From e9033438a0663a970ebad043815ff796c04f9d7a Mon Sep 17 00:00:00 2001 From: "Casper V. Kristensen" Date: Sat, 6 Apr 2019 12:14:55 +0200 Subject: [PATCH] Frokost here we fucking go. --- server/nightr/app.py | 47 +++++++++++++++++++++++-------- server/nightr/strategies/dmi.py | 10 +++++-- server/nightr/strategies/steam.py | 13 +++++++-- server/nightr/util.py | 14 +++++++++ server/requirements.txt | 1 + 5 files changed, 70 insertions(+), 15 deletions(-) create mode 100644 server/nightr/util.py diff --git a/server/nightr/app.py b/server/nightr/app.py index 104a1bd..1b4d4b5 100644 --- a/server/nightr/app.py +++ b/server/nightr/app.py @@ -1,41 +1,66 @@ import inspect import statistics +from dataclasses import asdict +from datetime import timedelta +from typing import List +import requests_cache from flask import Flask, jsonify from server.nightr.strategies import dmi, steam +from server.nightr.util import Context app = Flask(__name__) +requests_cache.install_cache("requests_cache.sqlite", expire_after=timedelta(minutes=10)) + strategies = { # name: (weight, probability function) - "dmi": (1.0, dmi.probability), - "steam": (0.5, steam.lol), + "dmi": (0.5, dmi.probability), + "steam": (1.0, steam.probability), } @app.route("/", methods=["GET", "POST"]) def probabilities(): - phone_data = None # TODO + phone_data = {} # TODO: get from POST request + context = Context(**phone_data) - probs = [] + predictions: List[dict] = [] for name, (weight, strategy) in strategies.items(): try: - prob = strategy(phone_data) + prediction = strategy(context) except Exception as e: print(f"Strategy {name} failed: {e}") continue - probs.append({ + predictions.append({ "name": name, - "doc": inspect.getdoc(strategy), - "prob": prob * weight, + "description": inspect.getdoc(strategy), + "weight": weight, + "weighted_probability": prediction.probability * weight, + "night": prediction.probability > 0.5, + **asdict(prediction), }) + mean = statistics.mean(p["weighted_probability"] for p in predictions) + median = statistics.median(p["weighted_probability"] for p in predictions) + night = mean > 0.5 + + # Calculate contributions of predictions + consensus_weight_sum = sum(p["weight"] for p in predictions if p["night"] == night) + for prediction in predictions: + # If this prediction agrees with the consensus it contributed + if prediction["night"] == night: + prediction["contribution"] = prediction["weight"] / consensus_weight_sum + else: + prediction["contribution"] = 0.0 + return jsonify({ - "strategies": probs, - "mean": statistics.mean(p["prob"] for p in probs), - "median": statistics.median(p["prob"] for p in probs), + "predictions": predictions, + "weighted_probabilities_mean": mean, + "weighted_probabilities_median": median, + "night": night, }) diff --git a/server/nightr/strategies/dmi.py b/server/nightr/strategies/dmi.py index 3c601a4..c2a983b 100644 --- a/server/nightr/strategies/dmi.py +++ b/server/nightr/strategies/dmi.py @@ -1,6 +1,12 @@ +from server.nightr.util import Context, Prediction -def probability(phone_data) -> float: + +def probability(context: Context) -> Prediction: """ The data from DMI. """ - return 0.63 + p = Prediction() + p.probability = 0.7 + p.reasons.append("It is raining in Tønder") + + return p diff --git a/server/nightr/strategies/steam.py b/server/nightr/strategies/steam.py index 194cca8..afd5753 100644 --- a/server/nightr/strategies/steam.py +++ b/server/nightr/strategies/steam.py @@ -1,3 +1,12 @@ +from server.nightr.util import Context, Prediction -def lol(phone_data) -> float: - return 0.21 + +def probability(context: Context) -> Prediction: + """ + How many players are currently online on Steam. + """ + p = Prediction() + p.probability = 0.2 + p.reasons.append("CSGO has more than 10.000 online players") + + return p diff --git a/server/nightr/util.py b/server/nightr/util.py new file mode 100644 index 0000000..ad4585d --- /dev/null +++ b/server/nightr/util.py @@ -0,0 +1,14 @@ +from dataclasses import dataclass, field +from typing import List, Tuple + + +@dataclass +class Context: + battery: float = 1.0 + coordinates: Tuple[float, float] = (0.0, 0.0) + + +@dataclass +class Prediction: + probability: float = 0.5 + reasons: List[str] = field(default_factory=list) diff --git a/server/requirements.txt b/server/requirements.txt index 0e2276f..031c1c9 100644 --- a/server/requirements.txt +++ b/server/requirements.txt @@ -1,2 +1,3 @@ Flask==1.0.2 requests==2.21.0 +requests-cache==0.4.13