def plot_bscan(dataset_name, save=False, noshow=False):
conf = arim.io.load_conf(dataset_name)
frame = common.load_frame(conf,
apply_filter=True,
expand=False,
warn_if_fallback_vel=True)
result_dir = conf["result_dir"]
# plot bscan
ax, imag = aplt.plot_bscan_pulse_echo(frame,
clim=[-40, 0],
filename=str(result_dir / "bscan"),
savefig=save)
if noshow:
plt.close("all")
else:
plt.show()
# %% Load datafile (exported from BRAIN)
expdata_filename = r"example-datasets/contact_notch_aluminium.mat"
frame = arim.io.load_expdata(expdata_filename)
print("Frame:")
pp(frame.metadata)
print(frame)
print()
print("Probe:")
print(frame.probe)
pp(frame.probe.metadata)
# %% Plot Bscans (unfiltered)
aplt.plot_bscan_pulse_echo(frame)
plt.draw()
# %% Filter data
filt = arim.signal.Hilbert() + arim.signal.ButterworthBandpass(
order=5, cutoff_min=0.5e6, cutoff_max=6e6, time=frame.time)
frame_raw = frame
frame = frame_raw.apply_filter(filt)
# %% Plot timetraces
plt.figure()
tx, rx = (19, 19)
plt.plot(frame_raw.time.samples, frame_raw.get_timetrace(tx, rx), label="raw")
plt.plot(frame.time.samples,
np.abs(frame.get_timetrace(tx, rx)),
def measure_probe_location(dataset_name, save=False, noshow=False):
# %%
conf = arim.io.load_conf(dataset_name)
logger.info(f"dataset_name: {dataset_name}")
frame = common.load_frame(conf,
apply_filter=True,
expand=False,
warn_if_fallback_vel=False)
result_dir = conf["result_dir"]
# Prepare
frame = frame.apply_filter(arim.signal.Abs())
plt.figure()
plt.plot(frame.time.samples, frame.scanlines[0])
plt.gca().yaxis.set_major_formatter(aplt.micro_formatter)
plt.title(f"{dataset_name}\nA-scan")
# plot bscan
ax, imag = aplt.plot_bscan_pulse_echo(frame,
clim=[-40, 0],
filename=str(result_dir / "bscan"),
savefig=save)
# Detect frontwall:
probe_standoff, probe_angle, time_to_surface = arim.measurement.find_probe_loc_from_frontwall(
frame,
frame.examination_object.couplant_material,
tmin=10e-6,
tmax=None)
plt.figure()
plt.plot(time_to_surface[frame.tx == frame.rx])
plt.xlabel("element")
plt.ylabel("time (µs)")
plt.gca().yaxis.set_major_formatter(aplt.micro_formatter)
plt.gca().yaxis.set_minor_formatter(aplt.micro_formatter)
plt.title(
f"{dataset_name}\ntime between elements and frontwall - must be a line!"
)
if save:
plt.savefig(str(result_dir / "frontwall_detection"))
new_conf = dict(
probe_location={
"standoff": probe_standoff.tolist(),
"angle_deg": np.rad2deg(probe_angle).tolist(),
})
conf_file = conf["root_dir"] / "conf.d/10probe_loc.yaml"
if save:
with conf_file.open("w", encoding="utf8") as stream:
stream.write("# generated by measure_probe_loc.py\n")
yaml.dump(dict(new_conf), stream=stream, default_flow_style=False)
if noshow:
plt.close("all")
else:
plt.show()
def test_fulltime_model(use_multifreq, show_plots):
# Setup
couplant = arim.Material(longitudinal_vel=1480.0,
density=1000.0,
state_of_matter="liquid")
block = arim.Material(
longitudinal_vel=6320.0,
transverse_vel=3130.0,
density=2700.0,
state_of_matter="solid",
longitudinal_att=arim.material_attenuation_factory("constant", 2.0),
transverse_att=arim.material_attenuation_factory("constant", 20.0),
)
probe = arim.Probe.make_matrix_probe(20, 1e-3, 1, np.nan, 5e6)
probe_element_width = 0.8e-3
probe.set_reference_element("first")
probe.reset_position()
probe.translate([0.0, 0.0, -5e-3])
probe.rotate(arim.geometry.rotation_matrix_y(np.deg2rad(10)))
probe_p = probe.to_oriented_points()
frontwall = arim.geometry.points_1d_wall_z(numpoints=1000,
xmin=0.0e-3,
xmax=40.0e-3,
z=0.0,
name="Frontwall")
backwall = arim.geometry.points_1d_wall_z(numpoints=1000,
xmin=0.0e-3,
xmax=40.0e-3,
z=30.0e-3,
name="Backwall")
scatterer_p = arim.geometry.default_oriented_points(
arim.Points([[35e-3, 0.0, 20e-3]]))
all_points = [probe_p, frontwall, backwall, scatterer_p]
# if show_plots:
# import arim.plot as aplt
# aplt.plot_interfaces(
# all_points, markers=["o", "o", "o", "d"], show_orientations=True
# )
# aplt.plt.show()
exam_obj = arim.BlockInImmersion(block, couplant, frontwall, backwall,
scatterer_p)
scat_obj = arim.scat.scat_factory(material=block,
kind="sdh",
radius=0.5e-3)
scat_funcs = scat_obj.as_angles_funcs(probe.frequency)
scat_angle = 0.0
tx_list, rx_list = arim.ut.fmc(probe.numelements)
# Toneburst
dt = 0.25 / probe.frequency # to adjust so that the whole toneburst is sampled
toneburst_time, toneburst, toneburst_t0_idx = arim.model.make_toneburst2(
5, probe.frequency, dt, num_before=1)
toneburst_f = np.fft.rfft(toneburst)
toneburst_freq = np.fft.rfftfreq(len(toneburst_time), dt)
# Allocate a long enough time vector for the timetraces
views = bim.make_views(
exam_obj,
probe_p,
scatterer_p,
max_number_of_reflection=0,
tfm_unique_only=False,
)
arim.ray.ray_tracing(views.values())
max_delay = max(
(view.tx_path.rays.times.max() + view.rx_path.rays.times.max()
for view in views.values()))
timetraces_time = arim.Time(
0.0, dt,
math.ceil(max_delay / dt) + len(toneburst_time))
timetraces = None
# Run model
if use_multifreq:
model_freq_array = toneburst_freq
else:
model_freq_array = probe.frequency
transfer_function_iterator = bim.scat_unshifted_transfer_functions(
views,
tx_list,
rx_list,
model_freq_array,
scat_obj,
probe_element_width=probe_element_width,
use_directivity=True,
use_beamspread=True,
use_transrefl=True,
use_attenuation=True,
scat_angle=scat_angle,
numangles_for_scat_precomp=120,
)
for unshifted_transfer_func, delays in transfer_function_iterator:
timetraces = arim.model.transfer_func_to_timetraces(
unshifted_transfer_func,
delays,
timetraces_time,
toneburst_time,
toneburst_freq,
toneburst_f,
toneburst_t0_idx,
timetraces=timetraces,
)
frame = arim.Frame(timetraces, timetraces_time, tx_list, rx_list, probe,
exam_obj)
if show_plots:
import matplotlib.pyplot as plt
import arim.plot as aplt
aplt.plot_bscan_pulse_echo(frame)
plt.title(
f"test_fulltime_model - Bscan - use_multifreq={use_multifreq}")
tx = 0
rx = probe.numelements - 1
plt.figure()
plt.plot(np.real(frame.get_timetrace(tx, rx)),
label=f"tx={tx}, rx={rx}")
plt.plot(np.real(frame.get_timetrace(rx, tx)),
label=f"tx={rx}, rx={tx}")
plt.title(f"test_fulltime_model - use_multifreq={use_multifreq}")
plt.legend()
plt.show()
def locate_artefact(dataset_name, save):
# %%
conf = arim.io.load_conf(dataset_name)
# conf['grid']['pixel_size'] = 2e-3 # debug
conf["grid"]["pixel_size"] = 0.5e-3 # hardcode to make faster
aplt.conf["savefig"] = False
result_dir = conf["result_dir"]
logger.info(f"dataset_name: {dataset_name}")
# Load frame
frame = common.load_frame(conf, apply_filter=True, expand=True)
# Make grid
z_backwall = conf["backwall"]["z"]
assert not np.isnan(z_backwall)
grid = common.make_grid_tfm(conf)
grid_p = grid.to_oriented_points()
probe_p = frame.probe.to_oriented_points()
# Make views
views = bim.make_views(
frame.examination_object,
probe_p,
grid_p,
tfm_unique_only=True,
max_number_of_reflection=1,
)
# %% Plot Bscan
bscan_ax, _ = aplt.plot_bscan_pulse_echo(frame,
clim=[-60, -20],
interpolation="bilinear")
bscan_ax.figure.canvas.set_window_title("Bscan")
# %% Perform ray tracing
arim.ray.ray_tracing(views.values(), convert_to_fortran_order=True)
# %% Run TFM
tfms = OrderedDict()
for i, view in enumerate(views.values()):
with arim.helpers.timeit("TFM {}".format(view.name), logger=logger):
tfms[view.name] = arim.im.tfm.tfm_for_view(frame,
grid,
view,
fillvalue=0.0)
# %% Plot all TFM
try:
reference_rect = common.reference_rect(conf)
reference_area = grid.points_in_rectbox(**reference_rect)
except common.NoDefect:
reference_rect = None
reference_area = None
if USE_DYNAMIC_SCALE:
scale = aplt.common_dynamic_db_scale(
[tfm.res for tfm in tfms.values()], reference_area)
else:
scale = itertools.repeat((None, None))
tfm_axes = {}
ncols = 3
nrows = 7
fig, axes = plt.subplots(ncols=ncols,
nrows=nrows,
figsize=(9, 12),
sharex=False,
sharey=False)
xmin = grid.xmin
xmax = grid.xmax
zmin = conf["frontwall"]["z"]
zmax = conf["backwall"]["z"]
for i, ((viewname, tfm), ax) in enumerate(zip(tfms.items(), axes.ravel())):
ref_db, clim = next(scale)
clim = [-40, 0.0]
ax, im = aplt.plot_tfm(
tfm,
ax=ax,
scale="db",
ref_db=ref_db,
clim=clim,
interpolation="none",
savefig=False,
draw_cbar=False,
)
ax.set_title(viewname, y=0.9, size="small")
ax.set_adjustable("box")
ax.axis([xmin, xmax, zmax, zmin])
tfm_axes[viewname] = ax
if ax in axes[-1, :]:
ax.set_xlabel("x (mm)")
ax.set_xticks(
[xmin, xmax,
np.round((xmin + xmax) / 2, decimals=3)])
else:
ax.set_xlabel("")
ax.set_xticks([])
if ax in axes[:, 0]:
ax.set_ylabel("z (mm)")
ax.set_yticks(
[zmax, zmin,
np.round((zmin + zmax) / 2, decimals=3)])
else:
ax.set_ylabel("")
ax.set_yticks([])
cbar = fig.colorbar(im,
ax=axes.ravel().tolist(),
location="top",
fraction=0.05,
aspect=40,
pad=0.03)
cbar.ax.set_ylabel("dB")
ax.figure.canvas.set_window_title(f"TFMs")
return bscan_ax, tfm_axes, tfms, views