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#!/usr/bin/env python3
from dfatool.functions import StaticFunction
from dfatool.loader import TimingData, pta_trace_to_aggregate
from dfatool.model import AnalyticModel
import os
import unittest
class TestModels(unittest.TestCase):
def test_model_singlefile_rf24(self):
raw_data = TimingData(["test-data/20190815_111745_nRF24_no-rx.json"])
preprocessed_data = raw_data.get_preprocessed_data()
by_name, parameters, arg_count = pta_trace_to_aggregate(preprocessed_data)
model = AnalyticModel(by_name, parameters, arg_count)
self.assertEqual(model.names, "setPALevel setRetries setup write".split(" "))
static_model = model.get_static()
self.assertAlmostEqual(static_model("setPALevel", "duration"), 146, places=0)
self.assertAlmostEqual(static_model("setRetries", "duration"), 73, places=0)
self.assertAlmostEqual(static_model("setup", "duration"), 6533, places=0)
self.assertAlmostEqual(static_model("write", "duration"), 12634, places=0)
for transition in "setPALevel setRetries setup write".split(" "):
self.assertAlmostEqual(
model.attr_by_name[transition]["duration"].stats.param_dependence_ratio(
"channel"
),
0,
places=2,
)
param_model, param_info = model.get_fitted()
self.assertIsInstance(param_info("setPALevel", "duration"), StaticFunction)
self.assertIsInstance(param_info("setRetries", "duration"), StaticFunction)
self.assertIsInstance(param_info("setup", "duration"), StaticFunction)
self.assertEqual(
param_info("write", "duration").model_function,
"0 + regression_arg(0) + regression_arg(1) * parameter(max_retry_count) + regression_arg(2) * parameter(retry_delay) + regression_arg(3) * function_arg(1) + regression_arg(4) * parameter(max_retry_count) * parameter(retry_delay) + regression_arg(5) * parameter(max_retry_count) * function_arg(1) + regression_arg(6) * parameter(retry_delay) * function_arg(1) + regression_arg(7) * parameter(max_retry_count) * parameter(retry_delay) * function_arg(1)",
)
self.assertAlmostEqual(
param_info("write", "duration").model_args[0], 1281, places=0
)
self.assertAlmostEqual(
param_info("write", "duration").model_args[1], 464, places=0
)
self.assertAlmostEqual(
param_info("write", "duration").model_args[2], 1, places=0
)
self.assertAlmostEqual(
param_info("write", "duration").model_args[3], -9, places=0
)
self.assertAlmostEqual(
param_info("write", "duration").model_args[4], 1, places=0
)
self.assertAlmostEqual(
param_info("write", "duration").model_args[5], 0, places=0
)
self.assertAlmostEqual(
param_info("write", "duration").model_args[6], 0, places=0
)
self.assertAlmostEqual(
param_info("write", "duration").model_args[7], 0, places=0
)
def test_dependent_parameter_pruning(self):
raw_data = TimingData(["test-data/20190815_103347_nRF24_no-rx.json"])
preprocessed_data = raw_data.get_preprocessed_data()
by_name, parameters, arg_count = pta_trace_to_aggregate(preprocessed_data)
model = AnalyticModel(by_name, parameters, arg_count)
self.assertEqual(
model.names, "getObserveTx setPALevel setRetries setup write".split(" ")
)
static_model = model.get_static()
self.assertAlmostEqual(static_model("getObserveTx", "duration"), 75, places=0)
self.assertAlmostEqual(static_model("setPALevel", "duration"), 146, places=0)
self.assertAlmostEqual(static_model("setRetries", "duration"), 73, places=0)
self.assertAlmostEqual(static_model("setup", "duration"), 6533, places=0)
self.assertAlmostEqual(static_model("write", "duration"), 12634, places=0)
for transition in "getObserveTx setPALevel setRetries setup write".split(" "):
self.assertAlmostEqual(
model.attr_by_name[transition]["duration"].stats.param_dependence_ratio(
"channel"
),
0,
places=2,
)
param_model, param_info = model.get_fitted()
self.assertIsInstance(param_info("getObserveTx", "duration"), StaticFunction)
self.assertIsInstance(param_info("setPALevel", "duration"), StaticFunction)
self.assertIsInstance(param_info("setRetries", "duration"), StaticFunction)
self.assertIsInstance(param_info("setup", "duration"), StaticFunction)
self.assertEqual(
param_info("write", "duration").model_function,
"0 + regression_arg(0) + regression_arg(1) * parameter(max_retry_count) + regression_arg(2) * parameter(retry_delay) + regression_arg(3) * function_arg(1) + regression_arg(4) * parameter(max_retry_count) * parameter(retry_delay) + regression_arg(5) * parameter(max_retry_count) * function_arg(1) + regression_arg(6) * parameter(retry_delay) * function_arg(1) + regression_arg(7) * parameter(max_retry_count) * parameter(retry_delay) * function_arg(1)",
)
self.assertAlmostEqual(
param_info("write", "duration").model_args[0], 1282, places=0
)
self.assertAlmostEqual(
param_info("write", "duration").model_args[1], 463, places=0
)
self.assertAlmostEqual(
param_info("write", "duration").model_args[2], 1, places=0
)
self.assertAlmostEqual(
param_info("write", "duration").model_args[3], -9, places=0
)
self.assertAlmostEqual(
param_info("write", "duration").model_args[4], 1, places=0
)
self.assertAlmostEqual(
param_info("write", "duration").model_args[5], 0, places=0
)
self.assertAlmostEqual(
param_info("write", "duration").model_args[6], 0, places=0
)
self.assertAlmostEqual(
param_info("write", "duration").model_args[7], 0, places=0
)
def test_function_override(self):
os.environ["DFATOOL_NO_DECISIONTREES"] = "1"
raw_data = TimingData(["test-data/20190815_122531_nRF24_no-rx.json"])
preprocessed_data = raw_data.get_preprocessed_data()
by_name, parameters, arg_count = pta_trace_to_aggregate(preprocessed_data)
model = AnalyticModel(
by_name,
parameters,
arg_count,
function_override={
(
"write",
"duration",
): "(parameter(auto_ack!) * (regression_arg(0) + regression_arg(1) * parameter(max_retry_count) + regression_arg(2) * parameter(retry_delay) + regression_arg(3) * parameter(max_retry_count) * parameter(retry_delay))) + ((1 - parameter(auto_ack!)) * regression_arg(4))"
},
)
self.assertEqual(
model.names, "setAutoAck setPALevel setRetries setup write".split(" ")
)
static_model = model.get_static()
self.assertAlmostEqual(static_model("setAutoAck", "duration"), 72, places=0)
self.assertAlmostEqual(static_model("setPALevel", "duration"), 146, places=0)
self.assertAlmostEqual(static_model("setRetries", "duration"), 73, places=0)
self.assertAlmostEqual(static_model("setup", "duration"), 6533, places=0)
self.assertAlmostEqual(static_model("write", "duration"), 1181, places=0)
for transition in "setAutoAck setPALevel setRetries setup write".split(" "):
self.assertAlmostEqual(
model.attr_by_name[transition]["duration"].stats.param_dependence_ratio(
"channel"
),
0,
places=2,
)
param_model, param_info = model.get_fitted()
self.assertIsInstance(param_info("setAutoAck", "duration"), StaticFunction)
self.assertIsInstance(param_info("setPALevel", "duration"), StaticFunction)
self.assertIsInstance(param_info("setRetries", "duration"), StaticFunction)
self.assertIsInstance(param_info("setup", "duration"), StaticFunction)
self.assertEqual(
param_info("write", "duration").model_function,
"(parameter(auto_ack!) * (regression_arg(0) + regression_arg(1) * parameter(max_retry_count) + regression_arg(2) * parameter(retry_delay) + regression_arg(3) * parameter(max_retry_count) * parameter(retry_delay))) + ((1 - parameter(auto_ack!)) * regression_arg(4))",
)
self.assertAlmostEqual(
param_info("write", "duration").model_args[0], 1162, places=0
)
self.assertAlmostEqual(
param_info("write", "duration").model_args[1], 464, places=0
)
self.assertAlmostEqual(
param_info("write", "duration").model_args[2], 1, places=0
)
self.assertAlmostEqual(
param_info("write", "duration").model_args[3], 1, places=0
)
self.assertAlmostEqual(
param_info("write", "duration").model_args[4], 1086, places=0
)
os.environ.pop("DFATOOL_NO_DECISIONTREES")
if __name__ == "__main__":
unittest.main()
|
