def metal_step(request):
all_points = []
client = database.getClient()
fs = GridFS(client.trace_database)
for traceFile in fs.find():
if 'sourceTypes' in traceFile.metadata and "vastplace_example" in traceFile.metadata[
'sourceTypes']:
points = get_example_points_for_source(traceFile._id)
all_points += points
all_points = sorted(all_points, key=lambda x: x[0])
buf = plotStep([
{
'x': [u[0] - all_points[0][0] for u in all_points],
'y': [u[1] for u in all_points],
'label': "metal points",
'color': 'green'
},
],
xlabel=' Time(s)',
ylabel='Metal',
legend=False)
return HttpResponse(buf, content_type='image/svg+xml')
def metal_bar(request):
bins = {30000: 0, 60000: 0}
client = database.getClient()
fs = GridFS(client.trace_database)
for traceFile in fs.find():
if 'sourceTypes' in traceFile.metadata and "vastplace_example" in traceFile.metadata[
'sourceTypes']:
points = get_example_points_for_source(traceFile._id)
for point in points:
if point[1] <= 30000:
bins[30000] += 1
else:
bins[60000] += 1
buf = plotBarGraph([{
'X': [int(u) for u in bins.keys()],
'Y': [bins[k] for k in bins],
'label': "Bin count",
'width': 5000,
'color': 'red'
}, {
'X': [int(u) + 5000 for u in bins.keys()],
'Y': [20 for k in bins],
'label': "always 20",
'width': 5000,
'color': 'green'
}],
xlabel='Sample bar graph',
ylabel='The y axis label',
legend=True)
return HttpResponse(buf, content_type='image/svg+xml')
def bargraph(request, targetId_str):
bins_lower_keys = [0, 14, 21, 28, 35, 60]
# Not all bins are the same size, adjust the widths
widths = [
bins_lower_keys[i + 1] - bins_lower_keys[i]
for i in range(len(bins_lower_keys) - 1)
]
widths.append(widths[-1])
x_labels = [
str(bins_lower_keys[i]) + ' - ' + str(bins_lower_keys[i + 1])
for i in range(len(bins_lower_keys) - 1)
]
x_labels.append('>' + str(bins_lower_keys[-1]))
#matplotlib would center around the lower key, add some offsets depending on the withs
bins_Xs = []
for bInd, bin_lower in enumerate(bins_lower_keys):
bins_Xs.append(bin_lower + 0.5 * widths[bInd])
barData = {k: 0 for k in bins_lower_keys}
target_ids = targetId_str.split(',')
client = database.getClient()
db = client.trace_database
fs = GridFS(db)
for traceFile in fs.find(
{'_id': {
'$in': [ObjectId(u) for u in target_ids]
}}):
point_collection = client.point_database.sensors.find({
'sourceId':
ObjectId(traceFile._id),
'sensorType':
'PM2.5'
})
for point in point_collection:
bin_key = max(
[k for k in bins_lower_keys if k <= point['sensorValue']])
barData[bin_key] += 1
buf = plotBarGraph([{
'X': bins_Xs,
'Y': [barData[k] for k in sorted(barData.keys())],
'label': "PM2.5",
'width': widths,
'color': 'green'
}],
xlabel='PM2.5',
ylabel='Occurence',
x_ticks=bins_Xs,
x_tick_labels=x_labels,
legend=True)
return HttpResponse(buf, content_type='image/svg+xml')
def get_example_points_for_source(sourceId):
retval = []
client = database.getClient()
points = client.point_database.sensors.find({'sourceId': sourceId})
for point in points:
if point['sensorType'] == "metal":
retval.append((point['vTimestamp'], point['sensorValue']))
return retval
def air_map_get_points_bysource(srcId):
retval = []
client = database.getClient()
point_collection = client.point_database.sensors.find(
{'sourceId': ObjectId(srcId)})
GPS = (-1, -1)
for point in point_collection:
if point['sensorType'] == 'GPS':
GPS = point['sensorValue']
elif point['sensorType'] == 'PM2.5':
if GPS != (-1, -1):
retval.append(GPS + [point['sensorValue']])
client.close()
return retval
def metal_rest(request):
bins = {'under 30000': 0, 'over 30000': 0}
client = database.getClient()
fs = GridFS(client.trace_database)
for traceFile in fs.find():
if 'sourceTypes' in traceFile.metadata and "vastplace_example" in traceFile.metadata[
'sourceTypes']:
points = get_example_points_for_source(traceFile._id)
for point in points:
if point[1] <= 30000:
bins['under 30000'] += 1
else:
bins['over 30000'] += 1
return Response(bins, status=status.HTTP_200_OK)
def getEvents(self):
retval = []
client = database.getClient()
file_db = client.trace_database
fs = GridFS(file_db)
traceFile = fs.get(ObjectId(self.fileId))
line = traceFile.readline()
while len(line) > 0:
data = line.rstrip('\n').split('\t')
if len(data) >= 1:
if data[1] == "GPS":
timestamp, _, lat, lon = data
lat = float(lat)
lon = float(lon)
retval.append({
"sourceId": ObjectId(self.fileId),
"sensorName": "example_module",
"sensorID": "example_module",
"vTimestamp": int(timestamp),
"tstype": "epoch",
"sensorType": "GPS",
"sensorValue": (lat, lon)
})
elif data[1] == "metal":
timestamp, _, value = data
retval.append({
"sourceId": ObjectId(self.fileId),
"sensorName": "example_module",
"sensorID": "example_module",
"vTimestamp": int(timestamp),
"tstype": "epoch",
"sensorType": "metal",
"sensorValue": float(value)
})
line = traceFile.readline()
return retval
def grafana_query_median_impl(request):
request_dict = json.loads(request.body)
responseData = [{"target": request_dict['targets'], "datapoints": []}]
values = []
target_ids = request_dict['targets'][0]['target'][:-len('.median')].lstrip(
'(').rstrip(')').split('|')
from_dt = datetime.strptime(request_dict["range"]["from"],
'%Y-%m-%dT%H:%M:%S.%fZ')
to_dt = datetime.strptime(request_dict["range"]["to"],
'%Y-%m-%dT%H:%M:%S.%fZ')
from_ts = float(from_dt.strftime('%s'))
to_ts = float(to_dt.strftime('%s'))
client = database.getClient()
db = client.trace_database
fs = GridFS(db)
for traceFile in fs.find(
{'_id': {
'$in': [ObjectId(u) for u in target_ids]
}}):
point_collection = client.point_database.sensors.find({
'sourceId':
ObjectId(traceFile._id),
'sensorType':
'PM2.5',
'vTimestamp': {
'$gt': from_ts,
'$lt': to_ts
}
})
for point in point_collection:
values.append(int(point["sensorValue"]))
responseData[0]["datapoints"].append(
[np.median(values), float(from_ts + to_ts) / 2])
return responseData
def grafana_sources_search(request, format=None):
request_dict = json.loads(request.body)
source_type = None
if request_dict['target'] == "mobile_ids":
source_type = "ambassadair_mobile"
elif request_dict['target'] == "static_ids":
source_type = "ambassadair_static"
client = database.getClient()
db = client.trace_database
fs = GridFS(db)
responseData = []
for traceFile in fs.find():
if 'sourceTypes' in traceFile.metadata and source_type in traceFile.metadata[
'sourceTypes']:
responseData.append({
"text": traceFile.filename,
"value": str(traceFile._id)
})
return Response(responseData, status=status.HTTP_200_OK)
def air_map(request):
tiling_level = 17
response = None
client = database.getClient()
db = client.trace_database
fs = GridFS(db)
responseData = {'trajectories': [], 'points': [], 'rectangles': []}
tiledMeasures = {}
for traceFile in fs.find():
if 'sourceTypes' in traceFile.metadata and (
"ambassadair_mobile" in traceFile.metadata['sourceTypes']
or "ambassadair_static" in traceFile.metadata['sourceTypes']):
points = air_map_get_points_bysource(traceFile._id)
responseData['trajectories'].append({
'points': [[lon, lat] for lat, lon, _ in points],
'id':
traceFile._id
})
for lat, lon, val in points:
tile_number = osm_latlon_to_tile_number(lon, lat, tiling_level)
if tile_number not in tiledMeasures:
tiledMeasures[tile_number] = []
tiledMeasures[tile_number].append(val)
for tileX, tileY in tiledMeasures:
x1, y1 = osm_tile_number_to_latlon(tileX, tileY, tiling_level)
x2, y2 = osm_tile_number_to_latlon(tileX + 1, tileY + 1, tiling_level)
mean = np.mean(tiledMeasures[tileX, tileY])
mean_str = "%.3f" % mean
if mean > 10:
color = 'rgba(255, 0, 0, 0.3)'
else:
color = 'rgba(0, 255, 0, 0.3)'
responseData['rectangles'].append((x1, x2, y1, y2, mean_str, color))
client.close()
return render(request, 'mapper/map.html', responseData)
def metal_cdf(request):
all_points = []
client = database.getClient()
fs = GridFS(client.trace_database)
for traceFile in fs.find():
if 'sourceTypes' in traceFile.metadata and "vastplace_example" in traceFile.metadata[
'sourceTypes']:
points = get_example_points_for_source(traceFile._id)
all_points += [p[1] for p in points]
buf = plotCDF([
{
'data': all_points,
'label': "metal points",
'color': 'green'
},
],
xlabel=' Metal',
ylabel='CDF',
legend=False)
return HttpResponse(buf, content_type='image/svg+xml')
def getEvents(self):
retval = []
client = database.getClient()
file_db = client.trace_database
fs = GridFS(file_db)
traceFile = fs.get(ObjectId(self.fileId))
#Copy the original db file
outPath = '/tmp/mongo_tmpfile_' + self.fileId
outF = open(outPath, 'w')
line = traceFile.readline()
while len(line) > 0:
outF.write(line)
line = traceFile.readline()
outF.close()
fIn = open(outPath)
line = fIn.readline()
lastGpsFix = (-1, -1)
while len(line) > 0:
data = line.rstrip('\n').split(',')
if len(data) >= 2:
date_data, lat, lon, value = data
lat = float(lat)
lon = float(lon)
value = float(value)
ts_str = date_data[:-6]
tz = date_data[-6:]
dt = datetime.strptime(ts_str[:26], '%Y-%m-%dT%H:%M:%S.%f')
timestamp = float(dt.strftime('%s'))
#Use timezone information to convert back to UTC (+00:00)
if tz[0] == '+':
offsetSign = -1
else:
offsetSign = 1
offset_hours, offset_minutes = tz[1:].split(':')
offset_hours = int(offset_hours)
offset_minutes = int(offset_minutes)
timestamp += offsetSign * (offset_hours * 3600 +
offset_minutes * 60)
if (lat, lon) != lastGpsFix:
retval.append({
"sourceId": ObjectId(self.fileId),
"sensorName": "ambassadair",
"sensorID": "ambassadair",
"vTimestamp": timestamp,
"tstype": "epoch",
"sensorType": "GPS",
"sensorValue": (lat, lon)
})
lastGpsFix = (lat, lon)
retval.append({
"sourceId": ObjectId(self.fileId),
"sensorName": "ambassadair",
"sensorID": "ambassadair",
"vTimestamp": timestamp,
"tstype": "epoch",
"sensorType": "PM2.5",
"sensorValue": value
})
line = fIn.readline()
return retval