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Improve plotting with concordant colours

master
tforest 2024-02-25 02:10:31 +01:00
parent 4aedf5e280
commit 03ea6f938b
1 changed files with 46 additions and 37 deletions
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swp2.py
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@ -176,7 +176,7 @@ def plot_all_epochs_thetafolder(full_dict, mu, tgen, title = "Title",
ax1.set_title(title) ax1.set_title(title)
breaks = len(full_dict['all_epochs']['plots']) breaks = len(full_dict['all_epochs']['plots'])
if ax is None: if ax is None:
plt.savefig(title+'_b'+str(breaks)+'.pdf') plt.savefig(title+'_'+str(breaks+1)+'_epochs.pdf')
# plot likelihood against nb of breakpoints # plot likelihood against nb of breakpoints
if ax is None: if ax is None:
fig, ax2 = plt.subplots(figsize=(5000/my_dpi, 2800/my_dpi), dpi=my_dpi) fig, ax2 = plt.subplots(figsize=(5000/my_dpi, 2800/my_dpi), dpi=my_dpi)
@ -184,8 +184,12 @@ def plot_all_epochs_thetafolder(full_dict, mu, tgen, title = "Title",
else: else:
#plt.rcParams['font.size'] = fnt_size #plt.rcParams['font.size'] = fnt_size
ax2 = ax[0][0,1] ax2 = ax[0][0,1]
# Retrieve the default color cycle from rcParams
ax2.plot(full_dict['Ln_Brks'][0], full_dict['Ln_Brks'][1], 'o', linestyle = "dotted", lw=2) default_colors = plt.rcParams['axes.prop_cycle'].by_key()['color']
# Create an array of colors from the default color cycle
colors = [default_colors[i % len(default_colors)] for i in range(len(full_dict['Ln_Brks'][0]))]
ax2.plot(full_dict['Ln_Brks'][0], full_dict['Ln_Brks'][1], "--", lw=1, color="black", zorder=1)
ax2.scatter(full_dict['Ln_Brks'][0], full_dict['Ln_Brks'][1], s=50, c=colors, marker='o', zorder=2)
ax2.axhline(y=full_dict['best_Ln'], linestyle = "-.", color = "red", label = "$-\log\mathcal{L}$ = "+str(round(full_dict['best_Ln'], 2))) ax2.axhline(y=full_dict['best_Ln'], linestyle = "-.", color = "red", label = "$-\log\mathcal{L}$ = "+str(round(full_dict['best_Ln'], 2)))
ax2.set_yscale('log') ax2.set_yscale('log')
ax2.set_xlabel("# breakpoints", fontsize=fnt_size) ax2.set_xlabel("# breakpoints", fontsize=fnt_size)
@ -202,7 +206,9 @@ def plot_all_epochs_thetafolder(full_dict, mu, tgen, title = "Title",
#plt.rcParams['font.size'] = fnt_size #plt.rcParams['font.size'] = fnt_size
ax3 = ax[1][0,1] ax3 = ax[1][0,1]
AIC = full_dict['AIC_Brks'] AIC = full_dict['AIC_Brks']
ax3.plot(AIC[0], AIC[1], 'o', linestyle = "dotted", lw=2) # ax3.plot(AIC[0], AIC[1], 'o', linestyle = "dotted", lw=2)
ax3.plot(AIC[0], AIC[1], "--", lw=1, color="black", zorder=1)
ax3.scatter(AIC[0], AIC[1], s=50, c=colors, marker='o', zorder=2)
ax3.axhline(y=full_dict['best_AIC'], linestyle = "-.", color = "red", ax3.axhline(y=full_dict['best_AIC'], linestyle = "-.", color = "red",
label = "Min. AIC = "+str(round(full_dict['best_AIC'], 2))) label = "Min. AIC = "+str(round(full_dict['best_AIC'], 2)))
ax3.set_yscale('log') ax3.set_yscale('log')
@ -341,7 +347,7 @@ def save_k_theta(folder_path, mu, tgen, title = "Title", theta_scale = True,
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)):
for k in range(breaks_max): for k in range(breaks_max+1):
x,y,likelihood,thetas,sfs,L = parse_stwp_theta_file(folder_path+file_name, breaks = k, x,y,likelihood,thetas,sfs,L = parse_stwp_theta_file(folder_path+file_name, breaks = k,
tgen = tgen, tgen = tgen,
mu = mu, relative_theta_scale = theta_scale) mu = mu, relative_theta_scale = theta_scale)
@ -443,6 +449,8 @@ def save_k_theta(folder_path, mu, tgen, title = "Title", theta_scale = True,
return saved_plots return saved_plots
def plot_scaled_theta(plot_lines, prop, title, mu, tgen, swp2_lines = None, ax = None, n_ticks = 10, subset = None, theta_scale = False): def plot_scaled_theta(plot_lines, prop, title, mu, tgen, swp2_lines = None, ax = None, n_ticks = 10, subset = None, theta_scale = False):
# nb of plot_lines represent the number of epochs stored (len(plot_lines) = #breaks+1)
nb_epochs = len(plot_lines)
# fig 2 & 3 # fig 2 & 3
if ax is None: if ax is None:
my_dpi = 500 my_dpi = 500
@ -463,40 +471,34 @@ def plot_scaled_theta(plot_lines, prop, title, mu, tgen, swp2_lines = None, ax =
swp2_lines[0][k] = swp2_lines[0][k]/tgen*mu swp2_lines[0][k] = swp2_lines[0][k]/tgen*mu
for k in range(len(swp2_lines[1])): for k in range(len(swp2_lines[1])):
swp2_lines[1][k] = swp2_lines[1][k]*4*mu swp2_lines[1][k] = swp2_lines[1][k]*4*mu
# plot_lines = [[swp2_lines[0], swp2_lines[1]]]+plot_lines
x2_plot, y2_plot = plot_straight_x_y(swp2_lines[0],swp2_lines[1]) x2_plot, y2_plot = plot_straight_x_y(swp2_lines[0],swp2_lines[1])
p2, = ax2.plot(x2_plot, y2_plot, linestyle="-", alpha=0.75, lw=2, label = 'swp2') p2, = ax2.plot(x2_plot, y2_plot, linestyle="-", alpha=0.75, lw=2, label = 'swp2', color="black")
lines_fig2.append(p2) lines_fig2.append(p2)
# Plotting (fig 3) which is the same but log scale for x # Plotting (fig 3) which is the same but log scale for x
p3, = ax3.plot(x2_plot, y2_plot, linestyle="-", alpha=0.75, lw=2, label = 'swp2') p3, = ax3.plot(x2_plot, y2_plot, linestyle="-", alpha=0.75, lw=2, label = 'swp2', color="black")
lines_fig3.append(p3) lines_fig3.append(p3)
nb_breaks = len(plot_lines)
for breaks, plot in enumerate(plot_lines): for breaks, plot in enumerate(plot_lines):
if subset is not None:
if breaks not in subset :
# skip if not in subset
if max(subset) > nb_breaks and breaks == nb_breaks:
pass
else:
continue
x,y=plot x,y=plot
# y = [k/(4*mu) for k in y]
# x = [k/(mu)*tgen for k in x]
x2_plot, y2_plot = plot_straight_x_y(x,y) x2_plot, y2_plot = plot_straight_x_y(x,y)
p2, = ax2.plot(x2_plot, y2_plot, 'o', linestyle="-", alpha=0.75, lw=2, label = str(breaks)+' brks') if subset is not None:
lines_fig2.append(p2) if breaks in subset:
masking_alpha = 0.75
else:
masking_alpha = 0
p2, = ax2.plot(x2_plot, y2_plot, 'o', linestyle="-", alpha=masking_alpha, lw=2, label = str(breaks)+' brks')
# Plotting (fig 3) which is the same but log scale for x # Plotting (fig 3) which is the same but log scale for x
p3, = ax3.plot(x2_plot, y2_plot, 'o', linestyle="-", alpha=0.75, lw=2, label = str(breaks)+' brks') p3, = ax3.plot(x2_plot, y2_plot, 'o', linestyle="-", alpha=masking_alpha, lw=2, label = str(breaks)+' brks')
if subset is not None and breaks in subset:
# store for legend
lines_fig2.append(p2)
lines_fig3.append(p3) lines_fig3.append(p3)
ax3.axvline(x=500/tgen*mu, linestyle="--") ax3.axvline(x=500/tgen*mu, linestyle="--")
if theta_scale: if theta_scale:
xlabel = "Theta scaled by N0" xlabel = "Theta scaled by N0"
ylabel = "Theta scaled by N0" ylabel = "Theta scaled by N0"
else: else:
xlabel = "Theta scale" xlabel = "t"
ylabel = "Theta" ylabel = r"$\theta$"
if ax is None: if ax is None:
# if not ax, then use the plt syntax, not ax... # if not ax, then use the plt syntax, not ax...
plt.xlabel(xlabel, fontsize=fnt_size) plt.xlabel(xlabel, fontsize=fnt_size)
@ -509,8 +511,7 @@ def plot_scaled_theta(plot_lines, prop, title, mu, tgen, swp2_lines = None, ax =
plt.legend(handles=lines_fig2, loc='best', fontsize = fnt_size*0.5) plt.legend(handles=lines_fig2, loc='best', fontsize = fnt_size*0.5)
plt.text(-0.13, -0.135, 'Coal. time\nGen. time\nYears', ha='left', va='bottom', transform=ax3.transAxes) plt.text(-0.13, -0.135, 'Coal. time\nGen. time\nYears', ha='left', va='bottom', transform=ax3.transAxes)
plt.subplots_adjust(bottom=0.2) # Adjust the value as needed plt.subplots_adjust(bottom=0.2) # Adjust the value as needed
# nb of plot_lines represent the number of epochs stored (len(plot_lines) = #breaks+1) plt.savefig(title+'_plotB_'+str(nb_epochs)+'_epochs.pdf')
plt.savefig(title+'_plot2_'+str(len(plot_lines))+'.pdf')
# close fig2 to save memory # close fig2 to save memory
plt.close(fig2) plt.close(fig2)
else: else:
@ -533,29 +534,37 @@ def plot_scaled_theta(plot_lines, prop, title, mu, tgen, swp2_lines = None, ax =
plt.subplots_adjust(bottom=0.2) # Adjust the value as needed plt.subplots_adjust(bottom=0.2) # Adjust the value as needed
if ax is None: if ax is None:
# nb of plot_lines represent the number of epochs stored (len(plot_lines) = #breaks+1) # nb of plot_lines represent the number of epochs stored (len(plot_lines) = #breaks+1)
plt.savefig(title+'_plot3_'+str(len(plot_lines))+'_log.pdf') plt.savefig(title+'_plotC_'+str(nb_epochs)+'_epochs_log.pdf')
# close fig3 to save memory # close fig3 to save memory
plt.close(fig3) plt.close(fig3)
return ax return ax
def plot_raw_stairs(plot_lines, prop, title, ax = None, n_ticks = 10, rescale = False, subset = None): def plot_raw_stairs(plot_lines, prop, title, ax = None, n_ticks = 10, rescale = False, subset = None, max_breaks = None):
if max_breaks:
nb_breaks = max_breaks
else:
nb_breaks = len(plot_lines)+1
# multiple fig # multiple fig
if ax is None: if ax is None:
# intialize figure 1 # intialize figure 1
my_dpi = 300 my_dpi = 500
fnt_size = 18 fnt_size = 18
# plt.rcParams['font.size'] = fnt_size # plt.rcParams['font.size'] = fnt_size
fig, ax1 = plt.subplots(figsize=(5000/my_dpi, 2800/my_dpi), dpi=my_dpi) fig, ax1 = plt.subplots(figsize=(5000/my_dpi, 2800/my_dpi), dpi=my_dpi)
plt.subplots_adjust(bottom=0.2) # Adjust the value as needed
else: else:
fnt_size = 12 fnt_size = 12
# plt.rcParams['font.size'] = fnt_size # plt.rcParams['font.size'] = fnt_size
ax1 = ax[0, 0] ax1 = ax[0, 0]
plt.subplots_adjust(wspace=0.3, hspace=0.3) plt.subplots_adjust(wspace=0.3, hspace=0.3)
plots = [] plots = []
for epoch, plot in enumerate(plot_lines): for breaks, plot in enumerate(plot_lines):
if max_breaks and breaks > max_breaks:
# stop plotting if it exceeds the limit
continue
x,y = plot x,y = plot
x_plot, y_plot = plot_straight_x_y(x,y) x_plot, y_plot = plot_straight_x_y(x,y)
p, = ax1.plot(x_plot, y_plot, 'o', linestyle="-", alpha=0.75, lw=2, label = str(epoch)+' brks') p, = ax1.plot(x_plot, y_plot, 'o', linestyle="-", alpha=0.75, lw=2, label = str(breaks)+' brks')
# add plot to the list of all plots to superimpose # add plot to the list of all plots to superimpose
plots.append(p) plots.append(p)
@ -565,7 +574,7 @@ def plot_raw_stairs(plot_lines, prop, title, ax = None, n_ticks = 10, rescale =
#ax.legend(handles=[p0]+plots) #ax.legend(handles=[p0]+plots)
ax1.set_xlabel("# bin & cumul. prop. of sites", fontsize=fnt_size) ax1.set_xlabel("# bin & cumul. prop. of sites", fontsize=fnt_size)
# Set the x-axis locator to reduce the number of ticks to 10 # Set the x-axis locator to reduce the number of ticks to 10
ax1.set_ylabel("theta", fontsize=fnt_size) ax1.set_ylabel(r'$\theta_k$', fontsize=fnt_size, rotation = 90)
ax1.set_title(title, fontsize=fnt_size) ax1.set_title(title, fontsize=fnt_size)
ax1.legend(handles=plots, loc='best', fontsize = fnt_size*0.5) ax1.legend(handles=plots, loc='best', fontsize = fnt_size*0.5)
ax1.set_xticks(x_ticks) ax1.set_xticks(x_ticks)
@ -579,7 +588,7 @@ def plot_raw_stairs(plot_lines, prop, title, ax = None, n_ticks = 10, rescale =
ax1.set_xticklabels([f'{values[k]}\n{val:.2f}' for k, val in enumerate(new_prop)], fontsize = fnt_size*0.8) ax1.set_xticklabels([f'{values[k]}\n{val:.2f}' for k, val in enumerate(new_prop)], fontsize = fnt_size*0.8)
if ax is None: if ax is None:
# nb of plot_lines represent the number of epochs stored (len(plot_lines) = #breaks+1) # nb of plot_lines represent the number of epochs stored (len(plot_lines) = #breaks+1)
plt.savefig(title+'_raw'+str(len(plot_lines))+'.pdf') plt.savefig(title+'_raw_'+str(nb_breaks)+'_breaks.pdf')
plt.close(fig) plt.close(fig)
# return plots # return plots
return ax return ax
@ -588,8 +597,8 @@ def combined_plot(folder_path, mu, tgen, breaks, title = "Title", theta_scale =
my_dpi = 300 my_dpi = 300
saved_plots_dict = save_all_epochs_thetafolder(folder_path, mu, tgen, title, theta_scale, output = title+"_plotdata.json") saved_plots_dict = save_all_epochs_thetafolder(folder_path, mu, tgen, title, theta_scale, output = title+"_plotdata.json")
nb_of_epochs = len(saved_plots_dict["all_epochs"]["plots"]) nb_of_epochs = len(saved_plots_dict["all_epochs"]["plots"])
print(nb_of_epochs)
best_epoch = saved_plots_dict["best_epoch_by_AIC"] best_epoch = saved_plots_dict["best_epoch_by_AIC"]
print("Best epoch based on AIC =", best_epoch)
save_k_theta(folder_path, mu, tgen, title, theta_scale, breaks_max = nb_of_epochs, input = title+"_plotdata.json", output = title+"_plotdata.json") save_k_theta(folder_path, mu, tgen, title, theta_scale, breaks_max = nb_of_epochs, input = title+"_plotdata.json", output = title+"_plotdata.json")
with open(title+"_plotdata.json", 'r') as json_file: with open(title+"_plotdata.json", 'r') as json_file:
@ -628,7 +637,7 @@ def combined_plot(folder_path, mu, tgen, breaks, title = "Title", theta_scale =
swp2_x, swp2_y = swp2_vals[0], swp2_vals[1] swp2_x, swp2_y = swp2_vals[0], swp2_vals[1]
# End of Parsing real swp2 output # End of Parsing real swp2 output
plot_raw_stairs(plot_lines = loaded_data['raw_stairs'], plot_raw_stairs(plot_lines = loaded_data['raw_stairs'],
prop = loaded_data['prop'], title = title, ax = None) prop = loaded_data['prop'], title = title, ax = None, max_breaks = breaks)
plot_scaled_theta(plot_lines = loaded_data['scaled_stairs'], mu = mu, tgen = tgen, subset=[loaded_data['best_epoch_by_AIC']]+selected_breaks, plot_scaled_theta(plot_lines = loaded_data['scaled_stairs'], mu = mu, tgen = tgen, subset=[loaded_data['best_epoch_by_AIC']]+selected_breaks,
# plot_scaled_theta(plot_lines = loaded_data['scaled_stairs'], subset=list(range(0,3))+[loaded_data['best_epoch_by_AIC']]+selected_breaks, # plot_scaled_theta(plot_lines = loaded_data['scaled_stairs'], subset=list(range(0,3))+[loaded_data['best_epoch_by_AIC']]+selected_breaks,
prop = loaded_data['prop'], title = title, swp2_lines = [swp2_x, swp2_y], ax = None) prop = loaded_data['prop'], title = title, swp2_lines = [swp2_x, swp2_y], ax = None)