我认为原始代码缓慢的原因是因为Coefficient
即使使用非常大的表达式也可以工作 - 如果天真地扩展这些表达式将不适合内存。
这是原始多项式:
poly[q_, x_] := Product[Sum[ x^(j*Prime[i]),
{j, 0, Floor[q/Prime[i]]}], {i, 1, PrimePi[q]}]
看看如果不是太大q
,扩展多项式会占用更多内存并且变得相当慢:
In[2]:= Through[{LeafCount, ByteCount}[poly[300, x]]] // Timing
Through[{LeafCount, ByteCount}[Expand@poly[300, x]]] // Timing
Out[2]= { 0.01, { 1859, 55864}}
Out[3]= {25.27, {77368, 3175840}}
现在让我们以 3 种不同的方式定义系数并为它们计时
coeff[q_] := Module[{x}, Coefficient[poly[q, x], x, q]]
exCoeff[q_] := Module[{x}, Coefficient[Expand@poly[q, x], x, q]]
serCoeff[q_] := Module[{x}, SeriesCoefficient[poly[q, x], {x, 0, q}]]
In[7]:= Table[ coeff[q],{q,1,30}]//Timing
Table[ exCoeff[q],{q,1,30}]//Timing
Table[serCoeff[q],{q,1,30}]//Timing
Out[7]= {0.37,{0,1,1,1,2,2,3,3,4,5,6,7,9,10,12,14,17,19,23,26,30,35,40,46,52,60,67,77,87,98}}
Out[8]= {0.12,{0,1,1,1,2,2,3,3,4,5,6,7,9,10,12,14,17,19,23,26,30,35,40,46,52,60,67,77,87,98}}
Out[9]= {0.06,{0,1,1,1,2,2,3,3,4,5,6,7,9,10,12,14,17,19,23,26,30,35,40,46,52,60,67,77,87,98}}
In[10]:= coeff[100]//Timing
exCoeff[100]//Timing
serCoeff[100]//Timing
Out[10]= {56.28,40899}
Out[11]= { 0.84,40899}
Out[12]= { 0.06,40899}
所以SeriesCoefficient
绝对是要走的路。当然,除非您在组合数学方面比我好一点,并且您知道以下素数分区公式(oeis)
In[13]:= CoefficientList[Series[1/Product[1-x^Prime[i],{i,1,30}],{x,0,30}],x]
Out[13]= {1,0,1,1,1,2,2,3,3,4,5,6,7,9,10,12,14,17,19,23,26,30,35,40,46,52,60,67,77,87,98}
In[14]:= f[n_]:=Length@IntegerPartitions[n,All,Prime@Range@PrimePi@n]; Array[f,30]
Out[14]= {0,1,1,1,2,2,3,3,4,5,6,7,9,10,12,14,17,19,23,26,30,35,40,46,52,60,67,77,87,98}