 # I can't how to generate a number of data points from this part of a package

I have a package and this part is written to calculate the quantity called ‘action’ at a output temperature T. But now I need a set of ‘action’ at slightly different temperatures say T+1e-3,T+31e-3,T+41e-3… Etc.Since I am a beginner at python I can’t figure out where in. This definition I have to put a loop to print different values of action at slightly different temperatures. The part of code is attached as below

``````def _tunnelFromPhaseAtT(T, phases, start_phase, V, dV,
phitol, overlapAngle, nuclCriterion,
fullTunneling_params, verbose, outdict):
"""
Find the lowest action tunneling solution.
Return ``nuclCriterion(S,T)``, and store a dictionary describing the
transition in outdict for key `T`.
"""
try:
T = T  # need this when the function is run from optimize.fmin
except:
pass
if T in outdict:
return nuclCriterion(outdict[T]['action'], T)

def fmin(x):
return optimize.fmin(V, x, args=(T,),
xtol=phitol, ftol=np.inf, disp=False)

# Loop through all the phases, adding acceptable minima
x0 = fmin(start_phase.valAt(T))
V0 = V(x0, T)
tunnel_list = []
for key in phases.keys():
if key == start_phase.key:
continue
p = phases[key]
if (p.T > T or p.T[-1] < T):
continue
x1 = fmin(p.valAt(T))
V1 = V(x1, T)
if V1 >= V0:
continue
tdict = dict(low_vev=x1, high_vev=x0, Tnuc=T,
low_phase=key, high_phase=start_phase.key)
tunnel_list.append(tdict)
# Check for overlap
if overlapAngle > 0:
excluded = []
cos_overlap = np.cos(overlapAngle * np.pi/180)
for i in xrange(1, len(tunnel_list)):
for j in xrange(i):
xi = tunnel_list[i]['low_vev']
xj = tunnel_list[j]['low_vev']
xi2 = np.sum((xi-x0)**2)
xj2 = np.sum((xj-x0)**2)
dotij = np.sum((xj-x0)*(xi-x0))
if dotij >= np.sqrt(xi2*xj2) * cos_overlap:
excluded.append(i if xi2 > xj2 else j)
for i in sorted(excluded)[::-1]:
del tunnel_list[i]
# Get rid of the T parameter for V and dV
def V_(x,T=T,V=V): return V(x,T)
def dV_(x,T=T,dV=dV): return dV(x,T)
# For each item in tunnel_list, try tunneling
lowest_action = np.inf
lowest_tdict = dict(action=np.inf)
for tdict in tunnel_list:
x1 = tdict['low_vev']
try:
print("Tunneling from phase %s to phase %s at T=%0.4g"
% (tdict['high_phase'], tdict['low_phase'], T))
print("high_vev =", tdict['high_vev'])
print("low_vev =", tdict['low_vev'])
tobj = pathDeformation.fullTunneling(
[x1,x0], V_, dV_, callback_data=T,
**fullTunneling_params)
tdict['instanton'] = tobj
tdict['action'] = tobj.action
tdict['trantype'] = 1
except tunneling1D.PotentialError as err:
if err.args == "no barrier":
tdict['trantype'] = 0
tdict['action'] = 0.0
elif err.args == "stable, not metastable":
tdict['trantype'] = 0
tdict['action'] = np.inf
else:
print("Unexpected error message.")
raise
if tdict['action'] <= lowest_action:
lowest_action = tdict['action']
lowest_tdict = tdict
outdict[T] = lowest_tdict
return nuclCriterion(lowest_action, T)
``````

At the top of this discourse category it says

A place to talk about packaging Python software and the tooling to make that possible.
Use this category for discussions relating to anything packaging in Python

So this is not the correct place for this kind of question, unless you are trying to package your code so others can use it. You may have better luck in a forum oriented toward python beginners or coding in general. When you ask there (not here), try to whittle the problem down to the essential question you are asking: I can’t really understand what you have vs. what you want.

I am very very sorry for this . I moved this question to users