def __init__(self, text, colour = None, size = None): Spectrum.__init__(self, text) self.colour = colour self.size = size self.make_spacer_line() self.construct()
def __init__(self, bins, s=1, r=2, thermal_t=600.0):
self.bins = bins
self.scaling = s
self.e2 = 1e6
self.thermal_t = thermal_t
# Maxwellian distribution, Eq.(9-6)
self.m = lambda x: x**0.5 * np.exp(-x / (k * self.thermal_t))
# U235 chi distribution, Eq.(2-112)
self.chi = lambda x: np.exp(-1.036e-6 * x) * np.sinh(
(2.29e-6 * x)**0.5)
# Middle energy range
self.f = lambda x: 1 / x
self.r = 0
E = np.logspace(-5, 1, 1000)
R = np.array([self.balance(e) for e in E])
self.e1 = np.interp(r, R, E)
self.r = r
self.c1 = 1.0
self.c2 = self.m(self.e1) / self.f(self.e1)
self.c3 = self.c2 * self.f(self.e2) / self.chi(self.e2)
vals = self.make_discrete(self.bins, self.scaling)
Spectrum.__init__(self, self.bins, vals, False, dfde=True)
def __init__(self, P):
self.power = P
data = self.get_data()
S = self.calc_scaling_factor()
bins = data[:, 0]
vals = data[:, 1][1:]
Spectrum.__init__(self, bins, vals, False, S)
def __init__(self, bins, s=1, r=2, thermal_t=600.0):
self.bins = bins
self.scaling = s
self.e2 = 1e6
self.thermal_t = thermal_t
# Maxwellian distribution, Eq.(9-6)
self.m = lambda x: x ** 0.5 * np.exp(-x / (k * self.thermal_t))
# U235 chi distribution, Eq.(2-112)
self.chi = lambda x: np.exp(-1.036e-6 * x) * np.sinh((2.29e-6 * x) ** 0.5)
# Middle energy range
self.f = lambda x: 1 / x
self.r = 0
E = np.logspace(-5, 1, 1000)
R = np.array([self.balance(e) for e in E])
self.e1 = np.interp(r, R, E)
self.r = r
self.c1 = 1.0
self.c2 = self.m(self.e1) / self.f(self.e1)
self.c3 = self.c2 * self.f(self.e2) / self.chi(self.e2)
vals = self.make_discrete(self.bins, self.scaling)
Spectrum.__init__(self, self.bins, vals, False, dfde=True)
def __init__(self, text, on_char = "O", off_char = " "): Spectrum.__init__(self, text) self.on_char = on_char self.off_char = off_char * len(self.on_char)
def __init__(self, surface_data, spectrum_data):
self.N = surface_data[0]
self.M = surface_data[1]
random_phases = surface_data[2]
kfrag = surface_data[3]
self.wind = surface_data[4]
Spectrum.__init__(self, spectrum_data)
self.spectrum = self.get_spectrum()
if kfrag == 'log':
self.k = np.logspace(np.log10(self.k_m/4), np.log10(self.k_edge['Ku']), self.N + 1)
elif kfrag == 'quad':
self.k = np.zeros(self.N+1)
for i in range(self.N+1):
self.k[i] = self.k_m/4 + (self.k_edge['Ku']-self.k_m/4)/(self.N+1)**2*i**2
else:
self.k = np.linspace(self.k_m/4, self.k_edge['Ku'], self.N + 1)
self.k_ku = self.k[ np.where(self.k <= self.k_edge['Ku']) ]
self.k_c = self.k[ np.where(self.k <= self.k_edge['C']) ]
print(\
"Параметры модели:\n\
N={},\n\
M={},\n\
U={} м/с,\n\
Band={}\n\
mean=0".format(self.N,self.M,self.U10,self.band)
)
self.phi = np.linspace(-np.pi, np.pi,self.M + 1)
self.phi_c = self.phi + self.wind
if random_phases == 0:
self.psi = np.array([
[0 for m in range(self.M) ] for n in range(self.N) ])
elif random_phases == 1:
self.psi = np.array([
[ np.random.uniform(0,2*pi) for m in range(self.M)]
for n in range(self.N) ])
print(\
"Методы:\n\
Случайные фазы {}\n\
Отбеливание 0\n\
Заостренная волна {}\n\
".format(bool(random_phases), False)
)
print('Вычисление амплитуд гармоник...')
self.A = self.amplitude(self.k)
self.F = self.angle(self.k,self.phi)
print('Подготовка завершена.')
