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Make table visible in Doryab's documentation

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JulioV 2020-07-24 20:26:15 -04:00
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docs/features/extracted.rst
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@ -676,30 +676,30 @@ minutes_data_used This is NOT a feature. This is just a quality control che
**Available Location Features** **Available Location Features**
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Name Units Description Name Units Description
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locationvariance :math:`meters^2` The sum of the variances of the latitude and longitude columns. locationvariance :math:`meters^2` The sum of the variances of the latitude and longitude columns.
loglocationvariance Log of the sum of the variances of the latitude and longitude columns. loglocationvariance Log of the sum of the variances of the latitude and longitude columns.
totaldistance meters Total distance travelled in a ``day_segment`` using the haversine formula. totaldistance meters Total distance travelled in a ``day_segment`` using the haversine formula.
averagespeed km/hr Average speed in a ``day_segment` considering only the instances labeled as Moving. averagespeed km/hr Average speed in a ``day_segment` considering only the instances labeled as Moving.
varspeed km/hr Speed variance in a ``day_segment`` considering only the instances labeled as Moving. varspeed km/hr Speed variance in a ``day_segment`` considering only the instances labeled as Moving.
circadianmovement "It encodes the extent to which a person’s location patterns follow a 24-hour circadian cycle." (Doryab et. al. 2019) circadianmovement "It encodes the extent to which a person’s location patterns follow a 24-hour circadian cycle." (Doryab et. al. 2019)
numberofsignificantplaces places Number of significant locations visited. It is calculated using the DBSCAN clustering algorithm which takes in EPS and MIN_SAMPLES as paramters to identify clusters. Each cluster is a significant place. numberofsignificantplaces places Number of significant locations visited. It is calculated using the DBSCAN clustering algorithm which takes in EPS and MIN_SAMPLES as paramters to identify clusters. Each cluster is a significant place.
numberlocationtransitions transitions Number of movements between any two clusters in a ``day_segment``. numberlocationtransitions transitions Number of movements between any two clusters in a ``day_segment``.
radiusgyration meters Quantifies the area covered by a participant radiusgyration meters Quantifies the area covered by a participant
timeattop1location minutes Time spent at the most significant location. timeattop1location minutes Time spent at the most significant location.
timeattop2location minutes Time spent at the 2nd most significant location. timeattop2location minutes Time spent at the 2nd most significant location.
timeattop3location minutes Time spent at the 3rd most significant location. timeattop3location minutes Time spent at the 3rd most significant location.
movingtostaticratio Ratio between the number of rows labeled Moving versus Static movingtostaticratio Ratio between the number of rows labeled Moving versus Static
outlierstimepercent Ratio between the number of rows that belong to non-significant clusters divided by the total number of rows in a ``day_segment``. outlierstimepercent Ratio between the number of rows that belong to non-significant clusters divided by the total number of rows in a ``day_segment``.
maxlengthstayatclusters minutes Maximum time spent in a cluster (significant location). maxlengthstayatclusters minutes Maximum time spent in a cluster (significant location).
minlengthstayatclusters minutes Minimum time spent in a cluster (significant location). minlengthstayatclusters minutes Minimum time spent in a cluster (significant location).
meanlengthstayatclusters minutes Average time spent in a cluster (significant location). meanlengthstayatclusters minutes Average time spent in a cluster (significant location).
stdlengthstayatclusters minutes Standard deviation of time spent in a cluster (significant location). stdlengthstayatclusters minutes Standard deviation of time spent in a cluster (significant location).
locationentropy nats Shannon Entropy computed over the row count of each cluster (significant location), it will be higher the more rows belong to a cluster (i.e. the more time a participant spent at a significant location). locationentropy nats Shannon Entropy computed over the row count of each cluster (significant location), it will be higher the more rows belong to a cluster (i.e. the more time a participant spent at a significant location).
normalizedlocationentropy nats Shannon Entropy computed over the row count of each cluster (significant location) divided by the number of clusters, it will be higher the more rows belong to a cluster (i.e. the more time a participant spent at a significant location). normalizedlocationentropy nats Shannon Entropy computed over the row count of each cluster (significant location) divided by the number of clusters, it will be higher the more rows belong to a cluster (i.e. the more time a participant spent at a significant location).
============================ ========= ============= ============================ ================ =============
**Assumptions/Observations:** **Assumptions/Observations:**