Commit fe2835b5 authored by Alexander Lercher's avatar Alexander Lercher

Merge branch 'feature/cluster-name-infos' into develop

parents 76a41124 a6213463
...@@ -14,7 +14,7 @@ basePath: "/api" ...@@ -14,7 +14,7 @@ basePath: "/api"
paths: paths:
/debug: /debug:
post: post:
operationId: "debug.echo" operationId: "rest.debug.echo"
tags: tags:
- "Echo" - "Echo"
summary: "Echo function for debugging purposes" summary: "Echo function for debugging purposes"
...@@ -70,7 +70,7 @@ paths: ...@@ -70,7 +70,7 @@ paths:
200: 200:
description: "Successful operation" description: "Successful operation"
schema: schema:
$ref: "#/definitions/Cluster" $ref: "#/definitions/ClusterValue"
/cluster/cluster.png: /cluster/cluster.png:
get: get:
...@@ -97,7 +97,7 @@ paths: ...@@ -97,7 +97,7 @@ paths:
200: 200:
description: "Successful operation" description: "Successful operation"
schema: schema:
$ref: "#/definitions/Cluster" $ref: "#/definitions/ClusterValue"
/agi/cluster/cluster.png: /agi/cluster/cluster.png:
get: get:
...@@ -119,7 +119,7 @@ definitions: ...@@ -119,7 +119,7 @@ definitions:
id: id:
type: string type: string
format: uuid format: uuid
username: user:
type: "string" type: "string"
latitude: latitude:
type: "number" type: "number"
...@@ -127,10 +127,20 @@ definitions: ...@@ -127,10 +127,20 @@ definitions:
type: "number" type: "number"
timestamp: timestamp:
type: "number" type: "number"
Cluster: ClusterValue:
type: "object" type: "object"
properties: properties:
id: id:
type: string type: string
format: uuid format: uuid
cluster_label:
type: number
latitude:
type: number
longitude:
type: number
timestamp:
type: number
user:
type: string
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import json import json
from typing import List, Dict from typing import List, Dict
import hashlib
class AgiRepository: class AgiRepository:
def getLocations(self) -> List: def getLocations(self) -> List:
...@@ -12,22 +12,19 @@ class AgiRepository: ...@@ -12,22 +12,19 @@ class AgiRepository:
travels = [t for t in travels if t['status'] >= 2] travels = [t for t in travels if t['status'] >= 2]
for travel in travels: for travel in travels:
locations.append(self.location(travel["id"], travel['startPlace.latitude'], travel['startPlace.longitude'], 0, ''))
continue # todo work on locations
# todo number of complete travels with startlocation and user data
num_complete_travels = min(len(travel['startedBy']), len(travel['users'])) num_complete_travels = min(len(travel['startedBy']), len(travel['users']))
for i in range(num_complete_travels): for i in range(num_complete_travels):
cur_location = travel['startedBy'][i] cur_location = travel['startedBy'][i]
cur_user = travel['users'][i] cur_user = travel['users'][i]
locations.append( locations.append(
self.location(f'{travel["id"]}-{cur_location["moment"]}', self.location(f'{travel["id"]}-{cur_location["moment"]}',
cur_location['coordinate']['latitude'], cur_location['coordinate']['latitude'],
cur_location['coordinate']['longitude'], cur_location['coordinate']['longitude'],
cur_location['moment'], cur_location['moment'],
# todo user in travel startedBy not available from dataset - currently using user list # todo user in travel startedBy not available from dataset - currently using user list
cur_user['userId'] hashlib.sha1(cur_user['userId'].encode()).hexdigest() # not showing generated username
)) ))
return locations return locations
...@@ -44,6 +41,6 @@ class AgiRepository: ...@@ -44,6 +41,6 @@ class AgiRepository:
'latitude': lat, 'latitude': lat,
'longitude': long_, 'longitude': long_,
"timestamp": timestamp, "timestamp": timestamp,
"username": username "user": username
} }
...@@ -17,7 +17,7 @@ class Clusterer: ...@@ -17,7 +17,7 @@ class Clusterer:
labels = self.create_labels(locations) labels = self.create_labels(locations)
return self._draw_locations( return self._draw_locations(
locations = np.asarray([(l['latitude'], l['longitude']) for l in locations]), locations = self.extract_location_data(locations),
partition_info = labels partition_info = labels
) )
...@@ -47,7 +47,7 @@ class Clusterer: ...@@ -47,7 +47,7 @@ class Clusterer:
if locations is None or len(locations) == 0: if locations is None or len(locations) == 0:
return locations # trash in trash out return locations # trash in trash out
locations = np.asarray([(l['latitude'], l['longitude']) for l in locations]) locations = self.extract_location_data(locations)
dbsc = DBSCAN(eps = self.epsilon, min_samples = self.min_points) dbsc = DBSCAN(eps = self.epsilon, min_samples = self.min_points)
dbsc = dbsc.fit(locations) dbsc = dbsc.fit(locations)
...@@ -78,3 +78,6 @@ class Clusterer: ...@@ -78,3 +78,6 @@ class Clusterer:
clusters[label] = [l for l in locations if l['cluster_label'] == label] clusters[label] = [l for l in locations if l['cluster_label'] == label]
return clusters return clusters
def extract_location_data(self, locations: List[dict]) -> np.ndarray:
return np.asarray([(float(l['latitude']), float(l['longitude'])) for l in locations])
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