def analyseTitDB(self, DB, col, names=None):
"""Extract titdb pKas"""
import matplotlib.pyplot as plt
plt.rc('font',size=28)
plt.rc('savefig',dpi=300)
plt.rc('axes',linewidth=.5)
#plt.rc('text',usetex=True)
nuclnames = {'1H NMR':'H','15N NMR':'N'}
t = TitrationAnalyser()
#extract reliable pkas from selected proteins
#p = t.extractpKas(DB, col, names=names, titratable=False, reliable=False, minspan=0.06)
#t.analysepKas(p)
t.compareNuclei(DB, '15N NMR', '1H NMR', names=names, titratable=True)
return
def showAnalysis(self):
"""Analysis of current pKas"""
from PEATDB.Ekin.Titration import TitrationAnalyser
self.showHeader(menu=1)
DB = self.DB = self.connect()
t = TitrationAnalyser()
print '<div class="main">'
print '<p>Selected plots below reflect some of the analysis shown in the \
<a href="%s/paper_2010.pdf"> original paper</a> updated for the current dataset. </p>' %self.bindir
print '<a>The distributions shown are of the change in chemical shift over all\
detected titrations. `Reliable` pKas are those associated with\
the largest chemical shift changes in a titration curve and that meets the criteria defined in\
the paper. We define primary pKa values simply as the subset of the reliable pKa values \
that originate from titration curves with with only one titration.</a>'
sys.stdout.flush()
colnames = ['1H NMR','15N NMR','13C NMR']
for col in colnames:
p = t.extractpKas(DB,col,silent=True,minspan=0.06)
print '<div>'
print "<h2>%s: Distribution of Δδ for fitted pKa values</h2>" %col
img1 = t.analysepKas(p, silent=True, prefix=col, path=self.imagepath)
#t.makepKasTable(p)
print '<img src="%s/%s" align=center width=800 class="plot">' %(self.plotsdir, img1)
print '</div>'
sys.stdout.flush()
#compare nuclei
img2, img3 = t.compareNuclei(DB, '15N NMR', '1H NMR', titratable=False, silent=True, path=self.imagepath)
print '<p>Below is an analysis of the correspondence between fitted pKas for 1H and 15N \
where they are available for the same residue in the same protein. This is the same\
plot as figure 4 in the original paper updated for the current dataset.\
The plots are divided into reliable and other pKas for comparison.</p>'
print '<div>'
print '<center><img src="%s/%s" align=center width=600 class="plot"></center>' %(self.plotsdir, img2)
print '</div>'
print '<p>The same plot as above broken down by residue type and shown only for titratable\
residues.</p>'
print '<div>'
print '<center><img src="%s/%s" align=center width=600 class="plot"></center>' %(self.plotsdir, img3)
print '</div>'
self.footer()
return
