M3nin0
/ metricas_pad.R
Last active
September 12, 2020 13:36
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| # Autor: Felipe Menino Carlos | |
| # Data: 11/09/2020 | |
| ' | |
| Calcula o SpeedUp | |
| ' | |
| speedUp <- function(serialTime, parallelTime) | |
| { | |
| return(serialTime / parallelTime) | |
| } |
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| # STAC.py | |
| bdc_stac_service = stac.STAC('http://brazildatacube.dpi.inpe.br/stac/') | |
| # Select a collection and get items | |
| collection = bdc_stac_service.collection('S2_10_16D_STK-1') | |
| items = collection.get_items(filter={'bbox':'-61, 2.8, -60, 1.8', 'datetime':'2018-08-01/2019-07-31'}) | |
| # Generate a "1D" (One variable) datacube | |
| ## mutate_1d_cube from github.com/M3nin0/xarray-stac/ | |
| cube1d = mutate_1d_cube(items['features'], 'NDVI') |
M3nin0
/ sits-bahia-classification.yaml
Created
October 30, 2020 04:55
An reana.yaml configuration to execute a classification using e-sensing/sits package
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| version: 0.6.0 | |
| inputs: | |
| directories: | |
| - R | |
| options: | |
| CACHE: on # Cache the steps results | |
| workflow: | |
| type: serial | |
| specification: | |
| steps: |
M3nin0
/ install-rsits.R
Last active
December 3, 2020 01:17
R Script to install e-sensing/sits package
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| chooseCRANmirror(graphics=FALSE, ind=1) | |
| # Install devtools, rmarkdown, knitr, testthat and Rcpp if not already available | |
| install.packages(c("devtools", "rmarkdown", "Rcpp", "knitr", "testthat", "remotes")) | |
| # Please install the Suggested packages that are used by sits | |
| install.packages(c("DBI","dendextend", "dtwclust","dtwSat", "e1071", "flexclust", | |
| "imager", "imputeTS", "kohonen", "lwgeom", "MASS", "methods", | |
| "mgcv", "nnet", "proto", "proxy", "ptw", "ranger", "RCurl", | |
| "RSQLite", "signal", "xgboost", "zoo", "randomForest", "desc")) |
M3nin0
/ sits-config.yaml
Created
December 4, 2020 11:16
Configuration file to execute SITS R Package with multiple vegetation index bands
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| default: | |
| # estimated relative growth size of R memory relative to block size | |
| R_memory_bloat : 4 | |
| R_processing_bloat : 5 | |
| # minimum number of samples for multicore processing | |
| minimum_number_samples : 1000 | |
| # Data cube types known to sits |
M3nin0
/ deforestation_sentinel2_sampling.R
Created
January 11, 2021 13:26
Script to randomly select 80 sample points from the data set provided in https://doi.pangaea.de/10.1594/PANGAEA.921387
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| # Adapted from: https://github.com/albhasan/deforestation-sentinel2/blob/master/06_validation/validate_results.R | |
| # validation_dataset_bands.csv is avaliable online on: https://doi.pangaea.de/10.1594/PANGAEA.921387?format=html#download | |
| set.seed(666) | |
| validation_dataset_bands <- readr::read_csv("validation_dataset_bands.csv") | |
| deforestation <- dplyr::filter(validation_dataset_bands, label == "Deforestation") | |
| non_forest <- dplyr::filter(validation_dataset_bands, label == "Non-Forest") | |
| forest <- dplyr::filter(validation_dataset_bands, label == "Forest") |
M3nin0
/ wtss-cmask-example.py
Last active
April 12, 2021 16:59
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| import numpy | |
| from wtss import WTSS | |
| service = WTSS('https://brazildatacube.dpi.inpe.br/', access_token='seu-token') | |
| cbers4_coverage = service['CB4_64_16D_STK-1'] | |
| # | |
| # bandas | |
| # |
M3nin0
/ lulc-classification-reprozip-trace.yaml
Last active
April 19, 2021 20:24
System Trace for a LULC Classification using SITS R Package. Generated by ReproZip
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| # Author: Felipe Menino Carlos | |
| # Date: 19/04/2021 | |
| # | |
| # ReproZip configuration file | |
| # This file was generated by reprozip 1.0.16 at 2021-03-15T02:04:56+00:00 | |
| # You might want to edit this file before running the packer | |
| # See 'reprozip pack -h' for help | |
| # Run info |
M3nin0
/ Visualização de Series Temporais.ipynb
Created
April 23, 2021 21:26
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M3nin0
/ 01_ExtractTimeSeries.R
Created
April 25, 2021 12:39
Exemplo de especificação de um workflow de classificação utilizando Common Workflow Language (CWL).
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| # Autor: Felipe Menino Carlos | |
| # Data: 25/04/2021 | |
| set.seed(777) | |
| library(sits) | |
| # | |
| # Auxiliary function | |
| # | |
| extract_ts_by_sample_location <- function(collection, start_date, end_date, bands, sample_file) { |