tsdat.qc.checkers

Classes

CheckFailDelta	Checks for deltas between consecutive values larger than 'fail_delta'.
CheckFailMax	Checks for values greater than 'fail_max'.
CheckFailMin	Checks for values less than 'fail_min'.
CheckFailRangeMax	Checks for values greater than 'fail_range'.
CheckFailRangeMin	Checks for values less than 'fail_range'.
CheckMissing	Checks if any data are missing. A variable's data are considered missing if they are
CheckMonotonic	Checks if any values are not ordered strictly monotonically (i.e. values must all be
CheckValidDelta	Checks for deltas between consecutive values larger than 'valid_delta'.
CheckValidMax	Checks for values greater than 'valid_max'.
CheckValidMin	Checks for values less than 'valid_min'.
CheckValidRangeMax	Checks for values greater than 'valid_range'.
CheckValidRangeMin	Checks for values less than 'valid_range'.
CheckWarnDelta	Checks for deltas between consecutive values larger than 'warn_delta'.
CheckWarnMax	Checks for values greater than 'warn_max'.
CheckWarnMin	Checks for values less than 'warn_min'.
CheckWarnRangeMax	Checks for values greater than 'warn_range'.
CheckWarnRangeMin	Checks for values less than 'warn_range'.

class tsdat.qc.checkers.CheckFailDelta

Bases: _CheckDelta

Checks for deltas between consecutive values larger than ‘fail_delta’.

attribute_name :str = fail_delta

class tsdat.qc.checkers.CheckFailMax

Bases: _CheckMax

Checks for values greater than ‘fail_max’.

attribute_name :str = fail_max

class tsdat.qc.checkers.CheckFailMin

Bases: _CheckMin

Checks for values less than ‘fail_min’.

attribute_name :str = fail_min

class tsdat.qc.checkers.CheckFailRangeMax

Bases: _CheckMax

Checks for values greater than ‘fail_range’.

attribute_name :str = fail_range

class tsdat.qc.checkers.CheckFailRangeMin

Bases: _CheckMin

Checks for values less than ‘fail_range’.

attribute_name :str = fail_range

class tsdat.qc.checkers.CheckMissing

Bases: tsdat.qc.base.QualityChecker

Checks if any data are missing. A variable’s data are considered missing if they are set to the variable’s _FillValue (if it has a _FillValue) or NaN (NaT for datetime- like variables).

Class Methods

run	Identifies and flags quality problems with the data.

Method Descriptions

run(self, dataset: xarray.Dataset, variable_name: str) → numpy.typing.NDArray[numpy.bool8]

Identifies and flags quality problems with the data.

Checks the quality of a specific variable in the dataset and returns the results of the check as a boolean array where True values represent quality problems and False values represent data that passes the quality check.

QualityCheckers should not modify dataset variables; changes to the dataset should be made by QualityHandler(s), which receive the results of a QualityChecker as input.

Parameters

• dataset (xr.Dataset) – The dataset containing the variable to check.

• variable_name (str) – The name of the variable to check.

Returns

NDArray[np.bool8] – The results of the quality check, where True values indicate a quality problem.

class tsdat.qc.checkers.CheckMonotonic

Bases: tsdat.qc.base.QualityChecker

Checks if any values are not ordered strictly monotonically (i.e. values must all be increasing or all decreasing). The check marks all values as failed if any data values are not ordered monotonically.

class Parameters

Bases: pydantic.BaseModel

dim :Optional[str]

require_decreasing :bool = False

require_increasing :bool = False

Class Methods

check_monotonic_not_increasing_and_decreasing

Method Descriptions

classmethod check_monotonic_not_increasing_and_decreasing(cls, inc: bool, values: Dict[str, Any]) → bool

parameters :CheckMonotonic.Parameters

Class Methods

get_axis
run	Identifies and flags quality problems with the data.

Method Descriptions

get_axis(self, variable: xarray.DataArray) → int

run(self, dataset: xarray.Dataset, variable_name: str) → numpy.typing.NDArray[numpy.bool8]

Identifies and flags quality problems with the data.

Checks the quality of a specific variable in the dataset and returns the results of the check as a boolean array where True values represent quality problems and False values represent data that passes the quality check.

QualityCheckers should not modify dataset variables; changes to the dataset should be made by QualityHandler(s), which receive the results of a QualityChecker as input.

Parameters

• dataset (xr.Dataset) – The dataset containing the variable to check.

• variable_name (str) – The name of the variable to check.

Returns

NDArray[np.bool8] – The results of the quality check, where True values indicate a quality problem.

class tsdat.qc.checkers.CheckValidDelta

Bases: _CheckDelta

Checks for deltas between consecutive values larger than ‘valid_delta’.

attribute_name :str = valid_delta

class tsdat.qc.checkers.CheckValidMax

Bases: _CheckMax

Checks for values greater than ‘valid_max’.

attribute_name :str = valid_max

class tsdat.qc.checkers.CheckValidMin

Bases: _CheckMin

Checks for values less than ‘valid_min’.

attribute_name :str = valid_min

class tsdat.qc.checkers.CheckValidRangeMax

Bases: _CheckMax

Checks for values greater than ‘valid_range’.

attribute_name :str = valid_range

class tsdat.qc.checkers.CheckValidRangeMin

Bases: _CheckMin

Checks for values less than ‘valid_range’.

attribute_name :str = valid_range

class tsdat.qc.checkers.CheckWarnDelta

Bases: _CheckDelta

Checks for deltas between consecutive values larger than ‘warn_delta’.

attribute_name :str = warn_delta

class tsdat.qc.checkers.CheckWarnMax

Bases: _CheckMax

Checks for values greater than ‘warn_max’.

attribute_name :str = warn_max

class tsdat.qc.checkers.CheckWarnMin

Bases: _CheckMin

Checks for values less than ‘warn_min’.

attribute_name :str = warn_min

class tsdat.qc.checkers.CheckWarnRangeMax

Bases: _CheckMax

Checks for values greater than ‘warn_range’.

attribute_name :str = warn_range

class tsdat.qc.checkers.CheckWarnRangeMin

Bases: _CheckMin

Checks for values less than ‘warn_range’.

attribute_name :str = warn_range