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Commit 5810b574 authored by markn92's avatar markn92
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evaluation/configs/example_rank.yaml
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...@@ -8,9 +8,9 @@ maps: ...@@ -8,9 +8,9 @@ maps:
queries_per_rank: 10 queries_per_rank: 10
ranks: [2, 4, 6, 8] ranks: [2, 4, 6, 8]
setups: setups:
- mu_s: 300 # Start and Target Soc - mu_s: 40 # Start and Target Soc
mu_t: 0 mu_t: 0
capacity: 300 # kWh capacity: 40 # kWh
consumption: consumption:
type: distance type: distance
consumption_coefficient: 0.1 # kWh/s consumption_coefficient: 0.5 # kWh/km = Wh/m
evaluation/run.py
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...@@ -37,8 +37,9 @@ def apply_conversions(conf): ...@@ -37,8 +37,9 @@ def apply_conversions(conf):
"""kWh to Wh""" """kWh to Wh"""
for setup in conf['setups']: for setup in conf['setups']:
setup['capacity'] = 1000 * setup['capacity'] setup['capacity'] = 1000 * setup['capacity']
setup['consumption']['consumption_coefficient'] = \ if setup['consumption'].get('type') == 'time':
1000 * setup['consumption']['consumption_coefficient'] setup['consumption']['consumption_coefficient'] = \
1000 * setup['consumption']['consumption_coefficient']
setup['mu_s'] = 1000 * setup['mu_s'] setup['mu_s'] = 1000 * setup['mu_s']
setup['mu_t'] = 1000 * setup['mu_t'] setup['mu_t'] = 1000 * setup['mu_t']
return conf return conf
......
evaluation/statistics.ipynb 0 → 100644
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%% Cell type:code id: tags:
``` python
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from pathlib import Path
```
%% Cell type:code id: tags:
``` python
# Paths to Benchmark Results
result_dir = Path('./results')
example_init = result_dir.joinpath('example_init/init')
example_init_query = result_dir.joinpath('example_init_query/queries')
example_init_rank = result_dir.joinpath('example_rank/ranked')
```
%% Cell type:code id: tags:
``` python
data = {
'init': example_init.joinpath('init.csv'),
'insert': example_init.joinpath('insert.csv'),
'init_charge_queries': example_init_query.joinpath('charge.csv'),
'charge_ranked': example_init_rank.joinpath('charge.csv'),
'classic_ranked': example_init_rank.joinpath('classic.csv')
}
```
%% Cell type:code id: tags:
``` python
for key, path in data.items():
data[key] = pd.read_csv(path,dtype={'start_node': str, 'target_node': str})
```
%% Cell type:markdown id: tags:
## Ranked Stats
%% Cell type:code id: tags:
``` python
ranks = np.log2(data['classic_ranked']['dijkstra_rank'])
```
%% Cell type:code id: tags:
``` python
fig = plt.figure()
for k in ['charge_ranked']:
data[k]['rank'] = ranks
_means = data[k].groupby(['rank']).mean()
_std = data[k].groupby(['rank']).std()
_x = _means.index
_y = _means['query_time']
_yerr = _std['query_time']
plt.errorbar(_x, _y, yerr=_yerr,fmt='o-')
plt.show()
```
%% Output
%% Cell type:markdown id: tags:
## Gasstation
%% Cell type:code id: tags:
``` python
data['init']
```
%% Output
time_contracted_graph time_state_graph nodes_state_graph \
0 0.000136 0.000030 1
1 0.323515 0.000028 2
2 9.928760 0.000098 6
3 9.078340 0.000190 12
4 31.818989 0.000110 8
5 62.850130 0.000063 10
edges_state_graph nodes_contracted_graph edges_contracted_graph \
0 0 1 0
1 0 2 0
2 3 4 1
3 9 6 3
4 2 8 1
5 0 10 0
charging_stations
0 1
1 2
2 4
3 6
4 8
5 10
%% Cell type:code id: tags:
``` python
fig = plt.figure()
x = data['init']['charging_stations']
time_contracted=data['init']['time_contracted_graph']
time_state_graph = data['init']['time_state_graph']
plt.bar(x, time_contracted)
plt.bar(x, time_state_graph)
charge_query_times = data['init_charge_queries'].groupby('charging_stations').mean()
charge_query_times_std = data['init_charge_queries'].groupby('charging_stations').std()
plt.errorbar(x, charge_query_times['query_time'], yerr=charge_query_times_std['query_time'], fmt='bo')
plt.show()
```
%% Output
evrouting/graph_tools.py
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...@@ -57,7 +57,7 @@ def sum_weights(G, path, weight: str) -> float: ...@@ -57,7 +57,7 @@ def sum_weights(G, path, weight: str) -> float:
def consumption_function_distance_factory(consumption: float) -> ConsumptionFunction: def consumption_function_distance_factory(consumption: float) -> ConsumptionFunction:
""" """
:param consumption: in kWh/km :param consumption: in kWh/m
""" """
def c(G, u, v): def c(G, u, v):
......
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