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This repository has been archived by the owner on Apr 25, 2023. It is now read-only.
For example, the dim_reduction module has the following usage:
config file
The configuration file now accepts a list of input, output full paths to directories. The file_name_prefixes is a list of string prefixes. The weights_dir is a single directory in which pca_model.pkl is written as a result of PCA fitting (fit_model = True). The conditions is a list of strings describing experimental conditions. This value is only used during plotting after fitting.
details
For fit_model: True:
loops over all directories listed in config's input_dirs
loops over all prefixes in config's file_name_prefixes
[aggregate all data]: searches for <prefix>_latent_space_after.pkl files in the input dirs and concatenates them in a vector list for subsequent PCA fitting
Fitting will write a model pca_model.pkl to the config's weights_dir directory.
Fitting will write a figure PCA.png to the config's weights_dir directory
finally, will loop over all pairs of input_dirs and output_dirs in the config:
will run inference on all individual <prefix>_latent_space_<suffix>.pkl in input_dir folder, where suffix='after' hardcoded. And where the supplied model is the one generated from step 4 above.
output of each inference is <prefix>_latent_space_after_PCAed.pkl and saved to each corresponding output_dir from 6
For fit_model: False:
loops over all pairs of directories listed in config's input_dirs / output_dirs
loops over all prefixes in config's file_name_prefixes
assumes the weights_dir supplied in the config is a directory, and looks for the pca_model.pkl file there.
runs inference on <prefix>_latent_space_<suffix>.pkl where suffix=after is hardcoded.
writes the transformed vectors to <prefix>_latent_space_<suffix>_PCAed.pkl in the corresponding output_dir directory
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Before 1.0-beta release:
A useful resource would be a centralized folder that contains multiple documents, one for each stage of the pipeline.
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