polpo.preprocessing#

Classes#

BranchingPipeline(branches[, merger])

Constant(value)

Constant.

Contains(item[, negate])

Check if an item is in a collection.

ContainsAll(items[, negate])

Check if a subset of items in a collection.

DataPrinter([silent])

DecorateToIterable([step])

EmptyRemover()

EmptySkipper([step])

Eval(expr[, imports])

Evaluate string.

EvalFromImport(import_)

Evaluate imported function.

ExceptionToWarning(step[, warn])

Filter(func[, collection_type, to_iter])

IdentityStep()

IfCondition(step, else_step, condition)

IfEmpty(step, else_step)

IndexMap(step[, index])

IndexSelector([index, repeat, step])

Lambda(args, expr[, imports])

Evaluate lambda function.

ListSqueeze([raise_])

Listify()

Map(step[, n_jobs, verbose, force_iter])

MethodApplier(*args, method, **kwargs)

Applies a named method with preset args and kwargs.

NestingSwapper()

NoneRemover()

NoneSkipper([step])

ParMap(step[, n_jobs, verbose])

PartiallyInitializedStep(Step[, pass_data])

Instantiate a step based on data.

Pipeline(steps[, data])

Prefix(prefix)

PreprocessingStep()

Preprocessing step.

RemoveIndex([index, inplace])

SerialMap(step[, pbar])

Sorter([key])

StepWithLogging(step, msg)

StepWrappingPreprocessingStep([step])

Truncater(value)

TupleWith(step[, incoming_first])

TupleWithIncoming(step)

Unnest()

WrapInList()

Modules#

base

dict

learning

load

mesh

mri

np

Preprocessing steps involving numpy arrays.

path

Preprocessing steps involving files.

pd

Preprocessing steps involving pandas dataframes.

point_cloud

ssh

str

Preprocessing steps involving strings.