dae.pheno.prepare package

Submodules

dae.pheno.prepare.individuals2ped module

dae.pheno.prepare.measure_classifier module

class dae.pheno.prepare.measure_classifier.ClassifierReport

Bases: object

Class used to collect clissifier reports.

DISTRIBUTION_CUTOFF = 20

MAX_CHARS = 32

calc_distribution_report(cursor: DuckDBPyConnection | None = None, instrument_table_name: str | None = None) → list[Any]

Construct measure distribution report.

static header_line(short: bool = False) → str

Construct clissifier report header line.

log_line(short: bool = False) → str

Construct a log line in clissifier report.

set_measure(measure: Box) → ClassifierReport

static short_attributes() → list[str]

static short_header_line() → str

class dae.pheno.prepare.measure_classifier.Convertible(value)

Bases: Enum

An enumeration.

nan = 0

non_numeric = 2

numeric = 1

class dae.pheno.prepare.measure_classifier.MeasureClassifier(config: Box)

Bases: object

Defines a measure classification report.

classify(rep: ClassifierReport) → MeasureType

Classify a measure based on classification report.

static convert_to_numeric(values: ndarray) → ndarray

Convert value to numeric.

static convert_to_string(values: ndarray) → ndarray

static meta_measures(cursor: DuckDBPyConnection, table_name: str, measure_name: str, report: ClassifierReport | None = None) → ClassifierReport

Build classifier meta report.

dae.pheno.prepare.measure_classifier.convert_to_numeric(val: Any) → float | float64

Convert passed value to float.

dae.pheno.prepare.measure_classifier.convert_to_string(val: Any) → str | None

Convert passed value to string.

dae.pheno.prepare.measure_classifier.is_convertible_to_numeric(val: Any) → Convertible

Check if the passed string is convertible to number.

dae.pheno.prepare.measure_classifier.is_nan(val: Any) → bool

Check if the passed value is a NaN.

dae.pheno.prepare.ped2individuals module

dae.pheno.prepare.pheno_prepare module

class dae.pheno.prepare.pheno_prepare.ClassifyMeasureTask(config: Box, instrument_name: str, instrument_table_name: str, measure_name: str, measure_desc: str, dbfile: str)

Bases: Task

Measure classification task.

build_meta_measure(cursor: DuckDBPyConnection) → None

Build measure meta data.

static create_default_measure(instrument_name: str, measure_name: str, measure_desc: str) → Box

Create empty measrue description.

done() → Any

run() → ClassifyMeasureTask

class dae.pheno.prepare.pheno_prepare.MeasureValuesTask(measure: Box, mdf: DataFrame)

Bases: Task

Task to prepare measure values.

done() → Any

run() → MeasureValuesTask

class dae.pheno.prepare.pheno_prepare.PrepareBase(config: Box)

Bases: PrepareCommon

Base class for phenotype data preparation tasks.

get_persons(force: bool = False) → dict[str, Any] | None

Return dictionary of all people in the pheno DB.

class dae.pheno.prepare.pheno_prepare.PrepareCommon

Bases: object

PED_COLUMNS_REQUIRED = ('family_id', 'person_id', 'mom_id', 'dad_id', 'sex', 'status')

PERSON_ID = 'person_id'

PID_COLUMN: str = '$Person_ID'

class dae.pheno.prepare.pheno_prepare.PreparePersons(config: Box)

Bases: PrepareBase

Praparation of individuals DB tables.

build_pedigree(pedfile: str | Path | TextIO) → DataFrame

Import pedigree data into the pheno DB.

save_pedigree(ped_df: DataFrame) → None

class dae.pheno.prepare.pheno_prepare.PrepareVariables(config: Box)

Bases: PreparePersons

Supports preparation of measurements.

build_instrument(instrument_name: str, descriptions: Callable | None = None) → None

Build and store all measures in an instrument.

build_pheno_common() → None

Build a pheno common instrument.

build_variables(instruments_dirname: str, description_path: str) → None

Build and store phenotype data into an sqlite database.

static create_default_measure(instrument_name: str, measure_name: str) → Box

Create default measure description.

static load_descriptions(description_path: str | None) → Callable | None

Load measure descriptions.

load_instrument(instrument_name: str, filenames: list[str]) → None

Load all measures in an instrument.

property log_filename: str

Construct a filename to use for logging work on phenotype data.

log_header() → None

log_measure(measure: Box, classifier_report: ClassifierReport) → None

Log measure classification.

class dae.pheno.prepare.pheno_prepare.Task

Bases: PrepareCommon

Preparation task that can be run in parallel.

done() → Any

run() → Task

class dae.pheno.prepare.pheno_prepare.TaskQueue

Bases: object

Queue of preparation tasks.

empty() → bool

get() → ApplyResult

put(task: ApplyResult) → None

dae.pheno.prepare.ssc_prepare module

Module contents