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@@ -480,7 +480,8 @@ def plot_scaled_theta(plot_lines, prop, title, mu, tgen, swp2_lines = None, ax =
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480
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480
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swp2_lines[0][k] = swp2_lines[0][k]/tgen*mu
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481
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481
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for k in range(len(swp2_lines[1])):
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482
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482
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swp2_lines[1][k] = swp2_lines[1][k]*4*mu
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483
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- x2_plot, y2_plot = plot_straight_x_y(swp2_lines[0],swp2_lines[1])
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483
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+ # x2_plot, y2_plot = plot_straight_x_y(swp2_lines[0],swp2_lines[1])
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484
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+ x2_plot, y2_plot = swp2_lines[0], swp2_lines[1]
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485
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p2, = ax2.plot(x2_plot, y2_plot, linestyle="-", alpha=0.75, lw=2, label = 'swp2', color="black")
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486
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lines_fig2.append(p2)
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487
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# Plotting (fig 3) which is the same but log scale for x
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@@ -530,7 +531,7 @@ def plot_scaled_theta(plot_lines, prop, title, mu, tgen, swp2_lines = None, ax =
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530
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531
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# plt.gca().set_xticks(x_ticks)
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531
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532
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plt.xticks(x_ticks)
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532
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533
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# plt.gca().set_xlim(xlim_val)
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533
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- plt.xlim(min_x, max_x)
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534
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+ plt.xlim(min(min_x,min(swp2_lines[0])), max(max(swp2_lines[0]), max_x))
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534
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535
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plt.gca().set_xticklabels([f'{k:.0e}\n{k/(mu):.0e}\n{k/(mu)*tgen:.0e}' for k in x_ticks], fontsize = fnt_size*0.5)
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536
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# rescale y to effective pop size
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536
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537
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# ylim_val = plt.gca().get_ylim()
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@@ -538,7 +539,7 @@ def plot_scaled_theta(plot_lines, prop, title, mu, tgen, swp2_lines = None, ax =
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538
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539
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# plt.gca().set_yticks(y_ticks)
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539
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540
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# plt.gca().set_ylim(ylim_val)
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541
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plt.yticks(y_ticks)
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541
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- plt.ylim(min_y, max_y+(max_y*0.05))
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542
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+ plt.ylim(min(min_y,min(swp2_lines[1])), max(max_y+(max_y*0.05), max(swp2_lines[1])+(max(swp2_lines[1])*0.05)))
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543
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plt.gca().set_yticklabels([f'{k/(4*mu):.0e}' for k in y_ticks], fontsize = fnt_size*0.5)
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543
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544
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plt.title(title, fontsize=fnt_size)
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545
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plt.legend(handles=lines_fig2, loc='best', fontsize = fnt_size*0.5)
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@@ -562,12 +563,12 @@ def plot_scaled_theta(plot_lines, prop, title, mu, tgen, swp2_lines = None, ax =
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562
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563
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# Scale the x-axis
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564
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x_ticks = list(ax3.get_xticks())
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565
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ax3.set_xticks(x_ticks)
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565
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- ax3.set_xlim(min(x_ticks), max_x)
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566
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+ ax3.set_xlim(min(min(x_ticks), min(swp2_lines[0])), max(max_x, max(swp2_lines[0])))
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567
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ax3.set_xticklabels([f'{k:.0e}\n{k/(mu):.0e}\n{k/(mu)*tgen:.0e}' for k in x_ticks], fontsize = fnt_size*0.5)
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567
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568
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# rescale y to effective pop size
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568
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569
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y_ticks = list(ax3.get_yticks())
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569
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570
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ax3.set_yticks(y_ticks)
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570
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- ax3.set_ylim(min(y_ticks), max_y+(max_y*0.5))
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571
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+ ax3.set_ylim(min(min(y_ticks), min(swp2_lines[1])), max(max_y+(max_y*0.5), max(swp2_lines[1])+(max(swp2_lines[1])*0.5)))
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572
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ax3.set_yticklabels([f'{k/(4*mu):.0e}' for k in y_ticks], fontsize = fnt_size*0.5)
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573
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plt.text(-0.13, -0.135, 'Coal. time\nGen. time\nYears', ha='left', va='bottom', transform=ax3.transAxes)
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573
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574
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plt.subplots_adjust(bottom=0.2) # Adjust the value as needed
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@@ -674,6 +675,7 @@ def combined_plot(folder_path, mu, tgen, breaks, title = "Title", theta_scale =
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674
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675
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swp2_summary = "/".join(folder_splitted[:-2])+'/'+folder_splitted[-3]+".final.summary"
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675
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676
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swp2_vals = parse_stairwayplot_output_summary(stwplt_out = swp2_summary)
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676
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677
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swp2_x, swp2_y = swp2_vals[0], swp2_vals[1]
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678
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+ remove_back_and_forth_points(swp2_x, swp2_y)
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677
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679
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# End of Parsing real swp2 output
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680
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plot_raw_stairs(plot_lines = loaded_data['raw_stairs'],
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679
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681
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prop = loaded_data['prop'], title = title, ax = None, max_breaks = breaks)
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@@ -684,6 +686,17 @@ def combined_plot(folder_path, mu, tgen, breaks, title = "Title", theta_scale =
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686
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685
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687
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# plt.close(fig1)
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688
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# plt.close(fig2)
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689
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+
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690
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+def remove_back_and_forth_points(x_values, y_values):
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691
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+ # to deal with some weirdness of plotting that occur sometimes with the swp2 output
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692
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+ # sometimes the line is going back and forth as x_k > x_(k+1), which is normally not possible
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693
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+ i = 0
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694
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+ while i < len(x_values) - 1:
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695
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+ if x_values[i] >= x_values[i+1]:
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696
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+ del x_values[i]
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697
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+ del y_values[i]
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698
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+ else:
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699
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+ i += 1
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687
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700
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def parse_stairwayplot_output_summary(stwplt_out, xlim = None, ylim = None, title = "default title", plot = False):
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688
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701
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#col 5
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689
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702
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year = []
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