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@@ -269,7 +269,7 @@ def plot_all_epochs_thetafolder(folder_path, mu, tgen, title = "Title", theta_sc
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else:
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fnt_size = 12
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# plt.rcParams['font.size'] = fnt_size
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- ax1 = ax[0,0]
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+ ax1 = ax[1][0,0]
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ax1.set_yscale('log')
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ax1.set_xscale('log')
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ax1.grid(True,which="both", linestyle='--', alpha = 0.3)
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@@ -346,7 +346,7 @@ def plot_all_epochs_thetafolder(folder_path, mu, tgen, title = "Title", theta_sc
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# plt.rcParams['font.size'] = fnt_size
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else:
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#plt.rcParams['font.size'] = fnt_size
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- ax2 = ax[2,0]
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+ ax2 = ax[0][0,1]
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ax2.plot(np.array(brkpt_lik)[:, 0], np.array(brkpt_lik)[:, 1].astype(float), 'o', linestyle = "dotted", lw=2)
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ax2.axhline(y=-Ln, linestyle = "-.", color = "red", label = "$-\log\mathcal{L}$ = "+str(round(-Ln, 2)))
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ax2.set_yscale('log')
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@@ -362,12 +362,17 @@ def plot_all_epochs_thetafolder(folder_path, mu, tgen, title = "Title", theta_sc
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# plt.rcParams['font.size'] = '18'
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else:
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#plt.rcParams['font.size'] = fnt_size
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- ax3 = ax[2,1]
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- AIC = 2*(len(brkpt_lik)+1)+2*np.array(brkpt_lik)[:, 1].astype(float)
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+ ax3 = ax[1][0,1]
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+ AIC = []
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+ for brk in np.array(brkpt_lik)[:, 0]:
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+ brk = int(brk)
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+ AIC.append((2*brk+1)+2*np.array(brkpt_lik)[brk, 1].astype(float))
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ax3.plot(np.array(brkpt_lik)[:, 0], AIC, 'o', linestyle = "dotted", lw=2)
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- AIC_ln = 2*(len(brkpt_lik)+1)-2*Ln
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+ # AIC = 2*k - 2ln(L) ; where k is the number of parameters, here brks+1
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+ AIC_ln = 2*(len(brkpt_lik)+1) - 2*Ln
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ax3.axhline(y=AIC_ln, linestyle = "-.", color = "red",
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label = "Min. AIC = "+str(round(AIC_ln, 2)))
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+ selected_brks_nb = AIC.index(min(AIC))
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ax3.set_yscale('log')
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ax3.set_xlabel("# breakpoints", fontsize=fnt_size)
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ax3.set_ylabel("AIC")
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@@ -377,7 +382,7 @@ def plot_all_epochs_thetafolder(folder_path, mu, tgen, title = "Title", theta_sc
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plt.savefig(title+'_Breakpts_Likelihood_AIC.pdf')
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print("S", S)
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# return plots
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- return ax
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+ return ax[0], ax[1]
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def save_k_theta(folder_path, mu, tgen, title = "Title", theta_scale = True,
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breaks_max = 10, output = None):
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@@ -482,7 +487,53 @@ def save_k_theta(folder_path, mu, tgen, title = "Title", theta_scale = True,
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json.dump(saved_plots, json_file)
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return saved_plots
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-def plot_raw_stairs(plot_lines, plot_lines2, prop, title, ax = None, n_ticks = 10):
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+def plot_scaled_theta(plot_lines, prop, title, ax = None, n_ticks = 10):
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+ # fig 2 & 3
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+ if ax is None:
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+ my_dpi = 300
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+ fnt_size = 18
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+ fig2, ax2 = plt.subplots(figsize=(5000/my_dpi, 2800/my_dpi), dpi=my_dpi)
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+ fig3, ax3 = plt.subplots(figsize=(5000/my_dpi, 2800/my_dpi), dpi=my_dpi)
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+ else:
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+ # plt.rcParams['font.size'] = fnt_size
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+ fnt_size = 12
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+ # place of plots on the grid
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+ ax2 = ax[1,0]
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+ ax3 = ax[1,1]
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+ lines_fig2 = []
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+ lines_fig3 = []
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+ #plt.figure(figsize=(5000/my_dpi, 2800/my_dpi), dpi=my_dpi)
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506
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+ for epoch, plot in enumerate(plot_lines):
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+ x,y=plot
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+ x2_plot, y2_plot = plot_straight_x_y(x,y)
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509
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+ p2, = ax2.plot(x2_plot, y2_plot, 'o', linestyle="-", alpha=0.75, lw=2, label = str(epoch)+' brks')
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+ lines_fig2.append(p2)
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511
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+ # Plotting (fig 3) which is the same but log scale for x
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+ p3, = ax3.plot(x2_plot, y2_plot, 'o', linestyle="-", alpha=0.75, lw=2, label = str(epoch)+' brks')
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+ lines_fig3.append(p3)
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+ ax2.set_xlabel("Relative scale", fontsize=fnt_size)
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+ ax2.set_ylabel("theta", fontsize=fnt_size)
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+ ax2.set_title(title, fontsize=fnt_size)
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+ ax2.legend(handles=lines_fig2, loc='best', fontsize = fnt_size*0.5)
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+ if ax is None:
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519
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+ # nb of plot_lines represent the number of epochs stored (len(plot_lines) = #breaks+1)
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+ plt.savefig(title+'_plot2_'+str(len(plot_lines))+'.pdf')
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521
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+ # close fig2 to save memory
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+ plt.close(fig2)
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+ ax3.set_xscale('log')
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+ ax3.set_yscale('log')
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+ ax3.set_xlabel("log Relative scale", fontsize=fnt_size)
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+ ax3.set_ylabel("theta", fontsize=fnt_size)
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527
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+ ax3.set_title(title, fontsize=fnt_size)
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528
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+ ax3.legend(handles=lines_fig3, loc='best', fontsize = fnt_size*0.5)
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529
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+ if ax is None:
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530
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+ # nb of plot_lines represent the number of epochs stored (len(plot_lines) = #breaks+1)
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531
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+ plt.savefig(title+'_plot3_'+str(len(plot_lines))+'_log.pdf')
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532
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+ # close fig3 to save memory
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533
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+ plt.close(fig3)
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534
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+ return ax
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+
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536
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+def plot_raw_stairs(plot_lines, prop, title, ax = None, n_ticks = 10):
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486
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537
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# multiple fig
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487
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538
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if ax is None:
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539
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# intialize figure 1
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@@ -493,7 +544,7 @@ def plot_raw_stairs(plot_lines, plot_lines2, prop, title, ax = None, n_ticks = 1
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544
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else:
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494
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545
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fnt_size = 12
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546
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# plt.rcParams['font.size'] = fnt_size
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- ax1 = ax[0, 1]
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547
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+ ax1 = ax[0, 0]
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548
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plt.subplots_adjust(wspace=0.3, hspace=0.3)
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549
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plots = []
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550
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@@ -508,10 +559,10 @@ def plot_raw_stairs(plot_lines, plot_lines2, prop, title, ax = None, n_ticks = 1
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508
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559
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# print(x_ticks)
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560
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#print(prop, "\n", sum(prop))
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561
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#ax.legend(handles=[p0]+plots)
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- ax1.set_xlabel("# bin", fontsize=fnt_size)
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+ ax1.set_xlabel("# bin & cumul. prop. of sites", fontsize=fnt_size)
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563
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# Set the x-axis locator to reduce the number of ticks to 10
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ax1.set_ylabel("theta", fontsize=fnt_size)
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- ax1.set_title("Title", fontsize=fnt_size)
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+ ax1.set_title(title, fontsize=fnt_size)
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566
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ax1.legend(handles=plots, loc='best', fontsize = fnt_size*0.5)
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567
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ax1.set_xticks(x_ticks)
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568
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step = len(x_ticks)//(n_ticks-1)
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@@ -523,42 +574,9 @@ def plot_raw_stairs(plot_lines, plot_lines2, prop, title, ax = None, n_ticks = 1
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523
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574
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ax1.set_xticks(values)
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524
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575
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ax1.set_xticklabels([f'{values[k]}\n{val:.2f}' for k, val in enumerate(new_prop)], fontsize = fnt_size*0.8)
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525
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576
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if ax is None:
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526
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- plt.savefig(title+'_raw'+str(k)+'.pdf')
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527
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- # fig 2 & 3
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528
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- if ax is None:
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529
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- fig2, ax2 = plt.subplots(figsize=(5000/my_dpi, 2800/my_dpi), dpi=my_dpi)
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530
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- fig3, ax3 = plt.subplots(figsize=(5000/my_dpi, 2800/my_dpi), dpi=my_dpi)
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531
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- else:
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532
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- # plt.rcParams['font.size'] = fnt_size
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533
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- # place of plots on the grid
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534
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- ax2 = ax[1,0]
|
535
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- ax3 = ax[1,1]
|
536
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- lines_fig2 = []
|
537
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- lines_fig3 = []
|
538
|
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- #plt.figure(figsize=(5000/my_dpi, 2800/my_dpi), dpi=my_dpi)
|
539
|
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- for epoch, plot in enumerate(plot_lines2):
|
540
|
|
- x,y=plot
|
541
|
|
- x2_plot, y2_plot = plot_straight_x_y(x,y)
|
542
|
|
- p2, = ax2.plot(x2_plot, y2_plot, 'o', linestyle="-", alpha=0.75, lw=2, label = str(epoch)+' brks')
|
543
|
|
- lines_fig2.append(p2)
|
544
|
|
- # Plotting (fig 3) which is the same but log scale for x
|
545
|
|
- p3, = ax3.plot(x2_plot, y2_plot, 'o', linestyle="-", alpha=0.75, lw=2, label = str(epoch)+' brks')
|
546
|
|
- lines_fig3.append(p3)
|
547
|
|
- ax2.set_xlabel("Relative scale", fontsize=fnt_size)
|
548
|
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- ax2.set_ylabel("theta", fontsize=fnt_size)
|
549
|
|
- ax2.set_title("Title", fontsize=fnt_size)
|
550
|
|
- ax2.legend(handles=lines_fig2, loc='best', fontsize = fnt_size*0.5)
|
551
|
|
- if ax is None:
|
552
|
|
- plt.savefig(title+'_plot2_'+str(k)+'.pdf')
|
553
|
|
- ax3.set_xscale('log')
|
554
|
|
- ax3.set_yscale('log')
|
555
|
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- ax3.set_xlabel("log Relative scale", fontsize=fnt_size)
|
556
|
|
- ax3.set_ylabel("theta", fontsize=fnt_size)
|
557
|
|
- ax3.set_title("Title", fontsize=fnt_size)
|
558
|
|
- ax3.legend(handles=lines_fig3, loc='best', fontsize = fnt_size*0.5)
|
559
|
|
- if ax is None:
|
560
|
|
- plt.savefig(title+'_plot3_'+str(k)+'_log.pdf')
|
561
|
|
- plt.clf()
|
|
577
|
+ # nb of plot_lines represent the number of epochs stored (len(plot_lines) = #breaks+1)
|
|
578
|
+ plt.savefig(title+'_raw'+str(len(plot_lines))+'.pdf')
|
|
579
|
+ plt.close(fig)
|
562
|
580
|
# return plots
|
563
|
581
|
return ax
|
564
|
582
|
|
|
@@ -642,7 +660,7 @@ def plot_test_theta(folder_path, mu, tgen, title = "Title", theta_scale = True,
|
642
|
660
|
ax1.set_xlabel("# bin", fontsize=fnt_size)
|
643
|
661
|
# Set the x-axis locator to reduce the number of ticks to 10
|
644
|
662
|
ax1.set_ylabel("theta", fontsize=fnt_size)
|
645
|
|
- ax1.set_title("Title", fontsize=fnt_size)
|
|
663
|
+ ax1.set_title(title, fontsize=fnt_size)
|
646
|
664
|
ax1.legend(handles=plots, loc='best', fontsize = fnt_size*0.5)
|
647
|
665
|
ax1.set_xticks(x_ticks)
|
648
|
666
|
if len(prop) >= 18:
|
|
@@ -699,7 +717,7 @@ def plot_test_theta(folder_path, mu, tgen, title = "Title", theta_scale = True,
|
699
|
717
|
lines_fig3.append(p3)
|
700
|
718
|
ax2.set_xlabel("Relative scale", fontsize=fnt_size)
|
701
|
719
|
ax2.set_ylabel("theta", fontsize=fnt_size)
|
702
|
|
- ax2.set_title("Title", fontsize=fnt_size)
|
|
720
|
+ ax2.set_title(title, fontsize=fnt_size)
|
703
|
721
|
ax2.legend(handles=lines_fig2, loc='best', fontsize = fnt_size*0.5)
|
704
|
722
|
if ax is None:
|
705
|
723
|
plt.savefig(title+'_plot2_'+str(k)+'.pdf')
|
|
@@ -707,7 +725,7 @@ def plot_test_theta(folder_path, mu, tgen, title = "Title", theta_scale = True,
|
707
|
725
|
ax3.set_yscale('log')
|
708
|
726
|
ax3.set_xlabel("log Relative scale", fontsize=fnt_size)
|
709
|
727
|
ax3.set_ylabel("theta", fontsize=fnt_size)
|
710
|
|
- ax3.set_title("Title", fontsize=fnt_size)
|
|
728
|
+ ax3.set_title(title, fontsize=fnt_size)
|
711
|
729
|
ax3.legend(handles=lines_fig3, loc='best', fontsize = fnt_size*0.5)
|
712
|
730
|
if ax is None:
|
713
|
731
|
plt.savefig(title+'_plot3_'+str(k)+'_log.pdf')
|
|
@@ -724,9 +742,8 @@ def combined_plot(folder_path, mu, tgen, breaks, title = "Title", theta_scale =
|
724
|
742
|
# ax = plot_all_epochs_thetafolder(folder_path, mu, tgen, title, theta_scale, ax = axs)
|
725
|
743
|
# ax = plot_test_theta(folder_path, mu, tgen, title, theta_scale, breaks_max = breaks, ax = axs)
|
726
|
744
|
# # Adjust layout to prevent clipping of titles
|
727
|
|
- # plt.tight_layout()
|
728
|
|
- # # Adjust absolute space between the top and bottom rows
|
729
|
|
- # #plt.subplots_adjust(hspace=0.7) # Adjust this value based on your requirement
|
|
745
|
+ #
|
|
746
|
+
|
730
|
747
|
# # Save the entire grid as a single figure
|
731
|
748
|
# plt.savefig(title+'_combined.pdf')
|
732
|
749
|
# plt.clf()
|
|
@@ -735,17 +752,31 @@ def combined_plot(folder_path, mu, tgen, breaks, title = "Title", theta_scale =
|
735
|
752
|
# # plot_test_theta(folder_path, mu, tgen, title, theta_scale, breaks_max = breaks, ax = None)
|
736
|
753
|
# # plt.clf()
|
737
|
754
|
# save_k_theta(folder_path, mu, tgen, title, theta_scale, breaks_max = breaks, output = title+"_plotdata.json")
|
738
|
|
-
|
739
|
755
|
with open(title+"_plotdata.json", 'r') as json_file:
|
740
|
756
|
loaded_data = json.load(json_file)
|
741
|
|
-
|
|
757
|
+ # plot page 1 of summary
|
742
|
758
|
fig1, ax1 = plt.subplots(2, 2, figsize=(5000/my_dpi, 2970/my_dpi), dpi=my_dpi)
|
743
|
|
- # plot_test_theta(folder_path, mu, tgen, title, theta_scale, breaks_max = breaks, ax = ax1)
|
744
|
|
- ax1 = plot_raw_stairs(plot_lines = loaded_data['raw_stairs'], plot_lines2 = loaded_data['scaled_stairs'],
|
|
759
|
+ # fig1.tight_layout()
|
|
760
|
+ # Adjust absolute space between the top and bottom rows
|
|
761
|
+ fig1.subplots_adjust(hspace=0.35) # Adjust this value based on your requirement
|
|
762
|
+ # plot page 2 of summary
|
|
763
|
+ fig2, ax2 = plt.subplots(2, 2, figsize=(5000/my_dpi, 2970/my_dpi), dpi=my_dpi)
|
|
764
|
+ # fig2.tight_layout()
|
|
765
|
+ ax1 = plot_raw_stairs(plot_lines = loaded_data['raw_stairs'],
|
|
766
|
+ prop = loaded_data['prop'], title = title, ax = ax1)
|
|
767
|
+
|
|
768
|
+ ax1 = plot_scaled_theta(plot_lines = loaded_data['scaled_stairs'],
|
745
|
769
|
prop = loaded_data['prop'], title = title, ax = ax1)
|
|
770
|
+ ax1, ax2 = plot_all_epochs_thetafolder(folder_path, mu, tgen, title, theta_scale, ax = [ax1, ax2])
|
|
771
|
+ fig1.savefig(title+'_combined_p1.pdf')
|
|
772
|
+ fig2.savefig(title+'_combined_p2.pdf')
|
|
773
|
+ plot_raw_stairs(plot_lines = loaded_data['raw_stairs'],
|
|
774
|
+ prop = loaded_data['prop'], title = title, ax = None)
|
|
775
|
+ plot_scaled_theta(plot_lines = loaded_data['scaled_stairs'],
|
|
776
|
+ prop = loaded_data['prop'], title = title, ax = None)
|
746
|
777
|
|
747
|
|
- plt.savefig(title+'_raw_scaled.pdf')
|
748
|
|
- fig1.clf()
|
|
778
|
+ plt.close(fig1)
|
|
779
|
+ plt.close(fig2)
|
749
|
780
|
if __name__ == "__main__":
|
750
|
781
|
|
751
|
782
|
if len(sys.argv) != 4:
|