# configure with random scatterers
data = np.empty((num_scatterers, 4), dtype="float32")
data[:, 0] = np.random.uniform(low=args.x0,
high=args.x1,
size=(num_scatterers, ))
data[:, 1] = np.random.uniform(low=args.x0,
high=args.x1,
size=(num_scatterers, ))
data[:, 2] = np.random.uniform(low=0.0,
high=args.line_length + 1e-2,
size=(num_scatterers, ))
data[:, 3] = np.random.uniform(low=-1.0,
high=1.0,
size=(num_scatterers, ))
sim.clear_fixed_scatterers()
sim.add_fixed_scatterers(data)
# do the simulation
start_time = time()
iq_lines = sim.simulate_lines()
end_time = time()
elapsed_time = end_time - start_time
print "Simulation took %f sec @ %d scatterers." % (elapsed_time,
num_scatterers)
# store time per IQ-line
sim_times.append(elapsed_time / args.num_lines)
sim_nums.append(num_scatterers)
plt.clf()
plt.plot(t, envelope, 'g--', t, excitation)
plt.title('Excitation', fontsize=16, y=-.15)
plt.gca().set_facecolor('white')
plt.xticks([])
plt.yticks([])
# Record range of scatterer data
x_range = scatterers[:, 0].min(), scatterers[:, 0].max()
y_range = scatterers[:, 1].min(), scatterers[:, 1].max()
z_range = scatterers[:, 2].min(), scatterers[:, 2].max()
a_range = scatterers[:, 3].min(), scatterers[:, 3].max()
# Set scatterers
sim.clear_fixed_scatterers() # Make this cell idempotent
data = scatterers
sim.add_fixed_scatterers(data)
# Set the beam profile
sigma_lateral = 1e-3
sigma_elevational = 1e-3
sim.set_analytical_beam_profile(sigma_lateral, sigma_elevational)
# Simulate all scanlines
decimation = 1
sim.set_parameter('radial_decimation', str(decimation))
plt.figure()
plt.ion()
plt.show()
sim_times = []
sim_nums = []
for num_scatterers in all_nums:
# configure with random scatterers
data = np.empty((num_scatterers, 4), dtype="float32")
data[:, 0] = np.random.uniform(low=args.x0, high=args.x1, size=(num_scatterers,))
data[:, 1] = np.random.uniform(low=args.x0, high=args.x1, size=(num_scatterers,))
data[:, 2] = np.random.uniform(low=0.0, high=args.line_length+1e-2, size=(num_scatterers,))
data[:, 3] = np.random.uniform(low=-1.0, high=1.0, size=(num_scatterers,))
sim.clear_fixed_scatterers()
sim.add_fixed_scatterers(data)
# do the simulation
start_time = time()
iq_lines = sim.simulate_lines()
end_time = time()
elapsed_time = end_time-start_time
print "Simulation took %f sec @ %d scatterers." % (elapsed_time, num_scatterers)
# store time per IQ-line
sim_times.append(elapsed_time/args.num_lines)
sim_nums.append(num_scatterers)
plt.clf()
plt.plot(sim_nums, sim_times)