kopia lustrzana https://github.com/glidernet/ogn-python
Replace ranks with pareto values (#161)
Meisterschueler
GitHub
rodzic
4e223b9941
commit
b4c7078fdb
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@ -1,6 +1,6 @@
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import os
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import re
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from datetime import date, time, datetime
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from datetime import date, time, datetime, timedelta
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from flask import request, render_template, send_file, abort, current_app, make_response
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from sqlalchemy.orm.exc import NoResultFound
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@ -226,25 +226,78 @@ def sender_ranking():
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@cache.cached(query_string=True)
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def receiver_ranking():
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sel_country = request.args.get("country")
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DAYS_FOR_AVERAGING = 28
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countries = db.session.query(Country) \
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.filter(Country.gid == ReceiverRanking.country_id) \
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.filter(ReceiverRanking.date == date.today()) \
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.order_by(Country.iso2)
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# Make the rank for today
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rank_today = db.session.query(
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ReceiverRanking.receiver_id,
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ReceiverRanking.country_id,
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db.func.rank().over(partition_by=ReceiverRanking.country_id, order_by=ReceiverRanking.local_distance_pareto.desc()).label('local_rank'),
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db.func.rank().over(order_by=ReceiverRanking.global_distance_pareto.desc()).label('global_rank')) \
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.filter(ReceiverRanking.date == date.today()) \
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.subquery()
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# Sum the pareto values for the last 28 days
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longtime_today = db.session.query(
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ReceiverRanking.receiver_id,
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ReceiverRanking.country_id,
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db.func.sum(ReceiverRanking.local_distance_pareto).label('local_distance_pareto'),
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db.func.sum(ReceiverRanking.global_distance_pareto).label('global_distance_pareto')) \
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.filter(ReceiverRanking.date.between(date.today() - timedelta(days=DAYS_FOR_AVERAGING), date.today())) \
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.group_by(ReceiverRanking.receiver_id, ReceiverRanking.country_id) \
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.subquery()
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# ... and make the longtime_ranking for today
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longtime_rank_today = db.session.query(
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longtime_today.c.receiver_id,
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longtime_today.c.country_id,
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db.func.rank().over(partition_by=longtime_today.c.country_id, order_by=longtime_today.c.local_distance_pareto.desc()).label('local_rank'),
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db.func.rank().over(order_by=longtime_today.c.global_distance_pareto.desc()).label('global_rank')) \
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.subquery()
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# Sum the pareto values for the last 28 days (beginning from yesterday!)
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longtime_yesterday = db.session.query(
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ReceiverRanking.receiver_id,
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ReceiverRanking.country_id,
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db.func.sum(ReceiverRanking.local_distance_pareto).label('local_distance_pareto'),
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db.func.sum(ReceiverRanking.global_distance_pareto).label('global_distance_pareto')) \
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.filter(ReceiverRanking.date.between(date.today() - timedelta(days=DAYS_FOR_AVERAGING + 1), date.today() - timedelta(days=1))) \
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.group_by(ReceiverRanking.receiver_id, ReceiverRanking.country_id) \
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.subquery()
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# ... and make the longtime_ranking for yesterday
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longtime_rank_yesterday = db.session.query(
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longtime_yesterday.c.receiver_id,
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longtime_yesterday.c.country_id,
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db.func.rank().over(partition_by=longtime_yesterday.c.country_id, order_by=longtime_yesterday.c.local_distance_pareto.desc()).label('local_rank'),
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db.func.rank().over(order_by=longtime_yesterday.c.global_distance_pareto.desc()).label('global_rank')) \
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.subquery()
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# we need the ReceiverRanking, but only from today
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receiver_rankings_from_today = db.session.query(ReceiverRanking).filter(ReceiverRanking.date == date.today()).subquery()
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receiver_rankings_from_today = db.aliased(ReceiverRanking, receiver_rankings_from_today)
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# Get receiver selection list
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if sel_country:
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ranking = db.session.query(ReceiverRanking) \
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.join(Country) \
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.filter(db.and_(ReceiverRanking.country_id == Country.gid, Country.iso2 == sel_country)) \
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.filter(db.and_(ReceiverRanking.date == date.today())) \
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.order_by(ReceiverRanking.global_rank.asc()) \
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.all()
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ranking = db.session.query(Receiver, receiver_rankings_from_today, rank_today.c.local_rank.label('rank_today'), longtime_rank_today.c.local_rank.label('longtime_rank_today'), longtime_rank_yesterday.c.local_rank.label('longtime_rank_yesterday')) \
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.join(receiver_rankings_from_today, isouter=True) \
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.join(rank_today, rank_today.c.receiver_id == Receiver.id, isouter=True) \
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.join(longtime_rank_yesterday, longtime_rank_yesterday.c.receiver_id == Receiver.id, isouter=True) \
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.join(longtime_rank_today, longtime_rank_today.c.receiver_id == Receiver.id) \
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.filter(db.and_(Receiver.country_id == Country.gid, Country.iso2 == sel_country)) \
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.order_by(longtime_rank_today.c.local_rank)
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else:
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ranking = db.session.query(ReceiverRanking) \
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.filter(db.and_(ReceiverRanking.date == date.today())) \
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.order_by(ReceiverRanking.global_rank.asc()) \
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.all()
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ranking = db.session.query(Receiver, receiver_rankings_from_today, rank_today.c.global_rank.label('rank_today'), longtime_rank_today.c.global_rank.label('longtime_rank_today'), longtime_rank_yesterday.c.global_rank.label('longtime_rank_yesterday')) \
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.join(receiver_rankings_from_today, isouter=True) \
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.join(rank_today, rank_today.c.receiver_id == Receiver.id, isouter=True) \
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.join(longtime_rank_yesterday, longtime_rank_yesterday.c.receiver_id == Receiver.id, isouter=True) \
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.join(longtime_rank_today, longtime_rank_today.c.receiver_id == Receiver.id) \
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.order_by(longtime_rank_today.c.global_rank)
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return render_template(
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"receiver_ranking.html",
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@ -7,12 +7,8 @@ class ReceiverRanking(db.Model):
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id = db.Column(db.Integer, primary_key=True)
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date = db.Column(db.Date)
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local_rank = db.Column(db.Integer)
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global_rank = db.Column(db.Integer)
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longtime_local_rank = db.Column(db.Integer)
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longtime_local_rank_delta = db.Column(db.Integer)
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longtime_global_rank = db.Column(db.Integer)
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longtime_global_rank_delta = db.Column(db.Integer)
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local_distance_pareto = db.Column(db.Integer)
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global_distance_pareto = db.Column(db.Integer)
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max_distance = db.Column(db.Float(precision=2))
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max_normalized_quality = db.Column(db.Float(precision=2))
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@ -81,14 +81,14 @@ def update_statistics(date_str=None):
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DELETE FROM receiver_rankings
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WHERE date = '{date_str}';
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INSERT INTO receiver_rankings AS rr (date, receiver_id, country_id, local_rank, global_rank, max_distance, max_normalized_quality, messages_count, coverages_count, senders_count)
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INSERT INTO receiver_rankings AS rr (date, receiver_id, country_id, local_distance_pareto, global_distance_pareto, max_distance, max_normalized_quality, messages_count, coverages_count, senders_count)
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SELECT
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rs.date,
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rs.receiver_id,
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r.country_id,
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RANK() OVER (PARTITION BY rs.date, r.country_id ORDER BY rs.max_distance DESC) AS local_rank,
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RANK() OVER (ORDER BY rs.max_distance DESC) AS global_rank,
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1.0 * RANK() OVER (PARTITION BY rs.date, r.country_id ORDER BY rs.max_distance) / COUNT(rs.*) OVER (PARTITION BY rs.date, r.country_id) AS local_distance_pareto,
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1.0 * RANK() OVER (PARTITION BY rs.date ORDER BY rs.max_distance) / COUNT(rs.*) OVER (PARTITION BY rs.date) AS global_distance_pareto,
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rs.max_distance,
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rs.max_normalized_quality,
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@ -100,54 +100,6 @@ def update_statistics(date_str=None):
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WHERE rs.date = '{date_str}' AND rs.is_trustworthy IS TRUE;
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""")
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db.session.execute(f"""
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UPDATE receiver_rankings AS rr
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SET
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longtime_global_rank = sq3.longtime_global_rank,
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longtime_local_rank = sq3.longtime_local_rank
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FROM (
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SELECT
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sq2.receiver_id,
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RANK() OVER (ORDER BY sq2.longtime_global_scores DESC) AS longtime_global_rank,
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RANK() OVER (PARTITION BY sq2.country_id ORDER BY sq2.longtime_local_scores DESC) AS longtime_local_rank
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FROM (
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SELECT
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sq.receiver_id,
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sq.country_id,
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SUM(sq.global_scores) AS longtime_global_scores,
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SUM(sq.local_scores) AS longtime_local_scores
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FROM (
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SELECT
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rr.receiver_id,
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rr.country_id,
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rr.date,
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MAX(rr.global_rank) OVER (PARTITION BY rr.date) + 1 - rr.global_rank AS global_scores,
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MAX(rr.local_rank) OVER (PARTITION BY rr.country_id, rr.date) + 1 - rr.local_rank AS local_scores
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FROM receiver_rankings AS rr
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) AS sq
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WHERE sq.date BETWEEN DATE '{date_str}' - INTEGER '28' AND DATE '{date_str}'
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GROUP BY sq.receiver_id, sq.country_id
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) AS sq2
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) AS sq3
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WHERE rr.receiver_id = sq3.receiver_id AND rr.date = '{date_str}';
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""")
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db.session.execute(f"""
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UPDATE receiver_rankings AS rr
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SET
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longtime_global_rank_delta = sq.longtime_global_rank_yesterday - rr.longtime_global_rank,
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longtime_local_rank_delta = sq.longtime_local_rank_yesterday - rr.longtime_local_rank
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FROM (
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SELECT
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rr.receiver_id,
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rr.longtime_global_rank AS longtime_global_rank_yesterday,
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rr.longtime_local_rank AS longtime_local_rank_yesterday
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FROM receiver_rankings AS rr
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WHERE rr.date = DATE '{date_str}' - INTEGER '1'
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) AS sq
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WHERE rr.receiver_id = sq.receiver_id;
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""")
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db.session.commit()
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@ -36,23 +36,18 @@
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</thead>
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<tbody>
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{% for entry in ranking %}
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{% if sel_country is none or sel_country == '' %}
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{% set rank = entry.global_rank %}{% set longtime_rank = entry.longtime_global_rank %}{% set longtime_rank_delta = entry.longtime_global_rank_delta %}
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{% else %}
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{% set rank = entry.local_rank %}{% set longtime_rank = entry.longtime_local_rank %}{% set longtime_rank_delta = entry.longtime_local_rank_delta %}
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{% endif %}
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{% for (receiver, ranking, current, today, yesterday) in ranking %}
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<tr>
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<td class="text-right">{{ longtime_rank }}</td>
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<td class="text-right">{% if longtime_rank_delta is none %}{% elif longtime_rank_delta > 0 %}<span class="text-success"><i class="fa fa-long-arrow-up"></i>{{ longtime_rank_delta }}</span>{% elif longtime_rank_delta < 0 %}<span class="text-danger"><i class="fa fa-long-arrow-down"></i>{{ -longtime_rank_delta }}</span>{% endif %}</td>
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<td class="text-right">{{ rank }}</td>
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<td>{{ entry.receiver.country|to_html_flag|safe }} {{ entry.receiver|to_html_link|safe }}</td>
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<td>{{ entry.receiver.airport|to_html_link|safe }}</td>
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<td class="text-right">{{ '%0.1f' | format(entry.max_distance/1000.0) }}</td>
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<td class="text-right">{{ '%0.1f' | format(entry.max_normalized_quality) }}</td>
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<td class="text-right">{{ entry.senders_count }}</td>
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<td class="text-right">{{ entry.coverages_count }}</td>
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<td class="text-right">{{ entry.messages_count }}</td>
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<td class="text-right">{{ today }}</td>
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<td class="text-right">{% if yesterday is none %}(new){% elif yesterday - today > 0 %}<span class="text-success"><i class="fa fa-long-arrow-up"></i>{{ yesterday - today }}</span>{% elif yesterday - today < 0 %}<span class="text-danger"><i class="fa fa-long-arrow-down"></i>{{ today - yesterday }}</span>{% endif %}</td>
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<td class="text-right">{% if current is not none %}{{ current }}{% else %}-{% endif %}</td>
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<td>{{ receiver.country|to_html_flag|safe }} {{ receiver|to_html_link|safe }}</td>
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<td>{{ receiver.airport|to_html_link|safe }}</td>
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<td class="text-right">{% if ranking is not none %}{{ '%0.1f' | format(ranking.max_distance/1000.0) }}{% else %}-{% endif %}</td>
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<td class="text-right">{% if ranking is not none %}{{ '%0.1f' | format(ranking.max_normalized_quality) }}{% else %}-{% endif %}</td>
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<td class="text-right">{% if ranking is not none %}{{ ranking.senders_count }}{% else %}-{% endif %}</td>
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<td class="text-right">{% if ranking is not none %}{{ ranking.coverages_count }}{% else %}-{% endif %}</td>
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<td class="text-right">{% if ranking is not none %}{{ ranking.messages_count }}{% else %}-{% endif %}</td>
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</tr>
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{% endfor %}
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</tbody>
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@ -0,0 +1,59 @@
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"""Replaced 'rank' with 'pareto'
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Revision ID: f3afd6197391
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Revises: 310027ddeea9
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Create Date: 2020-12-08 08:41:49.170716
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"""
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from alembic import op
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import sqlalchemy as sa
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# revision identifiers, used by Alembic.
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revision = 'f3afd6197391'
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down_revision = '310027ddeea9'
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branch_labels = None
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depends_on = None
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def upgrade():
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# ### commands auto generated by Alembic - please adjust! ###
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op.add_column('receiver_rankings', sa.Column('global_distance_pareto', sa.Float(precision=2), nullable=True))
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op.add_column('receiver_rankings', sa.Column('local_distance_pareto', sa.Float(precision=2), nullable=True))
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op.drop_column('receiver_rankings', 'global_rank')
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op.drop_column('receiver_rankings', 'longtime_local_rank_delta')
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op.drop_column('receiver_rankings', 'longtime_global_rank_delta')
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op.drop_column('receiver_rankings', 'longtime_global_rank')
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op.drop_column('receiver_rankings', 'longtime_local_rank')
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op.drop_column('receiver_rankings', 'local_rank')
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# ### end Alembic commands ###
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op.execute("""
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UPDATE receiver_rankings AS rr
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SET
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local_distance_pareto = sq.local_distance_pareto,
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global_distance_pareto = sq.global_distance_pareto
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FROM
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(
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SELECT
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date,
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receiver_id,
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1.0 * RANK() OVER (PARTITION BY date, country_id ORDER BY max_distance) / COUNT(*) OVER (PARTITION BY date, country_id) AS local_distance_pareto,
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1.0 * RANK() OVER (PARTITION BY date ORDER BY max_distance) / COUNT(*) OVER (PARTITION BY date) AS global_distance_pareto
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FROM receiver_rankings
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) AS sq
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WHERE rr.date = sq.date AND rr.receiver_id = sq.receiver_id;
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""")
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def downgrade():
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# ### commands auto generated by Alembic - please adjust! ###
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op.add_column('receiver_rankings', sa.Column('local_rank', sa.Float(precision=2), autoincrement=False, nullable=True))
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op.add_column('receiver_rankings', sa.Column('longtime_local_rank', sa.Float(precision=2), autoincrement=False, nullable=True))
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op.add_column('receiver_rankings', sa.Column('longtime_global_rank', sa.Float(precision=2), autoincrement=False, nullable=True))
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op.add_column('receiver_rankings', sa.Column('longtime_global_rank_delta', sa.Float(precision=2), autoincrement=False, nullable=True))
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op.add_column('receiver_rankings', sa.Column('longtime_local_rank_delta', sa.Float(precision=2), autoincrement=False, nullable=True))
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op.add_column('receiver_rankings', sa.Column('global_rank', sa.Float(precision=2), autoincrement=False, nullable=True))
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op.drop_column('receiver_rankings', 'local_distance_pareto')
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op.drop_column('receiver_rankings', 'global_distance_pareto')
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# ### end Alembic commands ###
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