def show_fwf(coord, pts):
global m
b = (coord == pts).all(axis=1)
if len(b[b]) > 0:
m += 1
# get first match
i = np.where(b)[0][0]
b = vlr_wpd == wpd[i]
step = vlr_temporal[b]
ampl = wf[i] * vlr_gain[b]
# remove background noise
ampl -= ampl[0:3].mean()
ampl[ampl < 0] = 0
V = dxdydz[i, :]
S_x = UTM_XYZ[i, 0] + ref_location_offset[i] * V[0]
S_y = UTM_XYZ[i, 1] + ref_location_offset[i] * V[1]
S_z = UTM_XYZ[i, 2] + ref_location_offset[i] * V[2]
pulse_x = S_x - np.arange(len(ampl)) * step * V[0]
pulse_y = S_y - np.arange(len(ampl)) * step * V[1]
pulse_z = S_z - np.arange(len(ampl)) * step * V[2]
exportlas('tmp_sel%i.las' % m, ampl,
np.transpose((pulse_x, pulse_y, pulse_z)))
call(['displaz', '-script', 'tmp_sel%i.las' % m])
pl.title('full wave form at (%.3f, %.3f, %.3f)' %
(coord[0], coord[1], coord[2]))
pl.plot(pulse_z, ampl, lw=1, alpha=0.7, label='p %i' % m)
pl.xlabel('Elevation [m]')
pl.ylabel('Amplitude')
call([
'displaz', '-annotation',
'p %i' % m,
'%.3f' % coord[0],
'%.3f' % coord[1],
'%.3f' % coord[2]
])
pl.legend(loc='upper right')
pl.axvline(x=ref_location_offset[i], c='r')
pl.grid()
pl.xlabel('Time [ps]')
pl.ylabel('Amplitude')
pl.title('Full Waveform of index %d' % i)
pl.show()
V = dxdydz[i, :]
S_x = UTM_XYZ[i, 0] + ref_location_offset[i] * V[0]
S_y = UTM_XYZ[i, 1] + ref_location_offset[i] * V[1]
S_z = UTM_XYZ[i, 2] + ref_location_offset[i] * V[2]
pulse_x = S_x - np.arange(len(ampl)) * step * V[0]
pulse_y = S_y - np.arange(len(ampl)) * step * V[1]
pulse_z = S_z - np.arange(len(ampl)) * step * V[2]
pts = np.transpose((pulse_x, pulse_y, pulse_z))
rgb = ampl
exportlas('%s_id%i.las' % (lasfname[:-4], i), rgb, pts)
pts_x = S_x - s[peaks] * V[0]
pts_y = S_y - s[peaks] * V[1]
pts_z = S_z - s[peaks] * V[2]
pts = np.transpose((pts_x, pts_y, pts_z))
rgb = usp(s)[peaks]
pts = pts[rgb > 20]
rgb = rgb[rgb > 20]
exportlas('%s_id%i_pts.las' % (lasfname[:-4], i), rgb, pts)
(coord[0], coord[1], coord[2]))
pl.plot(pulse_z, ampl, lw=1, alpha=0.7, label='p %i' % m)
pl.xlabel('Elevation [m]')
pl.ylabel('Amplitude')
call([
'displaz', '-annotation',
'p %i' % m,
'%.3f' % coord[0],
'%.3f' % coord[1],
'%.3f' % coord[2]
])
pl.legend(loc='upper right')
# load LAS file into displaz and start interaction
exportlas('tmp.las', intensity.astype('float64'), UTM_XYZ)
call(['displaz', '-script', 'tmp.las'])
pl.ion()
xo, yo, zo = 0, 0, 0
m = 0
pts = np.round(UTM_XYZ, decimals=3)
while True:
xs, ys, zs = map(
float,
str(check_output('displaz -script -querycursor', shell=True),
'utf-8').split())
d = np.sqrt((xs - xo)**2 + (ys - yo)**2 + (zs - zo)**2)
if d:
show_fwf(np.round([xs, ys, zs], decimals=3), pts)
fname = 'Haus29_ID04_FWF_V14_xyzinrtWV.asc'
UTM_XYZ, intensity, return_index, gps_time, wpd, byte_offset_wf_data, ref_location_offset, dxdydz, _, _, wf = loadfwf(
fname)
lasfname = 'Haus29_ID04_FWF.las'
_, _, vlr_bits_per_sample, vlr_compression, vlr_samples, vlr_temporal, vlr_gain, vlr_wpd = get_vlr_from_las(
lasfname)
from laspy.file import File
f = File(lasfname)
x = f.x
y = f.y
z = f.z
r = f.intensity
exportlas('%s_intensity.las' % lasfname[:-4], r.astype('float64'),
np.transpose((x, y, z, r)))
n = return_index.shape[0]
pts = np.zeros((n * 3, 3))
rgb = np.zeros(n * 3)
j = 0
for i in range(n):
if return_index[i, 1] > 1:
continue
print(i / n)
b = vlr_wpd == wpd[i]
step = vlr_temporal[b]
ampl = wf[i] * vlr_gain[b]
# remove background noise