return dist
if __name__ == "__main__": #If the module is executed as a program, run a test.
from cobra.io.sbml import read_sbml_model
cobramodel = read_sbml_model('../SBML/SCHUETZR.xml')
import loadData as load
fluxvalues = load.ExpFluxesfromXML('expdata.xml', 'Perrenoud', 'Batch',
'aerobe')
rmap = load.ReactionMapfromXML('reactionmaps.xml', 'Perrenoud', 'SCHUETZR')
optreq = 1.0
import QPmindist as qp
gurobimodel = qp.QPmindist(cobramodel, fluxvalues, rmap, optreq)
QPsolutiondict = qp.getgurobisolutiondict(gurobimodel)
import extractflux2 as extract
extractfluxdict = extract.extractfluxdict(QPsolutiondict, rmap)
dictdist = compdistdict(extractfluxdict)
print('dist:', dictdist)
simple1 = {"A": 1, "B": 2, "C": 3}
simple2 = {"A": 1, "B": 2, "C": 4}
simpledist = compdistdict(simple1, expdata=simple2)
def optreqanalysis(modeldicts,
objectives,
experiments,
steps=10,
makeplots=True,
expfluxdict="Default",
plotter="easyviz"):
'''Function for evaluating how the minimally achievable distance between a flux solution and a set of experimental fluxes
changes when varying the required relative FBA objective-optimality of the flux solution.
syntax: optreqanalysis(modeldicts,objectives,experiments,steps = 10,makeplots = True,expfluxdict)
arguments:
modeldicts: An array of python dictionaries with the following fields:
modelobject: A CobraPy model object for the model in question.
reactionmap: A reaction map array mapping between model reactions and experimental reactions for the model and experiment in question.
objectives: A list of objectives to be used in the analysis.
experiments: A list of experiments to be used in the analysis
steps: The granularity of the analysis and produced plots.
makeplots: Whether plots should be produced or not
expfluxdict: A python dictionary with experiment-ids as keys and the corresponding flux value arrays as values.
'''
for objective in objectives:
pass #Placeholder
for experiment in experiments:
pass #Placeholder
if expfluxdict == "Default": #This section should be rewritten to use an "expflux" dict.
expdata = scipy.io.loadmat('expdata.mat') #load experimentaldata
perrenoud = expdata['expdata']['perrenoud']
fluxvalarray = perrenoud[0][0][0][0][0][0][0][0][0][0][0][0][0][0]
fluxvalues = [row[0] for row in fluxvalarray
] #expdata.perrenoud.abs.batch.aerobe.fluxvalues
expfluxdict = load.ExpFluxesfromXML('expdata.xml', 'Perrenoud',
'Batch', 'aerobe')
resultlist = []
for modeldict in modeldicts:
cobramodel = modeldict['modelobject']
#print 'modeldict:',modeldict
reactionmap = modeldict['reactionmap']
#print 'cobramodel:',cobramodel
#print type(cobramodel)
optreqs = []
for i in range(steps + 1):
optreqs.append(float(i) / steps)
results = []
#print 'opreqs:',optreqs
#q = raw_input('Continue?')
for optreq in optreqs:
optimizedmodel = QPmindist(cobramodel, fluxvalues, reactionmap,
optreq)
results.append(math.sqrt(optimizedmodel.ObjVal))
resultlist.append(results)
#Using easyviz
#ev.plot(optreqs,results)
#ev.hold()
#Using prettyplotlib
#fig, ax = plt.subplots(1)
#ppl.scatter(ax, x, y)
#ppl.plot(optreqs,results)
return resultlist
