Numpy utilities

utilities for auxiliary numpy array processing

nan_helper_1d

 nan_helper_1d (y:numpy.ndarray)

*Helper to handle indices and logical indices of NaNs.

Parameters:

- y, 1d numpy array with possible NaNs

Returns:

- nans, logical indices of NaNs
- index, a function, with signature indices= index(logical_indices),
    to convert logical indices of NaNs to 'equivalent' indices

Example: linear interpolation of NaNs

>>> nans, x= nan_helper_1d(y)
>>> y[nans]= np.interp(x(nans), x(~nans), y[~nans])

sources:

https://stackoverflow.com/questions/6518811/interpolate-nan-values-in-a-numpy-array*

	Type	Details
y	ndarray	utils for handling indices and logical indices of NaNs
Returns	Tuple

source

nan_interp_1d

 nan_interp_1d (y:numpy.ndarray)

*Linear interpolation of NaNs.

Parameter:

- y, 1d numpy array with possible NaNs

Return:

- y, 1d numpy array with NaNs replaced by linear interpolation

Example: linear interpolation of NaNs

>>> y = nan_interp_1d(y)

sources:

https://stackoverflow.com/questions/6518811/interpolate-nan-values-in-a-numpy-array*

	Type	Details
y	ndarray	linear interpolation of NaNs
Returns	ndarray	np array with NaNs replaced by linear interpolation

source

ragged_nparray_list_interp

 ragged_nparray_list_interp (ragged_list_list:List[List], ob_num:int)

*Linear interpolation of NaNs.

Parameter:

- y, list ragged array

Return:

- y, 2d numpy array with missing elements replaced by linear interpolation

Example: linear interpolation of NaNs

>>> y = nan_interp_1d(y)

sources:

https://stackoverflow.com/questions/6518811/interpolate-nan-values-in-a-numpy-array*

	Type	Details
ragged_list_list	List	list to be interpolated with NaNs
ob_num	int	number of observations
Returns	ndarray	np array with NaNs replaced by linear interpolation

source

timestamps_from_can_strings

 timestamps_from_can_strings (can_timestamp_strings:List[str],
                              signal_freq:float, unit_num:int,
                              unit_duration:float)

*Extract timestamps from CAN strings.

Parameters:

- can_timestamp_strings, list of CAN strings
- signal_freq, signal frequency
- unit_num, number of CAN units
- unit_duration, duration in seconds per CAN unit

Return:

- timestamps, 1d numpy array of timestamps

Example: extract timestamps from “CAN” strings

>>> timestamps_arr = timestamps_from_can_strings(can_timestamp_strings)*

	Type	Details
can_timestamp_strings	List	list of strings from CAN
signal_freq	float	signal frequency
unit_num	int	number of CAN units
unit_duration	float	duration in seconds per CAN unit
Returns	ndarray	np array of timestamps