MHOD: moved the p estimation to the end, need to fix the tests
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@ -133,19 +133,19 @@ def mhod(state_config, otf, window_sizes, bruteforce_step, learning_steps,
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state['acceptable_variances'] = estimation.init_variances(
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window_sizes, number_of_states)
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n = len(utilization)
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#n = len(utilization)
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for i, current_state in enumerate(utilization_to_states(state_config, utilization)):
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if i == n - 1:
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selected_windows = estimation.select_window(
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state['variances'],
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state['acceptable_variances'],
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window_sizes)
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p = estimation.select_best_estimates(
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state['estimate_windows'],
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selected_windows)
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# These two are saved for testing purposes
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state['selected_windows'] = selected_windows
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state['p'] = p
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# if i == n - 1:
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# selected_windows = estimation.select_window(
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# state['variances'],
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# state['acceptable_variances'],
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# window_sizes)
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# p = estimation.select_best_estimates(
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# state['estimate_windows'],
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# selected_windows)
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# # These two are saved for testing purposes
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# state['selected_windows'] = selected_windows
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# state['p'] = p
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state['request_windows'] = estimation.update_request_windows(
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state['request_windows'],
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@ -165,6 +165,17 @@ def mhod(state_config, otf, window_sizes, bruteforce_step, learning_steps,
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previous_state)
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previous_state = current_state
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selected_windows = estimation.select_window(
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state['variances'],
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state['acceptable_variances'],
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window_sizes)
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p = estimation.select_best_estimates(
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state['estimate_windows'],
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selected_windows)
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# These two are saved for testing purposes
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state['selected_windows'] = selected_windows
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state['p'] = p
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state_vector = build_state_vector(state_config, utilization)
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current_state = get_current_state(state_vector)
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state['state_history'].append(current_state)
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