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Corrections for Julia 0.6.0 #13

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Jul 20, 2017
Merged

Corrections for Julia 0.6.0 #13

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5126191
Julia 0.6.0
Goysa2 Jul 17, 2017
677a461
corrections for Julia 0.6.0
Goysa2 Jul 19, 2017
0a3ef2f
Corrections for Julia 0.6.0 with NaNMath
Goysa2 Jul 19, 2017
920c9f0
Corrections for Julia 0.6.0 with NaNMath
Goysa2 Jul 19, 2017
1d24673
Corrections for Julia 0.6.0 with NaNMath
Goysa2 Jul 19, 2017
92073ae
Corrections for Julia 0.6.0 with NaNMath
Goysa2 Jul 19, 2017
00da5ce
NaNMath added to REQUIRE
Goysa2 Jul 19, 2017
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3 changes: 3 additions & 0 deletions REQUIRE
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Original file line number Diff line number Diff line change
@@ -1,2 +1,5 @@
julia 0.5
Plots

julia 0.6
Plots, NaNMath
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Just add NaNMath to the list on line 3.

2 changes: 1 addition & 1 deletion src/BenchmarkProfiles.jl
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@@ -1,6 +1,6 @@
module BenchmarkProfiles

import Plots
import Plots, NaNMath

export performance_ratios, performance_profile
export data_ratios, data_profile
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10 changes: 5 additions & 5 deletions src/performance_profiles.jl
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Expand Up @@ -13,21 +13,21 @@ function performance_ratios(T :: Array{Float64,2}; logscale :: Bool=true)

(np, ns) = size(T); # Number of problems and number of solvers.

T[isinf(T)] = NaN;
T[isinf.(T)] = NaN;
T[T .< 0] = NaN;
minperf = minimum(T, 2); # Minimal (i.e., best) performance per solver
minperf = Base.minimum(T, 2); # Minimal (i.e., best) performance per solver

# Compute ratios and divide by smallest element in each row.
r = zeros(np, ns);
for p = 1 : np
r[p, :] = T[p, :] / minperf[p];
end

logscale && (r = log2(r));
max_ratio = maximum(r);
logscale && (r = log2.(r));
max_ratio = NaNMath.maximum(r)

# Replace failures with twice the max_ratio and sort each column of r.
failures = isnan(r);
failures = isnan.(r);
r[failures] = 2 * max_ratio;
r = sort(r, 1);
return (r, max_ratio)
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