def extract_kml(self):
kml = fastkml.kml.KML()
ns = '{http://www.opengis.net/kml/2.2}'
doc = fastkml.kml.Document(
ns,
'nrd-cluster-%s' % (datetime.datetime.now().strftime('%Y-%m-%d'),),
'NRC Clusters %s' % (datetime.datetime.now().strftime('%Y-%m-%d'),),
'Cluster analysis of all recent NRC reports in the gulf of mexico that indicate a release of materials into the environment.')
kml.append(doc)
self.cur.execute("truncate table appomatic_nrccluster_nrcreport")
self.cur.execute("truncate table appomatic_nrccluster_cluster")
self.cur.execute("""
insert into appomatic_nrccluster_nrcreport(
geocode_source, reportnum, incident_datetime, incidenttype, lat, lng, location)
select
geocode_source, reportnum, incident_datetime, incidenttype, lat, lng, ST_MakePoint(lng, lat)
from
"NrcReleaseIncidents"
where
region='gulf'
and extract(day from NOW()-incident_datetime) <= 366
and geocode_source = 'Explicit';
""")
for timeperiod in (None, 12*30, 6*30, 3*30):
self.extract_clusters(timeperiod, doc)
self.extract_reports(doc)
return kml.to_string(prettyprint=True)
def main():
args = get_args()
T = TracksAnalysis(*args.paths)
V = WaypointVoronoi.from_tracks(T)
if args.kml:
kml = V.to_kml(alpha=args.alpha)
if args.output:
if args.gzip:
output_kmz(kml, args.output)
else:
output_kml(kml, args.output)
else:
print(kml.to_string())
def extract_kml(name, cur, query, size, radius, periods, **kw):
kml = fastkml.kml.KML()
docname = name
if periods:
docname += ' ' + ', '.join("%s:%s" % (timeperiod[0].strftime("%Y-%m-%d"), timeperiod[1].strftime("%Y-%m-%d"))
for timeperiod in periods)
doc = fastkml.kml.Document(KMLNS, django.template.defaultfilters.slugify(docname), docname, '')
kml.append(doc)
for timeperiod in periods:
extract_clusters_kml(cur, query, size, radius, timeperiod, doc, **kw)
extract_reports_kml(cur, query, periods, doc)
return kml.to_string(prettyprint=True)
def extract_kml(self):
kml = fastkml.kml.KML()
ns = '{http://www.opengis.net/kml/2.2}'
doc = fastkml.kml.Document(ns, 'regions', 'Regions', 'Region names and codes used by SkyTruth')
kml.append(doc)
self.cur.execute("""
select
distinct src
from
region
""")
srcs = [row[0] for row in self.cur]
for src in srcs:
folder = fastkml.kml.Folder('{http://www.opengis.net/kml/2.2}', src, src)
doc.append(folder)
self.cur.execute("""
select
src,
name,
code,
ST_AsText(the_geom) as the_geom
from
region
where
src = %(src)s
""", {'src': src})
for row in dictreader(self.cur):
keys = row.keys()
keys.sort()
placemark = fastkml.kml.Placemark('{http://www.opengis.net/kml/2.2}', "%(code)s" % row, "%(name)s" % row, "%(name)s (%(code)s, from %(src)s)" % row)
placemark.geometry = shapely.wkt.loads(str(row['the_geom']))
folder.append(placemark)
return kml.to_string(prettyprint=True)
def feed(request, format):
filter = {}
limit = 50
if 'l' in request.GET or 'BBOX' in request.GET:
if 'l' in request.GET:
lat1, lng1, lat2, lng2 = [float(x) for x in request.GET['l'].split(',')]
elif 'BBOX' in request.GET:
lng1, lat1, lng2, lat2 = [float(x) for x in request.GET['BBOX'].split(',')]
filter['the_geom__contained'] = shapely.geometry.box(min(lng1, lng2), min(lat1, lat2), max(lng1, lng2), max(lat1, lat2))
if 'dates' in request.GET:
if ',' in request.GET['dates']:
start, end = request.GET['dates'].split(',')
start = datetime.datetime.strptime(start, '%Y-%m-%d')
end = datetime.datetime.strptime(end, '%Y-%m-%d')
filter['incident_datetime__gte'] = start
filter['incident_datetime__lte'] = end
else:
start = datetime.datetime.strptime(request.GET['dates'], '%Y-%m-%d')
filter['incident_datetime__gte'] = start
if 'd' in request.GET:
filter['incident_datetime__gte'] = datetime.datetime.now() - datetime.timedelta(int(request.GET['d']))
if 'tag' in request.GET:
filter['tags__array_contains'] = request.GET['tag'].split(',')
if 'n' in request.GET:
limit = int(request.GET['n'])
entries = appomatic_feedserver.models.Feedentry.objects.filter(**filter).order_by('published')[:limit]
if format == 'kml':
kml = fastkml.kml.KML()
ns = '{http://www.opengis.net/kml/2.2}'
doc = fastkml.kml.Document(ns, 'docid', 'doc name', 'doc description')
kml.append(doc)
for entry in entries:
placemark = fastkml.kml.Placemark(ns, "entry-%s" % entry.id, entry.title, entry.content)
placemark.geometry = shapely.wkt.loads(entry.the_geom.wkt) # Bah, GeoDjango does not support the geo interface :(
doc.append(placemark)
result = kml.to_string(prettyprint=True).encode('utf-8')
elif format == 'geojson':
features = []
for entry in entries:
geometry = fcdjangoutils.jsonview.from_json(
geojson.dumps(
shapely.wkt.loads(
entry.the_geom.wkt)))
feature = {"type": "Feature",
"geometry": geometry,
"properties": {'id': entry.id,
'title': entry.title,
'link': entry.link,
'summary': entry.summary,
'content': entry.content,
'source': entry.source.name,
'kml_url': entry.kml_url,
'incident_datetime': entry.incident_datetime.strftime('%Y-%m-%d %H:%M:%S'),
'published': entry.published.strftime('%Y-%m-%d %H:%M:%S'),
'regions': [{'src': region.src,
'name': region.name,
'code': region.code}
for region in appomatic_mapdata.models.Region.objects.filter(id__in = entry.regions)],
'tags': entry.tags,
'source_item_id': entry.source_item_id
}}
features.append(feature)
result = fcdjangoutils.jsonview.to_json(
{"type": "FeatureCollection",
"features": features})
elif format == 'csv':
f = StringIO.StringIO()
writer = csv.writer(f)
writer.writerow(['id',
'lat',
'lng',
'title',
'link',
'summary',
'content',
'source',
'kml_url',
'incident_datetime',
'published',
'regions',
'tags',
'source_item_id'])
for entry in entries:
writer.writerow([entry.id,
entry.lat,
entry.lng,
entry.title,
entry.link,
entry.summary,
entry.content,
entry.source.name,
entry.kml_url,
entry.incident_datetime.strftime('%Y-%m-%d %H:%M:%S'),
entry.published.strftime('%Y-%m-%d %H:%M:%S'),
','.join(region.code
for region in appomatic_mapdata.models.Region.objects.filter(id__in = entry.regions)),
','.join(entry.tags),
entry.source_item_id
])
result = f.getvalue()
elif format == 'atom':
result = django.template.loader.get_template(
'appomatic_feedserver/feed.atom'
).render(
django.template.RequestContext(
request,
{"entries": entries,
"now": datetime.datetime.now(),
"id": uuid.uuid4().urn}))
else: # elif format == 'txt':
format = 'txt'
result = '\n'.join("%(title)s @ %(lat)sN %(lng)sE, %(incident_datetime)s (%(tags)s)" % DictWrapper(entry) for entry in entries)
contentTypes = {'kml': 'application/kml', 'atom': 'application/atom+xml', 'geojson': 'application/json', 'csv': 'text/csv', 'txt': 'text/plain'}
response = django.http.HttpResponse(result, content_type=contentTypes[format])
response['Content-Disposition'] = 'attachment; filename="feed.%s"' % (format,)
return response
def output_kmz(kml, path):
with zipfile.ZipFile(path, 'w') as wzf:
wzf.writestr('doc.kml',kml.to_string())
def output_kml(kml, path):
with open(path, 'wt') as wfp:
wfp.write(kml.to_string())
