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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=',') | |
| class Site(): | |
| def __init__(self, site_name, sub_range): | |
| self.site_name = site_name | |
| self.sub_range = sub_range | |
| self.snr_df_name = self.site_name + "_snr" | |
| self.motion_data = None | |
| self.signal_data = None | |
| self.slice_site() | |
| # 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(self): | |
| self.motion_data = combined[combined['Subject'].str.contains(self.sub_range)] | |
| self.signal_data = snr[snr['subject'].str.contains(self.sub_range)] | |
| print "Scans in motion data = "+str(len(self.motion_data.index)) | |
| print "Scans in SNR data = "+str(len(self.signal_data.index)) | |
| # for the love of god, rename me | |
| def make_pretty_thing(self): | |
| func_quad(site_name = self.site_name, meanfd_column = self.motion_data.MeanFD, | |
| meandvars_column = self.motion_data.MeanDVARS, | |
| pctvols_column = self.motion_data[self.motion_data.columns[37]], | |
| tsnr_column = self.signal_data.tsnr) | |
| # Utah 26017-26043 (178) | |
| utah = Site(site_name="Utah", sub_range="2601[7-9]|260[2-3][0-9]|2604[0-3]") | |
| utah.make_pretty_thing() |
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