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Adjust x-axis ticks for large SFSs

tforest 11 miesięcy temu
rodzic
commit
46a2990a2d
1 zmienionych plików z 43 dodań i 18 usunięć
  1. 43 18
      swp2.py

+ 43 - 18
swp2.py Wyświetl plik

@@ -4,6 +4,7 @@ import numpy as np
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 import math
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 from scipy.special import gammaln
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 from matplotlib.backends.backend_pdf import PdfPages
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+from matplotlib.ticker import MaxNLocator
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 def log_facto(k):
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     k = int(k)
@@ -320,7 +321,7 @@ def plot_all_epochs_thetafolder(folder_path, mu, tgen, title = "Title", theta_sc
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     plt.title(title)
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     plt.savefig(title+'_Breakpts_Likelihood_AIC.pdf')
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-def plot_test_theta(folder_path, mu, tgen, title = "Title", theta_scale = True, breaks_max = 5):
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+def plot_test_theta(folder_path, mu, tgen, title = "Title", theta_scale = True, breaks_max = 12):
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     """
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     Use theta values as is to do basic plots.
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     """
@@ -338,10 +339,17 @@ def plot_test_theta(folder_path, mu, tgen, title = "Title", theta_scale = True,
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                 epochs[k] = thetas
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     print("\n*******\n"+title+"\n--------\n"+"mu="+str(mu)+"\ntgen="+str(tgen)+"\nbreaks="+str(k)+"\n*******\n")
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     print(cpt, "theta file(s) have been scanned.")
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-
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     # intialize figure 1
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     my_dpi = 300
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-    plt.figure(figsize=(5000/my_dpi, 2800/my_dpi), dpi=my_dpi)
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+    # plt.figure(figsize=(5000/my_dpi, 2800/my_dpi), dpi=my_dpi)
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+    # multiple fig
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+    fig, ax = plt.subplots(figsize=(5000/my_dpi, 2800/my_dpi), dpi=my_dpi)
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+    # Add some extra space for the second axis at the bottom
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+    fig.subplots_adjust(bottom=0.15)
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+    twin = ax.twiny()
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+    # Offset the right spine of twin2
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+    # twin.spines.right.set_position(("axes", 1.2))
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+    plots = []
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     for epoch, theta in epochs.items():
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         groups = np.array(list(theta.values()), dtype=object)[:, 1].tolist()
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         x = []
@@ -352,21 +360,38 @@ def plot_test_theta(folder_path, mu, tgen, title = "Title", theta_scale = True,
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             y += list(np.repeat(thetas[i], len(group)))
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             if epoch == 0:
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                 N0 = y[0]
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+                # compute the proportion of information used at each bin of the SFS
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+                sum_theta_i = 0
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+                for i in range(2, len(y)+2):
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+                    sum_theta_i+=y[i-2] / (i-1)
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+                prop = []
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+                for k in range(2, len(y)+2):
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+                    prop.append(y[k-2] / (k - 1) / sum_theta_i)
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+                prop = prop[::-1]
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+                # print(prop, "\n", sum(prop))
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+        # normalise to N0 (N0 of epoch1)
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         for i in range(len(y)):
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             y[i] = y[i]/N0
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-        # compute the proportion of information used at each bin of the SFS
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-        sum_theta_i = 0
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-        for i in range(2, len(y)-1):
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-            sum_theta_i+=y[i] / (i-1)
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-        prop = []
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-        for k in range(2, len(y)-1):
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-            prop.append(y[k] / (k - 1) / sum_theta_i)
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-        # plot 
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-        plt.plot(x, y, 'o', linestyle="dotted", alpha=0.75, lw=2, label = str(epoch)+' brks')
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-        plt.xlabel("# breaks")
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-        plt.ylabel("theta")
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-        plt.legend(loc='upper right')
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-        plt.savefig(title+'_test'+str(k)+'.pdf')
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+        # plot
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+        #plt.plot(x, y, 'o', linestyle="dotted", alpha=0.75, lw=2, label = str(epoch)+' brks')
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+        p, = ax.plot(x, y, 'o', linestyle="dotted", alpha=0.75, lw=2, label = str(epoch)+' brks')
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+        # add plot to the list of all plots to superimpose
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+        plots.append(p)
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+    # virtual line to get the second x axis for proportions
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+    p0, = twin.plot(prop, y, alpha = 0, label="Proportion")
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+    # Move twinned axis ticks and label from top to bottom
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+    twin.xaxis.set_ticks_position("bottom")
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+    twin.xaxis.set_label_position("bottom")
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+    # Offset the twin axis below the host
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+    twin.spines["bottom"].set_position(("axes", -0.1))
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+    #ax.legend(handles=[p0]+plots)
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+    ax.set_xlabel("# breaks")
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+    # Set the x-axis locator to reduce the number of ticks = 10
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+    ax.xaxis.set_major_locator(MaxNLocator(nbins=10))
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+    ax.set_ylabel("theta")
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+    # twin.set_ylabel("Proportion")
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+    plt.legend(handles=plots, loc='upper right')
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+    plt.savefig(title+'_raw'+str(k)+'.pdf')
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     # fig 2 & 3
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     plt.figure(figsize=(5000/my_dpi, 2800/my_dpi), dpi=my_dpi)
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     for epoch, theta in epochs.items():
@@ -394,14 +419,14 @@ def plot_test_theta(folder_path, mu, tgen, title = "Title", theta_scale = True,
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         plt.xlabel("# breaks")
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         plt.ylabel("theta")
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         plt.legend(loc='upper right')
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-        plt.savefig(title+'_test'+str(k)+'.pdf')
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+        plt.savefig(title+'_plot2_'+str(k)+'.pdf')
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         # Plotting (fig 3) which is the same but log scale for x
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         plt.plot(x_2, y, 'o', linestyle="dotted", alpha=0.75, lw=2, label = str(epoch)+' brks')
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         plt.xscale('log')
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         plt.xlabel("# breaks")
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         plt.ylabel("theta")
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         plt.legend(loc='upper right')
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-        plt.savefig(title+'_test'+str(k)+'_log.pdf')
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+        plt.savefig(title+'_plot3_'+str(k)+'_log.pdf')
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 def save_multi_image(filename):
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     pp = PdfPages(filename)