Compute proportion of information used for theta plots
parent
23fef174f2
commit
87bef76e28
22
swp2.py
22
swp2.py
|
|
@ -262,14 +262,6 @@ def plot_all_epochs_thetafolder(folder_path, mu, tgen, title = "Title", theta_sc
|
|||
# divide by N0
|
||||
y[i] = y[i]/N0
|
||||
x[i] = x[i]/N0
|
||||
sum_theta_i = 0
|
||||
print(epoch, x, y)
|
||||
for i in range(2, len(y)-1):
|
||||
sum_theta_i=y[i] / (i-1)
|
||||
prop = []
|
||||
for k in range(2, len(y)-1):
|
||||
prop.append(y[k+1] / (k - 1) / sum_theta_i)
|
||||
#print(epoch, prop)
|
||||
plt.plot(x, y, 'o', linestyle = "-", alpha=0.75, lw=2, label = str(epoch)+' BrkPt | Lik='+greatest_likelihood)
|
||||
if theta_scale:
|
||||
plt.xlabel("Coal. time")
|
||||
|
|
@ -294,15 +286,15 @@ def plot_all_epochs_thetafolder(folder_path, mu, tgen, title = "Title", theta_sc
|
|||
# number of monomorphic sites
|
||||
L = L_stored
|
||||
S0 = L-S
|
||||
print("SFS", SFS_stored)
|
||||
print("S", S, "L", L, "S0=", S0)
|
||||
# print("SFS", SFS_stored)
|
||||
# print("S", S, "L", L, "S0=", S0)
|
||||
# compute Ln
|
||||
Ln = log_facto(S+S0) - log_facto(S0) + np.log(float(S0)/(S+S0)) * S0
|
||||
for xi in range(0, len(SFS_stored)):
|
||||
p_i = SFS_stored[xi] / float(S+S0)
|
||||
Ln += np.log(p_i) * SFS_stored[xi] - log_facto(SFS_stored[xi])
|
||||
res = Ln
|
||||
print(res)
|
||||
# print(res)
|
||||
# basic plot likelihood
|
||||
plt.figure(figsize=(5000/my_dpi, 2800/my_dpi), dpi=my_dpi)
|
||||
plt.rcParams['font.size'] = '18'
|
||||
|
|
@ -362,6 +354,14 @@ def plot_test_theta(folder_path, mu, tgen, title = "Title", theta_scale = True,
|
|||
N0 = y[0]
|
||||
for i in range(len(y)):
|
||||
y[i] = y[i]/N0
|
||||
# compute the proportion of information used at each bin of the SFS
|
||||
sum_theta_i = 0
|
||||
for i in range(2, len(y)-1):
|
||||
sum_theta_i+=y[i] / (i-1)
|
||||
prop = []
|
||||
for k in range(2, len(y)-1):
|
||||
prop.append(y[k] / (k - 1) / sum_theta_i)
|
||||
# plot
|
||||
plt.plot(x, y, 'o', linestyle="dotted", alpha=0.75, lw=2, label = str(epoch)+' brks')
|
||||
plt.xlabel("# breaks")
|
||||
plt.ylabel("theta")
|
||||
|
|
|
|||
Loading…
Reference in New Issue