Performance Improvements to preprocess + small changes in main

[dgorhe]

Hey there, I'm working in Marko Jovanovic's lab at Columbia University and I wanted to pull in some changes to SECAT. We use SECAT a lot but it takes a lot of time to run so I made some performance improvements that should help the average user. Some changes are more oriented toward general usability. The changes include:

• Only importing used functions from package namespace in main (e.g. from pandas import read_csv vs import pandas as pd)
• Using C engine for read_csv calls in preprocess.py wherever a separator is specified to improve parsing performance
• Adding a progress bar for namespace parsing in uniprot class within preprocess.py
• Checking if the df['run_id'] column is all strings before using the pandas.DataFrame.apply method within quantification.read_long() and quantification_read_matrix() in preprocess.py
• Multiprocessing support within normalization.slide_normalize() to use all available cores to normalize windows in parallel

Let me know if you have any feedback for these changes. Thanks!

[grosenberger]

Great work, thanks for the PR!