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feat: add C implementation for stats/base/dists/gumbel/skewness #5222
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--- type: pre_push_report description: Results of running various checks prior to pushing changes. report: --- --- type: pre_push_report description: Results of running various checks prior to pushing changes. report: --- --- type: pre_push_report description: Results of running various checks prior to pushing changes. report: - task: run_javascript_examples status: na - task: run_c_examples status: na - task: run_cpp_examples status: na - task: run_javascript_readme_examples status: na - task: run_c_benchmarks status: na - task: run_cpp_benchmarks status: na - task: run_fortran_benchmarks status: na - task: run_javascript_benchmarks status: na - task: run_julia_benchmarks status: na - task: run_python_benchmarks status: na - task: run_r_benchmarks status: na - task: run_javascript_tests status: na ---
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👋 Hi there! 👋
And thank you for opening your first pull request! We will review it shortly. 🏃 💨
--- type: pre_push_report description: Results of running various checks prior to pushing changes. report: - task: run_javascript_examples status: na - task: run_c_examples status: na - task: run_cpp_examples status: na - task: run_javascript_readme_examples status: na - task: run_c_benchmarks status: na - task: run_cpp_benchmarks status: na - task: run_fortran_benchmarks status: na - task: run_javascript_benchmarks status: na - task: run_julia_benchmarks status: na - task: run_python_benchmarks status: na - task: run_r_benchmarks status: na - task: run_javascript_tests status: na ---
Coverage Report
The above coverage report was generated for the changes in this PR. |
mu[ i ] = uniform( -50.0, 50.0 ); | ||
beta[ i ] = uniform( EPS, 20.0 ); | ||
mu[ i ] = ( randu() * 100.0 ) - 50.0; | ||
beta[ i ] = ( randu() * 20.0 ) + EPS; |
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These changes need to be reversed.
mu = new Float64Array( len ); | ||
beta = new Float64Array( len ); | ||
for ( i = 0; i < len; i++ ) { | ||
mu[ i ] = ( randu()*100.0 ) - 50.0; |
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According to current convention i think you need to use uniform
function to generate these.
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mu[ i ] = ( randu()*100.0 ) - 50.0; | |
mu[ i ] = uniform( -50.0, 50.0 ); | |
beta[ i ] = uniform( EPS, 20.0 ); |
t.equal( y, expected[i], 'mu:'+mu[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] ); | ||
} else { | ||
delta = abs( y - expected[ i ] ); | ||
tol = 2.0 * EPS * abs( expected[ i ] ); |
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Check for tolerance value here.
Thank you so much for your contribution and the effort you put into this PR. We ended up merging a different PR (link to PR) that addressed the same issue, so I am closing this one. |
Resolves #3654 .
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