openego /
eGon-data
| Conditions | 1 |
| Total Lines | 77 |
| Code Lines | 43 |
| Lines | 0 |
| Ratio | 0 % |
| Changes | 0 | ||
Small methods make your code easier to understand, in particular if combined with a good name. Besides, if your method is small, finding a good name is usually much easier.
For example, if you find yourself adding comments to a method's body, this is usually a good sign to extract the commented part to a new method, and use the comment as a starting point when coming up with a good name for this new method.
Commonly applied refactorings include:
If many parameters/temporary variables are present:
| 1 | """ |
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| 33 | def plot_installedcapacity(carrier, scenario="eGon2035"): |
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| 34 | """ |
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| 35 | Plots color maps according to the capacity of different generators |
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| 36 | of the two existing scenarios (eGon2035 and eGon100RE) |
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| 37 | |||
| 38 | |||
| 39 | Parameters |
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| 40 | ---------- |
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| 41 | carrier : generators |
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| 42 | The list of generators: biomass, central_biomass_CHP, central_biomass_CHP_heat, |
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| 43 | industrial_biomass_CHP, solar, solar_rooftop, wind_offshore, wind_onshore. |
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| 44 | |||
| 45 | scenario: eGon2035, eGon100RE |
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| 46 | |||
| 47 | Returns |
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| 48 | ---------- |
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| 49 | """ |
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| 50 | |||
| 51 | # This function must be called while in the folder |
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| 52 | # that contains the file egon-data.configuration.yaml. |
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| 53 | con = db.engine() |
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| 54 | # imports buses of Germany |
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| 55 | SQLBus = ( |
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| 56 | "SELECT bus_id, country FROM grid.egon_etrago_bus WHERE country='DE'" |
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| 57 | ) |
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| 58 | busDE = pd.read_sql(SQLBus, con) |
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| 59 | busDE = busDE.rename({"bus_id": "bus"}, axis=1) |
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| 60 | # Imports grid districs |
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| 61 | sql = "SELECT bus_id, geom FROM grid.egon_mv_grid_district" |
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| 62 | distr = gpd.GeoDataFrame.from_postgis(sql, con) |
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| 63 | distr = distr.rename({"bus_id": "bus"}, axis=1) |
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| 64 | distr = distr.set_index("bus") |
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| 65 | # merges grid districts with buses |
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| 66 | distr = pd.merge(busDE, distr, on="bus") |
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| 67 | # Imports generator |
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| 68 | sqlCarrier = "SELECT carrier, p_nom, bus FROM grid.egon_etrago_generator" |
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| 69 | sqlCarrier = "SELECT * FROM grid.egon_etrago_generator" |
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| 70 | Carriers = pd.read_sql(sqlCarrier, con) |
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| 71 | Carriers = Carriers.loc[Carriers["scn_name"] == scenario] |
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| 72 | Carriers = Carriers.set_index("bus") |
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| 73 | |||
| 74 | CarrierGen = Carriers.loc[Carriers["carrier"] == carrier] |
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| 75 | # merges districts with generators |
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| 76 | Merge = pd.merge(CarrierGen, distr, on="bus", how="outer") |
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| 77 | |||
| 78 | Merge.loc[Merge["carrier"] != carrier, "p_nom"] = 0 |
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| 79 | Merge.loc[Merge["country"] != "DE", "p_nom"] = 0 |
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| 80 | |||
| 81 | gdf = gpd.GeoDataFrame(Merge, geometry="geom") |
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| 82 | pnom = gdf["p_nom"] # |
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| 83 | # 0.95 quantile is used to filter values that are too high and make noise in the plots. |
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| 84 | max_pnom = pnom.quantile(0.95) |
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| 85 | gdf = gdf.to_crs(epsg=3857) |
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| 86 | |||
| 87 | fig, ax = plt.subplots(1, 1) |
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| 88 | |||
| 89 | ax.set_axis_off() |
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| 90 | plt.title(f" {carrier} installed capacity in MW , {scenario}") |
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| 91 | cmap = mpl.cm.coolwarm |
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| 92 | |||
| 93 | norm = mpl.colors.Normalize(vmin=0, vmax=max_pnom) |
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| 94 | gdf.plot( |
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| 95 | column="p_nom", |
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| 96 | ax=ax, |
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| 97 | legend=False, |
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| 98 | legend_kwds={"label": "p_nom(MW)", "orientation": "vertical"}, |
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| 99 | cmap=cmap, |
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| 100 | norm=norm, |
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| 101 | edgecolor="black", |
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| 102 | linewidth=0.1, |
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| 103 | zorder=2, |
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| 104 | ) |
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| 105 | scatter = ax.collections[0] |
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| 106 | cbar = plt.colorbar(scatter, ax=ax, extend="max") |
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| 107 | cbar.set_label("p_nom(MW)", rotation=90) |
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| 108 | |||
| 109 | return |
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| 110 |
