This project process accelerometry data and uses machine learning to predict small ruminants(Goats and sheep) health.
'project' code is found under projects/{projectname} with project names generally being named after the animal farm or study of interest. 'core' code is everything else.
Usage: ml.py [OPTIONS]
ML
Args:
output_dir: Output directory
dataset_folder: Dataset input directory
class_healthy: Label for healthy class
class_unhealthy: Label for unhealthy class
stratify: Enable stratiy for cross validation
s_output: Output sample files
cwt: Enable freq domain (cwt)
n_scales: n scales in dyadic array [2^2....2^n].
temp_file: csv file containing temperature features.
hum_file: csv file containing humidity features.
n_splits: Number of splits for repeatedkfold cv.
n_repeats: Number of repeats for repeatedkfold cv.
cv: RepeatedKFold
wavelet_f0: Mother Wavelet frequency for CWT
sfft_window: STFT window size
epochs: Cnn epochs
n_process:Number of threads to use.
Options:
--output-dir DIRECTORY [required]
--dataset-folder DIRECTORY [required]
--preprocessing-steps TEXT [default: QN, ANSCOMBE, LOG, DIFF]
--class-healthy-label TEXT [default: 1To1]
--class-unhealthy-label TEXT [default: 1To2]
--stratify TEXT [default: n]
--n-scales INTEGER [default: 30]
--hum-file PATH [default: .]
--temp-file PATH [default: .]
--n-splits INTEGER [default: 5]
--n-repeats INTEGER [default: 10]
--epochs INTEGER [default: 20]
--n-process INTEGER [default: 6]
--output-samples / --no-output-samples
[default: True]
--output-cwt / --no-output-cwt [default: True]
--cv TEXT [default: RepeatedKFold]
--wavelet-f0 INTEGER [default: 6]
--sfft-window INTEGER [default: 60]
--install-completion [bash|zsh|fish|powershell|pwsh]
Install completion for the specified shell.
--show-completion [bash|zsh|fish|powershell|pwsh]
Show completion for the specified shell, to
copy it or customize the installation.
--help Show this message and exit.##Blue Crystal 4
module load tools/git/2.18.0
module load languages/anaconda3/3.7
conda create --prefix /user/work/fo18103/PredictionOfHelminthsInfection/vgoat python=3.7
conda activate /user/work/fo18103/PredictionOfHelminthsInfection/vgoat
export PATH=/user/work/fo18103/PredictionOfHelminthsInfection/vgoat/bin/:$PATH
python -m pip install --upgrade pip
make environment##Blue Pebble
module load tools/git/2.22.0
module load lang/python/anaconda/3.7-2019.03-tensorflow
conda create --prefix /user/work/fo18103/PredictionOfHelminthsInfection/vgoat python=3.7
conda activate /user/work/fo18103/PredictionOfHelminthsInfection/vgoat
export PATH=/user/work/fo18103/PredictionOfHelminthsInfection/vgoat/bin/:$PATH
python -m pip install --upgrade pip
make environment