Add compound_bca_list_1d_py example.

examples/compound_bca_list_1d_py.py

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+from libRustBCA import *
+import numpy as np
+import matplotlib.pyplot as plt
+import sys, os
+sys.path.append(os.path.dirname(__file__)+'/../scripts')
+sys.path.append('scripts')
+from materials import *
+from formulas import *
+
+
+'''
+This script is intended to serve as an example of using the Python 
+interface for a multi-layer, multi-species simulation.
+
+In this simulation, 50 He and 50 H ions are incident on a target 
+of two layers, one titanium boride and one aluminum:
+
+_____________
+|           |
+|    TiB2   | dx = 100 A
+_____________
+|           |
+|     Al    | dx = 1 um
+|           |
+
+'''
+number_ions = 10000
+angle = 45.0 # angles in BCA codes are typically measured from the surface normal.
+energy = 1000.0 # eV
+
+ux = [np.cos(angle*np.pi/180.0)]*number_ions
+uy = [np.sin(angle*np.pi/180.0)]*number_ions
+uz = [0.0]*number_ions
+
+energies = [energy]*number_ions
+ion1 = hydrogen
+ion2 = helium
+
+# Ion properties are per-ion; so we have a list of number_ions/2 of each:
+Z1 = [ion1["Z"]]*(number_ions//2) + [ion2["Z"]]*(number_ions//2)
+m1 = [ion1["m"]]*(number_ions//2) + [ion2["m"]]*(number_ions//2)
+Ec1 = [ion1["Ec"]]*(number_ions//2) + [ion2["Ec"]]*(number_ions//2)
+Es1 = [ion1["Es"]]*(number_ions//2) + [ion2["Es"]]*(number_ions//2)
+
+# Material properties are per species; so we have a list of 3 species:
+Z2 = [titanium["Z"], boron["Z"], aluminum["Z"]]
+m2 = [titanium["m"], boron["m"], aluminum["m"]]
+Ec2 = [titanium["Ec"], boron["Ec"], aluminum["Ec"]]
+Es2 = [titanium["Es"], boron["Es"], aluminum["Es"]]
+Eb2 = [titanium["Eb"], boron["Eb"], aluminum["Eb"]]
+
+# Densities (n2) are specified as a list of layers,
+# each of which has a list of the densities per-species:
+
+#top layer, titanium diboride:
+# n_i calculated from ni = rho_TiB2 / (m_Ti + 2 * m_B)
+ni = 3.8e28 # 1/m3
+
+nTi1 = ni/10**30 # 1/A^3
+nB1 = 2 * ni/10**30  # 1/A^3
+nAl1 = 0.0
+
+# bottom layer, pure aluminum:
+nTi2 = 0.0
+nB2 = 0.0
+nAl2 = aluminum["n"]/10**30 # 1/A^3
+
+n2 = [
+    [nTi1, nB1, nAl1], # top layer
+    [nTi2, nB2, nAl2] # bottom layer
+]
+
+dx = [
+    100.0, # Angstrom, top layer
+    1.0*1e-6/1e-10 # Angstrom; bottom layer
+]
+
+# compound_bca_list_py provides three return values
+output, incident, stopped = compound_bca_list_1D_py(
+    ux,
+    uy,
+    uz,
+    energies,
+    Z1,
+    m1,
+    Ec1,
+    Es1,
+    Z2,
+    m2,
+    Ec2,
+    Es2,
+    Eb2,
+    n2,
+    dx
+)
+
+# output columns = [Z, m (amu), E (eV), x, y, z, (angstrom), ux, uy, uz]
+output = np.array(output)
+Z = output[:, 0]
+E = output[:, 0]
+
+# implanted ions can be selected using the stopped value
+x_He = output[np.logical_and(Z == helium["Z"], stopped), 3]
+x_H = output[np.logical_and(Z == hydrogen["Z"], stopped), 3]
+
+num_bins = 50
+bins = np.linspace(0.0, 400.0, num_bins)
+plt.hist(x_He, bins=bins, histtype='step', label='He')
+plt.hist(x_H, bins=bins, histtype='step', label='H')
+plt.plot([dx[0], dx[0]], [0.0, number_ions], linestyle='--', color='gray')
+plt.ylim([0.0, 375])
+plt.xlabel('x [A]')
+plt.ylabel('f(x) [counts]')
+plt.title('H/He implantation in TiB2 on Al')
+plt.legend()
+plt.show()