neptoon.quality_control

quality_assessment¶

Classes:

DateTimeIndexValidator
ValidationError
QualityCheck
QualityAssessmentFlagBuilder
DataQualityAssessor

Functions:

apply
add_check
apply_checks
return_targets
builder
builder
change_saqc_scheme
apply_quality_assessment
add_custom_flag_builder
add_quality_check
import_checks_from_config
return_data_frame
return_flags_data_frame

DateTimeIndexValidator ¶

DateTimeIndexValidator(data_frame)

Validator class which checks that the supplied data frame has a datetime index

Init

Parameters:

Name	Type	Description	Default
`data_frame`	`DataFrame`	DataFrame to be checked	required

ValidationError ¶

Bases: Exception

Custom exception for validation errors.

QualityCheck ¶

QualityCheck(target, method, parameters={})

Creates quality check.

Examples:

Create a quality check that flags neutron intensity values outside the range 500-550:

>>> from neptoon.column_info import ColumnInfo
>>> from neptoon.quality_control import QualityCheck, QAMethod
>>>
>>> check = QualityCheck(
...     target=QATarget.RAW_NEUTRONS,
...     method=QAMethod.RANGE_CHECK,
...     params={
...         "lower_bound": 500,
...         "upper_bound": 550,
...     },
... )

See neptoon.quality_control.WhatParamsDoINeed if you need help on allowable params.

QualityAssessmentFlagBuilder ¶

QualityAssessmentFlagBuilder()

Staging place for the checks as they are built. First a user adds a check using the add_check method.

DataQualityAssessor ¶

DataQualityAssessor(data_frame, saqc_scheme='simple', saqc=None)

Base class for working with SaQC in neptoon. It handles creating the object and checks that the data going in has a datetime index (essential for working in SaQC).

Parameters:

Name	Type	Description	Default
`data_frame`	`DataFrame`	DataFrame containing time series data.	required

change_saqc_scheme ¶

change_saqc_scheme(scheme)

Changes the saqc_scheme for SaQC object.

Parameters:

Name	Type	Description	Default
`scheme`	`str`	String representing the scheme for flags. Can be: - simple - float - dmp - positional - annotated-float see https://rdm-software.pages.ufz.de/saqc/index.html	required

apply_quality_assessment ¶

apply_quality_assessment()

Cycles through the quality checks in the builder applying each of them to the data frame

add_custom_flag_builder ¶

add_custom_flag_builder(builder)

Add a custom built flag builder to the object.

Parameters:

Name	Type	Description	Default
`builder`	`QualityAssessmentFlagBuilder`	A flag builder - presumed to be pre-constructed	required

add_quality_check ¶

add_quality_check(check)

Can be a check or a list of checks to the internal QualitCheckBuilder

Parameters:

Name	Type	Description	Default
`check`	`QualityCheck \| List of QualityCheck`	Quality checks	required

import_checks_from_config ¶

import_checks_from_config(config)

Here could be a function for building the quality checks from a supplied config file

return_data_frame ¶

return_data_frame()

Returns the timeseries DataFrame.

Returns:

Type	Description
`DataFrame`	The main DataFrame

return_flags_data_frame ¶

return_flags_data_frame(current_flag_data_frame=None)

Returns the flag dataframe

Returns:

Type	Description
`DataFrame`	The DataFrame with assigned flags