Merge branch 'master' into set_scenario_variables

.coveralls.yml

@@ -0,0 +1 @@
+repo_token: fZ0YDYNip5i0bzs2LTPY84oOzTJe01ppc

.pre-commit-config.yaml

@@ -0,0 +1,20 @@
+# See https://pre-commit.com for more information
+# See https://pre-commit.com/hooks.html for more hooks
+repos:
+-   repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v2.4.0
+    hooks:
+    -   id: trailing-whitespace
+    -   id: end-of-file-fixer
+    -   id: check-yaml
+    -   id: check-added-large-files
+    -   id: flake8
+        args: ['--max-line-length=120']  # default of Black
+    -   id: requirements-txt-fixer
+    -   id: check-merge-conflict
+    -   id: name-tests-test
+        args: ['--django']
+- repo: https://github.com/pre-commit/mirrors-isort
+  rev: v4.3.4
+  hooks:
+  - id: isort

.travis.yml

@@ -1,19 +1,20 @@
+sudo: false
 language: python
 python:
-  - "3.6"
+- "3.6"
 
 # easiest way of getting rtree
 before_install:
-  - sudo apt update
-  - sudo apt install libspatialindex-dev
+- sudo apt update
+- sudo apt install libspatialindex-dev
 
 # command to install dependencies
 install:
-  - pip install wheel
-  - pip install Rtree
-  - pip install -r requirements.txt
-  - python setup.py develop
-
-# command to run tests
+- pip install wheel Rtree
+- pip install -r requirements.txt
+- pip install -U pytest pytest-cov coverage coveralls
+- python setup.py develop
 script:
-  - pytest
+- pytest --cov onsset --cov-report html --verbose
+after_success:
+- coveralls

README.md

@@ -1,19 +1,23 @@
-onsset
-=================================
+onsset : Open Source Spatial Electrification Tool
+=================================================
 
-[![PyPI version](https://badge.fury.io/py/gridfinder.svg)](https://test.pypi.org/project/gep-onsset/)
+[![PyPI version](https://badge.fury.io/py/gridfinder.svg)](https://pypi.org/project/onsset/)
 [![Build Status](https://travis-ci.com/OnSSET/onsset.svg?branch=master)](https://travis-ci.com/OnSSET/onsset)
+[![Coverage Status](https://coveralls.io/repos/github/OnSSET/onsset/badge.svg?branch=master)](https://coveralls.io/github/OnSSET/onsset?branch=master)
 [![Documentation Status](https://readthedocs.org/projects/onsset/badge/?version=latest)](https://onsset.readthedocs.io/en/latest/?badge=latest)
 
-Documentation: https://onsset.readthedocs.io/en/latest/index.html#
-
 # Scope
 
-This repository contains the source code of the Open Source Spatial Electrification Tool ([OnSSET](http://www.onsset.org/)). The repository also includes sample test files available in ```.\test_data``` and sample output files available in ```.\sample_output```.
+This repository contains the source code of the Open Source Spatial Electrification Tool
+([OnSSET](http://www.onsset.org/)).
+
+
+The repository also includes sample test files available in ```.\test_data```
+and sample output files available in ```.\sample_output```.
 
 ## Installation
 
-**Requirements**
+### Requirements
 
 OnSSET requires Python > 3.5 with the following packages installed:
 - et-xmlfile
@@ -27,27 +31,26 @@ OnSSET requires Python > 3.5 with the following packages installed:
 - xlrd
 
 
-**Install with pip**
+### Install with pip
+
+Install onsset from the Python Packaging Index (PyPI):
 
 ```
 pip install onsset
 ```
 
-**Install from GitHub**
+### Install from GitHub
 
-Download or clone the repository and install the package in `develop` (editable) mode:
+Download or clone the repository and install the package in `develop`
+(editable) mode:
 
 ```
 git clone https://github.com/onsset/onsset.git
-cd gep-onsset
+cd onsset
 python setup.py develop
 ```
 
-The use of GEP generator requires also installation of
-- IPython
-- jupyter
-- matplotlib
-- seaborn
-
 ## Contact
-For more information regarding the tool, its functionality and implementation please visit https://www.onsset.org or contact the development team at seap@desa.kth.se.
+For more information regarding the tool, its functionality and implementation
+please visit https://www.onsset.org or contact the development team
+at seap@desa.kth.se.

onsset/gui_runner.py

@@ -1,11 +1,13 @@
-# This file runs either the calibration or scenario modules in the runner file,
-# and asks the user to browse to the necessary input files
+"""Provides a GUI for the user to choose input files
+
+This file runs either the calibration or scenario modules in the runner file,
+and asks the user to browse to the necessary input files
+"""
 
-import os
 import tkinter as tk
 from tkinter import filedialog, messagebox
 import pandas as pd
-from runner import *
+from runner import calibration, scenario
 
 root = tk.Tk()
 root.withdraw()
@@ -41,4 +43,3 @@
     summary_folder = filedialog.askdirectory()
 
     scenario(specs_path, calibrated_csv_path, results_folder, summary_folder)
-

onsset/onsset.py

@@ -1,23 +1,12 @@
-# Author: KTH dESA Last modified by Andreas Sahlberg
-# Date: 05 June 2019
-# Python version: 3.5
-
-import os
 import logging
-import pandas as pd
-from math import ceil, pi, exp, log, sqrt, radians, cos, sin, asin
+from math import asin, ceil, cos, exp, log, pi, radians, sin, sqrt
+
 # from pyproj import Proj
 import numpy as np
-from collections import defaultdict
-
-# from IPython.display import Markdown
+import pandas as pd
 
 logging.basicConfig(format='%(asctime)s\t\t%(message)s', level=logging.DEBUG)
 
-# General
-LHV_DIESEL = 9.9445485  # (kWh/l) lower heating value
-HOURS_PER_YEAR = 8760
-
 # Columns in settlements file must match these exactly
 SET_COUNTRY = 'Country'  # This cannot be changed, lots of code will break
 SET_X_DEG = 'X_deg'  # Coordinates in degrees
@@ -108,43 +97,9 @@
 SET_SA_DIESEL_FUEL = 'SADieselFuelCost'
 SET_MG_DIESEL_FUEL = 'MGDieselFuelCost'
 
-# Columns in the specs file must match these exactly
-SPE_COUNTRY = 'Country'
-SPE_POP = 'PopStartYear'  # The actual population in the base year
-SPE_URBAN = 'UrbanRatioStartYear'  # The ratio of urban population (range 0 - 1) in base year
-SPE_POP_FUTURE = 'PopEndYear'
-SPE_URBAN_FUTURE = 'UrbanRatioEndYear'
-SPE_URBAN_MODELLED = 'UrbanRatioModelled'  # The urban ratio in the model after calibration (for comparison)
-SPE_URBAN_CUTOFF = 'UrbanCutOff'  # The urban cutoff population calirated by the model, in people per km2
-SPE_URBAN_GROWTH = 'UrbanGrowth'  # The urban growth rate as a simple multplier (urban pop future / urban pop present)
-SPE_RURAL_GROWTH = 'RuralGrowth'  # Same as for urban
-SPE_NUM_PEOPLE_PER_HH_RURAL = 'NumPeoplePerHHRural'
-SPE_NUM_PEOPLE_PER_HH_URBAN = 'NumPeoplePerHHUrban'
-SPE_DIESEL_PRICE_LOW = 'DieselPriceLow'  # Diesel price in USD/litre
-SPE_DIESEL_PRICE_HIGH = 'DieselPriceHigh'  # Same, with a high forecast var
-SPE_GRID_PRICE = 'GridPrice'  # Grid price of electricity in USD/kWh
-SPE_GRID_CAPACITY_INVESTMENT = 'GridCapacityInvestmentCost'  # grid capacity investments costs from TEMBA USD/kW
-SPE_GRID_LOSSES = 'GridLosses'  # As a ratio (0 - 1)
-SPE_BASE_TO_PEAK = 'BaseToPeak'  # As a ratio (0 - 1)
-SPE_EXISTING_GRID_COST_RATIO = 'ExistingGridCostRatio'
-SPE_MAX_GRID_DIST = 'MaxGridDist'
-SPE_ELEC = 'ElecActual'  # Actual current percentage electrified population (0 - 1)
-SPE_ELEC_MODELLED = 'ElecModelled'  # The modelled version after calibration (for comparison)
-SPE_ELEC_URBAN = 'Urban_elec_ratio'  # Actual electrification for urban areas
-SPE_ELEC_RURAL = 'Rural_elec_ratio'  # Actual electrification for rural areas
-SPE_MIN_NIGHT_LIGHTS = 'MinNightLights'
-SPE_MAX_GRID_EXTENSION_DIST = 'MaxGridExtensionDist'
-SPE_MAX_ROAD_DIST = 'MaxRoadDist'
-SPE_POP_CUTOFF1 = 'PopCutOffRoundOne'
-SPE_POP_CUTOFF2 = 'PopCutOffRoundTwo'
-SPE_ELEC_LIMIT = "ElecLimit"
-SPE_INVEST_LIMIT = "InvestmentLimit"
-SPE_DIST_TO_TRANS = "DistToTrans"
-
-SPE_START_YEAR = "StartYear"
-SPE_END_YEAR = "EndYEar"
-SPE_TIMESTEP = "TimeStep"
-
+# General
+LHV_DIESEL = 9.9445485  # (kWh/l) lower heating value
+HOURS_PER_YEAR = 8760
 
 class Technology:
     """
@@ -196,6 +151,8 @@ def set_default_values(cls, base_year, start_year, end_year, discount_rate, HV_l
                            max_nodes_per_serv_trans=300, MV_LV_sub_station_type=400, MV_LV_sub_station_cost=10000,
                            MV_MV_sub_station_cost=10000, HV_LV_sub_station_type=1000, HV_LV_sub_station_cost=25000,
                            HV_MV_sub_station_cost=25000, power_factor=0.9, load_moment=9643):
+        """Initialises the class with parameter values common to all Technologies
+        """
         cls.base_year = base_year
         cls.start_year = start_year
         cls.end_year = end_year
@@ -700,10 +657,6 @@ def classify_slope(row):
             else:
                 return 1
 
-        def set_penalty(row):
-            classification = row[SET_COMBINED_CLASSIFICATION]
-            return 1 + (exp(0.85 * abs(1 - classification)) - 1) / 100
-
         logging.info('Classify road dist')
         self.df[SET_ROAD_DIST_CLASSIFIED] = self.df.apply(classify_road_dist, axis=1)
 
@@ -726,8 +679,22 @@ def set_penalty(row):
                                                 0.15 * self.df[SET_ELEVATION_CLASSIFIED] +
                                                 0.30 * self.df[SET_SLOPE_CLASSIFIED])
 
+        def set_penalty(classification):
+            """Return penalty value based on classification
+
+            Arguments
+            ---------
+            classification : float
+
+            Returns
+            -------
+            float
+
+            """
+            return 1 + (exp(0.85 * abs(1 - classification)) - 1) / 100
+
         logging.info('Grid penalty')
-        self.df[SET_GRID_PENALTY] = self.df.apply(set_penalty, axis=1)
+        self.df[SET_GRID_PENALTY] = self.df[SET_COMBINED_CLASSIFICATION].apply(set_penalty)
 
     def calc_wind_cfs(self):
         """
@@ -920,7 +887,7 @@ def elec_current_and_future(self, elec_actual, elec_actual_urban, elec_actual_ru
 
         logging.info('Calibrate current electrification')
         self.df[SET_ELEC_CURRENT] = 0
-        
+
 
         # This if function here skims through T&D columns to identify if any non 0 values exist; Then it defines priority accordingly.
         if max(self.df[SET_DIST_TO_TRANS]) > 0:

onsset/runner.py

@@ -1,13 +1,33 @@
 # Defines the modules
 
-from onsset import *
+import logging
+import os
+
 import pandas as pd
+from onsset import (SET_ELEC_ORDER, SET_LCOE_GRID, SET_MIN_GRID_DIST,
+                    SET_MV_CONNECT_DIST, SettlementProcessor, Technology)
+from onsset.specs import (SPE_COUNTRY, SPE_ELEC, SPE_ELEC_MODELLED,
+                          SPE_ELEC_RURAL, SPE_ELEC_URBAN, SPE_END_YEAR,
+                          SPE_EXISTING_GRID_COST_RATIO,
+                          SPE_GRID_CAPACITY_INVESTMENT, SPE_GRID_LOSSES,
+                          SPE_MAX_GRID_EXTENSION_DIST,
+                          SPE_NUM_PEOPLE_PER_HH_RURAL,
+                          SPE_NUM_PEOPLE_PER_HH_URBAN, SPE_POP, SPE_POP_FUTURE,
+                          SPE_START_YEAR, SPE_URBAN, SPE_URBAN_FUTURE,
+                          SPE_URBAN_MODELLED)
 from openpyxl import load_workbook
 
-def calibration(specs_path, csv_path, specs_path_calib, calibrated_csv_path):
-
 
-    specs = pd.read_excel(specs_path, index_col=0)
+def calibration(specs_path, csv_path, specs_path_calib, calibrated_csv_path):
+    """
+
+    Arguments
+    ---------
+    specs_path
+    csv_path
+    specs_path_calib
+    calibrated_csv_path
+    """
     SpecsData = pd.read_excel(specs_path, sheet_name='SpecsData')
     settlements_in_csv = csv_path
     settlements_out_csv = calibrated_csv_path
@@ -54,7 +74,7 @@ def calibration(specs_path, csv_path, specs_path_calib, calibrated_csv_path):
 
     # In case there are limitations in the way grid expansion is moving in a country, this can be reflected through gridspeed.
     # In this case the parameter is set to a very high value therefore is not taken into account.
-   
+
 
     SpecsData.loc[0, SPE_URBAN_MODELLED] = urban_modelled
     SpecsData.loc[0, SPE_ELEC_MODELLED] = elec_modelled
@@ -73,6 +93,16 @@ def calibration(specs_path, csv_path, specs_path_calib, calibrated_csv_path):
     onsseter.df.to_csv(settlements_out_csv, index=False)
 
 def scenario(specs_path, calibrated_csv_path, results_folder, summary_folder):
+    """
+
+    Arguments
+    ---------
+    specs_path : str
+    calibrated_csv_path : str
+    results_folder : str
+    summary_folder : str
+
+    """
 
 
     ScenarioInfo = pd.read_excel(specs_path, sheet_name='ScenarioInfo')

onsset/specs.py

@@ -0,0 +1,37 @@
+"""Columns in the specs file must match these exactly
+"""
+SPE_COUNTRY = 'Country'
+SPE_POP = 'PopStartYear'  # The actual population in the base year
+SPE_URBAN = 'UrbanRatioStartYear'  # The ratio of urban population (range 0 - 1) in base year
+SPE_POP_FUTURE = 'PopEndYear'
+SPE_URBAN_FUTURE = 'UrbanRatioEndYear'
+SPE_URBAN_MODELLED = 'UrbanRatioModelled'  # The urban ratio in the model after calibration (for comparison)
+SPE_URBAN_CUTOFF = 'UrbanCutOff'  # The urban cutoff population calirated by the model, in people per km2
+SPE_URBAN_GROWTH = 'UrbanGrowth'  # The urban growth rate as a simple multplier (urban pop future / urban pop present)
+SPE_RURAL_GROWTH = 'RuralGrowth'  # Same as for urban
+SPE_NUM_PEOPLE_PER_HH_RURAL = 'NumPeoplePerHHRural'
+SPE_NUM_PEOPLE_PER_HH_URBAN = 'NumPeoplePerHHUrban'
+SPE_DIESEL_PRICE_LOW = 'DieselPriceLow'  # Diesel price in USD/litre
+SPE_DIESEL_PRICE_HIGH = 'DieselPriceHigh'  # Same, with a high forecast var
+SPE_GRID_PRICE = 'GridPrice'  # Grid price of electricity in USD/kWh
+SPE_GRID_CAPACITY_INVESTMENT = 'GridCapacityInvestmentCost'  # grid capacity investments costs from TEMBA USD/kW
+SPE_GRID_LOSSES = 'GridLosses'  # As a ratio (0 - 1)
+SPE_BASE_TO_PEAK = 'BaseToPeak'  # As a ratio (0 - 1)
+SPE_EXISTING_GRID_COST_RATIO = 'ExistingGridCostRatio'
+SPE_MAX_GRID_DIST = 'MaxGridDist'
+SPE_ELEC = 'ElecActual'  # Actual current percentage electrified population (0 - 1)
+SPE_ELEC_MODELLED = 'ElecModelled'  # The modelled version after calibration (for comparison)
+SPE_ELEC_URBAN = 'Urban_elec_ratio'  # Actual electrification for urban areas
+SPE_ELEC_RURAL = 'Rural_elec_ratio'  # Actual electrification for rural areas
+SPE_MIN_NIGHT_LIGHTS = 'MinNightLights'
+SPE_MAX_GRID_EXTENSION_DIST = 'MaxGridExtensionDist'
+SPE_MAX_ROAD_DIST = 'MaxRoadDist'
+SPE_POP_CUTOFF1 = 'PopCutOffRoundOne'
+SPE_POP_CUTOFF2 = 'PopCutOffRoundTwo'
+SPE_ELEC_LIMIT = "ElecLimit"
+SPE_INVEST_LIMIT = "InvestmentLimit"
+SPE_DIST_TO_TRANS = "DistToTrans"
+
+SPE_START_YEAR = "StartYear"
+SPE_END_YEAR = "EndYEar"
+SPE_TIMESTEP = "TimeStep"