Can this be solved even faster?












12














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?










share|improve this question
























  • Note that N has built-in meanings.
    – Αλέξανδρος Ζεγγ
    Dec 9 '18 at 12:34










  • OK I have changed it.
    – Hubble07
    Dec 9 '18 at 12:46










  • Nice problem. No need to generate candidates... see my reply.
    – ciao
    Dec 10 '18 at 8:13
















12














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?










share|improve this question
























  • Note that N has built-in meanings.
    – Αλέξανδρος Ζεγγ
    Dec 9 '18 at 12:34










  • OK I have changed it.
    – Hubble07
    Dec 9 '18 at 12:46










  • Nice problem. No need to generate candidates... see my reply.
    – ciao
    Dec 10 '18 at 8:13














12












12








12


2





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?










share|improve this question















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






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited Dec 9 '18 at 13:00









Henrik Schumacher

49.2k467139




49.2k467139










asked Dec 9 '18 at 11:40









Hubble07

2,902720




2,902720












  • Note that N has built-in meanings.
    – Αλέξανδρος Ζεγγ
    Dec 9 '18 at 12:34










  • OK I have changed it.
    – Hubble07
    Dec 9 '18 at 12:46










  • Nice problem. No need to generate candidates... see my reply.
    – ciao
    Dec 10 '18 at 8:13


















  • Note that N has built-in meanings.
    – Αλέξανδρος Ζεγγ
    Dec 9 '18 at 12:34










  • OK I have changed it.
    – Hubble07
    Dec 9 '18 at 12:46










  • Nice problem. No need to generate candidates... see my reply.
    – ciao
    Dec 10 '18 at 8:13
















Note that N has built-in meanings.
– Αλέξανδρος Ζεγγ
Dec 9 '18 at 12:34




Note that N has built-in meanings.
– Αλέξανδρος Ζεγγ
Dec 9 '18 at 12:34












OK I have changed it.
– Hubble07
Dec 9 '18 at 12:46




OK I have changed it.
– Hubble07
Dec 9 '18 at 12:46












Nice problem. No need to generate candidates... see my reply.
– ciao
Dec 10 '18 at 8:13




Nice problem. No need to generate candidates... see my reply.
– ciao
Dec 10 '18 at 8:13










4 Answers
4






active

oldest

votes


















13














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:



enter image description here






share|improve this answer



















  • 3




    Pretty impressive. Would you mind to elaborate where these formulas come from or at least to provide an (accessible) source?
    – Henrik Schumacher
    Dec 10 '18 at 8:49








  • 3




    @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".
    – ciao
    Dec 10 '18 at 9:29






  • 2




    Chapeaux for recognizing the patterns! =D
    – Henrik Schumacher
    Dec 10 '18 at 10:14






  • 3




    @ciao - You Sir are a genius. Thank you.
    – Hubble07
    Dec 10 '18 at 14:02






  • 1




    Answers from ciao are generally great reads, +1.
    – Marius Ladegård Meyer
    Dec 11 '18 at 14:19



















13














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}







share|improve this answer































    2














    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.






    share|improve this answer































      2














      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 posis 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






      share|improve this answer























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        4 Answers
        4






        active

        oldest

        votes








        4 Answers
        4






        active

        oldest

        votes









        active

        oldest

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        active

        oldest

        votes









        13














        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:



        enter image description here






        share|improve this answer



















        • 3




          Pretty impressive. Would you mind to elaborate where these formulas come from or at least to provide an (accessible) source?
          – Henrik Schumacher
          Dec 10 '18 at 8:49








        • 3




          @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".
          – ciao
          Dec 10 '18 at 9:29






        • 2




          Chapeaux for recognizing the patterns! =D
          – Henrik Schumacher
          Dec 10 '18 at 10:14






        • 3




          @ciao - You Sir are a genius. Thank you.
          – Hubble07
          Dec 10 '18 at 14:02






        • 1




          Answers from ciao are generally great reads, +1.
          – Marius Ladegård Meyer
          Dec 11 '18 at 14:19
















        13














        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:



        enter image description here






        share|improve this answer



















        • 3




          Pretty impressive. Would you mind to elaborate where these formulas come from or at least to provide an (accessible) source?
          – Henrik Schumacher
          Dec 10 '18 at 8:49








        • 3




          @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".
          – ciao
          Dec 10 '18 at 9:29






        • 2




          Chapeaux for recognizing the patterns! =D
          – Henrik Schumacher
          Dec 10 '18 at 10:14






        • 3




          @ciao - You Sir are a genius. Thank you.
          – Hubble07
          Dec 10 '18 at 14:02






        • 1




          Answers from ciao are generally great reads, +1.
          – Marius Ladegård Meyer
          Dec 11 '18 at 14:19














        13












        13








        13






        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:



        enter image description here






        share|improve this answer














        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:



        enter image description here







        share|improve this answer














        share|improve this answer



        share|improve this answer








        edited Dec 10 '18 at 10:19

























        answered Dec 10 '18 at 8:11









        ciao

        17.3k138109




        17.3k138109








        • 3




          Pretty impressive. Would you mind to elaborate where these formulas come from or at least to provide an (accessible) source?
          – Henrik Schumacher
          Dec 10 '18 at 8:49








        • 3




          @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".
          – ciao
          Dec 10 '18 at 9:29






        • 2




          Chapeaux for recognizing the patterns! =D
          – Henrik Schumacher
          Dec 10 '18 at 10:14






        • 3




          @ciao - You Sir are a genius. Thank you.
          – Hubble07
          Dec 10 '18 at 14:02






        • 1




          Answers from ciao are generally great reads, +1.
          – Marius Ladegård Meyer
          Dec 11 '18 at 14:19














        • 3




          Pretty impressive. Would you mind to elaborate where these formulas come from or at least to provide an (accessible) source?
          – Henrik Schumacher
          Dec 10 '18 at 8:49








        • 3




          @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".
          – ciao
          Dec 10 '18 at 9:29






        • 2




          Chapeaux for recognizing the patterns! =D
          – Henrik Schumacher
          Dec 10 '18 at 10:14






        • 3




          @ciao - You Sir are a genius. Thank you.
          – Hubble07
          Dec 10 '18 at 14:02






        • 1




          Answers from ciao are generally great reads, +1.
          – Marius Ladegård Meyer
          Dec 11 '18 at 14:19








        3




        3




        Pretty impressive. Would you mind to elaborate where these formulas come from or at least to provide an (accessible) source?
        – Henrik Schumacher
        Dec 10 '18 at 8:49






        Pretty impressive. Would you mind to elaborate where these formulas come from or at least to provide an (accessible) source?
        – Henrik Schumacher
        Dec 10 '18 at 8:49






        3




        3




        @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".
        – ciao
        Dec 10 '18 at 9:29




        @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".
        – ciao
        Dec 10 '18 at 9:29




        2




        2




        Chapeaux for recognizing the patterns! =D
        – Henrik Schumacher
        Dec 10 '18 at 10:14




        Chapeaux for recognizing the patterns! =D
        – Henrik Schumacher
        Dec 10 '18 at 10:14




        3




        3




        @ciao - You Sir are a genius. Thank you.
        – Hubble07
        Dec 10 '18 at 14:02




        @ciao - You Sir are a genius. Thank you.
        – Hubble07
        Dec 10 '18 at 14:02




        1




        1




        Answers from ciao are generally great reads, +1.
        – Marius Ladegård Meyer
        Dec 11 '18 at 14:19




        Answers from ciao are generally great reads, +1.
        – Marius Ladegård Meyer
        Dec 11 '18 at 14:19











        13














        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}







        share|improve this answer




























          13














          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}







          share|improve this answer


























            13












            13








            13






            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}







            share|improve this answer














            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}








            share|improve this answer














            share|improve this answer



            share|improve this answer








            edited Dec 10 '18 at 8:45

























            answered Dec 9 '18 at 13:20









            Henrik Schumacher

            49.2k467139




            49.2k467139























                2














                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.






                share|improve this answer




























                  2














                  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.






                  share|improve this answer


























                    2












                    2








                    2






                    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.






                    share|improve this answer














                    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.







                    share|improve this answer














                    share|improve this answer



                    share|improve this answer








                    edited Dec 9 '18 at 23:42


























                    community wiki





                    2 revs
                    James Hollis
























                        2














                        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 posis 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






                        share|improve this answer




























                          2














                          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 posis 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






                          share|improve this answer


























                            2












                            2








                            2






                            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 posis 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






                            share|improve this answer














                            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 posis 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







                            share|improve this answer














                            share|improve this answer



                            share|improve this answer








                            edited 2 days ago

























                            answered 2 days ago









                            MikeY

                            2,097410




                            2,097410






























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