7 changed files with 7 additions and 202 deletions
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import matplotlib |
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matplotlib.use('Qt5Agg') # or 'Qt5Agg', depending on your setup |
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import matplotlib.pyplot as plt |
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import numpy as np |
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import json |
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import sys |
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import argparse |
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__author__ = 'm3x1m0m' |
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|
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class c_settings_extractor: |
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def __init__(self, fname): |
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with open(fname, "r") as rf: |
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settings = json.load(rf) |
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kilometer_price_ccar = settings["ccar"]["litres_per_kilometer"] * settings["juice_litre_price"] |
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self.labels = [settings["ecar"]["label"], settings["ccar"]["label"]] |
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self.purchase = np.array([settings["ecar"]["price"], settings["ccar"]["price"]]) |
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self.taxes = np.array([settings["ecar"]["taxes"], settings["ccar"]["taxes"]]) |
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self.insurance = np.array([settings["ecar"]["insurance"], settings["ccar"]["insurance"]]) |
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kilometer_price_ecar = ( settings["ecar"]["charging_behaviour"]["percent_home_charges"] * settings["kwh_price_home"] |
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+ settings["ecar"]["charging_behaviour"]["percent_commercial_charges"] * settings["kwh_price_commercial"]) / 100.0 |
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self.driving = np.array([kilometer_price_ecar * settings["kilometers_per_year"], kilometer_price_ccar * settings["kilometers_per_year"]]) |
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self.maintenance = np.array([settings["ecar"]["maintenance"], settings["ccar"]["maintenance"]]) |
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self.kilometers = settings["kilometers_per_year"] |
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self.currency = settings["currency"] |
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def get_labels(self): |
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return self.labels |
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def get_purchase(self): |
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return self.purchase |
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def get_taxes(self): |
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return self.taxes |
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def get_insurance(self): |
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return self.insurance |
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def get_driving(self): |
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return self.driving |
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def get_maintenance(self): |
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return self.maintenance |
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def get_kilometers(self): |
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return self.kilometers |
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def get_currency(self): |
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return self.currency |
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|
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class c_ecar_comparator: |
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def __init__(self, fname): |
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self.settings_extractor = c_settings_extractor(fname) |
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def calculate_costs_a_year(self): |
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taxes = self.settings_extractor.get_taxes() |
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insurance = self.settings_extractor.get_insurance() |
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driving = self.settings_extractor.get_driving() |
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maintenance = self.settings_extractor.get_maintenance() |
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return taxes + insurance + driving + maintenance |
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def calculate_costs(self, years, months): |
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months_a_year = 12.0 |
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costs_a_year = self.calculate_costs_a_year() |
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return costs_a_year * (years + months/months_a_year) |
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def calculate_break_even(self): |
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total_costs = self.settings_extractor.get_purchase() |
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months_a_year = 12.0 |
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increment = self.calculate_costs_a_year() / months_a_year |
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months = 0 |
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while total_costs[0] > total_costs[1]: |
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total_costs = total_costs + increment |
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months += 1 |
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kilometers = self.settings_extractor.get_kilometers() * months / months_a_year |
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return [months//months_a_year, months%months_a_year, kilometers] # years, months |
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def calculate_amortization_point(self): |
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y = 0 |
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m = 1 |
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months_a_year = 12.0 |
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# Insurance and taxes need to be payed anyway |
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relevant_costs_a_year = self.settings_extractor.get_driving() + self.settings_extractor.get_maintenance() |
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savings_a_month = (relevant_costs_a_year[1]-relevant_costs_a_year[0]) / months_a_year |
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months_till_amortized = self.settings_extractor.get_purchase()[0] / savings_a_month |
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kilometers = months_till_amortized * self.settings_extractor.get_kilometers() / months_a_year |
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months_till_amortized = np.ceil(months_till_amortized) |
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return months_till_amortized//months_a_year, months_till_amortized%months_a_year, round(kilometers, ndigits=2) |
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|
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def main(): |
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parser = argparse.ArgumentParser(description='This script allows to calculate if an electric car makes sense financially for you.') |
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parser.add_argument('-a','--settings', help='Settings file.', required=True, metavar=('FILENAME')) |
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parser.add_argument('-b','--break_even', help='Calculate the break even point (when the EV becomes cheaper).', action='store_true') |
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parser.add_argument('-c','--amortization', help='Calculate the point in time when the electric vehicle is amortized completely by savings.', action='store_true') |
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parser.add_argument('-d','--savings_per_month', help='Calculate savings per month.', action='store_true') |
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parser.add_argument('-e','--savings_per_year', help='Calculate savings per year.', action='store_true') |
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parser.add_argument('-f','--savings_per_kilometer', help='Calculate savings per 100 kilometers (only driving, no maintenance, taxes or insurance).', action='store_true') |
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parser.add_argument('-g','--plot', help='Visualize costs over one or multiple years.', type=int, metavar=('YEARS')) |
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args = parser.parse_args() |
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if not args.break_even and not args.savings_per_year and not args.savings_per_month and not args.plot: |
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sys.exit("Please choose one or multiple options") |
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comparator = c_ecar_comparator(args.settings) |
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extractor = c_settings_extractor(args.settings) |
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be_years = None |
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be_months = None |
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be_kilometers = None |
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if args.break_even: |
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be_years, be_months, be_kilometers = comparator.calculate_break_even() |
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print("Break even after {} years and {} months.".format(be_years, be_months)) |
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if args.savings_per_month: |
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years = 0 |
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months = 1 |
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savings = comparator.calculate_costs(years, months) |
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print("Savings per month based on yearly spending: {}.".format(round(savings[1]-savings[0], ndigits=2))) |
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if args.savings_per_year: |
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years = 1 |
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months = 0 |
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savings = comparator.calculate_costs(years, months) |
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print("Savings per year: {}.".format(round(savings[1]-savings[0], ndigits=2))) |
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if args.savings_per_kilometer: |
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hundred_km = 100.0 |
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driving = hundred_km * extractor.get_driving() / extractor.get_kilometers() |
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labels = extractor.get_labels() |
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print("Costs driving 100 km in the {}: {}. Costs driving 100 km in the {}: {}.".format(labels[0], round(driving[0], ndigits=2), labels[1], round(driving[1]), ndigits=2)) |
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am_years = None |
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am_months = None |
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am_kilometers = None |
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if args.amortization: |
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am_years, am_months, am_kilometers = comparator.calculate_amortization_point() |
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print("The electric vehicle will be amortized by savings after {} years, {} months or exactely at {} kilometres.".format(am_years, am_months, am_kilometers)) |
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if args.plot != None: |
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width = 0.3 |
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plt_colors = ["#8ecae6", "#219ebc", "#023047", "#ffb703", "#fb8500"]; |
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color_ind = 0 |
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labels = extractor.get_labels() |
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purchase = extractor.get_purchase() |
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taxes = extractor.get_taxes() |
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insurance = extractor.get_insurance() |
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driving = extractor.get_driving() |
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maintenance = extractor.get_maintenance() |
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fig, ax = plt.subplots() |
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ax.bar(labels, purchase, width, label = "Price", color = plt_colors[0]) |
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current_y = extractor.get_purchase() |
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y = 0 |
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for i in range(args.plot): |
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ax.bar(labels, taxes, width, bottom = current_y, label = "Taxes".format(y), color = plt_colors[1]) |
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current_y = current_y + taxes |
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ax.bar(labels, insurance, width, bottom = current_y, label = "Insurance".format(y), color = plt_colors[2]) |
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current_y = current_y + insurance |
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ax.bar(labels, driving, width, bottom = current_y, label = "Driving".format(y), color = plt_colors[3]) |
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current_y = current_y + driving |
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ax.bar(labels, maintenance, width, bottom = current_y, label = "Maintenance".format(y), color = plt_colors[4]) |
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current_y = current_y + maintenance |
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y += 1 |
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labels = ["Purchase", "Taxes", "Insurance", "Driving", "Maintenance"] |
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lnspace_start = -0.2 |
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lnspace_stop = 1.2 |
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lnspace_n = 10 |
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x_text = 0.2 |
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if args.break_even: |
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months_a_year = 12.0 |
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be_money = (be_years + be_months/months_a_year) * comparator.calculate_costs_a_year() |
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be_money = be_money[1] + extractor.get_purchase() |
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ax.plot(np.linspace(lnspace_start, lnspace_stop, lnspace_n), [be_money[1]]*lnspace_n, "--", color = plt_colors[2], label = "Break even") |
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ax.text(x_text, be_money[1] + 100, "Break even: {} years, {} months, {} kilometers".format(be_years, be_months, be_kilometers)) |
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labels = ["Break even"] + labels |
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if args.amortization: |
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months_a_year = 12.0 |
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am_money = (am_years + am_months/months_a_year) * comparator.calculate_costs_a_year() |
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am_money = am_money[1] + extractor.get_purchase() |
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ax.plot(np.linspace(lnspace_start, lnspace_stop, lnspace_n), [am_money[1]]*lnspace_n, "--", color = plt_colors[2], label = "Amortization") |
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ax.text(x_text, am_money[1] + 100, "Amortization: {} years, {} months, {} kilometers".format(am_years, am_months, am_kilometers)) |
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labels = ["Amortization"] + labels |
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ax.set_ylabel(extractor.get_currency()) |
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ax.set_title("Comparision of economics: Electric vs. combustion car") |
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ax.legend(labels) |
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ax.grid(axis = "y") |
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plt.show() |
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|
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if __name__ == "__main__": |
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main() |
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@ -1,28 +0,0 @@ |
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{ |
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"currency": "CHF", |
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"kwh_price_home": 0.2, |
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"kwh_price_commercial": 0.5, |
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"juice_litre_price": 1.75, |
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"kilometers_per_year": 20000.0, |
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"ecar": { |
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"label": "Nissan Leaf 2013", |
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"price": 7600, |
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"taxes": 0, |
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"insurance": 354, |
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"kwh_per_kilometer": 0.16, |
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"maintenance": 100, |
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"charging_behaviour": { |
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"percent_free_charges": 90, |
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"percent_home_charges": 5, |
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"percent_commercial_charges": 5 |
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} |
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}, |
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"ccar": { |
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"label": "Suzuki Grand Vitara 2008", |
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"price": 7000, |
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"taxes": 350, |
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"insurance": 362, |
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"litres_per_kilometer": 0.08, |
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"maintenance": 1000 |
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} |
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} |
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After Width: | Height: | Size: 79 KiB |
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Before Width: | Height: | Size: 52 KiB |
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