def SpectralEfficiency(TE, lam, lbg):
ynum = TE * lam / lbg
upper = np.amax(lam)
num = numlib.Integrate(ynum, lam, 1e-9, lbg)
den = numlib.Integrate(TE, lam, 1e-9, upper)
SE = num / den
return SE
def Abs_eff(lam, EM, solarconc, T):
AM = datalib.AM(lam)
upper = np.amax(lam)
BBs = datalib.BB(lam, T)
TE = BBs * EM
alpha = solarconc * (numlib.Integrate(AM * EM, lam, 100e-9, upper))
beta = np.pi * numlib.Integrate(TE, lam, 100e-9, upper)
return (alpha - beta) / (alpha)
def Lum_efficiency(lam, TE):
upper = np.amax(lam)
ph = datalib.PhLum(lam)
num = ph*TE
numerator = numlib.Integrate(num, lam, 0, upper )
den = TE
denominator = numlib.Integrate(den, lam, 0, upper)
return (numerator/denominator)
def Lum_efficiency_prime(lam, TE, TE_prime):
upper = np.amax(lam)
ph = datalib.PhLum(lam)
num = ph*TE
num_prime = ph*TE_prime
numerator = numlib.Integrate(num, lam, 0, upper )
numerator_prime = numlib.Integrate(num_prime, lam, 0, upper)
denominator = numlib.Integrate(TE, lam, 0, upper)
denominator_prime = numlib.Integrate(TE_prime, lam, 0, upper)
return (denominator*numerator_prime - numerator*denominator_prime)/(denominator**2)
def ambient_jsc(eps, lam, lbg):
### get upper bound of integral
upper = np.amax(lam)
### get AM1.5 spectrum
AM = datalib.AM(lam)
### get spectral response function (currently only Si supported for
### traditional PV... more to come soon)
SR = datalib.SR_Si(lam)
### jsc integrand
integrand = AM * SR * eps
### integrate it!
jsc = numlib.Integrate(integrand, lam, 1e-9, upper)
return jsc
def JSC(TE, lam, PV):
### hard-coding view factor for now!
F = 0.84
### get spectral response function for appropriate PV material
if (PV == 'InGaAsSb'):
SR = datalib.SR_InGaAsSb(lam)
elif (PV == 'GaSb'):
SR = datalib.SR_GaSb(lam)
else:
SR = datalib.SR_InGaAsSb(lam)
### get upper limit of lambda array... will integrate over entire
### range, in principle spectral response function will vanish at the
### appropriate boundaries of lambda
upper = np.amax(lam)
integrand = TE * SR * F * np.pi
jshc = numlib.Integrate(integrand, lam, 1e-9, upper)
return jshc
def p_in(TE, lam):
integrand = TE * np.pi
upper = np.amax(lam)
p = numlib.Integrate(integrand, lam, 1e-9, upper)
return p
def Pwr_den(TE, lam, lbg):
PDA = (lam / lbg) * TE
PD = numlib.Integrate(PDA, lam, 1e-9, lbg)
return PD * np.pi
def integrated_solar_power(lam):
AM = datalib.AM(lam)
upper = np.amax(lam)
p_in = numlib.Integrate(AM, lam, 1e-9, upper)
return p_in
def RGB_FromSpec(TE, lam):
### get color response functions
cie = datalib.CIE(lam)
### get X from TE spectrum
X = numlib.Integrate(TE*cie['xbar'], lam, 380e-9, 780e-9)
### get Y from TE spectrum
Y = numlib.Integrate(TE*cie['ybar'], lam, 380e-9, 780e-9)
### get Z from TE spectrum
Z = numlib.Integrate(TE*cie['zbar'], lam, 380e-9, 780e-9)
### get total magnitude
tot = X+Y+Z
### get normalized values
x = X/tot
y = Y/tot
z = Z/tot
## should also be equal to z = 1 - x - y
### array of xr, xg, xb, xw, ..., zr, zg, zb, zw
### use hdtv standard
xrgbw = [0.670, 0.210, 0.150, 0.3127]
yrgbw = [0.330, 0.710, 0.060, 0.3291]
zrgbw = []
for i in range(0,len(xrgbw)):
zrgbw.append(1. - xrgbw[i] - yrgbw[i])
#print("zrgbw is ",zrgbw)
## rx = yg*zb - yb*zg
rx = yrgbw[1]*zrgbw[2] - yrgbw[2]*zrgbw[1]
## ry = xb*zg - xg*zb
ry = xrgbw[2]*zrgbw[1] - xrgbw[1]*zrgbw[2]
## rz = (xg * yb) - (xb * yg)
rz = xrgbw[1]*yrgbw[2] - xrgbw[2]*yrgbw[1]
## gx = (yb * zr) - (yr * zb)
gx = yrgbw[2]*zrgbw[0] - yrgbw[0]*zrgbw[2]
## gy = (xr * zb) - (xb * zr)
gy = xrgbw[0]*zrgbw[2] - xrgbw[2]*zrgbw[0]
## gz = (xb * yr) - (xr * yb)
gz = xrgbw[2]*yrgbw[0] - xrgbw[0]*yrgbw[2]
## bx = (yr * zg) - (yg * zr)
bx = yrgbw[0]*zrgbw[1] - yrgbw[1]*zrgbw[0]
## by = (xg * zr) - (xr * zg)
by = xrgbw[1]*zrgbw[0] - xrgbw[0]*zrgbw[1]
## bz = (xr * yg) - (xg * yr)
bz = xrgbw[0]*yrgbw[1] - xrgbw[1]*yrgbw[0]
## rw = ((rx * xw) + (ry * yw) + (rz * zw)) / yw;
rw = (rx * xrgbw[3] + ry * yrgbw[3] + rz * zrgbw[3])/yrgbw[3]
## gw = ((gx * xw) + (gy * yw) + (gz * zw)) / yw;
gw = (gx * xrgbw[3] + gy * yrgbw[3] + gz * zrgbw[3])/yrgbw[3]
## bw = ((bx * xw) + (by * yw) + (bz * zw)) / yw;
bw = (bx * xrgbw[3] + by * yrgbw[3] + bz * zrgbw[3])/yrgbw[3]
## /* xyz -> rgb matrix, correctly scaled to white. */
rx = rx / rw
ry = ry / rw
rz = rz / rw
gx = gx / gw
gy = gy / gw
gz = gz / gw
bx = bx / bw
by = by / bw
bz = bz / bw
## /* rgb of the desired point */
r = (rx * x) + (ry * y) + (rz * z)
g = (gx * x) + (gy * y) + (gz * z)
b = (bx * x) + (by * y) + (bz * z)
rgblist = []
rgblist.append(r)
rgblist.append(g)
rgblist.append(b)
# are there negative values?
w = np.amin(rgblist)
if w<0:
rgblist[0] = rgblist[0] - w
rgblist[1] = rgblist[1] - w
rgblist[2] = rgblist[2] - w
# scale things so that max has value of 1
mag = np.amax(rgblist)
rgblist[0] = rgblist[0]/mag
rgblist[1] = rgblist[1]/mag
rgblist[2] = rgblist[2]/mag
#rgb = {'r': rgblist[0]/mag, 'g': rgblist[1]/mag, 'b': rgblist[2]/mag }
return rgblist
def FalseColor_FromSpec(TE, lam):
### get color response functions
#cie = datalib.CIE((lam+1500e-9)*400e-9/2400e-9)
SR = datalib.SR_InGaAsSb(lam)
#plt.plot(1e9*lam, cie['xbar'], 'red', 1e9*lam, cie['ybar'], 'green', 1e9*lam, cie['zbar'], 'blue')
#plt.show()
### This will be the shifted color cone response model for InGaAsSb
### get X from TE spectrum
#X = numlib.Integrate(TE*SR*cie['xbar'], lam, 100e-9, 4000e-9)
### get Y from TE spectrum
#Y = numlib.Integrate(TE*SR*cie['ybar'], lam, 100e-9, 4000e-9)
### get Z from TE spectrum
#Z = numlib.Integrate(TE*SR*cie['zbar'], lam, 100e-9, 4000e-9)
### this will be the step-function model for the response of
### InGaAsSb PV cell
### get X from TE spectrum only - red is a penalty coming from sub-bg emission
X = numlib.Integrate(TE, lam, 2250e-9, 10000e-9)
### get Y from TE spectrum weighted by SR function... green is good!
Y = numlib.Integrate(TE*SR, lam, 1900e-9, 2250e-9)
### get Z from TE spectrum weighted by SR function... blue is less good!
Z = numlib.Integrate(TE*SR, lam, 400e-9, 1900e-9)
### get total magnitude
tot = X+Y+Z
### get normalized values
x = X/tot
y = Y/tot
z = Z/tot
## should also be equal to z = 1 - x - y
### array of xr, xg, xb, xw, ..., zr, zg, zb, zw
### use hdtv standard
xrgbw = [0.670, 0.210, 0.150, 0.3127]
yrgbw = [0.330, 0.710, 0.060, 0.3291]
zrgbw = []
for i in range(0,len(xrgbw)):
zrgbw.append(1. - xrgbw[i] - yrgbw[i])
#print("zrgbw is ",zrgbw)
## rx = yg*zb - yb*zg
rx = yrgbw[1]*zrgbw[2] - yrgbw[2]*zrgbw[1]
## ry = xb*zg - xg*zb
ry = xrgbw[2]*zrgbw[1] - xrgbw[1]*zrgbw[2]
## rz = (xg * yb) - (xb * yg)
rz = xrgbw[1]*yrgbw[2] - xrgbw[2]*yrgbw[1]
## gx = (yb * zr) - (yr * zb)
gx = yrgbw[2]*zrgbw[0] - yrgbw[0]*zrgbw[2]
## gy = (xr * zb) - (xb * zr)
gy = xrgbw[0]*zrgbw[2] - xrgbw[2]*zrgbw[0]
## gz = (xb * yr) - (xr * yb)
gz = xrgbw[2]*yrgbw[0] - xrgbw[0]*yrgbw[2]
## bx = (yr * zg) - (yg * zr)
bx = yrgbw[0]*zrgbw[1] - yrgbw[1]*zrgbw[0]
## by = (xg * zr) - (xr * zg)
by = xrgbw[1]*zrgbw[0] - xrgbw[0]*zrgbw[1]
## bz = (xr * yg) - (xg * yr)
bz = xrgbw[0]*yrgbw[1] - xrgbw[1]*yrgbw[0]
## rw = ((rx * xw) + (ry * yw) + (rz * zw)) / yw;
rw = (rx * xrgbw[3] + ry * yrgbw[3] + rz * zrgbw[3])/yrgbw[3]
## gw = ((gx * xw) + (gy * yw) + (gz * zw)) / yw;
gw = (gx * xrgbw[3] + gy * yrgbw[3] + gz * zrgbw[3])/yrgbw[3]
## bw = ((bx * xw) + (by * yw) + (bz * zw)) / yw;
bw = (bx * xrgbw[3] + by * yrgbw[3] + bz * zrgbw[3])/yrgbw[3]
## /* xyz -> rgb matrix, correctly scaled to white. */
rx = rx / rw
ry = ry / rw
rz = rz / rw
gx = gx / gw
gy = gy / gw
gz = gz / gw
bx = bx / bw
by = by / bw
bz = bz / bw
## /* rgb of the desired point */
r = (rx * x) + (ry * y) + (rz * z)
g = (gx * x) + (gy * y) + (gz * z)
b = (bx * x) + (by * y) + (bz * z)
rgblist = []
rgblist.append(r)
rgblist.append(g)
rgblist.append(b)
# are there negative values?
w = np.amin(rgblist)
if w<0:
rgblist[0] = rgblist[0] - w
rgblist[1] = rgblist[1] - w
rgblist[2] = rgblist[2] - w
# scale things so that max has value of 1
mag = np.amax(rgblist)
rgblist[0] = rgblist[0]/mag
rgblist[1] = rgblist[1]/mag
rgblist[2] = rgblist[2]/mag
#rgb = {'r': rgblist[0]/mag, 'g': rgblist[1]/mag, 'b': rgblist[2]/mag }
return rgblist