| #!/usr/bin/env python3.4 |
| # |
| # Copyright 2022 - The Android Open Source Project |
| # |
| # Licensed under the Apache License, Version 2.0 (the 'License'); |
| # you may not use this file except in compliance with the License. |
| # You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an 'AS IS' BASIS, |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| |
| import collections |
| import csv |
| import itertools |
| import numpy |
| import json |
| import os |
| from acts import context |
| from acts import base_test |
| from acts.metrics.loggers.blackbox import BlackboxMappedMetricLogger |
| from acts_contrib.test_utils.wifi import wifi_performance_test_utils as wputils |
| from acts_contrib.test_utils.wifi.wifi_performance_test_utils.bokeh_figure import BokehFigure |
| from CellularLtePlusFr1PeakThroughputTest import CellularFr1SingleCellPeakThroughputTest |
| |
| from functools import partial |
| |
| |
| class CellularFr1RvrTest(CellularFr1SingleCellPeakThroughputTest): |
| """Class to test single cell FR1 NSA sensitivity""" |
| |
| def __init__(self, controllers): |
| base_test.BaseTestClass.__init__(self, controllers) |
| self.testcase_metric_logger = ( |
| BlackboxMappedMetricLogger.for_test_case()) |
| self.testclass_metric_logger = ( |
| BlackboxMappedMetricLogger.for_test_class()) |
| self.publish_testcase_metrics = True |
| self.testclass_params = self.user_params['nr_rvr_test_params'] |
| self.tests = self.generate_test_cases( |
| channel_list=['LOW', 'MID', 'HIGH'], |
| nr_ul_mcs=4, |
| lte_dl_mcs_table='QAM256', |
| lte_dl_mcs=4, |
| lte_ul_mcs_table='QAM256', |
| lte_ul_mcs=4, |
| transform_precoding=0) |
| |
| def process_testclass_results(self): |
| pass |
| |
| def process_testcase_results(self): |
| if self.current_test_name not in self.testclass_results: |
| return |
| testcase_data = self.testclass_results[self.current_test_name] |
| results_file_path = os.path.join( |
| context.get_current_context().get_full_output_path(), |
| '{}.json'.format(self.current_test_name)) |
| with open(results_file_path, 'w') as results_file: |
| json.dump(wputils.serialize_dict(testcase_data), |
| results_file, |
| indent=4) |
| |
| average_throughput_list = [] |
| theoretical_throughput_list = [] |
| nr_cell_index = testcase_data['testcase_params']['endc_combo_config']['lte_cell_count'] |
| cell_power_list = testcase_data['testcase_params']['cell_power_sweep'][nr_cell_index] |
| for result in testcase_data['results']: |
| average_throughput_list.append( |
| result['throughput_measurements']['nr_tput_result']['total']['DL']['average_tput']) |
| theoretical_throughput_list.append( |
| result['throughput_measurements']['nr_tput_result']['total']['DL']['theoretical_tput']) |
| padding_len = len(cell_power_list) - len(average_throughput_list) |
| average_throughput_list.extend([0] * padding_len) |
| theoretical_throughput_list.extend([0] * padding_len) |
| |
| testcase_data['average_throughput_list'] = average_throughput_list |
| testcase_data[ |
| 'theoretical_throughput_list'] = theoretical_throughput_list |
| testcase_data['cell_power_list'] = cell_power_list |
| |
| plot = BokehFigure( |
| title='Band {} - RvR'.format(testcase_data['testcase_params']['endc_combo_config']['cell_list'][nr_cell_index]['band']), |
| x_label='Cell Power (dBm)', |
| primary_y_label='PHY Rate (Mbps)') |
| |
| plot.add_line( |
| testcase_data['cell_power_list'], |
| testcase_data['average_throughput_list'], |
| 'Average Throughput', |
| width=1) |
| plot.add_line( |
| testcase_data['cell_power_list'], |
| testcase_data['theoretical_throughput_list'], |
| 'Average Throughput', |
| width=1, |
| style='dashed') |
| plot.generate_figure() |
| output_file_path = os.path.join(self.log_path, '{}.html'.format(self.current_test_name)) |
| BokehFigure.save_figure(plot, output_file_path) |
| |
| |
| def get_per_cell_power_sweeps(self, testcase_params): |
| nr_cell_index = testcase_params['endc_combo_config']['lte_cell_count'] |
| start_atten = self.testclass_params['nr_cell_power_start'] |
| # get current cell power start |
| nr_cell_sweep = list( |
| numpy.arange(start_atten, |
| self.testclass_params['nr_cell_power_stop'], |
| self.testclass_params['nr_cell_power_step'])) |
| lte_sweep = [self.testclass_params['lte_cell_power'] |
| ] * len(nr_cell_sweep) |
| if nr_cell_index == 0: |
| cell_power_sweeps = [nr_cell_sweep] |
| else: |
| cell_power_sweeps = [lte_sweep, nr_cell_sweep] |
| return cell_power_sweeps |
| |
| def generate_test_cases(self, channel_list, **kwargs): |
| test_cases = [] |
| with open(self.testclass_params['nr_single_cell_configs'], |
| 'r') as csvfile: |
| test_configs = csv.DictReader(csvfile) |
| for test_config, channel in itertools.product( |
| test_configs, channel_list): |
| if int(test_config['skip_test']): |
| continue |
| endc_combo_config = self.generate_endc_combo_config( |
| test_config) |
| test_name = 'test_fr1_{}_{}'.format( |
| test_config['nr_band'], channel.lower()) |
| test_params = collections.OrderedDict( |
| endc_combo_config=endc_combo_config, |
| nr_dl_mcs=self.testclass_params['link_adaptation_config'], |
| **kwargs) |
| setattr(self, test_name, |
| partial(self._test_throughput_bler, test_params)) |
| test_cases.append(test_name) |
| return test_cases |
