Keeping only thetas with the lowest logLik for breakpoints thetas
tforest
parent
6287f2aa71
commit
66d399d6f0
47
swp2.py
47
swp2.py
|
|
@ -56,12 +56,18 @@ def return_x_y_from_stwp_theta_file(stwp_theta_file, breaks, mu, tgen, relative_
|
|||
#### END of parsing
|
||||
# quit this file if the number of dimensions is incorrect
|
||||
if dim < breaks+1:
|
||||
return 0,0,0,0,0
|
||||
return 0,0,0,0,0,0
|
||||
# get n, the last bin of the last group
|
||||
# revert the list of groups as the most recent times correspond
|
||||
# to the closest and last leafs of the coal. tree.
|
||||
groups = groups[::-1]
|
||||
theta_site = theta_site[::-1]
|
||||
# store thetas for later use
|
||||
grps = groups.copy()
|
||||
thetas = {}
|
||||
for i in range(len(groups)):
|
||||
grps[i] = grps[i].split(',')
|
||||
thetas[i] = [float(theta_site[i]), grps[i], likelihood]
|
||||
# initiate the dict of times
|
||||
t = {}
|
||||
# list of thetas
|
||||
|
|
@ -119,7 +125,7 @@ def return_x_y_from_stwp_theta_file(stwp_theta_file, breaks, mu, tgen, relative_
|
|||
# # # divide by N0
|
||||
# # y[i] = y[i]/N0
|
||||
# # x[i] = x[i]/N0
|
||||
return x,y,likelihood,sfs,L
|
||||
return x,y,likelihood,thetas,sfs,L
|
||||
|
||||
def return_x_y_from_stwp_theta_file_as_is(stwp_theta_file, breaks, mu, tgen, relative_theta_scale = False):
|
||||
with open(stwp_theta_file, "r") as swp_file:
|
||||
|
|
@ -163,7 +169,7 @@ def return_x_y_from_stwp_theta_file_as_is(stwp_theta_file, breaks, mu, tgen, rel
|
|||
|
||||
for i in range(len(groups)):
|
||||
groups[i] = groups[i].split(',')
|
||||
#print(groups[i], len(groups[i]))
|
||||
# print(groups[i], len(groups[i]))
|
||||
thetas[i] = [float(theta_site[i]), groups[i], likelihood]
|
||||
return thetas, sfs
|
||||
|
||||
|
|
@ -236,7 +242,7 @@ def plot_all_epochs_thetafolder(folder_path, mu, tgen, title = "Title", theta_sc
|
|||
breaks = 0
|
||||
cpt +=1
|
||||
if os.path.isfile(os.path.join(folder_path, file_name)):
|
||||
x, y, likelihood, sfs, L = return_x_y_from_stwp_theta_file(folder_path+file_name, breaks = breaks,
|
||||
x, y, likelihood, theta, sfs, L = return_x_y_from_stwp_theta_file(folder_path+file_name, breaks = breaks,
|
||||
tgen = tgen,
|
||||
mu = mu, relative_theta_scale = theta_scale)
|
||||
SFS_stored = sfs
|
||||
|
|
@ -246,7 +252,7 @@ def plot_all_epochs_thetafolder(folder_path, mu, tgen, title = "Title", theta_sc
|
|||
epochs[breaks] = {}
|
||||
epochs[breaks][likelihood] = x,y
|
||||
breaks += 1
|
||||
x,y,likelihood,sfs,L = return_x_y_from_stwp_theta_file(folder_path+file_name, breaks = breaks,
|
||||
x,y,likelihood,theta,sfs,L = return_x_y_from_stwp_theta_file(folder_path+file_name, breaks = breaks,
|
||||
tgen = tgen,
|
||||
mu = mu, relative_theta_scale = theta_scale)
|
||||
if x == 0:
|
||||
|
|
@ -373,6 +379,7 @@ def plot_all_epochs_thetafolder(folder_path, mu, tgen, title = "Title", theta_sc
|
|||
if ax is None:
|
||||
plt.savefig(title+'_Breakpts_Likelihood_AIC.pdf')
|
||||
print("S", S)
|
||||
# return plots
|
||||
return ax
|
||||
|
||||
def plot_test_theta(folder_path, mu, tgen, title = "Title", theta_scale = True, breaks_max = 10, ax = None, n_ticks = 10):
|
||||
|
|
@ -381,6 +388,7 @@ def plot_test_theta(folder_path, mu, tgen, title = "Title", theta_scale = True,
|
|||
"""
|
||||
cpt = 0
|
||||
epochs = {}
|
||||
len_sfs = 0
|
||||
for file_name in os.listdir(folder_path):
|
||||
cpt +=1
|
||||
if os.path.isfile(os.path.join(folder_path, file_name)):
|
||||
|
|
@ -390,7 +398,13 @@ def plot_test_theta(folder_path, mu, tgen, title = "Title", theta_scale = True,
|
|||
mu = mu, relative_theta_scale = theta_scale)
|
||||
if thetas == 0:
|
||||
continue
|
||||
epochs[k] = thetas
|
||||
if len(thetas)-1 != k:
|
||||
continue
|
||||
if k not in epochs.keys():
|
||||
epochs[k] = {}
|
||||
likelihood = thetas[k][2]
|
||||
epochs[k][likelihood] = thetas
|
||||
#epochs[k] = thetas
|
||||
print("\n*******\n"+title+"\n--------\n"+"mu="+str(mu)+"\ntgen="+str(tgen)+"\nbreaks="+str(k)+"\n*******\n")
|
||||
print(cpt, "theta file(s) have been scanned.")
|
||||
# multiple fig
|
||||
|
|
@ -405,9 +419,16 @@ def plot_test_theta(folder_path, mu, tgen, title = "Title", theta_scale = True,
|
|||
# plt.rcParams['font.size'] = fnt_size
|
||||
ax1 = ax[0, 1]
|
||||
plt.subplots_adjust(wspace=0.3, hspace=0.3)
|
||||
|
||||
plots = []
|
||||
for epoch, theta in epochs.items():
|
||||
best_epochs = {}
|
||||
for epoch in epochs:
|
||||
likelihoods = []
|
||||
for key in epochs[epoch].keys():
|
||||
likelihoods.append(float(key))
|
||||
likelihoods.sort()
|
||||
minLogLn = str(likelihoods[0])
|
||||
best_epochs[epoch] = epochs[epoch][minLogLn]
|
||||
for epoch, theta in best_epochs.items():
|
||||
groups = np.array(list(theta.values()), dtype=object)[:, 1].tolist()
|
||||
x = []
|
||||
y = []
|
||||
|
|
@ -467,7 +488,7 @@ def plot_test_theta(folder_path, mu, tgen, title = "Title", theta_scale = True,
|
|||
lines_fig2 = []
|
||||
lines_fig3 = []
|
||||
#plt.figure(figsize=(5000/my_dpi, 2800/my_dpi), dpi=my_dpi)
|
||||
for epoch, theta in epochs.items():
|
||||
for epoch, theta in best_epochs.items():
|
||||
groups = np.array(list(theta.values()), dtype=object)[:, 1].tolist()
|
||||
x = []
|
||||
y = []
|
||||
|
|
@ -529,10 +550,10 @@ def combined_plot(folder_path, mu, tgen, breaks, title = "Title", theta_scale =
|
|||
# Save the entire grid as a single figure
|
||||
plt.savefig(title+'_combined.pdf')
|
||||
plt.clf()
|
||||
# second call for individual plots
|
||||
plot_all_epochs_thetafolder(folder_path, mu, tgen, title, theta_scale, ax = None)
|
||||
plot_test_theta(folder_path, mu, tgen, title, theta_scale, breaks_max = breaks, ax = None)
|
||||
plt.clf()
|
||||
# # second call for individual plots
|
||||
# plot_all_epochs_thetafolder(folder_path, mu, tgen, title, theta_scale, ax = None)
|
||||
# plot_test_theta(folder_path, mu, tgen, title, theta_scale, breaks_max = breaks, ax = None)
|
||||
# plt.clf()
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue