25:["$","title",null,{"children":"Temperature Analysis | Jairo Aguilar | Observable"}] 49:T642,smothed_z_score = (y, params)=>{ function stddev(arr) { const arr_mean = d3.mean(arr) const r = function(acc, val) { return acc + ((val - arr_mean) * (val - arr_mean)) } return Math.sqrt(arr.reduce(r, 0.0) / arr.length) } let lag = params.lag || 5; let threshold = params.threshold || 3.5; let influence = params.influence || 0.5; if( y== undefined || y.length < lag + 2){ throw `## y data array to short(${y.length}) for given lag of ${lag}` } // init variables var signals = Array(y.length).fill(0) var filteredY = y.slice(0) const lead_in = y.slice(0, lag) //console.log("1: " + lead_in.toString()) var avgFilter = [] avgFilter[lag - 1] = d3.mean(lead_in) var stdFilter = [] stdFilter[lag - 1] = stddev(lead_in) for (var i = lag; i < y.length; i++) { //console.log(`${y[i]}, ${avgFilter[i-1]}, ${threshold}, ${stdFilter[i-1]}`) if (Math.abs(y[i] - avgFilter[i - 1]) > (threshold * stdFilter[i - 1])) { if (y[i] > avgFilter[i - 1]) { signals[i] = +1 // positive signal } else { signals[i] = 0//-1 // negative signal } // make influence lower filteredY[i] = influence * y[i] + (1 - influence) * filteredY[i - 1] } else { signals[i] = 0 // no signal filteredY[i] = y[i] } // adjust the filters const y_lag = filteredY.slice(i - lag, i) avgFilter[i] = d3.mean(y_lag) stdFilter[i] = stddev(y_lag) } return signals }4a:[{"id":"5ff9acab9765a232199f667cb0f1f00a4ac3d3c7cf37fe66c7f79b784c8a320cf3442b6ef3b7417b6c2e2150ed4e968893b08cb6561dcf26f27d8c763b6ab71a","href":"https://static.observableusercontent.com/files/5ff9acab9765a232199f667cb0f1f00a4ac3d3c7cf37fe66c7f79b784c8a320cf3442b6ef3b7417b6c2e2150ed4e968893b08cb6561dcf26f27d8c763b6ab71a","name":"temperatures_crms.csv","type":"text/csv","lastModified":1705851451204.292,"size":85814}] 29:{"id":"726cb067663d5067","slug":null,"title":"Temperature Analysis","thumbnail":"cc193fab79473e43f587ec4139bbe910a032a8baffec18f5555b46b07b500506","access_level":"public","create_time":"$D2024-01-21T15:30:12.299Z","update_time":"$D2024-01-27T14:16:08.663Z","view_time":null,"first_public_time":"$D2024-01-21T15:30:12.299Z","has_unpublished_edits":null,"fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"fc6dd962483ab49f","login":"jab91","name":"Jairo Aguilar","avatar_url":"https://avatars-next.observableusercontent.com/b4dd657592a671b51bee8c0907fb1a4e1b65105b9106cedeff6bde7730b4580c","tier":"starter_2024","bio":"","following":false},"version":247,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"62f0c591012eca4a","login":"jab91","name":"Jairo Aguilar","avatar_url":"https://avatars-next.observableusercontent.com/b4dd657592a671b51bee8c0907fb1a4e1b65105b9106cedeff6bde7730b4580c","tier":null,"bio":"","following":false}],"members":[{"type":"individual","id":"62f0c591012eca4a","login":"jab91","name":"Jairo Aguilar","avatar_url":"https://avatars-next.observableusercontent.com/b4dd657592a671b51bee8c0907fb1a4e1b65105b9106cedeff6bde7730b4580c","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":1,"collection":null,"type":"notebook","body":{"titling":"auto","title":"Temperature Analysis","cells":[{"id":0,"value":"# Temperature Analysis","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":80,"value":"

${type}

${type}'s temperature must be below ${upper_bound}°C

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":127,"value":"viewof type = Inputs.select([\"cooler\", \"freezer\"], {label: \"Type\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":91,"value":"viewof upper_bound = Inputs.range(type==\"cooler\"?[3, 6]:[-15, 10], {value: type==\"cooler\"?4:-10, step: type==\"cooler\"?0.1:1, label: `${type} upper bound`})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":101,"value":"Upper limit: ${upper_bound}
\nNumber of ocurrence: ${temperature_above_range.count}
\nMin Temp (in upper range): ${temperature_above_range.min}
\nMax Temp (in upper range): ${temperature_above_range.max}
","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":68,"value":"Plot.plot({\n y: {\n domain: type==\"cooler\"?[1.5, 5]:[-25, 10]\n },\n marks:[\n Plot.ruleY([upper_bound], {stroke: \"red\", strokeWidth: 2, markerEnd: \"dot\"}),\n Plot.lineY(temperatures, {x:\"datetime\", y:type, stroke:\"blue\", opacity: 0.5}),\n Plot.dot(temperature_above_range.values , {x: \"datetime\", y: type, fill:\"red\"})\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":39,"value":"Plot.plot({\n marks: [\n Plot.rectY(temperatures, Plot.binX({y: \"count\"}, {x: type, fill: (d) => d[type]>=upper_bound?\"red\":\"blue\"})),\n Plot.ruleY([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":203,"value":"viewof threshold = Inputs.range([3, 10], {value: 3, step: 1, label: \"threshold\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":235,"value":"viewof lag = Inputs.range([3, 20], {value: 3, step: 1, label: \"Lag\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":175,"value":"zscores = {\n let temps = temperatures.map(d=>d.freezer);\n let temps_cooler = temperatures.map(d=>d.cooler);\n let zs = smothed_z_score(temps, {lag:lag, threshold: threshold});\n let zs_cooler = smothed_z_score(temps_cooler, {lag:lag, threshold: threshold});\n return {\n \"zscore_freezer\": zs,\n \"zscore_cooler\": zs_cooler\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":34,"value":"temperatures.forEach((d, i)=> {\n d.datetime=new Date(d.datetime)\n d.cooler = +d.cooler\n d.freezer = +d.freezer\n d.zs_cooler = zscores.zscore_cooler[i]\n d.zs_freezer = zscores.zscore_freezer[i]\n return d\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":187,"value":"{\n let y2 = d3.scaleLinear( d3.extent(temperatures, d=>d[`zs_${type}`]), d3.extent(temperatures, d=>d[type]));\n \n return Plot.plot({\n width: 1200,\n height: 600,\n y: {axis: \"left\", label: \"Temperature (°C)\"},\n marks: [\n Plot.axisY(y2.ticks(), {color: \"steelblue\", anchor: \"right\", label: \"Peaks\", y: y2, tickFormat: y2.tickFormat()}),\n Plot.ruleY([0]),\n Plot.lineY(temperatures, {x:\"datetime\", y:type, stroke:\"blue\", opacity: 0.5}),\n Plot.lineY(temperatures, Plot.mapY((d)=>d.map(y2), {x: \"datetime\", y: (d)=>d[`zs_${type}`], stroke: \"red\", opacity: 0.5})),\n ]\n })\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":29,"value":"temperatures = await FileAttachment(\"temperatures_crms.csv\").csv()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":169,"value":"$49","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":87,"value":"temperature_above_range = {\n let values = temperatures.filter(d=>d[type]>upper_bound);\n let count = values.length;\n let min_max = d3.extent(values, (d)=>d[type]);\n\n return {\n values,\n count,\n max:min_max[1], \n min: min_max[0],\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":245,"value":"# References\n1. [Smooth Z score](https://stackoverflow.com/questions/22583391/peak-signal-detection-in-realtime-timeseries-data/57889588#57889588)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"}],"files":"$W4a","stdlib":"1"}} 24:null