seg1d.Segmenter.t_segments

property Segmenter.t_segments

Returns an array of segmented target data

Parameters:

None

Returns:

SegmentsList[Dict[str,numpy.array]]

applies the segment endpoints to the given target data t on all features.

Examples

>>> import numpy as np
>>> import seg1d

>>> #create an array of data
>>> x = np.linspace(-np.pi*2, np.pi*2, 500)
>>> #get an array of data from a sin function
>>> targ = np.sin(x)

>>> #Make an instance of the segmenter
>>> s = seg1d.Segmenter()
>>> #set scaling parameters
>>> s.minW,s.maxW,s.step = 98, 105, 1
>>> #Set target and reference data
>>> s.set_target(targ)

>>> #define a segment within the sine wave to use as reference
>>> s.add_reference(targ[75:100])
>>> #call the segmentation algorithm
>>> segments = s.segment()
>>> np.around(segments, decimals=7)
array([[ 75.       , 100.       ,   1.       ],
       [324.       , 348.       ,   0.9999992]])

>>> s.t_segments
[{'0': array([0.94988243, 0.94170965, 0.93293968, 0.92357809, 0.91363079,
       0.90310412, 0.89200474, 0.88033969, 0.86811636, 0.85534252,
       0.84202625, 0.82817601, 0.81380058, 0.79890907, 0.78351093,
       0.76761592, 0.75123412, 0.73437593, 0.71705202, 0.6992734 ,
       0.68105132, 0.66239735, 0.64332332, 0.62384133, 0.60396372])}, {'0': array([0.95374324, 0.94587102, 0.93739898, 0.92833248, 0.91867727,
       0.90843947, 0.89762559, 0.88624247, 0.87429733, 0.86179776,
       0.84875167, 0.83516734, 0.82105338, 0.80641875, 0.79127273,
       0.77562491, 0.75948523, 0.74286391, 0.72577151, 0.70821885,
       0.69021707, 0.67177759, 0.6529121 , 0.63363256])}]