virocon.intervals module

Interval definitions for the subsequent model fitting.

class virocon.intervals.NumberOfIntervalsSlicer(n_intervals, reference='center', include_max=True, value_range=None, **kwargs)[source]

Bases: virocon.intervals.IntervalSlicer

IntervalSlicer that uses a number of intervals to define intervals of equal width.

Parameters

  • n_intervals (int) – Number of intervals the dataset is split into.

  • reference (str or callable, optional) – Determines the reference value for each interval. If a string the following keywords are available: ‘center’: use the center / midpoint of the interval as reference, ‘left’: use the left / lower bound of the interval and ‘right’: use the right / upper bound of the interval as reference. If a callable, a function is expected, that maps from an array with the values of an interval to the reference of that interval (e.g. np.median). Defaults to ‘center’.

  • include_max (boolean, optional) – Determines if the upper boundary of the last interval is inclusive. True if inclusive. Defaults to True.

  • value_range (tuple or None, optional) – Determines the value range used for creating n_intervals equally sized intervals. If a tuple it contains the upper and lower limit of the range. If None the min and max of the data are used. Defaults to None.

  • min_n_points (int, optional) – Minimal number of points per interval. Intervals with fewer points are discarded. Defaults to 50.

  • min_n_intervals (int, optional) – Minimal number of intervals. Raises a RuntimeError if slicing resulted in fewer intervals. Defaults to 3.

Raises

RuntimeError – if slicing resulted in fewer than min_n_intervals intervals.

class virocon.intervals.PointsPerIntervalSlicer(n_points, reference=<function median>, last_full=True, **kwargs)[source]

Bases: virocon.intervals.IntervalSlicer

Uses a number of points per interval to define intervals.

Sorts the data and splits it into intervals with the same number of points. In general this results in intervals with varying width.

Parameters

  • n_points (int) – The number of points per interval.

  • reference (callable, optional) – Determines the reference value for each interval. A function is expected, that maps from an array with the values of an interval to the reference of that interval. Defaults to np.median.

  • last_full (boolean, optional) – If it is not possible to split the data in chunks with the same number of points, one interval will have fewer points. This determines if the last or the first interval should have n_points points. If True the last interval contains n_points points and the first interval contains the remaining points. Defaults to True.

  • min_n_points (int, optional) – Minimal number of points per interval. Intervals with fewer points are discarded. Defaults to 50.

  • min_n_intervals (int, optional) – Minimal number of intervals. Raises a RuntimeError if slicing resulted in fewer intervals. Defaults to 3.

Raises

RuntimeError – if slicing resulted in fewer than min_n_intervals intervals.

class virocon.intervals.WidthOfIntervalSlicer(width, reference='center', right_open=True, value_range=None, **kwargs)[source]

Bases: virocon.intervals.IntervalSlicer

IntervalSlicer that uses width of intervals to define intervals.

Parameters

  • width (float) – The width of each interval.

  • reference (str or callable, optional) – Determines the reference value for each interval. If a string the following keywords are available: ‘center’: use the center / midpoint of the interval as reference, ‘left’: use the left / lower bound of the interval and ‘right’: use the right / upper bound of the interval as reference. If a callable, a function is expected, that maps from an array with the values of an interval to the reference of that interval (e.g. np.median). Defaults to ‘center’.

  • right_open (boolean, optional) – Determines how the boundaries of the intervals are defined. Either the left or the right boundary is inclusive. Defaults to True, meaning the left boundary is inclusive and the right exclusive, i.e. \([a, b)\).

  • value_range (tuple, optional) – Determines the value range used for creating the intervals. If None, 0 and np.max(data) are used. If a 2-tuple it contains the lower and upper limit of the range. If either entry of the tuple is None the default for that entry is used. Defaults to None.

  • min_n_points (int, optional) – Minimal number of points per interval. Intervals with fewer points are discarded. Defaults to 50.

  • min_n_intervals (int, optional) – Minimal number of intervals. Raises a RuntimeError if slicing resulted in fewer intervals. Defaults to 3.

Raises

RuntimeError – if slicing resulted in fewer than min_n_intervals intervals.