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Merge 439dd61 into 5a8e50b
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@edwardoughton
edwardoughton committed Sep 30, 2019
2 parents 5a8e50b + 439dd61 commit 25e998a
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Showing 8 changed files with 309 additions and 94 deletions.
2 changes: 1 addition & 1 deletion requirements.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@ shapely
numpy
fiona>=1.7
Rtree>=0.8.3
pyproj
pyproj=2.2.1
pytest
#for visualisation
matplotlib
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283 changes: 252 additions & 31 deletions scripts/run.py
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Original file line number Diff line number Diff line change
Expand Up @@ -510,9 +510,7 @@ def write_frequency_lookup_table(result, environment, site_radius,
lut_file.close()


def write_cost_lookup_table(results, environment, site_radius,
frequency, bandwidth, generation, ant_height,
directory, filename, parameters):
def write_cost_lookup_table(results, directory, filename):
"""
Write the main, comprehensive lookup table for all environments,
Expand All @@ -522,28 +520,12 @@ def write_cost_lookup_table(results, environment, site_radius,
----------
results : list of dicts
Contains all results ready to be written.
environment : string
Either urban, suburban or rural clutter type.
site_radius : int
Radius of site area in meters.
frequency : float
Spectral frequency of carrier band in GHz.
bandwidth : int
Channel bandwidth of carrier band in MHz.
generation : string
Either 4G or 5G depending on technology generation.
ant_height : int
Height of the transmitters modelled in meters.
directory : string
Folder the data will be written to.
filename : string
Name of the .csv file.
parameters : dict
Contains all necessary simulation parameters.
"""
sectors = parameters['sectorization']

if not os.path.exists(directory):
os.makedirs(directory)

Expand All @@ -556,6 +538,7 @@ def write_cost_lookup_table(results, environment, site_radius,
(
'results_type',
'strategy',
'environment',
'inter_site_distance_m',
'site_area_km2',
'sites_per_km2',
Expand All @@ -582,6 +565,7 @@ def write_cost_lookup_table(results, environment, site_radius,
(
result['results_type'],
result['strategy'],
result['environment'],
result['inter_site_distance'],
result['site_area_km2'],
result['sites_per_km2'],
Expand All @@ -603,6 +587,241 @@ def write_cost_lookup_table(results, environment, site_radius,
lut_file.close()


def write_export_strategy_costs(data_path, directory, filename):

data = []
isd = []

with open(data_path, 'r') as source:
reader = csv.DictReader(source)
for result in reader:
result = dict(result)
data.append({
'strategy': result['strategy'],
'inter_site_distance': int(result['inter_site_distance_m']),
'sector_antenna_costs_km2': float(result['ran_sector_antenna_costs_km2']),
'remote_radio_unit_costs_km2': float(result['ran_remote_radio_unit_costs_km2']),
'baseband_unit_costs_km2': float(result['ran_baseband_unit_costs_km2']),
'site_rental_km2': float(result['site_rental_km2']),
'tower_costs_km2': float(result['civil_tower_costs_km2']),
'civil_material_costs_km2': float(result['civil_material_costs_km2']),
'transportation_costs_km2': float(result['civil_transportation_costs_km2']),
'installation_costs_km2': float(result['civil_installation_costs_km2']),
'power_system_costs_km2': float(result['power_system_costs_km2']),
'fiber_backhaul_costs_km2': float(result['backhaul_fiber_backhaul_costs_km2']),
'router_costs_km2': float(result['backhaul_router_costs_km2']),
})
isd.append(int(result['inter_site_distance_m']))

bins = [
(0.5, 1.5),
(1.5, 2.5),
(2.5, 3.5),
(3.5, 4.5),
(4.5, 5.5),
]

strategies = [
'baseline',# 'Baseline (No Sharing)',
'passive_site_sharing',# 'Passive Site Sharing',
'passive_backhaul_sharing',# 'Passive Backhaul Sharing',
'active_moran',# 'Multi Operator RAN',
]

intermediate = []

#get the average values across strategies and each bin range
for strategy in strategies:
for lower, upper in bins:

ran_sector_antenna_costs_km2 = []
ran_remote_radio_unit_costs_km2 = []
ran_baseband_unit_costs_km2 = []
site_rental_km2 = []
civil_tower_costs_km2 = []
civil_material_costs_km2 = []
civil_transportation_costs_km2 = []
civil_installation_costs_km2 = []
power_system_costs_km2 = []
backhaul_fiber_backhaul_costs_km2 = []
backhaul_router_costs_km2 = []

for item in data:
if item['strategy'] == strategy:
if lower <= (int(item['inter_site_distance'])/1e3) < upper:
ran_sector_antenna_costs_km2.append(item['sector_antenna_costs_km2'])
ran_remote_radio_unit_costs_km2.append(item['remote_radio_unit_costs_km2'])
ran_baseband_unit_costs_km2.append(item['baseband_unit_costs_km2'])
site_rental_km2.append(item['site_rental_km2'])
civil_tower_costs_km2.append(item['tower_costs_km2'])
civil_material_costs_km2.append(item['civil_material_costs_km2'])
civil_transportation_costs_km2.append(item['transportation_costs_km2'])
civil_installation_costs_km2.append(item['installation_costs_km2'])
power_system_costs_km2.append(item['power_system_costs_km2'])
backhaul_fiber_backhaul_costs_km2.append(item['fiber_backhaul_costs_km2'])
backhaul_router_costs_km2.append(item['router_costs_km2'])

if len(ran_sector_antenna_costs_km2) == 0:
continue

intermediate.append({
'Results Type': 'Raw ($/km2)',
'Strategy': strategy,
'ISD (km)': (lower + upper) / 2,
'RAN Antenna': sum(ran_sector_antenna_costs_km2) / len(ran_sector_antenna_costs_km2),
'RAN RRU': sum(ran_remote_radio_unit_costs_km2) / len(ran_remote_radio_unit_costs_km2),
'RAN BBU': sum(ran_baseband_unit_costs_km2) / len(ran_baseband_unit_costs_km2),
'Site Rental': sum(site_rental_km2) / len(site_rental_km2),
'Civil Tower': sum(civil_tower_costs_km2) / len(civil_tower_costs_km2),
'Civil Material': sum(civil_material_costs_km2) / len(civil_material_costs_km2),
'Civil Transport': sum(civil_transportation_costs_km2) / len(civil_transportation_costs_km2),
'Civil Installation': sum(civil_installation_costs_km2) / len(civil_installation_costs_km2),
'Power System': sum(power_system_costs_km2) / len(power_system_costs_km2),
'Backhaul Fiber': sum(backhaul_fiber_backhaul_costs_km2) / len(backhaul_fiber_backhaul_costs_km2),
'Backhaul Router': sum(backhaul_router_costs_km2) / len(backhaul_router_costs_km2),
})

unique_isd = set()
unique_strategies = set()
cost_saving_by_strategy = []
results = []

#write results out by individual equipment type
for item in intermediate:

ran_cost = 0
site_rental = 0
civils_cost = 0
power_cost = 0
backhaul_cost = 0
total_cost = 0
for key, value in item.items():
if key == 'ISD (km)':
unique_isd.add(value)
if key == 'Strategy':
unique_strategies.add(value)
if key == 'ISD (km)' or key == 'Strategy' or key == 'Results Type':
pass
else:
if key.startswith('RAN'):
ran_cost += value
if key.startswith('Site'):
site_rental += value
if key.startswith('Civil'):
civils_cost += value
if key.startswith('Power'):
power_cost += value
if key.startswith('Backhaul'):
backhaul_cost += value
total_cost += value

results.append({
'Results Type': item['Results Type'],
'Strategy': item['Strategy'],
'ISD (km)': item['ISD (km)'],
'RAN': round(ran_cost),
'Site Rental': round(site_rental),
'Civil': round(civils_cost),
'Power': round(power_cost),
'Backhaul': round(backhaul_cost),
'Total': round(total_cost),
})

results.append({
'Results Type': 'Percentage (%)',
'Strategy': item['Strategy'],
'ISD (km)': item['ISD (km)'],
'RAN': round(ran_cost / total_cost * 100, 2),
'Site Rental': round(site_rental / total_cost * 100, 2),
'Civil': round(civils_cost / total_cost * 100, 2),
'Power': round(power_cost / total_cost * 100, 2),
'Backhaul': round(backhaul_cost / total_cost * 100, 2),
'Total': 100
})

if item['Results Type'] == 'Raw ($/km2)':
cost_saving_by_strategy.append({
'Strategy': item['Strategy'],
'ISD (km)': item['ISD (km)'],
'Total': total_cost,
})

results_to_write = []
for strategy in list(unique_strategies):
for isd in list(unique_isd):
for item in cost_saving_by_strategy:
if item['Strategy'] == 'baseline' and item['ISD (km)'] == isd:
baseline_total_cost = item['Total']
for item in cost_saving_by_strategy:
if item['Strategy'] == strategy and item['ISD (km)'] == isd:
total_cost = item['Total']
if strategy == 'baseline':
saving = 0
else:
saving = 100 - round(total_cost / baseline_total_cost * 100, 2)

for item in results:
if item['Strategy'] == strategy and item['ISD (km)'] == isd:
item['Saving on Baseline (%)'] = saving
results_to_write.append(item)

baseline_total_cost = 0

if not os.path.exists(directory):
os.makedirs(directory)

directory = os.path.join(directory, filename)

if not os.path.exists(directory):
lut_file = open(directory, 'w', newline='')
lut_writer = csv.writer(lut_file)
lut_writer.writerow(
(
'Results Type',
'Strategy',
'ISD (km)',
'RAN',
'Site Rental',
'Civils',
'Power',
'Backhaul',
'Total',
'Saving (%)',
)
)
else:
lut_file = open(directory, 'a', newline='')
lut_writer = csv.writer(lut_file)

for result in results_to_write:

if result['Strategy'] == 'baseline':
strategy = 'Baseline (No Sharing)'
elif result['Strategy'] == 'passive_site_sharing':
strategy = 'Passive Site Sharing'
elif result['Strategy'] == 'passive_backhaul_sharing':
strategy = 'Passive Backhaul Sharing'
elif result['Strategy'] == 'active_moran':
strategy = 'Multi-Operator RAN'

lut_writer.writerow(
(
result['Results Type'],
strategy,
result['ISD (km)'],
round(result['RAN'], 2),
round(result['Site Rental'], 2),
round(result['Civil'], 2),
round(result['Power'], 2),
round(result['Backhaul'], 2),
round(result['Total'], 2),
round(result['Saving (%)'], 2),
)
)

lut_file.close()


def write_shapefile(data, directory, filename, crs):
"""
Expand Down Expand Up @@ -676,21 +895,21 @@ def run_simulator(parameters, spectrum_portfolio,
projected_crs
)

receivers = generate_receivers(site_area, SIMULATION_PARAMETERS, 1)
receivers = generate_receivers(site_area, PARAMETERS, 1)

for frequency, bandwidth, generation in spectrum_portfolio:
for ant_height in ant_heights:

MANAGER = SimulationManager(
transmitter, interfering_transmitters, receivers,
site_area, SIMULATION_PARAMETERS
site_area, PARAMETERS
)

results = MANAGER.estimate_link_budget(
frequency, bandwidth, generation, ant_height,
environment,
MODULATION_AND_CODING_LUT,
SIMULATION_PARAMETERS
PARAMETERS
)

folder = os.path.join(BASE_PATH, '..', 'results', 'full_tables')
Expand Down Expand Up @@ -720,12 +939,9 @@ def run_simulator(parameters, spectrum_portfolio,
site_radius, environment
)

write_cost_lookup_table(percentile_site_results, environment,
site_radius, frequency, bandwidth, generation,
ant_height, results_directory,
write_cost_lookup_table(percentile_site_results, results_directory,
'percentile_{}_capacity_lut.csv'.format(
parameters['percentile']),
parameters
parameters['percentile'])
)

geojson_receivers = convert_results_geojson(results)
Expand Down Expand Up @@ -760,10 +976,15 @@ def run_simulator(parameters, spectrum_portfolio,
projected_crs
)

write_export_strategy_costs(os.path.join(results_directory,
'percentile_{}_capacity_lut.csv'.format(PARAMETERS['percentile'])),
results_directory,
'aggregate_strategy_costs.csv'.format(PARAMETERS['percentile'])
)

if __name__ == '__main__':

SIMULATION_PARAMETERS = {
PARAMETERS = {
'iterations': 5,
'seed_value1': 1,
'seed_value2': 2,
Expand All @@ -784,7 +1005,7 @@ def run_simulator(parameters, spectrum_portfolio,
'network_load': 50,
'percentile': 50,
'sectorization': 3,
'overbooking_factor': 50,
#'overbooking_factor': 50,
'mnos': 2,
'asset_lifetime': 10,
'discount_rate': 3.5,
Expand Down Expand Up @@ -861,7 +1082,7 @@ def generate_site_radii(min, max, increment):
for n in range(min, max, increment):
yield n

INCREMENT = (400, 5800, 200)
INCREMENT = (400, 5400, 400)

SITE_RADII = {
'urban':
Expand All @@ -873,7 +1094,7 @@ def generate_site_radii(min, max, increment):
}

run_simulator(
SIMULATION_PARAMETERS,
PARAMETERS,
SPECTRUM_PORTFOLIO,
ANT_HEIGHT,
SITE_RADII,
Expand Down
2 changes: 1 addition & 1 deletion tests/conftest.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -397,7 +397,7 @@ def setup_costs():
'civil_materials': 5000,
'transportation': 10000,
'installation': 5000,
'site_rental': 15000,
'site_rental': 9600,
'power_generator_battery_system': 5000,
'high_speed_backhaul_hub': 15000,
'router': 2000,
Expand Down
Binary file modified tests/cost_calculation_validation.xlsx
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