def __init__(self):
"""Make permutations of a two-group acid-acid system"""
self.pHstart=0.0
self.pHend=20.0
self.pHstep=0.1
self.pKa_MCsteps=2000000
import numpy
pka_diffs=numpy.arange(0.0,2.0,0.01)
int_enes=numpy.arange(0.0,2.0,0.01)
#
import math
matrix={}
for pka_diff in pka_diffs:
print pka_diff
matrix[pka_diff]={}
for int_ene in int_enes:
pKa_values, prot_states=self.do_pKa_calc(pka_diff,int_ene)
#print int_ene,pKa_values
#del prot_states[':0002:GLU']
matrix[pka_diff][int_ene]=self.fit_curves(prot_states)
#stop
import TwoDplots
TwoDplots.heatmap(matrix,'Two-group scan',firstkey='Difference in intrinsic pKa',secondkey='Interaction energy (kT)',zlabel='Average slope',
firstticks=[numpy.arange(0,200,10),numpy.arange(0.0,2.0,0.1)],
secondticks=[numpy.arange(0,200,10),numpy.arange(0.0,2.0,0.1)])
#
return
def __init__(self,options):
#
# Read the dir
#
import large_dataset_manager
self.DM=large_dataset_manager.data_manager(options.dir)
#
# Read all datasets
#
matrix={}
count=0
data=self.DM(count)
while data:
count=count+1
data=self.DM(count)
if count>1000:
data=None
print '\b.',
import sys
sys.stdout.flush()
#
if data:
sum_intpkadiff,sum_intene,tit_fit,pHact_fit=self.analyze_point(data)
if not matrix.has_key(sum_intpkadiff):
matrix[sum_intpkadiff]={}
if not matrix[sum_intpkadiff].has_key(sum_intene):
matrix[sum_intpkadiff][sum_intene]=[0,0]
matrix[sum_intpkadiff][sum_intene][0]=matrix[sum_intpkadiff][sum_intene][0]+tit_fit
matrix[sum_intpkadiff][sum_intene][1]=matrix[sum_intpkadiff][sum_intene][1]+pHact_fit
#
# Calculate ratio
#
minS=9999.9
maxS=-9999.9
for ip in matrix.keys():
for ie in matrix[ip].keys():
minS=min(minS,ie)
maxS=max(maxS,ie)
#
vals=matrix[ip][ie]
matrix[ip][ie]=vals[0]
# Fill in empty values
minF=min(matrix.keys())
maxF=max(matrix.keys())
print minF,maxF
print minS,maxS
#stop
for ip in np.arange(minF,maxF+1,1):
if not matrix.has_key(ip):
matrix[ip]={}
for ie in range(minS,maxS+1,1):
if not matrix[ip].has_key(ie):
matrix[ip][ie]=0.0
import TwoDplots
TwoDplots.heatmap(matrix,firstkey='sum intpka diff',secondkey='sum intene (kT)')
print 'I found %7.2e datasets' %count
return
def heatmap():
"""|Make a heatmap - not sure what this function does..."""
data = getdata()
TGs = sorted(data.keys())
for titgroup in TGs:
thisN = []
thisH = []
for residue in sorted(data[titgroup].keys()):
Hval = 0.0
Nval = 0.0
for atom in ['H', 'N']:
if data[titgroup][residue].has_key(atom):
x = data[titgroup][residue][atom]
#
# -----
#
if x == 'absent':
print 'abs'
if atom == 'H':
Hval = -20
else:
Nval = -20
else:
if x[0] == 'q':
x = x[1:]
x = x.split(';')[0]
if x[0] in ['<', '>']:
x = x[1:]
x = float(x)
if atom == 'H':
Hval = 20
else:
Nval = 20
#
#
thisN.append(Nval)
thisH.append(Hval)
for y in range(10):
Ndata.append(thisN)
Hdata.append(thisH)
#
#
import TwoDplots
blue_red1 = TwoDplots.LinearSegmentedColormap('BlueRed1', cdict1)
#
plt.imshow(Ndata, interpolation='nearest', cmap=blue_red1)
cbar = plt.colorbar()
cbar.set_label('score')
#
plt.yticks(range(5, 105, 10), TGs)
plt.ylim([0, 100])
plt.show()
return
exp[T2] = {}
exp[T2][T1] = exp[T1][T2]
matrix2 = {}
tTGs = matrix.keys()
TGs = []
for tg in tTGs:
if tg.find('TYR') == -1:
TGs.append(tg)
for TG1 in TGs:
matrix2[TG1] = {}
for TG2 in TGs:
value = 0.0
if exp.has_key(TG1):
if exp[TG1].has_key(TG2):
import math
value = math.log(10) * exp[TG1][TG2]
#value=abs((matrix[TG1][TG2][0]+matrix[TG2][TG1][0])/2.0)
#if value<0.7:
# value=value
matrix2[TG1][TG2] = value
import TwoDplots
TwoDplots.heatmap(matrix2,
title='Interaction energy matrix',
firstkey='TG1',
secondkey='TG2',
zlabel='Interaction energy (kT)',
firstticks=sorted(TGs),
secondticks=sorted(TGs))
exp={':0035:GLU':{':0052:ASP':1.2,':0119:ASP':0.3,':0007:GLU':0.3}}
for T1 in exp.keys():
for T2 in exp[T1].keys():
if not exp.has_key(T2):
exp[T2]={}
exp[T2][T1]=exp[T1][T2]
matrix2={}
tTGs=matrix.keys()
TGs=[]
for tg in tTGs:
if tg.find('TYR')==-1:
TGs.append(tg)
for TG1 in TGs:
matrix2[TG1]={}
for TG2 in TGs:
value=0.0
if exp.has_key(TG1):
if exp[TG1].has_key(TG2):
import math
value=math.log(10)*exp[TG1][TG2]
#value=abs((matrix[TG1][TG2][0]+matrix[TG2][TG1][0])/2.0)
#if value<0.7:
# value=value
matrix2[TG1][TG2]=value
import TwoDplots
TwoDplots.heatmap(matrix2,title='Interaction energy matrix',firstkey='TG1',secondkey='TG2',zlabel='Interaction energy (kT)',firstticks=sorted(TGs),secondticks=sorted(TGs))