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Keeping only thetas with the lowest logLik for breakpoints thetas

master
tforest 2023-12-06 22:30:48 +01:00
parent 6287f2aa71
commit 66d399d6f0
1 changed files with 34 additions and 13 deletions
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swp2.py
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@ -56,12 +56,18 @@ def return_x_y_from_stwp_theta_file(stwp_theta_file, breaks, mu, tgen, relative_
#### END of parsing #### END of parsing
# quit this file if the number of dimensions is incorrect # quit this file if the number of dimensions is incorrect
if dim < breaks+1: 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 # get n, the last bin of the last group
# revert the list of groups as the most recent times correspond # revert the list of groups as the most recent times correspond
# to the closest and last leafs of the coal. tree. # to the closest and last leafs of the coal. tree.
groups = groups[::-1] groups = groups[::-1]
theta_site = theta_site[::-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 # initiate the dict of times
t = {} t = {}
# list of thetas # 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 # # # divide by N0
# # y[i] = y[i]/N0 # # y[i] = y[i]/N0
# # x[i] = x[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): 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: with open(stwp_theta_file, "r") as swp_file:
@ -236,7 +242,7 @@ def plot_all_epochs_thetafolder(folder_path, mu, tgen, title = "Title", theta_sc
breaks = 0 breaks = 0
cpt +=1 cpt +=1
if os.path.isfile(os.path.join(folder_path, file_name)): 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, tgen = tgen,
mu = mu, relative_theta_scale = theta_scale) mu = mu, relative_theta_scale = theta_scale)
SFS_stored = sfs SFS_stored = sfs
@ -246,7 +252,7 @@ def plot_all_epochs_thetafolder(folder_path, mu, tgen, title = "Title", theta_sc
epochs[breaks] = {} epochs[breaks] = {}
epochs[breaks][likelihood] = x,y epochs[breaks][likelihood] = x,y
breaks += 1 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, tgen = tgen,
mu = mu, relative_theta_scale = theta_scale) mu = mu, relative_theta_scale = theta_scale)
if x == 0: if x == 0:
@ -373,6 +379,7 @@ def plot_all_epochs_thetafolder(folder_path, mu, tgen, title = "Title", theta_sc
if ax is None: if ax is None:
plt.savefig(title+'_Breakpts_Likelihood_AIC.pdf') plt.savefig(title+'_Breakpts_Likelihood_AIC.pdf')
print("S", S) print("S", S)
# return plots
return ax return ax
def plot_test_theta(folder_path, mu, tgen, title = "Title", theta_scale = True, breaks_max = 10, ax = None, n_ticks = 10): 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 cpt = 0
epochs = {} epochs = {}
len_sfs = 0
for file_name in os.listdir(folder_path): for file_name in os.listdir(folder_path):
cpt +=1 cpt +=1
if os.path.isfile(os.path.join(folder_path, file_name)): 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) mu = mu, relative_theta_scale = theta_scale)
if thetas == 0: if thetas == 0:
continue 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("\n*******\n"+title+"\n--------\n"+"mu="+str(mu)+"\ntgen="+str(tgen)+"\nbreaks="+str(k)+"\n*******\n")
print(cpt, "theta file(s) have been scanned.") print(cpt, "theta file(s) have been scanned.")
# multiple fig # 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 # plt.rcParams['font.size'] = fnt_size
ax1 = ax[0, 1] ax1 = ax[0, 1]
plt.subplots_adjust(wspace=0.3, hspace=0.3) plt.subplots_adjust(wspace=0.3, hspace=0.3)
plots = [] 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() groups = np.array(list(theta.values()), dtype=object)[:, 1].tolist()
x = [] x = []
y = [] y = []
@ -467,7 +488,7 @@ def plot_test_theta(folder_path, mu, tgen, title = "Title", theta_scale = True,
lines_fig2 = [] lines_fig2 = []
lines_fig3 = [] lines_fig3 = []
#plt.figure(figsize=(5000/my_dpi, 2800/my_dpi), dpi=my_dpi) #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() groups = np.array(list(theta.values()), dtype=object)[:, 1].tolist()
x = [] x = []
y = [] 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 # Save the entire grid as a single figure
plt.savefig(title+'_combined.pdf') plt.savefig(title+'_combined.pdf')
plt.clf() plt.clf()
# second call for individual plots # # second call for individual plots
plot_all_epochs_thetafolder(folder_path, mu, tgen, title, theta_scale, ax = None) # 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) # plot_test_theta(folder_path, mu, tgen, title, theta_scale, breaks_max = breaks, ax = None)
plt.clf() # plt.clf()
if __name__ == "__main__": if __name__ == "__main__":