10 Processing Data Type 5 - No Heat Demand Values
Contents
© Alexander Jüstel, Fraunhofer IEG, Institution for Energy Infrastructures and Geothermal Systems, RWTH Aachen University, GNU Lesser General Public License v3.0
10 Processing Data Type 5 - No Heat Demand Values#
This notebook illustrates how to process data of Data Type 5 - No Heat Demand Values - To be developed.
Importing Libraries#
[1]:
import rasterio
from rasterio.plot import show
import geopandas as gpd
import pandas as pd
import numpy as np
from shapely.geometry import box
import matplotlib.pyplot as plt
from pyheatdemand import processing
C:\Users\ale93371\Anaconda3\envs\pygeomechanical\lib\site-packages\numpy\_distributor_init.py:30: UserWarning: loaded more than 1 DLL from .libs:
C:\Users\ale93371\Anaconda3\envs\pygeomechanical\lib\site-packages\numpy\.libs\libopenblas.FB5AE2TYXYH2IJRDKGDGQ3XBKLKTF43H.gfortran-win_amd64.dll
C:\Users\ale93371\Anaconda3\envs\pygeomechanical\lib\site-packages\numpy\.libs\libopenblas64__v0.3.23-246-g3d31191b-gcc_10_3_0.dll
warnings.warn("loaded more than 1 DLL from .libs:"
Loading Building Data#
The sample data is loaded using GeoPandas. The building data was extracted from OpenStreet Maps
[2]:
data = gpd.read_file('../../../test/data/Building_Polygons_Aachen.shp')
data
[2]:
| FID | geometry | |
|---|---|---|
| 0 | 0 | POLYGON ((6.07837 50.77791, 6.07823 50.77782, ... |
| 1 | 1 | POLYGON ((6.09864 50.76763, 6.09925 50.76775, ... |
| 2 | 2 | POLYGON ((6.09514 50.77314, 6.09517 50.77330, ... |
| 3 | 3 | POLYGON ((6.09287 50.77261, 6.09269 50.77263, ... |
| 4 | 4 | POLYGON ((6.08927 50.77262, 6.08935 50.77259, ... |
| ... | ... | ... |
| 12472 | 12472 | POLYGON ((6.09058 50.76660, 6.09053 50.76666, ... |
| 12473 | 12473 | POLYGON ((6.09060 50.76671, 6.09068 50.76677, ... |
| 12474 | 12474 | POLYGON ((6.07318 50.76966, 6.07328 50.76966, ... |
| 12475 | 12475 | POLYGON ((6.10029 50.77165, 6.10029 50.77171, ... |
| 12476 | 12476 | POLYGON ((6.06956 50.76559, 6.06949 50.76553, ... |
12477 rows × 2 columns
[3]:
fig, ax = plt.subplots(figsize=(10,10))
data.plot(ax=ax)
plt.xlabel('X [m]')
plt.ylabel('Y [m]')
[3]:
Text(61.472222222222214, 0.5, 'Y [m]')
