The localisation and activity examples use different format of descriptor_map
eg. The localisation uses arrays of integers denoting the labels
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descriptor_map = { |
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'foyer' : [0], |
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'bedroom' : [1], |
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'living_room' : [2], |
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'bathroom' : [3] |
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} |
While the accelerometer example uses integers
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descriptor_map = { |
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'sitting' : 77, |
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'walking' : 78, |
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'washing' : 79, |
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'eating' : 80, |
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'sleeping': 81, |
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'studying': 82 |
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} |
What is the reasoning behind it, and which method should we choose as standard. A benefit from the list is that it could group labels, for example "upstairs" could be associated to [0, 1, 2], or "sedentary" as well.
I am not sure if there are collateral implications on this modification.
The localisation and activity examples use different format of descriptor_map
eg. The localisation uses arrays of integers denoting the labels
bHealth/examples/localisation_example.py
Lines 100 to 105 in 73bd95f
While the accelerometer example uses integers
bHealth/examples/accelerometer_example.py
Lines 114 to 121 in 73bd95f
What is the reasoning behind it, and which method should we choose as standard. A benefit from the list is that it could group labels, for example "upstairs" could be associated to [0, 1, 2], or "sedentary" as well.
I am not sure if there are collateral implications on this modification.