def main(args):
'''
Main function, invoked from either command line or qc_wrap
'''
pargs = parser.parse_args(args[1:])
lasname = pargs.las_file
kmname = constants.get_tilename(lasname)
msg = "Running %s on block: %s, %s"
print(msg % (os.path.basename(args[0]), kmname, time.asctime()))
if pargs.schema is not None:
report.set_schema(pargs.schema)
reporter = report.ReportSpikes(pargs.use_local)
if pargs.zlim < 0:
print("zlim must be positive!")
usage()
if pargs.slope < 0 or pargs.slope >= 90:
print("Specify a slope angle in the range 0->90 degrees.")
usage()
cut_class = pargs.cut_class
print("Cutting to class (terrain) {0:d}".format(cut_class))
pc = pointcloud.fromAny(lasname).cut_to_class(cut_class)
if pc.get_size() < 10:
print("Too few points in pointcloud.")
return
print("Sorting spatially...")
pc.sort_spatially(FILTER_RAD)
slope_arg = np.tan(np.radians(pargs.slope))**2
msg = "Using steepnes parameters: angle: {0:.2f} degrees, delta-z: {1:.2f}"
print(msg.format(pargs.slope, pargs.zlim))
print("Filtering, radius: {0:.2f}".format(FILTER_RAD))
dz = pc.spike_filter(FILTER_RAD, slope_arg, pargs.zlim)
mask = (dz != 0)
dz = dz[mask]
pc = pc.cut(mask)
print("Spikes: {0:d}".format(mask.sum()))
for i in range(pc.size):
x, y = pc.xy[i]
z = pc.z[i]
mdz = dz[i]
c = pc.c[i]
pid = pc.pid[i]
print("spike: x: {0:.2f} y: {1:.2f} mean-dz: {2:.2f}".format(
x, y, mdz))
wkt_geom = "POINT({0:.2f} {1:.2f})".format(x, y)
reporter.report(kmname,
FILTER_RAD,
mdz,
x,
y,
z,
c,
pid,
wkt_geom=wkt_geom)
def main(args): pargs=parser.parse_args(args[1:]) lasname=pargs.las_file roadname=pargs.road_data cut=pargs.cut_to if pargs.schema is not None: report.set_schema(pargs.schema) reporter=report.ReportZcheckRoad(pargs.use_local) done=zcheck_base.zcheck_base(lasname,roadname,angle_tolerance,xy_tolerance,z_tolerance,cut,reporter,buffer_dist=buffer_dist,layername=pargs.layername,layersql=pargs.layersql)
def main(args):
try:
pargs = parser.parse_args(args[1:])
except Exception as e:
print(str(e))
return 1
lasname = pargs.las_file
kmname = constants.get_tilename(lasname)
print("Running %s on block: %s, %s" % (progname, kmname, time.asctime()))
if pargs.schema is not None:
report.set_schema(pargs.schema)
reporter = report.ReportWobbly(pargs.use_local)
pc = pointcloud.fromAny(lasname).cut_to_class(pargs.cut_to)
print("%d points of class %d in this tile..." %
(pc.get_size(), pargs.cut_to))
if pc.get_size() < 3:
print("Few points of class %d in this tile..." % pargs.cut_to)
return 0
print("Using z-limit %.2f m" % pargs.zmin)
pc.sort_spatially(pargs.frad)
meanz = pc.mean_filter(pargs.frad)
diff = pc.z - meanz
M = (np.fabs(diff) > pargs.zmin)
n = M.sum()
print("Found %d wobbly points" % n)
if n > 0:
pc = pc.cut(M)
diff = diff[M]
ds, lyr = polygonise_points(pc, 2 * pargs.frad, 1)
nf = lyr.GetFeatureCount()
for i in range(nf):
fet = lyr.GetNextFeature()
geom = fet.GetGeometryRef()
arr_geom = array_geometry.ogrpoly2array(geom, flatten=True)
N = array_geometry.points_in_polygon(pc.xy, arr_geom)
n = N.sum()
if n > 0:
d = diff[N]
m1 = d.min()
m2 = d.max()
else:
m1 = -999
m2 = -999
reporter.report(kmname,
pargs.cut_to,
pargs.frad,
n,
m1,
m2,
ogr_geom=geom)
return 0
def main(args):
'''
Main function that can be called from either the command line or via qc_wrap.py
'''
try:
pargs = parser.parse_args(args[1:])
except Exception as error_msg:
print(str(error_msg))
return 1
kmname = constants.get_tilename(pargs.las_file)
print("Running %s on block: %s, %s" % (PROGNAME, kmname, time.asctime()))
if pargs.below_poly:
below_poly = True
ptype = "below_poly"
else:
below_poly = False
if pargs.type is not None:
ptype = pargs.type
else:
ptype = "undefined"
if below_poly:
print("Only using points which lie below polygon mean z!")
pc = pointcloud.fromAny(pargs.las_file)
print("Classes in pointcloud: %s" % pc.get_classes())
try:
extent = np.asarray(constants.tilename_to_extent(kmname))
except Exception:
print("Could not get extent from tilename.")
extent = None
polygons = vector_io.get_geometries(pargs.ref_data, pargs.layername,
pargs.layersql, extent)
feature_count = 0
use_local = pargs.use_local
if pargs.schema is not None:
report.set_schema(pargs.schema)
reporter = report.ReportClassCheck(use_local)
for polygon in polygons:
if below_poly:
if polygon.GetCoordinateDimension() < 3:
print(
"Error: polygon not 3D - below_poly does not make sense!")
continue
a_polygon3d = array_geometry.ogrpoly2array(polygon,
flatten=False)[0]
#warping loop here....
if pargs.toE:
geoid = grid.fromGDAL(GEOID_GRID, upcast=True)
print("Using geoid from %s to warp to ellipsoidal heights." %
GEOID_GRID)
toE = geoid.interpolate(a_polygon3d[:, :2].copy())
mask = toE == geoid.nd_val
if mask.any():
raise Warning(
"Warping to ellipsoidal heights produced no-data values!"
)
a_polygon3d[:, 2] += toE
mean_z = a_polygon3d[:, 2].mean()
if mean_z < SENSIBLE_Z_MIN or mean_z > SENSIBLE_Z_MAX:
msg = "Warning: This feature seems to have unrealistic mean z value: {0:.2f} m"
print(msg.format(mean_z))
continue
del a_polygon3d
else:
mean_z = -1
polygon.FlattenTo2D()
feature_count += 1
separator = "-" * 70
print("%s\nFeature %d\n%s" % (separator, feature_count, separator))
a_polygon = array_geometry.ogrpoly2array(polygon)
pc_in_poly = pc.cut_to_polygon(a_polygon)
if below_poly:
pc_in_poly = pc_in_poly.cut_to_z_interval(-999, mean_z)
n_all = pc_in_poly.get_size()
freqs = [0] * (len(constants.classes) + 1) #list of frequencies...
if n_all > 0:
c_all = pc_in_poly.get_classes()
if below_poly and DEBUG:
print("Mean z of polygon is: %.2f m" % mean_z)
print("Mean z of points below is: %.2f m" %
pc_in_poly.z.mean())
print("Number of points in polygon: %d" % n_all)
print("Classes in polygon: %s" % str(c_all))
# important for reporting that the order here is the same as in the table
# definition in report.py!!
n_found = 0
for i, cls in enumerate(constants.classes):
if cls in c_all:
pcc = pc_in_poly.cut_to_class(cls)
n_c = pcc.get_size()
f_c = n_c / float(n_all)
n_found += n_c
print("Class %d::" % cls)
print(" #Points: %d" % n_c)
print(" Fraction: %.3f" % f_c)
freqs[i] = f_c
f_other = (n_all - n_found) / float(n_all)
freqs[-1] = f_other
send_args = [kmname] + freqs + [n_all, ptype]
reporter.report(*send_args, ogr_geom=polygon)
def main(args):
'''
Core function. Called either stand-alone or from qc_wrap.
'''
try:
pargs = parser.parse_args(args[1:])
except Exception as error_str:
print(str(error_str))
return 1
kmname = constants.get_tilename(pargs.las_file)
print("Running %s on block: %s, %s" % (PROGNAME, kmname, time.asctime()))
cell_size = pargs.cs
ncols_f = TILE_SIZE / cell_size
ncols = int(ncols_f)
if ncols != ncols_f:
print("TILE_SIZE: %d must be divisible by cell size..." % (TILE_SIZE))
usage()
return 1
print("Using cell size: %.2f" % cell_size)
use_local = pargs.use_local
if pargs.schema is not None:
report.set_schema(pargs.schema)
reporter = report.ReportDensity(use_local)
outdir = pargs.outdir
if not os.path.exists(outdir):
os.mkdir(outdir)
lasname = pargs.las_file
waterconnection = pargs.ref_data
outname_base = "den_{0:.0f}_".format(cell_size) + os.path.splitext(
os.path.basename(lasname))[0] + ".tif"
outname = os.path.join(outdir, outname_base)
print("Reading %s, writing %s" % (lasname, outname))
try:
(x_min, y_min, x_max, y_max) = constants.tilename_to_extent(kmname)
except Exception as error_str:
print("Exception: %s" % str(error_str))
print("Bad 1km formatting of las file: %s" % lasname)
return 1
las_file = laspy.file.File(lasname, mode='r')
nx = int((x_max - x_min) / cell_size)
ny = int((y_max - y_min) / cell_size)
ds_grid = gdal.GetDriverByName('GTiff').Create(outname, nx, ny, 1,
gdal.GDT_Float32)
georef = (x_min, cell_size, 0, y_max, 0, -cell_size)
ds_grid.SetGeoTransform(georef)
band = ds_grid.GetRasterBand(1)
band.SetNoDataValue(ND_VAL)
# make local copies so we don't have to call the x and y getter functions
# of las_file a nx*ny times
xs = las_file.x
ys = las_file.y
# determine densities
den_grid = np.ndarray(shape=(nx, ny), dtype=float)
for i in range(nx):
for j in range(ny):
I = np.ones(las_file.header.count, dtype=bool)
if i < nx - 1:
I &= np.logical_and(xs >= x_min + i * cell_size,
xs < x_min + (i + 1) * cell_size)
else:
I &= np.logical_and(xs >= x_min + i * cell_size,
xs <= x_min + (i + 1) * cell_size)
if j < ny - 1:
I &= np.logical_and(ys >= y_min + j * cell_size,
ys < y_min + (j + 1) * cell_size)
else:
I &= np.logical_and(ys >= y_min + j * cell_size,
ys <= y_min + (j + 1) * cell_size)
den_grid[ny - j - 1][i] = np.sum(I) / (cell_size * cell_size)
band.WriteArray(den_grid)
las_file.close()
t1 = time.clock()
if pargs.lakesql is None and pargs.seasql is None:
print('No layer selection specified!')
print(
'Assuming that all water polys are in first layer of connection...'
)
lake_mask = vector_io.burn_vector_layer(
waterconnection,
georef,
den_grid.shape,
None,
None,
)
else:
lake_mask = np.zeros(den_grid.shape, dtype=np.bool)
if pargs.lakesql is not None:
print("Burning lakes...")
lake_mask |= vector_io.burn_vector_layer(
waterconnection,
georef,
den_grid.shape,
None,
pargs.lakesql,
)
if pargs.seasql is not None:
print("Burning sea...")
lake_mask |= vector_io.burn_vector_layer(
waterconnection,
georef,
den_grid.shape,
None,
pargs.seasql,
)
t2 = time.clock()
print("Burning 'water' took: %.3f s" % (t2 - t1))
# what to do with nodata??
nd_mask = (den_grid == ND_VAL)
den_grid[den_grid == ND_VAL] = 0
n_lake = lake_mask.sum()
print("Number of no-data densities: %d" % (nd_mask.sum()))
print("Number of water cells : %d" % (n_lake))
if n_lake < den_grid.size:
not_lake = den_grid[np.logical_not(lake_mask)]
den = not_lake.min()
mean_den = not_lake.mean()
else:
den = ALL_LAKE
mean_den = ALL_LAKE
print("Minumum density : %.2f" % den)
wkt = constants.tilename_to_extent(kmname, return_wkt=True)
reporter.report(kmname, den, mean_den, cell_size, wkt_geom=wkt)
return 0
def main(args):
'''
Main script functionality. Can be invoked from either the command line
or via qc_wrap.py
'''
try:
pargs = parser.parse_args(args[1:])
except Exception as error_msg:
print(str(error_msg))
return 1
kmname = get_tilename(pargs.las_file)
print("Running %s on block: %s, %s" % (PROGNAME, kmname, time.asctime()))
if pargs.schema is not None:
report.set_schema(pargs.schema)
reporter = report.ReportClassCount(pargs.use_local)
pc = pointcloud.fromAny(pargs.las_file)
n_points_total = pc.get_size()
if n_points_total == 0:
print(
"Something is terribly terribly wrong here! Simon - vi skal melde en fjel"
)
pc_temp = pc.cut_to_class(constants.created_unused)
n_created_unused = pc_temp.get_size()
pc_temp = pc.cut_to_class(constants.surface)
n_surface = pc_temp.get_size()
pc_temp = pc.cut_to_class(constants.terrain)
n_terrain = pc_temp.get_size()
pc_temp = pc.cut_to_class(constants.low_veg)
n_low_veg = pc_temp.get_size()
pc_temp = pc.cut_to_class(constants.high_veg)
n_high_veg = pc_temp.get_size()
pc_temp = pc.cut_to_class(constants.med_veg)
n_med_veg = pc_temp.get_size()
pc_temp = pc.cut_to_class(constants.building)
n_building = pc_temp.get_size()
pc_temp = pc.cut_to_class(constants.outliers)
n_outliers = pc_temp.get_size()
pc_temp = pc.cut_to_class(constants.mod_key)
n_mod_key = pc_temp.get_size()
pc_temp = pc.cut_to_class(constants.water)
n_water = pc_temp.get_size()
pc_temp = pc.cut_to_class(constants.ignored)
n_ignored = pc_temp.get_size()
pc_temp = pc.cut_to_class(constants.bridge)
n_bridge = pc_temp.get_size()
# new classes
pc_temp = pc.cut_to_class(constants.high_noise)
n_high_noise = pc_temp.get_size()
pc_temp = pc.cut_to_class(constants.power_line)
n_power_line = pc_temp.get_size()
pc_temp = pc.cut_to_class(constants.terrain_in_buildings)
n_terrain_in_buildings = pc_temp.get_size()
pc_temp = pc.cut_to_class(constants.low_veg_in_buildings)
n_low_veg_in_buildings = pc_temp.get_size()
pc_temp = pc.cut_to_class(constants.man_excl)
n_man_excl = pc_temp.get_size()
polywkt = tilename_to_extent(kmname, return_wkt=True)
print(polywkt)
reporter.report(kmname,
n_created_unused,
n_surface,
n_terrain,
n_low_veg,
n_med_veg,
n_high_veg,
n_building,
n_outliers,
n_mod_key,
n_water,
n_ignored,
n_power_line,
n_bridge,
n_high_noise,
n_terrain_in_buildings,
n_low_veg_in_buildings,
n_man_excl,
n_points_total,
wkt_geom=polywkt)
def main(args):
try:
pargs = parser.parse_args(args[1:])
except Exception as e:
print(str(e))
return 1
kmname = constants.get_tilename(pargs.las_file)
print("Running %s on block: %s, %s" % (progname, kmname, time.asctime()))
lasname = pargs.las_file
polyname = pargs.poly_data
use_local = pargs.use_local
if pargs.schema is not None:
report.set_schema(pargs.schema)
reporter = report.ReportBuildingAbsposCheck(use_local)
##################################
pc = pointcloud.fromAny(lasname).cut_to_class(cut_to_classes)
try:
extent = np.asarray(constants.tilename_to_extent(kmname))
except Exception as e:
print("Could not get extent from tilename.")
extent = None
polys = vector_io.get_geometries(polyname, pargs.layername, pargs.layersql,
extent)
fn = 0
sl = "-" * 65
for poly in polys:
n_corners_found = 0
fn += 1
print("%s\nChecking feature %d\n%s\n" % (sl, fn, sl))
a_poly = array_geometry.ogrgeom2array(poly)
pcp = pc.cut_to_polygon(a_poly)
if pcp.get_size() < 500:
print("Few points in polygon...")
continue
a_poly = a_poly[0]
all_post = np.zeros_like(a_poly) #array of vertices found
all_pre = np.zeros_like(
a_poly) #array of vertices in polygon, correpsonding to found...
pcp.triangulate()
geom = pcp.get_triangle_geometry()
m = geom[:, 1].mean()
sd = geom[:, 1].std()
if (m > 1.5 or 0.5 * sd > m):
print("Feature %d, bad geometry...." % fn)
print("{} {}".format(m, sd))
continue
#geom is ok - we proceed with a buffer around da house
poly_buf = poly.Buffer(2.0)
a_poly2 = array_geometry.ogrgeom2array(poly_buf)
pcp = pc.cut_to_polygon(a_poly2)
print("Points in buffer: %d" % pcp.get_size())
pcp.triangulate()
geom = pcp.get_triangle_geometry()
tanv2 = tan(radians(cut_angle))**2
#set a mask to mark the triangles we want to consider as marking the house boundary
mask = np.logical_and(geom[:, 0] > tanv2, geom[:, 2] > z_limit)
#we consider the 'high' lying vertices - could also just select the highest of the three vertices...
p_mask = (pcp.z > pcp.z.min() + 2)
#and only consider those points which lie close to the outer bd of the house...
p_mask &= array_geometry.points_in_buffer(
pcp.xy, a_poly, 1.2) #a larger shift than 1.2 ??
#this just selects vertices where p_mask is true, from triangles where mask is true - nothing else...
bd_mask = pcp.get_boundary_vertices(mask, p_mask)
bd_pts = pcp.xy[bd_mask]
#subtract mean to get better numeric stability...
xy_t = bd_pts.mean(axis=0)
xy = bd_pts - xy_t
a_poly -= xy_t
if DEBUG:
plot_points(a_poly, xy)
#now find those corners!
lines_ok = dict()
found_lines = dict()
for vertex in range(a_poly.shape[0] -
1): #check line emanating from vertex...
p1 = a_poly[vertex]
p2 = a_poly[vertex + 1]
ok, pts = check_distribution(p1, p2, xy)
lines_ok[vertex] = (ok, pts)
#now find corners
vertex = 0 #handle the 0'th corner specially...
while vertex < a_poly.shape[0] - 2:
if lines_ok[vertex][0] and lines_ok[vertex + 1][0]: #proceed
print("%s\nCorner %d should be findable..." %
("+" * 50, vertex + 1))
corner_found = find_corner(vertex, lines_ok, found_lines,
a_poly)
all_pre[n_corners_found] = a_poly[vertex + 1]
all_post[n_corners_found] = corner_found
#print a_poly[vertex+1],corner_found,vertex
n_corners_found += 1
vertex += 1
else: #skip to next findable corner
vertex += 2
if lines_ok[0][0] and lines_ok[a_poly.shape[0] - 2][0]:
print("Corner 0 should also be findable...")
corner_found = find_corner(a_poly.shape[0] - 2, lines_ok,
found_lines, a_poly)
all_pre[n_corners_found] = a_poly[0]
all_post[n_corners_found] = corner_found
n_corners_found += 1
print("\n********** In total for feature %d:" % fn)
print("Corners found: %d" % n_corners_found)
if n_corners_found > 0:
all_post = all_post[:n_corners_found]
all_pre = all_pre[:n_corners_found]
all_dxy = all_post - all_pre
mdxy = all_dxy.mean(axis=0)
sdxy = np.std(all_dxy, axis=0)
ndxy = norm(all_dxy)
params = (1, mdxy[0], mdxy[1])
print("Mean dxy: %.3f, %.3f" % (mdxy[0], mdxy[1]))
print("Sd : %.3f, %.3f" % (sdxy[0], sdxy[1]))
print("Max absolute : %.3f m" % (ndxy.max()))
print("Mean absolute: %.3f m" % (ndxy.mean()))
if n_corners_found > 1:
print("Helmert transformation (pre to post):")
params = helmert2d(all_pre, all_post)
print("Scale: %.5f ppm" % ((params[0] - 1) * 1e6))
print("dx: %.3f m" % params[1])
print("dy: %.3f m" % params[2])
print("Residuals:")
all_post_ = params[0] * all_pre + params[1:]
all_dxy = all_post - all_post_
mdxy = all_dxy.mean(axis=0)
sdxy = np.std(all_dxy, axis=0)
ndxy = norm(all_dxy)
print("Mean dxy: %.3f, %.3f" % (mdxy[0], mdxy[1]))
print("Sd : %.3f, %.3f" % (sdxy[0], sdxy[1]))
print("Max absolute : %.3f m" % (ndxy.max()))
print("Mean absolute: %.3f m" % (ndxy.mean()))
reporter.report(kmname,
params[0],
params[1],
params[2],
n_corners_found,
ogr_geom=poly)
def run_check(p_number, testname, db_name, add_args, runid, use_local, schema,
use_ref_data, lock):
'''
Main checker rutine which should be defined for all processes.
'''
logger = multiprocessing.log_to_stderr()
test_func = qc.get_test(testname)
#Set up some globals in various modules... per process.
if runid is not None:
report.set_run_id(runid)
if use_local:
# rather than sending args to scripts, which might not have implemented
# handling that particular argument, set a global attr in report.
report.set_use_local(True)
elif schema is not None:
report.set_schema(schema)
#LOAD THE DATABASE
con = sqlite.connect(db_name)
if con is None:
logger.error(
"[qc_wrap]: Process: {0:d}, unable to fetch process db".format(
p_number))
return
cur = con.cursor()
timestamp = (time.asctime().split()[-2]).replace(':', '_')
logname = testname + '_' + timestamp + '_' + str(p_number) + '.log'
logname = os.path.join(LOGDIR, logname)
logfile = open(logname, 'w')
stdout = osutils.redirect_stdout(logfile)
stderr = osutils.redirect_stderr(logfile)
filler = '*-*' * 23
print(filler)
print(
'[qc_wrap]: Running {test} routine at {time}, process: {proc}, run id: {rid}'
.format(test=testname, time=time.asctime(), proc=p_number, rid=runid))
print(filler)
done = 0
cur.execute('select count() from ' + testname + ' where status=0')
n_left = cur.fetchone()[0]
while n_left > 0:
print(filler)
print("[qc_wrap]: Number of tiles left: {0:d}".format(n_left))
print(filler)
#Critical section#
lock.acquire()
cur.execute("select id,las_path,ref_path from " + testname +
" where status=0")
data = cur.fetchone()
if data is None:
print("[qc_wrap]: odd - seems to be no more tiles left...")
lock.release()
break
fid, lasname, vname = data
cur.execute(
"update " + testname +
" set status=?,prc_id=?,exe_start=? where id=?",
(STATUS_PROCESSING, p_number, time.asctime(), fid))
try:
con.commit()
except Exception as err_msg:
stderr.write(
"[qc_wrap]: Unable to update tile to finish status...\n" +
err_msg + "\n")
break
finally:
lock.release()
#end critical section#
print("[qc_wrap]: Doing lasfile {0:s}...".format(lasname))
send_args = [testname, lasname]
if use_ref_data:
send_args.append(vname)
send_args += add_args
try:
return_code = test_func(send_args)
except Exception as err_msg:
return_code = -1
msg = str(err_msg)
status = STATUS_ERROR
stderr.write("[qc_wrap]: Exception caught:\n" + msg + "\n")
stderr.write("[qc_wrap]: Traceback:\n" + traceback.format_exc() +
"\n")
else:
#set new status
msg = "ok"
status = STATUS_OK
try:
return_code = int(return_code)
except (NameError, ValueError, TypeError):
return_code = 0
cur.execute(
"update " + testname +
" set status=?,exe_end=?,rcode=?,msg=? where id=?",
(status, time.asctime(), return_code, msg, fid))
done += 1
try:
con.commit()
except Exception as err_msg:
stderr.write(
"[qc_wrap]: Unable to update tile to finish status...\n" +
err_msg + "\n")
#go on to next one...
cur.execute("select count() from " + testname + " where status=0")
n_left = cur.fetchone()[0]
print("[qc_wrap]: Checked %d tiles, finished at %s" %
(done, time.asctime()))
cur.close()
con.close()
#avoid writing to a closed fp...
stdout.close()
stderr.close()
logfile.close()
def main(args):
pargs = parser.parse_args(args[1:])
lasname = pargs.las_file
polyname = pargs.build_polys
kmname = constants.get_tilename(lasname)
print("Running %s on block: %s, %s" %
(os.path.basename(args[0]), kmname, time.asctime()))
use_local = pargs.use_local
if pargs.schema is not None:
report.set_schema(pargs.schema)
reporter = report.ReportRoofridgeCheck(use_local)
cut_class = pargs.cut_class
print("Using class(es): %s" % (cut_class))
# default step values for search...
steps1 = 32
steps2 = 14
search_factor = pargs.search_factor
if search_factor != 1:
# can turn search steps up or down
steps1 = int(search_factor * steps1)
steps2 = int(search_factor * steps2)
print("Incresing search factor by: %.2f" % search_factor)
print(
"Running time will increase exponentionally with search factor...")
pc = pointcloud.fromAny(lasname).cut_to_class(cut_class).cut_to_z_interval(
Z_MIN, Z_MAX)
try:
extent = np.asarray(constants.tilename_to_extent(kmname))
except Exception:
print("Could not get extent from tilename.")
extent = None
polys = vector_io.get_geometries(polyname, pargs.layername, pargs.layersql,
extent)
fn = 0
sl = "+" * 60
is_sloppy = pargs.sloppy
use_all = pargs.use_all
for poly in polys:
print(sl)
fn += 1
print("Checking feature number %d" % fn)
a_poly = array_geometry.ogrgeom2array(poly)
# secret argument to use all buildings...
if (len(a_poly) > 1 or
a_poly[0].shape[0] != 5) and (not use_all) and (not is_sloppy):
print("Only houses with 4 corners accepted... continuing...")
continue
pcp = pc.cut_to_polygon(a_poly)
# hmmm, these consts should perhaps be made more visible...
if (pcp.get_size() < 500 and (not is_sloppy)) or (pcp.get_size() < 10):
print("Few points in polygon...")
continue
# Go to a more numerically stable coord system - from now on only consider outer ring...
a_poly = a_poly[0]
xy_t = a_poly.mean(axis=0)
a_poly -= xy_t
pcp.xy -= xy_t
pcp.triangulate()
geom = pcp.get_triangle_geometry()
m = geom[:, 1].mean()
sd = geom[:, 1].std()
if (m > 1.5 or 0.5 * sd > m) and (not is_sloppy):
print("Feature %d, bad geometry...." % fn)
print(m, sd)
continue
planes = cluster(pcp, steps1, steps2)
if len(planes) < 2:
print("Feature %d, didn't find enough planes..." % fn)
pair, equation = find_planar_pairs(planes)
if pair is not None:
p1 = planes[pair[0]]
p2 = planes[pair[1]]
z1 = p1[0] * pcp.xy[:, 0] + p1[1] * pcp.xy[:, 1] + p1[2]
z2 = p2[0] * pcp.xy[:, 0] + p2[1] * pcp.xy[:, 1] + p2[2]
print("%s" % ("*" * 60))
print("Statistics for feature %d" % fn)
if DEBUG:
plot3d(pcp.xy, pcp.z, z1, z2)
intersections, distances, rotations = get_intersections(
a_poly, equation)
if intersections.shape[0] == 2:
line_x = intersections[:, 0]
line_y = intersections[:, 1]
z_vals = p1[0] * intersections[:, 0] + p1[
1] * intersections[:, 1] + p1[2]
if abs(z_vals[0] - z_vals[1]) > 0.01:
print("Numeric instabilty for z-calculation...")
z_val = float(np.mean(z_vals))
print("Z for intersection is %.2f m" % z_val)
if abs(equation[1]) > 1e-3:
a = -equation[0] / equation[1]
b = equation[2] / equation[1]
line_y = a * line_x + b
elif abs(equation[0]) > 1e-3:
a = -equation[1] / equation[0]
b = equation[2] / equation[0]
line_x = a * line_y + b
if DEBUG:
plot_intersections(a_poly, intersections, line_x, line_y)
# transform back to real coords
line_x += xy_t[0]
line_y += xy_t[1]
wkt = "LINESTRING(%.3f %.3f %.3f, %.3f %.3f %.3f)" % (
line_x[0], line_y[0], z_val, line_x[1], line_y[1], z_val)
print("WKT: %s" % wkt)
reporter.report(kmname,
rotations[0],
distances[0],
distances[1],
wkt_geom=wkt)
else:
print(
"Hmmm - something wrong, didn't get exactly two intersections..."
)
def main(args):
try:
pargs = parser.parse_args(args[1:])
except Exception as e:
print(str(e))
return 1
kmname = constants.get_tilename(pargs.las_file)
print("Running %s on block: %s, %s" % (progname, kmname, time.asctime()))
lasname = pargs.las_file
pointname = pargs.ref_data
use_local = pargs.use_local
if pargs.schema is not None:
report.set_schema(pargs.schema)
reporter = report.ReportZcheckAbs(use_local)
try:
extent = np.asarray(constants.tilename_to_extent(kmname))
except Exception as e:
print("Could not get extent from tilename.")
extent = None
pc_ref = None #base reference pointcloud
pc_refs = [] #list of possibly 'cropped' pointclouds...
if pargs.multipoints:
ftype = "multipoints"
explode = False
elif pargs.lines:
ftype = "lines"
explode = True
geoms = vector_io.get_geometries(pointname,
pargs.layername,
pargs.layersql,
extent,
explode=explode)
for geom in geoms:
xyz = array_geometry.ogrgeom2array(geom, flatten=False)
if xyz.shape[0] > 0:
pc_refs.append(pointcloud.Pointcloud(xyz[:, :2], xyz[:, 2]))
print("Found %d non-empty geometries" % len(pc_refs))
if len(pc_refs) == 0:
print("No input geometries in intersection...")
if pargs.ftype is not None:
ftype = pargs.ftype
cut_input_to = pargs.cut_to
print("Cutting input pointcloud to class %d" % cut_input_to)
pc = pointcloud.fromAny(lasname).cut_to_class(
cut_input_to) #what to cut to here...??
#warping loop here....
if (pargs.toE):
geoid = grid.fromGDAL(GEOID_GRID, upcast=True)
print("Using geoid from %s to warp to ellipsoidal heights." %
GEOID_GRID)
for i in range(len(pc_refs)):
toE = geoid.interpolate(pc_refs[i].xy)
M = (toE == geoid.nd_val)
if (M.any()):
print(
"Warping to ellipsoidal heights produced no-data values!")
M = np.logical_not(M)
toE = toE[M]
pc_refs[i] = pc_refs[i].cut(M)
pc_refs[i].z += toE
#Remove empty pointsets
not_empty = []
for pc_r in pc_refs:
if pc_r.get_size() > 0:
not_empty.append(pc_r) #dont worry, just a pointer...
else:
raise Warning("Empty input set...")
print("Checking %d point sets" % len(not_empty))
#Loop over strips#
for id in pc.get_pids():
print("%s\n" % ("+" * 70))
print("Strip id: %d" % id)
pc_c = pc.cut_to_strip(id)
if pc_c.get_size() < 50:
print("Not enough points...")
continue
might_intersect = []
for i, pc_r in enumerate(not_empty):
if pc_c.might_overlap(pc_r):
might_intersect.append(i)
if len(might_intersect) == 0:
print("Strip does not intersect any point 'patch'...")
continue
pc_c.triangulate()
pc_c.calculate_validity_mask(angle_tolerance, xy_tolerance,
z_tolerance)
#now loop over the patches which might intersect this strip...
any_checked = False
for i in might_intersect:
pc_r = not_empty[i].cut_to_box(*(pc_c.get_bounds()))
if pc_r.get_size == 0:
continue
any_checked = True
print("Stats for check of 'patch/set' %d against strip %d:" %
(i, id))
stats = check_points(pc_c, pc_r)
if stats is None:
print("Not enough points in proper triangles...")
continue
m, sd, n = stats
cm_x, cm_y = pc_r.xy.mean(axis=0)
cm_z = pc_r.z.mean()
print("Center of mass: %.2f %.2f %.2f" % (cm_x, cm_y, cm_z))
cm_geom = ogr.Geometry(ogr.wkbPoint25D)
cm_geom.SetPoint(0, cm_x, cm_y, cm_z)
#what geometry should be reported, bounding box??
reporter.report(kmname, id, ftype, m, sd, n, ogr_geom=cm_geom)
if not any_checked:
print("Strip did not intersect any point 'patch'...")
def main(args):
pargs = parser.parse_args(args[1:])
lasname = pargs.las_file
use_local = pargs.use_local
if pargs.schema is not None:
report.set_schema(pargs.schema)
if pargs.height is not None:
reporter = report.ReportClouds(use_local)
CS = 4
CELL_COUNT_LIM = 4
else:
reporter = report.ReportAutoBuilding(use_local)
CS = 1
CELL_COUNT_LIM = 2
kmname = constants.get_tilename(lasname)
print("Running %s on block: %s, %s" %
(os.path.basename(args[0]), kmname, time.asctime()))
try:
xul, yll, xlr, yul = constants.tilename_to_extent(kmname)
except Exception as e:
print("Exception: %s" % str(e))
print("Bad 1km formatting of las file name: %s" % lasname)
return 1
if pargs.height is not None:
print("Cutting to z above %.2f m" % (pargs.height))
pc = pointcloud.fromAny(lasname).cut_to_z_interval(
pargs.height, default_max_z)
else:
print("Cutting to class %d" % pargs.cut_to)
pc = pointcloud.fromAny(lasname).cut_to_class(pargs.cut_to)
if pc.get_size() == 0:
print("No points after restriction...")
return 0
cs = CS
ncols = TILE_SIZE // cs
nrows = ncols
georef = [xul, cs, 0, yul, 0, -cs]
arr_coords = ((pc.xy - (georef[0], georef[3])) /
(georef[1], georef[5])).astype(np.int32)
M = np.logical_and(arr_coords[:, 0] >= 0, arr_coords[:, 0] < ncols)
M &= np.logical_and(arr_coords[:, 1] >= 0, arr_coords[:, 1] < nrows)
arr_coords = arr_coords[M]
# Wow - this gridding is sooo simple! and fast!
#create flattened index
B = arr_coords[:, 1] * ncols + arr_coords[:, 0]
bins = np.arange(0, ncols * nrows + 1)
h, b = np.histogram(B, bins)
print("{} {} {}".format(h.shape, h.max(), h.min()))
h = h.reshape((nrows, ncols))
if DEBUG:
plt.imshow(h)
plt.show()
M = (h >= CELL_COUNT_LIM).astype(np.uint8)
#Now create a GDAL memory raster
mem_driver = gdal.GetDriverByName("MEM")
mask_ds = mem_driver.Create("dummy", int(M.shape[1]), int(M.shape[0]), 1,
gdal.GDT_Byte)
mask_ds.SetGeoTransform(georef)
mask_ds.GetRasterBand(1).WriteArray(M) #write zeros to output
#Ok - so now polygonize that - use the mask as ehem... mask...
m_drv = ogr.GetDriverByName("Memory")
ds = m_drv.CreateDataSource("dummy")
if ds is None:
print("Creation of output ds failed.\n")
return
lyr = ds.CreateLayer("polys", None, ogr.wkbPolygon)
fd = ogr.FieldDefn(dst_fieldname, ogr.OFTInteger)
lyr.CreateField(fd)
dst_field = 0
print("Polygonizing.....")
gdal.Polygonize(mask_ds.GetRasterBand(1), mask_ds.GetRasterBand(1), lyr,
dst_field)
lyr.ResetReading()
nf = lyr.GetFeatureCount()
for i in range(nf):
fet = lyr.GetNextFeature()
geom = fet.GetGeometryRef()
reporter.report(kmname, ogr_geom=geom)
return 0
def main(args):
'''
Run road delta check. Invoked from either command line or qc_wrap.py
'''
pargs = parser.parse_args(args[1:])
lasname = pargs.las_file
linename = pargs.lines
kmname = constants.get_tilename(lasname)
print("Running %s on block: %s, %s" %
(os.path.basename(args[0]), kmname, time.asctime()))
if pargs.schema is not None:
report.set_schema(pargs.schema)
reporter = report.ReportDeltaRoads(pargs.use_local)
cut_class = pargs.cut_class
pc = pointcloud.fromAny(lasname).cut_to_class(cut_class)
if pc.get_size() < 5:
print("Too few points to bother..")
return 1
pc.triangulate()
geom = pc.get_triangle_geometry()
print("Using z-steepnes limit {0:.2f} m".format(pargs.zlim))
mask = np.logical_and(geom[:, 1] < XY_MAX, geom[:, 2] > pargs.zlim)
geom = geom[mask] # save for reporting
if not mask.any():
print("No steep triangles found...")
return 0
# only the centers of the interesting triangles
centers = pc.triangulation.get_triangle_centers()[mask]
print("{0:d} steep triangles in tile.".format(centers.shape[0]))
try:
extent = np.asarray(constants.tilename_to_extent(kmname))
except Exception:
print("Could not get extent from tilename.")
extent = None
lines = vector_io.get_geometries(linename, pargs.layername, pargs.layersql,
extent)
feature_count = 0
for line in lines:
xy = array_geometry.ogrline2array(line, flatten=True)
if xy.shape[0] == 0:
print("Seemingly an unsupported geometry...")
continue
# select the triangle centers which lie within line_buffer of the road segment
mask = array_geometry.points_in_buffer(centers, xy, LINE_BUFFER)
critical = centers[mask]
print("*" * 50)
print("{0:d} steep centers along line {1:d}".format(
critical.shape[0], feature_count))
feature_count += 1
if critical.shape[0] > 0:
z_box = geom[mask][:, 2]
z1 = z_box.max()
z2 = z_box.min()
wkt = "MULTIPOINT("
for point in critical:
wkt += "{0:.2f} {1:.2f},".format(point[0], point[1])
wkt = wkt[:-1] + ")"
reporter.report(kmname, z1, z2, wkt_geom=wkt)
con.commit()
continue
testname,schema,runid,targs=data
logger.info("Was told to do job with id %s, test %s, on data (%s,%s)" %(job_id,testname,path,ref_path))
#now just run the script.... hmm - perhaps import with importlib and run it??
stdout.write(sl+"[proc_client] Doing definition %s from %s, test: %s\n"%(job_id,db_cstr,testname))
args={"__name__":"qc_wrap","path":path}
try:
targs=json.loads(targs) #convert to a python list
test_func=qc.get_test(testname)
use_ref_data=qc.tests[testname][0]
use_reporting=qc.tests[testname][1]
#both of these can be None - but that's ok.
if use_reporting:
report.set_run_id(runid)
report.set_schema(schema)
send_args=[testname,path]
if use_ref_data:
assert(len(ref_path)>0)
send_args.append(ref_path)
send_args+=targs
rc=test_func(send_args)
except Exception,e:
stderr.write("[proc_client]: Exception caught:\n"+str(e)+"\n")
stderr.write("[proc_client]: Traceback:\n"+traceback.format_exc()+"\n")
logger.error("Caught: \n"+str(e))
msg=str(e)[:128] #truncate msg for now - or use larger field width.
cur.execute("update proc_jobs set status=%s,msg=%s where ogc_fid=%s",(STATUS_ERROR,msg,id))
con.commit()
else:
def main(args):
try:
pargs = parser.parse_args(args[1:])
except Exception as e:
print(str(e))
return 1
kmname = constants.get_tilename(pargs.las_file)
print("Running %s on block: %s, %s" % (progname, kmname, time.asctime()))
lasname = pargs.las_file
polyname = pargs.poly_data
use_local = pargs.use_local
if pargs.schema is not None:
report.set_schema(pargs.schema)
reporter = report.ReportBuildingRelposCheck(use_local)
##################################
pc = pointcloud.fromAny(lasname).cut_to_z_interval(
-10, 200).cut_to_class(cut_to_classes)
try:
extent = np.asarray(constants.tilename_to_extent(kmname))
except Exception as e:
print("Could not get extent from tilename.")
extent = None
polys = vector_io.get_geometries(polyname)
fn = 0
sl = "-" * 65
pcs = dict()
for id in pc.get_pids():
print("%s\n" % ("+" * 70))
print("Strip id: %d" % id)
pc_ = pc.cut_to_strip(id)
if pc_.get_size() > 500:
pcs[id] = pc_
else:
print("Not enough points....")
del pc
done = []
for id1 in pcs:
pc1 = pcs[id1]
for id2 in pcs:
if id1 == id2 or (id1, id2) in done or (id2, id1) in done:
continue
done.append((id1, id2))
pc2 = pcs[id2]
ml = "-" * 70
print("%s\nChecking strip %d against strip %d\n%s" %
(ml, id1, id2, ml))
if not pc1.might_overlap(pc2):
if DEBUG:
print(
"Strip %d and strip %d does not seem to overlap. Continuing..."
% (id1, id2))
print("DEBUG: Strip1 bounds:\n%s\nStrip2 bounds:\n%s" %
(pc1.get_bounds(), pc2.get_bounds()))
continue
for poly in polys:
centroid = poly.Centroid()
centroid.FlattenTo2D()
if LIGHT_DEBUG:
print("Geom type: %s" % centroid.GetGeometryName())
n_corners_found = 0
fn += 1
print("%s\nChecking feature %d\n%s\n" % (sl, fn, sl))
a_poly = array_geometry.ogrgeom2array(poly)
pcp1 = pc1.cut_to_polygon(a_poly)
if pcp1.get_size() < 300:
print("Few (%d) points in polygon..." % pcp1.get_size())
continue
pcp2 = pc2.cut_to_polygon(a_poly)
if pcp2.get_size() < 300:
print("Few (%d) points in polygon..." % pcp2.get_size())
continue
a_poly = a_poly[0]
poly_buf = poly.Buffer(2.0)
xy_t = a_poly.mean(
axis=0
) #transform later to center of mass system for numerical stability...
#transform a_poly coords to center of mass system here
a_poly -= xy_t
a_poly2 = array_geometry.ogrgeom2array(poly_buf)
#dicts to store the found corners in the two strips...
found1 = dict()
found2 = dict()
for pc, pcp, store in [(pc1, pcp1, found1),
(pc2, pcp2, found2)]:
pcp.triangulate()
geom = pcp.get_triangle_geometry()
m = geom[:, 1].mean()
sd = geom[:, 1].std()
if (m > 1.5 or 0.5 * sd > m):
print("Feature %d, bad geometry...." % fn)
print("{} {}".format(m, sd))
break
#geom is ok - we proceed with a buffer around da house
pcp = pc.cut_to_polygon(a_poly2)
######
## Transform pointcloud to center of mass system here...
#######
pcp.xy -= xy_t
print("Points in buffer: %d" % pcp.get_size())
pcp.triangulate()
geom = pcp.get_triangle_geometry()
tanv2 = tan(radians(cut_angle))**2
#set a mask to mark the triangles we want to consider as marking the house boundary
mask = np.logical_and(geom[:, 0] > tanv2,
geom[:, 2] > z_limit)
#we consider the 'high' lying vertices - could also just select the highest of the three vertices...
p_mask = (pcp.z > pcp.z.min() + 2)
#and only consider those points which lie close to the outer bd of the house...
p_mask &= array_geometry.points_in_buffer(
pcp.xy, a_poly, 1.2) #a larger shift than 1.2 ??
#this just selects vertices where p_mask is true, from triangles where mask is true - nothing else...
bd_mask = pcp.get_boundary_vertices(mask, p_mask)
xy = pcp.xy[bd_mask]
print("Boundary points: %d" % xy.shape[0])
if DEBUG:
plot_points(a_poly, xy)
#now find those corners!
lines_ok = dict()
found_lines = dict()
for vertex in range(
a_poly.shape[0] -
1): #check line emanating from vertex...
p1 = a_poly[vertex]
p2 = a_poly[vertex + 1]
ok, pts = check_distribution(p1, p2, xy)
lines_ok[vertex] = (ok, pts)
#now find corners
vertex = 0 #handle the 0'th corner specially...
while vertex < a_poly.shape[0] - 2:
if lines_ok[vertex][0] and lines_ok[vertex +
1][0]: #proceed
print("%s\nCorner %d should be findable..." %
("+" * 50, vertex + 1))
corner_found = find_corner(vertex, lines_ok,
found_lines, a_poly)
diff = norm2(a_poly[vertex + 1] - corner_found)
if (
diff < TOL_CORNER
): #seems reasonable that this is a true corner...
store[vertex + 1] = corner_found
n_corners_found += 1
#print a_poly[vertex+1],corner_found,vertex
vertex += 1
else: #skip to next findable corner
vertex += 2
if lines_ok[0][0] and lines_ok[a_poly.shape[0] - 2][0]:
print("Corner 0 should also be findable...")
corner_found = find_corner(a_poly.shape[0] - 2,
lines_ok, found_lines,
a_poly)
diff = norm2(a_poly[0] - corner_found)
if (diff < TOL_CORNER
): #seems reasonable that this is a true corner...
store[0] = corner_found
n_corners_found += 1
print("Corners found: %d" % n_corners_found)
if n_corners_found == 0: #no need to do another check...
break
print(
"Found %d corners in strip %d, and %d corners in strip %d"
% (len(found1), id1, len(found2), id2))
if len(found1) > 0 and len(found2) > 0:
match1 = []
match2 = []
for cn in found1:
if cn in found2:
match1.append(found1[cn])
match2.append(found2[cn])
if len(match1) > 0:
match1 = np.array(match1)
match2 = np.array(match2)
n_corners_found = match1.shape[0]
print("\n********** In total for feature %d:" % fn)
print("Corners found in both strips: %d" %
n_corners_found)
all_dxy = match1 - match2
mdxy = all_dxy.mean(axis=0)
sdxy = np.std(all_dxy, axis=0)
ndxy = norm(all_dxy)
params = (1, mdxy[0], mdxy[1])
print("Mean dxy: %.3f, %.3f" % (mdxy[0], mdxy[1]))
print("Sd : %.3f, %.3f" % (sdxy[0], sdxy[1]))
print("Max absolute : %.3f m" % (ndxy.max()))
print("Mean absolute: %.3f m" % (ndxy.mean()))
if n_corners_found > 1:
print(
"Helmert transformation (corners1 to corners2):"
)
params = helmert2d(match1, match2) #2->1 or 1->2 ?
print("Scale: %.5f ppm" % ((params[0] - 1) * 1e6))
print("dx: %.3f m" % params[1])
print("dy: %.3f m" % params[2])
print("Residuals:")
match2_ = params[0] * match1 + params[1:]
all_dxy = match2_ - match2
mdxy_ = all_dxy.mean(axis=0)
sdxy_ = np.std(all_dxy, axis=0)
ndxy_ = norm(all_dxy)
if DEBUG or LIGHT_DEBUG:
plot3([match1, match2, match2_])
#center of mass distances only!!
cm_vector = (match2.mean(axis=0) -
match1.mean(axis=0))
cm_dist = norm2(cm_vector)
print("Mean dxy: %.3f, %.3f" %
(mdxy_[0], mdxy_[1]))
print("Sd : %.3f, %.3f" %
(sdxy_[0], sdxy_[1]))
print("Max absolute : %.3f m" % (ndxy_.max()))
print("Mean absolute: %.3f m" % (ndxy_.mean()))
reporter.report(kmname,
id1,
id2,
cm_vector[0],
cm_vector[1],
cm_dist,
params[0],
params[1],
params[2],
sdxy_[0],
sdxy_[1],
n_corners_found,
ogr_geom=centroid)
def run_check(p_number, testname, db_name, add_args, runid, use_local, schema,
use_ref_data, lock):
'''
Main checker rutine which should be defined for all processes.
'''
logger = multiprocessing.log_to_stderr()
test_func = qc.get_test(testname)
#Set up some globals in various modules... per process.
if runid is not None:
report.set_run_id(runid)
if use_local:
# rather than sending args to scripts, which might not have implemented
# handling that particular argument, set a global attr in report.
report.set_use_local(True)
elif schema is not None:
report.set_schema(schema)
#LOAD THE DATABASE
con = sqlite.connect(db_name)
if con is None:
logger.error(
"[qc_wrap]: Process: {0:d}, unable to fetch process db".format(
p_number))
return
cur = con.cursor()
timestamp = (time.asctime().split()[-2]).replace(':', '_')
logname = testname + '_' + timestamp + '_' + str(p_number) + '.log'
logname = os.path.join(LOGDIR, logname)
logfile = open(logname, 'w')
stdout = osutils.redirect_stdout(logfile)
stderr = osutils.redirect_stderr(logfile)
filler = '*-*' * 23
print(filler)
print(
'[qc_wrap]: Running {test} routine at {time}, process: {proc}, run id: {rid}'
.format(test=testname, time=time.asctime(), proc=p_number, rid=runid))
print(filler)
done = 0
cur.execute('select count() from ' + testname + ' where status=0')
n_left = cur.fetchone()[0]
while n_left > 0:
print(filler)
print("[qc_wrap]: Number of tiles left: {0:d}".format(n_left))
print(filler)
#Critical section#
lock.acquire()
cur.execute("select id,las_path,ref_path from " + testname +
" where status=0")
data = cur.fetchone()
if data is None:
print("[qc_wrap]: odd - seems to be no more tiles left...")
lock.release()
break
fid, lasname, vname = data
cur.execute(
"update " + testname +
" set status=?,prc_id=?,exe_start=? where id=?",
(STATUS_PROCESSING, p_number, time.asctime(), fid))
try:
con.commit()
except Exception, err_msg:
stderr.write(
"[qc_wrap]: Unable to update tile to finish status...\n" +
err_msg + "\n")
break
finally:
def main(args):
pargs = parser.parse_args(args[1:])
lasname = pargs.las_file
polyname = pargs.build_polys
kmname = constants.get_tilename(lasname)
print("Running %s on block: %s, %s" % (os.path.basename(args[0]), kmname, time.asctime()))
if pargs.schema is not None:
report.set_schema(pargs.schema)
reporter = report.ReportRoofridgeStripCheck(pargs.use_local)
cut_class = pargs.cut_class
# default step values for search...
steps1 = 30
steps2 = 13
search_factor = pargs.search_factor
if search_factor != 1:
# can turn search steps up or down
steps1 = int(search_factor * steps1)
steps2 = int(search_factor * steps2)
print("Incresing search factor by: %.2f" % search_factor)
print("Running time will increase exponentionally with search factor...")
pc = pointcloud.fromAny(lasname).cut_to_class(cut_class).cut_to_z_interval(Z_MIN, Z_MAX)
try:
extent = np.asarray(constants.tilename_to_extent(kmname))
except Exception:
print("Could not get extent from tilename.")
extent = None
polys = vector_io.get_geometries(polyname, pargs.layername, pargs.layersql, extent)
fn = 0
sl = "+" * 60
is_sloppy = pargs.sloppy
use_all = pargs.use_all
for poly in polys:
print(sl)
fn += 1
print("Checking feature number %d" % fn)
a_poly = array_geometry.ogrgeom2array(poly)
# secret argument to use all buildings...
if (len(a_poly) > 1 or a_poly[0].shape[0] != 5) and (not use_all) and (not is_sloppy):
print("Only houses with 4 corners accepted... continuing...")
continue
pcp = pc.cut_to_polygon(a_poly)
strips = pcp.get_pids()
if len(strips) != 2:
print("Not exactly two overlapping strips... continuing...")
continue
# Go to a more numerically stable coord system - from now on only consider outer ring...
a_poly = a_poly[0]
xy_t = a_poly.mean(axis=0) # center of mass system
a_poly -= xy_t
lines = [] # for storing the two found lines...
for sid in strips:
print("-*-" * 15)
print("Looking at strip %d" % sid)
pcp_ = pcp.cut_to_strip(sid)
# hmmm, these consts should perhaps be made more visible...
if (pcp_.get_size() < 500 and (not is_sloppy)) or (pcp_.get_size() < 10):
print("Few points in polygon... %d" % pcp_.get_size())
continue
pcp_.xy -= xy_t
pcp_.triangulate()
geom = pcp_.get_triangle_geometry()
m = geom[:, 1].mean()
sd = geom[:, 1].std()
if (m > 1.5 or 0.5 * sd > m) and (not is_sloppy):
print("Feature %d, strip %d, bad geometry...." % (fn, sid))
break
planes = cluster(pcp_, steps1, steps2)
if len(planes) < 2:
print("Feature %d, strip %d, didn't find enough planes..." % (fn, sid))
pair, equation = find_planar_pairs(planes)
if pair is not None:
p1 = planes[pair[0]]
print("%s" % ("*" * 60))
print("Statistics for feature %d" % fn)
# Now we need to find some points on the line near the house... (0,0) is
# the center of mass
norm_normal = equation[0]**2 + equation[1]**2
if norm_normal < 1e-10:
print("Numeric instablity, small normal")
break
# this should be on the line
cm_line = np.asarray(equation[:2]) * (equation[2] / norm_normal)
line_dir = np.asarray((-equation[1], equation[0])) / (sqrt(norm_normal))
end1 = cm_line + line_dir * LINE_RAD
end2 = cm_line - line_dir * LINE_RAD
intersections = np.vstack((end1, end2))
line_x = intersections[:, 0]
line_y = intersections[:, 1]
z_vals = p1[0] * intersections[:, 0] + p1[1] * intersections[:, 1] + p1[2]
if abs(z_vals[0] - z_vals[1]) > 0.01:
print("Numeric instabilty for z-calculation...")
z_val = float(np.mean(z_vals))
print("Z for intersection is %.2f m" % z_val)
# transform back to real coords
line_x += xy_t[0]
line_y += xy_t[1]
wkt = "LINESTRING(%.3f %.3f %.3f, %.3f %.3f %.3f)" % (
line_x[0], line_y[0], z_val, line_x[1], line_y[1], z_val)
print("WKT: %s" % wkt)
lines.append([sid, wkt, z_val, cm_line, line_dir])
if len(lines) == 2:
# check for parallelity
id1 = lines[0][0]
id2 = lines[1][0]
z1 = lines[0][2]
z2 = lines[1][2]
if abs(z1 - z2) > 0.5:
print("Large difference in z-values for the two lines!")
else:
ids = "{0:d}_{1:d}".format(id1, id2)
inner_prod = (lines[0][4] * lines[1][4]).sum()
inner_prod = max(-1, inner_prod)
inner_prod = min(1, inner_prod)
if DEBUG:
print("Inner product: %.4f" % inner_prod)
ang = abs(degrees(acos(inner_prod)))
if ang > 175:
ang = abs(180 - ang)
if ang < 15:
v = (lines[0][3] - lines[1][3])
d = np.sqrt((v**2).sum())
if d < 5:
for line in lines:
reporter.report(kmname, id1, id2, ids, d, ang,
line[2], wkt_geom=line[1])
else:
print("Large distance between centers %s, %s, %.2f" %
(lines[0][3], lines[1][3], d))
else:
print("Pair found - but not very well aligned - angle: %.2f" % ang)
else:
print("Pair not found...")
