Idr stream module refactor #26
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jenna-tomkinson
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LGTM! I just asked one clarifying question but other than that this is a very clean PR!
roshankern
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* refactor locate data module (#25) * Idr stream module refactor (#26) * Co-authored-by: Jenna Tomkinson <jenna.tomkinson@ucdenver.edu> * add files for CP run * remove run cellpose plugin * refactor idrstreams * create python merge files * remove unecessary create folder line * docs * change conda environments with bash file * black formatting * Refactor format module (#27) * rerun module * rerun script * rerun notebook * greg suggestion * Refactor normalize module (#29) * rerun format module * refactor raw data umaps * update utils * run umaps notebook * reconvert jupyter notebook * normalize training data * rerun pipeline * jenna suggestions * Refactor umaps module (#30) * rerun notebook * docs, convert notebook * Update 4.analyze_data/README.md Co-authored-by: Erik Serrano <31600622+axiomcura@users.noreply.github.com> * documentation --------- Co-authored-by: Erik Serrano <31600622+axiomcura@users.noreply.github.com> * remove unecessary line from gitignore * fix typo * move constants outside of for loop --------- Co-authored-by: Erik Serrano <31600622+axiomcura@users.noreply.github.com>
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This PR is ready for review!
The main focus of this PR is extracting CP features for the MitoCheck labeled dataset (in addition to the DP features that have already been extracted).
The structure of this module has also been shifted to utilize the different conda environments for
idrstream_cpandidr_stream_dp. Instead of using 3 python files for the different data types (training, negative control, positive control), this PR uses 3 python files for the CP feature extraction, DP feature extraction, and merging. In the CP/DP feature extraction files, for loops are used to extract the 3 different data types (training, negative control, positive control). The structure shift is shown in the screenshots below:Before PR:
After PR:
