Improving Map Function on Lists

Question

Dealing with spectral data (2D lists) where offsets (corresponding 1D list) must be removed from each individual spectrum. Looking for feedback on improvements over my current method.

    offset = {53.0617, 52.5185, 53.2469, 52.8025, 53.2716, 53.284, 53.2716, 53.6049, 53.5062, 53.642};

    data = {{-0.0617284, -1.51852, -2.24691, -1.80247, -2.2716, -0.283951, -2.2716, -4.60494, -2.50617, -2.64198}, {0.938272, -1.51852, -0.246914, 0.197531, -0.271605, 0.716049, 1.7284, 0.395062, -0.506173, 1.35802}, {-0.0617284, 0.481481, -0.246914, 0.197531, -0.271605, -0.283951, -1.2716, -2.60494, -2.50617, -0.641975}, {-4.06173, -3.51852, -2.24691, -1.80247, -2.2716, -2.28395, -2.2716, -2.60494, -2.50617, -0.641975}, {-0.0617284, -1.51852, -2.24691, -1.80247, -2.2716, -2.28395, -2.2716, -2.60494, -2.50617, -4.64198}, {-2.06173, -1.51852, -0.246914, 0.197531, -2.2716, -2.28395, -1.2716, -0.604938, -0.506173, -2.64198}, {-4.06173, -3.51852, -2.24691, -3.80247, -4.2716, -3.28395, -2.2716, -3.60494, -4.50617, -4.64198}, {-3.06173, -3.51852, -2.24691, -3.80247, -3.2716, -2.28395, -2.2716, -3.60494, -4.50617, -2.64198}, {-2.06173, -3.51852, -2.24691, -3.80247, -3.2716, -2.28395, -2.2716, -2.60494, -2.50617, -4.64198}, {-1.06173, -3.51852, -2.24691, -1.80247, -4.2716, -3.28395, -1.2716, -0.604938, -0.506173, -0.641975}};

I currently always use the following MMA code snippet for processing.

    data = (# - offset) & /@ data;

Is there a better use of Thread, Map, etc. that may be considered? The data sets typically include 1000's of spectra each 1000-2000 points long. So 2D list with some million values.

Answer 1

{n, m} = {10^4, 10^4};
offset = RandomReal[1, n];

data = RandomReal[1, {m, n}];

cf = Compile[{{v, _Real, 1}, {offset, _Real, 1}}, 
   Table[v[[i]] - offset[[i]], {i, Length[v]}],
   RuntimeAttributes -> {Listable}, CompilationTarget -> "C", 
   RuntimeOptions -> "Speed"];

r1 = (# - offset) & /@ data; // RepeatedTiming
r2 = Plus[data, ConstantArray[-offset, m]]; // RepeatedTiming
r3 = ArrayReshape[Outer[Plus, Developer`ToPackedArray@{-offset}, data, 1], 
      {m, n}]; // RepeatedTiming
r4 = cf[data, offset]; // RepeatedTiming

r1 == r2 == r3 == r4

Output

{1.08, Null}

{0.557, Null}

{0.233, Null}

{0.20, Null}

True

Answer 2

A slightly faster method uses KroneckerProduct to create a suitable matrix of offsets. Some data:

{n, m} = {10^4, 10^4};
offset = RandomReal[100, n];
data = RandomReal[100, {m, n}];

Your method:

r1 = (#-offset)& /@ data; //AbsoluteTiming

{1.80568, Null}

Using KroneckerProduct:

r2 = data + KroneckerProduct[ConstantArray[-1., m], offset]; //AbsoluteTiming

{0.830738, Null}

Check:

r1 == r2

True

Answer 3

The Map version looks efficient compared with MapThread.

data2 = Flatten[ConstantArray[data, 100000], 1];
First[Timing[data3 = (# - offset) & /@ data2;]]

0.384383

First[Timing[
  data4 = MapThread[
     Plus, {data2, -ConstantArray[offset, Length[data2]]}];]]

2.80672

data3 == data4

True