def plot_variances(chemnames, logprior, scale=1.0, return_var=False):
"""
chemnames: list of chemical names
logprior: prior on params. logprior = log(1000.0) means parameters
allowed to fluctuate by a factor of 1000 """
times, bestfit, var = variances(chemnames, logprior)
for key in bestfit.keys():
Plotting.figure()
Plotting.plot(times, bestfit[key] / scale)
Plotting.hold(True)
Plotting.plot(times,
bestfit[key] / scale + scipy.sqrt(var[key]) / scale,
'r--')
Plotting.plot(times,
bestfit[key] / scale - scipy.sqrt(var[key]) / scale,
'r--')
Plotting.title(key, fontsize=16)
Plotting.xlabel('time (minutes)', fontsize=16)
Plotting.ylabel('number of molecules', fontsize=16)
xtics = Plotting.gca().get_xticklabels()
ytics = Plotting.gca().get_yticklabels()
Plotting.setp(xtics, size=16)
Plotting.setp(ytics, size=16)
#Plotting.axis([0.0,40.0,-.01,1.2e4])
Plotting.show()
if return_var:
return times, bestfit, var
def plot_variances(chemnames,logprior,scale=1.0,return_var = False) :
"""
chemnames: list of chemical names
logprior: prior on params. logprior = log(1000.0) means parameters
allowed to fluctuate by a factor of 1000 """
times, bestfit, var = variances(chemnames,logprior)
for key in bestfit.keys() :
Plotting.figure()
Plotting.plot(times,bestfit[key]/scale)
Plotting.hold(True)
Plotting.plot(times,bestfit[key]/scale + scipy.sqrt(var[key])/scale,'r--')
Plotting.plot(times,bestfit[key]/scale - scipy.sqrt(var[key])/scale,'r--')
Plotting.title(key,fontsize=16)
Plotting.xlabel('time (minutes)',fontsize=16)
Plotting.ylabel('number of molecules',fontsize=16)
xtics = Plotting.gca().get_xticklabels()
ytics = Plotting.gca().get_yticklabels()
Plotting.setp(xtics,size=16)
Plotting.setp(ytics,size=16)
#Plotting.axis([0.0,40.0,-.01,1.2e4])
Plotting.show()
if return_var :
return times, bestfit, var
