From 0694e135b636d2de760ab28252d1c46b14fa329a Mon Sep 17 00:00:00 2001 From: Luis Fabregas Date: Sat, 30 Jul 2022 02:51:58 +0200 Subject: [PATCH 1/3] fix minor logic error --- deerlab/model.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/deerlab/model.py b/deerlab/model.py index 406804d3..18a1d749 100644 --- a/deerlab/model.py +++ b/deerlab/model.py @@ -939,7 +939,7 @@ def _print_fitresults(fitresult,model): hasregularization = fitresult.regparam!=0 haspenalties = fitresult.penweights - if hasregularization and haspenalties: + if hasregularization or haspenalties: string += 'Model hyperparameters: \n' tags = [] values = [] From a310171a6aced26547697f548267b85665418f18 Mon Sep 17 00:00:00 2001 From: Luis Fabregas Date: Sat, 30 Jul 2022 02:35:55 +0200 Subject: [PATCH 2/3] minor documentation update --- docsrc/source/installation.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docsrc/source/installation.rst b/docsrc/source/installation.rst index 10716596..f71e8556 100644 --- a/docsrc/source/installation.rst +++ b/docsrc/source/installation.rst @@ -8,7 +8,7 @@ Requirements To install DeerLab, first install Python on your computer. Python can be downloaded from the `official Python distribution `_. There are many online tutorials to guide you through the installation and setup (see `here `_ for example). Make sure you install -one of the Python versions compatible with DeerLab, either **Python 3.6**, **3.7**, **3.8**, **3.9**, or **3.10**. +one of the Python versions compatible with DeerLab, either **Python 3.8**, **3.9**, or **3.10**. .. rubric:: Windows systems From dea82cbf5c88029469b83fe05678ffa4cfb98892 Mon Sep 17 00:00:00 2001 From: Luis Fabregas Date: Sat, 30 Jul 2022 18:16:40 +0200 Subject: [PATCH 3/3] fix minor bug --- deerlab/model.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/deerlab/model.py b/deerlab/model.py index 18a1d749..252b95b6 100644 --- a/deerlab/model.py +++ b/deerlab/model.py @@ -946,8 +946,10 @@ def _print_fitresults(fitresult,model): alignment = [] if hasregularization: alignment.append('^') - tags.append('Regularization parameter') - values.append(fitresult.regparam) + tags.append('Regularization parameter') + regparam = fitresult.regparam + if regparam is None: regparam = 0 + values.append(regparam) if haspenalties: for n,penweight in enumerate(fitresult.penweights): alignment.append('^')