bniebuhr

import wx

class Form1(wx.Panel):
    def __init__(self, parent, id):
        wx.Panel.__init__(self, parent, id)
        
        self.button =wx.Button(self, 10, "MULTIPLICA", wx.Point(20,10))
        wx.EVT_BUTTON(self, 10, self.OnClick)
        
        self.button =wx.Button(self, 20, "SOMA", wx.Point(20,100))

bniebuhr

class Classe():
    
    def __init__(self):
        
        Classe.var1 = 10
        Classe.var2 = 3
        
    def printClasse(self):
        
        print 'multiply = ' + str(Classe.var1*Classe.var2)

bniebuhr

# Solucao Maumau
p = int(input("Digite o primeiro número: "))
s = int(input("Digite o segundo número: "))
m = 0
x = 0
if p < 0 and s < 0:
    while x < abs(p):
        m = m + abs(s)
        x = x + 1
    print("A multiplicação utilizando apenas a soma é: %d" % (m))

bniebuhr

#!/bin/bash

TEXT_RESET='\e[0m'
TEXT_YELLOW='\e[0;33m'
TEXT_RED_B='\e[1;31m'

sudo apt-get update
echo -e $TEXT_YELLOW
echo 'APT update finished...'
echo -e $TEXT_RESET

bniebuhr

# import modules
import grass.script as grass

def export_statistics(input_map = ''):
	'''
	Function to calculate and export statistics (using r.stats) from landscape metrics maps.
	Results are given in hectares.
		
	Parameters
	----------

bniebuhr

#!/usr/bin/env python3

import grass.script as gscript


def main():
    
    # Define input: roads maps
    input = "roadsmajor@PERMANENT"
    # Set region - 30m res

bniebuhr

# packages
library(dplyr)
library(landscapemetrics)
library(sf)
library(terra)

# Load data - Latlon, WGS84, 
forest_1985 <- raster::raster("data/mapbiomas_v06_1985_forest.tif")

# CRS

bniebuhr

# library(devtools)
# devtools::install_github("bniebuhr/landscapemetrics", ref = "multibuffer")
# devtools::install_github("bniebuhr/landscapetools", ref = "multibuffer")

# packages
library(dplyr)
library(readxl)
library(ggplot2)
library(forcats)

bniebuhr

# File 1: Rmd template
---
title: "Untitled"
author: "Bernardo, Yves"
date: "3/24/2022"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)

bniebuhr

library(dplyr)
library(tibble)

# read table
tab <- read.csv("results/calving_period_bn.csv")
# this is not necessary but I find it easier to read data.frames as tibbles
tab <- tibble::as_tibble(tab)
tab <- dplyr::rename(tab, rowid = X)
tab