def _kml_shp_2_bb(self, filename):
# from kml and shape file to a bounding box. We will always use a bounding box to create the final product.
if filename.endswith('.shp'):
with collection(filename, "r") as inputshape:
shapes = [shape for shape in inputshape]
# only first shape
dat = shapes[0]['geometry']['coordinates']
lon = [l[0] for l in dat[0]]
lat = [l[1] for l in dat[0]]
latlim = [min(lat), max(lat)]
lonlim = [min(lon), max(lon)]
elif filename.endswith('.kml'):
doc = file(filename).read()
k = fastkml.KML()
k.from_string(doc)
dat = list(list(k.features())[0].features())[0].geometry[0].exterior.coords[:]
lon = [l[0] for l in dat[0]]
lat = [l[1] for l in dat[0]]
latlim = [min(lat), max(lat)]
lonlim = [min(lon), max(lon)]
else:
print 'format not recognized! Pleas creat either a .kml or .shp file.'
return []
return latlim, lonlim
def convert_gsientries_to_kml(entries: List[GSIEntry]) -> fastkml.KML: # # Boilerplate for creating a new KML doc. kml = fastkml.KML() d = fastkml.Document() kml.append(d) s = fastkml.Style(id=style_id) d.append_style(s) s.append_style(fastkml.LineStyle(color="Af00ffff", width=6)) s.append_style(fastkml.PolyStyle(color="7f00ff00")) p = fastkml.Placemark() d.append(p) p.styleUrl = "#" + style_id g = fastkml.geometry.Geometry( extrude=True, tessellate=True, altitude_mode="relativeToGround", ) g.geometry = fastkml.geometry.LineString([ (entry.longitude, entry.latitude, entry.speed) for entry in entries ]) p.geometry = g return kml
def __init__(self) -> None:
self.kml = K.KML()
self.doc = K.Document(
ns=KmlMaker.NS,
id='docid',
name=f'foursquare-{datetime.now().strftime("%Y%m%d")}',
description='Foursquare lists',
)
self.color2style: Dict[str, str] = {}
self.kml.append(self.doc)
def load_geo_images_list(kml_path='.'):
import fastkml, shapely
def process_KML_feature(e):
global geo_images
if hasattr(e, 'features'):
for f in e.features():
process_KML_feature(f)
return
if not hasattr(e, 'geometry'):
return
if not isinstance(
e.geometry,
shapely.geometry.point.Point) or not is_valid_image_id(e.name):
return
if not hasattr(e, 'description'):
return
if not e.description:
return
fields = e.description.split()
if len(fields) < 1:
return
center_azimuth_deg = float(fields[0].partition('deg')[0])
owner_uid = 0
sharing_mode = None
if len(fields) >= 2:
owner_uid = int(fields[1])
if len(fields) >= 3:
sharing_mode = fields[2]
geo_images[e.name] = tuple(e.geometry.coords[0][:2]) + (
center_azimuth_deg, owner_uid, sharing_mode)
k = fastkml.KML()
k.from_string(open(kml_path + '/images.kml', 'r').read().encode('utf-8'))
process_KML_feature(k)
def kml_poly_to_geom(kml_poly):
""" Convert KML polygon in AVIRIS kml_poly field to a shapely Geometry """
# Not all KML polygons are correct (missing LinearRing tag); grab coords directly
kmldom = minidom.parseString(
'<?xml version="1.0" encoding="UTF-8"?>' +
'<kml xmlns="http://www.opengis.net/kml/2.2"><Document><Placemark>' +
kml_poly + "</Placemark></Document></kml>")
coords = kmldom.getElementsByTagName(
"outerBoundaryIs")[0].getElementsByTagName("coordinates")[0]
kml = fastkml.KML()
kml.from_string(
'<?xml version="1.0" ?>' +
'<kml xmlns="http://www.opengis.net/kml/2.2">' +
"<Document><Placemark><Polygon><outerBoundaryIs><LinearRing>" +
coords.toxml() +
"</LinearRing></outerBoundaryIs></Polygon></Placemark></Document></kml>"
)
return next(next(kml.features()).features()).geometry
def load_streets_kml(self):
with open('{}/streets.kml'.format(self.streets_dir)) as data_file:
self.kml = fastkml.KML()
self.kml.from_string(data_file.read())
features = list(self.kml.features())
self.itemsGen = list(features)[0].features()
good_dZ[0:-1]=np.abs(np.diff(D.elevation))<0.25
good_dZ=np.convolve(good_dZ.astype(float), np.ones(3), mode='same')==3
xx=np.unique(np.round(D.longitude/.001)+1j*np.round(D.latitude/.001))
D1=pc.data().from_dict({'latitude': np.imag(xx)/1000, 'longitude':np.real(xx)/1000-360})
D_filt=D[good_dZ]
D_nonscat=D_filt[D_filt.K0==0]
D_scat=D_filt[D_filt.K0>0]
geoms={}
for file in ['Airstrip_outer.kml', 'Grassy_1.kml', 'Grassy_2.kml' ]:
with open(file,'rb') as ff:
doc=ff.read()
K=fastkml.KML()
K.from_string(doc)
geoms[file.replace('.kml','')] =K._features[0]._features[0].geometry
inside = [geo.Point(item[0], item[1]).within(geoms['Airstrip_outer']) for item in zip(D_filt.longitude, D_filt.latitude)]
plt.figure(1);
plt.clf()
plt.plot(D_nonscat.x, D_nonscat.y,'k.', markersize=2, zorder=0)
ii=np.argsort(D_scat.K0)
plt.scatter(D_scat.x[ii], D_scat.y[ii], 2, c=np.log10(D_scat.K0[ii]), vmin=-4.5, vmax=-3, zorder=1);
hb=plt.colorbar()
hb.set_label('log $r_{eff}$, m')
from psycopg2.extras import execute_values
import fastkml as fk
import shapely.wkt
from shapely.geometry.point import Point
import sys
if len(sys.argv) < 3:
print("Usage: python load_takeout.py <userid> <Location History.json>")
sys.exit(1)
userid, location_file = sys.argv[1], sys.argv[2]
print(f"Loading {location_file} data for userid {userid}")
conn = psycopg2.connect("dbname=covid19 user=covid19 port=5434\
password=covid19databasepassword host=localhost")
k = fk.KML()
k.from_string(open(location_file).read())
doc = list(k.features())[0]
values = []
cur = conn.cursor()
for point in doc.features():
if type(point.geometry) != shapely.geometry.point.Point:
continue
start = point.begin.strftime('%Y-%m-%dT%H:%M:%S')
end = point.end.strftime('%Y-%m-%dT%H:%M:%S')
print(point.address, '|', point.name, '|',
point.begin.strftime('%Y-%m-%dT%H:%M:%S'),
point.end.strftime('%Y-%m-%dT%H:%M:%S'), point.geometry)
geopoint = Point(point.geometry.x, point.geometry.y)
geo = shapely.wkt.dumps(geopoint)
geopoint = f"SRID=4326;{geo}"