Closed jeipollack closed 1 year ago
oops. I just remembered that I need to write a method to verify that the config parameters are correct.
Thanks @jeipollack, I will start reviewing this tomorrow. :)
Thanks, @sfarrens. I am reviewing myself, too! I see that I need to tidy up the io.py
module. And, since the construction of the output file directory is automatic I was thinking to convert it to internal commands. If you have any thoughts on that, let me know. Thanks!
Hi @sfarrens , I pushed doc string style changes for read_config.py
.
Hi @sfarrens, just want to send you a FYI that I did a few more changes in this branch more related to restructuring the package, but I did not push them. Instead I decided to checkout a new branch to continue development there until this PR can be merged to the dummy_main
branch.
This PR features many changes which I subdivide into major and minor categories:
Major
run.py
module to launch at execution which parses the command line arg specifying the name of the configuration file:configs.yaml
.env
script storing the environment variables required to be set at execution with thedotenv
package methodload_dotenv
.env.example
in the repo which the user should update with the appropriate paths to the directorieswf-psf
repo, the directory for training and test datasets, and the location of the output directory closes #51io.py
module with methods to automatically make thewf-outputs
file structure defined in long-runs instructionsconfigs.yaml
file which should store individualconfig
files:training_config.yaml
,eval_config.yaml
,plotting_config.yaml
and alogging.conf
. Only thetraining_config.yaml
andlogging.conf
have been written and used so far.training
package which should containtrain.py
module with a classTrainingParamsHandler
for extracting the different parameter subsets for training, psf model, and datasets, and atrain
method which should do the training once the psf model, training and test datasets have been specified (TO DO)psf_model
package containing for now apsf_model.py
module with a decoratorregister_psf_class
wrapping each PSF model class. At runtime, a dictionary calledPSF_CLASSES
will get loaded with all of the psf_model classes. Thedict
key is determined according to the class attributeids
which stores the short model name of the class specified in thetraining_config.yaml
.utils.py
module to azernikes.py
moduleMinor Changes
script_utils.py
to only train thepoly
model. Have not tested it.metrics
package and moved themetrics.py
module there.wf_psf/__init__.py
with thetrain
,psf_models
andmetrics
packages