In [1]:

    

%matplotlib inline

import numpy as np
import pandas as pd
from scipy import stats, integrate
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(color_codes=True)
sns.set_context('poster', font_scale=1.5)
mpl.rcParams['svg.fonttype'] = 'none'
mpl.rcParams['pdf.fonttype'] = 42


    

    




/usr/local/lib/python2.7/site-packages/matplotlib/__init__.py:872: UserWarning: axes.color_cycle is deprecated and replaced with axes.prop_cycle; please use the latter.
  warnings.warn(self.msg_depr % (key, alt_key))

In [2]:

    

def plotHist(inputFile):
    x = pd.read_csv('qcstatscsv/%s.csv' % inputFile)
    x = pd.concat((x['acq-AP_run-01'], x['acq-PA_run-01'], x['acq-AP_run-02'], x['acq-PA_run-02']))
    x = np.array(x)
    x = x[np.isnan(x) == False]
    return x


    

In [3]:

    

f = plt.figure(figsize=(30,10))

f.add_subplot(1,3,1)
x = plotHist('max_FD')
plt.hist(x, 100)
plt.xlabel('mm')
plt.ylabel('number of runs')
plt.title('maximum framewise displacement', fontsize=30)

f.add_subplot(1,3,2)
x = plotHist('mean_FD')
plt.hist(x, 100)
plt.xlabel('mm')
plt.title('mean framewise displacement', fontsize=30)

f.add_subplot(1,3,3)
x = plotHist('median_tsnr')
plt.hist(x, 100)
plt.xlabel('tSNR')
plt.title('temporal signal-to-noise (tSNR)', fontsize=30)

f.savefig('qcplots.pdf')
plt.show()


    

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