Description of all sound examples
Time scaling in all examples:
playback uses 50 data values per second, in time order; 15 minutes are 96 values per day, so a day becomes ca 2 secs (1.92), and a week becomes ca 14 secs (13.44). This time scale seemed well chosen, so after comparisons with faster and slower alternatives, we kept it for all examples.
Sound example 1 - map 5 powers to frequency
Value mapping:
Powers control the frequencies of 5 tones: data range is from 0 - 2.24 units. frequency = data_value * 500 + 200, so the resulting frequency range is 200 - 1320 Hz.
TeamA_1_FiveSines_PowersToFreqs.mp3
Sound example 2 - map 5 powers to amplitudes
map powers (data values) to the amplitudes of 5 different tones:
Much detail information is lost, the change that was audible in ex1 in the last 2 days is now hard to detect. This was tried because power and amplitude seemed to be a natural mapping choice; but resolution of amplitude is not high enough to be useful.
TeamA_2_FiveTones_PowersToAmps.mp3
Sound example 3 - map 5 powers to amplitudes and filter frequencies
powers control amplitudes and filter frequencies, so bright and loud means high energy levels. This works better than example 2.
TeamA_3_FiveTones_PowersToAmpsAndFilterfreqs.mp3
Sound example 4 - simple identification markers for the 5 channels
Each of the 5 channels is a sine oscillator with a different intensity of phase modulation (leading to a kind of different brightness). Also, the amplitude in all channels is controlled by the power; so zero consumption becomes silent.
TeamA_4_FiveFMSounds_IDbyModDepth.mp3
Sound example 5 - 2 FM sounds, map difference to modulation depth
This was meant to try whether transformations are more interesting: So we map the difference of the 2 chans to modulation depth of both. This is not very useful, a more meaningful data transformation than linear difference would be needed (maybe ratio).