This is gonna be a merge hell

client/Nightr/src/app/component/camera-button/camera-button.component.ts

@@ -1,6 +1,5 @@
 import { Component, OnInit } from '@angular/core';
 import { MyCameraService } from '../../services/my-camera-service';
-import { Image } from 'tns-core-modules/ui/image'
 
 @Component({
   selector: 'ns-camera-button',

client/Nightr/src/app/home-page/home-page.component.ts

@@ -23,8 +23,7 @@ export class HomePageComponent implements OnInit {
     flat_earth: boolean;
     in_australia: boolean;
 
-    constructor(private myHttpPostSerivce: MyHttpPostService,
+    constructor(private routerExtensions: RouterExtensions,
-                private routerExtensions: RouterExtensions,
     ) { }
 
     ngOnInit(): void {
@@ -32,35 +31,5 @@ export class HomePageComponent implements OnInit {
 
     public onTap(args: GestureEventData): void {
         this.routerExtensions.navigateByUrl("/result-page");
-        /* return this.cameraService.takePicture().
-        then(picture => {
-            this.image = JSON.stringify(picture);
-            //console.log('this is picture in json', JSON.stringify(picture));
-            this.getLocation();
-        }) */
     }
-
-    /* public getLocation(): any {
-        this.geoLocationService.getLocation().then(location => {
-            this.locationData = location;
-            //console.log('this is locationData', this.locationData);
-            this.submit();
-        }).catch(error => {
-        });
-    }
-
-    public submit(): void {
-        this.makePostRequest();
-    }
-
-    private makePostRequest(): void {
-        this.myHttpPostSerivce
-            .postData({ position: this.locationData, image: this.image, flat_earth: true, in_australia: true, })
-            .subscribe(res => {
-                //console.log('This is res', res);
-                this.myReturnJSON = res;
-                console.log('THis is myreturnJSON', this.myReturnJSON);
-                this.routerExtensions.navigateByUrl("/result-page");
-            });
-    } */
 }

client/Nightr/src/app/result-page/result-page.component.css

@@ -1 +1,19 @@
-/* Add mobile styles for the component here.  */
+.title-container
+ {
+    font-family: 'Times New Roman', Times, serif;
+    font-size: 20px;
+    color: black;
+    padding: 5px;
+    text-align: center;
+ }
+.page {
+ background-color: lightskyblue;
+}
+.item-header {
+    font-family: 'Times New Roman', Times, serif;
+    font-size: 14px;
+}
+.item-header {
+    font-family: 'Times New Roman', Times, serif;
+    font-size: 10px;
+}

client/Nightr/src/app/result-page/result-page.component.html

@@ -1,7 +1,18 @@
 <ActionBar title="Result" class="action-bar"></ActionBar>
 
-<ScrollView class="page">
+<StackLayout class="page" height="100%">
-        <AbsoluteLayout>
+    <StackLayout height="10%" class="title-container">
-            <Button class="btn btn-primary" text="Home" [nsRouterLink]="['/home-page']"></Button>
+        <Label text="{{night}}"></Label>
-        </AbsoluteLayout>
+        <Label text="{{percentage}}"></Label>
+    </StackLayout>
+    <ScrollView height='90%'>
+        <ListView [items]="reasons" class="list-group">
+            <ng-template let-reason="item" let-i="index" let-odd="odd" let-even="even">
+                <StackLayout orientation="vertical" class="list-group-item">
+                    <Label class="item-header" [text]="reason.str" width="100%" textWrap="true"></Label>
+                    <Label class="item-item" [text]="reason.causestring" width="100%" textWrap="true"></Label>
+                </StackLayout>
+            </ng-template>
+        </ListView>
     </ScrollView>
+</StackLayout>

client/Nightr/src/app/result-page/result-page.component.ts

@@ -7,6 +7,12 @@ import { MyCameraService } from '../services/my-camera-service'
 import { RouterExtensions } from 'nativescript-angular/router';
 import { Location } from 'nativescript-geolocation';
 
+class Reason {
+    constructor(public str: string, public causestring: string) {
+
+     }
+}
+
 @Component({
   selector: 'result-page',
   templateUrl: './result-page.component.html',
@@ -21,13 +27,16 @@ export class ResultPageComponent implements OnInit {
     image: any;
     flat_earth: boolean;
     in_australia: boolean;
+    night: string = "";
+    percentage: string = "";
+    JSONObject;
+    public reasons: Array<Reason>;
 
   constructor(private myHttpPostSerivce: MyHttpPostService,
             private routerExtensions: RouterExtensions,
             private geoLocationService: MyGeoLocationService,
             private batterInfoService: MyBatteryInfoService,
-            private cameraService: MyCameraService,
+            private cameraService: MyCameraService,){ }
-    ) { }
 
   ngOnInit(): Promise<void> {
     return this.cameraService.takePicture().
@@ -55,8 +64,8 @@ private makePostRequest(): void {
         .postData({ position: this.locationData, image: this.image, flat_earth: true, in_australia: true, })
         .subscribe(res => {
             //console.log('This is res', res);
-            this.myReturnJSON = res;
+            this.JSONObject = res;
-            console.log('THis is myreturnJSON', this.myReturnJSON);
+            //console.log('THis is myreturnJSON', this.myReturnJSON);
         });
 }
 

server/nightr/app.py

@@ -10,27 +10,29 @@ from typing import List
 import requests_cache
 from flask import Flask, jsonify, logging, request
 
-from .strategies import miloStrats, iss, cars_in_traffic, tide_strat, upstairs_neighbour, bing, battery
+from .strategies import miloStrats, iss, cars_in_traffic, tide_strat, upstairs_neighbour, bing, svm_strat, battery, just_eat
 from .util import Context
 
 app = Flask(__name__)
 logger = logging.create_logger(app)
 logger.setLevel(DEBUG)
 
-requests_cache.install_cache("requests_cache", expire_after=timedelta(minutes=10))
+requests_cache.install_cache("requests_cache", expire_after=timedelta(minutes=2))
 
 
 strategies = {
     # name: (weight, probability function)
-    "tv2news": miloStrats.tv2newsStrat,
+    "TV2 News": miloStrats.tv2newsStrat,
-    "australia": miloStrats.australiaStrat,
+    "Australia": miloStrats.australiaStrat,
-    "camera": miloStrats.camImgStrat,
+    "Camera Image": miloStrats.camImgStrat,
-    "iss": iss.night_on_iss,
+    "The International Space Station": iss.night_on_iss,
-    "cars_in_traffic": cars_in_traffic.cars_in_traffic,
+    "Nearby Traffic situation": cars_in_traffic.cars_in_traffic,
-    "tide": tide_strat.is_tide,
+    "Tidal Measurements": tide_strat.is_tide,
-    "upstairs_neighbour": upstairs_neighbour.check_games,
+    "Legends of Nighttime": upstairs_neighbour.check_games,
-    "bing": bing.clock,
+    "Bing AI": bing.clock,
-    "battery_level": battery.battery_level,
+    "ML Parking": svm_strat.perform_svm_pred,
+    "Phone Battery Level": battery.battery_level,
+    "Pizza Availability": just_eat.do_just_eat_strat,
 }
 
 
@@ -86,6 +88,9 @@ def probabilities():
         # If this prediction disagrees with the consensus it contributed negatively
         if prediction["night"] != night:
             prediction["contribution"] *= -1
+
+    predictions.sort(key=lambda p: (p["contribution"], p["probability"]), reverse=True)
+
     return jsonify({
         "predictions": predictions,
         "weighted_probabilities_mean": mean,

server/nightr/strategies/iss.py

@@ -40,11 +40,11 @@ def night_on_iss(context: Context) -> Prediction:
     side = "same" if on_iss_time else "other"
     p.reasons.append(f"{the_iss} is {int(distance)} km away, so we are on the {side} side of the earth.")
     for i in itertools.count(1):
-        iss_tz = tf.closest_timezone_at(lng=float(iss_position["longitude"]),
+        iss_tz = tf.closest_timezone_at(lng=float(iss_position["longitude"]), lat=float(iss_position["latitude"]),
-                                        lat=float(iss_position["latitude"]),
                                         delta_degree=i)
         if iss_tz is not None:
             break
+
     iss_time = datetime.now(pytz.timezone(iss_tz))
 
     iss_night = iss_time.hour < 6 or iss_time.hour >= 22
@@ -75,6 +75,9 @@ def haversine(pos1, pos2):
     lat2 = float(pos2["latitude"])
     long2 = float(pos2["longitude"])
 
+    lat1 = 0  # we're only interested in the distance in the longitude for the timezone calculation
+    lat2 = 0
+
     degree_to_rad = float(pi / 180.0)
 
     d_lat = (lat2 - lat1) * degree_to_rad

server/nightr/strategies/just_eat.py

@@ -1,12 +1,8 @@
 import requests
 from bs4 import BeautifulSoup
-from datetime import datetime, timedelta
-import requests_cache
 
 from ..util import Context, Prediction
 
-requests_cache.install_cache("requests_cache", expire_after=timedelta(minutes=10))
-
 
 def is_restaurant_open(name, open, close) -> Prediction:
     p = Prediction()
@@ -44,4 +40,7 @@ def is_restaurant_open(name, open, close) -> Prediction:
 
 
 def do_just_eat_strat(context: Context) -> Prediction:
+    """
+    Is this random Kiosk in Vester Alle open?
+    """
     return is_restaurant_open('stop2shop', 12, 23)

server/nightr/strategies/miloStrats.py

@@ -51,7 +51,7 @@ def tv2newsStrat(context : Context) -> Prediction:
     r = requests.get('http://mpx.services.tv2.dk/api/latest')
 
     data = r.json()
-    publish_dates = [(x['pubDate'])//1000 for x in data][:10]
+    publish_dates = [(x['pubDate'])//1000 for x in data[:5]]
     delta_times = []
     for i in range(len(publish_dates)):
         if i == 0 : continue
@@ -66,6 +66,7 @@ def tv2newsStrat(context : Context) -> Prediction:
         p.weight = 0.0
     else:
         p.weight = 0.7
-    p.probability = 1.0 if avg_timestamp > 50 else 0.0
+    print(avg_timestamp)
-    p.reasons.append('There were ' + ('few' if avg_timestamp > 50 else 'many') + ' recent articles on TV2 News')
+    p.probability = 0.75 if avg_timestamp > 40 else 0.25
+    p.reasons.append('There were ' + ('few' if avg_timestamp > 40 else 'many') + ' recent articles on TV2 News')
     return p

server/nightr/strategies/parking_aarhus_2235.json

@@ -0,0 +1 @@
+{"help": "https://portal.opendata.dk/api/3/action/help_show?name=datastore_search", "success": true, "result": {"include_total": true, "resource_id": "2a82a145-0195-4081-a13c-b0e587e9b89c", "fields": [{"type": "int", "id": "_id"}, {"type": "text", "id": "date"}, {"type": "text", "id": "garageCode"}, {"type": "int4", "id": "totalSpaces"}, {"type": "int4", "id": "vehicleCount"}], "records_format": "objects", "records": [{"_id": 1, "date": "2019/04/06 22:30:01", "garageCode": "NORREPORT", "totalSpaces": 80, "vehicleCount": 61}, {"_id": 2, "date": "2019/04/06 22:30:01", "garageCode": "SCANDCENTER", "totalSpaces": 1240, "vehicleCount": 442}, {"_id": 6, "date": "2019/04/06 22:30:01", "garageCode": "SALLING", "totalSpaces": 700, "vehicleCount": 290}, {"_id": 7, "date": "2019/04/06 22:30:01", "garageCode": "DOKK1", "totalSpaces": 1000, "vehicleCount": 0}, {"_id": 8, "date": "2019/04/06 22:30:01", "garageCode": "Navitas", "totalSpaces": 449, "vehicleCount": 161}, {"_id": 9, "date": "2019/04/06 22:30:01", "garageCode": "NewBusgadehuset", "totalSpaces": 105, "vehicleCount": 99}, {"_id": 3, "date": "2019/04/06 22:30:01", "garageCode": "BRUUNS", "totalSpaces": 953, "vehicleCount": 598}, {"_id": 4, "date": "2019/04/06 22:30:01", "garageCode": "MAGASIN", "totalSpaces": 378, "vehicleCount": 65}, {"_id": 5, "date": "2019/04/06 22:30:01", "garageCode": "KALKVAERKSVEJ", "totalSpaces": 210, "vehicleCount": 278}, {"_id": 10, "date": "2019/04/06 22:30:01", "garageCode": "Urban Level 1", "totalSpaces": 319, "vehicleCount": 32}, {"_id": 11, "date": "2019/04/06 22:30:01", "garageCode": "Urban Level 2+3", "totalSpaces": 654, "vehicleCount": 66}], "_links": {"start": "/api/3/action/datastore_search?resource_id=2a82a145-0195-4081-a13c-b0e587e9b89c", "next": "/api/3/action/datastore_search?offset=100&resource_id=2a82a145-0195-4081-a13c-b0e587e9b89c"}, "total": 11}}

server/nightr/strategies/svm_strat.py

@@ -1,3 +1,5 @@
+from pathlib import Path
+
 from sklearn import svm
 from sklearn.externals import joblib
 import requests
@@ -5,11 +7,9 @@ import glob
 import json
 import numpy as np
 
-
 from .strat_utils import write_json
 from ..util import Context, Prediction
 
-
 def write_data(time):
     write_json("https://portal.opendata.dk/api/3/action/datastore_search?resource_id=2a82a145-0195-4081-a13c-b0e587e9b89c", "parking_aarhus", time)
 
@@ -38,12 +38,15 @@ def train():
     joblib.dump(classifier, "nightness_classifier.pkl")
 
 def predict(X):
-    classifier = joblib.load("nightness_classifier.pkl")
+    classifier = joblib.load(str(Path(__file__).parent.joinpath("nightness_classifier.pkl")))
     prob = classifier.predict_proba(np.array(X).reshape(1, -1))
     return prob[0, 1]
 
 
 def perform_svm_pred(context: Context) -> Prediction:
+    """
+    An SVM trained on two data points, which is capable of guessing 0.5 no matter what.
+    """
     p = Prediction()
     data = requests.get('https://portal.opendata.dk/api/3/action/datastore_search?resource_id=2a82a145-0195-4081-a13c-b0e587e9b89c')
 
@@ -54,5 +57,5 @@ def perform_svm_pred(context: Context) -> Prediction:
     p.reasons.append("Our only two data points have 11 dimensions")
     p.reasons.append("We are using a SVM")
 
-    p.probability = predict(X)
+    p.probability = float(predict(X))
     return p