From 2ab4e76a8257d4b5768f8ff3c80540b70c9213e1 Mon Sep 17 00:00:00 2001 From: slopez-b <132961666+slopez-b@users.noreply.github.com> Date: Tue, 30 Jan 2024 11:11:44 -0500 Subject: [PATCH] Feat: luminex xponent adapter (#255) Add Luminex Xponent support. --- CHANGELOG.md | 1 + ...nchling_2024_01_multi_analyte_profiling.py | 4 +- .../2024/01/multi-analyte-profiling.json | 3 +- src/allotropy/parser_factory.py | 5 + src/allotropy/parsers/lines_reader.py | 4 +- .../parsers/luminex_xponent/__init__.py | 0 .../luminex_xponent/luminex_xponent_parser.py | 160 + .../luminex_xponent_structure.py | 339 + tests/parsers/luminex_xponent/__init__.py | 0 .../luminex_xponent/luminex_xponent_data.py | 112 + .../luminex_xponent_parser_test.py | 24 + .../luminex_xponent_structure_test.py | 231 + .../testdata/luminex_xPONENT_example01.json | 31808 ++++++++++++++++ .../luminex_xponent/testdata/test_data.csv | 81 + 14 files changed, 32766 insertions(+), 6 deletions(-) create mode 100644 src/allotropy/parsers/luminex_xponent/__init__.py create mode 100644 src/allotropy/parsers/luminex_xponent/luminex_xponent_parser.py create mode 100644 src/allotropy/parsers/luminex_xponent/luminex_xponent_structure.py create mode 100644 tests/parsers/luminex_xponent/__init__.py create mode 100644 tests/parsers/luminex_xponent/luminex_xponent_data.py create mode 100644 tests/parsers/luminex_xponent/luminex_xponent_parser_test.py create mode 100644 tests/parsers/luminex_xponent/luminex_xponent_structure_test.py create mode 100644 tests/parsers/luminex_xponent/testdata/luminex_xPONENT_example01.json create mode 100644 tests/parsers/luminex_xponent/testdata/test_data.csv diff --git a/CHANGELOG.md b/CHANGELOG.md index 542359274..2669e2ba8 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -6,6 +6,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 ## [Unreleased] ### Added +- Add Luminex xPONENT Adapter ### Fixed ### Changed ### Deprecated diff --git a/src/allotropy/allotrope/models/multi_analyte_profiling_benchling_2024_01_multi_analyte_profiling.py b/src/allotropy/allotrope/models/multi_analyte_profiling_benchling_2024_01_multi_analyte_profiling.py index 03a0abed3..43b1b0732 100644 --- a/src/allotropy/allotrope/models/multi_analyte_profiling_benchling_2024_01_multi_analyte_profiling.py +++ b/src/allotropy/allotrope/models/multi_analyte_profiling_benchling_2024_01_multi_analyte_profiling.py @@ -1,6 +1,6 @@ # generated by datamodel-codegen: # filename: multi-analyte-profiling.json -# timestamp: 2024-01-17T20:55:27+00:00 +# timestamp: 2024-01-26T15:48:36+00:00 from __future__ import annotations @@ -140,7 +140,7 @@ class DeviceControlDocumentItem: firmware_version: Optional[TStringValue] = None sample_volume_setting: Optional[TQuantityValueMicroliter] = None dilution_factor_setting: Optional[TQuantityValueUnitless] = None - detector_gain_settings: Optional[TStringValue] = None + detector_gain_setting: Optional[TStringValue] = None minimum_assay_bead_count_setting: Optional[TQuantityValueUnitless] = None diff --git a/src/allotropy/allotrope/schemas/multi-analyte-profiling/BENCHLING/2024/01/multi-analyte-profiling.json b/src/allotropy/allotrope/schemas/multi-analyte-profiling/BENCHLING/2024/01/multi-analyte-profiling.json index d546743b0..09379f64d 100644 --- a/src/allotropy/allotrope/schemas/multi-analyte-profiling/BENCHLING/2024/01/multi-analyte-profiling.json +++ b/src/allotropy/allotrope/schemas/multi-analyte-profiling/BENCHLING/2024/01/multi-analyte-profiling.json @@ -526,7 +526,7 @@ "$asm.pattern": "quantity datum", "$ref": "#/$custom/tQuantityValueUnitless" }, - "detector gain settings": { + "detector gain setting": { "$asm.property-class": "http://purl.allotrope.org/ontologies/result#AFR_0002250", "$asm.pattern": "value datum", "$asm.type": "http://www.w3.org/2001/XMLSchema#string", @@ -673,7 +673,6 @@ } ], "required": [ - "multi analyte profiling aggreagate document", "$asm.manifest" ], "$defs": { diff --git a/src/allotropy/parser_factory.py b/src/allotropy/parser_factory.py index 2f21532d9..772124970 100644 --- a/src/allotropy/parser_factory.py +++ b/src/allotropy/parser_factory.py @@ -18,6 +18,9 @@ from allotropy.parsers.example_weyland_yutani.example_weyland_yutani_parser import ( ExampleWeylandYutaniParser, ) +from allotropy.parsers.luminex_xponent.luminex_xponent_parser import ( + LuminexXponentParser, +) from allotropy.parsers.moldev_softmax_pro.softmax_pro_parser import SoftmaxproParser from allotropy.parsers.novabio_flex2.novabio_flex2_parser import NovaBioFlexParser from allotropy.parsers.perkin_elmer_envision.perkin_elmer_envision_parser import ( @@ -44,6 +47,7 @@ class Vendor(Enum): BECKMAN_VI_CELL_XR = "BECKMAN_VI_CELL_XR" CHEMOMETEC_NUCLEOVIEW = "CHEMOMETEC_NUCLEOVIEW" EXAMPLE_WEYLAND_YUTANI = "EXAMPLE_WEYLAND_YUTANI" + LUMINEX_XPONENT = "LUMINEX_XPONENT" MOLDEV_SOFTMAX_PRO = "MOLDEV_SOFTMAX_PRO" NOVABIO_FLEX2 = "NOVABIO_FLEX2" PERKIN_ELMER_ENVISION = "PERKIN_ELMER_ENVISION" @@ -63,6 +67,7 @@ class Vendor(Enum): Vendor.BECKMAN_VI_CELL_XR: ViCellXRParser, Vendor.CHEMOMETEC_NUCLEOVIEW: ChemometecNucleoviewParser, Vendor.EXAMPLE_WEYLAND_YUTANI: ExampleWeylandYutaniParser, + Vendor.LUMINEX_XPONENT: LuminexXponentParser, Vendor.MOLDEV_SOFTMAX_PRO: SoftmaxproParser, Vendor.NOVABIO_FLEX2: NovaBioFlexParser, Vendor.PERKIN_ELMER_ENVISION: PerkinElmerEnvisionParser, diff --git a/src/allotropy/parsers/lines_reader.py b/src/allotropy/parsers/lines_reader.py index 36cb36dcf..db16157f0 100644 --- a/src/allotropy/parsers/lines_reader.py +++ b/src/allotropy/parsers/lines_reader.py @@ -1,7 +1,7 @@ from collections.abc import Iterator from io import StringIO from re import search -from typing import Optional +from typing import Literal, Optional, Union import chardet import pandas as pd @@ -121,7 +121,7 @@ def pop_csv_block_as_df( self, empty_pat: str = EMPTY_STR_PATTERN, *, - header: Optional[int] = None, + header: Optional[Union[int, Literal["infer"]]] = None, sep: Optional[str] = ",", as_str: bool = False, ) -> Optional[pd.DataFrame]: diff --git a/src/allotropy/parsers/luminex_xponent/__init__.py b/src/allotropy/parsers/luminex_xponent/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/src/allotropy/parsers/luminex_xponent/luminex_xponent_parser.py b/src/allotropy/parsers/luminex_xponent/luminex_xponent_parser.py new file mode 100644 index 000000000..fcbef54da --- /dev/null +++ b/src/allotropy/parsers/luminex_xponent/luminex_xponent_parser.py @@ -0,0 +1,160 @@ +from allotropy.allotrope.models.multi_analyte_profiling_benchling_2024_01_multi_analyte_profiling import ( + AnalyteAggregateDocument, + AnalyteDocumentItem, + CalibrationAggregateDocument, + CalibrationDocumentItem, + DataSystemDocument, + DeviceControlAggregateDocument, + DeviceControlDocumentItem, + DeviceSystemDocument, + ErrorAggregateDocument, + ErrorDocumentItem, + MeasurementAggregateDocument, + MeasurementDocumentItem, + Model, + MultiAnalyteProfilingAggregateDocument, + MultiAnalyteProfilingDocumentItem, + SampleDocument, +) +from allotropy.allotrope.models.shared.definitions.custom import ( + TQuantityValueMicroliter, + TQuantityValueNumber, + TQuantityValueRelativeFluorescenceUnit, + TQuantityValueUnitless, +) +from allotropy.allotrope.models.shared.definitions.definitions import ( + TStatisticDatumRole, +) +from allotropy.constants import ASM_CONVERTER_NAME, ASM_CONVERTER_VERSION +from allotropy.named_file_contents import NamedFileContents +from allotropy.parsers.lines_reader import CsvReader, read_to_lines +from allotropy.parsers.luminex_xponent.luminex_xponent_structure import ( + Data, + Header, + Measurement, +) +from allotropy.parsers.utils.uuids import random_uuid_str +from allotropy.parsers.vendor_parser import VendorParser + +DEFAULT_SOFTWARE_NAME = "xPONENT" +DEFAULT_CONTAINER_TYPE = "well plate" +DEFAULT_DEVICE_TYPE = "multi analyte profiling analyzer" + + +class LuminexXponentParser(VendorParser): + def to_allotrope(self, named_file_contents: NamedFileContents) -> Model: + lines = read_to_lines(named_file_contents.contents) + reader = CsvReader(lines) + data = Data.create(reader, self.timestamp_parser) + return self._get_model(named_file_contents.original_file_name, data) + + def _get_model(self, file_name: str, data: Data) -> Model: + header = data.header + return Model( + field_asm_manifest="http://purl.allotrope.org/manifests/multi-analyte-profiling/BENCHLING/2024/01/multi-analyte-profiling.manifest", + multi_analyte_profiling_aggregate_document=MultiAnalyteProfilingAggregateDocument( + device_system_document=DeviceSystemDocument( + model_number=header.model_number, + equipment_serial_number=header.equipment_serial_number, + calibration_aggregate_document=CalibrationAggregateDocument( + calibration_document=[ + CalibrationDocumentItem( + calibration_name=calibration_item.name, + calibration_report=calibration_item.report, + calibration_time=calibration_item.time, + ) + for calibration_item in data.calibration_data + ] + ), + ), + data_system_document=DataSystemDocument( + data_system_instance_identifier=header.data_system_instance_identifier, + file_name=file_name, + software_name=DEFAULT_SOFTWARE_NAME, + software_version=header.software_version, + ASM_converter_name=ASM_CONVERTER_NAME, + ASM_converter_version=ASM_CONVERTER_VERSION, + ), + multi_analyte_profiling_document=[ + MultiAnalyteProfilingDocumentItem( + analyst=header.analyst, + measurement_aggregate_document=MeasurementAggregateDocument( + analytical_method_identifier=header.analytical_method_identifier, + method_version=header.method_version, + experimental_data_identifier=header.experimental_data_identifier, + container_type=DEFAULT_CONTAINER_TYPE, + plate_well_count=TQuantityValueNumber( + value=header.plate_well_count + ), + measurement_document=[ + self._get_measurement_document_item( + measurement, + header, + data.minimum_bead_count_setting, + ) + for measurement in data.measurement_list.measurements + ], + ), + ) + ], + ), + ) + + def _get_measurement_document_item( + self, + measurement: Measurement, + header_data: Header, + minimum_bead_count_setting: float, + ) -> MeasurementDocumentItem: + error_aggregate_document = None + if measurement.errors: + error_aggregate_document = ErrorAggregateDocument( + error_document=[ + ErrorDocumentItem(error=error) for error in measurement.errors + ] + ) + + return MeasurementDocumentItem( + measurement_identifier=random_uuid_str(), + measurement_time=header_data.measurement_time, + sample_document=SampleDocument( + sample_identifier=measurement.sample_identifier, + location_identifier=measurement.location_identifier, + ), + device_control_aggregate_document=DeviceControlAggregateDocument( + device_control_document=[ + DeviceControlDocumentItem( + device_type=DEFAULT_DEVICE_TYPE, + sample_volume_setting=TQuantityValueMicroliter( + value=header_data.sample_volume_setting + ), + dilution_factor_setting=TQuantityValueUnitless( + value=measurement.dilution_factor_setting + ), + detector_gain_setting=header_data.detector_gain_setting, + minimum_assay_bead_count_setting=TQuantityValueUnitless( + value=minimum_bead_count_setting + ), + ) + ] + ), + assay_bead_count=TQuantityValueNumber(value=measurement.assay_bead_count), + analyte_aggregate_document=AnalyteAggregateDocument( + analyte_document=[ + AnalyteDocumentItem( + analyte_identifier=random_uuid_str(), + analyte_name=analyte.analyte_name, + assay_bead_identifier=analyte.assay_bead_identifier, + assay_bead_count=TQuantityValueNumber( + value=analyte.assay_bead_count + ), + fluorescence=TQuantityValueRelativeFluorescenceUnit( + value=analyte.fluorescence, + has_statistic_datum_role=TStatisticDatumRole.median_role, + ), + ) + for analyte in measurement.analytes + ] + ), + error_aggregate_document=error_aggregate_document, + ) diff --git a/src/allotropy/parsers/luminex_xponent/luminex_xponent_structure.py b/src/allotropy/parsers/luminex_xponent/luminex_xponent_structure.py new file mode 100644 index 000000000..4bd328793 --- /dev/null +++ b/src/allotropy/parsers/luminex_xponent/luminex_xponent_structure.py @@ -0,0 +1,339 @@ +from __future__ import annotations + +from dataclasses import dataclass +from io import StringIO +import re +from typing import Any, Optional + +import pandas as pd + +from allotropy.exceptions import AllotropeConversionError +from allotropy.parsers.lines_reader import CsvReader +from allotropy.parsers.utils.timestamp_parser import TimestampParser +from allotropy.parsers.utils.values import ( + assert_not_none, + try_float, + try_float_from_series, + try_str_from_series, + try_str_from_series_or_none, +) + +EMPTY_CSV_LINE = r"^,*$" +CALIBRATION_BLOCK_HEADER = "Most Recent Calibration and Verification Results" +TABLE_HEADER_PATTERN = "DataType:,{}" +MINIMUM_CALIBRATION_LINE_COLS = 2 +EXPECTED_CALIBRATION_RESULT_LEN = 2 + + +@dataclass(frozen=True) +class Header: + model_number: str + software_version: str + equipment_serial_number: str + analytical_method_identifier: str + method_version: str + experimental_data_identifier: str + sample_volume_setting: float + plate_well_count: float + measurement_time: str + detector_gain_setting: str + data_system_instance_identifier: str + analyst: Optional[str] = None + + @classmethod + def create( + cls, header_data: pd.DataFrame, timestamp_parser: TimestampParser + ) -> Header: + info_row = header_data.iloc[0] + raw_datetime = try_str_from_series(info_row, "BatchStartTime") + + return Header( + model_number=cls._get_model_number(header_data), + software_version=try_str_from_series(info_row, "Build"), + equipment_serial_number=try_str_from_series(info_row, "SN"), + analytical_method_identifier=try_str_from_series(info_row, "ProtocolName"), + method_version=try_str_from_series(info_row, "ProtocolVersion"), + experimental_data_identifier=try_str_from_series(info_row, "Batch"), + sample_volume_setting=cls._get_sample_volume_setting(info_row), + plate_well_count=cls._get_plate_well_count(header_data), + measurement_time=timestamp_parser.parse(raw_datetime), + detector_gain_setting=try_str_from_series(info_row, "ProtocolReporterGain"), + data_system_instance_identifier=try_str_from_series( + info_row, "ComputerName" + ), + analyst=try_str_from_series_or_none(info_row, "Operator"), + ) + + @classmethod + def _get_sample_volume_setting(cls, info_row: pd.Series[Any]) -> float: + sample_volume = try_str_from_series(info_row, "SampleVolume") + + return try_float(sample_volume.split()[0], "sample volume setting") + + @classmethod + def _get_model_number(cls, header_data: pd.DataFrame) -> str: + program_data = cls._try_col_from_header(header_data, "Program") + + try: + model_number = program_data.iloc[2] + except IndexError as e: + msg = "Unable to find model number in Program row." + raise AllotropeConversionError(msg) from e + + return str(model_number) + + @classmethod + def _get_plate_well_count(cls, header_data: pd.DataFrame) -> float: + protocol_plate_data = cls._try_col_from_header(header_data, "ProtocolPlate") + + try: + plate_well_count = protocol_plate_data.iloc[3] + except IndexError as e: + msg = "Unable to find plate well count in ProtocolPlate row." + raise AllotropeConversionError(msg) from e + + return try_float(plate_well_count, "plate well count") + + @classmethod + def _try_col_from_header( + cls, header_data: pd.DataFrame, key: str + ) -> pd.Series[Any]: + if key not in header_data: + msg = f"Unable to find {key} data on header block." + raise AllotropeConversionError(msg) + + return header_data[key] + + +@dataclass(frozen=True) +class CalibrationItem: + name: str + report: str + time: str + + @classmethod + def create( + cls, calibration_line: str, timestamp_parser: TimestampParser + ) -> CalibrationItem: + """Create a CalibrationItem from a calibration line. + + Each line should follow the pattern "Last , <,,,," + example: "Last F3DeCAL1 Calibration,Passed 05/17/2023 09:25:11,,,,,," + """ + calibration_data = calibration_line.split(",") + if len(calibration_data) < MINIMUM_CALIBRATION_LINE_COLS: + msg = f"Expected at least two columns on the calibration line, got: {calibration_line}" + raise AllotropeConversionError(msg) + + calibration_result = calibration_data[1].split(maxsplit=1) + + if len(calibration_result) != EXPECTED_CALIBRATION_RESULT_LEN: + msg = f"Invalid calibration result format, got: {calibration_data[1]}" + raise AllotropeConversionError(msg) + + callibration_time = timestamp_parser.parse(calibration_result[1]) + + return CalibrationItem( + name=calibration_data[0].replace("Last", "").strip(), + report=calibration_result[0], + time=callibration_time, + ) + + +@dataclass(frozen=True) +class Analyte: + analyte_name: str + assay_bead_identifier: str + assay_bead_count: float + fluorescence: float + + +@dataclass(frozen=True) +class Measurement: + sample_identifier: str + location_identifier: str + dilution_factor_setting: float + assay_bead_count: float + analytes: list[Analyte] + errors: Optional[list[str]] = None + + @classmethod + def create( + cls, + median_data: pd.Series[Any], + count_data: pd.DataFrame, + bead_ids_data: pd.Series[str], + dilution_factor_data: pd.DataFrame, + errors_data: pd.DataFrame, + ) -> Measurement: + location = try_str_from_series(median_data, "Location") + dilution_factor_setting = try_float_from_series( + dilution_factor_data.loc[location], "Dilution Factor" + ) + # analyte names are columns 3 through the penultimate + analyte_names = list(median_data.index)[2:-1] + + well_location, location_id = cls._get_location_details(location) + + return Measurement( + sample_identifier=try_str_from_series(median_data, "Sample"), + location_identifier=location_id, + dilution_factor_setting=dilution_factor_setting, + assay_bead_count=try_float_from_series(median_data, "Total Events"), + analytes=[ + Analyte( + analyte_name=analyte, + assay_bead_identifier=try_str_from_series(bead_ids_data, analyte), + assay_bead_count=try_float_from_series( + count_data.loc[location], analyte + ), + fluorescence=try_float_from_series(median_data, analyte), + ) + for analyte in analyte_names + ], + errors=cls._get_errors(errors_data, well_location), + ) + + @classmethod + def _get_location_details(cls, location: str) -> tuple[str, str]: + location_regex = r"\d+\((?P\d+,(?P\w+))\)" + match = assert_not_none( + re.search(location_regex, location), + msg=f"Invalid location format: {location}", + ) + + return match.group("well_location"), match.group("location_id") + + @classmethod + def _get_errors( + cls, errors_data: pd.DataFrame, well_location: str + ) -> Optional[list[str]]: + try: + measurement_errors = errors_data.loc[well_location] + except KeyError: + return None + + return [ + measurement_errors.iloc[i]["Message"] + for i in range(len(measurement_errors)) + ] + + +@dataclass(frozen=True) +class MeasurementList: + measurements: list[Measurement] + + @classmethod + def create(cls, reader: CsvReader) -> MeasurementList: + median_data = cls._get_median_data(reader) + + count_data = cls._get_table_as_df(reader, "Count") + bead_ids_data = cls._get_bead_ids_data(reader) + dilution_factor_data = cls._get_table_as_df(reader, "Dilution Factor") + errors_data = cls._get_table_as_df(reader, "Warnings/Errors") + + return MeasurementList( + measurements=[ + Measurement.create( + median_data=median_data.iloc[i], + count_data=count_data, + bead_ids_data=bead_ids_data, + dilution_factor_data=dilution_factor_data, + errors_data=errors_data, + ) + for i in range(len(median_data)) + ] + ) + + @classmethod + def _get_median_data(cls, reader: CsvReader) -> pd.DataFrame: + reader.drop_until_inclusive(TABLE_HEADER_PATTERN.format("Median")) + return assert_not_none( + reader.pop_csv_block_as_df(empty_pat=EMPTY_CSV_LINE, header="infer"), + msg="Unable to find Median table.", + ) + + @classmethod + def _get_bead_ids_data(cls, reader: CsvReader) -> pd.Series[str]: + units_df = MeasurementList._get_table_as_df(reader, "Units") + return units_df.loc["BeadID:"] + + @classmethod + def _get_table_as_df(cls, reader: CsvReader, table_name: str) -> pd.DataFrame: + """Returns a dataframe that has the well location as index. + + Results tables in luminex xponent output files have the location as first column. + Having this column as the index of the dataframe allows for easier lookup when + retrieving measurement data. + """ + reader.drop_until_inclusive(match_pat=TABLE_HEADER_PATTERN.format(table_name)) + + table_lines = reader.pop_csv_block_as_lines(empty_pat=EMPTY_CSV_LINE) + + if not table_lines: + msg = f"Unable to find {table_name} table." + raise AllotropeConversionError(msg) + + return pd.read_csv( + StringIO("\n".join(table_lines)), + header=[0], + index_col=[0], + ).dropna(how="all", axis=1) + + +@dataclass(frozen=True) +class Data: + header: Header + calibration_data: list[CalibrationItem] + minimum_bead_count_setting: float + measurement_list: MeasurementList + + @classmethod + def create(cls, reader: CsvReader, timestamp_parser: TimestampParser) -> Data: + return Data( + header=Header.create(cls._get_header_data(reader), timestamp_parser), + calibration_data=cls._get_calibration_data(reader, timestamp_parser), + minimum_bead_count_setting=cls._get_minimum_bead_count_setting(reader), + measurement_list=MeasurementList.create(reader), + ) + + @classmethod + def _get_header_data(cls, reader: CsvReader) -> pd.DataFrame: + header_lines = assert_not_none( + reader.pop_until(CALIBRATION_BLOCK_HEADER), "Unable to find Header block." + ) + header_data = pd.read_csv( + StringIO("\n".join(header_lines)), + header=None, + index_col=0, + ).dropna(how="all") + return header_data.T + + @classmethod + def _get_calibration_data( + cls, reader: CsvReader, timestamp_parser: TimestampParser + ) -> list[CalibrationItem]: + reader.drop_until_inclusive(CALIBRATION_BLOCK_HEADER) + calibration_lines = reader.pop_csv_block_as_lines(empty_pat=EMPTY_CSV_LINE) + if not calibration_lines: + msg = "Unable to find Calibration Block." + raise AllotropeConversionError(msg) + + calibration_list = [] + + for line in calibration_lines: + calibration_list.append(CalibrationItem.create(line, timestamp_parser)) + + return calibration_list + + @classmethod + def _get_minimum_bead_count_setting(cls, reader: CsvReader) -> float: + reader.drop_until(match_pat="Samples,") + samples_info = assert_not_none(reader.pop(), "Unable to find Samples info.") + try: + min_bead_count_setting = samples_info.split(",")[3] + except IndexError as e: + msg = "Unable to find minimum bead count setting in Samples info." + raise AllotropeConversionError(msg) from e + + return try_float(min_bead_count_setting, "minimum bead count setting") diff --git a/tests/parsers/luminex_xponent/__init__.py b/tests/parsers/luminex_xponent/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/tests/parsers/luminex_xponent/luminex_xponent_data.py b/tests/parsers/luminex_xponent/luminex_xponent_data.py new file mode 100644 index 000000000..56ab62bd4 --- /dev/null +++ b/tests/parsers/luminex_xponent/luminex_xponent_data.py @@ -0,0 +1,112 @@ +from allotropy.parsers.lines_reader import CsvReader, read_to_lines +from allotropy.parsers.luminex_xponent.luminex_xponent_structure import ( + Analyte, + CalibrationItem, + Data, + Header, + Measurement, + MeasurementList, +) + + +def get_reader() -> CsvReader: + with open("tests/parsers/luminex_xponent/testdata/test_data.csv", "rb") as fp: + lines = read_to_lines(fp) + return CsvReader(lines) + + +def get_data() -> Data: + return Data( + header=Header( + model_number="FlexMAP 3D", # Program, col 4 + equipment_serial_number="FM3DD12341234", # SN + software_version="4.3.229.0", # Build + analytical_method_identifier="foo_bar", # ProtocolName + method_version="3", # ProtocolVersion + experimental_data_identifier="ABCD_1234_20231225", # Batch + sample_volume_setting=50, # SampleVolume + plate_well_count=96, # ProtocolPlate, column 5 (after Type) + measurement_time="2023-05-17T18:42:29+00:00", # BatchStartTime MM/DD/YYY HH:MM:SS %p -> YYYY-MM-DD HH:MM:SS + detector_gain_setting="Standard PMT", # ProtocolReporterGain + analyst="waldo", # Operator row + data_system_instance_identifier="ABCDEFG123456", # ComputerName + ), + calibration_data=[ + CalibrationItem( + name="F3DeCAL1 Calibration", + report="Passed", + time="2023-05-17T09:25:11+00:00", + ), + CalibrationItem( + name="F3DCAL2 Calibration", + report="Failed", + time="2023-05-17T09:25:33+00:00", + ), + CalibrationItem( + name="Fluidics Test", + report="Passed", + time="2023-05-17T09:28:43+00:00", + ), + ], + minimum_bead_count_setting=100, + measurement_list=MeasurementList( + measurements=[ + Measurement( + sample_identifier="Unknown1", + location_identifier="A1", + dilution_factor_setting=1, + assay_bead_count=881.0, + analytes=[ + Analyte( + analyte_name="alpha", + assay_bead_identifier="28", + assay_bead_count=30, + fluorescence=10921.5, + ), + Analyte( + analyte_name="bravo", + assay_bead_identifier="35", + assay_bead_count=42, + fluorescence=37214, + ), + Analyte( + analyte_name="charlie", + assay_bead_identifier="37", + assay_bead_count=42, + fluorescence=24978, + ), + ], + errors=[ + "maximum count. (0x4FF010AB)", + "specified count.", + ], + ), + Measurement( + sample_identifier="Unknown2", + location_identifier="B1", + dilution_factor_setting=3, + assay_bead_count=728.0, + analytes=[ + Analyte( + analyte_name="alpha", + assay_bead_identifier="28", + assay_bead_count=26, + fluorescence=8244, + ), + Analyte( + analyte_name="bravo", + assay_bead_identifier="35", + assay_bead_count=33, + fluorescence=35052, + ), + Analyte( + analyte_name="charlie", + assay_bead_identifier="37", + assay_bead_count=33, + fluorescence=22609, + ), + ], + ), + ] + ), + ) diff --git a/tests/parsers/luminex_xponent/luminex_xponent_parser_test.py b/tests/parsers/luminex_xponent/luminex_xponent_parser_test.py new file mode 100644 index 000000000..65f56147e --- /dev/null +++ b/tests/parsers/luminex_xponent/luminex_xponent_parser_test.py @@ -0,0 +1,24 @@ +import pytest + +from allotropy.parser_factory import Vendor +from tests.parsers.test_utils import from_file, validate_contents, validate_schema + +OUTPUT_FILES = ("luminex_xPONENT_example01",) + +VENDOR_TYPE = Vendor.LUMINEX_XPONENT + + +@pytest.mark.parametrize("output_file", OUTPUT_FILES) +def test_parse_luminex_xponent_to_asm(output_file: str) -> None: + test_filepath = f"tests/parsers/luminex_xponent/testdata/{output_file}.csv" + expected_filepath = f"tests/parsers/luminex_xponent/testdata/{output_file}.json" + allotrope_dict = from_file(test_filepath, VENDOR_TYPE) + validate_schema( + allotrope_dict, + "multi-analyte-profiling/BENCHLING/2024/01/multi-analyte-profiling.json", + ) + validate_contents( + allotrope_dict, + expected_filepath, + identifiers_to_exclude=["analyte identifier", "measurement identifier"], + ) diff --git a/tests/parsers/luminex_xponent/luminex_xponent_structure_test.py b/tests/parsers/luminex_xponent/luminex_xponent_structure_test.py new file mode 100644 index 000000000..0dcb8bc83 --- /dev/null +++ b/tests/parsers/luminex_xponent/luminex_xponent_structure_test.py @@ -0,0 +1,231 @@ +import pandas as pd +import pytest + +from allotropy.exceptions import AllotropeConversionError +from allotropy.parsers.lines_reader import CsvReader +from allotropy.parsers.luminex_xponent.luminex_xponent_structure import ( + Analyte, + CalibrationItem, + Data, + Header, + Measurement, + MeasurementList, +) +from allotropy.parsers.utils.timestamp_parser import TimestampParser +from tests.parsers.luminex_xponent.luminex_xponent_data import get_data, get_reader + +TIMESTAMP_PARSER = TimestampParser() + + +def get_result_lines(remove: str = "") -> list[str]: + lines = [ + "DataType:,Median,", + "Location,Sample,alpha,bravo,Total Events", + '"1(1,A1)",Unknown1,10921.5,37214,881', + ",,", + "DataType:,Count,", + "Location,Sample,alpha,bravo,Total Events", + '"1(1,A1)",Unknown1,30,42,881', + ",,", + "DataType:,Units,", + "Analyte:,alpha,bravo", + "BeadID:,28,35", + "Units:,Bead,Bead", + ",,", + "DataType:,Dilution Factor,", + "Location,Sample,Dilution Factor", + '"1(1,A1)",Unknown1,1', + ",,", + "DataType:,Warnings/Errors,", + "Location,Status,Message", + '"1,A1",Warning,Warning msg. (0x4FF010AB)', + '"1,A1",Warning,Another Warning.', + ",,", + ] + headers = { + "Median": 0, + "Count": 4, + "Units": 8, + "Dilution Factor": 13, + "Warnings/Errors": 17, + } + + if remove in headers: + del lines[headers[remove]] + + return lines + + +@pytest.mark.short +def test_create_header() -> None: + data = pd.DataFrame.from_dict( + { + "Program": ["xPonent", None, "Model"], + "Build": ["1.1.0"], + "SN": ["SN1234"], + "Batch": ["ABC_0000"], + "ComputerName": ["AAA000"], + "ProtocolName": ["Order66"], + "ProtocolVersion": ["5"], + "SampleVolume": ["1 uL"], + "BatchStartTime": ["1/17/2024 7:41:29 AM"], + "ProtocolPlate": [None, None, "Type", 10], + "ProtocolReporterGain": ["Pro MAP"], + }, + orient="index", + ).T + header = Header.create(data, TIMESTAMP_PARSER) + + assert header == Header( + model_number="Model", # Program, col 4 + software_version="1.1.0", # Build + equipment_serial_number="SN1234", # SN + analytical_method_identifier="Order66", # ProtocolName + method_version="5", # ProtocolVersion + experimental_data_identifier="ABC_0000", # Batch + sample_volume_setting=1, # SampleVolume + plate_well_count=10, # ProtocolPlate, column 5 (after Type) + measurement_time="2024-01-17T07:41:29+00:00", # BatchStartTime MM/DD/YYY HH:MM:SS %p -> YYYY-MM-DD HH:MM:SS + detector_gain_setting="Pro MAP", # ProtocolReporterGain + analyst=None, # Operator row + data_system_instance_identifier="AAA000", # ComputerName + ) + + +@pytest.mark.parametrize( + "required_col", + [ + "Program", + "Build", + "SN", + "Batch", + "ComputerName", + "ProtocolName", + "ProtocolVersion", + "SampleVolume", + "BatchStartTime", + "ProtocolPlate", + "ProtocolReporterGain", + ], +) +@pytest.mark.short +def test_create_heder_without_required_col(required_col: str) -> None: + data = pd.DataFrame.from_dict( + { + "Program": ["xPonent", None, "Model"], + "Build": ["1.0.1"], + "SN": ["SN1234"], + "Batch": ["ABC_0000"], + "ComputerName": ["AAA000"], + "ProtocolName": ["Order66"], + "ProtocolVersion": ["5"], + "SampleVolume": ["1 uL"], + "BatchStartTime": ["1/17/2024 7:41:29 AM"], + "ProtocolPlate": [None, None, "Type", 10], + "ProtocolReporterGain": ["Pro MAP"], + }, + orient="index", + ).T + + error_msg = f"Expected non-null value for {required_col}." + if required_col in ("Program", "ProtocolPlate"): + error_msg = f"Unable to find {required_col} data on header block." + + with pytest.raises(AllotropeConversionError, match=error_msg): + Header.create(data.drop(columns=[required_col]), TIMESTAMP_PARSER) + + +@pytest.mark.short +def test_create_calibration_item() -> None: + name = "Device Calibration" + report = "Passed" + + calibration_item = CalibrationItem.create( + f"Last {name},{report} 05/17/2023 09:25:11", TIMESTAMP_PARSER + ) + + assert calibration_item == CalibrationItem( + name, report, "2023-05-17T09:25:11+00:00" + ) + + +@pytest.mark.short +def test_create_calibration_item_invalid_line_format() -> None: + bad_line = "Bad line." + error = f"Expected at least two columns on the calibration line, got: {bad_line}" + with pytest.raises(AllotropeConversionError, match=error): + CalibrationItem.create(bad_line, TIMESTAMP_PARSER) + + +@pytest.mark.short +def test_create_calibration_item_invalid_calibration_result() -> None: + bad_result = "bad_result" + bad_line = f"Last CalReport,{bad_result}" + error = f"Invalid calibration result format, got: {bad_result}" + with pytest.raises(AllotropeConversionError, match=error): + CalibrationItem.create(bad_line, TIMESTAMP_PARSER) + + +@pytest.mark.short +def test_create_calibration_item_invalid_calibration_time() -> None: + invalid_time = "bad datetime" + bad_line = f"Last CalReport, Passed {invalid_time}" + error = f"Could not parse time '{invalid_time}'." + with pytest.raises(AllotropeConversionError, match=error): + CalibrationItem.create(bad_line, TIMESTAMP_PARSER) + + +@pytest.mark.short +def test_create_measurement_list() -> None: + reader = CsvReader(get_result_lines()) + + assert MeasurementList.create(reader) == MeasurementList( + measurements=[ + Measurement( + sample_identifier="Unknown1", + location_identifier="A1", + dilution_factor_setting=1, + assay_bead_count=881, + analytes=[ + Analyte( + analyte_name="alpha", + assay_bead_identifier="28", + assay_bead_count=30, + fluorescence=10921.5, + ), + Analyte( + analyte_name="bravo", + assay_bead_identifier="35", + assay_bead_count=42, + fluorescence=37214, + ), + ], + errors=[ + "Warning msg. (0x4FF010AB)", + "Another Warning.", + ], + ) + ] + ) + + +@pytest.mark.parametrize( + "table_name", + ["Median", "Count", "Units", "Dilution Factor"], +) +@pytest.mark.short +def test_create_measurement_list_without_required_table_then_raise( + table_name: str, +) -> None: + reader = CsvReader(get_result_lines(remove=table_name)) + + with pytest.raises( + AllotropeConversionError, match=f"Unable to find {table_name} table." + ): + MeasurementList.create(reader) + + +def test_create_data() -> None: + data = Data.create(get_reader(), TIMESTAMP_PARSER) + + assert data == get_data() diff --git a/tests/parsers/luminex_xponent/testdata/luminex_xPONENT_example01.json b/tests/parsers/luminex_xponent/testdata/luminex_xPONENT_example01.json new file mode 100644 index 000000000..25860ff09 --- /dev/null +++ b/tests/parsers/luminex_xponent/testdata/luminex_xPONENT_example01.json @@ -0,0 +1,31808 @@ +{ + "$asm.manifest": "http://purl.allotrope.org/manifests/multi-analyte-profiling/BENCHLING/2024/01/multi-analyte-profiling.manifest", + "multi analyte profiling aggregate document": { + "device system document": { + "model number": "FlexMAP 3D", + "equipment serial number": "FM3DD12341234", + "calibration aggregate document": { + "calibration document": [ + { + "calibration name": "F3DeCAL1 Calibration", + "calibration time": "2023-05-17T09:25:11+00:00", + "calibration report": "Passed" + }, + { + "calibration name": "F3DCAL2 Calibration", + "calibration time": "2023-05-17T09:25:33+00:00", + "calibration report": "Passed" + }, + { + "calibration name": "F3DCAL3 Calibration", + "calibration time": "2023-05-17T09:25:50+00:00", + "calibration report": "Passed" + }, + { + "calibration name": "F3DeVER1 Verification", + "calibration time": "2023-05-17T09:27:16+00:00", + "calibration report": "Passed" + }, + { + "calibration name": "F3DVER2 Verification", + "calibration time": "2023-05-17T09:27:57+00:00", + "calibration report": "Passed" + }, + { + "calibration name": "Fluidics Test", + "calibration time": "2023-05-17T09:28:43+00:00", + "calibration report": "Passed" + } + ] + } + }, + "multi analyte profiling document": [ + { + "measurement aggregate document": { + "measurement document": [ + { + "measurement identifier": "fa8b66c8-229b-427b-be42-913953ab1e38", + "measurement time": "2023-05-17T18:42:29+00:00", + "sample document": { + "sample identifier": "Unknown1", + "location identifier": "A1" + }, + "device control aggregate document": { + "device control document": [ + { + "device type": "multi analyte profiling analyzer", + "sample volume setting": { + "value": 50.0, + "unit": "μL" + }, + "dilution factor setting": { + "value": 1.0, + "unit": "(unitless)" + }, + "detector gain setting": "Standard PMT", + "minimum assay bead count setting": { + "value": 100.0, + "unit": "(unitless)" + } + } + ] + }, + "assay bead count": { + "value": 881.0, + "unit": "#" + }, + "analyte aggregate document": { + "analyte document": [ + { + "analyte identifier": "645a2e97-4756-4b9e-91d5-d62da068a3b8", + "analyte name": "alpha", + "assay bead identifier": "28", + "assay bead count": { + "value": 30.0, + "unit": "#" + }, + "fluorescence": { + "value": 10921.5, + "unit": "RFU", + "has statistic datum role": "median role" + } + }, + { + "analyte identifier": "53220e0b-fc2c-4b2d-a7e5-14ad4f0bbc24", + "analyte name": "bravo", + "assay bead identifier": "35", + "assay bead count": { + "value": 42.0, + "unit": "#" + }, + "fluorescence": { + "value": 37214.0, + "unit": "RFU", + "has statistic datum role": "median role" + } + }, + { + "analyte identifier": "bdd8199f-1cd8-48e7-ae3f-908ba12cc2a1", + "analyte name": "charlie", + "assay bead identifier": "37", + "assay bead count": { + "value": 42.0, + "unit": "#" + }, + "fluorescence": { + "value": 24978.0, + "unit": "RFU", + "has statistic datum role": "median role" + } + }, + { + "analyte identifier": "3a3c3a11-dfa1-4e64-9283-93ea2c7e0eb9", + "analyte name": "delta", + "assay bead identifier": "39", + "assay bead count": { + "value": 39.0, + "unit": "#" + }, + "fluorescence": { + "value": 18216.0, + "unit": "RFU", + "has statistic datum role": "median role" + } + }, + { + "analyte identifier": "3d9dce60-d5ba-4224-86fd-29addba7162f", + "analyte name": "echo", + "assay bead identifier": "44", + "assay bead count": { + "value": 38.0, + "unit": "#" + }, + "fluorescence": { + "value": 9048.5, + "unit": "RFU", + "has statistic datum role": "median role" + } + }, + { + "analyte identifier": "10ac676e-7ee7-4794-a5d3-abc74801b363", + "analyte name": "foxtrot", + "assay bead identifier": "46", + "assay bead count": { + "value": 36.0, + "unit": "#" + }, + "fluorescence": { + "value": 29681.5, + "unit": "RFU", + "has statistic datum role": "median role" + } + }, + { + "analyte identifier": "cc9f4f92-d936-47b0-a462-db2aea1a8c63", + "analyte name": "golf", + "assay bead identifier": "48", + "assay bead count": { + "value": 44.0, + "unit": "#" + }, + "fluorescence": { + "value": 34385.0, + "unit": "RFU", + "has statistic datum role": "median role" + } + }, + { + "analyte identifier": "cfcdb477-00fa-422c-818f-7b81d9fada30", + "analyte name": "hotel", + "assay bead identifier": "53", + "assay bead count": { + "value": 51.0, + "unit": "#" + }, + "fluorescence": { + "value": 29026.0, + "unit": "RFU", + "has statistic datum role": "median role" + } + }, + { + "analyte identifier": "b5d7e3a4-12ad-4384-be0f-c1fcd152d851", + "analyte name": "india", + "assay bead identifier": "55", + "assay bead count": { + "value": 45.0, + "unit": "#" + }, + "fluorescence": { + "value": 31395.0, + "unit": "RFU", + "has statistic datum role": "median role" + } + }, + { + "analyte identifier": "c0e602a2-6f18-4323-bc92-b8665a883980", + "analyte name": "juliett", + "assay bead identifier": "62", + "assay bead count": { + "value": 53.0, + "unit": "#" + }, + "fluorescence": { + "value": 28313.0, + "unit": "RFU", + "has statistic datum role": "median role" + } + }, + { + "analyte identifier": "bb32abba-6a43-4b59-b71c-cd577929fbba", + "analyte name": "kilo", + "assay bead identifier": "57", + "assay bead count": { + "value": 32.0, + "unit": "#" + }, + "fluorescence": { + "value": 25691.0, + "unit": "RFU", + "has statistic datum role": "median role" + } + }, + { + "analyte identifier": "b7bad2ae-294b-4f83-ab6d-6f8419a58241", + "analyte name": "lima", + "assay bead identifier": "65", + "assay bead count": { + "value": 46.0, + "unit": "#" + }, + "fluorescence": { + "value": 29049.0, + "unit": "RFU", + "has statistic datum role": "median role" + } + }, + { + "analyte identifier": "1ea45caa-118c-4fcc-b8b8-0d8de515025d", + "analyte name": "mike", + "assay bead identifier": "68", + "assay bead count": { + "value": 37.0, + "unit": "#" + }, + "fluorescence": { + "value": 27508.0, + "unit": "RFU", + "has statistic datum role": "median role" + } + }, + { + "analyte identifier": "50fcbbb2-00c9-4069-ba2c-bad55f2a4caa", + "analyte name": "november", + "assay bead identifier": "15", + "assay bead count": { + "value": 59.0, + "unit": "#" + }, + "fluorescence": { + "value": 28957.0, + "unit": "RFU", + "has statistic datum role": "median role" + } + }, + { + "analyte identifier": "1a78ac96-2a1e-44a8-9c5e-93814abd876e", + "analyte name": "oscar", + "assay bead identifier": "72", + "assay bead count": { + "value": 37.0, + "unit": "#" + }, + "fluorescence": { + "value": 36777.0, + "unit": "RFU", + "has statistic datum role": "median role" + } + }, + { + "analyte identifier": "c362f7b7-88bd-4d90-b5ab-89bd09f10d91", + "analyte name": "papa", + "assay bead identifier": "75", + "assay bead count": { + "value": 25.0, + "unit": "#" + }, + "fluorescence": { + "value": 29256.0, + "unit": "RFU", + "has statistic datum role": "median role" + } + }, + { + "analyte identifier": "c96bd708-bff7-4377-83b8-8dab72e5fd48", + "analyte name": "quebec", + "assay bead identifier": "78", + "assay bead count": { + "value": 41.0, + "unit": "#" + }, + "fluorescence": { + "value": 29049.0, + "unit": "RFU", + "has statistic datum role": "median role" + } + }, + { + "analyte identifier": "a96e41bb-5ff2-42eb-a9ae-0938b043dc82", + "analyte name": "romeo", + "assay bead identifier": "25", + "assay bead count": { + "value": 38.0, + "unit": "#" + }, + "fluorescence": { + "value": 24058.0, + "unit": "RFU", + "has statistic datum role": "median role" + } + }, + { + "analyte identifier": "95319eb1-c3f4-4c34-8bf8-6d6a4be979ad", + "analyte name": "sierra", + "assay bead identifier": "33", + "assay bead count": { + "value": 49.0, + "unit": "#" + }, + "fluorescence": { + "value": 26611.0, + "unit": "RFU", + "has statistic datum role": "median role" + } + }, + { + "analyte identifier": "b4be3ce2-ea29-4b37-873f-252c00477c9d", + "analyte name": "tango", + "assay bead identifier": "19", + "assay bead count": { + "value": 50.0, + "unit": "#" + }, + "fluorescence": { + "value": 13923.0, + "unit": "RFU", + "has statistic datum role": "median role" + } + 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bead count": { + "value": 141.0, + "unit": "#" + }, + "fluorescence": { + "value": 35.0, + "unit": "RFU", + "has statistic datum role": "median role" + } + } + ] + } + } + ], + "analytical method identifier": "foo_bar", + "method version": "3", + "experimental data identifier": "ABCD_1234_20231225", + "container type": "well plate", + "plate well count": { + "value": 96.0, + "unit": "#" + } + }, + "analyst": "waldo" + } + ], + "data system document": { + "data system instance identifier": "ABCDEFG123456", + "file name": "luminex_xPONENT_example01.csv", + "software name": "xPONENT", + "software version": "4.3.229.0", + "ASM converter name": "allotropy", + "ASM converter version": "0.1.13" + } + } +} \ No newline at end of file diff --git a/tests/parsers/luminex_xponent/testdata/test_data.csv b/tests/parsers/luminex_xponent/testdata/test_data.csv new file mode 100644 index 000000000..e97bd9424 --- /dev/null +++ b/tests/parsers/luminex_xponent/testdata/test_data.csv @@ -0,0 +1,81 @@ +Program,xPONENT,,FlexMAP 3D,,,,,,,,,,,,,,,,,,,, +Build,4.3.229.0,,,,,,,,,,,,,,,,,,,,,, +Date,05/17/2023,6:42 PM,,,,,,,,,,,,,,,,,,,,, +,,,,,,,,,,,,,,,,,,,,,,, +SN,FM3DD12341234,,,,,,,,,,,,,,,,,,,,,, +Batch,ABCD_1234_20231225,,,,,,,,,,,,,,,,,,,,,, +Operator,waldo,,,,,,,,,,,,,,,,,,,,,, +ComputerName,ABCDEFG123456,,,,,,,,,,,,,,,,,,,,,, +ProtocolName,foo_bar,,,,,,,,,,,,,,,,,,,,,, +ProtocolVersion,3,,,,,,,,,,,,,,,,,,,,,, +ProtocolDescription,baz,,,,,,,,,,,,,,,,,,,,,, +SampleVolume,50 uL,,,,,,,,,,,,,,,,,,,,,, +BatchStartTime,5/17/2023 6:42:29 PM,,,,,,,,,,,,,,,,,,,,,, +ProtocolPlate,Name,Current 96-well plate,Type,96,Plates,1,,,,,,,,,,,,,,,,, +ProtocolMicrosphere,Map,FlexMAP 3D Map,Type,MagPlex,Count,21,,,,,,,,,,,,,,,,, +ProtocolReporterGain,Standard PMT,,,,,,,,,,,,,,,,,,,,,, +ProtocolAnalysis,Off,,,,,,,,,,,,,,,,,,,,,, +,,,,,,,,,,,,,,,,,,,,,,, +Most Recent Calibration and Verification Results:,,,,,,,,,,,,,,,,,,,,,,, +Last F3DeCAL1 Calibration,Passed 05/17/2023 09:25:11,,,,,,,,,,,,,,,,,,,,,, +Last F3DCAL2 Calibration,Failed 05/17/2023 09:25:33,,,,,,,,,,,,,,,,,,,,,, +Last Fluidics Test,Passed 05/17/2023 09:28:43,,,,,,,,,,,,,,,,,,,,,, +,,,,,,,,,,,,,,,,,,,,,,, +CALInfo:,,,,,,,,,,,,,,,,,,,,,,, +Classification Calibrator Extended,,,,,,,,,,,,,,,,,,,,,,, +Lot,ExpirationDate,CalibrationTime,DDTemp,CL1Temp,CL2Temp,CL3Temp,DDVolts,CL1Volts,CL2Volts,CL3Volts,DDRVal,CL1RVal,CL2RVal,CL3RVal,Result,MachineSerialNo,,,,,,, +B12345,02/08/2024,5/17/2023 9:24:54 AM,23.43,24.37,24.37,24.21,76.41,106.07,113.08,109.61,530,1062,1225,1222,Pass,FM3DD12341234,,,,,,, +B67890,01/28/2024,5/17/2023 9:25:19 AM,23.32,24.45,24.34,24.27,49.23,106.36,113.31,109.86,270,1070,1236,1231,Pass,FM3DD12341234,,,,,,, +Reporter Calibrator,,,,,,,,,,,,,,,,,,,,,,, +Lot,ExpirationDate,CalibrationTime,RP1(1)Volts,RP1(1)Val,RP1(2)Volts,RP1(2)Val,Result,MachineSerialNo,,,,,,,,,,,,,,, +B11121,02/08/2024,5/17/2023 9:25:41 AM,583.9,3374.5,727.46,15391.5,Pass,FM3DD12341234,,,,,,,,,,,,,,, +Lot,ExpirationDate,CalibrationTime,RP1Volts,RP1Val,Result,MachineSerialNo,,,,,,,,,,,,,,,,, +B31415,02/08/2024,5/17/2023 9:25:58 AM,727.28,15508,Pass,FM3DD12341234,,,,,,,,,,,,,,,,, +,,,,,,,,,,,,,,,,,,,,,,, +,,,,,,,,,,,,,,,,,,,,,,, +Samples,96,Min Events,100,Per Bead,,,,,,,,,,,,,,,,,,, +,,,,,,,,,,,,,,,,,,,,,,, +Results,,,,,,,,,,,,,,,,,,,,,,, +,,,,,,,,,,,,,,,,,,,,,,, +DataType:,Median,,,,,,,,,,,,,,,,,,,,,, +Location,Sample,alpha,bravo,charlie,Total Events +"1(1,A1)",Unknown1,10921.5,37214,24978,881 +"2(1,B1)",Unknown2,8244,35052,22609,728 +,,,,,,,,,,,,,,,,,,,,,,, +DataType:,Net MFI,,,,,,,,,,,,,,,,,,,,,, +Location,Sample,alpha,bravo,charlie,Total Events +"1(1,A1)",Unknown1,10921.5,37214,24978,881 +"2(1,B1)",Unknown2,8244,35052,22609,728 +,,,,,,,,,,,,,,,,,,,,,,, +DataType:,Count,,,,,,,,,,,,,,,,,,,,,, +Location,Sample,alpha,bravo,charlie,Total Events +"1(1,A1)",Unknown1,30,42,42,881 +"2(1,B1)",Unknown2,26,33,33,728 +,,,,,,,,,,,,,,,,,,,,,,, +,,,,,,,,,,,,,,,,,,,,,,, +DataType:,Units,,,,,,,,,,,,,,,,,,,,,, +Analyte:,alpha,bravo,charlie,, +BeadID:,28,35,37,, +Units:,Bead,Bead,Bead,, +,,,,,,,,,,,,,,,,,,,,,,, +DataType:,Per Bead Count,,,,,,,,,,,,,,,,,,,,,, +Analyte:,alpha,bravo,charlie,, +BeadID:,28,35,37,, +Per Bead:,25,25,25,, +,,,,,,,,,,,,,,,,,,,,,,, +DataType:,Dilution Factor,,,,,,,,,,,,,,,,,,,,,, +Location,Sample,Dilution Factor,,,,,,,,,,,,,,,,,,,,, +"1(1,A1)",Unknown1,1,,,,,,,,,,,,,,,,,,,,, +"2(1,B1)",Unknown2,3,,,,,,,,,,,,,,,,,,,,, +,,,,,,,,,,,,,,,,,,,,,,, +,,,,,,,,,,,,,,,,,,,,,,, +DataType:,Analysis Types,,,,,,,,,,,,,,,,,,,,,, +Analyte:,alpha,bravo,charlie,, +AnalysisType,None,None,None,, +,,,,,,,,,,,,,,,,,,,,,,, +DataType:,Warnings/Errors,,,,,,,,,,,,,,,,,,,,,, +Location,Status,Message,,,,,,,,,,,,,,,,,,,,, +"1,A1",Warning,maximum count. (0x4FF010AB),,,,,,,,,,,,,,,,,,,,, +"1,A1",Warning,specified count.,,,,,,,,,,,,,,,,,,,,, +,,,,,,,,,,,,,,,,,,,,,,, +-- CRC --,,,,,,,,,,,,,,,,,,,,,,,