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data_filters

MultiLATSelectionFilter

Bases: DataFilter

Filter that selects the next LAT value.

min_lat = min_lat instance-attribute

__init__(min_lat=0)

Parameters:

Name Type Description Default
min_lat int

Minimum lat value. Defaults to 0.

0

apply(scalars)

Select next closest to min_lat non-nan LAT from 2d array of LAT values.

Parameters:

Name Type Description Default
scalars ndarray

array of scalars

required

Returns:

Type Description
ndarray

np.ndarray[N,]: Selected LAT values.

PeriodicRangeFilter

Bases: DataFilter

A data filter to constrain the data to a range. This range can be defined in a number of ways: - Using a period and an upper and lower bound: range of [lower_bound, upper_bound] - Using an upper and lower bound: range of [lower_bound, upper_bound], period = upper_bound - lower_bound - using a period and an upper bound: range of ]-inf, upper_bound] - using a period and a lower bound: range of [lower_bound, inf[ - using only a period: range of [0, period]

lower_bound = lower_bound instance-attribute

period = period instance-attribute

upper_bound = upper_bound instance-attribute

__init__(period=None, lower_bound=None, upper_bound=None)

Parameters:

Name Type Description Default
period float | NoneType

The period of the scalar data. Defaults to None.

None
lower_bound float | NoneType

The lower bound of the selected range (inclusive). Defaults to None.

None
upper_bound float | NoneType

The upper bound of the selected range (inclusive). Defaults to None.

None

apply(scalars)

Check if enough arguments are passed to use this method/NoneType and then limit the scalar range by using a method based on the arguments passed.

Parameters:

Name Type Description Default
scalars ndarray

array of scalars

required

Returns:

Name Type Description
scalars ndarray

updated array of scalars

ScalarCorrectionFilter

Bases: DataFilter

A data filter to make values smaller than a certain threshold larger than said threshold. This is done by adding a correction value (often the period) to each scalar until its value is above the threshold.

This can be used to make negative scalar values positive.

correction_value = correction_value instance-attribute

threshold = threshold instance-attribute

__init__(threshold, correction_value)

Parameters:

Name Type Description Default
threshold float

The threshold under which all values are corrected.

required
correction_value float

The value added N times to each scalar under the threshold.

required

apply(scalars)

Moves values below the threshold to above the threshold by adding the correction value N times.

Parameters:

Name Type Description Default
scalars ndarray

array of scalars

required

Returns:

Name Type Description
scalars ndarray

updated array of scalars

ScalarRangeFilter

Bases: DataFilter

A data filter to constrain the data to a range. Values outside the range are

marking_val = marking_val instance-attribute

max_threshold = max_threshold instance-attribute

min_threshold = min_threshold instance-attribute

__init__(min_threshold=None, max_threshold=None, marking_val=None)

Parameters:

Name Type Description Default
min_threshold float

The lower bound of the selected range (inclusive).

None
max_threshold float

The upper bound of the selected range (inclusive).

None
marking_val float

If a marking value is passed, all values outside the selected range are marked with said value (e.g. NaN, -1, etc.).

None

apply(scalars)

Apply the filter to remove or mark any values outside the selected range.

Parameters:

Name Type Description Default
scalars ndarray

array of scalars

required

Returns:

Name Type Description
scalars ndarray

updated array of scalars