31:T5b9,md`The NSF GAGE Facility (formerly UNAVCO), operated by EarthSCope Consortium, [Web Services](https://www.unavco.org/data/web-services/documentation/documentation.html) provide the basic building blocks with which GAGE Facility and third party web-based tools can be built to access data. In other words, this notebook gives you tools to build more complex tools that deal with the data made available by the GAGE Facility. This notebook is aimed at demonstrating how GAGE Facility Web APIs can be accessed and utilized in a notebook environment like Observable. Notebooks which use JavaScript and "reactive" dataflows can be used to support exploratory data analysis and help students, educators, and researchers interact with data in a productive manner. Getting data is one thing. Understanding it is the goal! Other notebooks can import the functions exposed in this notebook in order to build more complex web interfaces which deal with GAGE maintained data from GAGE Facility operated sensor networks. The examples found in this notebook are designed to demonstrate how our Web APIs work and provide a good starting point for you to start using the functionality found here in your own notebooks. Import, fork, modify, and share what you see here. We believe you will have the best experience using this tool in the [Chrome Browser](https://www.google.com/chrome/). Contact **data-help@earthscope.org** with questions and bug (🐛🐜🐞🕷) reports.`32:T65a,viewof globe = { const width = 720; const height = width; const context = DOM.context2d(width, height); const projection = d3 .geoOrthographic() .rotate(selectedQuake.geometry.coordinates.slice(0, 2).map((d) => d * -1)) .fitExtent( [ [-1, -1], [width + 1, height + 1] ], sphere ) .clipExtent([ [-1, -1], [width + 1, height + 1] ]); let path = d3.geoPath(projection, context); function render() { context.clearRect(0, 0, width, height); path.pointRadius(1.5); context.beginPath(); path(graticule); context.lineWidth = 0.5; context.strokeStyle = "#aaa"; context.stroke(); context.beginPath(); path(world); context.fillStyle = "#000"; context.fill(); context.beginPath(); path(sphere); context.lineWidth = 1.5; context.strokeStyle = "#000"; context.stroke(); // Event Responses. context.beginPath(); path({ type: "MultiPoint", coordinates: eventResponses.map((d) => [d.lon, d.lat]) }); context.lineWidth = 1.5; context.fillOpacity = "0.25"; context.fillStyle = "magenta"; context.fill(); // Earthquake, with magnitude represented by radius. context.beginPath(); path.pointRadius(quakeRadius); path(selectedQuake); let color = d3.color("yellow"); color.opacity = 0.25; context.fillStyle = color; context.strokeStyle = "#ddd"; context.stroke(); context.fill(); } return d3 .select(context.canvas) .call(zoom(projection).on("zoom.render", render)) .call(render) .node(); }33:T657,md`Retrieves summary information, a list of file paths, or a list of file paths + file metadata of products given station_id and site_code and data type selections between one (or several) start and end date(s). Currently available data: - GNSS: - RINEX 2 or RINEX 3 Hatanaka compressed **obs**ervation files. - RINEX 2 or RINEX 3 **nav** files, RINEX 2 **qc** files. - Computed **position** files with specified analysis center and reference frame (note: position files returned ignore date range requested). - METEOROLOGICAL: **met** files. The following structure specified the array of items that may be passed to the function to perform a POST request: ~~~ key: "items" (required) value: (list of objects) A list of objects with each object containing the following keys/value pairs: -- key: "gnss", value: (object) -- -- key: "rinex" (optional), value: (object) -- -- -- key: "selections", value: (object) -- -- -- -- key: "rinex2", value: (list of strings) ["obs", "nav", "qc"] (any combination) -- -- -- -- key: "rinex3", value: (list of strings) ["obs", "nav"] (any combination) -- -- -- key: "items", (object) value: {station_id:station_code} -- -- key: "position", (optional) value: (object) -- -- -- key: "selections", value: (object) -- -- -- -- key: "reference_frame" (required), value: (list of strings) ["igs14", "nam14"] (any combination) -- -- -- -- key: "analysis_center" (required), value: (list of strings) ["cwu", "nmt", "pbo"] (any combination) -- -- -- key: "items", (object) value: {station_id:station_code} -- key: "met", value: (list of strings) ["igs14", "nam14"] (any combination) ~~~`34:T4f4,viewof globe2 = { const width = 720; const height = width; const context = DOM.context2d(width, height); const projection = d3 .geoOrthographic() .fitExtent( [ [-1, -1], [width + 1, height + 1] ], sphere ) .clipExtent([ [-1, -1], [width + 1, height + 1] ]); let path = d3.geoPath(projection, context); function render() { context.clearRect(0, 0, width, height); path.pointRadius(1.5); context.beginPath(); path(graticule); context.lineWidth = 0.5; context.strokeStyle = "#aaa"; context.stroke(); context.beginPath(); path(world); context.fillStyle = "#000"; context.fill(); context.beginPath(); path(sphere); context.lineWidth = 1.5; context.strokeStyle = "#000"; context.stroke(); // Results. context.beginPath(); path({ type: "MultiPoint", coordinates: metadataSearchResults.features.map( (d) => d.geometry.coordinates ) }); context.lineWidth = 1.5; context.fillOpacity = "0.25"; context.fillStyle = "magenta"; context.fill(); } return d3 .select(context.canvas) .call(zoom(projection).on("zoom.render", render)) .call(render) .node(); }35:T829,// This map will redraw if the underlying data specifying the markers on the map changes. // To preserve state, we redraw polygons in the event tileMap is reevaluated. viewof tileMap = { const container = html`

`; yield container; // Give the container dimensions. const map = (container.value = new mapboxgl.Map({ container, center: [0, 0], zoom: 1, style: "mapbox://styles/mapbox/streets-v11", scrollZoom: true })); map.addControl(new mapboxgl.FullscreenControl()); var draw = new MapboxDraw({ displayControlsDefault: false, controls: { polygon: true, trash: true }, defaultMode: "draw_polygon" }); map.addControl(draw, "top-left"); // Add a polygon, index by ID. map.on("draw.create", (e) => { console.log(e); let feature = e.features[0]; mutable polygons[feature.id] = feature.geometry.coordinates[0]; mutable signal *= -1; }); // Remove a polygon by ID. map.on("draw.delete", (e) => { let feature = e.features[0]; delete mutable polygons[feature.id]; mutable signal *= -1; }); // Update a polygon by ID. map.on("draw.update", (e) => { let feature = e.features[0]; mutable polygons[feature.id] = feature.geometry.coordinates[0]; mutable signal *= -1; }); // Place markers on the map to represent geodetic locations. metadataSearchResults.features.forEach((feature) => { var el = document.createElement("div"); el.className = "marker"; el.style.color = "#FF00FF"; el.innerHTML = "" + feature.properties.site_code + ""; new mapboxgl.Marker(el).setLngLat(feature.geometry.coordinates).addTo(map); }); // Redraw previously drawn polygons, if any. for (let id in polygons) { console.log(id); draw.add({ type: "Feature", properties: { type: "Feature" }, id: id, geometry: { type: "Polygon", coordinates: [polygons[id]] } // Note, coordinates is an array of (one) polygon. }); // Add a Polygon feature. } invalidation.then(() => map.remove()); }36:T4f5,stationAvailabilityTableData = stationCoverage().then((data) => { return data.features .map((d, i) => { let dates = []; let ranges = JSON.parse(d.properties.ranges); let firstDate = d3.min(ranges, (d) => d3.timeParse("%s")(d.start_date)); let lastDate = d3.max(ranges, (d) => d3.timeParse("%s")(d.end_date)); let scale = d3 .scaleLinear() .domain([ parseDate(stationCoverageStartDate), parseDate(stationCoverageEndDate) ]) // TODO: determine best interval to display .range([0, 1]) .clamp(true); let datum = { site_id: d.properties.site_id, first_date: firstDate, last_date: lastDate, sample_interval: d.properties.sample_interval, coverage: ranges.map((range) => { return [ // overlapping intervals scale(d3.timeParse("%s")(range.start_date)), scale(d3.timeParse("%s")(range.end_date)) ]; }) }; datum.percent = d3.sum(datum.coverage, (d) => d[1] - d[0]); datum.i = i; return datum; }) .filter((d) => d.percent > 0) // Disregard sites with no data in our date range. .sort((a, b) => d3.descending(a.percent, b.percent)); })37:T5b8,function metadataSearch({ receiver, radome, antenna, antenna_height, sample_interval, metpack, realtime, startDate = "1991-01-01", endDate = dateFormat(today), rinex = true, position = false }) { let url = `https://web-services.unavco.org/${stack}/gnss/ows?service=WFS&version=1.0.0&request=GetFeature&typeName=gnss%3Ametadata_search_data_availability&outputFormat=application%2Fjson&viewparams=start_date:${startDate};end_date:${endDate};`; // Add optional queryparams. if (sample_interval) { url += `sample_interval:${encodeURIComponent(sample_interval)};`; } if (rinex && position) { url += `data_type:${encodeURIComponent("rinex|position")};`; } else if (rinex) { url += `data_type:${encodeURIComponent("rinex")};`; } else if (position) { url += `data_type:${encodeURIComponent("position")};`; } else { url += `data_type:${encodeURIComponent("none")};`; } if (receiver) { url += `receiver_type:${encodeURIComponent(receiver)};`; } if (radome) { url += `radome_type:${encodeURIComponent(radome)};`; } if (antenna) { url += `antenna_type:${encodeURIComponent(antenna)};`; } if (antenna_height) { url += `antenna_height:${antenna_height};`; } if (metpack) { url += `metpack_type:${encodeURIComponent(metpack)};`; } if (realtime) { url += `is_realtime:${encodeURIComponent(realtime)};`; } return fetch(url).then((response) => response.json()); }38:[{"id":"25f3cf544e03a020ad57fefb85943409459e4c3415352e2b438a926ca2e334512044065de2d60d72bf12139b061a1b7353413edae4d797de8337679d25ad4007","href":"https://static.observableusercontent.com/files/25f3cf544e03a020ad57fefb85943409459e4c3415352e2b438a926ca2e334512044065de2d60d72bf12139b061a1b7353413edae4d797de8337679d25ad4007","name":"data_center.jpeg","type":"image/jpeg","lastModified":1646084285898.37,"size":87689}] 2f:{"title":"📓 Web Services","cells":[{"id":0,"value":"# 📓 Web Services","pinned":false,"hidden":false,"mode":"md"},{"id":1557,"value":"ac59 = html`

\n ${await FileAttachment(\"data_center.jpeg\").image()}\n

Beep. Boop. Bop.

\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":167,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":652,"value":"md`The following functions are demonstrated and exported by this notebook:\n~~~js\nimport {\n eventSearch, // radius_search\n position, // web-services\n velocity, // web-services\n fetchProducts, // multisensor/file-metadata/fetch-products/beta\n stationCoverage, // data_availability_ranges\n stationList,\n metadataSearch, // metadata_search_data_availability\n metadataAvailabilityRadius, // data_availability_radius_search\n metadataOptions, // metadata_unique_values\n polygonSearch, // data_availability,\n campaigns, // campaigns geojson layer with cql filters\n} with {env as environment} from \"@earthscope/gnss-web-services\" // \"prod\", \"dev\"\n~~~`","pinned":false,"hidden":false,"mode":"ojs"},{"id":233,"value":"toc()","pinned":false,"hidden":false,"mode":"ojs"},{"id":77,"value":"eventSearchTitle = md`## 🌋 Event Search (Beta)\n\n~~~js\nimport {eventSearch} from \"@earthscope/gnss-web-services\"\n~~~`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1041,"value":"md`Choose a location, and search radius (in meters). Returns a list of sites with data related to an earthquake event in the past 30 days.\n\nThe example below allows demonstrates how we can combine a list of earthquakes over the last week as reported by [USGS](https://www.usgs.gov/) with the \\`eventResponse\\` results; USGS data shows us when and where to look and a GAGE Facility API provides us the sites with corresponding data.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":705,"value":"viewof eventRadius = Inputs.range([1000, 250000], {\n value: 75000,\n step: 25,\n label: \"Distance (m)\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1793,"value":"viewof quakeInput = Inputs.select(\n d3.group(quakes.features, (d) => d.properties.title),\n { required: true, multiple: false }\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":887,"value":"md`Location: **${selectedQuake.geometry.coordinates.join(\", \")}**\n\n**${d3.timeFormat(\"%B %d, %Y\")(new Date(selectedQuake.properties.time))}**\n\nShowing event responses (magenta) from **${\n eventResponses.length\n}** sites for a given earthquake (yellow).`","pinned":false,"hidden":false,"mode":"ojs"},{"id":674,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":1056,"value":"md`Here's a table of search results for our selected time, location, and search radius:`","pinned":false,"hidden":false,"mode":"ojs"},{"id":148,"value":"viewof eventResponseTable = Table(eventResponses, {\n columns: [\n \"distance\",\n \"station_code\",\n \"lon\",\n \"lat\",\n \"has_streaming_available\",\n \"latest_data_from_search\"\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1079,"value":"md`Here is a GeoJSON layer representing the past week's earthquakes. We are using this layer in this example to find places to look for event data from stations in the network that have data available within 30 days prior to the selected date. Easier than searching randomly in time and space to test out this web service!`","pinned":false,"hidden":false,"mode":"ojs"},{"id":828,"value":"quakes = (\n await fetch(\n \"https://earthquake.usgs.gov/earthquakes/feed/v1.0/summary/all_week.geojson\"\n )\n).json()","pinned":true,"hidden":false,"mode":"ojs"},{"id":1862,"value":"md`We could select multiple earthquakes at once to view, but for now, let's just look at a single earthquake at a time from. the dropdown selector above.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1854,"value":"selectedQuake = quakeInput[0]","pinned":false,"hidden":false,"mode":"ojs"},{"id":1084,"value":"md`We can use one particular earthquake from the past week of data along with a search radius within which we would like to find results. We get a list of one or more sites with data related to this search if there is any data available.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":104,"value":"// Search for the location and time of occurrence of a selected quake fromt the past week.\neventResponses = eventSearch({\n lat: selectedQuake.geometry.coordinates[1],\n lon: selectedQuake.geometry.coordinates[0],\n date: dateFormat(new Date(selectedQuake.properties.time)),\n radius: eventRadius // meters\n})","pinned":true,"hidden":false,"mode":"ojs"},{"id":1075,"value":"md`\\`quakeRadius\\` is an arbitrary function designed to represent the magnitude of an earthquake with bigger or smaller radius circle on our globe. Remember, earthquake magnitude is non-linear.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":994,"value":"quakeRadius = {\n const scale = d3.scaleSqrt().domain([0, 100]).range([0, 100]);\n return function (quake) {\n return scale(Math.exp(quake.properties.mag));\n };\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":34,"value":"positionTitle = md`## 🌐 Position\n~~~js\nimport {position} from \"@earthscope/gnss-web-services\"\n~~~`","pinned":false,"hidden":false,"mode":"ojs"},{"id":647,"value":"md`Outputs processed GPS station position time series.\n- [GPS Position Documentation](https://www.unavco.org/data/web-services/documentation/gps-position-documentation.html)`","pinned":false,"hidden":false,"mode":"ojs"},{"id":40,"value":"viewof positionStartDate = date({\n title: \"Start Date\",\n min: \"1992-01-01\",\n max: dateFormat(today),\n value: dateFormat(oneWeekAgo), // Try changing to `oneYearAgo`\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":55,"value":"viewof positionEndDate = date({\n title: \"End Date\",\n min: \"1901-01-01\",\n max: dateFormat(today),\n value: dateFormat(today), // Will force update when allTime is true\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":22,"value":"positionCsv = position({\n station: \"NIST\",\n starttime: positionStartDate,\n endtime: positionEndDate\n})","pinned":true,"hidden":false,"mode":"ojs"},{"id":1093,"value":"md`**Bonus:** Here's an example of how we can easily download the CSV file (with header comments) in the browser:\n\n~~~js\nimport { download } from \"@mbostock/lazy-download\"\n~~~`","pinned":false,"hidden":false,"mode":"ojs"},{"id":265,"value":"download(async () => {\n await Promises.delay(1000);\n return new Blob([positionCsv], { type: \"text\" }); // CSV file with # header comments\n}, \"position\")","pinned":true,"hidden":false,"mode":"ojs"},{"id":2307,"value":"position2Json = md`Here's how we might turn the CSV file into a JavaScript object that we can directly manipulate in the browser.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2316,"value":"import { removeComments } from \"@earthscope/earthscope-notebook-utilities\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":2320,"value":"d3.csvParse(removeComments(positionCsv), (d) => {\n return {\n date: dateFormat(d3.timeParse(\"%Y-%m-%dT%H:%M:%SZ\")(d[\"Datetime\"])),\n deltaN: +d[\" delta N\"], // We can \"shim\" our data's column names and coerce data types as appropriate\n deltaE: +d[\" delta E\"], // strings forced to become float data type\n deltaU: +d[\" delta U\"],\n stdDevN: +d[\" Std Dev N\"],\n stdDevE: +d[\" Std Dev E\"],\n stdDevU: +d[\" Std Dev U\"],\n solution: +d[\" Solution\"]\n };\n})","pinned":true,"hidden":false,"mode":"ojs"},{"id":607,"value":"velocityTitle = md`## ↗️ Velocity\n~~~js\nimport {velocity} from \"@earthscope/gnss-web-services\"\n~~~`","pinned":false,"hidden":false,"mode":"ojs"},{"id":639,"value":"md`Outputs GPS crustal motion velocity field estimates.\nResults from daily GPS station position solutions are combined to generate\nlong-term velocity estimate solutions of stations in IGS08 and NAM08 (North America fixed)\nreference frames. Station offsets due to earthquakes and equipment changes are estimated\nand low-quality outliers due to snow, for example, are removed from the velocity estimate\nsolutions. \n- [GPS Velocity Documentation](https://www.unavco.org/data/web-services/documentation/gps-velocity-documentation.html)`","pinned":false,"hidden":false,"mode":"ojs"},{"id":617,"value":"viewof velocityStartDate = date({\n title: \"Start Date\",\n min: \"1992-01-01\",\n max: dateFormat(today),\n value: dateFormat(oneWeekAgo), // Try changing to `oneYearAgo`\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":619,"value":"viewof velocityEndDate = date({\n title: \"End Date\",\n min: \"1992-01-01\",\n max: dateFormat(today),\n value: dateFormat(today), // Try changing to `oneYearAgo`\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":614,"value":"velocityCsv = velocity({\n station: \"AB02\",\n starttime: positionStartDate,\n endtime: positionEndDate\n})","pinned":true,"hidden":false,"mode":"ojs"},{"id":2587,"value":"velocityCsv","pinned":true,"hidden":false,"mode":"ojs"},{"id":2336,"value":"md`See [Position](https://observablehq.com/@unavco/web-services#position2Json) to see how we can parse a GeoCSV file with a bunch of header comments.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":188,"value":"fetchProductsTitle = md`## 📁 Fetch Products (Beta)\n\n~~~js\nimport {fetchProducts} from \"@earthscope/gnss-web-services\"\n~~~`","pinned":false,"hidden":false,"mode":"ojs"},{"id":225,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":1259,"value":"md`Here's a concrete \"hard-coded\" example of the data structure we can pass into \\`fetchProducts\\`.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":194,"value":"itemsExample = [\n {\n endDate: \"2020-01-31\",\n gnss: {\n position: {\n items: [\"SC01\", \"AB33\"],\n selections: {\n analysis_center: [\"cwu\", \"pbo\", \"nmt\"],\n reference_frame: [\"igs14\", \"nam14\"]\n }\n },\n rinex: {\n items: {\n \"410\": \"SC01\",\n \"1190\": \"P123\"\n },\n selections: {\n rinex2: [\"obs\", \"nav\", \"qc\"],\n rinex3: [\"obs\", \"nav\"]\n }\n }\n },\n met: [\"P123\", \"BGGY\"],\n startDate: \"2020-01-01\"\n }\n]","pinned":true,"hidden":false,"mode":"ojs"},{"id":1262,"value":"md`A summary view is useful for showing how much data is available. Warning: the size of the download that will result from fetching each file in the list can be quite large. Here, we would be looking at a **${bytesToString(\n summary.overall_file_size\n)}** download.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":198,"value":"summary = fetchProducts({ items: itemsExample, view: \"summary\" })","pinned":true,"hidden":false,"mode":"ojs"},{"id":1276,"value":"md`Bonus: Here's a neat way to format the download size for readability.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1266,"value":"// e.g. 10394879 -> 10MB\nbytesToString = function (bytes) {\n let format = d3.format(\".0f\");\n\n if (bytes < 1024) {\n return format(bytes) + \"B\";\n } else if (bytes < 1024 * 1024) {\n return format(bytes / 1024) + \"kB\";\n } else if (bytes < 1024 * 1024 * 1024) {\n return format(bytes / 1024 / 1024) + \"MB\";\n } else if (bytes < 1024 * 1024 * 1024 * 1024) {\n return format(bytes / 1024 / 1024 / 1024) + \"GB\";\n } else if (bytes < 1024 * 1024 * 1024 * 1024 * 1024) {\n return format(bytes / 1024 / 1024 / 1024 / 1024) + \"TB\";\n } else {\n return (\n d3.format(\",\")(format(bytes / 1024 / 1024 / 1024 / 1024 / 1024)) + \"PB\"\n );\n }\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":1281,"value":"md`You can also just retrieve a simple text list of the file paths to be downloaded from our HTTPS file server.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":210,"value":"fetchProducts({ items: itemsExample, view: \"list\" })","pinned":true,"hidden":false,"mode":"ojs"},{"id":1284,"value":"md`Use \\`view: \"metadata\"\\` if you care about the metdatadata for each filepath.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":204,"value":"fetchMetadataExample = fetchProducts({ items: itemsExample, view: \"metadata\" })","pinned":true,"hidden":false,"mode":"ojs"},{"id":1291,"value":"md`Here's all that file metadata for \\`fetchProducts\\` in a table.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":243,"value":"fetchProductsTable = Table(fetchMetadataExample, {\n columns: [\"path\", \"file_size\", \"data_type\", \"sample_interval\"],\n format: { file_size: (d) => bytesToString(d) }\n})","pinned":true,"hidden":false,"mode":"ojs"},{"id":336,"value":"metadataOptionsTitle = md`## 🎱 Metadata Options\n~~~js\nimport {metadataOptions} from \"@earthscope/gnss-web-services\"\n~~~`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1159,"value":"md`Returns radome, antenna, receiver, and metpack unique values.\n\nThis method can be used to offer metadata values to choose from when searching for data using \\`metadataSearch\\`. Consider populating things like dropdown selectors with these values.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1175,"value":"viewof metadataTable = Table(metadataTableRows)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1373,"value":"md`No parameters, just call the method to get an object with arrays hanging off of properties for Radome, Antenna, Receiver, and Metpack unique values in our database.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":343,"value":"metadataValues = metadataOptions()","pinned":true,"hidden":false,"mode":"ojs"},{"id":1182,"value":"md`**Bonus:** We can rearrange our data to let us easily display our unique values in a table. Same data, just organized differently.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1163,"value":"// Notice that this code does not need to know the property names of the object returned by metadataOptions.\nmetadataTableRows = {\n let rows = [];\n let max = 0;\n let properties = [];\n\n for (let p in metadataValues) {\n properties.push(p);\n if (metadataValues[p].length >= max) {\n max = metadataValues[p].length;\n }\n }\n\n for (let i = 0; i < max; i++) {\n let row = {};\n properties.forEach((p) => (row[p] = metadataValues[p][i]));\n rows.push(row);\n }\n\n return rows;\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":320,"value":"metadataSearchTitle = md`## 📡 Metadata Search\n~~~js\nimport {metadataSearch} from \"@earthscope/gnss-web-services\"\n~~~`","pinned":false,"hidden":false,"mode":"ojs"},{"id":326,"value":"viewof metadataStartDate = date({\n title: \"Start Date\",\n min: \"1992-01-01\",\n max: dateFormat(today),\n value: dateFormat(oneWeekAgo)\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":327,"value":"viewof metadataEndDate = date({\n title: \"End Date\",\n min: \"1992-01-01\",\n max: dateFormat(today),\n value: dateFormat(today)\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":591,"value":"viewof sampleIntervalSelection = Radio([\">0\", \"<=1\", \">1\"], {\n label: \"Sample Interval (seconds)\",\n value: \">0\"\n}) // sampleInterval does not need to be chosen if only position files are being retreived","pinned":false,"hidden":false,"mode":"ojs"},{"id":1746,"value":"viewof realTimeSelection = Radio([\"Y\", \"N\", \"Both\"], {\n label: \"Realtime\",\n value: \"Both\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1377,"value":"md`We can use [\\`metadataOptions\\`](https://observablehq.com/@unavco/web-services#metadataOptionsTitle) to populate our dropdowns with unique values.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":363,"value":"viewof antennaSelection = Inputs.select(\n [null].concat(metadataValues.ant),\n {\n label: \"Antenna\",\n value: null\n }\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":368,"value":"viewof receiverSelection = Inputs.select(\n [null].concat(metadataValues.rec),\n {\n label: \"Receiver\",\n value: null\n }\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":373,"value":"viewof radomeSelection = Inputs.select(\n [null].concat(metadataValues.dome),\n {\n label: \"Radome\",\n value: null\n }\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":391,"value":"viewof metpackSelection = Inputs.select([null].concat(metadataValues.metpack), {\n label: \"Metpack\",\n value: null\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1382,"value":"md`We can search for a list of \\`site_id\\`s, where multiple \\`site_id\\`s representing different sample intervals (seconds) can belong to a \\`site_code\\`. If we ommit antenna, receiver, radome, and metpack selections we are simply searching based on our date range and chosen sample interval. But we can further restrict this time-based search by introducing metadata constraints, where these metadata constraints are related to the actual installed equipment that produce data.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":394,"value":"metadataSearchResults = metadataSearch({\n startDate: metadataStartDate,\n endDate: metadataEndDate,\n sample_interval: sampleIntervalSelection,\n receiver: receiverSelection,\n antenna: antennaSelection,\n // antenna_height: antennaHeightSelection, TODO\n radome: radomeSelection,\n metpack: metpackSelection,\n realtime: realTimeSelection == \"Both\" ? undefined : realTimeSelection\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1214,"value":"md`Here are those results painted on an interactive globe.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1208,"value":"$34","pinned":false,"hidden":false,"mode":"ojs"},{"id":2281,"value":"metadataRadiusTitle = md`## 📡 Metadata Radius\n~~~js\nimport {metadataRadius} from \"@earthscope/gnss-web-services\"\n~~~`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2286,"value":"md`### Metata Display\n\ne.g. Station P123 metadata indicating when firmware updates, hardware changes were made, or sample intervals started and ended along with physical changes to a station's equipment.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2444,"value":"metadataDisplay({ station: \"P123\" })","pinned":true,"hidden":false,"mode":"ojs"},{"id":2248,"value":"radiusSearchResults = metadataAvailabilityRadius({\n longitude: -105.2705,\n latitude: 40.1512,\n radius: 45000 // meters\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1549,"value":"polygonSearchTitle = md`## 📍 Polygon Search\n~~~js\nimport {polygonSearch} from \"@earthscope/gnss-web-services\"\n~~~`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1553,"value":"md`Search for geodetic locations in one or more polygons, where a polygon is a ring of lon/lat coordinates.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1582,"value":"md`In this example, we draw site codes (magenta) at their respective geodetic locations corresponding to the metadata search results in the previous section. Using third party libraries like Mapbox necessarily introduces a bit of complexity, but bear with us. The purpose of this example is to demonstrate how you can use interactive maps to produce geospatial search queries.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1562,"value":"$35","pinned":false,"hidden":false,"mode":"ojs"},{"id":1687,"value":"md`We use this signal to force evaluation of cells across cell boundaries. This is a bit of an advanced hack. Read more about the \\`mutable\\` operator and mutable state in Observable notebooks [here](https://observablehq.com/@observablehq/introduction-to-mutable-state).`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1633,"value":"mutable signal = 1","pinned":true,"hidden":false,"mode":"ojs"},{"id":1589,"value":"mutable polygons = ({})","pinned":true,"hidden":false,"mode":"ojs"},{"id":1658,"value":"md`We can search over our polygons drawn on the map to find the sites that have been *selected* on the map.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1621,"value":"polygonSearchResults = {\n if (Object.keys(polygons).length) {\n return await polygonSearch({\n polygons: Object.keys(polygons).map((id) => {\n signal; // Force evaluation of this cell to occur.\n return polygons[id];\n })\n });\n }\n return [];\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":1729,"value":"md`**Bonus:** Using the \\`d3.group\\` [function](https://observablehq.com/@d3/d3-group) we can create a quick-lookup Map object, where the keys of this [Map](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Map) are unique site-codes.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1721,"value":"metadataMap = d3.group(\n metadataSearchResults.features,\n (d) => d.properties.site_code\n)","pinned":true,"hidden":false,"mode":"ojs"},{"id":1733,"value":"md`Because our spatial search can return site_codes that are not visible on our interactive map, we might want to filter out results that were not displayed on the map in the first place in our table below. The table simply renders properties of the features returned by our geospatial search, with a filter slapped on the end to \"hide\" sites we don't want to consider, based on our metadata constraints imposed in \"metadataSearch\" in the previous section.\n~~~js\npolygonSearchResults.features\n .map((d) => d.properties)\n .filter((d) => metadataMap.has(d.site_code))\n~~~`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1665,"value":"viewof polygonSearchTable = Object.keys(polygons).length\n ? Table(\n polygonSearchResults.features\n .map((d) => d.properties)\n .filter((d) => metadataMap.has(d.site_code)),\n {\n columns: [\"site_code\", \"start_date\", \"end_date\"]\n }\n )\n : md`⚠️ Draw polygons on the map above so select geodetic locations.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":448,"value":"stationCoverageTitle = md`## 🗓️ Station Coverage\n~~~js\nimport {stationCoverage} from \"@earthscope/gnss-web-services\"\n~~~`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1098,"value":"md`Returns site availability as a series of ranges [start, end] for a given site ID. These series of ranges represent the station \"coverage\" during a period of time.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1101,"value":"md`The example shown here demonstrates how the results of \\`stationCoverage\\` can be visually represented as simple \"sparkline\" graphic in a table which encodes the station coverage during a period of time. The question, \"How good is the data in this time range?\" can be answered qualitatively with a little math and a \\`Canvas\\` element.\n\nBy mapping intervals in the range **${stationCoverageStartDate} to ${stationCoverageEndDate}** to the interval \\`[0, 1]\\` we can represent data availability as a serious of green bars, where gaps between bars indicates gaps in coverage (i.e no available data). The function \\`sparkline()\\` takes care of turning intervals in the range \\`[0, 1]\\` into the green HTML elements you see.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":510,"value":"viewof stationCoverageStartDate = date({\n title: \"Start Date\",\n min: \"1992-01-01\",\n max: dateFormat(today),\n value: dateFormat(oneDecadeAgo)\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":516,"value":"viewof stationCoverageEndDate = date({\n title: \"End Date\",\n min: \"1992-01-01\",\n max: dateFormat(today),\n value: dateFormat(today)\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1307,"value":"md`Scroll down the table to see gaps in coverage with associated lower \\`percent\\` coverage.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":525,"value":"stationAvailabilityTable = Table(stationAvailabilityTableData, {\n columns: [\n \"site_id\",\n \"sample_interval\",\n \"first_date\",\n \"last_date\",\n \"percent\",\n \"coverage\"\n ],\n format: {\n coverage: (intervals) => sparkline(intervals, { width: 450 }),\n percent: (d) => d3.format(\".2%\")(d)\n },\n width: {\n coverage: \"450px\"\n }\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2346,"value":"md`Here's our GeoJSON object.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1357,"value":"stationCoverage()","pinned":true,"hidden":false,"mode":"ojs"},{"id":2349,"value":"md`We can manipulate our Feature Collection into a data structure that will provide us a table with those sparklines which illustrate coverage qualitatively.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":449,"value":"$36","pinned":true,"hidden":false,"mode":"ojs"},{"id":465,"value":"// Returns a canvas element to represent a series of intervals in the range [0, 1].\nfunction sparkline(intervals, { width = 250, height = 20 }) {\n const x = d3\n .scaleLinear()\n .domain([0, 1])\n .range([1, width - 1]);\n const y = d3\n .scaleLinear()\n .domain([0, 1])\n .range([height / 2, height / 2]);\n const context = DOM.context2d(width, height);\n const line = d3\n .line()\n .x((d, i) => x(d))\n .y(y)\n .context(context);\n\n context.beginPath();\n context.rect(0, 0, width, height);\n context.stroke();\n\n context.lineWidth = height - 2;\n context.strokeStyle = \"green\";\n\n intervals.forEach((range) => {\n context.beginPath();\n line(range);\n context.stroke();\n });\n\n return context.canvas;\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":1409,"value":"md`**Bonus:** Here's a histogram of the percentages of coverage across all of the sites with *any* data available in our selected date range. If each \\`Canvas\\` in our table above summarizes a site in our date range, this plot summarizes all of those \\`Canvas\\` elements together.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1390,"value":"Plot.rectY(\n stationAvailabilityTableData,\n Plot.binX({ y: \"count\" }, { x: \"percent\" })\n).plot()","pinned":true,"hidden":false,"mode":"ojs"},{"id":1947,"value":"meteorologicalTitle = md`## 🗓️ Meteorological\n~~~js\nimport {\n meteorological,\n meteorologicalAvailability,\n meteorologicalCoverage\n} from \"@unavco/unavco-web-services\"\n~~~`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2079,"value":"viewof meteorologicalStartDate = date({\n title: \"Start Date\",\n min: \"1992-01-01\",\n max: dateFormat(today),\n value: dateFormat(oneDecadeAgo)\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2082,"value":"viewof meteorologicalEndDate = date({\n title: \"End Date\",\n min: \"1992-01-01\",\n max: dateFormat(today),\n value: dateFormat(today)\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2005,"value":"meteoroglogicalData = meteorologicalAvailability({\n startDate: meteorologicalStartDate,\n endDate: meteorologicalEndDate\n})","pinned":true,"hidden":false,"mode":"ojs"},{"id":2068,"value":"meteorologicalTableData = meteoroglogicalData.features.map((d) => {\n return {\n site_code: d.properties.site_code,\n start_date: d.properties.start_date,\n end_date: d.properties.end_date,\n longitude: d.geometry.coordinates[0],\n latitude: d.geometry.coordinates[1]\n };\n})","pinned":true,"hidden":false,"mode":"ojs"},{"id":2012,"value":"viewof meteorologicalTable = Table(meteorologicalTableData, {\n value: meteorologicalTableData[0],\n multiple: false,\n format: {\n start_date: (d) => parseDateZulu(d),\n end_date: (d) => parseDateZulu(d)\n }\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2104,"value":"md`*Click rows in the table above to retreive a GeoCSV file containing the meteorological data available for a particular site code.*`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1958,"value":"meteorological({\n station: meteorologicalTable ? meteorologicalTable.site_code : \"P005\", // Not all stations provide meteorological data!\n starttime: meteorologicalStartDate,\n endtime: meteorologicalEndDate\n})","pinned":true,"hidden":false,"mode":"ojs"},{"id":2135,"value":"meteorologicalCoverage()","pinned":true,"hidden":false,"mode":"ojs"},{"id":2356,"value":"campaignsTitle = md`## 🏫 Campaigns\n~~~js\nimport {\n campaigns,\n} from \"@earthscope/gnss-web-services\"\n~~~`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2408,"value":"md`Here's a search for campaign data within the last decade in a 4-sided irregular polygon somewhere in the northwest United States. GeoJSON \\`FeatureCollection\\` is returned, with the following properties for each feature:\n\n~~~\nuid(fid)\ngeodetic_location\ngroup_id\ndata_set\nsite_code\nstart_date\nend_date\nnetwork_campaign\n~~~`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2379,"value":"campaignData = campaigns({\n startDate: dateFormat(oneDecadeAgo),\n endDate: dateFormat(today),\n polygons: [\n [\n [-127.40280407111175, 39.220112585833874],\n [-128.29095730114574, 49.12208889984461],\n [-122.69559195193145, 50.66670685596603],\n [-115.67918143466305, 41.586847475882706],\n [-127.40280407111175, 39.220112585833874]\n ]\n ]\n})","pinned":true,"hidden":false,"mode":"ojs"},{"id":2486,"value":"podStationsHeader = md`## 💽 Pod Stations\n~~~js\nimport {\n podStations,\n} from \"@earthscope/gnss-web-services\"\n~~~`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2493,"value":"Returns stations that are available in the POD with corresponding station pages like [this one for AB06](https://www.unavco.org/instrumentation/networks/status/nota/overview/AB06).","pinned":false,"hidden":false,"mode":"md"},{"id":2490,"value":"pod = podStations()","pinned":true,"hidden":false,"mode":"ojs"},{"id":2498,"value":"podMap = d3.group(pod.features, (d) => d.properties.fourcharid) // create a convenient constant time lookup table","pinned":true,"hidden":false,"mode":"ojs"},{"id":2503,"value":"podMap.has(\"AB06\")","pinned":true,"hidden":false,"mode":"ojs"},{"id":5,"value":"md`# Appendix`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2161,"value":"viewof environment = Inputs.select([\"prod\", \"dev\"], {\n label: \"Environment\",\n value: \"dev\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2153,"value":"stackMapping = ({\n prod: \"geoserver-dai/\",\n dev: \"backoffice-geoserver-test\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2167,"value":"stack = stackMapping[environment]","pinned":false,"hidden":false,"mode":"ojs"},{"id":2467,"value":"## Stations","pinned":false,"hidden":false,"mode":"md"},{"id":2469,"value":"function stationList() {\n let url = `https://web-services.unavco.org/${stack}/gnss/ows?service=WFS&version=1.0.0&request=GetFeature&typeName=gnss%3Adata_availability&outputFormat=application%2Fjson`;\n\n return fetch(url)\n .then((response) => response.json())\n .then((data) => data.features.map((d) => d.properties.site_code));\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2364,"value":"md`## Campaigns`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2368,"value":"function campaigns({\n startDate = \"1991-01-01\",\n endDate = dateFormat(today),\n polygons\n}) {\n let url = `https://web-services.unavco.org/${stack}/gnss/ows?service=WFS&version=1.0.0&request=GetFeature&typeName=gnss%3Acampaigns&outputFormat=application%2Fjson&viewparams=start_date:${startDate};end_date:${endDate}`;\n\n if (polygons) {\n let polygonQuery = \"INTERSECTS(geodetic_location,\";\n\n polygons.forEach((polygon, i) => {\n polygonQuery +=\n \"POLYGON((\" +\n polygon.map((d) => encodeURIComponent(d.join(\" \"))).join(\",\") +\n \"))\";\n\n // If there is at least one more polygon to add to the querystring.\n if (i < polygons.length - 1) {\n polygonQuery += \")%20OR%20INTERSECTS(geodetic_location,\";\n }\n });\n\n polygonQuery += \")\";\n\n url += `&cql_filter=${polygonQuery}`;\n }\n\n return fetch(url).then((response) => response.json());\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2181,"value":"md`## Metadata`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2481,"value":"function podStations() {\n return fetch(\n `https://web-services.unavco.org/${stack}/gnss/ows?service=WFS&version=1.0.0&request=GetFeature&typeName=gnss%3Apod_stations&outputFormat=application%2Fjson`\n ).then((response) => response.json());\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":446,"value":"function stationCoverage() {\n return fetch(\n `https://web-services.unavco.org/${stack}/gnss/ows?service=WFS&version=1.0.0&request=GetFeature&typeName=gnss%3Adata_availability_ranges&outputFormat=application%2Fjson`\n ).then((response) => response.json());\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":339,"value":"function metadataOptions() {\n return fetch(\n `https://web-services.unavco.org/${stack}/gnss/ows?service=WFS&version=1.0.0&request=GetFeature&typeName=gnss%3Ametadata_unique_values&maxFeatures=50&outputFormat=application%2Fjson`\n )\n .then((response) => response.json())\n .then((data) => {\n let properties = data.features[0].properties;\n for (const property in properties) {\n properties[property] = JSON.parse(properties[property]).filter(\n (d) => d\n ); // Remove null values\n }\n return properties;\n })\n .then((properties) => {\n for (let p in properties) {\n properties[p.split(\"_\")[1]] = properties[p];\n delete properties[p];\n }\n\n return properties;\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":311,"value":"$37","pinned":false,"hidden":false,"mode":"ojs"},{"id":1973,"value":"function metadataAvailabilityRadius({ radius, latitude, longitude }) {\n let url = `https://web-services.unavco.org/backoffice-geoserver-test/gnss/ows?service=WFS&version=1.0.0&request=GetFeature&typeName=gnss%3Adata_availability_radius_search&outputFormat=application%2Fjson&viewparams=latitude:${latitude};longitude:${longitude};radius:${radius}`;\n\n return fetch(url).then((response) => response.json());\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":662,"value":"function metadata({ stationList = \"ALL\" }) {\n return fetch(\n `https://web-services.unavco.org/metadata/stationlist/sites/beta?station=stationList`\n ).then((response) => response.json());\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2449,"value":"function metadataDisplay({ station }) {\n let url = `https://web-services.unavco.org/${stack}/gnss/ows?service=WFS&version=1.0.0&request=GetFeature&typeName=gnss%3Ametadata_display&viewparams=site_code:${station}&outputFormat=application%2Fjson`;\n\n return fetch(url).then((response) => response.json());\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2189,"value":"md`## Position`","pinned":false,"hidden":false,"mode":"ojs"},{"id":13,"value":"function position({\n station,\n analysisCenter = \"cwu\",\n referenceFrame = \"nam14\",\n starttime,\n endtime,\n report = \"short\",\n dataPostProcessing = \"Uncleaned\",\n refCoordOption = \"from_analysis_center\"\n} = {}) {\n return fetch(\n `https://web-services.unavco.org/gps/data/position/${station}/v3?analysisCenter=cwu&referenceFrame=nam14&starttime=${starttime}&endtime=${endtime}&report=${report}&dataPostProcessing=${dataPostProcessing}&refCoordOption=from_analysis_center`\n ).then((response) => response.text());\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2192,"value":"md`## Velocity`","pinned":false,"hidden":false,"mode":"ojs"},{"id":629,"value":"function velocity({\n station,\n analysisCenter = \"cwu\",\n referenceFrame = \"igs08\",\n starttime,\n endtime,\n report = \"short\",\n solutionType = \"snaps\"\n} = {}) {\n return fetch(\n `https://web-services.unavco.org/gps/data/velocity/${station}/beta?analysisCenter=${analysisCenter}&referenceFrame=${referenceFrame}&report=${report}&solutionType=${solutionType}`\n ).then((response) => response.text());\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2197,"value":"md`## Multisensor`","pinned":false,"hidden":false,"mode":"ojs"},{"id":175,"value":"function fetchProducts({ view = \"summary\", prettyPrint = true, items, abort }) {\n let Accept = {\n summary: \"application/json\",\n metadata: \"application/json\",\n list: \"application/octet-stream\"\n };\n\n return fetch(\n \"https://web-services.unavco.org/multisensor/file-metadata/fetch-products/beta\",\n {\n signal: abort,\n body: JSON.stringify({\n items: items,\n prettyPrint: false,\n view: view // application/json or text/csv\n }),\n headers: {\n Accept: Accept[view],\n \"Content-Type\": \"application/json\",\n credentials: \"include\"\n },\n method: \"POST\",\n mode: \"cors\"\n }\n )\n .then((response) => {\n return view == \"list\" ? response.text() : response.json();\n })\n .catch((e) => console.log(e));\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2205,"value":"md`## Meteorological`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2000,"value":"function meteorologicalAvailability({ startDate, endDate }) {\n return fetch(\n `https://web-services.unavco.org/${stack}/met/ows?service=WFS&version=1.0.0&request=GetFeature&typeName=met%3Adata_availability&viewparams=start_date:${startDate};end_date:${endDate}&outputFormat=application/json\n`\n ).then((response) => response.json());\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2123,"value":"function meteorologicalCoverage() {\n return fetch(\n `https://web-services.unavco.org/${stack}/met/ows?service=WFS&version=1.0.0&request=GetFeature&typeName=met%3Adata_availability_ranges&outputFormat=application%2Fjson`\n ).then((response) => response.json());\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1940,"value":"function meteorological({ station, starttime, endtime } = {}) {\n return fetch(\n `https://web-services.unavco.org/met/data/${station}/beta?starttime=${starttime}&endtime=${endtime}\n`\n ).then((response) => response.text());\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2210,"value":"md`## Polygons, Maps, Geographic Search`","pinned":false,"hidden":false,"mode":"ojs"},{"id":92,"value":"function eventSearch({ lat, lon, date, radius }) {\n return fetch(\n `https://web-services.unavco.org/events/event_response/radius_search/beta?lat=${encodeURIComponent(\n lat\n )}&lon=${encodeURIComponent(lon)}&date=${date}&radius=${radius}`\n ).then((response) => {\n // Empty response, no results.\n if (response.status == 204) {\n return [];\n }\n return response.json();\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1223,"value":"function polygonSearch({ polygons }) {\n let polygonQuery = \"INTERSECTS(geodetic_location,\";\n\n polygons.forEach((polygon, i) => {\n polygonQuery +=\n \"POLYGON((\" +\n polygon.map((d) => encodeURIComponent(d.join(\" \"))).join(\",\") +\n \"))\";\n\n // If there is at least one more polygon to add to the querystring.\n if (i < polygons.length - 1) {\n polygonQuery += \")%20OR%20INTERSECTS(geodetic_location,\";\n }\n });\n\n polygonQuery += \")\";\n\n return fetch(\n `https://web-services.unavco.org/${stack}/gnss/ows?service=WFS&version=1.0.0&request=GetFeature&typeName=gnss:data_availability&cql_filter=${polygonQuery}&outputFormat=application/json`\n ).then((response) => response.json());\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2216,"value":"md`## Miscellaneous`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2422,"value":"function locations() {\n return fetch(\n `https://web-services.unavco.org/backoffice-geoserver-test/gnss/ows?service=WFS&version=1.0.0&request=GetFeature&typeName=gnss%3Adata_availability&outputFormat=application%2Fjson`\n ).then((response) => response.json());\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1567,"value":"mapboxgl = {\n const gl = await require(\"mapbox-gl@1\");\n if (!gl.accessToken) {\n // https://www.mapbox.com/help/how-access-tokens-work/\n gl.accessToken = \"pk.eyJ1IjoiYnJvb2tzbWFwcyIsImEiOiJja25ycjdmZXMwc3NoMm9xbXdpNThra2huIn0.j1ccDRj-S8MCp33aq9zbDw\";\n const href = await require.resolve(\"mapbox-gl@1/dist/mapbox-gl.css\");\n document.head.appendChild(html``);\n }\n return gl;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1568,"value":"MapboxDraw = {\n const gl = await require(\"@mapbox/mapbox-gl-draw\");\n const href = await require.resolve(\"@mapbox/mapbox-gl-draw/dist/mapbox-gl-draw.css\");\n document.head.appendChild(html``);\n return gl;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":686,"value":"topojson = require('topojson')","pinned":false,"hidden":false,"mode":"ojs"},{"id":683,"value":"world = {\n var world = await (await fetch(\"https://unpkg.com/world-atlas@1/world/110m.json\")).json();\n return topojson.feature(world, world.objects.countries);\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":784,"value":"sphere = ({ type: \"Sphere\" })","pinned":false,"hidden":false,"mode":"ojs"},{"id":787,"value":"graticule = d3.geoGraticule10()","pinned":false,"hidden":false,"mode":"ojs"},{"id":475,"value":"parseDateZulu = d3.timeParse(\"%Y-%m-%d%Z\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":507,"value":"parseDate = d3.timeParse(\"%Y-%m-%d\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":42,"value":"oneWeekAgo = {\n let c = new Date(); // today, still today!\n c.setDate(today.getDate() - 7);\n return c;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2043,"value":"oneDecadeAgo = d3.timeYear.offset(new Date(), -10)","pinned":false,"hidden":false,"mode":"ojs"},{"id":583,"value":"oneYearAgo = d3.timeYear.offset(new Date(), -1)\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":45,"value":"today = new Date()","pinned":false,"hidden":false,"mode":"ojs"},{"id":1049,"value":"dateFormat = d3.timeFormat(\"%Y-%m-%d\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":2221,"value":"md`## Imports`","pinned":false,"hidden":false,"mode":"ojs"},{"id":687,"value":"d3 = require(\"d3\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":753,"value":"import { zoom } from \"@d3/versor-zooming\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":37,"value":"import { date, worldMapCoordinates } from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":143,"value":"import { Table, Toggle, Radio } from \"@observablehq/inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":269,"value":"import { download } from \"@mbostock/lazy-download\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":234,"value":"import { toc } from \"@mbostock/toc\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":2512,"value":"import { DuckDBClient } from \"@cmudig/duckdb\"","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W38","stdlib":"1","titling":"auto"}