def __init__(self, parameters, maxParameter,
g, V, prefac, gtot,
scaledVolt, T, Vq):
self.Vq = Vq
self.parameters = parameters
self.V = V
self.T = T
self.isZeroT = mp.almosteq(self.T, mpf(0))
self.scaledVolt = scaledVolt
self.g = g
self.maxParameter = maxParameter
self.prefac = prefac
self.gtot = gtot
### input check ###
if len(self.maxParameter.shape) == 1:
self.maxParameter = self.maxParameter[newaxis,:]
if len(self.prefac.shape) == 1:
self.prefac = self.prefac[newaxis,:]
if self.g.shape != self.parameters.shape or \
self.V.shape != self.scaledVolt.shape or \
self.maxParameter.shape[1] != self.parameters.shape[0]:
raise ValueError
if len(self.g.shape) == 1:
self.g = self.g[:, newaxis]
self.parameters = self.parameters[:, newaxis]
self.prefac = self.prefac * np.power(self.maxParameter,
-self.scaledVolt[...,newaxis])
def emit(name, iname, cdf, args, no_small=False):
V = []
for arg in sorted(args):
y = cdf(*arg)
if isinstance(y, mpf):
e = sp.nsimplify(y, rational=True)
if e.is_Rational and e.q <= 1000 and mp.almosteq(e, y, 1e-25):
y = e
else:
y = N(y)
V.append(arg + (y,))
for v in V:
if name:
test(name, *v)
for v in V:
if iname and (not no_small or 1/1000 <= v[-1] <= 999/1000):
test(iname, *(v[:-2] + v[:-3:-1]))
def __init__(self, input_parameters, V, Q, T):
self.V, self.Q, self.T = V, mpf(Q), mpf(T)
########## Process input # Perform Sanity Checks ###########
for i, j in input_parameters.items():
if not isinstance(j, list):
raise ValueError
self.input_parameters[i] = np.asarray(j)
if len(set(map(len, input_parameters.values()))) > 1:
raise ValueError
if not isinstance(self.V, np.ndarray) or not isinstance(self.V, list):
self.V = np.array([self.V]).ravel()
self.isZeroT = mp.almosteq(self.T, mpf(0))
########### Restructure distance and voltage, if necessary
if len(self.input_parameters["x"].shape) == 1:
self.input_parameters["x"] = self.input_parameters["x"][:,newaxis]
########### Generate parameters
self.gtot = mp.fsum(self.input_parameters["g"])
self.genParameters()
self.genScaledVoltage()
def __init__(self, input_parameters, V, Q, T):
self.V, self.Q, self.T = V, mpf(Q), mpf(T)
########## Process input # Perform Sanity Checks ###########
for i, j in input_parameters.items():
if not isinstance(j, list):
raise ValueError
self.input_parameters[i] = np.asarray(j)
if len(set(map(len, input_parameters.values()))) > 1:
raise ValueError
if not isinstance(self.V, np.ndarray) or not isinstance(self.V, list):
self.V = np.array([self.V]).ravel()
self.isZeroT = mp.almosteq(self.T, mpf(0))
########### Restructure distance and voltage, if necessary
if len(self.input_parameters["x"].shape) == 1:
self.input_parameters["x"] = self.input_parameters["x"][:, newaxis]
########### Generate parameters
self.gtot = mp.fsum(self.input_parameters["g"])
self.genParameters()
self.genScaledVoltage()