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df-aggregator
Commit abf20f0d by Corey Koval
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Added Confidence Ellipses

parent 6855f509
Showing with 51 additions and 47 deletions
README.md
# DF Aggregator
## Dependencies:
- Python >= 3.6
- [numpy](https://numpy.org/install/)
- [scikit-learn](https://scikit-learn.org/stable/install.html)
- [python-geojson](https://python-geojson.readthedocs.io/en/latest/)
- [czml3](https://pypi.org/project/czml3/)
- [czml3](https://github.com/poliastro/czml3)
- As of this writing, the version from pip does not support ellipses. Please use the version from GitHub.
- [geojson](https://pypi.org/project/geojson/)
## Other things you'll need:
......
df-aggregator.py
......@@ -146,7 +146,8 @@ def process_data(database_name, outfile):
c.execute("SELECT COUNT(*) FROM intersects")
n_intersects = int(c.fetchone()[0])
#print(n_intersects)
c.execute("SELECT latitude, longitude, num_parents FROM intersects")
# c.execute("SELECT latitude, longitude, num_parents FROM intersects")
c.execute("SELECT longitude, latitude, num_parents FROM intersects")
intersect_array = np.array(c.fetchall())
# print(intersect_array)
likely_location = []
......@@ -179,37 +180,45 @@ def process_data(database_name, outfile):
for y in range(len(intersect_array)):
if intersect_array[y][-1] == x:
cluster = np.concatenate((cluster, [intersect_array[y][0:-1]]), axis = 0)
weighted_location.append(np.average(cluster[:,0:2], weights=cluster[:,2], axis=0).tolist())
# weighted_location.append(np.average(cluster[:,0:2], weights=cluster[:,2], axis=0).tolist())
clustermean = np.mean(cluster[:,0:2], axis=0)
likely_location.append(clustermean.tolist())
cov = np.cov(cluster[:,0], cluster[:,1])
pearson = cov[0, 1]/np.sqrt(cov[0, 0] * cov[1, 1])
ell_radius_x = np.sqrt(1 + pearson) * np.sqrt(cov[0, 0]) * n_std
ell_radius_y = np.sqrt(1 - pearson) * np.sqrt(cov[1, 1]) * n_std
axis_x = v.inverse(clustermean.tolist(), (ell_radius_x + clustermean[0], clustermean[1]))[0]
axis_y = v.inverse(clustermean.tolist(), (clustermean[0], ell_radius_y + clustermean[1]))[0]
u = [[ell_radius_x, ell_radius_y], clustermean.tolist()]
w = np.sum(u, axis = 0)
ellipsedata.append([axis_x, axis_y, v.inverse(clustermean.tolist(), w)[1], *clustermean.tolist()])
print(ellipsedata)
a = cov[0,0]
b = cov[0,1]
c = cov[1,1]
lam1 = a+c/2 + np.sqrt((a-c/2)**2 + b**2)
lam2 = a+c/2 - np.sqrt((a-c/2)**2 + b**2)
pearson = b/np.sqrt(a * c)
ell_radius_x = np.sqrt(1 + pearson) * np.sqrt(a) * n_std
ell_radius_y = np.sqrt(1 - pearson) * np.sqrt(c) * n_std
axis_x = v.inverse(Reverse(clustermean.tolist()), (ell_radius_x + clustermean[1], clustermean[0]))[0]
axis_y = v.inverse(Reverse(clustermean.tolist()), (clustermean[1], ell_radius_y + clustermean[0]))[0]
if b == 0 and a >= c:
rotation = 0
elif b == 0 and a < c:
rotation = np.pi/2
else:
rotation = math.atan2(lam1 - a, b)
ellipsedata.append([axis_x, axis_y, rotation, *clustermean.tolist()])
for x in likely_location:
print(x)
print(Reverse(x))
else:
likely_location = None
for x in intersect_array:
try:
if x[-1] >= 0:
intersect_list.append(Reverse(x[0:2].tolist()))
intersect_list.append(x[0:2].tolist())
except IndexError:
intersect_list.append(Reverse(x.tolist()))
intersect_list.append(x.tolist())
#print(intersect_list)
#all_the_points = Feature(properties = all_pt_style, geometry = MultiPoint(tuple(intersect_list)))
return likely_location, intersect_list, weighted_location, ellipsedata
return likely_location, intersect_list, ellipsedata
else:
print("No Intersections.")
......@@ -226,7 +235,7 @@ def write_geojson(best_point, all_the_points):
file1.write(str(FeatureCollection([all_the_points])))
print(f"Wrote file {geofile}")
def write_czml(best_point, all_the_points, weighted_point, ellipsedata):
def write_czml(best_point, all_the_points, ellipsedata):
point_properties = {
"pixelSize":5.0,
"heightReference":"RELATIVE_TO_GROUND",
......@@ -241,13 +250,13 @@ def write_czml(best_point, all_the_points, weighted_point, ellipsedata):
"rgba": [0, 255, 0, 255],
}
}
weighted_properties = {
"pixelSize":20.0,
"heightReference":"RELATIVE_TO_GROUND",
"color": {
"rgba": [0, 0, 255, 255],
}
}
# weighted_properties = {
# "pixelSize":20.0,
# "heightReference":"RELATIVE_TO_GROUND",
# "color": {
# "rgba": [0, 0, 255, 255],
# }
# }
rx_properties = {
"image":
{
......@@ -276,7 +285,7 @@ def write_czml(best_point, all_the_points, weighted_point, ellipsedata):
top = Preamble(name="Geolocation Data")
all_point_packets = []
best_point_packets = []
weighted_point_packets = []
# weighted_point_packets = []
receiver_point_packets = []
ellipse_packets = []
......@@ -292,32 +301,28 @@ def write_czml(best_point, all_the_points, weighted_point, ellipsedata):
point=best_point_properties,
position={"cartographicDegrees": [ x[1], x[0], 15 ]}))
if weighted_point != None:
for x in weighted_point:
weighted_point_packets.append(Packet(id=str(x[0]) + ", " + str(x[1]),
point=weighted_properties,
position={"cartographicDegrees": [ x[1], x[0], 15 ]}))
# if weighted_point != None:
# for x in weighted_point:
# weighted_point_packets.append(Packet(id=str(x[1]) + ", " + str(x[0]),
# point=weighted_properties,
# position={"cartographicDegrees": [ x[0], x[1], 15 ]}))
if ellipsedata != None:
for x in ellipsedata:
rotation = 2 * np.pi - x[2]
if x[0] >= x[1]:
semiMajorAxis = x[0]
semiMinorAxis = x[1]
rotation = 360 - x[2]
rotation += np.pi/2
else:
semiMajorAxis = x[1]
semiMinorAxis = x[0]
rotation = 360 - x[2]
rotation += 90
if rotation < 0:
rotation += 360
elif rotation > 359:
rotation -= 360
ellipse_info = {"semiMajorAxis": semiMajorAxis, "semiMinorAxis": semiMinorAxis, "rotation": math.radians(rotation-45)}
ellipse_packets.append(Packet(id=str(x[3]) + ", " + str(x[4]),
# rotation += np.pi/2
ellipse_info = {"semiMajorAxis": semiMajorAxis, "semiMinorAxis": semiMinorAxis, "rotation": rotation}
ellipse_packets.append(Packet(id=str(x[4]) + ", " + str(x[3]),
ellipse={**ellipse_properties, **ellipse_info},
position={"cartographicDegrees": [ x[4], x[3], 15 ]}))
position={"cartographicDegrees": [ x[3], x[4], 15 ]}))
for x in receivers:
receiver_point_packets.append(Packet(id=x.station_id,
......@@ -325,9 +330,8 @@ def write_czml(best_point, all_the_points, weighted_point, ellipsedata):
position={"cartographicDegrees": [ x.longitude, x.latitude, 15 ]}))
with open("static/output.czml", "w") as file1:
if best_point and weighted_point != None:
file1.write(str(Document([top] + best_point_packets + weighted_point_packets +
all_point_packets + receiver_point_packets + ellipse_packets)))
if best_point and ellipsedata != None:
file1.write(str(Document([top] + best_point_packets + all_point_packets + receiver_point_packets + ellipse_packets)))
elif best_point != None:
file1.write(str(Document([top] + best_point_packets + all_point_packets + receiver_point_packets)))
elif all_the_points != None:
......@@ -443,7 +447,6 @@ def run_receiver(receivers):
conn.close()
if __name__ == '__main__':
# ipaddr = "127.0.0.1"
usage = "usage: %prog -r FILE -d FILE [options]"
parser = OptionParser(usage=usage)
parser.add_option("-r", "--receivers", dest="rx_file", help="REQUIRED List of receiver URLs", metavar="FILE")
......@@ -498,7 +501,6 @@ if __name__ == '__main__':
receivers.append(receiver(x.replace('\n', '')))
except IOError:
ms.receiving = False
# average_intersects = np.array([]).reshape(0,2)
while True:
if ms.receiving:
......
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