def run_2(num_of_agents, noise, values):
print('start calculating agents-{0} , noise-{1}, {2}'.format(num_of_agents, noise, datetime.utcnow()))
identical_values = numbersUtils.values_to_allocations(numbersUtils.noisy_values_array(values, 0, None, num_of_agents))
noise_values = numbersUtils.values_to_allocations(numbersUtils.noisy_values_array(values, noise, None, num_of_agents))
index_to_location_type = envinfluence.index_to_location_type(values, envinfluence. LOCATION_TYPES())
env_influence_values = numbersUtils.values_to_allocations(numbersUtils.preferences_values_array(values, index_to_location_type, None, num_of_agents))
ldResults = calc_single_row(num_of_agents, noise, deepcopy(noise_values), deepcopy(identical_values), deepcopy(env_influence_values), LastDiminisher.last_diminisher_allocation)
print('ldResults calculated {0}'.format(datetime.utcnow()))
evenPazResults = calc_single_row(num_of_agents, noise, deepcopy(noise_values), deepcopy(identical_values), deepcopy(env_influence_values), evenpazalg.even_paz_dividion)
print('evenPazResults calculated {0}'.format(datetime.utcnow()))
return evenPazResults,ldResults
def run_ex_for_params(num_of_agents, noise, values):
results_by_exp_type = {}
for exp_type in expType.ExperimentType:
results_by_exp_type[exp_type] =[]
identical_values = numbersUtils.noisy_values_array(values, 0, None, num_of_agents)
for exp in range(EXPERIMENTS_PER_CELL):
noise_values = numbersUtils.noisy_values_array(values, noise, None, num_of_agents)
allocations1 = numbersUtils.values_to_allocations(noise_values)
identical_allocation_even_paz = numbersUtils.values_to_allocations(identical_values)
#even paz..
results_even_paz = calc_results_with_exchnages(evenpazalg.even_paz_dividion, expType.ExperimentType.even_paz, expType.ExperimentType.even_paz_exchange_jealous, allocations1,
num_of_agents, noise, None, identical_allocation_even_paz, expType.ExperimentType.even_paz_appraiser, results_by_exp_type)
allocations2 = numbersUtils.values_to_allocations(noise_values)
identical_allocation_last_diminisher = numbersUtils.values_to_allocations(identical_values)
#last diminisher
calc_results_with_exchnages(LastDiminisher.last_diminisher_allocation, expType.ExperimentType.last_diminisher, expType.ExperimentType.last_diminisher_exchange_jealous,
allocations2, num_of_agents, noise, None, identical_allocation_last_diminisher, expType.ExperimentType.last_diminisher_appraiser, results_by_exp_type)
#env influence
index_to_location_type = envinfluence.index_to_location_type(values, envinfluence. LOCATION_TYPES())
env_influence_values = numbersUtils.preferences_values_array(values, index_to_location_type, None, num_of_agents)
#even paz
even_paz_env_allocations = numbersUtils.values_to_allocations(env_influence_values)
calc_results_with_exchnages(evenpazalg.even_paz_dividion, expType.ExperimentType.even_paz_env_influence, expType.ExperimentType.even_paz_env_influence_exchange,
even_paz_env_allocations, num_of_agents, 0, None, None, None, results_by_exp_type)
#last diminisher
last_diminisher_env_allocations = numbersUtils.values_to_allocations(env_influence_values)
calc_results_with_exchnages(LastDiminisher.last_diminisher_allocation, expType.ExperimentType.last_diminisher_env_influence, expType.ExperimentType.last_diminisher_env_influence_exchange,
last_diminisher_env_allocations, num_of_agents, 0, None, None, None, results_by_exp_type)
#fraud agent
for i in range(num_of_agents):
identical_allocation_last_diminisher_i = numbersUtils.values_to_allocations(identical_values)
allocations_even_paz_fraud = numbersUtils.values_to_allocations(noise_values)
calc_results_with_exchnages(evenpazalg.even_paz_dividion, expType.ExperimentType.even_paz_fraud_agent_index,
expType.ExperimentType.even_paz_fraud_agent_index_with_exchange, allocations_even_paz_fraud, num_of_agents, noise, i,
identical_allocation_last_diminisher_i, expType.ExperimentType.even_paz_fraud_identical, results_by_exp_type)
allocations_last_diminisher_fraud = numbersUtils.values_to_allocations(noise_values)
calc_results_with_exchnages(LastDiminisher.last_diminisher_allocation, expType.ExperimentType.last_diminisher_fraud_agent_index,
expType.ExperimentType.last_diminisher_fraud_agent_index_with_exchange, allocations_last_diminisher_fraud, num_of_agents, noise, i,
identical_allocation_last_diminisher_i, expType.ExperimentType.last_diminisher_fraud_identical, results_by_exp_type)
#calc mid
for type, results in results_by_exp_type.items():
for result in results:
#todo: calc average from same type of alg..
pass
return results_by_exp_type