def demo3(self):
import databundles
import databundles.library as dl
import databundles.geo as dg
from matplotlib import pyplot as plt
import numpy as np
l = dl.get_library()
aa = dg.get_analysis_area(l, geoid='CG0666000')
r = l.find(dl.QueryCommand().identity(id='a2z2HM').partition(table='incidents',space=aa.geoid)).pop()
p = l.get(r.partition).partition
a = aa.new_array()
k = dg.ConstantKernel(9)
print aa
k.apply_add(a, dg.Point(400,1919))
k.apply_add(a, dg.Point(400,1920))
k.apply_add(a, dg.Point(400,1921))
k.apply_add(a, dg.Point(400,1922))
k.apply_add(a, dg.Point(400,1923))
for row in p.query("select date, time, cellx, celly from incidents"):
p = dg.Point(row['cellx'],row['celly'])
k.apply_add(a, p)
a /= np.max(a)
print np.sum(a)
img = plt.imshow(a, interpolation='nearest')
img.set_cmap('spectral_r')
plt.colorbar()
plt.show()
def get_incident_source(self):
"""Return the partition from the dataset that has the incidents"""
import databundles.library as dl
import databundles.geo as dg
l = self.library
aa = dg.get_analysis_area(l, geoid=self.config.build.aa_geoid)
r = l.find(dl.QueryCommand().identity(id='a2z2HM').partition(table='incidents',space=aa.geoid)).pop()
return aa, l.get(r.partition).partition
def _get_sub_aas(self):
import yaml
import databundles.geo as dg
import databundles.library as dl
aa = dg.get_analysis_area(dl.get_library(), geoid=self.config.build.aa_geoid)
with open(self.filesystem.path('extracts','envelopes.yaml')) as f:
envelopes = yaml.load(f)
aas = []
for r in envelopes:
saa = aa.get_aa_from_envelope(r['env'], '', '')
aas.append( (r['area'], saa))
aas = sorted(aas, cmp=lambda x,y: cmp(x[0], y[0]), reverse=True)
return [aa[1] for aa in aas]
def build_aa_map(self):
'''
'''
import databundles.library as dl
import databundles.geo as dg
import random
from numpy import ma
rs = 3
# make a helper to store files in the extracts directory
ed = lambda f: self.filesystem.path('extracts','subs',f+'.tiff')
l = dl.get_library()
aa = dg.get_analysis_area(l, geoid=self.config.build.aa_geoid)
r = l.find(dl.QueryCommand().identity(id='a2z2HM').partition(table='incidents',space=aa.geoid)).pop()
source_partition = l.get(r.partition).partition
k = dg.GaussianKernel(33,11)
sub_aas = [self.get_sub_aas()[1]]
top_a = aa.new_array()
for i, sub_aa in enumerate(sub_aas):
where = sub_aa.is_in_ll_query()
sub_a = sub_aa.new_array()
trans = sub_aa.get_translator()
q = "select * from incidents WHERE {}".format(where)
for row in source_partition.query(q):
p = trans(row['lon'],row['lat'])
k.apply_add(sub_a, p)
print row
sub_aa.write_geotiff(ed(str(i)), dg.std_norm(ma.masked_equal(sub_a,0)))
sub_aa.write_geotiff(ed(str(i)), sub_a)
return True
def extract_incident_shapefile(self, data):
import ogr
import databundles.library as dl
import databundles.geo as dg
import random
import dateutil.parser
path, fpath, drv, options = self.get_extract_name(data)
if os.path.exists(fpath):
return fpath
year = data['year']
source_bundle = self.library.dep('aacrime')
l = self.library
aa = dg.get_analysis_area(l, geoid=self.config.build.aa_geoid)
r = l.find(dl.QueryCommand().identity(id=source_bundle.identity.id_).partition(table='incidents',space=aa.geoid)).pop()
source_partition = l.get(r.partition).partition
ds = drv.CreateDataSource(path, options=options)
srs = ogr.osr.SpatialReference()
srs.ImportFromEPSG(4326) # Lat/Long in WGS84
lyr = ds.CreateLayer( "incidents", srs, ogr.wkbPoint )
lyr.CreateField(ogr.FieldDefn( "type", ogr.OFTString )) # 0
fn=ogr.FieldDefn( "time", ogr.OFTString ) # 1
fn.SetWidth(8)
lyr.CreateField(fn)
lyr.CreateField(ogr.FieldDefn( "hour", ogr.OFTInteger )) # 2
lyr.CreateField(ogr.FieldDefn( "day_time", ogr.OFTInteger )) # 3
fn = ogr.FieldDefn( "date", ogr.OFTString ) # 4
fn.SetWidth(10)
lyr.CreateField(fn)
fn = ogr.FieldDefn( "desc", ogr.OFTString ) # 5
fn.SetWidth(400)
lyr.CreateField(fn)
fn = ogr.FieldDefn( "addr", ogr.OFTString ) # 6
fn.SetWidth(100)
lyr.CreateField(fn)
rnd = .00001 * 100 # Approx 100m
for row in source_partition.query("""
select date, time, lat, lon, type , description, address from incidents
where CAST(strftime('%Y', date) AS INTEGER) = {year} """.format(year=year)):
pt = ogr.Geometry(ogr.wkbPoint)
px = row['lon']+random.uniform(-rnd, rnd)
py = row['lat']+random.uniform(-rnd, rnd)
pt.SetPoint_2D(0, px, py )
feat = ogr.Feature(lyr.GetLayerDefn())
try: hour = dateutil.parser.parse(row['time']).time().hour
except: hour = None
feat.SetField(0, str(row['type']) )
feat.SetField(1, str(row['time']) )
feat.SetField(2, hour )
feat.SetField(3, None )
feat.SetField(4, str(row['date']) )
feat.SetField(5, str(row['description']) )
feat.SetField(6, str(row['address']) )
feat.SetGeometry(pt)
lyr.CreateFeature(feat)
feat.Destroy()
if data['format'] == 'shapefile':
from databundles.util import zip_dir
zip_dir(os.path.dirname(path), fpath)
return fpath
else:
return path
