start new:
tmux
start new with session name:
tmux new -s myname
#!/bin/bash | |
# forma de uso ./exportar <host> <porta> <nome_do_banco_de_dados> <usuario> <senha> <caminho> <formato> | |
# este script depende de: lib32z1 lib32ncurses5 lib32bz2-1.0 e filegdbapi | |
export SHAPE_ENCODING="ISO-8859-1" | |
SERVIDOR=$1 | |
PORTA=$2 | |
BANCO_DADOS=$3 | |
USUARIO=$4 | |
SENHA=$5 |
eigenvariables.fct <- function(vars, name, proportion = 0.95){ | |
library("raster") | |
if (file.exists("./pca") == FALSE) dir.create("./pca") | |
#Running PCA: | |
# Counts not NA cels | |
non.na <- sum(!is.na(values(vars[[1]]))) | |
# Sample the study area with n-non.na and creates an environmental table | |
sr <- sampleRandom(vars, non.na) | |
# faz o PCA dessa tabela padronizada | |
pca <- prcomp(scale(sr)) |
ID:LC08_L1TP_225079_20170109_20170311_01_T1 | |
Acquisition Date:09-JAN-17 | |
Path:225 | |
Row:79 |
"Path","nome","data_source","resolution","description","period" | |
"./worldclim/v2/30sec/presente/wc2.0_bio_30s_04.tif","bio4","worldclim v2","30s","Temperature Seasonality (standard deviation *100)","presente" | |
"./worldclim/v2/30sec/presente/wc2.0_bio_30s_01.tif","bio1","worldclim v2","30s","Annual Mean Temperature","presente" | |
"./worldclim/v2/30sec/presente/wc2.0_bio_30s_19.tif","bio19","worldclim v2","30s","Precipitation of Coldest Quarter","presente" | |
"./worldclim/v2/30sec/presente/wc2.0_bio_30s_02.tif","bio2","worldclim v2","30s","Mean Diurnal Range (Mean of monthly (max temp - min temp))","presente" | |
"./worldclim/v2/30sec/presente/wc2.0_bio_30s_16.tif","bio16","worldclim v2","30s","Precipitation of Wettest Quarter","presente" | |
"./worldclim/v2/30sec/presente/wc2.0_bio_30s_05.tif","bio5","worldclim v2","30s","Max Temperature of Warmest Month","presente" | |
"./worldclim/v2/30sec/presente/wc2.0_bio_30s_03.tif","bio3","worldclim v2","30s","Isothermality (BIO2/BIO7) (* 100)","presente" | |
"./worldclim/v2/30sec/presente/wc2 |
#Atenção: | |
# comandos meramente ilustrativos. Vários parâmetros dos comando usados (shp2pgsql) foram ignorados! | |
# ${a%.*} remove a extenção .shp do nome | |
for a in *.shp; do echo "Convertentado $a"; shp2pgsql $a schema.table > ${a%.*}.sql; done | |
# Depois, para cada .SQL: | |
for b in *.sql; do psql -d iis -f $b; done |
import requests | |
import urllib | |
def geocode(address, city, state, zip_code): | |
try: | |
location_param = ("%s+%s+%s+%s" % ("Pedernera", "Posadas", "Misiones", "2037")) | |
#url_request = "http://nominatim.openstreetmap.org/search?q=" + location_param + "&format=json&polygon_geojson=1" | |
#url_request = "maps.googleapis.com/maps/api/geocode/json?address=%s&sensor=false" % location_param | |
url_request = "http://graphhopper.com/api/1/geocode?q=" + location_param + "&key=PUT_YOUR_KEY_HERE" | |
result = requests.get(url_request) |
/* | |
This is an example Overpass query. | |
Try it out by pressing the Run button above! | |
You can find more examples with the Load tool. | |
*/ | |
[out:json][timeout:25]; | |
//Buscando area "Posadas" | |
area(3602294383)->.searchArea; | |
//Results | |
( |
library(ggplot2) | |
library(ggmap) | |
library(maps) | |
library(mapdata) | |
library(dismo) | |
#Usando dados do pacote "mapdata" | |
usa <- map_data("usa") # Definindo qual dado queremos trabalhar | |
ggplot() + | |
geom_polygon(data = usa, aes(x=long, y = lat, group = group)) + # Aqui estamos usando o data frame "usa" para plotar-lo como poligono | |
coord_fixed(1.3) |
sudo apt-get update && | |
sudo apt-get upgrade && | |
sudo apt-get autoremove && | |
sudo apt-get autoclean && | |
sudo apt-get clean && | |
sudo apt-get install sqlite3 && | |
sudo apt-get install -y python3-pip && | |
sudo apt-get install build-essential libssl-dev libffi-dev python-dev && | |
sudo apt-get install -y python3-venv python3-bs4 python3-pandas* |