Exemplo n.º 1
0
def generate_protocol_files_from_csv(csv_filename, output_directory=None):

    """
    Generates a set of protocol files from csv filename input by
    reading protocol file input corresponding to each line of
    the csv file. Writes a csv file that.

    Args:
        csv_filename (str): CSV containing protocol file parameters.
        output_directory (str): directory in which to place the output files
    """
    # Read csv file
    protocol_params_df = pd.read_csv(csv_filename)

    new_files = []
    names = []
    result = ""
    message = {"comment": "", "error": ""}
    if output_directory is None:
        output_directory = PROCEDURE_TEMPLATE_DIR
    for index, protocol_params in protocol_params_df.iterrows():
        template = protocol_params["template"]
        # Filename for the output
        filename_prefix = "_".join(
            [
                protocol_params["project_name"],
                "{:06d}".format(protocol_params["seq_num"]),
            ]
        )

        # Switch for template invocation
        if template == "EXP.000":
            protocol = Procedure.from_exp(
                **protocol_params[["cutoff_voltage", "charge_rate", "discharge_rate"]]
            )
            filename = "{}.000".format(filename_prefix)
            filename = os.path.join(output_directory, "procedures", filename)
        elif template == "diagnosticV2.000":
            diag_params_df = pd.read_csv(
                os.path.join(PROCEDURE_TEMPLATE_DIR, "PreDiag_parameters - DP.csv")
            )
            diagnostic_params = diag_params_df[
                diag_params_df["diagnostic_parameter_set"]
                == protocol_params["diagnostic_parameter_set"]
            ].squeeze()

            # TODO: should these be separated?
            protocol = Procedure.from_regcyclev2(protocol_params)
            protocol.add_procedure_diagcyclev2(
                protocol_params["capacity_nominal"], diagnostic_params
            )
            filename = "{}.000".format(filename_prefix)
            filename = os.path.join(output_directory, "procedures", filename)
        # TODO: how are these different?
        elif template in ["diagnosticV3.000", "diagnosticV4.000"]:
            diag_params_df = pd.read_csv(
                os.path.join(PROCEDURE_TEMPLATE_DIR, "PreDiag_parameters - DP.csv")
            )
            diagnostic_params = diag_params_df[
                diag_params_df["diagnostic_parameter_set"]
                == protocol_params["diagnostic_parameter_set"]
            ].squeeze()

            protocol = Procedure.generate_procedure_regcyclev3(index, protocol_params)
            protocol.generate_procedure_diagcyclev3(
                protocol_params["capacity_nominal"], diagnostic_params
            )
            filename = "{}.000".format(filename_prefix)
            filename = os.path.join(output_directory, "procedures", filename)
        elif template == "formationV1.mps":
            protocol = Settings.from_file(os.path.join(BIOLOGIC_TEMPLATE_DIR, template))
            protocol = protocol.formation_protocol_bcs(protocol, protocol_params)
            filename = "{}.mps".format(filename_prefix)
            filename = os.path.join(output_directory, "settings", filename)
        else:
            warnings.warn("Unsupported file template {}, skipping.".format(template))
            result = "error"
            message = {
                "comment": "Unable to find template: " + template,
                "error": "Not Found",
            }
            continue

        logger.info(filename, extra=s)
        if not os.path.isfile(filename):
            protocol.to_file(filename)
            new_files.append(filename)
            names.append(filename_prefix + "_")

        elif ".sdu" in template:
            logger.warning("Schedule file generation not yet implemented", extra=s)
            result = "error"
            message = {
                "comment": "Schedule file generation is not yet implemented",
                "error": "Not Implemented",
            }

    # This block of code produces the file containing all of the run file
    # names produced in this function call. This is to make starting tests easier
    _, namefile = os.path.split(csv_filename)
    namefile = namefile.split("_")[0] + "_names_"
    namefile = namefile + datetime.datetime.now().strftime("%Y%m%d_%H%M") + ".csv"
    with open(
        os.path.join(output_directory, "names", namefile), "w", newline=""
    ) as outputfile:
        wr = csv.writer(outputfile)
        for name in names:
            wr.writerow([name])
    outputfile.close()

    if not result:
        result = "success"
        message = {
            "comment": "Generated {} protocols".format(str(len(new_files))),
            "error": "",
        }

    return new_files, result, message
Exemplo n.º 2
0
def generate_protocol_files_from_csv(csv_filename, output_directory=None):
    """
    Generates a set of protocol files from csv filename input by
    reading protocol file input corresponding to each line of
    the csv file. Writes a csv file that.

    Args:
        csv_filename (str): CSV containing protocol file parameters.
        output_directory (str): directory in which to place the output files
    """
    # Read csv file
    protocol_params_df = pd.read_csv(csv_filename)

    new_files = []
    names = []
    result = ''
    message = {'comment': '', 'error': ''}
    if output_directory is None:
        output_directory = PROCEDURE_TEMPLATE_DIR
    for index, protocol_params in protocol_params_df.iterrows():
        template = protocol_params['template']

        # Switch for template invocation
        if template == "EXP.000":
            procedure = Procedure.from_exp(**protocol_params[
                ["cutoff_voltage", "charge_rate", "discharge_rate"]])
        elif template == 'diagnosticV2.000':
            diag_params_df = pd.read_csv(
                os.path.join(PROCEDURE_TEMPLATE_DIR,
                             "PreDiag_parameters - DP.csv"))
            diagnostic_params = diag_params_df[
                diag_params_df['diagnostic_parameter_set'] ==
                protocol_params['diagnostic_parameter_set']].squeeze()

            # TODO: should these be separated?
            procedure = Procedure.from_regcyclev2(protocol_params)
            procedure.add_procedure_diagcyclev2(
                protocol_params["capacity_nominal"], diagnostic_params)

        # TODO: how are these different?
        elif template in ['diagnosticV3.000', 'diagnosticV4.000']:
            diag_params_df = pd.read_csv(
                os.path.join(PROCEDURE_TEMPLATE_DIR,
                             "PreDiag_parameters - DP.csv"))
            diagnostic_params = diag_params_df[
                diag_params_df['diagnostic_parameter_set'] ==
                protocol_params['diagnostic_parameter_set']].squeeze()

            procedure = Procedure.generate_procedure_regcyclev3(
                index, protocol_params)
            procedure.generate_procedure_diagcyclev3(
                protocol_params["capacity_nominal"], diagnostic_params)
        else:
            warnings.warn(
                "Unsupported file template {}, skipping.".format(template))
            result = "error"
            message = {
                'comment': 'Unable to find template: ' + template,
                'error': 'Not Found'
            }
            continue

        filename_prefix = '_'.join([
            protocol_params["project_name"],
            '{:06d}'.format(protocol_params["seq_num"])
        ])
        filename = "{}.000".format(filename_prefix)
        filename = os.path.join(output_directory, 'procedures', filename)
        logger.info(filename, extra=s)
        if not os.path.isfile(filename):
            procedure.to_file(filename)
            new_files.append(filename)
            names.append(filename_prefix + '_')

        elif '.sdu' in template:
            logger.warning('Schedule file generation not yet implemented',
                           extra=s)
            result = "error"
            message = {
                'comment': 'Schedule file generation is not yet implemented',
                'error': 'Not Implemented'
            }

    # This block of code produces the file containing all of the run file
    # names produced in this function call. This is to make starting tests easier
    _, namefile = os.path.split(csv_filename)
    namefile = namefile.split('_')[0] + '_names_'
    namefile = namefile + datetime.datetime.now().strftime(
        "%Y%m%d_%H%M") + '.csv'
    with open(os.path.join(output_directory, "names", namefile),
              'w',
              newline='') as outputfile:
        wr = csv.writer(outputfile)
        for name in names:
            wr.writerow([name])
    outputfile.close()

    if not result:
        result = "success"
        message = {
            'comment': 'Generated {} protocols'.format(str(len(new_files))),
            'error': ''
        }

    return new_files, result, message
Exemplo n.º 3
0
    def test_schedule_creation(self):
        protocol_params_dict = {
            'project_name': ['PreDiag'],
            'seq_num': [100],
            'template': ['diagnosticV3.000'],
            'charge_constant_current_1': [1],
            'charge_percent_limit_1': [30],
            'charge_constant_current_2': [1],
            'charge_cutoff_voltage': [3.6],
            'charge_constant_voltage_time': [30],
            'charge_rest_time': [5],
            'discharge_constant_current': [1],
            'discharge_cutoff_voltage': [3.0],
            'discharge_rest_time': [15],
            'cell_temperature_nominal': [25],
            'cell_type': ['Tesla_Model3_21700'],
            'capacity_nominal': [1.1],
            'diagnostic_type': ['HPPC+RPT'],
            'diagnostic_parameter_set': ['Tesla21700'],
            'diagnostic_start_cycle': [30],
            'diagnostic_interval': [100]
        }
        procedure_to_convert = 'test_procedure.000'
        with ScratchDir('.') as scratch_dir:
            protocol_params_df = pd.DataFrame.from_dict(protocol_params_dict)
            protocol_params = protocol_params_df.iloc[[0]].squeeze()

            diag_params_df = pd.read_csv(
                os.path.join(PROCEDURE_TEMPLATE_DIR,
                             "PreDiag_parameters - DP.csv"))
            diagnostic_params = diag_params_df[
                diag_params_df['diagnostic_parameter_set'] == 'A123LFP']

            procedure = Procedure.generate_procedure_regcyclev3(
                0, protocol_params)
            procedure.generate_procedure_diagcyclev3(
                protocol_params["capacity_nominal"], diagnostic_params)
            procedure.set_skip_to_end_diagnostic(3.8, 2.0, step_key='070')
            self.assertEqual(procedure['MaccorTestProcedure']['ProcSteps']['TestStep'][0]\
                                 ['Ends']['EndEntry'][1]['Value'], 3.8)
            self.assertEqual(procedure['MaccorTestProcedure']['ProcSteps']['TestStep'][0]\
                                 ['Ends']['EndEntry'][2]['Value'], 2.0)
            procedure.to_file(os.path.join(scratch_dir, procedure_to_convert))

            sdu_test_input = os.path.join(SCHEDULE_TEMPLATE_DIR,
                                          '20170630-3_6C_9per_5C.sdu')
            converted_sdu_name = 'schedule_test_20200724.sdu'
            proc_dict = procedure.from_file(
                os.path.join(scratch_dir, procedure_to_convert))

            sdu_test_output = os.path.join(TEST_FILE_DIR, converted_sdu_name)
            test_step_dict = proc_dict['MaccorTestProcedure']['ProcSteps'][
                'TestStep']

            converter = ProcedureToSchedule(test_step_dict)
            global_min_cur = -2 * 1.5 * protocol_params['capacity_nominal']
            global_max_cur = 2 * 1.5 * protocol_params['capacity_nominal']
            converter.create_sdu(
                sdu_test_input,
                sdu_test_output,
                current_range='Range2',
                global_v_range=[2.0, 3.8],
                global_temp_range=[0, 60],
                global_current_range=[global_min_cur, global_max_cur])
            parsed = open(sdu_test_output, encoding='latin-1').readlines()
            self.assertEqual(parsed[328], '[Schedule_Step3_Limit0]\n')
            self.assertEqual(parsed[6557], '[Schedule_UserDefineSafety15]\n')
            schedule = Schedule.from_file(os.path.join(sdu_test_output))
            self.assertEqual(schedule['Schedule']['Step15']['m_uLimitNum'],
                             '2')
            self.assertEqual(schedule['Schedule']['Step14']['m_uLimitNum'],
                             '6')
            self.assertEqual(schedule['Schedule']['m_uStepNum'], '96')
            self.assertEqual(schedule['Schedule']['Step86']['m_szCtrlValue'],
                             '15')
            self.assertEqual(
                schedule['Schedule']['Step86']['m_szExtCtrlValue1'], '1')
            self.assertEqual(
                schedule['Schedule']['Step86']['m_szExtCtrlValue2'], '0')
Exemplo n.º 4
0
    def test_prediag_with_waveform(self):
        maccor_waveform_file = os.path.join(TEST_FILE_DIR, "LA4_8rep_lim.MWF")
        test_file = os.path.join(PROCEDURE_TEMPLATE_DIR, "diagnosticV3.000")
        csv_file = os.path.join(TEST_FILE_DIR,
                                "PredictionDiagnostics_parameters.csv")
        protocol_params_df = pd.read_csv(csv_file)
        index = 1
        protocol_params_df.iloc[
            index,
            protocol_params_df.columns.get_loc("capacity_nominal")] = 3.71
        protocol_params = protocol_params_df.iloc[index]
        diag_params_df = pd.read_csv(
            os.path.join(PROCEDURE_TEMPLATE_DIR,
                         "PreDiag_parameters - DP.csv"))
        diagnostic_params = diag_params_df[
            diag_params_df["diagnostic_parameter_set"] ==
            protocol_params["diagnostic_parameter_set"]].squeeze()

        procedure = Procedure.generate_procedure_regcyclev3(
            index, protocol_params)
        procedure.generate_procedure_diagcyclev3(
            protocol_params["capacity_nominal"], diagnostic_params)

        steps = [
            x["StepType"]
            for x in procedure["MaccorTestProcedure"]["ProcSteps"]["TestStep"]
        ]
        print(steps)
        start = 27
        reg_cycle_steps = [
            "Do 1",
            "Charge",
            "Charge",
            "Charge",
            "Rest",
            "Dischrge",
            "Rest",
            "AdvCycle",
            "Loop 1",
        ]
        reg_steps_len = len(reg_cycle_steps)
        self.assertEqual(steps[start:start + reg_steps_len], reg_cycle_steps)
        start = 59
        reg_cycle_steps = [
            "Do 2",
            "Charge",
            "Charge",
            "Charge",
            "Rest",
            "Dischrge",
            "Rest",
            "AdvCycle",
            "Loop 2",
        ]
        reg_steps_len = len(reg_cycle_steps)
        self.assertEqual(steps[start:start + reg_steps_len], reg_cycle_steps)
        print(procedure["MaccorTestProcedure"]["ProcSteps"]["TestStep"][32])
        print(procedure["MaccorTestProcedure"]["ProcSteps"]["TestStep"][64])

        procedure.insert_maccor_waveform_discharge(32, maccor_waveform_file)
        procedure.insert_maccor_waveform_discharge(64, maccor_waveform_file)
        self.assertEqual(
            procedure["MaccorTestProcedure"]["ProcSteps"]["TestStep"][32]
            ["StepType"],
            "FastWave",
        )
        self.assertEqual(
            procedure["MaccorTestProcedure"]["ProcSteps"]["TestStep"][64]
            ["StepType"],
            "FastWave",
        )
        with ScratchDir(".") as scratch_dir:
            driving_test_name = "Drive_test20200716.000"
            procedure.to_file(driving_test_name)
Exemplo n.º 5
0
    def test_conversion_with_updated(self):
        converter = MaccorToBiologicMb()

        with ScratchDir(".") as scratch_dir:
            # Generate a protocol that can be used with the existing cells for testing purposes
            reg_params = {
                'project_name': {
                    0: 'FormDegrade'
                },
                'seq_num': {
                    0: 0
                },
                'template': {
                    0: 'diagnosticV5.000'
                },
                'charge_constant_current_1': {
                    0: 2.0
                },
                'charge_percent_limit_1': {
                    0: 30
                },
                'charge_constant_current_2': {
                    0: 2.0
                },
                'charge_cutoff_voltage': {
                    0: 4.4
                },
                'charge_constant_voltage_time': {
                    0: 60
                },
                'charge_rest_time': {
                    0: 5
                },
                'discharge_constant_current': {
                    0: 1.0
                },
                'discharge_cutoff_voltage': {
                    0: 3.0
                },
                'discharge_rest_time': {
                    0: 15
                },
                'cell_temperature_nominal': {
                    0: 25
                },
                'cell_type': {
                    0: 'LiFun240'
                },
                'capacity_nominal': {
                    0: 0.240
                },
                'diagnostic_type': {
                    0: 'HPPC+RPT'
                },
                'diagnostic_parameter_set': {
                    0: 'LiFunForm'
                },
                'diagnostic_start_cycle': {
                    0: 30
                },
                'diagnostic_interval': {
                    0: 100
                }
            }

            protocol_params_df = pd.DataFrame.from_dict(reg_params)
            index = 0
            protocol_params = protocol_params_df.iloc[index]
            diag_params_df = pd.read_csv(
                os.path.join(PROCEDURE_TEMPLATE_DIR,
                             "PreDiag_parameters - DP.csv"))
            diagnostic_params = diag_params_df[
                diag_params_df["diagnostic_parameter_set"] ==
                protocol_params["diagnostic_parameter_set"]].squeeze()

            procedure = Procedure.generate_procedure_regcyclev3(
                index, protocol_params)
            procedure.generate_procedure_diagcyclev3(
                protocol_params["capacity_nominal"], diagnostic_params)
            procedure.set_skip_to_end_diagnostic(4.5,
                                                 2.0,
                                                 step_key="070",
                                                 new_step_key="095")
            procedure.to_file(os.path.join(scratch_dir, "BioTest_000001.000"))

            # Setup the converter and run it
            def set_i_range(tech_num, seq, idx):
                seq_copy = copy.deepcopy(seq)
                seq_copy["I Range"] = "1 A"
                return seq_copy

            converter.seq_mappers.append(set_i_range)
            converter.min_voltage_v = 2.0
            converter.max_voltage_v = 4.5

            converter.convert(os.path.join(scratch_dir, "BioTest_000001.000"),
                              TEST_FILE_DIR, "BioTest_000001")
            f = open(os.path.join(TEST_FILE_DIR, "BioTest_000001.mps"),
                     encoding="ISO-8859-1")
            file = f.readlines()
            control_list = [
                'ctrl_type', 'Rest', 'CC', 'Rest', 'CC', 'CV', 'CC', 'Loop',
                'CC', 'CV', 'Rest', 'CC', 'Rest', 'CC', 'CC', 'Loop', 'CV',
                'CC', 'CC', 'CV', 'CC', 'CC', 'CV', 'CC', 'CC', 'CV', 'CC',
                'CC', 'CC', 'CV', 'Rest', 'CC', 'Rest', 'Loop'
            ]
            self.assertListEqual(control_list, file[35].split())
            value_list = [
                'ctrl1_val', '240.000', '34.300', '4.400', '34.300', '100.000',
                '80.000', '4.400', '240.000', '180.000', '80.000', '100.000',
                '3.000', '80.000', '48.000', '4.400', '48.000', '48.000',
                '4.400', '240.000', '48.000', '4.400', '480.000', '480.000',
                '480.000', '4.400', '240.000', '100.000'
            ]
            self.assertListEqual(value_list, file[37].split())

            voltage_min = '\tEcell min = 2.00 V\n'
            self.assertEqual(voltage_min, file[9])
            voltage_max = '\tEcell max = 4.50 V\n'
            self.assertEqual(voltage_max, file[10])
Exemplo n.º 6
0
def generate_protocol_files_from_csv(csv_filename, output_directory=None):

    """
    Generates a set of protocol files from csv filename input by
    reading protocol file input corresponding to each line of
    the csv file. Writes a csv file that.

    Args:
        csv_filename (str): CSV containing protocol file parameters.
        output_directory (str): directory in which to place the output files
    """
    # Read csv file
    protocol_params_df = pd.read_csv(csv_filename)

    successfully_generated_files = []
    file_generation_failures = []
    names = []
    result = ""
    message = {"comment": "", "error": ""}
    if output_directory is None:
        output_directory = PROCEDURE_TEMPLATE_DIR

    for index, protocol_params in protocol_params_df.iterrows():
        template = protocol_params["template"]
        protocol = None
        # Filename for the output
        filename_prefix = "_".join(
            [
                protocol_params["project_name"],
                "{:06d}".format(protocol_params["seq_num"]),
            ]
        )
        if ".000" in template:  # Extension for maccor procedure files
            template_fullpath = os.path.join(PROCEDURE_TEMPLATE_DIR, template)
            template_length = template_detection(template_fullpath)
            if "diagnostic_parameter_set" in protocol_params:  # For parameters include diagnostics load those values
                diag_params_df = pd.read_csv(
                    os.path.join(PROCEDURE_TEMPLATE_DIR, "PreDiag_parameters - DP.csv")
                )
                diagnostic_params = diag_params_df[
                    diag_params_df["diagnostic_parameter_set"]
                    == protocol_params["diagnostic_parameter_set"]
                    ].squeeze()

            if template_length == 23 and template == "EXP.000":  # length and name for initial procedure files
                protocol = Procedure.from_exp(
                    **protocol_params[["cutoff_voltage", "charge_rate", "discharge_rate"]]
                )
            elif template_length == 72:  # length for V1 and V1 diagnostic templates without ending diagnostics
                protocol = Procedure.from_regcyclev2(protocol_params)
                protocol.add_procedure_diagcyclev2(
                    protocol_params["capacity_nominal"], diagnostic_params
                )
            elif template_length == 96:  # template length for diagnostic type cycling
                mwf_dir = os.path.join(output_directory, "mwf_files")
                if protocol_params["project_name"] == "RapidC":  # Project with charging waveform
                    waveform_name = insert_charging_parametersv1(protocol_params,
                                                                 waveform_directory=mwf_dir)
                    protocol = Procedure.generate_procedure_chargingv1(index,
                                                                       protocol_params,
                                                                       waveform_name,
                                                                       template=template_fullpath)
                elif protocol_params["project_name"] == "Drive":  # Project with discharging waveform
                    waveform_name = insert_driving_parametersv1(protocol_params,
                                                                waveform_directory=mwf_dir)
                    protocol = Procedure.generate_procedure_drivingv1(index,
                                                                      protocol_params,
                                                                      waveform_name,
                                                                      template=template_fullpath)
                else:  # Use the default parameterization for PreDiag/Prediction Diagnostic projects
                    protocol = Procedure.generate_procedure_regcyclev3(index,
                                                                       protocol_params,
                                                                       template=template_fullpath)
                protocol.generate_procedure_diagcyclev3(
                    protocol_params["capacity_nominal"], diagnostic_params
                )
            else:  # Case where its not possible to match the procedure template
                failure = {
                    "comment": "Unable to find template: " + template,
                    "error": "Not Found",
                }
                file_generation_failures.append(failure)
                warnings.warn("Unsupported file template {}, skipping.".format(template))
                result = "error"
                continue

            filename = "{}.000".format(filename_prefix)
            filename = os.path.join(output_directory, "procedures", filename)

        elif ".mps" in template and template == "formationV1.mps":  # biologic settings template and formation project
            protocol = Settings.from_file(os.path.join(BIOLOGIC_TEMPLATE_DIR, template))
            protocol = protocol.formation_protocol_bcs(protocol_params)
            filename = "{}.mps".format(filename_prefix)
            filename = os.path.join(output_directory, "settings", filename)
        elif ".sdu" in template:  # No schedule file templates implemented
            failure = {
                "comment": "Schedule file generation is not yet implemented",
                "error": "Not Implemented"
            }
            file_generation_failures.append(failure)
            logger.warning("Schedule file generation not yet implemented", extra=s)
            result = "error"
            continue
        else:  # Unable to match to any known template format
            failure = {
                "comment": "Unable to find template: " + template,
                "error": "Not Found",
            }
            file_generation_failures.append(failure)
            warnings.warn("Unsupported file template {}, skipping.".format(template))
            result = "error"
            continue

        logger.info(filename, extra=s)
        protocol.to_file(filename)
        successfully_generated_files.append(filename)
        names.append(filename_prefix + "_")

    # This block of code produces the file containing all of the run file
    # names produced in this function call. This is to make starting tests easier
    _, namefile = os.path.split(csv_filename)
    namefile = namefile.split("_")[0] + "_names_"
    namefile = namefile + datetime.datetime.now().strftime("%Y%m%d_%H%M") + ".csv"

    names_dir = os.path.join(output_directory, "names")
    os.makedirs(names_dir, exist_ok=True)

    with open(os.path.join(names_dir, namefile), "w", newline="") as outputfile:
        wr = csv.writer(outputfile)
        for name in names:
            wr.writerow([name])
    outputfile.close()

    num_generated_files = len(successfully_generated_files)
    num_generation_failures = len(file_generation_failures)
    num_files = num_generated_files + num_generation_failures

    message = {
        "comment": "Generated {} of {} protocols".format(num_generated_files, num_files),
        "error": ""
    }
    if not result:
        result = "success"
    else:
        message["error"] = "Failed to generate {} of {} protocols".format(num_generation_failures, num_files)
        logger.error(message["error"])

    return successfully_generated_files, file_generation_failures, result, message