%global __brp_check_rpaths %{nil}
%global __requires_exclude ^libmpi
%global packname  glmnetr
%global packver   0.5-1
%global rlibdir   /usr/local/lib/R/library

Name:             R-CRAN-%{packname}
Version:          0.5.1
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.  Nested cross validation (or analogous for
the random forest) is used to estimate and compare performances between
these models with results presented in tabular or graphical means.
Calibration plots can also be generated, again based upon (nested) cross
validation. 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 with
the 'path=TRUE' options 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 helpful
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}