<reponame>nismod/energy_demand
"""testing load_factors.py
"""
from energy_demand.profiles import load_factors

import numpy as np

def test_peak_shaving_max_min():
    """Test
    """
    fuel_yh = np.zeros((2, 1, 24)) #tow fueltypes one day

    # -------
    '''fuel_yh[0][0] = [
        0.00016234, 0.00016234, 0.00016234, 0.00016234, 0.00016234, 0.00089288,
        0.00243513, 0.00389622, 0.00211045, 0.00097405, 0.00089288, 0.00105522,
        0.00089288, 0.00097405, 0.00097405, 0.00162342, 0.00243513, 0.00389622,
        0.00381504, 0.00316567, 0.00251631, 0.00235396, 0.00154225, 0.00040586]'''

    # fill all first 100 days with one
    for fueltype in range(2):
        for hour in range(12):
            fuel_yh[fueltype][0][hour] = 1
        for hour in range(12, 24):
            fuel_yh[fueltype][0][hour] = 0.5

    average_yd = np.average(fuel_yh, axis=2)
    '''loac_factor_improvement = 0.05
    loadfactor_yd_cy = load_factors.calc_lf_d(fuel_yh, average_yd, mode_constrained=False)
    loadfactor_yd_cy_improved = loadfactor_yd_cy + loac_factor_improvement'''

    loadfactor_yd_cy_improved = 0.75 + 0.1

    result = load_factors.peak_shaving_max_min(
        loadfactor_yd_cy_improved,
        average_yd,
        fuel_yh,
        mode_constrained=False)

    # ---------
    # expected
    # ---------
    max_daily_demand_allowed = 0.75 / (0.75 + 0.1)

    fuel_yh_expected = np.zeros((2, 1, 24))

    area_to_shift = (1 - max_daily_demand_allowed) * 12

    for fueltype in range(2):
        for hour in range(12):
            fuel_yh_expected[fueltype][0][hour] = max_daily_demand_allowed
        for hour in range(12, 24):
            fuel_yh_expected[fueltype][0][hour] = 0.5 + (area_to_shift / 12)

    np.testing.assert_equal(result, fuel_yh_expected)

test_peak_shaving_max_min()

def test_calc_lf_d():
    """Test
    """
    fuel_yh = np.ones((2, 2, 24)) #tow fueltype, Two day example

    fuel_yh[1][1] = np.array((range(24)))
    for i in range(12):
        fuel_yh[1][0][i] = 5
    for i in range(12, 24):
        fuel_yh[1][1][i] = 10
    average_per_day = np.average(fuel_yh, axis=2)

    result = load_factors.calc_lf_d(fuel_yh, average_per_day, mode_constrained=False)

    expected = np.zeros((2, 2))
    expected[1][0] = np.average(fuel_yh[1][0]) / np.max(fuel_yh[1][0])
    expected[1][1] = np.average(fuel_yh[1][1]) / np.max(fuel_yh[1][1])

    assert expected[1][0] == result[1][0]
    assert expected[1][1] == result[1][1]

def test_calc_lf_y():
    """Test
    """
    # fueltype, days, hours
    fuel_yh = np.ones((8, 365, 24)) #Two day example
    fuel_yh[2][1] = np.array((range(24)))
    for i in range(12):
        fuel_yh[2][0][i] = 5
    for i in range(12, 24):
        fuel_yh[2][1][i] = 10

    result = load_factors.calc_lf_y(fuel_yh)

    expected = np.zeros((8))
    expected[0] = np.average(fuel_yh[0]) / np.max(fuel_yh[0])
    expected[2] = np.average(fuel_yh[2]) / np.max(fuel_yh[2])

    assert expected[0] == result[0]
    assert expected[2] == result[2]

def test_calc_lf_season():
    """Test
    """
    # fueltype, days, hours
    fuel_yh = np.ones((8, 3, 24))
    seasons = {'seasonA': [1, 2]}  #Two day example, seasonA is second and third day

    fuel_yh[2][1] = np.array((range(24)))
    for i in range(12):
        fuel_yh[2][0][i] = 5
    for i in range(12, 24):
        fuel_yh[2][1][i] = 10
    average_per_day = np.average(fuel_yh, axis=2)

    result = load_factors.calc_lf_season(seasons, fuel_yh, average_per_day)

    expected = {'seasonA': np.zeros((8))}
    expected['seasonA'][2] = np.average(fuel_yh[2]) / np.max(fuel_yh[2][1:3])

    #if within seasons
    #expected['seasonA'][2] = np.average(fuel_yh[2][1:3]) / np.max(fuel_yh[2][1:3]) * 100
    assert expected['seasonA'][2] == result['seasonA'][2]

"""testing load_factors.py
"""
from energy_demand.profiles import load_factors

import numpy as np

def test_peak_shaving_max_min():
    """Test
    """
    fuel_yh = np.zeros((2, 1, 24)) #tow fueltypes one day

    # -------
    '''fuel_yh[0][0] = [
        0.00016234, 0.00016234, 0.00016234, 0.00016234, 0.00016234, 0.00089288,
        0.00243513, 0.00389622, 0.00211045, 0.00097405, 0.00089288, 0.00105522,
        0.00089288, 0.00097405, 0.00097405, 0.00162342, 0.00243513, 0.00389622,
        0.00381504, 0.00316567, 0.00251631, 0.00235396, 0.00154225, 0.00040586]'''

    # fill all first 100 days with one
    for fueltype in range(2):
        for hour in range(12):
            fuel_yh[fueltype][0][hour] = 1
        for hour in range(12, 24):
            fuel_yh[fueltype][0][hour] = 0.5

    average_yd = np.average(fuel_yh, axis=2)
    '''loac_factor_improvement = 0.05
    loadfactor_yd_cy = load_factors.calc_lf_d(fuel_yh, average_yd, mode_constrained=False)
    loadfactor_yd_cy_improved = loadfactor_yd_cy + loac_factor_improvement'''

    loadfactor_yd_cy_improved = 0.75 + 0.1

    result = load_factors.peak_shaving_max_min(
        loadfactor_yd_cy_improved,
        average_yd,
        fuel_yh,
        mode_constrained=False)

    # ---------
    # expected
    # ---------
    max_daily_demand_allowed = 0.75 / (0.75 + 0.1)

    fuel_yh_expected = np.zeros((2, 1, 24))

    area_to_shift = (1 - max_daily_demand_allowed) * 12

    for fueltype in range(2):
        for hour in range(12):
            fuel_yh_expected[fueltype][0][hour] = max_daily_demand_allowed
        for hour in range(12, 24):
            fuel_yh_expected[fueltype][0][hour] = 0.5 + (area_to_shift / 12)

    np.testing.assert_equal(result, fuel_yh_expected)

test_peak_shaving_max_min()

def test_calc_lf_d():
    """Test
    """
    fuel_yh = np.ones((2, 2, 24)) #tow fueltype, Two day example

    fuel_yh[1][1] = np.array((range(24)))
    for i in range(12):
        fuel_yh[1][0][i] = 5
    for i in range(12, 24):
        fuel_yh[1][1][i] = 10
    average_per_day = np.average(fuel_yh, axis=2)

    result = load_factors.calc_lf_d(fuel_yh, average_per_day, mode_constrained=False)

    expected = np.zeros((2, 2))
    expected[1][0] = np.average(fuel_yh[1][0]) / np.max(fuel_yh[1][0])
    expected[1][1] = np.average(fuel_yh[1][1]) / np.max(fuel_yh[1][1])

    assert expected[1][0] == result[1][0]
    assert expected[1][1] == result[1][1]

def test_calc_lf_y():
    """Test
    """
    # fueltype, days, hours
    fuel_yh = np.ones((8, 365, 24)) #Two day example
    fuel_yh[2][1] = np.array((range(24)))
    for i in range(12):
        fuel_yh[2][0][i] = 5
    for i in range(12, 24):
        fuel_yh[2][1][i] = 10

    result = load_factors.calc_lf_y(fuel_yh)

    expected = np.zeros((8))
    expected[0] = np.average(fuel_yh[0]) / np.max(fuel_yh[0])
    expected[2] = np.average(fuel_yh[2]) / np.max(fuel_yh[2])

    assert expected[0] == result[0]
    assert expected[2] == result[2]

def test_calc_lf_season():
    """Test
    """
    # fueltype, days, hours
    fuel_yh = np.ones((8, 3, 24))
    seasons = {'seasonA': [1, 2]}  #Two day example, seasonA is second and third day

    fuel_yh[2][1] = np.array((range(24)))
    for i in range(12):
        fuel_yh[2][0][i] = 5
    for i in range(12, 24):
        fuel_yh[2][1][i] = 10
    average_per_day = np.average(fuel_yh, axis=2)

    result = load_factors.calc_lf_season(seasons, fuel_yh, average_per_day)

    expected = {'seasonA': np.zeros((8))}
    expected['seasonA'][2] = np.average(fuel_yh[2]) / np.max(fuel_yh[2][1:3])

    #if within seasons
    #expected['seasonA'][2] = np.average(fuel_yh[2][1:3]) / np.max(fuel_yh[2][1:3]) * 100
    assert expected['seasonA'][2] == result['seasonA'][2]
testing load_factors.py Test #tow fueltypes one day # ------- fuel_yh[0][0] = [         0.00016234, 0.00016234, 0.00016234, 0.00016234, 0.00016234, 0.00089288,         0.00243513, 0.00389622, 0.00211045, 0.00097405, 0.00089288, 0.00105522,         0.00089288, 0.00097405, 0.00097405, 0.00162342, 0.00243513, 0.00389622,         0.00381504, 0.00316567, 0.00251631, 0.00235396, 0.00154225, 0.00040586] # fill all first 100 days with one loac_factor_improvement = 0.05     loadfactor_yd_cy = load_factors.calc_lf_d(fuel_yh, average_yd, mode_constrained=False)     loadfactor_yd_cy_improved = loadfactor_yd_cy + loac_factor_improvement # --------- # expected # --------- Test #tow fueltype, Two day example Test # fueltype, days, hours #Two day example Test # fueltype, days, hours #Two day example, seasonA is second and third day #if within seasons #expected['seasonA'][2] = np.average(fuel_yh[2][1:3]) / np.max(fuel_yh[2][1:3]) * 100