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https://github.com/gsi-upm/soil
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fc48ed7e09
Now the environment does not deal with history directly, it delegates it to a specific class. The analysis also uses history instances instead of either using the database directly or creating a proxy environment. This should make it easier to change the implementation in the future. In fact, the change was motivated by the large size of the csv files in previous versions. This new implementation only stores results in deltas, and it fills any necessary values when needed.
91 lines
2.4 KiB
Python
91 lines
2.4 KiB
Python
from unittest import TestCase
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import os
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import pandas as pd
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import yaml
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from functools import partial
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from os.path import join
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from soil import simulation, analysis, agents
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ROOT = os.path.abspath(os.path.dirname(__file__))
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class Ping(agents.FSM):
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defaults = {
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'count': 0,
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}
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@agents.default_state
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@agents.state
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def even(self):
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self['count'] += 1
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return self.odd
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@agents.state
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def odd(self):
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self['count'] += 1
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return self.even
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class TestAnalysis(TestCase):
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# Code to generate a simple sqlite history
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def setUp(self):
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"""
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The initial states should be applied to the agent and the
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agent should be able to update its state."""
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config = {
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'name': 'analysis',
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'dry_run': True,
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'seed': 'seed',
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'network_params': {
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'generator': 'complete_graph',
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'n': 2
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},
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'agent_type': Ping,
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'states': [{'interval': 1}, {'interval': 2}],
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'max_time': 30,
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'num_trials': 1,
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'environment_params': {
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}
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}
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s = simulation.from_config(config)
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self.env = s.run_simulation()[0]
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def test_saved(self):
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env = self.env
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assert env.get_agent(0)['count', 0] == 1
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assert env.get_agent(0)['count', 29] == 30
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assert env.get_agent(1)['count', 0] == 1
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assert env.get_agent(1)['count', 29] == 15
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assert env['env', 29, None]['SEED'] == env['env', 29, 'SEED']
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def test_count(self):
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env = self.env
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df = analysis.read_sql(env._history._db)
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res = analysis.get_count(df, 'SEED', 'id')
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assert res['SEED']['seedanalysis_trial_0'].iloc[0] == 1
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assert res['SEED']['seedanalysis_trial_0'].iloc[-1] == 1
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assert res['id']['odd'].iloc[0] == 2
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assert res['id']['even'].iloc[0] == 0
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assert res['id']['odd'].iloc[-1] == 1
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assert res['id']['even'].iloc[-1] == 1
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def test_value(self):
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env = self.env
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df = analysis.read_sql(env._history._db)
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res_sum = analysis.get_value(df, 'count')
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assert res_sum['count'].iloc[0] == 2
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import numpy as np
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res_mean = analysis.get_value(df, 'count', aggfunc=np.mean)
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assert res_mean['count'].iloc[0] == 1
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res_total = analysis.get_value(df)
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res_total['SEED'].iloc[0] == 'seedanalysis_trial_0'
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