tidied up a few things

examples/graph-example-beta-delayed.py

@@ -2,17 +2,55 @@ import numpy as np
 import matplotlib as mpl
 import matplotlib.pyplot as plt
 import matplotlib.patheffects as pe
-
 mpl.style.use('seaborn-colorblind')
 
+
+# IMPORT DATA
 n, Z, N, QEC, QB, Qa, QECp, QBn, QEC2p, QB2n, QECa, QBa, QECp_est, QBn_est, QEC2p_est, \
 QB2n_est, QECa_est, QBa_est, half_life, half_life_est, half_life_stbl = np.loadtxt('examples/beta-delayed.dat', unpack=True)
 
+
+# DEFINE HELPFUL SCALARS AND ARRAYS
 xmin = int(np.min(N))
 xmax = int(np.max(N))
 ymin = int(np.min(Z))
 ymax = int(np.max(Z))
 
+xlower = xupper = ylower = yupper = np.array([])
+for i in range(xmin, xmax + 1):
+  x_indices = np.argwhere(Z == i)
+  xlower = np.append(xlower, np.max(N[x_indices]))
+  xupper = np.append(xupper, np.min(N[x_indices]))
+for i in range(ymin, ymax + 1):
+  y_indices = np.argwhere(N == i)
+  ylower = np.append(ylower, np.min(Z[y_indices]))
+  yupper = np.append(yupper, np.max(Z[y_indices]))
+# fix data-inherent shortcomings and align arrays
+xupper[0] = 0
+xupper[2] = 0
+ylower[0] = 0
+yupper = np.append(yupper, yupper[-1])
+yupper = np.roll(yupper, -1)
+xlower = np.append(xlower, xlower[-1])
+xlower = np.roll(xlower, -1)
+
+
+# SET SOME GENERAL PROPERTIES ON OUTPUT FIGURE
+ax = plt.gca()
+ax.set_xticks(np.arange(xmin, xmax + 1, 8))
+ax.set_yticks(np.arange(xmin, xmax + 1, 8))
+ax.set_xticks(np.arange(xmin, xmax + 1, 4), minor=True)
+ax.set_yticks(np.arange(xmin, xmax + 1, 4), minor=True)
+ax.set_axisbelow(True)
+ax.grid(which='both', linestyle='--', alpha=0.3)
+ax.set_aspect('equal')
+plt.xlim(xmin - 0.5, 36 + 0.5)
+plt.ylim(xmin - 0.5, 36 + 0.5)
+plt.xlabel('$N$')
+plt.ylabel('$Z$')
+
+
+# DEFINE THE DISTINCTIONS TO BE MADE BETWEEN NUCLIDES IN THE CHART OF NUCLIDES
 filters = [(np.ones(len(n), dtype=bool)), 
            (half_life_stbl == 1), 
            (
@@ -28,13 +66,12 @@ filters = [(np.ones(len(n), dtype=bool)),
            (((QBa > 0) & (QB > 0) & (half_life > 1e-4)) | ((QECa > 0) & (QEC > 0) & (half_life > 1e-4))),
            ((half_life < 1e-4) | (np.isnan(half_life))) & ~(half_life_stbl == 1)
            ]
-
 labels = ['',
-          '$\mathtt{Stable}$',
-          '$\mathtt{ECp}$  / $\mathtt{\\beta^{-}n}$',
-          '$\mathtt{EC2p}$ / $\mathtt{\\beta^{-}2n}$', 
-          '$\mathtt{EC\\alpha}$  / $\mathtt{\\beta^{-}\\alpha}$',
-          '$\mathtt{t_{1/2} }$ < 0.1 ms or \n$\mathtt{t_{1/2} }$ unknown']
+          'Stable',
+          'ECp  / $\mathtt{\\beta^{-}}$n',
+          'EC2p / $\mathtt{\\beta^{-}}$2n',
+          'EC$\mathtt{\\alpha}$  / $\mathtt{\\beta^{-}\\alpha}$',
+          '$t_{1/2}$ < 0.1 ms or \n$t_{1/2}$ unknown']
 rectcenters = [0.5, 0.5, 0.5, 0.5, 0.3, 0.5]
 rectsizes = [1.0, 1.0, 1.0, 1.0, 0.6, 1.0]
 linewidths = [0.0, 0.0, 0.0, 0.0, 0.2, 0.0]
@@ -43,23 +80,8 @@ edgecolors = ['w', 'k', 'C5', 'C2', 'k', 'C9']
 facecolors = ['w', 'k', 'C5', 'C2', 'C4', 'C9']
 shapes = ['s', 's', 's', 's', 'D', 's']
 
-xlower = xupper = ylower = yupper = np.array([])
-for i in range(xmin, xmax + 1):
-  x_indices = np.argwhere(Z == i)
-  xlower = np.append(xlower, np.max(N[x_indices]))
-  xupper = np.append(xupper, np.min(N[x_indices]))
-for i in range(ymin, ymax + 1):
-  y_indices = np.argwhere(N == i)
-  ylower = np.append(ylower, np.min(Z[y_indices]))
-  yupper = np.append(yupper, np.max(Z[y_indices]))
 
-ax = plt.gca()
-ax.set_xticks(np.arange(xmin, xmax + 1, 8))
-ax.set_yticks(np.arange(xmin, xmax + 1, 8))
-ax.set_xticks(np.arange(xmin, xmax + 1, 4), minor=True)
-ax.set_yticks(np.arange(xmin, xmax + 1, 4), minor=True)
-ax.set_axisbelow(True)
-ax.grid(which='both', linestyle='--', alpha=0.3)
+# PLOT THE DISTINCTIONS
 for i in range(len(filters)):
   if i > 0: # no legend for white squares which are printed for all existing nuclides (otherwise grid is obstructing)
     plt.plot(-100, -100, marker=shapes[i], markeredgecolor=edgecolors[i], markersize=markersizes[i],
@@ -73,20 +95,18 @@ for i in range(len(filters)):
       ax.add_patch(plt.Rectangle((x, y - np.sqrt(2)*rectcenters[i]),
                                rectsizes[i], rectsizes[i], edgecolor=edgecolors[i],
                                facecolor=facecolors[i], linewidth=linewidths[i], angle=45.0))
-ax.set_aspect('equal')
+handles, labels = plt.gca().get_legend_handles_labels()
+order = [0, 1, 2, 3, 4]
+L = plt.legend([handles[idx] for idx in order], [labels[idx] for idx in order], fontsize=8.0)
+plt.setp(L.texts, family='monospace')
 
 
-# align arrays and fix data-inherent shortcomings
-yupper = np.append(yupper, yupper[-1])
-yupper = np.roll(yupper, -1)
-xupper[0] = 0
-xupper[2] = 0
-ylower[0] = 0
-xlower = np.append(xlower, xlower[-1])
-xlower = np.roll(xlower, -1)
+# PLOT A GRID ON TOP OF ALL KNOWN NUCLIDES
 plt.vlines(np.array(range(int(xmin), int(xmax) + 1)) + 0.5, ylower - 0.5, yupper[0:-1] + 0.5, lw=0.4, color='k', capstyle='round')
 plt.hlines(np.array(range(int(ymin), int(ymax) + 1)) + 0.5, xlower[0:-1] + 0.5, xupper - 0.5, lw=0.4, color='k', capstyle='round')
 
+
+# HIGHLIGHT SPECIFIC NUCLIDES
 text0 = plt.annotate("$\mathtt{^{21}Mg}$", (9, 12), (3.5, 17), arrowprops=dict(arrowstyle="wedge", lw=1, facecolor='k'), ha="right", path_effects=[pe.withStroke(linewidth=0.6, foreground='lightgrey')])
 text0.arrow_patch.set_path_effects([pe.Stroke(linewidth=1.6, foreground='lightgrey'), pe.Normal()])
 text1 = plt.annotate("$\mathtt{^{22}Al}$", (9, 13), (7.5, 21), arrowprops=dict(arrowstyle="wedge", lw=1, edgecolor='whitesmoke', facecolor='whitesmoke'), ha="right", color='whitesmoke', path_effects=[pe.withStroke(linewidth=0.6, foreground='k')])
@@ -94,13 +114,6 @@ text1.arrow_patch.set_path_effects([pe.Stroke(linewidth=1.6, foreground='k'), pe
 text2 = plt.annotate("$\mathtt{^{26}P}$", (11, 15), (11, 21), arrowprops=dict(arrowstyle="wedge", lw=1, edgecolor='whitesmoke', facecolor='whitesmoke'), ha="right", color='whitesmoke', path_effects=[pe.withStroke(linewidth=0.6, foreground='k')])
 text2.arrow_patch.set_path_effects([pe.Stroke(linewidth=1.6, foreground='k'), pe.Normal()])
 
-plt.xlim(xmin - 0.5, 36 + 0.5)
-plt.ylim(xmin - 0.5, 36 + 0.5)
-plt.xlabel('$N$')
-plt.ylabel('$Z$')
-handles, labels = plt.gca().get_legend_handles_labels()
-order = [0, 1, 2, 3, 4]
-L = plt.legend([handles[idx] for idx in order], [labels[idx] for idx in order], fontsize=8.0)
-plt.setp(L.texts, family='monospace')
-plt.savefig('examples/beta-delayed.pdf', bbox_inches='tight', dpi=300)
 
+# SAVE THE FIGURE
+plt.savefig('examples/beta-delayed.pdf', bbox_inches='tight', dpi=300)

treemaker.py

@@ -105,18 +105,14 @@ while True:
   result2 = re2.findall(line2)
   result3 = re3.findall(line3)
   result4 = re4.findall(line4)
-  result5 = re5.findall(line4)
+  while not is_ground_state(result4): # all data files nicely follow the same ordering of isotopes if none-ground state isotopes are skipped in file4
+    line4 = file4.readline()
+    result4 = re4.findall(line4)
+  result5 = re5.findall(line4) # regex patterns 4, 5, 6 and 7 all refer to file4
   result6 = re6.findall(line4)
-  result7 = re7.findall(line4) # regex patterns 4, 5, 6 and 7 all refer to file4
-  
+  result7 = re7.findall(line4)
+
   for i in range(len(code_strings)):
-    #all data files nicely follow the same ordering of isotopes if none-ground state isotopes are skipped in file4
-    while not is_ground_state(result4):
-      line4 = file4.readline()
-      result4 = re4.findall(line4)
-      result5 = re5.findall(line4)
-      result6 = re6.findall(line4)
-      result7 = re7.findall(line4)
     exec(code_strings[i])
   t.Fill()