def test_can_pad_with_zero(self):
# probability sums up to 0.7
p3 = ProbabilityDistribution({
1: 0.5,
2: 0.2
}, normalize=False)
# sanity check
self.assertAlmostEqual(p3.p(0), 0)
self.assertEqual(p3.mean, None)
p3.pad()
self.assertAlmostEqual(p3.p(0), 0.3)
self.assertEqual(p3.mean, 0.9)
def process_insulation_type(self, dwelling, insulation_type):
base_dist = self.get_base_dist(dwelling)[insulation_type]
construction_year = dwelling.attributes['bouwjaar']
dwelling_type = dwelling.attributes['woningtype']
if insulation_type == 'cavity wall':
# Only buildings between 1920 and 1974
# are eligible for cavity wall insulation upgrade:
# older buildings have no cavity wall,
# newer buildings already have an insulated cavity wall.
if 1920 <= construction_year <= 1974:
applicable_measure_years = range(2010, 2019 + 1)
else:
applicable_measure_years = []
else:
# We only have data available for 2010 to 2019,
# and we assume a waiting period of
# MIN_YEAR_MEASURE_AFTER_CONSTRUCTION
# after construction before a measure gets taken.
applicable_measure_years = range(
max(
2010, construction_year +
self.MIN_YEAR_MEASURE_AFTER_CONSTRUCTION), 2019 + 1)
if insulation_type in ['facade', 'floor', 'roof']:
measures_r_values = [
self.insulation_measures_r_values[year]
for year in applicable_measure_years
]
elif insulation_type == 'window':
# The info on measures that we have is on
# HR glazing.
measures_r_values = [
self.glazing_r_values['hr'].copy()
for _ in applicable_measure_years
]
elif insulation_type == 'cavity wall':
measures_r_values = [
self.cavity_wall_r_value for _ in applicable_measure_years
]
else:
raise NotImplementedError
measure_prob_multiplier = self.dwelling_type_multipliers[dwelling_type]
measures_prob = [
measure_prob_multiplier *
self.insulation_measures_p[self.insulation_measures_p.year ==
year][insulation_type].values[0]
for year in applicable_measure_years
]
if len(applicable_measure_years) == 0:
# No measures apply,
# so no probability for increases.
# We need to set this case specifically,
# because else the sum() will return 0,
# which can't be .pad()-ded.
measures_dist = ProbabilityDistribution({0: 1})
else:
measures_dist = sum([
measures_r_values[i] * measures_prob[i]
for i in range(len(measures_r_values))
])
if insulation_type in ['facade', 'floor', 'roof']:
measures_dist.pad()
# Add the increase of R-values in measures_dist
# to the base distribution base_dist.
return base_dist & measures_dist
# With windows, the measure is not an addition to the
# existing insulation, but a replacement.
elif insulation_type == 'window':
p_measures = sum(measures_prob)
# 'measures_dist' already includes the absolute
# probability of the measures, so doesn't need to
# be multiplied by p_measures.
if p_measures != 0:
window_r_dist = (1 - p_measures) * base_dist + measures_dist
else:
window_r_dist = base_dist
return window_r_dist
elif insulation_type == 'cavity wall':
measures_dist.pad()
# This comes as an addon to regular facade insulation.
return measures_dist
else:
raise NotImplementedError
