Created
March 31, 2014 15:54
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| import numpy as np | |
| import pandas as pd | |
| from scipy import stats | |
| import matplotlib as mpl | |
| import matplotlib.pyplot as plt | |
| import seaborn as sns | |
| combined = pd.read_csv('/Users/daniel.lurie/Dropbox/CMI/INDI/CoRR/qc/temp_motion_326.csv', sep=',') | |
| snr = pd.read_csv('/Users/daniel.lurie/Dropbox/CMI/INDI/CoRR/qc/tsnr_temp_328.csv', sep=',') | |
| # Define a function that creates site-specific data frames based on a range of subject numbers (specified as regex) | |
| # One data frame for motion data, one for SNR data | |
| # Prints number of rows in each new DF | |
| def slice_site (site_name, sub_range): | |
| snr_df = site_name+"_snr" | |
| vars()[site_name] = combined[combined['Subject'].str.contains(sub_range)] | |
| vars()[snr_df] = snr[snr['subject'].str.contains(sub_range)] | |
| print "Scans in motion data = "+str(len(vars()[site_name].index)) | |
| print "Scans in SNR data = "+str(len(vars()[snr_df].index)) | |
| #import code | |
| #code.interact(local=locals()) | |
| return vars()[site_name], vars()[snr_df] | |
| # Utah 26017-26043 (178) | |
| slice_site(site_name="utah", sub_range="2601[7-9]|260[2-3][0-9]|2604[0-3]") | |
| print len(site_name.index) |
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