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Add ability to calculate glucose noise #1298
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#!/usr/bin/env node | ||
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/* | ||
Glucose noise calculation | ||
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Released under MIT license. See the accompanying LICENSE.txt file for | ||
full terms and conditions | ||
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR | ||
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, | ||
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE | ||
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER | ||
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, | ||
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN | ||
THE SOFTWARE. | ||
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*/ | ||
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var generate = require('../lib/calc-glucose-stats').updateGlucoseStats; | ||
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function usage ( ) { | ||
console.log('usage: ', process.argv.slice(0, 2), '<glucose.json>'); | ||
} | ||
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if (!module.parent) { | ||
var argv = require('yargs') | ||
.usage("$0 <glucose.json>") | ||
.strict(true) | ||
.help('help'); | ||
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var params = argv.argv; | ||
var inputs = params._ | ||
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if (inputs.length !== 1) { | ||
argv.showHelp() | ||
console.error('Incorrect number of arguments'); | ||
process.exit(1); | ||
} | ||
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var glucose_input = inputs[0]; | ||
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var cwd = process.cwd(); | ||
var glucose_hist = require(cwd + '/' + glucose_input); | ||
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inputs = { | ||
glucose_hist: glucose_hist | ||
}; | ||
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glucose_hist = generate(inputs); | ||
console.log(JSON.stringify(glucose_hist)); | ||
} | ||
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const moment = require('moment'); | ||
const _ = require('lodash'); | ||
const stats = require('./glucose-stats'); | ||
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module.exports = {}; | ||
const calcStatsExports = module.exports; | ||
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calcStatsExports.updateGlucoseStats = (options) => { | ||
var hist = _.map(_.sortBy(options.glucose_hist, 'dateString'), function readDate(value) { | ||
value.readDateMills = moment(value.dateString).valueOf(); | ||
return value; | ||
}); | ||
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if (hist && hist.length > 0) { | ||
var noise_val = stats.calcSensorNoise(null, hist, null, null); | ||
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var ns_noise_val = stats.calcNSNoise(noise_val, hist); | ||
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console.error("Glucose noise calculated: ", noise_val, " setting noise level to ", ns_noise_val); | ||
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if ('noise' in options.glucose_hist[0]) { | ||
options.glucose_hist[0].noise = Math.max(ns_noise_val, options.glucose_hist[0].noise); | ||
} else { | ||
options.glucose_hist[0].noise = ns_noise_val; | ||
} | ||
} | ||
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return options.glucose_hist; | ||
}; |
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const moment = require('moment'); | ||
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const log = console.error; | ||
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/* eslint-disable-next-line no-unused-vars */ | ||
const error = console.error; | ||
const debug = console.error; | ||
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module.exports = {}; | ||
const calcStatsExports = module.exports; | ||
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// Calculate the sum of the distance of all points (sod) | ||
// Calculate the overall distance between the first and the last point (overallDistance) | ||
// Calculate the noise as the following formula: 1 - sod / overallDistance | ||
// Noise will get closer to zero as the sum of the individual lines are mostly | ||
// in a straight or straight moving curve | ||
// Noise will get closer to one as the sum of the distance of the individual lines get large | ||
// Also add multiplier to get more weight to the latest BG values | ||
// Also added weight for points where the delta shifts from pos to neg or neg to pos (peaks/valleys) | ||
// the more peaks and valleys, the more noise is amplified | ||
// Input: | ||
// [ | ||
// { | ||
// real glucose -- glucose value in mg/dL | ||
// real readDate -- milliseconds since Epoch | ||
// },... | ||
// ] | ||
const calcNoise = (sgvArr) => { | ||
let noise = 0; | ||
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const n = sgvArr.length; | ||
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const firstSGV = sgvArr[0].glucose * 1000.0; | ||
const firstTime = sgvArr[0].readDate / 1000.0 * 30.0; | ||
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const lastSGV = sgvArr[n - 1].glucose * 1000.0; | ||
const lastTime = sgvArr[n - 1].readDate / 1000.0 * 30.0; | ||
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const xarr = []; | ||
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for (let i = 0; i < n; i += 1) { | ||
xarr.push(sgvArr[i].readDate / 1000.0 * 30.0 - firstTime); | ||
} | ||
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// sod = sum of distances | ||
let sod = 0; | ||
const lastDelta = 0; | ||
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for (let i = 1; i < n; i += 1) { | ||
// y2y1Delta adds a multiplier that gives | ||
// higher priority to the latest BG's | ||
let y2y1Delta = (sgvArr[i].glucose - sgvArr[i - 1].glucose) * 1000.0 * (1 + i / (n * 3)); | ||
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const x2x1Delta = xarr[i] - xarr[i - 1]; | ||
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if ((lastDelta > 0) && (y2y1Delta < 0)) { | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. @jpcunningh There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Thanks, @jotomo! You are right, the assignment line was missing. |
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// switched from positive delta to negative, increase noise impact | ||
y2y1Delta *= 1.1; | ||
} else if ((lastDelta < 0) && (y2y1Delta > 0)) { | ||
// switched from negative delta to positive, increase noise impact | ||
y2y1Delta *= 1.2; | ||
} | ||
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sod += Math.sqrt(Math.pow(x2x1Delta, 2) + Math.pow(y2y1Delta, 2)); | ||
} | ||
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const overallsod = Math.sqrt(Math.pow(lastSGV - firstSGV, 2) + Math.pow(lastTime - firstTime, 2)); | ||
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if (sod === 0) { | ||
// protect from divide by 0 | ||
noise = 0; | ||
} else { | ||
noise = 1 - (overallsod / sod); | ||
} | ||
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return noise; | ||
}; | ||
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calcStatsExports.calcSensorNoise = (calcGlucose, glucoseHist, lastCal, sgv) => { | ||
const MAXRECORDS = 8; | ||
const MINRECORDS = 4; | ||
const sgvArr = []; | ||
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const numRecords = Math.max(glucoseHist.length - MAXRECORDS, 0); | ||
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for (let i = numRecords; i < glucoseHist.length; i += 1) { | ||
// Only use values that are > 30 to filter out invalid values. | ||
if (lastCal && (glucoseHist[i].glucose > 30) && ('unfiltered' in glucoseHist[i]) && (glucoseHist[i].unfiltered > 100)) { | ||
// use the unfiltered data with the most recent calculated calibration value | ||
// this will provide a noise calculation that is independent of calibration jumps | ||
sgvArr.push({ | ||
glucose: calcGlucose(glucoseHist[i], lastCal), | ||
readDate: glucoseHist[i].readDateMills, | ||
}); | ||
} else if (glucoseHist[i].glucose > 30) { | ||
// if raw data isn't available, use the transmitter calibrated glucose | ||
sgvArr.push({ | ||
glucose: glucoseHist[i].glucose, | ||
readDate: glucoseHist[i].readDateMills, | ||
}); | ||
} | ||
} | ||
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if (sgv) { | ||
if (lastCal && 'unfiltered' in sgv && sgv.unfiltered > 100) { | ||
sgvArr.push({ | ||
glucose: calcGlucose(sgv, lastCal), | ||
readDate: sgv.readDateMills, | ||
}); | ||
} else { | ||
sgvArr.push({ | ||
glucose: sgv.glucose, | ||
readDate: sgv.readDateMills, | ||
}); | ||
} | ||
} | ||
if (sgvArr.length < MINRECORDS) { | ||
return 0; | ||
} | ||
return calcNoise(sgvArr); | ||
}; | ||
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// Return 10 minute trend total | ||
calcStatsExports.calcTrend = (calcGlucose, glucoseHist, lastCal, sgv) => { | ||
let sgvHist = null; | ||
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let trend = 0; | ||
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if (glucoseHist.length > 0) { | ||
let maxDate = null; | ||
let timeSpan = 0; | ||
let totalDelta = 0; | ||
const currentTime = sgv ? moment(sgv.readDateMills) | ||
: moment(glucoseHist[glucoseHist.length - 1].readDateMills); | ||
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sgvHist = []; | ||
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// delete any deltas > 16 minutes and any that don't have an unfiltered value (backfill records) | ||
let minDate = currentTime.valueOf() - 16 * 60 * 1000; | ||
for (let i = 0; i < glucoseHist.length; i += 1) { | ||
if (lastCal && (glucoseHist[i].readDateMills >= minDate) && ('unfiltered' in glucoseHist[i]) && (glucoseHist[i].unfiltered > 100)) { | ||
sgvHist.push({ | ||
glucose: calcGlucose(glucoseHist[i], lastCal), | ||
readDate: glucoseHist[i].readDateMills, | ||
}); | ||
} else if (glucoseHist[i].readDateMills >= minDate) { | ||
sgvHist.push({ | ||
glucose: glucoseHist[i].glucose, | ||
readDate: glucoseHist[i].readDateMills, | ||
}); | ||
} | ||
} | ||
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if (sgv) { | ||
if (lastCal && ('unfiltered' in sgv) && (sgv.unfiltered > 100)) { | ||
sgvHist.push({ | ||
glucose: calcGlucose(sgv, lastCal), | ||
readDate: sgv.readDateMills, | ||
}); | ||
} else { | ||
sgvHist.push({ | ||
glucose: sgv.glucose, | ||
readDate: sgv.readDateMills, | ||
}); | ||
} | ||
} | ||
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if (sgvHist.length > 1) { | ||
minDate = sgvHist[0].readDate; | ||
maxDate = sgvHist[sgvHist.length - 1].readDate; | ||
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// Use the current calibration value to calculate the glucose from the | ||
// unfiltered data. This allows the trend calculation to be independent | ||
// of the calibration jumps | ||
totalDelta = sgvHist[sgvHist.length - 1].glucose - sgvHist[0].glucose; | ||
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timeSpan = (maxDate - minDate) / 1000.0 / 60.0; | ||
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trend = 10 * totalDelta / timeSpan; | ||
} | ||
} else { | ||
debug(`Not enough history for trend calculation: ${glucoseHist.length}`); | ||
} | ||
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return trend; | ||
}; | ||
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// Return sensor noise | ||
calcStatsExports.calcNSNoise = (noise, glucoseHist) => { | ||
let nsNoise = 0; // Unknown | ||
const currSGV = glucoseHist[glucoseHist.length - 1]; | ||
let deltaSGV = 0; | ||
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if (glucoseHist.length > 1) { | ||
const priorSGV = glucoseHist[glucoseHist.length - 2]; | ||
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if ((currSGV.glucose > 30) && (priorSGV.glucose > 30)) { | ||
deltaSGV = currSGV.glucose - priorSGV.glucose; | ||
} | ||
} | ||
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if (!currSGV) { | ||
nsNoise = 1; | ||
} else if (currSGV.glucose > 400) { | ||
log(`Glucose ${currSGV.glucose} > 400 - setting noise level Heavy`); | ||
nsNoise = 4; | ||
} else if (currSGV.glucose < 40) { | ||
log(`Glucose ${currSGV.glucose} < 40 - setting noise level Light`); | ||
nsNoise = 2; | ||
} else if (Math.abs(deltaSGV) > 30) { | ||
// This is OK even during a calibration jump because we don't want OpenAPS to be too | ||
// agressive with the "false" trend implied by a large positive jump | ||
log(`Glucose change ${deltaSGV} out of range [-30, 30] - setting noise level Heavy`); | ||
nsNoise = 4; | ||
} else if (noise < 0.35) { | ||
nsNoise = 1; // Clean | ||
} else if (noise < 0.5) { | ||
nsNoise = 2; // Light | ||
} else if (noise < 0.7) { | ||
nsNoise = 3; // Medium | ||
} else if (noise >= 0.7) { | ||
nsNoise = 4; // Heavy | ||
} | ||
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return nsNoise; | ||
}; | ||
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calcStatsExports.NSNoiseString = (nsNoise) => { | ||
switch (nsNoise) { | ||
case 1: | ||
return 'Clean'; | ||
case 2: | ||
return 'Light'; | ||
case 3: | ||
return 'Medium'; | ||
case 4: | ||
return 'Heavy'; | ||
case 0: | ||
default: | ||
return 'Unknown'; | ||
} | ||
}; |
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This seems backwards?
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It seems to work right. It defaults to false (the second argument to check_pref_bool) if .calc_glucose_noise is not set, so the if expression only evaluates to true if .calc_glucose_noise is in the preferences.json file and is set to true.
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Ok, that's a really confusing implementation of check_pref_bool (not your fault). I read it to be equivalent to "if calc_glucose_noise === false".
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Yes! that's the way I wrote it first, but it didn't work! 😄