data:image/png;base64,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:image/png;base64,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: (latitude, longitude) for these placesCommands to make the built-in Map Library work.
Play with them to figure out how they work.If building a clickable map interface, you will need these.A simple "place" ADT for you to use.The NWS forecast handlers I built for you. It is basically an ADT light. I only wrote one selector (there could be dozens).
Look into the comments to see how they work.pt:os dados JSON _ em formato de lista
pt:o valor com chave _ em _
pt:a resposta a _ de _ enviando _ e cabeçalhos _
GETGET
POST
PUT
DELETEhttps://snap.berkeley.edupt:um par (chave: _ , valor: _ )
Reports a three-item list containing the latitude and longitude of the user, and the precision of the measurements. Works only if the user allows snap.berkeley.edu access to location data. Some browsers also require an HTTPS connection to Snap!.pt:a localização actual do dispositivo
SELECTOR BLOCK for temperature data from the "forecast" object returned from the NWS API.
From the NWS, forecast periods are defined as Day / Night cycles.
e.g. (presuming it is currently daytime)
0 periods from now = now (today)
1 period from now = tonight
2 periods from now = tomorrow (day)
3 periods from now = tomorrow (night)
...
7 periods from now = 3 days from now (day)
... etcde:$globe zeige aktuellen Standort
pt:mostra a localização corrente do dispositivo no $globe
ca:$globe centra a la meva ubicació
de:$globe Zoom
pt:o zoom do $globe
ca:$globe zoom
de:setze $globe Zoom auf _
pt:altera o zoom do $globe para _
ca:$globe fixa el zoom a _
10de:$globe Längengrad von x _
pt:a longitude no $globe da coordenada x _
ca:$globe longitud per a x _
0de:$globe Breitengrad von y _
pt:a latitude no $globe da coordenada y _
ca:$globe latitud per a y _
0de:setze $globe auf Länge: _ Breite: _
pt:altera a posição no $globe para (longitude: _ , latitude: _ )
ca:$globe centra a longitud: _ latitud: _
-122.25785237.872099de:y von $globe Breitengrad _
pt:a coordenada y da latitude _ no $globe
ca:$globe y per a latitud _
de:x von $globe Längengrad _
pt:a coordenada x da longidude _ no $globe
ca:$globe x per a longitud _
de:ändere $globe um x: _ y: _ Pixel
pt:desloca a posição do mapa de (x: _ , y: _ )
ca:$globe canvia la ubicació en x: _ y: _ píxels
1010de:$globe Entfernung in km zu _
pt:a tua distância em km a _ no $globo
ca:$globe distància en km fins a _
§_objectsMenustagelat1lng1lat2lng2return stage.worldMap.distanceInKm(lat1, lng1, lat2, lng2)de:$globe aktuelle Position
pt:a localização corrente do dispositivo no $globe
ca:$globe ubicació actual
de:$globe aktueller Breitengrad
pt:a latitude corrente do dispositivo no $globe
ca:$globe latitud actual
de:$globe aktueller Längengrad
pt:a longitude corrente do dispositivo no $globe
ca:$globe longitud actual
de:aktualisiere $globe
pt:actualiza o $globe
ca:$globe força refresc
de:$globe als Kostüm
pt:a parte visível do $globe na forma de traje
ca:$globe vestit del mapa actual
de:setze $globe Stil auf _
pt:altera o estilo do $globe para _
ca:$globe fixa l'estil de mapa a _
WikimediaOpenStreetMap
Wikimedia
Watercolor
Toner
Terrain
Topographic
Satellite
Streets
Shading
Mapbox (experimental)CONSTRUCTOR BLOCK for forecast data from the NWS API.
WARNING: This only works inside the USA.
This grabs NWS forecast data for a given set of Lat/Long coordinates. The reported value is something of a mess (large JSON object, aka complicated list-of-lists structure). Use the "temperature" block I built for you to get temperature out. If you want other data than temperature, you'll need to dig into the return from this function more deeply.Handler for "place" data to go into get forecast. See the more detailed get forecast for full description.36.14860427656425,-96.0074394174935743.754125721795546,-71.3910751033782740.660498808019135,-73.92819612723514