Add script files for installation and minimal case for a complete run

templates/install.sh

+#!/bin/bash
+
+# Script with the installation of the dependencies using conda.
+# Adapt your conda and deconvnet repository paths if necessary
+
+. "${HOME}/anaconda3/etc/profile.d/conda.sh"
+LIB_FOLDER="${HOME}/dev/deeplearning/deconvnet"
+
+# this will create a deconvnet env on conda default folder
+# you may add flag `--prefix <desired path>` to change it
+conda env create -f "${LIB_FOLDER}/conda_env.yml" --verbose
\ No newline at end of file

templates/minimal.sh

+#!/bin/bash
+
+# Script with an example of a complete training procedure, from
+# database generation to testing. On a quad-core notebook it
+# should take about 7 minutes to run all commands. Generate data around
+# 90 Mb of data (database + test files).
+
+# Adapt your conda env name and deconvnet repository paths if necessary
+
+# starting conda and the env
+. "${HOME}/anaconda3/etc/profile.d/conda.sh"
+LIB_FOLDER="${HOME}/dev/deeplearning/deconvnet"
+conda activate deconvnet
+
+date
+echo "=========="
+
+echo "Generating the databases (2000 Hz, 1 to 5 incoherent sources)..."
+sizes=(1000 200 10)
+names=('training' 'validation' 'testing' )
+for i in "${!names[@]}"
+do
+    echo ${names[i]}
+    python "${LIB_FOLDER}/generate.py" \
+        -n=${sizes[i]} -max=5 -workers=4 -filename=${names[i]}
+done
+echo "=========="
+
+echo "Launching the training..."
+python "${LIB_FOLDER}/train.py" \
+    -epochs=100 \
+    -database_format='{:}_f02000Hz.npz'
+echo "=========="
+
+echo "Testing the trained model..."
+python "${LIB_FOLDER}/test.py" \
+    -experiment_folder="test" \
+    -case_name="testing" \
+    -database_format='{:}_f02000Hz.npz' \
+    -workers=4
+echo "=========="
+
+date