def Generatetest(wa, wp, f = dCPL(), dbao = dBAO()):
f.update(wa= wa, wp = wp)
dic = {"z":[], "theta":[], "a":[]}
for z in np.arange(0.1,2.1,.1):
dic["z"].append(z)
dic["theta"].append(dbao.cal(f.cal(z)))
dic["a"].append(1/(1+z))
df = pd.DataFrame(dic)
print(df)
df.to_csv("data/data_test.csv")
for y, x in zip(Y, X):
a += math.pow((y - (db.lbao * x)), 2)
b += math.pow(y - mean, 2)
rs.append([r, 1 - (a / b)])
for r in rs:
if r[1] > 1 or r[1] < 0:
rs.remove(r)
rsmin = max([item[1] for item in rs])
for r in rs:
if rsmin == r[1]:
print(r)
d = dCPL()
step = .00005 # Initial stepsize
tolerance = 0.1
iP = [-.1, -0.99] # Initial point
ranges = [[-0.11, -.1], [-1., -.8]]
inpdata = obtaindata("data")
wa = iP[0]
wp = iP[1]
wa, wp, step = LineMethod(wa, wp, tolerance, step, inpdata, d)
fwa = wa