diff --git a/api/GetAverageData.py b/api/GetAverageData.py
index 10d642708878b6479b73d2a9a1d2e9c8e7e94e7d..0a8542d1b09e56947a6445c74d76e57a73903bb6 100644
--- a/api/GetAverageData.py
+++ b/api/GetAverageData.py
@@ -61,6 +61,13 @@ def find_extremum(cursor, years, extremum):
return result
+def get_min_max(cursor):
+ years = get_year_columns(cursor)
+ min = find_extremum(cursor, years, 'MIN')
+ max = find_extremum(cursor, years, 'MAX')
+ return min, max
+
+
# Find n (defined in config) neighbours and return them ordered by distance
def get_neighbours(cursor, lat, lon, columns):
values = '' # Used in second parameter of cursor.execute() (Avoids SQL injection)
diff --git a/api/api.py b/api/api.py
index 11a84d28a5bf9a516daa6852cc6402117e73cf37..399060416505d256d5ec092f64f32400463c0422 100644
--- a/api/api.py
+++ b/api/api.py
@@ -3,8 +3,8 @@ from flask import Flask, jsonify, request
from flask_cors import cross_origin
from psycopg2 import sql
import configparser
-from GetAverageData import get_interpolation_data_for_point, get_year_columns, get_average_of_multiple_years, find_extremum
-from api import write_raster
+from GetAverageData import get_interpolation_data_for_point, get_year_columns, get_average_of_multiple_years, get_min_max
+from write_raster import write_raster
import SQLPandasTools as s2pTool
cfg = configparser.ConfigParser()
@@ -97,13 +97,10 @@ def getStandardQuery():
@app.route('/minmax', methods=['GET'])
-def get_min_max():
+def return_min_max():
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:
- years = get_year_columns(cursor)
- min = find_extremum(cursor, years, 'MIN')
- max = find_extremum(cursor, years, 'MAX')
- print(min, max)
+ min, max = get_min_max(cursor)
return {'min': str(min), 'max': str(max)}
@@ -117,7 +114,7 @@ def get_raster():
with connection.cursor() as cursor:
# all_years = get_year_columns(cursor)
average_data = get_average_of_multiple_years(cursor, years)
- write_raster.write_raster(average_data)
+ write_raster(average_data)
# return send_from_directory('D:/Uni/Master/01_SS2021/Automatisierte_Geodatenprozessierung/temperaturverteilung/dataacquisition/output', filename='myraster.tif', as_attachment=True)
return 'Läuft, Brudi'
diff --git a/api/write_raster.py b/api/write_raster.py
index c8d62ca67c9fb2146affd7dc7664dfc76fd4360b..99770a2d911b91ec929ec0d441508c523e62bb04 100644
--- a/api/write_raster.py
+++ b/api/write_raster.py
@@ -1,31 +1,104 @@
+import configparser
+import math
+
import numpy as np
+import psycopg2
from osgeo import gdal, osr
+from GetAverageData import get_min_max
+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"]
+
+ramp = [[255,255,255,1],[255,244,191,1],[255,233,128,1],[255,221,64,1],[255,210,0,1],[243,105,0,1],[230,0,0,1],[153,0,0,1],[77,0,0,1],[0,0,0,1]]
+
+
+def get_class_steps(colour_ramp):
+ 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:
+ min_max = get_min_max(cursor)
+ classes = len(colour_ramp)
+ temp_range = min_max[1] - min_max[0]
+ steps = temp_range / classes
+ min = min_max[0]
+ # print(min_max)
+ return min, steps, classes
+
+
+def colour_picker(min, steps, classes, colour_ramp, value):
+ # print(min, steps, classes, value)
+ rgba = None
+ for i in range(0, classes + 1):
+
+ minor = math.floor(min + (i * steps))
+ major = math.ceil(min + ((i + 1) * steps))
+ # print('k:', minor, 'wert:', value, 'g:', major)
+ if minor <= value <= major:
+
+ try:
+ rgba = colour_ramp[i]
+ except IndexError:
+ rgba = colour_ramp[-1]
+ # print(i)
+ # print('ramp:', rgba)
+ if not rgba:
+ rgba = [0, 0, 0, 0]
+ return rgba
def write_raster(data):
- pixel_array = []
- pixel_array_alpha = []
+ min, steps, classes = get_class_steps(ramp)
+
+ pixel_array_r = []
+ pixel_array_g = []
+ pixel_array_b = []
+ pixel_array_a = []
for j in range(0, 36):
- row_array = []
- row_array_alpha = []
+ row_array_r = []
+ row_array_g = []
+ row_array_b = []
+ row_array_a = []
for i, station_id in enumerate(data):
if i % 36 == 0:
value = data[i + j][1]
value = 0 if not value else value
value = 0 if str(value) == 'NaN' else value
- alpha_value = data[i + j][2]
- alpha_value = 0 if alpha_value else 255
- row_array.append(value)
- row_array_alpha.append(alpha_value)
- np_row_array = np.array(row_array)
- np_row_array_alpha = np.array(row_array_alpha)
- pixel_array.append(np_row_array)
- pixel_array_alpha.append(np_row_array_alpha)
- np_pixel_array = np.array(pixel_array)
- np_pixel_array_alpha = np.array(pixel_array_alpha)
+ if not value == 0:
+ rgba = colour_picker(min, steps, classes, ramp, value)
+ # print(rgba)
+ r, g, b, a = rgba[0], rgba[1], rgba[2], rgba[3]
+ else:
+ r, g, b, a = 0, 0, 0, 0
+ # print('r', r, 'g', g, 'b', b, 'a', a)
+ transparent = data[i + j][2]
+ print(transparent)
+ a = 0 if transparent else a
+ a = 255 if a == 1 else a
+ row_array_r.append(r)
+ row_array_g.append(g)
+ row_array_b.append(b)
+ row_array_a.append(a)
+ np_row_array_r = np.array(row_array_r)
+ np_row_array_g = np.array(row_array_g)
+ np_row_array_b = np.array(row_array_b)
+ np_row_array_a = np.array(row_array_a)
+ pixel_array_r.append(np_row_array_r)
+ pixel_array_g.append(np_row_array_g)
+ pixel_array_b.append(np_row_array_b)
+ pixel_array_a.append(np_row_array_a)
+ np_pixel_array_r = np.array(pixel_array_r)
+ np_pixel_array_g = np.array(pixel_array_g)
+ np_pixel_array_b = np.array(pixel_array_b)
+ np_pixel_array_a = np.array(pixel_array_a)
+
+ r_band = np_pixel_array_r
+ g_band = np_pixel_array_g
+ b_band = np_pixel_array_b
+ a_band = np_pixel_array_a
xmin, ymin, xmax, ymax = [5.01, 47.15, 14.81, 55.33]
- nrows, ncols = np.shape(np_pixel_array)
+ nrows, ncols = np.shape(r_band)
xres = (xmax - xmin) / float(ncols)
yres = (ymax - ymin) / float(nrows)
geotransform = (xmin, xres, 0, ymax, 0, -yres)
@@ -35,9 +108,11 @@ def write_raster(data):
srs = osr.SpatialReference()
srs.ImportFromEPSG(4326)
output_raster.SetProjection(srs.ExportToWkt())
- output_raster.GetRasterBand(1).WriteArray(np_pixel_array)
- # output_raster.GetRasterBand(2).WriteArray(np_pixel_array)
- # output_raster.GetRasterBand(3).WriteArray(np_pixel_array)
- output_raster.GetRasterBand(4).WriteArray(np_pixel_array_alpha)
+ output_raster.GetRasterBand(1).WriteArray(r_band)
+ output_raster.GetRasterBand(2).WriteArray(g_band)
+ output_raster.GetRasterBand(3).WriteArray(b_band)
+ output_raster.GetRasterBand(4).WriteArray(a_band)
output_raster.FlushCache()
+
+