%global __brp_check_rpaths %{nil}
%global __requires_exclude ^libmpi
%global packname  glmnetr
%global packver   0.5-4
%global rlibdir   /usr/local/lib/R/library

Name:             R-CRAN-%{packname}
Version:          0.5.4
Release:          1%{?dist}%{?buildtag}
Summary:          Nested Cross Validation for the Relaxed Lasso and Other Machine Learning Models

License:          GPL-3
URL:              https://cran.r-project.org/package=%{packname}
Source0:          %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz


BuildRequires:    R-devel >= 3.4.0
Requires:         R-core >= 3.4.0
BuildArch:        noarch
BuildRequires:    R-CRAN-glmnet 
BuildRequires:    R-CRAN-survival 
BuildRequires:    R-CRAN-Matrix 
BuildRequires:    R-CRAN-xgboost 
BuildRequires:    R-CRAN-smoof 
BuildRequires:    R-CRAN-mlrMBO 
BuildRequires:    R-CRAN-ParamHelpers 
BuildRequires:    R-CRAN-randomForestSRC 
BuildRequires:    R-CRAN-rpart 
BuildRequires:    R-CRAN-torch 
BuildRequires:    R-CRAN-aorsf 
BuildRequires:    R-CRAN-DiceKriging 
BuildRequires:    R-CRAN-rgenoud 
Requires:         R-CRAN-glmnet 
Requires:         R-CRAN-survival 
Requires:         R-CRAN-Matrix 
Requires:         R-CRAN-xgboost 
Requires:         R-CRAN-smoof 
Requires:         R-CRAN-mlrMBO 
Requires:         R-CRAN-ParamHelpers 
Requires:         R-CRAN-randomForestSRC 
Requires:         R-CRAN-rpart 
Requires:         R-CRAN-torch 
Requires:         R-CRAN-aorsf 
Requires:         R-CRAN-DiceKriging 
Requires:         R-CRAN-rgenoud 

%description
Cross validation informed Relaxed LASSO, Artificial Neural Network (ANN),
gradient boosting machine ('xgboost'), Random Forest ('RandomForestSRC'),
Oblique Random Forest ('aorsf'), Recursive Partitioning ('RPART') or step
wise regression models are fit.  Cross validation leave out samples
(leading to nested cross validation) or bootstrap out-of-bag samples are
used to evaluate and compare performances between these models with
results presented in tabular or graphical means.  Calibration plots can
also be generated, again based upon (outer nested) cross validation or
bootstrap leave out (out of bag) samples. For some datasets, for example
when the design matrix is not of full rank, 'glmnet' may have very long
run times when fitting the relaxed lasso model, from our experience when
fitting Cox models on data with many predictors and many patients, making
it difficult to get solutions from either glmnet() or cv.glmnet().  This
may be remedied by using the 'path=TRUE' option when calling glmnet() and
cv.glmnet().  Within the glmnetr package the approach of path=TRUE is
taken by default. When fitting not a relaxed lasso model but an
elastic-net model, then the R-packages 'nestedcv'
<https://cran.r-project.org/package=nestedcv>, 'glmnetSE'
<https://cran.r-project.org/package=glmnetSE> or others may provide
greater functionality when performing a nested CV. Use of the 'glmnetr'
has many similarities to the 'glmnet' package and it is recommended that
the user of 'glmnetr' also become familiar with the 'glmnet' package
<https://cran.r-project.org/package=glmnet>, with the "An Introduction to
'glmnet'" and "The Relaxed Lasso" being especially useful in this regard.

%prep
%setup -q -c -n %{packname}

# fix end of executable files
find -type f -executable -exec grep -Iq . {} \; -exec sed -i -e '$a\' {} \;
# prevent binary stripping
[ -d %{packname}/src ] && find %{packname}/src -type f -exec \
  sed -i 's@/usr/bin/strip@/usr/bin/true@g' {} \; || true
[ -d %{packname}/src ] && find %{packname}/src/Make* -type f -exec \
  sed -i 's@-g0@@g' {} \; || true
# don't allow local prefix in executable scripts
find -type f -executable -exec sed -Ei 's@#!( )*/usr/local/bin@#!/usr/bin@g' {} \;

%build

%install

mkdir -p %{buildroot}%{rlibdir}
%{_bindir}/R CMD INSTALL -l %{buildroot}%{rlibdir} %{packname}
test -d %{packname}/src && (cd %{packname}/src; rm -f *.o *.so)
rm -f %{buildroot}%{rlibdir}/R.css
# remove buildroot from installed files
find %{buildroot}%{rlibdir} -type f -exec sed -i "s@%{buildroot}@@g" {} \;

%files
%{rlibdir}/%{packname}