PySAL: Python Spatial Analysis Library
- Name: Taylor Oshan
| Total CO2 emissions from fossil-fuels (1000 metric tons) for the United States | |
| Data source: | |
| Source organization(s): CDIAC (Carbon Dioxide Information Analysis Center) | |
| Link to source organization: http://cdiac.ornl.gov/ | |
| File name: nation.1751_2009.csv | |
| Link to complete reference: http://cdiac.ornl.gov/ftp/ndp030/CSV-FILES/ | |
| Data attributes: | |
| year: |
| from shapely import wkt | |
| from shapely import ops | |
| import matplotlib.pyplot as plt | |
| %matplotlib inline | |
| a = wkt.loads("LINESTRING (-180 68.96363636363637, -177.55 68.2, -174.92825 67.20589, -175.01425 66.58435, -174.33983 66.33556, -174.57182 67.06219, -171.85731 66.91307999999999, -169.89958 65.97723999999999, -170.89107 65.54139000000001, -172.53025 65.43791, -172.555 64.46079, -172.95533 64.25269, -173.89184 64.2826, -174.65392 64.63124999999999, -175.98353 64.92288000000001, -176.20716 65.35666999999999, -177.22266 65.52024, -178.35993 65.39052, -178.90332 65.74044000000001, -178.68611 66.11211, -179.88377 65.87456, -179.43268 65.40411, -180 64.97970870219837)") | |
| b = wkt.loads("LINESTRING (180 64.97432999999999, 178.7072000000003 64.53493, 177.4112800000002 64.60821, 178.3130000000002 64.07593, 178.9082500000002 63.25197000000014, 179.37034 62.98262000000011, 179.48636 62.56894, 179.2282500000001 62.30410000000015, 177.3643 62.5219, 174.5692900000002 61.76915, 173.68013 61.65261, 172.15 60.95, 170.698500000000 |
| func circularMean() { | |
| let formatter = DateFormatter() | |
| formatter.dateFormat = "yyyy/MM/dd HH:mm:ss zzz" | |
| let times = [Date](arrayLiteral: formatter.date(from: "2017/10/17 23:00:17 UTC")!, formatter.date(from: "2017/10/17 23:40:20 UTC")!, formatter.date(from: "2017/10/17 00:12:45 UTC")!, formatter.date(from: "2017/10/17 00:17:19 UTC")!) | |
| // 1 second of time = 360/(24 * 3600) = 1/240th degree | |
| let angles = times.map { secondOfDay(fromDate: $0) / 240 } | |
| print(degreeToTime(degree: meanAngle(angles: angles), forDate: Date())!) | |
| } | |
| func meanAngle(angles: [Double]) -> Double { |
| import Neuralyzer | |
| struct IrisData: Codable { | |
| let row: [Double] | |
| } | |
| var parsedData: [IrisData] = [] | |
| if let file = Bundle.main.path(forResource: "iris", ofType: "json") { | |
| do { | |
| let jsonDecoder = JSONDecoder() |
I hereby claim:
To claim this, I am signing this object:
| const setup = async () => { | |
| // The root IPFS CID for our xkcd archive | |
| const xkcdRoot = '/ipfs/QmS74HhZt3ZekqUDqdttSgMsHwYQ6miDLwGUHy6pp4qLyD' | |
| // Pick and random comic between 1 and 2003 (which is the latest in the archive) | |
| const comicNumber = Math.floor(Math.random() * 2003) + 1 | |
| try { | |
| // Create IPFS peer | |
| const ipfs = await getIpfs() | |
| // Connect to public peer pinning xkcd comics (might not be needed) | |
| await ipfs.swarm.connect( |
| <!doctype html> | |
| <html> | |
| <head> | |
| <meta charset="utf8"> | |
| <title>Encryptoid ĐApp</title> | |
| <link rel="stylesheet" href="./style.css"> | |
| </head> | |
| <body> | |
| <div id="main"> | |
| <h1>Welcome to Encryptoid!</h1> |