def main():
""" Interkin - folding kinetics of two interacting RNA molecules
* call the pipeline: "RNAsubopt | barriers" in order to get tree files and
rate matrices
* make a reaction graph composed of uni- and bi-molecular reactions found
in the rate matrices
* visualize the graph using networkx or D3js
* calculate the equilibrium distribution and see how much it differs from
the complete cofolded ensemble
* dump the graph in order to translate it into a ODE system using the perl
SundialsWrapper library
TODO: write a landscape library in order to get rid of BarMap dependency
"""
args = get_interkin_args()
""" Read Input & Update Arguments """
name, inseq = ril.parse_vienna_stdin(sys.stdin)
if args.name == '':
args.name = name
else:
name = args.name
if args.verbose:
print "# Input: {:s} {:s} {:6.2f} kcal/mol".format(name, inseq, args.s_ener)
if args.s_ener == 0:
args.s_ener, args.s_maxn = ril.sys_subopt_range(inseq,
nos=args.s_maxn,
maxe=20, # args.s_maxe,
verb=args.verbose)
if args.verbose:
print "# Energyrange {:.2f} computes {:d} sequences".format(
args.s_ener, args.s_maxn)
""" Dirty way to use RNAsubopt symmetry correction as commandline interface """
s_options = ['|', args.spatch]
if args.symmetry:
s_options.append('-s')
""" Choose the set of species for further analysis """
# default: [A, A, AA], [A, B, AB, AA, BB], [A, B, C, AA, AB, AC, BB, BC, CC]
# nohomo: [A, B, AB] (for debugging)
specieslist = get_species(inseq, args.nohomo)
""" Compute folding kinetics """
bionly = False # Debugging option, compute kinetics only from cofold tree
RG, nodes = cofold_barriers(name, specieslist,
s_ener=args.s_ener,
s_maxn=args.s_maxn,
s_opts=s_options,
barriers='barriers',
minh=args.b_minh,
maxn=args.b_maxn,
k0=args.k0,
temp=37.0,
moves='single-base-pair',
gzip=True,
rates=True,
bsize=False,
saddle=False,
bionly=bionly,
force=args.force,
verb=args.verbose)
# NOTE: Hack to check out if crnsimulator works like sundials:
from crnsimulator import writeODElib
import sympy
ntv = dict()
vtn = dict()
oV = []
for e, n in enumerate(filter(lambda x: nodes[x] != 0, nodes)):
var = n[0].translate(string.maketrans("&", "_")) + '_' + str(e)
ntv[n] = var
vtn[var] = n
oV.append(var)
NLRG = nx.relabel_nodes(RG, ntv)
oR = dict()
ode = dict()
for r in NLRG.nodes_iter():
if r in vtn:
continue
rate = 'k' + str(len(oR.keys()))
reactants = []
for reac in NLRG.predecessors_iter(r):
for i in range(NLRG.number_of_edges(reac, r)):
reactants.append(str(reac))
products = []
for prod in NLRG.successors_iter(r):
edict = NLRG.get_edge_data(r, prod)
oR[rate] = str(edict[0]['weight'])
for i in range(NLRG.number_of_edges(r, prod)):
products.append(str(prod))
for x in reactants:
if x in ode:
ode[x].append(['-' + rate] + reactants)
else:
ode[x] = [['-' + rate] + reactants]
for x in products:
if x in ode:
ode[x].append([rate] + reactants)
else:
ode[x] = [[rate] + reactants]
oM = []
for dx in oV:
sfunc = sympy.sympify(
' + '.join(['*'.join(map(str, xp)) for xp in ode[dx]]))
ode[dx] = sfunc
oM.append(sfunc)
oM = sympy.Matrix(oM)
oJ = None
odefile, odename = writeODElib(
oV, oM, jacobian=oJ, rdict=oR, filename='interkin')
print 'Happy simulating: ODE system wrote to File:', odefile
'''
""" Compute equilibrium properties """
# plot RNAcofold equilibrium properties with a given range of a0s and b0s
# plot gradient basin equilibrium for a given range of a0s and b0s
# => [seq&seq], [K]
kT=0.61632077549999997
a0s = map(lambda x: 10**-x, range(9,8,-3))
b0s = map(lambda x: 10**-x, range(6,1,-1))
eA =0
eB =0
eAA=0
eAB=0
eBB=0
for (name, species) in specieslist :
if '&' not in name: continue
[seqA, seqB] = species.split('&')
[nA, nB] = name.split('&')
plotname = args.name+'_'+nA+'_'+nB
homodimer = (seqA == seqB)
""" if it is a homodimer, G_A = G_B and G_AB = G_AA = G_BB """
if not homodimer :
[G_A, G_B, G_AB, G_AA, G_BB] = conc.cofold_free_energies(species)
print 'ref_cfold', species, nA, G_A, nB, G_B, \
nA+nB, G_AB, nA*2, G_AA, nB*2, G_BB
eqdata = conc.cofold_equilibrium(species, a0s, b0s)
conc.cofold_plot(eqdata,plotname+'_cofold_plot')
"""
[G_A, G_B, G_AB, G_AA, G_BB] = basin_free_energies(species)
print 'ref_cfold', species, nA, G_A, nB, G_B, \
nA+nB, G_AB, nA*2, G_AA, nB*2, G_BB
eqdata = conc.cofold_equilibrium(species, a0s, b0s)
"""
RNA.cvar.cut_point = len(seqA)+1
[stmp,G_A,G_B,G_AB,waste] = RNA.co_pf_fold(seqA+seqB,None)
K = math.e**((G_A+G_B-G_AB)/kT)
print 'ref_bimol', species, nA, G_A, nB, G_B, nA+nB, G_AB, "K", K
if homodimer :
eqdata = conc.bimol_equilibrium(K, b0s, [])
conc.homodim_plot(eqdata,plotname+'_bimol_plot')
else :
eqdata = conc.bimol_equilibrium(K, a0s, b0s)
conc.bimol_plot(eqdata,plotname+'_bimol_plot')
if not bionly :
[G_A, G_B, G_AB] = unimolecular_basins(RG, name, species, args, nodes)
K = math.e**((G_A+G_B-G_AB)/kT)
print 'uitree', species, nA, G_A, nB, G_B, nA+nB, G_AB, "K", K
[G_ApB, G_AB] = bimolecular_cofold_basins(
RG, name, species, args, nodes, bionly)
K = math.e**((G_ApB-G_AB)/kT)
print 'bitree', species, nA+'+'+nB, G_ApB, nA+nB, G_AB, "K", K
if homodimer :
eqdata = conc.bimol_equilibrium(K, b0s, [])
conc.homodim_plot(eqdata, plotname+'_coarse_grain_plot')
else :
eqdata = conc.bimol_equilibrium(K, a0s, b0s)
[a0, b0, eA, eB, eAB] = zip(*eqdata)
conc.bimol_plot(eqdata, plotname+'_coarse_grain_plot')
if False : # Depricated and a bit ugly code, it is for debugging only
""" Compare lists of gradient basin energies for fake and true dimers """
interkin_equilibrium(specieslist, args)
# Calculate equilibrium distribution by hand... (like for prions!)
# use that as a start for the simulation:
# *) calculate the concentrations of species
# *) calculate the occupancy of an lmin at equilibrium
# *) return the equilibrium starting population for a simulation ...
'''
return
def cofold_barriers(_name, species,
s_opts=['|', 'pylands_spatch.py'],
s_ener=None,
s_maxn=59000000,
barriers='barriers',
minh=0.001,
maxn=50,
k0=1.0,
temp=37.0,
moves='single-base-pair',
gzip=True,
rates=True,
bsize=False,
saddle=False,
bionly=False,
force=False,
verb=False):
""" Simulate inter-molecular folding
Compute folding kinetics
returns the biggest connected component and a list of nodes
TODO:
*) @h**o-dimers: RNAsubopt-barriers does not correct for two-fold symmetry!
"""
noLP = False # MUST BE FALSE!
circ = False # MUST BE FALSE!
mfile = ''
if minh > 0.5:
print "Warning: increasing the minh option for cofolded barriers may " + \
"destroy the separation of monomer and dimer gradient basins!"
RG = nx.MultiDiGraph()
sortednodes = c.OrderedDict()
hypercount = [0]
for spe, seq in species:
name = _name + "_" + spe
if '&' in name:
""" true dimer only run """
name = name.translate(string.maketrans("&", "_"))
if s_ener is None:
myener, nos = ril.sys_subopt_range(
seq, nos=s_maxn, maxe=20, verb=verb)
else:
myener = s_ener
if bionly is False:
_fname = name + "_truedimers"
s_opts.append('-d')
sfile = ril.sys_suboptimals(_fname, seq,
ener=myener, opts=s_opts, verb=verb, force=force)
[sfile, bfile, efile, rfile, psfile] = ril.sys_barriers(_fname, seq, sfile,
barriers=barriers, minh=minh, maxn=maxn, k0=k0, temp=temp,
verb=verb, force=force)
# this function modifies sortednodes and hypercount... not
# nice!
add_edges(
RG,
bfile,
rfile,
'uni',
spe,
seq,
sortednodes,
hypercount)
s_opts.pop()
_fname = name
sfile = ril.sys_suboptimals(_fname, seq,
ener=myener, opts=[], verb=verb, force=force)
[sfile, bfile, efile, rfile, psfile] = ril.sys_barriers(_fname, seq, sfile,
barriers=barriers, minh=minh, maxn=maxn, k0=k0, temp=temp,
verb=verb, force=force)
if bionly:
add_edges(
RG,
bfile,
rfile,
'bionly',
spe,
seq,
sortednodes,
hypercount)
else:
add_edges(
RG,
bfile,
rfile,
'bi',
spe,
seq,
sortednodes,
hypercount)
elif bionly:
continue
else:
if s_ener is None:
myener, nos = ril.sys_subopt_range(
seq, nos=s_maxn, maxe=20, verb=verb)
else:
myener = s_ener
_fname = name
sfile = ril.sys_suboptimals(_fname, seq,
ener=myener, opts=[], verb=verb, force=force)
[sfile, bfile, efile, rfile, psfile] = ril.sys_barriers(_fname, seq, sfile,
barriers=barriers, minh=minh, maxn=maxn, k0=k0, temp=temp,
verb=verb, force=force)
add_edges(
RG,
bfile,
rfile,
'uni',
spe,
seq,
sortednodes,
hypercount)
print "connected components",
print [len(comp) for comp in
sorted(nx.strongly_connected_components(RG), key=len, reverse=True)]
for e, comp in enumerate(
sorted(nx.strongly_connected_components(RG), key=len, reverse=True)):
# print 'e', comp
if e == 0:
continue
print "Discarding connected component!", len(comp) # , comp
for i in comp:
sortednodes[i] = 0
return max(nx.strongly_connected_component_subgraphs(
RG), key=len), sortednodes
def main():
""" Interkin - folding kinetics of two interacting RNA molecules
* call the pipeline: "RNAsubopt | barriers" in order to get tree files and
rate matrices
* make a reaction graph composed of uni- and bi-molecular reactions found
in the rate matrices
* visualize the graph using networkx or D3js
* calculate the equilibrium distribution and see how much it differs from
the complete cofolded ensemble
* dump the graph in order to translate it into a ODE system using the perl
SundialsWrapper library
TODO: write a landscape library in order to get rid of BarMap dependency
"""
args = get_interkin_args()
""" Read Input & Update Arguments """
name, inseq = ril.parse_vienna_stdin(sys.stdin)
if args.name == '' :
args.name = name
else :
name = args.name
if args.verbose:
print "# Input: {:s} {:s} {:6.2f} kcal/mol".format(name, inseq, args.s_ener)
if args.s_ener == 0 :
args.s_ener, args.s_maxn = ril.sys_subopt_range(inseq,
nos=args.s_maxn,
maxe=20, #args.s_maxe,
verb=args.verbose)
if args.verbose:
print "# Energyrange {:.2f} computes {:d} sequences".format(
args.s_ener, args.s_maxn)
""" Dirty way to use RNAsubopt symmetry correction as commandline interface """
s_options = ['|', args.spatch]
if args.symmetry : s_options.append('-s')
""" Choose the set of species for further analysis """
# default: [A, A, AA], [A, B, AB, AA, BB], [A, B, C, AA, AB, AC, BB, BC, CC]
# nohomo: [A, B, AB] (for debugging)
specieslist = get_species(inseq, args.nohomo)
""" Compute folding kinetics """
bionly = False # Debugging option, compute kinetics only from cofold tree
RG, nodes = cofold_barriers(name, specieslist,
s_ener = args.s_ener,
s_maxn = args.s_maxn,
s_opts = s_options,
barriers='barriers',
minh=args.b_minh,
maxn=args.b_maxn,
k0=args.k0,
temp=37.0,
moves='single-base-pair',
gzip=True,
rates=True,
bsize=False,
saddle=False,
bionly=bionly,
force=args.force,
verb=args.verbose)
##### NOTE: Hack to check out if crnsimulator works like sundials:
from crnsimulator import writeODElib
import sympy
ntv = dict()
vtn = dict()
oV = []
for e, n in enumerate(filter(lambda x : nodes[x] != 0, nodes)):
var = n[0].translate(string.maketrans("&", "_"))+'_'+str(e)
ntv[n] = var
vtn[var] = n
oV.append(var)
NLRG = nx.relabel_nodes(RG, ntv)
oR = dict()
ode = dict()
for r in NLRG.nodes_iter() :
if r in vtn: continue
rate = 'k'+str(len(oR.keys()))
reactants = []
for reac in NLRG.predecessors_iter(r) :
for i in range(NLRG.number_of_edges(reac, r)) :
reactants.append(str(reac))
products = []
for prod in NLRG.successors_iter(r) :
edict = NLRG.get_edge_data(r, prod)
oR[rate] = str(edict[0]['weight'])
for i in range(NLRG.number_of_edges(r, prod)) :
products.append(str(prod))
for x in reactants:
if x in ode :
ode[x].append(['-'+rate] + reactants)
else :
ode[x]= [['-'+rate] + reactants]
for x in products:
if x in ode :
ode[x].append([rate] + reactants)
else :
ode[x]= [[rate] + reactants]
oM = []
for dx in oV :
sfunc = sympy.sympify(' + '.join(['*'.join(map(str,xp)) for xp in ode[dx]]))
ode[dx] = sfunc
oM.append(sfunc)
oM = sympy.Matrix(oM)
oJ = None
odefile, odename = writeODElib(oV, oM, jacobian=oJ, rdict=oR, filename='interkin')
print 'Happy simulating: ODE system wrote to File:', odefile
'''
""" Compute equilibrium properties """
# plot RNAcofold equilibrium properties with a given range of a0s and b0s
# plot gradient basin equilibrium for a given range of a0s and b0s
# => [seq&seq], [K]
kT=0.61632077549999997
a0s = map(lambda x: 10**-x, range(9,8,-3))
b0s = map(lambda x: 10**-x, range(6,1,-1))
eA =0
eB =0
eAA=0
eAB=0
eBB=0
for (name, species) in specieslist :
if '&' not in name: continue
[seqA, seqB] = species.split('&')
[nA, nB] = name.split('&')
plotname = args.name+'_'+nA+'_'+nB
homodimer = (seqA == seqB)
""" if it is a homodimer, G_A = G_B and G_AB = G_AA = G_BB """
if not homodimer :
[G_A, G_B, G_AB, G_AA, G_BB] = conc.cofold_free_energies(species)
print 'ref_cfold', species, nA, G_A, nB, G_B, \
nA+nB, G_AB, nA*2, G_AA, nB*2, G_BB
eqdata = conc.cofold_equilibrium(species, a0s, b0s)
conc.cofold_plot(eqdata,plotname+'_cofold_plot')
"""
[G_A, G_B, G_AB, G_AA, G_BB] = basin_free_energies(species)
print 'ref_cfold', species, nA, G_A, nB, G_B, \
nA+nB, G_AB, nA*2, G_AA, nB*2, G_BB
eqdata = conc.cofold_equilibrium(species, a0s, b0s)
"""
RNA.cvar.cut_point = len(seqA)+1
[stmp,G_A,G_B,G_AB,waste] = RNA.co_pf_fold(seqA+seqB,None)
K = math.e**((G_A+G_B-G_AB)/kT)
print 'ref_bimol', species, nA, G_A, nB, G_B, nA+nB, G_AB, "K", K
if homodimer :
eqdata = conc.bimol_equilibrium(K, b0s, [])
conc.homodim_plot(eqdata,plotname+'_bimol_plot')
else :
eqdata = conc.bimol_equilibrium(K, a0s, b0s)
conc.bimol_plot(eqdata,plotname+'_bimol_plot')
if not bionly :
[G_A, G_B, G_AB] = unimolecular_basins(RG, name, species, args, nodes)
K = math.e**((G_A+G_B-G_AB)/kT)
print 'uitree', species, nA, G_A, nB, G_B, nA+nB, G_AB, "K", K
[G_ApB, G_AB] = bimolecular_cofold_basins(
RG, name, species, args, nodes, bionly)
K = math.e**((G_ApB-G_AB)/kT)
print 'bitree', species, nA+'+'+nB, G_ApB, nA+nB, G_AB, "K", K
if homodimer :
eqdata = conc.bimol_equilibrium(K, b0s, [])
conc.homodim_plot(eqdata, plotname+'_coarse_grain_plot')
else :
eqdata = conc.bimol_equilibrium(K, a0s, b0s)
[a0, b0, eA, eB, eAB] = zip(*eqdata)
conc.bimol_plot(eqdata, plotname+'_coarse_grain_plot')
if False : # Depricated and a bit ugly code, it is for debugging only
""" Compare lists of gradient basin energies for fake and true dimers """
interkin_equilibrium(specieslist, args)
# Calculate equilibrium distribution by hand... (like for prions!)
# use that as a start for the simulation:
# *) calculate the concentrations of species
# *) calculate the occupancy of an lmin at equilibrium
# *) return the equilibrium starting population for a simulation ...
'''
return
def cofold_barriers(_name, species,
s_opts = ['|', 'pylands_spatch.py'],
s_ener = None,
s_maxn = 59000000,
barriers='barriers',
minh=0.001,
maxn=50,
k0=1.0,
temp=37.0,
moves='single-base-pair',
gzip=True,
rates=True,
bsize=False,
saddle=False,
bionly=False,
force=False,
verb=False):
""" Simulate inter-molecular folding
Compute folding kinetics
returns the biggest connected component and a list of nodes
TODO:
*) @h**o-dimers: RNAsubopt-barriers does not correct for two-fold symmetry!
"""
noLP=False # MUST BE FALSE!
circ=False # MUST BE FALSE!
mfile=''
if minh > 0.5 :
print "Warning: increasing the minh option for cofolded barriers may " + \
"destroy the separation of monomer and dimer gradient basins!"
RG = nx.MultiDiGraph()
sortednodes = c.OrderedDict()
hypercount = [0]
for spe, seq in species :
name = _name + "_" + spe
if '&' in name :
""" true dimer only run """
name = name.translate(string.maketrans("&", "_"))
if s_ener is None :
myener, nos = ril.sys_subopt_range(seq, nos=s_maxn, maxe=20, verb=verb)
else :
myener = s_ener
if bionly is False :
_fname = name + "_truedimers"
s_opts.append('-d')
sfile = ril.sys_suboptimals(_fname, seq,
ener=myener, opts=s_opts, verb=verb, force=force)
[sfile, bfile, efile, rfile, psfile] = ril.sys_barriers(_fname, seq, sfile,
barriers=barriers, minh=minh, maxn=maxn, k0=k0, temp=temp,
verb=verb, force=force)
# this function modifies sortednodes and hypercount... not nice!
add_edges(RG, bfile, rfile, 'uni', spe, seq, sortednodes, hypercount)
s_opts.pop()
_fname = name
sfile = ril.sys_suboptimals(_fname, seq,
ener=myener, opts=[], verb=verb, force=force)
[sfile, bfile, efile, rfile, psfile] = ril.sys_barriers(_fname, seq, sfile,
barriers=barriers, minh=minh, maxn=maxn, k0=k0, temp=temp,
verb=verb, force=force)
if bionly :
add_edges(RG, bfile, rfile, 'bionly', spe, seq, sortednodes, hypercount)
else :
add_edges(RG, bfile, rfile, 'bi', spe, seq, sortednodes, hypercount)
elif bionly :
continue
else :
if s_ener is None :
myener, nos = ril.sys_subopt_range(seq, nos=s_maxn, maxe=20, verb=verb)
else :
myener = s_ener
_fname = name
sfile = ril.sys_suboptimals(_fname, seq,
ener=myener, opts=[], verb=verb, force=force)
[sfile, bfile, efile, rfile, psfile] = ril.sys_barriers(_fname, seq, sfile,
barriers=barriers, minh=minh, maxn=maxn, k0=k0, temp=temp,
verb=verb, force=force)
add_edges(RG, bfile, rfile, 'uni', spe, seq, sortednodes, hypercount)
print "connected components",
print [len(comp) for comp in
sorted(nx.strongly_connected_components(RG), key=len, reverse=True)]
for e, comp in enumerate(
sorted(nx.strongly_connected_components(RG), key=len, reverse=True)) :
#print 'e', comp
if e == 0 : continue
print "Discarding connected component!", len(comp)#, comp
for i in comp: sortednodes[i] = 0
return max(nx.strongly_connected_component_subgraphs(RG), key=len), sortednodes
def main(args):
""" BarMap-v2.0 -- cotransriptional folding
Dependencies: RNAsubopt, barriers, treekin
The implementation is split into 4 steps ...
"""
# Read Input & Update Arguments
name, seq = ril.parse_vienna_stdin(sys.stdin)
# One name, just to be clear ...
(args.name, name) = (args.name, args.name) if args.name else (name, name)
if args.stop is None:
args.stop = len(seq)
else:
seq = seq[:args.stop]
print("# Input: {:s} {:s}".format(name, seq))
if args.s_ener is None:
args.s_ener, args.s_maxn = ril.sys_subopt_range(seq,
nos=args.s_maxn, maxe=args.s_maxe, verb=(args.verbose > 0))
print("# Energyrange {:.2f} computes {:d} sequences".format(
args.s_ener, args.s_maxn))
elif args.verbose:
args.s_ener, args.s_maxn = ril.sys_subopt_range(seq,
nos=0, maxe=args.s_ener, verb=False)
print("# Energyrange {:.2f} computes {:d} sequences".format(
args.s_ener, args.s_maxn))
if not args.tmpdir:
args.tmpdir = 'BarMap_' + args.name
if not os.path.exists(args.tmpdir):
os.makedirs(args.tmpdir)
"""# Starting with BarMap computations ... """
while True:
print("""# writing RNAsubopt files ... """)
sname = "{}/{}-ener_{:.2f}".format(args.tmpdir, args.name, args.s_ener)
#if args.circ: myfile += '_circ'
if args.noLP:
sname += '_noLP'
sfiles = barmap_subopts(sname, seq, args)
print("""# writing barriers files ... """)
bname = "{}-minh_{}-maxn_{}-k0_{}".format(sname,
args.b_minh, args.b_maxn, args.k0)
bfiles = barmap_barriers(bname, seq, sfiles, args)
print("""# writing/parsing mapping information ... """)
plist = barmap_mapping(bname, seq, args)
print("""# simulations using treekin ... """)
try:
tfiles = barmap_treekin(bname, seq, bfiles, plist, args)
break
except LostPopulationError as e:
if args.adaptive:
args.s_ener += 2
print('repeating caluclations with higher energy:', args.s_ener)
else:
print('caluclations failed with current suboptimal energy range:', args.s_ener)
break
except SubprocessError as e:
if args.adaptive:
args.s_ener += 2
print('repeating caluclations with higher energy:', args.s_ener)
else:
print('caluclations failed with current suboptimal energy range:', args.s_ener)
break
if args.xmgrace or args.pyplot:
print("""# Processing treekin results for plotting ... """)
courses = get_plot_data(tfiles, plist, args)
if args.xmgrace:
grfile = plot_xmgrace(courses, plist, args)
print("# Your results have been plotted in the file: {}".format(grfile))
if args.pyplot:
plotfile = plot_matplotlib(name, seq, courses, plist, args)
print("# Your results have been plotted in the file: {}".format(plotfile))
print("# Thank you for using BarMap b(^.^)d")
def main(args):
""" BarMap-v2.0 -- cotransriptional folding
Dependencies: RNAsubopt, barriers, treekin
The implementation is split into 4 steps ...
"""
# Read Input & Update Arguments
name, seq = ril.parse_vienna_stdin(sys.stdin)
# One name, just to be clear ...
(args.name, name) = (args.name, args.name) if args.name else (name, name)
if args.stop is None:
args.stop = len(seq)
else:
seq = seq[:args.stop]
print("# Input: {:s} {:s}".format(name, seq))
if args.pourRNA:
args.s_ener = args.max_energy
else:
if args.s_ener is None:
args.s_ener, args.s_maxn = ril.sys_subopt_range(seq,
nos=args.s_maxn, maxe=args.s_maxe, verb=(args.verbose > 0))
print("# Energyrange {:.2f} computes {:d} sequences".format(
args.s_ener, args.s_maxn))
elif args.verbose:
args.s_ener, args.s_maxn = ril.sys_subopt_range(seq,
nos=0, maxe=args.s_ener, verb=False)
print("# Energyrange {:.2f} computes {:d} sequences".format(
args.s_ener, args.s_maxn))
if not args.tmpdir:
args.tmpdir = 'BarMap_' + args.name
if not os.path.exists(args.tmpdir):
os.makedirs(args.tmpdir)
"""# Starting with BarMap computations ... """
while True:
bfiles = None
plist = None
sname = "{}/{}-ener_{:.2f}".format(args.tmpdir, args.name, args.s_ener)
bname = "{}-minh_{}-maxn_{}-k0_{}".format(sname, args.b_minh, args.b_maxn, args.k0)
if args.pourRNA:
print("""# computing pourRNA... """)
bfiles = barmap_pourRNA(bname, seq, args)
print("""# writing/parsing mapping information ... """)
plist = barmap_mapping_pourRNA(bname, seq, args)
else:
#if args.circ: myfile += '_circ'
if args.noLP:
sname += '_noLP'
print("""# writing RNAsubopt files ... """)
sfiles = barmap_subopts(sname, seq, args)
print("""# writing barriers files ... """)
bfiles = barmap_barriers(bname, seq, sfiles, args)
print("""# writing/parsing mapping information ... """)
plist = barmap_mapping(bname, seq, args)
print("""# simulations using treekin ... """)
try:
tfiles = barmap_treekin(bname, seq, bfiles, plist, args)
break
except LostPopulationError as e:
if args.adaptive:
args.s_ener += 2
print('repeating caluclations with higher energy:', args.s_ener)
else:
print('caluclations failed with current suboptimal energy range:', args.s_ener)
exit()
except SubprocessError as e:
if args.adaptive:
args.s_ener += 2
print('repeating caluclations with higher energy:', args.s_ener)
else:
print('caluclations failed with current suboptimal energy range:', args.s_ener)
exit()
if args.xmgrace or args.pyplot:
print("""# Processing treekin results for plotting ... """)
courses = get_plot_data(tfiles, plist, args)
if args.xmgrace:
grfile = plot_xmgrace(courses, plist, args)
print("# Your results have been plotted in the file: {}".format(grfile))
if args.pyplot:
plotfile = plot_matplotlib(name, seq, courses, plist, args)
print("# Your results have been plotted in the file: {}".format(plotfile))
print("# Thank you for using BarMap b(^.^)d")