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How to use load_file method in Airtest

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test_im_calculation.py

Source:test_im_calculation.py

1import argparse2import filecmp3import os4import pickle5import pytest6import numpy as np7from qcore.constants import Components8import IM_calculation.IM.im_calculation as calculate_ims9from qcore import utils, constants10from IM_calculation.test.test_common_set_up import INPUT, OUTPUT, compare_dicts, set_up11# This is a hack, to allow loading of the test pickle objects12import sys13import IM_calculation.IM as IM14sys.modules["IM"] = IM15PARSER = argparse.ArgumentParser()16BSC_PERIOD = [0.05, 0.1, 5.0, 10.0]17TEST_IMS = ["PGA", "PGV", "Ds575", "pSA"]18FAKE_DIR = (19    "fake_dir"20)  # should be created in set_up module and remove in tear_down module21utils.setup_dir("fake_dir")22@pytest.mark.parametrize(23    "test_period, test_extended, expected_period",24    [25        (BSC_PERIOD, False, np.array(BSC_PERIOD)),26        (BSC_PERIOD, True, np.unique(np.append(BSC_PERIOD, constants.EXT_PERIOD))),27    ],28)29def test_validate_period(test_period, test_extended, expected_period):30    assert all(31        np.equal(32            calculate_ims.validate_period(test_period, test_extended), expected_period33        )34    )35@pytest.mark.parametrize("test_path, test_file_type", [("asdf", "b"), (FAKE_DIR, "b")])36def test_validate_input_path_fail(test_path, test_file_type):37    with pytest.raises(SystemExit):38        calculate_ims.validate_input_path(PARSER, test_path, test_file_type)39def convert_str_comps_to_enum(expected_result):40    for station in expected_result.keys():41        for im in expected_result[station].keys():42            if im == "pSA":43                for comp in list(expected_result[station][im][1]):44                    expected_result[station][im][1][45                        Components.from_str(comp)46                    ] = expected_result[station][im][1][comp]47                    del expected_result[station][im][1][comp]48            else:49                for comp in list(expected_result[station][im]):50                    expected_result[station][im][51                        Components.from_str(comp)52                    ] = expected_result[station][im][comp]53                    del expected_result[station][im][comp]54class TestPickleTesting:55    def test_convert_str_comp(self, set_up):56        function = "convert_str_comp"57        for root_path in set_up:58            with open(59                os.path.join(root_path, INPUT, function + "_comp.P"), "rb"60            ) as load_file:61                comp = pickle.load(load_file)62            int_comp, str_comp = Components.get_comps_to_calc_and_store(comp)63            with open(64                os.path.join(root_path, OUTPUT, function + "_str_comp_for_int.P"), "rb"65            ) as load_file:66                expected_int_comp = pickle.load(load_file)67            with open(68                os.path.join(root_path, OUTPUT, function + "_str_comp.P"), "rb"69            ) as load_file:70                expected_str_comp = pickle.load(load_file)71            assert [x.str_value for x in int_comp] == expected_int_comp72            assert [x.str_value for x in str_comp] == expected_str_comp73    def test_array_to_dict(self, set_up):74        function = "array_to_dict"75        for root_path in set_up:76            with open(77                os.path.join(root_path, INPUT, function + "_value.P"), "rb"78            ) as load_file:79                value = pickle.load(load_file)80            with open(81                os.path.join(root_path, INPUT, function + "_comp.P"), "rb"82            ) as load_file:83                arg_comps = pickle.load(load_file)84            with open(85                os.path.join(root_path, INPUT, function + "_str_comp.P"), "rb"86            ) as load_file:87                str_comps = pickle.load(load_file)88            with open(89                os.path.join(root_path, INPUT, function + "_im.P"), "rb"90            ) as load_file:91                im = pickle.load(load_file)92            str_comps = [Components.from_str(x) for x in str_comps]93            arg_comps = [Components.from_str(x) for x in arg_comps]94            actual_value_dict = calculate_ims.array_to_dict(value, str_comps, im, arg_comps)95            with open(96                os.path.join(root_path, OUTPUT, function + "_value_dict.P"), "rb"97            ) as load_file:98                expected_value_dict = pickle.load(load_file)99            assert actual_value_dict == expected_value_dict100    def test_compute_measure_single(self, set_up):101        function = "compute_measure_single"102        for root_path in set_up:103            with open(104                os.path.join(root_path, INPUT, function + "_value_tuple.P"), "rb"105            ) as load_file:106                value_tuple = pickle.load(load_file)107            waveform, ims, comps, periods, str_comps = value_tuple108            im_options = {"pSA": periods}109            comps = [Components.from_str(x) for x in comps]110            str_comps = [Components.from_str(x) for x in str_comps]111            actual_result = calculate_ims.compute_measure_single(112                waveform, ims, comps, im_options, str_comps, (0,0)113            )114            with open(115                os.path.join(root_path, OUTPUT, function + "_result.P"), "rb"116            ) as load_file:117                expected_result = pickle.load(load_file)118                convert_str_comps_to_enum(expected_result)119                actual_expected_result = self.convert_to_results_dict(periods, expected_result)120            compare_dicts(actual_result, actual_expected_result)121    def test_get_bbseis(self, set_up):122        function = "get_bbseis"123        for root_path in set_up:124            with open(125                os.path.join(root_path, INPUT, function + "_selected_stations.P"), "rb"126            ) as load_file:127                stations = pickle.load(load_file)128            actual_converted_stations = calculate_ims.get_bbseis(129                os.path.join(root_path, INPUT, "BB.bin"), "binary", stations130            )[1]131            with open(132                os.path.join(root_path, OUTPUT, function + "_station_names.P"), "rb"133            ) as load_file:134                expected_converted_stations = pickle.load(load_file)135            assert actual_converted_stations == expected_converted_stations136    def test_compute_measures_multiprocess(self, set_up):137        function = "compute_measures_multiprocess"138        for root_path in set_up:139            input_path = os.path.join(root_path, INPUT, "BB.bin")140            with open(141                os.path.join(root_path, INPUT, function + "_file_type.P"), "rb"142            ) as load_file:143                file_type = pickle.load(load_file)144            with open(145                os.path.join(root_path, INPUT, function + "_wave_type.P"), "rb"146            ) as load_file:147                wave_type = pickle.load(load_file)148            with open(149                os.path.join(root_path, INPUT, function + "_ims.P"), "rb"150            ) as load_file:151                ims = pickle.load(load_file)152            with open(153                os.path.join(root_path, INPUT, function + "_comp.P"), "rb"154            ) as load_file:155                comp = pickle.load(load_file)156            with open(157                os.path.join(root_path, INPUT, function + "_period.P"), "rb"158            ) as load_file:159                period = pickle.load(load_file)160            with open(161                os.path.join(root_path, INPUT, function + "_identifier.P"), "rb"162            ) as load_file:163                identifier = pickle.load(load_file)164            with open(165                os.path.join(root_path, INPUT, function + "_rupture.P"), "rb"166            ) as load_file:167                rupture = pickle.load(load_file)168            with open(169                os.path.join(root_path, INPUT, function + "_run_type.P"), "rb"170            ) as load_file:171                run_type = pickle.load(load_file)172            with open(173                os.path.join(root_path, INPUT, function + "_version.P"), "rb"174            ) as load_file:175                version = pickle.load(load_file)176            with open(177                os.path.join(root_path, INPUT, function + "_process.P"), "rb"178            ) as load_file:179                process = pickle.load(load_file)180            with open(181                os.path.join(root_path, INPUT, function + "_simple_output.P"), "rb"182            ) as load_file:183                simple_output = pickle.load(load_file)184            station_names = ["099A"]185            output = root_path186            os.makedirs(os.path.join(output, "stations"), exist_ok=True)187            calculate_ims.compute_measures_multiprocess(188                input_path,189                file_type,190                wave_type,191                station_names,192                ims,193                comp,194                {"pSA": period},195                output,196                identifier,197                rupture,198                run_type,199                version,200                process,201                simple_output,202            )203    def test_get_result_filepath(self, set_up):204        function = "get_result_filepath"205        for root_path in set_up:206            with open(207                os.path.join(root_path, INPUT, function + "_output_folder.P"), "rb"208            ) as load_file:209                output_folder = pickle.load(load_file)210            with open(211                os.path.join(root_path, INPUT, function + "_arg_identifier.P"), "rb"212            ) as load_file:213                arg_identifier = pickle.load(load_file)214            with open(215                os.path.join(root_path, INPUT, function + "_suffix.P"), "rb"216            ) as load_file:217                suffix = pickle.load(load_file)218            actual_ret_val = calculate_ims.get_result_filepath(219                output_folder, arg_identifier, suffix220            )221            with open(222                os.path.join(root_path, OUTPUT, function + "_ret_val.P"), "rb"223            ) as load_file:224                expected_ret_val = pickle.load(load_file)225            assert actual_ret_val == expected_ret_val226    def test_write_result(self, set_up):227        function = "write_result"228        for root_path in set_up:229            with open(230                os.path.join(root_path, INPUT, function + "_period.P"), "rb"231            ) as load_file:232                period = pickle.load(load_file)233            with open(234                os.path.join(root_path, INPUT, function + "_result_dict.P"), "rb"235            ) as load_file:236                temp_result_dict = pickle.load(load_file)237                convert_str_comps_to_enum(temp_result_dict)238                result_dict = self.convert_to_results_dict(period, temp_result_dict, keep_ps=True)239            with open(240                os.path.join(root_path, INPUT, function + "_identifier.P"), "rb"241            ) as load_file:242                identifier = pickle.load(load_file)243            with open(244                os.path.join(root_path, INPUT, function + "_simple_output.P"), "rb"245            ) as load_file:246                simple_output = pickle.load(load_file)247            output_folder = root_path248            os.makedirs(249                os.path.join(output_folder, calculate_ims.OUTPUT_SUBFOLDER),250                exist_ok=True,251            )252            calculate_ims.write_result(result_dict, output_folder, identifier, simple_output)253            expected_output_path = calculate_ims.get_result_filepath(254                output_folder, identifier, ".csv"255            )256            actual_output_path = os.path.join(257                root_path, OUTPUT, function + "_outfile.csv"258            )259            expected_output = np.loadtxt(expected_output_path, delimiter=',',usecols=range(2,24), skiprows=1)260            actual_output = np.loadtxt(actual_output_path, delimiter=',',usecols=range(2,24), skiprows=1)261            assert np.isclose(expected_output, actual_output).all()262    def convert_to_results_dict(self, period, temp_result_dict, keep_ps=False):263        result_dict = {}264        for station in sorted(temp_result_dict):265            temp_result_dict[station]["pSA"] = temp_result_dict[station]["pSA"][1]266            for im in sorted(temp_result_dict[station]):267                for comp in temp_result_dict[station][im]:268                    if (station, comp.str_value) not in result_dict:269                        result_dict[(station, comp.str_value)] = {}270                    if im in calculate_ims.MULTI_VALUE_IMS:271                        for i, val in enumerate(period):272                            if keep_ps:273                                result_dict[(station, comp.str_value)][f"{im}_{str(val).replace('.', 'p')}"] = \274                                temp_result_dict[station][im][comp][i]275                            else:276                                result_dict[(station, comp.str_value)][f"{im}_{str(val)}"] = \277                                temp_result_dict[station][im][comp][i]278                    else:279                        result_dict[(station, comp.str_value)][im] = temp_result_dict[station][im][comp]280        return result_dict281    def test_generate_metadata(self, set_up):282        function = "generate_metadata"283        for root_path in set_up:284            with open(285                os.path.join(root_path, INPUT, function + "_identifier.P"), "rb"286            ) as load_file:287                identifier = pickle.load(load_file)288            with open(289                os.path.join(root_path, INPUT, function + "_rupture.P"), "rb"290            ) as load_file:291                rupture = pickle.load(load_file)292            with open(293                os.path.join(root_path, INPUT, function + "_run_type.P"), "rb"294            ) as load_file:295                run_type = pickle.load(load_file)296            with open(297                os.path.join(root_path, INPUT, function + "_version.P"), "rb"298            ) as load_file:299                version = pickle.load(load_file)300            # Save to the realisations folder that will be deleted after the run has finished301            output_folder = root_path302            calculate_ims.generate_metadata(303                output_folder, identifier, rupture, run_type, version304            )305            actual_output_path = calculate_ims.get_result_filepath(306                output_folder, identifier, "_imcalc.info"307            )308            expected_output_path = os.path.join(309                root_path, OUTPUT, function + "_outfile.info"310            )311            filecmp.cmp(actual_output_path, expected_output_path)312    def test_validate_input_path(self, set_up):313        function = "validate_input_path"314        for root_path in set_up:315            arg_input = os.path.join(root_path, INPUT, "BB.bin")316            with open(317                os.path.join(root_path, INPUT, function + "_arg_file_type.P"), "rb"318            ) as load_file:319                arg_file_type = pickle.load(load_file)320            calculate_ims.validate_input_path(PARSER, arg_input, arg_file_type)321            # Function does not return anything, only raises errors through the parser322    def test_validate_period(self, set_up):323        function = "validate_period"324        for root_path in set_up:325            with open(326                os.path.join(root_path, INPUT, function + "_arg_period.P"), "rb"327            ) as load_file:328                arg_period = pickle.load(load_file)329            with open(330                os.path.join(root_path, INPUT, function + "_arg_extended_period.P"),331                "rb",332            ) as load_file:333                arg_extended_period = pickle.load(load_file)334            actual_period = calculate_ims.validate_period(335                arg_period, arg_extended_period336            )337            with open(338                os.path.join(root_path, OUTPUT, function + "_period.P"), "rb"339            ) as load_file:340                expected_period = pickle.load(load_file)341            assert (actual_period == expected_period).all()342    def test_get_steps(self, set_up):343        function = "get_steps"344        for root_path in set_up:345            input_path = os.path.join(root_path, INPUT, "BB.bin")346            with open(347                os.path.join(root_path, INPUT, function + "_nps.P"), "rb"348            ) as load_file:349                nps = pickle.load(load_file)350            with open(351                os.path.join(root_path, INPUT, function + "_total_stations.P"), "rb"352            ) as load_file:353                total_stations = pickle.load(load_file)354            actual_steps = calculate_ims.get_steps(input_path, nps, total_stations)355            with open(356                os.path.join(root_path, OUTPUT, function + "_steps.P"), "rb"357            ) as load_file:358                expected_steps = pickle.load(load_file)...

test_intensity_measures.py

Source:test_intensity_measures.py

1import os2import pickle3import numpy as np4import pytest5from IM_calculation.IM import intensity_measures6from IM_calculation.test.test_common_set_up import INPUT, OUTPUT, set_up7def get_common_spectral_vals(root_path, function_name):8    with open(9        os.path.join(root_path, INPUT, function_name + "_acceleration.P"), "rb"10    ) as load_file:11        acc = pickle.load(load_file)12    with open(13        os.path.join(root_path, INPUT, function_name + "_period.P"), "rb"14    ) as load_file:15        period = pickle.load(load_file)16    with open(17        os.path.join(root_path, INPUT, function_name + "_NT.P"), "rb"18    ) as load_file:19        NT = pickle.load(load_file)20    with open(21        os.path.join(root_path, INPUT, function_name + "_DT.P"), "rb"22    ) as load_file:23        DT = pickle.load(load_file)24    return acc, period, NT, DT25def get_common_vals(root_path, function_name):26    with open(27        os.path.join(root_path, INPUT, function_name + "_acceleration.P"), "rb"28    ) as load_file:29        acc = pickle.load(load_file)30    with open(31        os.path.join(root_path, INPUT, function_name + "_times.P"), "rb"32    ) as load_file:33        times = pickle.load(load_file)34    return acc, times35def get_common_ds_vals(root_path, function_name):36    with open(37        os.path.join(root_path, INPUT, function_name + "_dt.P"), "rb"38    ) as load_file:39        dt = pickle.load(load_file)40    with open(41        os.path.join(root_path, INPUT, function_name + "_percLow.P"), "rb"42    ) as load_file:43        perc_low = pickle.load(load_file)44    with open(45        os.path.join(root_path, INPUT, function_name + "_percHigh.P"), "rb"46    ) as load_file:47        perc_high = pickle.load(load_file)48    return dt, perc_low, perc_high49def test_get_max_nd(set_up):50    function = "get_max_nd"51    for root_path in set_up:52        with open(53            os.path.join(root_path, INPUT, function + "_data.P"), "rb"54        ) as load_file:55            data = pickle.load(load_file)56        test_output = intensity_measures.get_max_nd(data)57        with open(58            os.path.join(root_path, OUTPUT, function + "_ret_val.P"), "rb"59        ) as load_file:60            bench_output = pickle.load(load_file)61        assert np.isclose(test_output, bench_output).all()62def test_get_spectral_acceleration(set_up):63    function = "get_spectral_acceleration"64    for root_path in set_up:65        acc, period, NT, DT = get_common_spectral_vals(root_path, function)66        test_output = intensity_measures.get_spectral_acceleration(67            acc, period, NT, DT, intensity_measures.calculate_Nstep(DT, NT)68        )69        with open(70            os.path.join(root_path, OUTPUT, function + "_ret_val.P"), "rb"71        ) as load_file:72            bench_output = pickle.load(load_file)73        assert np.isclose(test_output, bench_output).all()74def test_get_spectral_acceleration_nd(set_up):75    function = "get_spectral_acceleration_nd"76    for root_path in set_up:77        acc, period, NT, DT = get_common_spectral_vals(root_path, function)78        test_output = intensity_measures.get_spectral_acceleration_nd(79            acc, period, NT, DT80        )81        with open(82            os.path.join(root_path, OUTPUT, function + "_values.P"), "rb"83        ) as load_file:84            bench_output = pickle.load(load_file)85        assert np.isclose(test_output, bench_output).all()86def test_get_cumulative_abs_velocity_nd(set_up):87    function = "get_cumulative_abs_velocity_nd"88    for root_path in set_up:89        acc, times = get_common_vals(root_path, function)90        test_output = intensity_measures.get_cumulative_abs_velocity_nd(acc, times)91        with open(92            os.path.join(root_path, OUTPUT, function + "_ret_val.P"), "rb"93        ) as load_file:94            bench_output = pickle.load(load_file)95        assert np.isclose(test_output, bench_output).all()96def test_get_arias_intensity_nd(set_up):97    function = "get_arias_intensity_nd"98    for root_path in set_up:99        acc, times = get_common_vals(root_path, function)100        test_output = intensity_measures.get_arias_intensity_nd(acc, times)101        with open(102            os.path.join(root_path, OUTPUT, function + "_ret_val.P"), "rb"103        ) as load_file:104            bench_output = pickle.load(load_file)105        assert np.isclose(test_output, bench_output).all()106def test_calculate_MMI_nd(set_up):107    function = "calculate_MMI_nd"108    for root_path in set_up:109        with open(110            os.path.join(root_path, INPUT, function + "_velocities.P"), "rb"111        ) as load_file:112            vel = pickle.load(load_file)113        test_output = intensity_measures.calculate_MMI_nd(vel)114        with open(115            os.path.join(root_path, OUTPUT, function + "_ret_val.P"), "rb"116        ) as load_file:117            bench_output = pickle.load(load_file)118        assert np.isclose(test_output, bench_output).all()119def test_getDs(set_up):120    function = "getDs"121    for root_path in set_up:122        dt, perc_low, perc_high = get_common_ds_vals(root_path, function)123        with open(124            os.path.join(root_path, INPUT, function + "_fx.P"), "rb"125        ) as load_file:126            fx = pickle.load(load_file)127        test_output = intensity_measures.getDs(dt, fx, perc_low, perc_high)128        with open(129            os.path.join(root_path, OUTPUT, function + "_Ds.P"), "rb"130        ) as load_file:131            bench_output = pickle.load(load_file)132        assert np.isclose(test_output, bench_output).all()133def test_getDs_nd(set_up):134    function = "getDs_nd"135    for root_path in set_up:136        dt, perc_low, perc_high = get_common_ds_vals(root_path, function)137        with open(138            os.path.join(root_path, INPUT, function + "_accelerations.P"), "rb"139        ) as load_file:140            acc = pickle.load(load_file)141        test_output = intensity_measures.getDs_nd(acc, dt, perc_low, perc_high)142        with open(143            os.path.join(root_path, OUTPUT, function + "_values.P"), "rb"144        ) as load_file:145            bench_output = pickle.load(load_file)146        assert np.isclose(test_output, bench_output).all()147def test_get_geom(set_up):148    function = "get_geom"149    for root_path in set_up:150        with open(151            os.path.join(root_path, INPUT, function + "_d1.P"), "rb"152        ) as load_file:153            d1 = pickle.load(load_file)154        with open(155            os.path.join(root_path, INPUT, function + "_d2.P"), "rb"156        ) as load_file:157            d2 = pickle.load(load_file)158        test_output = intensity_measures.get_geom(d1, d2)159        with open(160            os.path.join(root_path, OUTPUT, function + "_ret_val.P"), "rb"161        ) as load_file:162            bench_output = pickle.load(load_file)163        assert np.isclose(test_output, bench_output).all()164@pytest.mark.parametrize(165    "test_d1, test_d2, expected_geom", [(0, 0, 0), (1, 5, 2.236067)]166)167def test_get_geom_params(test_d1, test_d2, expected_geom):168    assert np.isclose(169        intensity_measures.get_geom(test_d1, test_d2), expected_geom...

data_loader.py

Source:data_loader.py

1import csv2def load_file(file_name,data,labels):3    with open(file_name, 'r') as ppd:4        for line in ppd:5            attr = line.split(',')6            data.append(list(map(float, attr[0:31])))7            labels.append(attr[31][0:-1])8def data_loader():9    data = []10    labels = []11    load_file("../old/master_data/Alice/g_m.csv",data,labels)12    load_file("../old/master_data/Alice/n_s.csv",data,labels)13    load_file("../old/master_data/Alice/t_y.csv",data,labels)14    load_file("../old/master_data/Anisha/a_f.csv",data,labels)15    load_file("../old/master_data/Anisha/g_m.csv",data,labels)16    load_file("../old/master_data/Anisha/n_s.csv",data,labels)17    load_file("../old/master_data/Anisha/t_y.csv",data,labels)18    load_file("../old/master_data/Asutosh/a_f.csv",data,labels)19    load_file("../old/master_data/Asutosh/g_m.csv",data,labels)20    load_file("../old/master_data/Asutosh/n_s.csv",data,labels)21    load_file("../old/master_data/Asutosh/t_y.csv",data,labels)22    load_file("../old/master_data/Rishav/a_f.csv",data,labels)23    load_file("../old/master_data/Rishav/g_m.csv",data,labels)24    load_file("../old/master_data/Rishav/n_s.csv",data,labels)25    load_file("../old/master_data/Rishav/t_y.csv",data,labels)26    load_file("../old/master_data/Sai/a_f.csv",data,labels)27    load_file("../old/master_data/Sai/g_m.csv",data,labels)28    load_file("../old/master_data/Sai/n_s.csv",data,labels)29    load_file("../old/master_data/Sai/t_y.csv",data,labels)30    load_file("../old/master_data/Sandy/a_f.csv",data,labels)31    load_file("../old/master_data/Sandy/g_m.csv",data,labels)32    load_file("../old/master_data/Sandy/n_s.csv",data,labels)33    load_file("../old/master_data/Sandy/t_y.csv",data,labels)34    load_file("../old/master_data/Sohini/a_f.csv",data,labels)35    load_file("../old/master_data/Sohini/g_m.csv",data,labels)36    load_file("../old/master_data/Sohini/n_s.csv",data,labels)37    load_file("../old/master_data/Sohini/t_y.csv",data,labels)38    load_file("../old/master_data/zairza.csv",data,labels)...

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