From 168d8d23ceacf80e4edff3592c8bc8faebc8b60b Mon Sep 17 00:00:00 2001
From: Clemens Berteld <clemens@berteld.com>
Date: Mon, 13 Sep 2021 10:24:36 +0200
Subject: [PATCH] Interpolation is calculated using weights
---
dataacquisition/GetAverageData.py | 38 +++++++++++++++++++++++--------
dataacquisition/api.py | 4 ++--
dataacquisition/config.ini | 5 +++-
dataacquisition/sandbox.py | 21 +++++++++++------
4 files changed, 48 insertions(+), 20 deletions(-)
diff --git a/dataacquisition/GetAverageData.py b/dataacquisition/GetAverageData.py
index 38d1716..48d947e 100644
--- a/dataacquisition/GetAverageData.py
+++ b/dataacquisition/GetAverageData.py
@@ -6,7 +6,9 @@ from psycopg2 import sql
cfg = configparser.ConfigParser()
cfg.read('config.ini')
assert "POSTGRES" in cfg, "missing POSTGRES in config.ini"
+assert "INTERPOLATION" in cfg, "missing INTERPOLATION in config.ini"
param_postgres = cfg["POSTGRES"]
+param_interpol = cfg["INTERPOLATION"]
def get_year_columns(cursor):
@@ -29,23 +31,23 @@ def get_neighbours(cursor, lat, lon, columns):
query = sql.SQL("""
SELECT array_to_json(array_agg(row_to_json(t))) from (
- SELECT {columns} FROM stations
- ORDER BY ST_Distance(ST_MakePoint(lon, lat), ST_MakePoint({lon}, {lat}))
- LIMIT 10
+ SELECT {columns}, ST_Distance(ST_MakePoint(lon, lat), ST_MakePoint({lon}, {lat})) AS distance
+ FROM stations
+ ORDER BY distance
+ LIMIT {amount_neighbours}
) t;
- """).format(columns=columns, lon=sql.Placeholder(), lat=sql.Placeholder())
+ """).format(columns=columns, lon=sql.Placeholder(), lat=sql.Placeholder(), amount_neighbours=sql.SQL(param_interpol["amount_neighbours"]))
cursor.execute(query, values)
neighbours = cursor.fetchall()[0][0]
return neighbours
+# Unused
def calc_averages(neighbours, years):
averages = {}
for year in years:
values = []
- # print(neighbours)
for neighbour in neighbours:
-
# print(neighbour[str(year)])
if not neighbour[str(year)] == 'NaN': values.append(neighbour[str(year)])
avg = round(sum(values) / len(values), 3)
@@ -53,17 +55,33 @@ def calc_averages(neighbours, years):
return averages
-def get_average_data_for_point(lat, lon, columns):
+def calc_idw(neighbours, years):
+ weighted_values = {}
+ for year in years:
+ values = []
+ # print(neighbours)
+ distances = []
+ for neighbour in neighbours:
+ distances.append(neighbour['distance'])
+ for neighbour in neighbours:
+ normalizer = float(param_interpol["amount_neighbours"]) / sum(distances)
+ weight = neighbour['distance'] * normalizer
+ print('weight', weight)
+ if not neighbour[str(year)] == 'NaN': values.append(neighbour[str(year)] * weight)
+ avg = round(sum(values) / len(values), 3)
+ weighted_values[year] = avg
+ return weighted_values
+
+
+def get_interpolation_data_for_point(lat, lon, columns):
with psycopg2.connect(database=param_postgres["dbName"], user=param_postgres["user"], password=param_postgres["password"], host=param_postgres["host"], port=param_postgres["port"]) as connection:
with connection.cursor() as cursor:
- print(columns)
if '*' in str(columns):
year_columns = get_year_columns(cursor)
else:
year_columns = (str(columns).replace("""SQL('""", "").replace('"', '').replace("')", "")).split(',')
- print(year_columns)
neighbours = get_neighbours(cursor, lat, lon, columns)
- avg_data = calc_averages(neighbours, year_columns)
+ avg_data = calc_idw(neighbours, year_columns)
print(avg_data)
return avg_data
diff --git a/dataacquisition/api.py b/dataacquisition/api.py
index d4d984c..5e16b76 100644
--- a/dataacquisition/api.py
+++ b/dataacquisition/api.py
@@ -4,7 +4,7 @@ import psycopg2
from flask import Flask, jsonify, request
from psycopg2 import sql
import configparser
-from GetAverageData import get_average_data_for_point
+from GetAverageData import get_interpolation_data_for_point
cfg = configparser.ConfigParser()
cfg.read('config.ini')
@@ -39,7 +39,7 @@ def index():
if 'lat' in request.args or 'lng' in request.args:
lat = request.args['lat']
lon = request.args['lon']
- return get_average_data_for_point(lat, lon, columns)
+ return get_interpolation_data_for_point(lat, lon, columns)
else:
if 'id' in request.args:
diff --git a/dataacquisition/config.ini b/dataacquisition/config.ini
index dfbe24d..7d49d0c 100644
--- a/dataacquisition/config.ini
+++ b/dataacquisition/config.ini
@@ -3,4 +3,7 @@ host = localhost
port = 5432
user = postgres
password = postgres
-dbName = temperatures_berteld_morstein
\ No newline at end of file
+dbName = temperatures_berteld_morstein
+
+[INTERPOLATION]
+amount_neighbours = 5
\ No newline at end of file
diff --git a/dataacquisition/sandbox.py b/dataacquisition/sandbox.py
index 7b1e42c..f245d89 100644
--- a/dataacquisition/sandbox.py
+++ b/dataacquisition/sandbox.py
@@ -1,9 +1,16 @@
-import psycopg2
-from psycopg2 import sql
+# import psycopg2
+# from psycopg2 import sql
+#
+# query = sql.SQL("select {0} from {1} where {2} LIKE {3} {4}").format(sql.SQL(', ').join([sql.Identifier('foo'), sql.Identifier('bar')]), sql.Identifier('table'), sql.Identifier('coulumn'), sql.Placeholder(),
+# sql.SQL('AND 1 = 1'))
+#
+# with psycopg2.connect(database='temperatures_berteld_morstein', user='postgres', password='postgres', host='localhost', port=5432) as connection:
+# with connection.cursor() as cursor:
+# print(query.as_string(cursor))
-query = sql.SQL("select {0} from {1} where {2} LIKE {3} {4}").format(sql.SQL(', ').join([sql.Identifier('foo'), sql.Identifier('bar')]), sql.Identifier('table'), sql.Identifier('coulumn'), sql.Placeholder(),
- sql.SQL('AND 1 = 1'))
-with psycopg2.connect(database='temperatures_berteld_morstein', user='postgres', password='postgres', host='localhost', port=5432) as connection:
- with connection.cursor() as cursor:
- print(query.as_string(cursor))
+weights = [2, 1.25, 0.75, 0.6, 0.4]
+neighbours = [{'2015': 'NaN', '2010': 9.333, '2014': 'NaN', '1998': 'NaN', 'distance': 0.0223606797750006}, {'2015': 11.233, '2010': 8.883, '2014': 11.458, '1998': 10.05, 'distance': 0.0300000000000011}, {'2015': 11.133, '2010': 8.767, '2014': 11.467, '1998': 'NaN', 'distance': 0.108166538263921}, {'2015': 10.667, '2010': 8.208, '2014': 11.025, '1998': 9.8, 'distance': 0.111803398874988}, {'2015': 10.667, '2010': 8.35, '2014': 10.908, '1998': 'NaN', 'distance': 0.176918060129539}]
+
+for weight, neighbour in zip(weights, neighbours):
+ print(weight, neighbour['2015'])
--
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