def residual(data, dataerr, redshift, h, m, de):
def integrand(z, m, de): ##Integral in luminosity distance equation
return 1 / np.sqrt((m * (1 + z)**3) + de)
resid = 0
for i in range(len(data)):
integral = quad(integrand, 0, redshift[i], args=(m, de))
d = (fun.c * (1 + redshift[i])) / h * integral[0]
model = fun.dmod(d) + 20
resid = resid + (data[i] -
model)**2 / dataerr[i]**2 ##Sum of each residual
return resid
small_H = fun.HMpc(np.array(smallred), np.array(smalldist))
small_dH = fun.dHMpc(np.array(smallred), np.array(smalldist),
np.array(smalldisterror))
Allred = [x[0] for x in All]
Alldist = [x[1] for x in All]
Alldisterror = [x[2] for x in All]
AllRA = [x[3] for x in All]
Alldec = [x[4] for x in All]
minres = 100000
largeH = 0
i = 0
while i < 1000:
h = 65 + i / 100
res = fun.residual(fun.dmod(largedist), fun.dmod(largedisterror), largered,
h, 0.2807, 0.7193)
if res < minres:
minres = res
largeH = h
i += 1
largebestH = 73.7
smallbestH = 64.1
redshiftrange = np.linspace(minredshift, maxredshift, 10)
largeH = [fun.c * x / largebestH for x in redshiftrange]
smallH = [fun.c * x / smallbestH for x in redshiftrange]
##Graph for redshift vs distance
plt.figure()
SGCdec = [x[4] for x in SN_SGC]
SGC_H = fun.HMpc(np.array(SGCred), np.array(SGCdist))
SGC_dH = fun.dHMpc(np.array(SGCred), np.array(SGCdist), np.array(SGCdisterror))
Allred = [x[0] for x in All]
Alldist = [x[1] for x in All]
Alldisterror = [x[2] for x in All]
AllRA = [x[3] for x in All]
Alldec = [x[4] for x in All]
minres = 100000
NGCH = 0
i = 0
while i < 1000:
h = 65 + i / 100
res = fun.residual(fun.dmod(NGCdist), fun.dmod(NGCdisterror), NGCred, h,
0.2807, 0.7193)
if res < minres:
minres = res
NGCH = h
i += 1
redshiftrange = np.linspace(minredshift, maxredshift, 10)
NGCH = [fun.c * x / 68.41 for x in redshiftrange]
SGCH = [fun.c * x / 66.9 for x in redshiftrange]
##Graph for redshift vs distance
plt.figure()
plt.errorbar(NGCred,
NGCdist,
yerr=NGCdisterror,