def showUI(*args, **kwargs):
if chimera.nogui:
tk.Tk().withdraw()
model = Model()
global ui
if not ui:
ui = DummyDialog(*args, **kwargs)
model.gui = ui
controller = Controller(gui=ui, model=model)
ui.enter()
def showUI(*args, **kwargs):
if chimera.nogui:
tk.Tk().withdraw()
ui = QMSetupDialog(*args, **kwargs)
model = Model(gui=ui)
controller = Controller(gui=ui, model=model)
ui.enter()
def showUI():
if chimera.nogui:
tk.Tk().withdraw()
global ui
if not ui:
ui = PoPMuSiCExtension()
model = Model(gui=ui)
controller = Controller(gui=ui, model=model)
ui.enter()
def plot_ionization_(elem,model_lst,xlims=None):
Zcolor=[ 'red','orangered','orange',
'yellow','yellowgreen','green', 'cyan',
'teal','blue','blueviolet']
Z = [-4.,-3.8,-3.6,
-3.4,-3.2,-3.0,-2.8,
-2.6,-2.4,-2.2]
for i in to_plot[elem]:
if xlims:
l,u = observed[elem][i]["column"][0], observed[elem][i]["column"][2]
if l==-30.: l=0.
plt.fill( [xlims[0], xlims[1], xlims[1], xlims[0]],
[l,l,u,u], '0.50', alpha=0.1)
plt.axhline(y=u,linestyle='dashed',linewidth=2, color='k')
for j in range(len(Z)):
mods=[item for item in model_lst if Z[j]-0.05<float(item.data['Z'])<Z[j]+0.05]
if len(mods)==0:
print("skipping Z=%lf"%(Z[j]))
continue
U=[item.data['U'] for item in mods]
N=Model.get_qty_lst(mods,elem,"column",i)
#if elem=='Si':
# N=[item+1.34 for item in N] #ISM to popII
try:
assert(len(N)>0 and len(U)>0)
except AssertionError:
print('N=',N)
print('U=',U)
raise
plt.plot(U, N, 'o', color=Zcolor[j],label="Z="+str(Z[j]))
plt.minorticks_on()
plt.ylabel(r"log $N_{%s}$"%(elem+roman[i]))
plt.xlabel(r"log U")
plt.legend(loc='lower right', shadow=True,numpoints=1)
plt.title('%s'%elem+roman[i])
plt.xlim(min(U),max(U))
plt.ylim(min(N)-1.,max(N)+1.)
plt.show()
def showUI(callback=None, *args, **kwargs):
"""
Requested by Chimera way-of-doing-things
"""
if chimera.nogui:
tk.Tk().withdraw()
global ui
if not ui: # Edit this to reflect the name of the class!
ui = MMSetupDialog(*args, **kwargs)
model = Model(gui=ui)
controller = Controller(gui=ui, model=model)
ui.enter()
if callback:
ui.addCallback(callback)
def __init__(self,name="Truss Model 01"):
Model.__init__(self,name=name,mtype="truss")
self.F = [] # Forces
self.U = [] # Displacements
self.dof = 2 # 2 DOF for truss element
def __init__(self,name="Spring Model 01"):
Model.__init__(self,name=name,mtype="spring")
self.F = {} # Forces
self.U = {} # Displacements
self.dof = 1 # 1 DOF per Node
self.IS_KG_BUILDED = False
def __init__(self,name="Beam Model 01"):
Model.__init__(self,name=name,mtype="beam")
self.F = {} # Forces
self.U = {} # Displacements
self.dof = 2 # 2 DOF for beam element
self.IS_KG_BUILDED = False
def __init__(self,name="Bar Model 01"):
Model.__init__(self,name=name,mtype="bar")
self.F = {} # Forces
self.U = {} # Displacements
self.dof = 1 # 1 DOF for bar element (per node)
self.IS_KG_BUILDED = False
optimization.report()
# Choose problem to solve
problem_ids = []
##problem_ids = range(0,230)
##problem_ids = chain(range(200,203), range(191, 193))
for problem_id in problem_ids:
print(f"######### Solving problem {problem_id} #########")
# Initialize the settings
update_settings(problem_id)
# Initialize the model
model = Model()
# Check computation setup
build_surrogate = bool(settings["surrogate"]["surrogate"])
load_surrogate = settings["surrogate"]["surrogate"] == "load"
train_from_data = settings["data"]["evaluator"] == "data"
perform_optimization = bool(settings["optimization"]["algorithm"])
# Initialize
if build_surrogate:
surrogate = Surrogate(model)
if perform_optimization:
optimization = Optimization(model)
# Perform computation
# Surrogate only
def model(self, key):
return Model(key)