Fix pre-commit

.gitignore

@@ -57,9 +57,9 @@ notebooks/old_notebooks/*.tif
 doc/_build
 
 # VS code related
-.vscode
-doc/.vscode/settings.json
-.vscode/settings.json
+*.vscode
+doc/*.vscode/settings.json
+*.vscode/settings.json
 *.code-workspace
 
 # Additional debugging folders

.pre-commit-config.yaml

@@ -4,7 +4,7 @@
 
 # Copied from https://github.com/PyPSA/pypsa-eur/pull/302/files
 
-exclude: ^(LICENSES|README.md)
+exclude: ^(LICENSES)
 
 
 repos:
@@ -35,6 +35,18 @@ repos:
     types_or: [python, rst, markdown]
     files: ^(scripts|doc)/
 
+  # Make docstrings PEP 257 compliant
+- repo: https://github.com/PyCQA/docformatter
+  rev: v1.7.3
+  hooks:
+  - id: docformatter
+    args: ["--in-place", "--make-summary-multi-line", "--pre-summary-newline"]
+
+- repo: https://github.com/keewis/blackdoc
+  rev: v0.3.8
+  hooks:
+  - id: blackdoc
+
 # Formatting with "black" coding style
 - repo: https://github.com/psf/black
   rev: 23.3.0

README.md

@@ -6,7 +6,7 @@ SPDX-License-Identifier: AGPL-3.0-or-later
 
 # PyPSA-Earth
 
-<p align="left"> 
+<p align="left">
 by
 <a href="https://pypsa-meets-earth.github.io">
     <img src="https://github.com/pypsa-meets-earth/pypsa-meets-earth.github.io/raw/main/assets/img/logo.png" width="150">

config.default.yaml

@@ -341,8 +341,8 @@ monte_carlo:
       # Key: add below the pypsa object for the monte_carlo sampling, "network" is only allowed for filtering!
       # Value: currently supported format [l_bound, u_bound] or empty [], represent multiplication factors for the object
     loads_t.p_set: [0.9, 1.1]
-    generators_t.p_max_pu.loc[:, n.generators.carrier == "wind"]: [0.9, 1.1]
-    generators_t.p_max_pu.loc[:, n.generators.carrier == "solar"]: [0.9, 1.1]
+    # generators_t.p_max_pu.loc[:, n.generators.carrier == "wind"]: [0.9, 1.1]
+    # generators_t.p_max_pu.loc[:, n.generators.carrier == "solar"]: [0.9, 1.1]
 
 
 solving:

config.tutorial.yaml

@@ -328,7 +328,7 @@ costs:
 
 monte_carlo:
   options:
-    add_to_snakefile: false
+    add_to_snakefile: true
     samples: 7    # number of optimizations
     sampling_strategy: "chaospy"    # "pydoe2", "chaospy", "scipy", packages that are supported
   pypsa_standard:
@@ -337,8 +337,8 @@ monte_carlo:
       # Key: add below the pypsa object for the monte_carlo sampling, "network" is only allowed for filtering!
       # Value: currently supported format [l_bound, u_bound] or empty [], represent multiplication factors for the object
     loads_t.p_set: [0.9, 1.1]
-    generators_t.p_max_pu.loc[:, n.generators.carrier == "wind"]: [0.9, 1.1]
-    generators_t.p_max_pu.loc[:, n.generators.carrier == "solar"]: [0.9, 1.1]
+    # generators_t.p_max_pu.loc[:, n.generators.carrier == "wind"]: [0.9, 1.1]
+    # generators_t.p_max_pu.loc[:, n.generators.carrier == "solar"]: [0.9, 1.1]
 
 
 solving:

doc/short_tutorial.rst

@@ -68,6 +68,7 @@ The solved networks can be analysed just like any other PyPSA network (e.g. in J
 .. code:: python
 
     import pypsa
+
     network = pypsa.Network("results/networks/elec_s_6_ec_lcopt_Co2L-4H.nc")
 
 The video below shows how to analyse solved PyPSA-Eur networks in Jupyter Notebooks.

doc/wildcards.rst

@@ -154,4 +154,5 @@ formats depends on the used backend. To query the supported file types on your s
 .. code:: python
 
     import matplotlib.pyplot as plt
+
     plt.gcf().canvas.get_supported_filetypes()

scripts/_helpers.py

@@ -26,7 +26,6 @@ def sets_path_to_root(root_directory_name):
         Name of the root directory.
     n : int
         Number of folders the function will check upwards/root directed.
-
     """
     import os
 
@@ -294,7 +293,8 @@ def aggregate_costs(n, flatten=False, opts=None, existing_only=False):
 
 def progress_retrieve(url, file, data=None, disable_progress=False, roundto=1.0):
     """
-    Function to download data from a url with a progress bar progress in retrieving data
+    Function to download data from a url with a progress bar progress in
+    retrieving data.
 
     Parameters
     ----------
@@ -328,9 +328,10 @@ def dlProgress(count, blockSize, totalSize, roundto=roundto):
 
 def get_aggregation_strategies(aggregation_strategies):
     """
-    default aggregation strategies that cannot be defined in .yaml format must be specified within
-    the function, otherwise (when defaults are passed in the function's definition) they get lost
-    when custom values are specified in the config.
+    Default aggregation strategies that cannot be defined in .yaml format must
+    be specified within the function, otherwise (when defaults are passed in
+    the function's definition) they get lost when custom values are specified
+    in the config.
     """
     import numpy as np
 
@@ -429,7 +430,7 @@ def make_accessable(*ios):
 
 def getContinent(code):
     """
-    Returns continent names that contains list of iso-code countries
+    Returns continent names that contains list of iso-code countries.
 
     Parameters
     ----------
@@ -549,7 +550,7 @@ def two_digits_2_name_country(two_code_country, nocomma=False, remove_start_word
 
 def country_name_2_two_digits(country_name):
     """
-    Convert full country name to 2-digit country code
+    Convert full country name to 2-digit country code.
 
     Parameters
     ----------
@@ -614,9 +615,9 @@ def save_to_geojson(df, fn):
 
 def read_geojson(fn, cols=[], dtype=None, crs="EPSG:4326"):
     """
-    Function to read a geojson file fn.
-    When the file is empty, then an empty GeoDataFrame is returned having columns cols,
-    the specified crs and the columns specified by the dtype dictionary it not none
+    Function to read a geojson file fn. When the file is empty, then an empty
+    GeoDataFrame is returned having columns cols, the specified crs and the
+    columns specified by the dtype dictionary it not none.
 
     Parameters:
     ----------
@@ -643,7 +644,7 @@ def read_geojson(fn, cols=[], dtype=None, crs="EPSG:4326"):
 
 def create_country_list(input, iso_coding=True):
     """
-    Create a country list for defined regions in config_osm_data.py
+    Create a country list for defined regions in config_osm_data.py.
 
     Parameters
     ----------
@@ -672,8 +673,10 @@ def create_country_list(input, iso_coding=True):
     def filter_codes(c_list, iso_coding=True):
         """
         Filter list according to the specified coding.
-        When iso code are implemented (iso_coding=True), then remove the geofabrik-specific ones.
-        When geofabrik codes are selected(iso_coding=False), ignore iso-specific names.
+
+        When iso code are implemented (iso_coding=True), then remove the
+        geofabrik-specific ones. When geofabrik codes are
+        selected(iso_coding=False), ignore iso-specific names.
         """
         if (
             iso_coding

scripts/add_electricity.py

@@ -5,7 +5,8 @@
 
 # -*- coding: utf-8 -*-
 """
-Adds electrical generators, load and existing hydro storage units to a base network.
+Adds electrical generators, load and existing hydro storage units to a base
+network.
 
 Relevant Settings
 -----------------
@@ -109,7 +110,7 @@ def normed(s):
 def calculate_annuity(n, r):
     """
     Calculate the annuity factor for an asset with lifetime n years and
-    discount rate of r, e.g. annuity(20, 0.05) * 20 = 1.6
+    discount rate of r, e.g. annuity(20, 0.05) * 20 = 1.6.
     """
     if isinstance(r, pd.Series):
         return pd.Series(1 / n, index=r.index).where(
@@ -137,7 +138,7 @@ def _add_missing_carriers_from_costs(n, costs, carriers):
 
 def load_costs(tech_costs, config, elec_config, Nyears=1):
     """
-    set all asset costs and other parameters
+    Set all asset costs and other parameters.
     """
     costs = pd.read_csv(tech_costs, index_col=["technology", "parameter"]).sort_index()
 
@@ -232,7 +233,7 @@ def load_powerplants(ppl_fn):
 
 def attach_load(n, demand_profiles):
     """
-    Add load profiles to network buses
+    Add load profiles to network buses.
 
     Parameters
     ----------
@@ -374,7 +375,9 @@ def attach_conventional_generators(
     conventional_config,
     conventional_inputs,
 ):
-    carriers = set(conventional_carriers) | (set(extendable_carriers["Generator"]) - set(renewable_carriers))
+    carriers = set(conventional_carriers) | (
+        set(extendable_carriers["Generator"]) - set(renewable_carriers)
+    )
     _add_missing_carriers_from_costs(n, costs, carriers)
 
     ppl = (

scripts/augmented_line_connections.py

@@ -27,8 +27,6 @@
 
 Description
 -----------
-
-
 """
 import logging
 import os

scripts/base_network.py

@@ -5,7 +5,7 @@
 
 # -*- coding: utf-8 -*-
 """
-Creates the network topology from a OpenStreetMap
+Creates the network topology from a OpenStreetMap.
 
 Relevant Settings
 -----------------
@@ -54,7 +54,6 @@
 
 Description
 -----------
-
 """
 import logging
 import os
@@ -411,7 +410,7 @@ def _set_countries_and_substations(inputs, config, n):
 
 def _rebase_voltage_to_config(config, component):
     """
-    Rebase the voltage of components to the config.yaml input
+    Rebase the voltage of components to the config.yaml input.
 
     Components such as line and buses have voltage levels between
     110 kV up to around 850 kV. PyPSA-Africa uses 3 voltages as config input.

scripts/build_bus_regions.py

@@ -5,7 +5,8 @@
 
 # -*- coding: utf-8 -*-
 """
-Creates Voronoi shapes for each bus representing both onshore and offshore regions.
+Creates Voronoi shapes for each bus representing both onshore and offshore
+regions.
 
 Relevant Settings
 -----------------
@@ -40,7 +41,6 @@
 
 Description
 -----------
-
 """
 import logging
 import os

scripts/build_demand_profiles.py

@@ -5,7 +5,7 @@
 
 # -*- coding: utf-8 -*-
 """
-Creates electric demand profile csv
+Creates electric demand profile csv.
 
 Relevant Settings
 -----------------
@@ -39,7 +39,6 @@
 It creates the load paths for GEGIS outputs by combining the input parameters of the countries, weather year, prediction year, and SSP scenario.
 Then with a function that takes in the PyPSA network "base.nc", region and gadm shape data, the countries of interest, a scale factor, and the snapshots,
 it returns a csv file called "demand_profiles.csv", that allocates the load to the buses of the network according to GDP and population.
-
 """
 import logging
 import os
@@ -63,7 +62,7 @@ def normed(s):
 
 def get_load_paths_gegis(ssp_parentfolder, config):
     """
-    Create load paths for GEGIS outputs
+    Create load paths for GEGIS outputs.
 
     The paths are created automatically according to included country,
     weather year, prediction year and ssp scenario
@@ -143,7 +142,7 @@ def build_demand_profiles(
 
     def upsample(cntry, group):
         """
-        Distributes load in country according to population and gdp
+        Distributes load in country according to population and gdp.
         """
         l = gegis_load.loc[gegis_load.region_code == cntry]["Electricity demand"]
         if len(group) == 1:

scripts/build_natura_raster.py

@@ -116,15 +116,15 @@ def get_transform_and_shape(bounds, res, out_logging):
 
 def unify_protected_shape_areas(inputs, natura_crs, out_logging):
     """
-    Iterates through all snakemake rule inputs and unifies shapefiles (.shp) only.
+    Iterates through all snakemake rule inputs and unifies shapefiles (.shp)
+    only.
 
     The input is given in the Snakefile and shapefiles are given by .shp
 
 
     Returns
     -------
     unified_shape : GeoDataFrame with a unified "multishape"
-
     """
     import pandas as pd
     from shapely.ops import unary_union