data.datasets.plotdatascn

Complexity

Total Complexity

4

Size/Duplication

Total Lines	191
Duplicated Lines	0 %

Importance

Changes

0

3 Functions

Rating	Name	Duplication	Size	Complexity
A	set_epsg_network()	0	19	1
A	plot_osm()	0	40	1
B	plot_generation()	0	76	2

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# File description
"""
Created on Tue May 24 14:42:05 2022
Plotdatascn.py defines functions to plot to provide a better context of the different parameters part of
scenarios eGon2035 and eGon100RE .
@author: Alonso

"""


    
   
   
   
import logging
import os
from matplotlib import pyplot as plt
import matplotlib as mpl
import pandas as pd
from math import sqrt, log10
from pyproj import Proj, transform
from egon.data import db
from egon.data.datasets import Dataset
import egon.data.config
import geopandas as gpd
import tilemapbase
from math import sqrt, log10
from pyproj import Proj, transform
import tilemapbase
from matplotlib_scalebar.scalebar import ScaleBar


logger = logging.getLogger(__name__)

if 'READTHEDOCS' not in os.environ:
    from geoalchemy2.shape import to_shape

__copyright__ = ("Flensburg University of Applied Sciences, "
                 "Europa-Universität Flensburg, "
                 "Centre for Sustainable Energy Systems, "
                 "DLR-Institute for Networked Energy Systems")
__license__ = ""
__author__ = ""






  
   
def set_epsg_network(network):
    """
    Change EPSG from 4326 to 3857. Needed when using osm-background.

    Parameters
    ----------
    network : PyPSA network container

    Returns
    -------
    """

    inProj = Proj(init='epsg:4326')
    outProj = Proj(init='epsg:3857')
    x1, y1 = network.buses.x.values, network.buses.y.values
    x2, y2 = transform(inProj, outProj, x1, y1)
    network.buses.x, network.buses.y = x2, y2
    network.epsg = 3857
    set_epsg_network.counter = set_epsg_network.counter + 1
    
def plot_osm(x, y, zoom, alpha=0.4):
    """
    Plots openstreetmap as background of network-plots

    Parameters
    ----------
    x : array of two floats
        Define x-axis boundaries (lat) of osm plot
    y : array of two floats
        Define y-axis boundaries (long) of osm plot
    zoom : int
        Define zoom of osm, higher values for higher resolution
    alpha : float
        Sets osm-visibility, increase value if osm covers network-plot
    osm : bool or dict, e.g. {'x': [1,20], 'y': [47, 56], 'zoom' : 6}
        If not False, osm is set as background
        with the following settings as dict:
                'x': array of two floats, x axis boundaries (lat)
                'y': array of two floats, y axis boundaries (long)
                'zoom' : resolution of osm. The default is False.

    Returns
    -------
    """

    tilemapbase.init(create=True)

    extent = tilemapbase.Extent.from_lonlat(x[0], x[1], y[0], y[1])
    extent = extent.to_aspect(1.0)
    extent = extent.to_project_3857()

    fig, ax = plt.subplots(1,1)
    ax.set_zorder(1)
    ax.add_artist(ScaleBar(1))
    plt.axis('off')
    plotter = tilemapbase.Plotter(extent, tilemapbase.tiles.build_OSM(),
                                  zoom=zoom)
    plotter.plot(ax, alpha=alpha)
    #ax.plot(x, y, "ro-")
    return fig, ax

def plot_generation(
              carrier,scenario, osm = False
            ):
   """
    Plots color maps according to the capacity of different generators
    of the two existing scenarios (eGon2035 and eGon100RE)
    

    Parameters
    ----------
    carrier : generators
    The list of generators: biomass, central_biomass_CHP, central_biomass_CHP_heat,
    industrial_biomass_CHP, solar, solar_rooftop, wind_offshore, wind_onshore. 
      
    scenario: eGon2035, eGon100RE
        
        
   """
    

   con = db.engine()
   SQLBus = "SELECT bus_id, country FROM grid.egon_etrago_bus WHERE country='DE'" #imports buses of Germany
   busDE = pd.read_sql(SQLBus,con) 
   busDE = busDE.rename({'bus_id': 'bus'},axis=1) 

   sql = "SELECT bus_id, geom FROM grid.egon_mv_grid_district"#Imports grid districs 
   distr = gpd.GeoDataFrame.from_postgis(sql, con)
   distr = distr.rename({'bus_id': 'bus'},axis=1)
   distr = distr.set_index("bus")
   distr = pd.merge(busDE, distr, on='bus') #merges grid districts with buses 

   sqlCarrier = "SELECT carrier, p_nom, bus FROM grid.egon_etrago_generator" #Imports generator
   sqlCarrier = "SELECT * FROM grid.egon_etrago_generator"
   Carriers = pd.read_sql(sqlCarrier,con)
   Carriers = Carriers.loc[Carriers['scn_name'] == scenario]
   Carriers = Carriers.set_index("bus")


   CarrierGen = Carriers.loc[Carriers['carrier'] == carrier]

   Merge = pd.merge(CarrierGen, distr, on ='bus', how="outer") #merges districts with generators 

    
   Merge.loc[Merge ['carrier'] != carrier, "p_nom" ] = 0
   Merge.loc[Merge ['country'] != "DE", "p_nom" ] = 0

   gdf = gpd.GeoDataFrame(Merge , geometry='geom')
   pnom=gdf['p_nom']  
   max_pnom=pnom.quantile(0.95) #0.95 quantile is used to filter values that are too high and make noise in the plots.
   gdf = gdf.to_crs(epsg=3857)

   
   # Plot osm map in background
   if osm != False:
       #if network.srid == 4326:
           #set_epsg_network(network)
       fig, ax = plot_osm(osm['x'], osm['y'], osm['zoom'])

   else:
       fig, ax = plt.subplots(1, 1)
   
   
   
   ax.set_axis_off();
   plt.title(f" {carrier} installed capacity in MW , {scenario}")
   cmap = mpl.cm.coolwarm
   
  
   norm = mpl.colors.Normalize(vmin=0, vmax=max_pnom)
   gdf.plot(column='p_nom', ax=ax, legend=False,  legend_kwds={'label': "p_nom(MW)",

                       'orientation': "vertical"}, cmap=cmap, norm=norm, edgecolor='black', linewidth=0.1,zorder=2)
   scatter = ax.collections[0]
   cbar=plt.colorbar(scatter, ax=ax, extend='max')
   cbar.set_label('p_nom(MW)', rotation=90)
   return 0