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 at 12:34










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










  • Nice problem. No need to generate candidates... see my reply.
    – ciao
    Dec 10 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 at 12:34










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










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














12












12








12


1





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 at 13:00









Henrik Schumacher

48.6k467139




48.6k467139










asked Dec 9 at 11:40









Hubble07

2,977719




2,977719












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










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










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


















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










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










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
















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




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












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




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












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




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










3 Answers
3






active

oldest

votes


















12














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 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 at 9:29






  • 2




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






  • 3




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






  • 1




    Answers from ciao are generally great reads, +1.
    – Marius Ladegård Meyer
    Dec 11 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























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      3 Answers
      3






      active

      oldest

      votes








      3 Answers
      3






      active

      oldest

      votes









      active

      oldest

      votes






      active

      oldest

      votes









      12














      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 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 at 9:29






      • 2




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






      • 3




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






      • 1




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
















      12














      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 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 at 9:29






      • 2




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






      • 3




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






      • 1




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














      12












      12








      12






      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 at 10:19

























      answered Dec 10 at 8:11









      ciao

      17.3k138108




      17.3k138108








      • 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 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 at 9:29






      • 2




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






      • 3




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






      • 1




        Answers from ciao are generally great reads, +1.
        – Marius Ladegård Meyer
        Dec 11 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 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 at 9:29






      • 2




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






      • 3




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






      • 1




        Answers from ciao are generally great reads, +1.
        – Marius Ladegård Meyer
        Dec 11 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 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 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 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 at 9:29




      2




      2




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




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




      3




      3




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




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




      1




      1




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




      Answers from ciao are generally great reads, +1.
      – Marius Ladegård Meyer
      Dec 11 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 at 8:45

























          answered Dec 9 at 13:20









          Henrik Schumacher

          48.6k467139




          48.6k467139























              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 at 23:42


























                  community wiki





                  2 revs
                  James Hollis































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