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fix whitespace in distances table
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README.md

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@@ -146,12 +146,12 @@ Each distance corresponds to a distance type. The type name and the correspondin
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| GenKLDivergence | `gkl_divergence(x, y)` | `sum(p .* log(p ./ q) - p + q)` |
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| RenyiDivergence | `renyi_divergence(p, q, k)`| `log(sum( p .* (p ./ q) .^ (k - 1))) / (k - 1)` |
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| JSDivergence | `js_divergence(p, q)` | `KL(p, m) / 2 + KL(p, m) / 2 with m = (p + q) / 2` |
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| SpanNormDist | `spannorm_dist(x, y)` | `max(x - y) - min(x - y )` |
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| SpanNormDist | `spannorm_dist(x, y)` | `max(x - y) - min(x - y)` |
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| BhattacharyyaDist | `bhattacharyya(x, y)` | `-log(sum(sqrt(x .* y) / sqrt(sum(x) * sum(y)))` |
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| HellingerDist | `hellinger(x, y) ` | `sqrt(1 - sum(sqrt(x .* y) / sqrt(sum(x) * sum(y))))` |
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| Haversine | `haversine(x, y, r)` | [Haversine formula](https://en.wikipedia.org/wiki/Haversine_formula) |
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| Mahalanobis | `mahalanobis(x, y, Q)` | `sqrt((x - y)' * Q * (x - y))` |
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| SqMahalanobis | `sqmahalanobis(x, y, Q)` | ` (x - y)' * Q * (x - y)` |
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| SqMahalanobis | `sqmahalanobis(x, y, Q)` | `(x - y)' * Q * (x - y)` |
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| MeanAbsDeviation | `meanad(x, y)` | `mean(abs.(x - y))` |
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| MeanSqDeviation | `msd(x, y)` | `mean(abs2.(x - y))` |
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| RMSDeviation | `rmsd(x, y)` | `sqrt(msd(x, y))` |
@@ -194,9 +194,9 @@ julia> pairwise(Euclidean(1e-12), x, x)
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## Benchmarks
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The implementation has been carefully optimized based on benchmarks. The script in `benchmark/benchmarks.jl` defines a benchmark suite
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for a variety of distances, under column-wise and pairwise settings.
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The implementation has been carefully optimized based on benchmarks. The script in `benchmark/benchmarks.jl` defines a benchmark suite
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for a variety of distances, under column-wise and pairwise settings.
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Here are benchmarks obtained running Julia 0.6 on a computer with a quad-core Intel Core i5-2500K processor @ 3.3 GHz.
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The tables below can be replicated using the script in `benchmark/print_table.jl`.
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