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import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.font_manager as fntmgr
from decimal import Decimal as deci
get_ipython().magic('matplotlib inline')
plt.rcParams['figure.figsize'] = [10,8]


    

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plt.rcParams['figure.figsize'] = [10,8]


    

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e_iso_lin = pd.read_csv('NRMSE_iso_lin.csv', header = None).values.squeeze()
e_iso_rf = pd.read_csv('NRMSE_iso_rf.csv', header = None).values.squeeze()
e_oxi_rf = pd.read_csv('NRMSE_oxi_rf.csv', header = None).values.squeeze()
e_sa_rf = pd.read_csv('NRMSE_sa_rf.csv', header = None).values.squeeze()
pHs_iso = pd.read_csv('pHs_iso.csv', header = None).values.squeeze()
pHs_oxi = pd.read_csv('pHs_oxi.csv', header = None).values.squeeze()
pHs_sa = pd.read_csv('pHs_sa.csv', header = None).values.squeeze()


    

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h = plt.figure();
plt.rc('font',size=24)
plt.hold;
plt.plot(pHs_iso,e_iso_lin,'b--',label = 'Iopamidol acidoCEST Approach',linewidth = 5);
plt.plot(pHs_iso,e_iso_rf,'ro--',label = 'Iopamidol ML Approach',linewidth = 5,markersize=12);
plt.plot(pHs_oxi,e_oxi_rf,'g-',label = 'Ioxilan ML Approach',linewidth = 5);
plt.plot(pHs_sa,e_sa_rf,'c:',label = 'Salicylic Acid ML Approach',linewidth = 5);
plt.ylabel('Normalized Root-mean-square Error (%)', fontsize = 24); plt.xlabel('Expected pH', fontsize = 24); plt.legend(fontsize = 22);
fnt = fntmgr.FontProperties(size = 24)
plt.title('pH Prediction Error as Function of Expected pH', fontsize = 24);
plt.ylim((0.1,5));
plt.xlim((6,7));
plt.savefig('NRMSE_vs_pH.tif',dpi = 300, format='tif')


    

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