问题描述
这是更新后的帖子：我提供了完整的代码。在这段代码中，我是常数。我试图使 I 成为可以使用此代码生成的高斯函数：
高斯代码：
mean = 0
standard_deviation = 1
x_values = np.arange(-5,5,0.1)
y_values = scipy.stats.norm(mean,standard_deviation)
plt.plot(x_values,y_values.pdf(x_values))
我想将常量 I 更改为上面的曲线的主要代码，即 I 不再是常量而是 I(t) 形式的高斯曲线：
from scipy import *
from scipy.integrate import ode
from pylab import *
import matplotlib.pyplot as plt
### Simualtion Outputs ###
N = [] # y[0] Carrier concentration
S = [] # y[1] Photon concentration
### Simualtion input parameters ###
I = 2.0e-2 # p[0] Pumping current (A)
q = 1.6e-19 # p[1] Electron charge (C)
V = 9e-11 # p[2] Device volume (cm^3)
tn = 1.0e-9 # p[3] Carrier relaxation time in seconds (s)
g0 = 1.5e-5 # p[4] Gain slope constant (cm^3/s)
Nth = 1e18 # p[5] Threshold carrier density (cm^-3)
EPS = 1.5e-17 # p[6] Gain compression factor (cm^3)
Gamma = 0.3 # p[7] Confinement factor
tp = 1.0e-12 # p[8] Photon lifetime in cavity (s)
Beta = 1.0e-4 # p[9] Spontaneous Emission Factor
### Define equations to be solved
def Laser_rates(t,y,p):
I = p[0]; q = p[1]; V = p[2]; tn = p[3]; g0 = p[4]; Nth = p[5]; EPS = p[6]; Gamma = p[7]; tp = p[8]; Beta = p[9]
dy = zeros([2])
dy[0] = (I/(q* V)) - (y[0]/tn) - g0*(y[0] - Nth)*(y[1]/(1 + EPS* y[1]))
dy[1] = Gamma* g0* (y[0] - Nth)*(y[1]/(1 + EPS* y[1])) - y[1]/tp + (Gamma* Beta* y[0]) / tn
return dy
### Time and initial conditions ###
t0 = 0; tEnd = 1e-9; dt = 1e-12 #Time constraints
y0 = [4.78e18,1e12] #Initial conditions
Y=[]; T=[] #Create empty lists
p = [41.8742e-2,1.6e-19,9e-11,5e-9,1.5e-5,5.75e18,1.5e-17,0.2,1.33e-12,0.0001] #Parameters for odes
#p = [ I,q,V,tn,g0,Nth,EPS,Gamma,tp,Beta]
#Setup integrator with desired parameters
r = ode(Laser_rates).set_integrator('vode',method = 'bdf')
r = ode(Laser_rates).set_integrator('dopri5',nsteps = 1e4)
r.set_f_params(p).set_initial_value(y0,t0)
### Simualtion check ###
while r.successful() and r.t+dt < tEnd:
r.integrate(r.t + dt)
Y.append(r.y) #Makes a list of 1d arrays
T.append(r.t)
### Format output ###
Y = array(Y) #Convert from list to 2d array
N = Y[:,0]
S = Y[:,1]
### Plotting ###
f,axarr = plt.subplots(2,sharex=True) # Two subplots,the axes array is 1-d
axarr[0].plot(T,N)
axarr[0].set_ylabel("Carrier Conc (cm^-3)")
axarr[0].set_title('Laser-Rate Simulation')
axarr[1].plot(T,S)
axarr[1].set_ylabel("Photon Conc (cm^-3)")
axarr[1].set_xlabel("Time (s)")
show()
解决方法
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