Nm, {4}, Range[0, Nm]]],
4]], True,
Module[{res},
res = Partition[
Flatten[Permutations /@ IntegerPartitions[Mm, {4}, Range[-Nm, Nm]]],
4];
Length[
Select[res, (Abs[#[[1]]] + Abs[#[[2]]] + Abs[#[[3]]] +
Abs[#[[4]]]) == Nm &]]]]
The second method is much faster than the first specially for $N_m=M_m$.
But I would like to increase the speed further for $N_mge M_m$ case if possible.
dimNM1[2, 2] // AbsoluteTiming
(*{0.177768, 10}*)
dimNM2[2, 2] // AbsoluteTiming
(*{0.0000899056, 10}*)
So is there any other way to solve these equation faster?
equation-solving performance-tuning
$endgroup$
So I would like to solve the following set of equation for $m_i$ given a set of ${M_m,N_m}$.
$$
m_1 +m_2 +m_3 +m_4 =M_m \
|m_1| +|m_2| +|m_3| +|m_4| =N_m
$$
All variables are integers.
Also $N_m ge M_m$ and their maximum value can reach up-to 30.
I only need the total number of possible solution not the solutions themselves. So my first trivial attempt was to just use Solve
dimNM1[Nm_, Mm_] :=
Length[(Solve[m1 + m2 + m3 + m4 == Mm &&
Abs[m1] + Abs[m2] + Abs[m3] + Abs[m4] == Nm, {m1, m2, m3, m4}, Integers])]
My second slightly non-trivial attempt is the following:-
dimNM2[Nm_, Mm_] :=
Which[Nm === Mm,
Length[Partition[
Flatten[Permutations /@ IntegerPartitions[Nm, {4}, Range[0, Nm]]],
4]], True,
Module[{res},
res = Partition[
Flatten[Permutations /@ IntegerPartitions[Mm, {4}, Range[-Nm, Nm]]],
4];
Length[
Select[res, (Abs[#[[1]]] + Abs[#[[2]]] + Abs[#[[3]]] +
Abs[#[[4]]]) == Nm &]]]]
The second method is much faster than the first specially for $N_m=M_m$.
But I would like to increase the speed further for $N_mge M_m$ case if possible.
dimNM1[2, 2] // AbsoluteTiming
(*{0.177768, 10}*)
dimNM2[2, 2] // AbsoluteTiming
(*{0.0000899056, 10}*)
So is there any other way to solve these equation faster?
equation-solving performance-tuning
equation-solving performance-tuning
edited Dec 9 '18 at 13:00
Henrik Schumacher
51.3k469146
51.3k469146
asked Dec 9 '18 at 11:40
Hubble07Hubble07
2,988721
2,988721
$begingroup$
Note thatN
has built-in meanings.
$endgroup$
– Αλέξανδρος Ζεγγ
Dec 9 '18 at 12:34
$begingroup$
OK I have changed it.
$endgroup$
– Hubble07
Dec 9 '18 at 12:46
$begingroup$
Nice problem. No need to generate candidates... see my reply.
$endgroup$
– ciao
Dec 10 '18 at 8:13
add a comment |
$begingroup$
Note thatN
has built-in meanings.
$endgroup$
– Αλέξανδρος Ζεγγ
Dec 9 '18 at 12:34
$begingroup$
OK I have changed it.
$endgroup$
– Hubble07
Dec 9 '18 at 12:46
$begingroup$
Nice problem. No need to generate candidates... see my reply.
$endgroup$
– ciao
Dec 10 '18 at 8:13
$begingroup$
Note that
N
has built-in meanings.$endgroup$
– Αλέξανδρος Ζεγγ
Dec 9 '18 at 12:34
$begingroup$
Note that
N
has built-in meanings.$endgroup$
– Αλέξανδρος Ζεγγ
Dec 9 '18 at 12:34
$begingroup$
OK I have changed it.
$endgroup$
– Hubble07
Dec 9 '18 at 12:46
$begingroup$
OK I have changed it.
$endgroup$
– Hubble07
Dec 9 '18 at 12:46
$begingroup$
Nice problem. No need to generate candidates... see my reply.
$endgroup$
– ciao
Dec 10 '18 at 8:13
$begingroup$
Nice problem. No need to generate candidates... see my reply.
$endgroup$
– ciao
Dec 10 '18 at 8:13
add a comment |
4 Answers
4
active
oldest
votes
$begingroup$
ClearAll[num];
num[n_, m_] /; OddQ[n + m] = 0;
num[n_, n_] := Binomial[n + 3, 3];
num[n_, m_] /; OddQ[n] := With[{z = Ceiling[m/2]}, (5*n^2 + 3)/2 + 2 z - (2 z^2)];
num[n_, m_] /; EvenQ[n] := With[{z = Ceiling[m/2]}, (5*n^2 + 4)/2 - (2 z^2)];
Testing vs fastest answer here at writing (Henrik Schumacher):
stop = 100;
res = Table[{n, m, dimNM3[n, m]}, {n, 1, stop}, {m, 1, n}]; // AbsoluteTiming//First
res2 = Table[{n, m, num[n, m]}, {n, 1, stop}, {m, 1, n}]; // AbsoluteTiming//First
res == res2
169.203
0.0219434
True
Large cases are a non-issue:
num[123423456, 123412348] // AbsoluteTiming
{0.0000247977, 30468069908023290}
Some quick timings:
$endgroup$
3
$begingroup$
Pretty impressive. Would you mind to elaborate where these formulas come from or at least to provide an (accessible) source?
$endgroup$
– Henrik Schumacher
Dec 10 '18 at 8:49
3
$begingroup$
@HenrikSchumacher - I derived them, looking at a set of results: I recognized the pattern(s). Neat that the tetrahedral numbers and coordination sequences popped out. See e.g. Sloan, "Low-Dimensional Lattices VII: Coordination Sequences".
$endgroup$
– ciao
Dec 10 '18 at 9:29
2
$begingroup$
Chapeaux for recognizing the patterns! =D
$endgroup$
– Henrik Schumacher
Dec 10 '18 at 10:14
3
$begingroup$
@ciao - You Sir are a genius. Thank you.
$endgroup$
– Hubble07
Dec 10 '18 at 14:02
1
$begingroup$
Answers from ciao are generally great reads, +1.
$endgroup$
– Marius Ladegård Meyer
Dec 11 '18 at 14:19
add a comment |
$begingroup$
It is more efficient to first pick the integer partitions whose absolute values sum up to n
before generating the permutations.
dimNM3[n_, m_] := Total[
Map[
Length@*Permutations,
Pick[#, Abs[#].ConstantArray[1, 4], n] &[
IntegerPartitions[m, {4}, Range[-n, n]
]
]
]
];
m = 20;
n = 40;
dimNM1[n, m] // AbsoluteTiming
dimNM2[n, m] // AbsoluteTiming
dimNM3[n, m] // AbsoluteTiming
{0.116977, 3802}
{0.995365, 3802}
{0.005579, 3802}
$endgroup$
add a comment |
$begingroup$
Sorry for not knowing much Mathematica, but I have a Python solution you might be able to follow. I'm putting this on the community wiki for anyone who wants to translate it.
def count_solutions(Nm, Mm):
firsthalves = dict()
for m1 in range(-Nm,Nm+1):
for m2 in range(-Nm,Nm+1):
m = m1+m2
n = abs(m1)+abs(m2)
key = (m,n)
if key in firsthalves:
firsthalves[key] += 1
else:
firsthalves[key] = 1
solutions = 0
for m3 in range(-Nm,Nm+1):
for m4 in range(-Nm,Nm+1):
m = m3+m4
n = abs(m3)+abs(m4)
key = (Mm-m, Nm-n)
if key in firsthalves:
solutions += firsthalves[key]
return solutions
This is a meet in the middle strategy. I enumerate all the possible $m1,m2$ combinations and record how many times each $m1+m2,|m1|+|m2|$ combination occurs in a dictionary.
Then I go through all the possible $m3,m4$ combinations and for each combination I calculate the necessary $m1+m2,|m1|+|m2|$ combination to make $Mm,Nm$, and I refer to the dictionary to find out how many $m1,m2$ combinations can make that.
The difference is that you go through the $m1,m2$ combination then the $m3,m4$ combinations, and the number of operations is roughly a square root of going through every $m1,m2,m3,m4$ combination. You should be able to solve for $Nm = 1000,Mn = 0$ in a few seconds.
$endgroup$
add a comment |
$begingroup$
A different approach, tied to @Hubble7's other question, that has the same speed as @ciao's answer. The key is in noting the sum of the negative numbers and sum of the nonnegative numbers are each fixed values, and so it is just a counting problem when we have 1 negative and 3 nonnegative terms, then 2 and 2, then 3 and 1. We can then use Mathematica's NumberOfCompositions[ ]
function.
For values of Mn
and Nn
define
pos = (Nn+Mn)/2
neg = (Nn-Mn)/2
where pos
is the sum of the positive numbers in {m1, m2, m3, m4}
and neg
is the sum of the absolute value of the negatives ( so it is a positive number).
Now use Mathematica's NumberOfCompositions[n, k ]
function which gives you the count of all of the ways to divide integer n
into k
terms, including 0
terms. If we want to find the number of compositions not including 0
terms we calculate NumberOfCompositions[n - k, k]
.
Note that for k=1
, we have NumberOfCompositions[n, 1] = 1
If we have k
negative terms, then we have Binomial[4,k]
ways to arrange them. This is just {4, 6, 4}
for k = {1, 2, 3}
So for values of neg
and pos
perms = 4 * NumberOfCompositions[pos, 3]
+ 6 NumberOfCompositions[neg - 2, 2] NumberOfCompositions[pos, 2]
+ 4 NumberOfCompositions[neg - 3, 3]
And finally converting it into a function that accepts Mn
and Nm
( while stealing some code from @ciao)
numNew[n_, m_] /; OddQ[n + m] = 0;
numNew[n_, n_] := Binomial[n + 3, 3];
numNew[n_, m_] := 4*NumberOfCompositions[(n + m)/2, 3]
+ 6*NumberOfCompositions[(n - m)/2 - 2, 2] NumberOfCompositions[(n + m)/2, 2]
+ 4*NumberOfCompositions[(n - m)/2 - 3, 3]
Check the timing against @ciao's answer above
num[123423456, 123412348] // AbsoluteTiming
{0.0000390021, 30468069908023290}
my function
numNew[123423456, 123412348] // AbsoluteTiming
{0.0000369493, 30468069908023290}
It is about as fast as @ciao's and also suggests (to me!) an approach to this question:
Find position without iterating
$endgroup$
add a comment |
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4 Answers
4
active
oldest
votes
4 Answers
4
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
ClearAll[num];
num[n_, m_] /; OddQ[n + m] = 0;
num[n_, n_] := Binomial[n + 3, 3];
num[n_, m_] /; OddQ[n] := With[{z = Ceiling[m/2]}, (5*n^2 + 3)/2 + 2 z - (2 z^2)];
num[n_, m_] /; EvenQ[n] := With[{z = Ceiling[m/2]}, (5*n^2 + 4)/2 - (2 z^2)];
Testing vs fastest answer here at writing (Henrik Schumacher):
stop = 100;
res = Table[{n, m, dimNM3[n, m]}, {n, 1, stop}, {m, 1, n}]; // AbsoluteTiming//First
res2 = Table[{n, m, num[n, m]}, {n, 1, stop}, {m, 1, n}]; // AbsoluteTiming//First
res == res2
169.203
0.0219434
True
Large cases are a non-issue:
num[123423456, 123412348] // AbsoluteTiming
{0.0000247977, 30468069908023290}
Some quick timings:
$endgroup$
3
$begingroup$
Pretty impressive. Would you mind to elaborate where these formulas come from or at least to provide an (accessible) source?
$endgroup$
– Henrik Schumacher
Dec 10 '18 at 8:49
3
$begingroup$
@HenrikSchumacher - I derived them, looking at a set of results: I recognized the pattern(s). Neat that the tetrahedral numbers and coordination sequences popped out. See e.g. Sloan, "Low-Dimensional Lattices VII: Coordination Sequences".
$endgroup$
– ciao
Dec 10 '18 at 9:29
2
$begingroup$
Chapeaux for recognizing the patterns! =D
$endgroup$
– Henrik Schumacher
Dec 10 '18 at 10:14
3
$begingroup$
@ciao - You Sir are a genius. Thank you.
$endgroup$
– Hubble07
Dec 10 '18 at 14:02
1
$begingroup$
Answers from ciao are generally great reads, +1.
$endgroup$
– Marius Ladegård Meyer
Dec 11 '18 at 14:19
add a comment |
$begingroup$
ClearAll[num];
num[n_, m_] /; OddQ[n + m] = 0;
num[n_, n_] := Binomial[n + 3, 3];
num[n_, m_] /; OddQ[n] := With[{z = Ceiling[m/2]}, (5*n^2 + 3)/2 + 2 z - (2 z^2)];
num[n_, m_] /; EvenQ[n] := With[{z = Ceiling[m/2]}, (5*n^2 + 4)/2 - (2 z^2)];
Testing vs fastest answer here at writing (Henrik Schumacher):
stop = 100;
res = Table[{n, m, dimNM3[n, m]}, {n, 1, stop}, {m, 1, n}]; // AbsoluteTiming//First
res2 = Table[{n, m, num[n, m]}, {n, 1, stop}, {m, 1, n}]; // AbsoluteTiming//First
res == res2
169.203
0.0219434
True
Large cases are a non-issue:
num[123423456, 123412348] // AbsoluteTiming
{0.0000247977, 30468069908023290}
Some quick timings:
$endgroup$
3
$begingroup$
Pretty impressive. Would you mind to elaborate where these formulas come from or at least to provide an (accessible) source?
$endgroup$
– Henrik Schumacher
Dec 10 '18 at 8:49
3
$begingroup$
@HenrikSchumacher - I derived them, looking at a set of results: I recognized the pattern(s). Neat that the tetrahedral numbers and coordination sequences popped out. See e.g. Sloan, "Low-Dimensional Lattices VII: Coordination Sequences".
$endgroup$
– ciao
Dec 10 '18 at 9:29
2
$begingroup$
Chapeaux for recognizing the patterns! =D
$endgroup$
– Henrik Schumacher
Dec 10 '18 at 10:14
3
$begingroup$
@ciao - You Sir are a genius. Thank you.
$endgroup$
– Hubble07
Dec 10 '18 at 14:02
1
$begingroup$
Answers from ciao are generally great reads, +1.
$endgroup$
– Marius Ladegård Meyer
Dec 11 '18 at 14:19
add a comment |
$begingroup$
ClearAll[num];
num[n_, m_] /; OddQ[n + m] = 0;
num[n_, n_] := Binomial[n + 3, 3];
num[n_, m_] /; OddQ[n] := With[{z = Ceiling[m/2]}, (5*n^2 + 3)/2 + 2 z - (2 z^2)];
num[n_, m_] /; EvenQ[n] := With[{z = Ceiling[m/2]}, (5*n^2 + 4)/2 - (2 z^2)];
Testing vs fastest answer here at writing (Henrik Schumacher):
stop = 100;
res = Table[{n, m, dimNM3[n, m]}, {n, 1, stop}, {m, 1, n}]; // AbsoluteTiming//First
res2 = Table[{n, m, num[n, m]}, {n, 1, stop}, {m, 1, n}]; // AbsoluteTiming//First
res == res2
169.203
0.0219434
True
Large cases are a non-issue:
num[123423456, 123412348] // AbsoluteTiming
{0.0000247977, 30468069908023290}
Some quick timings:
$endgroup$
ClearAll[num];
num[n_, m_] /; OddQ[n + m] = 0;
num[n_, n_] := Binomial[n + 3, 3];
num[n_, m_] /; OddQ[n] := With[{z = Ceiling[m/2]}, (5*n^2 + 3)/2 + 2 z - (2 z^2)];
num[n_, m_] /; EvenQ[n] := With[{z = Ceiling[m/2]}, (5*n^2 + 4)/2 - (2 z^2)];
Testing vs fastest answer here at writing (Henrik Schumacher):
stop = 100;
res = Table[{n, m, dimNM3[n, m]}, {n, 1, stop}, {m, 1, n}]; // AbsoluteTiming//First
res2 = Table[{n, m, num[n, m]}, {n, 1, stop}, {m, 1, n}]; // AbsoluteTiming//First
res == res2
169.203
0.0219434
True
Large cases are a non-issue:
num[123423456, 123412348] // AbsoluteTiming
{0.0000247977, 30468069908023290}
Some quick timings:
edited Dec 10 '18 at 10:19
answered Dec 10 '18 at 8:11
ciaociao
17.3k138109
17.3k138109
3
$begingroup$
Pretty impressive. Would you mind to elaborate where these formulas come from or at least to provide an (accessible) source?
$endgroup$
– Henrik Schumacher
Dec 10 '18 at 8:49
3
$begingroup$
@HenrikSchumacher - I derived them, looking at a set of results: I recognized the pattern(s). Neat that the tetrahedral numbers and coordination sequences popped out. See e.g. Sloan, "Low-Dimensional Lattices VII: Coordination Sequences".
$endgroup$
– ciao
Dec 10 '18 at 9:29
2
$begingroup$
Chapeaux for recognizing the patterns! =D
$endgroup$
– Henrik Schumacher
Dec 10 '18 at 10:14
3
$begingroup$
@ciao - You Sir are a genius. Thank you.
$endgroup$
– Hubble07
Dec 10 '18 at 14:02
1
$begingroup$
Answers from ciao are generally great reads, +1.
$endgroup$
– Marius Ladegård Meyer
Dec 11 '18 at 14:19
add a comment |
3
$begingroup$
Pretty impressive. Would you mind to elaborate where these formulas come from or at least to provide an (accessible) source?
$endgroup$
– Henrik Schumacher
Dec 10 '18 at 8:49
3
$begingroup$
@HenrikSchumacher - I derived them, looking at a set of results: I recognized the pattern(s). Neat that the tetrahedral numbers and coordination sequences popped out. See e.g. Sloan, "Low-Dimensional Lattices VII: Coordination Sequences".
$endgroup$
– ciao
Dec 10 '18 at 9:29
2
$begingroup$
Chapeaux for recognizing the patterns! =D
$endgroup$
– Henrik Schumacher
Dec 10 '18 at 10:14
3
$begingroup$
@ciao - You Sir are a genius. Thank you.
$endgroup$
– Hubble07
Dec 10 '18 at 14:02
1
$begingroup$
Answers from ciao are generally great reads, +1.
$endgroup$
– Marius Ladegård Meyer
Dec 11 '18 at 14:19
3
3
$begingroup$
Pretty impressive. Would you mind to elaborate where these formulas come from or at least to provide an (accessible) source?
$endgroup$
– Henrik Schumacher
Dec 10 '18 at 8:49
$begingroup$
Pretty impressive. Would you mind to elaborate where these formulas come from or at least to provide an (accessible) source?
$endgroup$
– Henrik Schumacher
Dec 10 '18 at 8:49
3
3
$begingroup$
@HenrikSchumacher - I derived them, looking at a set of results: I recognized the pattern(s). Neat that the tetrahedral numbers and coordination sequences popped out. See e.g. Sloan, "Low-Dimensional Lattices VII: Coordination Sequences".
$endgroup$
– ciao
Dec 10 '18 at 9:29
$begingroup$
@HenrikSchumacher - I derived them, looking at a set of results: I recognized the pattern(s). Neat that the tetrahedral numbers and coordination sequences popped out. See e.g. Sloan, "Low-Dimensional Lattices VII: Coordination Sequences".
$endgroup$
– ciao
Dec 10 '18 at 9:29
2
2
$begingroup$
Chapeaux for recognizing the patterns! =D
$endgroup$
– Henrik Schumacher
Dec 10 '18 at 10:14
$begingroup$
Chapeaux for recognizing the patterns! =D
$endgroup$
– Henrik Schumacher
Dec 10 '18 at 10:14
3
3
$begingroup$
@ciao - You Sir are a genius. Thank you.
$endgroup$
– Hubble07
Dec 10 '18 at 14:02
$begingroup$
@ciao - You Sir are a genius. Thank you.
$endgroup$
– Hubble07
Dec 10 '18 at 14:02
1
1
$begingroup$
Answers from ciao are generally great reads, +1.
$endgroup$
– Marius Ladegård Meyer
Dec 11 '18 at 14:19
$begingroup$
Answers from ciao are generally great reads, +1.
$endgroup$
– Marius Ladegård Meyer
Dec 11 '18 at 14:19
add a comment |
$begingroup$
It is more efficient to first pick the integer partitions whose absolute values sum up to n
before generating the permutations.
dimNM3[n_, m_] := Total[
Map[
Length@*Permutations,
Pick[#, Abs[#].ConstantArray[1, 4], n] &[
IntegerPartitions[m, {4}, Range[-n, n]
]
]
]
];
m = 20;
n = 40;
dimNM1[n, m] // AbsoluteTiming
dimNM2[n, m] // AbsoluteTiming
dimNM3[n, m] // AbsoluteTiming
{0.116977, 3802}
{0.995365, 3802}
{0.005579, 3802}
$endgroup$
add a comment |
$begingroup$
It is more efficient to first pick the integer partitions whose absolute values sum up to n
before generating the permutations.
dimNM3[n_, m_] := Total[
Map[
Length@*Permutations,
Pick[#, Abs[#].ConstantArray[1, 4], n] &[
IntegerPartitions[m, {4}, Range[-n, n]
]
]
]
];
m = 20;
n = 40;
dimNM1[n, m] // AbsoluteTiming
dimNM2[n, m] // AbsoluteTiming
dimNM3[n, m] // AbsoluteTiming
{0.116977, 3802}
{0.995365, 3802}
{0.005579, 3802}
$endgroup$
add a comment |
$begingroup$
It is more efficient to first pick the integer partitions whose absolute values sum up to n
before generating the permutations.
dimNM3[n_, m_] := Total[
Map[
Length@*Permutations,
Pick[#, Abs[#].ConstantArray[1, 4], n] &[
IntegerPartitions[m, {4}, Range[-n, n]
]
]
]
];
m = 20;
n = 40;
dimNM1[n, m] // AbsoluteTiming
dimNM2[n, m] // AbsoluteTiming
dimNM3[n, m] // AbsoluteTiming
{0.116977, 3802}
{0.995365, 3802}
{0.005579, 3802}
$endgroup$
It is more efficient to first pick the integer partitions whose absolute values sum up to n
before generating the permutations.
dimNM3[n_, m_] := Total[
Map[
Length@*Permutations,
Pick[#, Abs[#].ConstantArray[1, 4], n] &[
IntegerPartitions[m, {4}, Range[-n, n]
]
]
]
];
m = 20;
n = 40;
dimNM1[n, m] // AbsoluteTiming
dimNM2[n, m] // AbsoluteTiming
dimNM3[n, m] // AbsoluteTiming
{0.116977, 3802}
{0.995365, 3802}
{0.005579, 3802}
edited Dec 10 '18 at 8:45
answered Dec 9 '18 at 13:20
Henrik SchumacherHenrik Schumacher
51.3k469146
51.3k469146
add a comment |
add a comment |
$begingroup$
Sorry for not knowing much Mathematica, but I have a Python solution you might be able to follow. I'm putting this on the community wiki for anyone who wants to translate it.
def count_solutions(Nm, Mm):
firsthalves = dict()
for m1 in range(-Nm,Nm+1):
for m2 in range(-Nm,Nm+1):
m = m1+m2
n = abs(m1)+abs(m2)
key = (m,n)
if key in firsthalves:
firsthalves[key] += 1
else:
firsthalves[key] = 1
solutions = 0
for m3 in range(-Nm,Nm+1):
for m4 in range(-Nm,Nm+1):
m = m3+m4
n = abs(m3)+abs(m4)
key = (Mm-m, Nm-n)
if key in firsthalves:
solutions += firsthalves[key]
return solutions
This is a meet in the middle strategy. I enumerate all the possible $m1,m2$ combinations and record how many times each $m1+m2,|m1|+|m2|$ combination occurs in a dictionary.
Then I go through all the possible $m3,m4$ combinations and for each combination I calculate the necessary $m1+m2,|m1|+|m2|$ combination to make $Mm,Nm$, and I refer to the dictionary to find out how many $m1,m2$ combinations can make that.
The difference is that you go through the $m1,m2$ combination then the $m3,m4$ combinations, and the number of operations is roughly a square root of going through every $m1,m2,m3,m4$ combination. You should be able to solve for $Nm = 1000,Mn = 0$ in a few seconds.
$endgroup$
add a comment |
$begingroup$
Sorry for not knowing much Mathematica, but I have a Python solution you might be able to follow. I'm putting this on the community wiki for anyone who wants to translate it.
def count_solutions(Nm, Mm):
firsthalves = dict()
for m1 in range(-Nm,Nm+1):
for m2 in range(-Nm,Nm+1):
m = m1+m2
n = abs(m1)+abs(m2)
key = (m,n)
if key in firsthalves:
firsthalves[key] += 1
else:
firsthalves[key] = 1
solutions = 0
for m3 in range(-Nm,Nm+1):
for m4 in range(-Nm,Nm+1):
m = m3+m4
n = abs(m3)+abs(m4)
key = (Mm-m, Nm-n)
if key in firsthalves:
solutions += firsthalves[key]
return solutions
This is a meet in the middle strategy. I enumerate all the possible $m1,m2$ combinations and record how many times each $m1+m2,|m1|+|m2|$ combination occurs in a dictionary.
Then I go through all the possible $m3,m4$ combinations and for each combination I calculate the necessary $m1+m2,|m1|+|m2|$ combination to make $Mm,Nm$, and I refer to the dictionary to find out how many $m1,m2$ combinations can make that.
The difference is that you go through the $m1,m2$ combination then the $m3,m4$ combinations, and the number of operations is roughly a square root of going through every $m1,m2,m3,m4$ combination. You should be able to solve for $Nm = 1000,Mn = 0$ in a few seconds.
$endgroup$
add a comment |
$begingroup$
Sorry for not knowing much Mathematica, but I have a Python solution you might be able to follow. I'm putting this on the community wiki for anyone who wants to translate it.
def count_solutions(Nm, Mm):
firsthalves = dict()
for m1 in range(-Nm,Nm+1):
for m2 in range(-Nm,Nm+1):
m = m1+m2
n = abs(m1)+abs(m2)
key = (m,n)
if key in firsthalves:
firsthalves[key] += 1
else:
firsthalves[key] = 1
solutions = 0
for m3 in range(-Nm,Nm+1):
for m4 in range(-Nm,Nm+1):
m = m3+m4
n = abs(m3)+abs(m4)
key = (Mm-m, Nm-n)
if key in firsthalves:
solutions += firsthalves[key]
return solutions
This is a meet in the middle strategy. I enumerate all the possible $m1,m2$ combinations and record how many times each $m1+m2,|m1|+|m2|$ combination occurs in a dictionary.
Then I go through all the possible $m3,m4$ combinations and for each combination I calculate the necessary $m1+m2,|m1|+|m2|$ combination to make $Mm,Nm$, and I refer to the dictionary to find out how many $m1,m2$ combinations can make that.
The difference is that you go through the $m1,m2$ combination then the $m3,m4$ combinations, and the number of operations is roughly a square root of going through every $m1,m2,m3,m4$ combination. You should be able to solve for $Nm = 1000,Mn = 0$ in a few seconds.
$endgroup$
Sorry for not knowing much Mathematica, but I have a Python solution you might be able to follow. I'm putting this on the community wiki for anyone who wants to translate it.
def count_solutions(Nm, Mm):
firsthalves = dict()
for m1 in range(-Nm,Nm+1):
for m2 in range(-Nm,Nm+1):
m = m1+m2
n = abs(m1)+abs(m2)
key = (m,n)
if key in firsthalves:
firsthalves[key] += 1
else:
firsthalves[key] = 1
solutions = 0
for m3 in range(-Nm,Nm+1):
for m4 in range(-Nm,Nm+1):
m = m3+m4
n = abs(m3)+abs(m4)
key = (Mm-m, Nm-n)
if key in firsthalves:
solutions += firsthalves[key]
return solutions
This is a meet in the middle strategy. I enumerate all the possible $m1,m2$ combinations and record how many times each $m1+m2,|m1|+|m2|$ combination occurs in a dictionary.
Then I go through all the possible $m3,m4$ combinations and for each combination I calculate the necessary $m1+m2,|m1|+|m2|$ combination to make $Mm,Nm$, and I refer to the dictionary to find out how many $m1,m2$ combinations can make that.
The difference is that you go through the $m1,m2$ combination then the $m3,m4$ combinations, and the number of operations is roughly a square root of going through every $m1,m2,m3,m4$ combination. You should be able to solve for $Nm = 1000,Mn = 0$ in a few seconds.
edited Dec 9 '18 at 23:42
community wiki
2 revs
James Hollis
add a comment |
add a comment |
$begingroup$
A different approach, tied to @Hubble7's other question, that has the same speed as @ciao's answer. The key is in noting the sum of the negative numbers and sum of the nonnegative numbers are each fixed values, and so it is just a counting problem when we have 1 negative and 3 nonnegative terms, then 2 and 2, then 3 and 1. We can then use Mathematica's NumberOfCompositions[ ]
function.
For values of Mn
and Nn
define
pos = (Nn+Mn)/2
neg = (Nn-Mn)/2
where pos
is the sum of the positive numbers in {m1, m2, m3, m4}
and neg
is the sum of the absolute value of the negatives ( so it is a positive number).
Now use Mathematica's NumberOfCompositions[n, k ]
function which gives you the count of all of the ways to divide integer n
into k
terms, including 0
terms. If we want to find the number of compositions not including 0
terms we calculate NumberOfCompositions[n - k, k]
.
Note that for k=1
, we have NumberOfCompositions[n, 1] = 1
If we have k
negative terms, then we have Binomial[4,k]
ways to arrange them. This is just {4, 6, 4}
for k = {1, 2, 3}
So for values of neg
and pos
perms = 4 * NumberOfCompositions[pos, 3]
+ 6 NumberOfCompositions[neg - 2, 2] NumberOfCompositions[pos, 2]
+ 4 NumberOfCompositions[neg - 3, 3]
And finally converting it into a function that accepts Mn
and Nm
( while stealing some code from @ciao)
numNew[n_, m_] /; OddQ[n + m] = 0;
numNew[n_, n_] := Binomial[n + 3, 3];
numNew[n_, m_] := 4*NumberOfCompositions[(n + m)/2, 3]
+ 6*NumberOfCompositions[(n - m)/2 - 2, 2] NumberOfCompositions[(n + m)/2, 2]
+ 4*NumberOfCompositions[(n - m)/2 - 3, 3]
Check the timing against @ciao's answer above
num[123423456, 123412348] // AbsoluteTiming
{0.0000390021, 30468069908023290}
my function
numNew[123423456, 123412348] // AbsoluteTiming
{0.0000369493, 30468069908023290}
It is about as fast as @ciao's and also suggests (to me!) an approach to this question:
Find position without iterating
$endgroup$
add a comment |
$begingroup$
A different approach, tied to @Hubble7's other question, that has the same speed as @ciao's answer. The key is in noting the sum of the negative numbers and sum of the nonnegative numbers are each fixed values, and so it is just a counting problem when we have 1 negative and 3 nonnegative terms, then 2 and 2, then 3 and 1. We can then use Mathematica's NumberOfCompositions[ ]
function.
For values of Mn
and Nn
define
pos = (Nn+Mn)/2
neg = (Nn-Mn)/2
where pos
is the sum of the positive numbers in {m1, m2, m3, m4}
and neg
is the sum of the absolute value of the negatives ( so it is a positive number).
Now use Mathematica's NumberOfCompositions[n, k ]
function which gives you the count of all of the ways to divide integer n
into k
terms, including 0
terms. If we want to find the number of compositions not including 0
terms we calculate NumberOfCompositions[n - k, k]
.
Note that for k=1
, we have NumberOfCompositions[n, 1] = 1
If we have k
negative terms, then we have Binomial[4,k]
ways to arrange them. This is just {4, 6, 4}
for k = {1, 2, 3}
So for values of neg
and pos
perms = 4 * NumberOfCompositions[pos, 3]
+ 6 NumberOfCompositions[neg - 2, 2] NumberOfCompositions[pos, 2]
+ 4 NumberOfCompositions[neg - 3, 3]
And finally converting it into a function that accepts Mn
and Nm
( while stealing some code from @ciao)
numNew[n_, m_] /; OddQ[n + m] = 0;
numNew[n_, n_] := Binomial[n + 3, 3];
numNew[n_, m_] := 4*NumberOfCompositions[(n + m)/2, 3]
+ 6*NumberOfCompositions[(n - m)/2 - 2, 2] NumberOfCompositions[(n + m)/2, 2]
+ 4*NumberOfCompositions[(n - m)/2 - 3, 3]
Check the timing against @ciao's answer above
num[123423456, 123412348] // AbsoluteTiming
{0.0000390021, 30468069908023290}
my function
numNew[123423456, 123412348] // AbsoluteTiming
{0.0000369493, 30468069908023290}
It is about as fast as @ciao's and also suggests (to me!) an approach to this question:
Find position without iterating
$endgroup$
add a comment |
$begingroup$
A different approach, tied to @Hubble7's other question, that has the same speed as @ciao's answer. The key is in noting the sum of the negative numbers and sum of the nonnegative numbers are each fixed values, and so it is just a counting problem when we have 1 negative and 3 nonnegative terms, then 2 and 2, then 3 and 1. We can then use Mathematica's NumberOfCompositions[ ]
function.
For values of Mn
and Nn
define
pos = (Nn+Mn)/2
neg = (Nn-Mn)/2
where pos
is the sum of the positive numbers in {m1, m2, m3, m4}
and neg
is the sum of the absolute value of the negatives ( so it is a positive number).
Now use Mathematica's NumberOfCompositions[n, k ]
function which gives you the count of all of the ways to divide integer n
into k
terms, including 0
terms. If we want to find the number of compositions not including 0
terms we calculate NumberOfCompositions[n - k, k]
.
Note that for k=1
, we have NumberOfCompositions[n, 1] = 1
If we have k
negative terms, then we have Binomial[4,k]
ways to arrange them. This is just {4, 6, 4}
for k = {1, 2, 3}
So for values of neg
and pos
perms = 4 * NumberOfCompositions[pos, 3]
+ 6 NumberOfCompositions[neg - 2, 2] NumberOfCompositions[pos, 2]
+ 4 NumberOfCompositions[neg - 3, 3]
And finally converting it into a function that accepts Mn
and Nm
( while stealing some code from @ciao)
numNew[n_, m_] /; OddQ[n + m] = 0;
numNew[n_, n_] := Binomial[n + 3, 3];
numNew[n_, m_] := 4*NumberOfCompositions[(n + m)/2, 3]
+ 6*NumberOfCompositions[(n - m)/2 - 2, 2] NumberOfCompositions[(n + m)/2, 2]
+ 4*NumberOfCompositions[(n - m)/2 - 3, 3]
Check the timing against @ciao's answer above
num[123423456, 123412348] // AbsoluteTiming
{0.0000390021, 30468069908023290}
my function
numNew[123423456, 123412348] // AbsoluteTiming
{0.0000369493, 30468069908023290}
It is about as fast as @ciao's and also suggests (to me!) an approach to this question:
Find position without iterating
$endgroup$
A different approach, tied to @Hubble7's other question, that has the same speed as @ciao's answer. The key is in noting the sum of the negative numbers and sum of the nonnegative numbers are each fixed values, and so it is just a counting problem when we have 1 negative and 3 nonnegative terms, then 2 and 2, then 3 and 1. We can then use Mathematica's NumberOfCompositions[ ]
function.
For values of Mn
and Nn
define
pos = (Nn+Mn)/2
neg = (Nn-Mn)/2
where pos
is the sum of the positive numbers in {m1, m2, m3, m4}
and neg
is the sum of the absolute value of the negatives ( so it is a positive number).
Now use Mathematica's NumberOfCompositions[n, k ]
function which gives you the count of all of the ways to divide integer n
into k
terms, including 0
terms. If we want to find the number of compositions not including 0
terms we calculate NumberOfCompositions[n - k, k]
.
Note that for k=1
, we have NumberOfCompositions[n, 1] = 1
If we have k
negative terms, then we have Binomial[4,k]
ways to arrange them. This is just {4, 6, 4}
for k = {1, 2, 3}
So for values of neg
and pos
perms = 4 * NumberOfCompositions[pos, 3]
+ 6 NumberOfCompositions[neg - 2, 2] NumberOfCompositions[pos, 2]
+ 4 NumberOfCompositions[neg - 3, 3]
And finally converting it into a function that accepts Mn
and Nm
( while stealing some code from @ciao)
numNew[n_, m_] /; OddQ[n + m] = 0;
numNew[n_, n_] := Binomial[n + 3, 3];
numNew[n_, m_] := 4*NumberOfCompositions[(n + m)/2, 3]
+ 6*NumberOfCompositions[(n - m)/2 - 2, 2] NumberOfCompositions[(n + m)/2, 2]
+ 4*NumberOfCompositions[(n - m)/2 - 3, 3]
Check the timing against @ciao's answer above
num[123423456, 123412348] // AbsoluteTiming
{0.0000390021, 30468069908023290}
my function
numNew[123423456, 123412348] // AbsoluteTiming
{0.0000369493, 30468069908023290}
It is about as fast as @ciao's and also suggests (to me!) an approach to this question:
Find position without iterating
edited Jan 2 at 17:12
answered Jan 2 at 17:04
MikeYMikeY
2,477412
2,477412
add a comment |
add a comment |
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$begingroup$
Note that
N
has built-in meanings.$endgroup$
– Αλέξανδρος Ζεγγ
Dec 9 '18 at 12:34
$begingroup$
OK I have changed it.
$endgroup$
– Hubble07
Dec 9 '18 at 12:46
$begingroup$
Nice problem. No need to generate candidates... see my reply.
$endgroup$
– ciao
Dec 10 '18 at 8:13