862 search results for "how to import image file to R"

Add a background png image to ggplot2

February 16, 2014
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Add a background png image to ggplot2

Hey everybody, this is just a short post but I found it very useful. I want to show you how to add images as a background to your ggplot2 plots. To do so we need the packages png and grid Btw, this is just a cool and fast way to import different packages at once. …

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Importing bathymetry and coastline data in R

January 25, 2014
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Importing bathymetry and coastline data in R

After noticing some frustrating inaccuracies with the high-resolution world coastlines and national boundaries database found in worldHires from the package mapdata (based on CIA World Data Bank II data), I decided to look into other options. Although listed as "depreciated", the data found in NOAAs online "Coastline Extractor" is a big step forward. There...

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Fast-track publishing using knitr: exporting images for sharing and press (part III)

January 7, 2014
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Fast-track publishing using knitr: exporting images for sharing and press (part III)

(This article was first published on G-Forge » R, and kindly contributed to R-bloggers) Images can be a powerful medium if used right. The image is CC by alemdag. Fast-track publishing using knitr is a short series on how I use knitr to speedup publishing in my research. This is the third article in the series devoted to plots....

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R vs Stata: Importing and Saving Datasets

January 6, 2014
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R vs Stata: Importing and Saving Datasets

Today, I got a license of the new Stata/MP 13 (dual core), so I decided to make some succinct comparisons with R (Rstudio). Much more tests will come in the following weeks, but today I focused only on the basics: processing text files. Essentially, reading and writing raw datasets. The results I obtained, surprised me—I've

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Fast-track publishing using knitr: the setup using .RProfile with custom CSS + some HTML goodies (part II)

January 3, 2014
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Fast-track publishing using knitr: the setup using .RProfile with custom CSS + some HTML goodies (part II)

Fast-track publishing using knitr is a short is a short series on how I use knitr to get my articles faster published. This is part II where I will show how you can tweak RStudio into producing seamless MS Word-integration by using the .RProfile together with CSS, a few basics about HTML that might be...

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Looping Through Files

Looping Through Files

Today, I finally got inspired to deal with tons of datasets from the Tribunal Superior Eleitoral on the Brazilian elections. The cause of the delay for putting my finger on them was simply to avoid troubles with messy large text files. The set of data I collect consists of above 40GB of pure text files,

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Importance sampling schemes for evidence approximation in mixture models

November 26, 2013
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Importance sampling schemes for evidence approximation in mixture models

Jeong Eun (Kate) Lee and I completed this paper, “Importance sampling schemes for evidence approximation in mixture models“, now posted on arXiv. (With the customary one-day lag for posting, making me bemoan the days of yore when arXiv would give a definitive arXiv number at the time of submission.) Kate came twice to Paris in the past

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Working with hdf files in R – Example: Pathfinder SST data

November 8, 2013
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Working with hdf files in R – Example: Pathfinder SST data

Following  a question that I posted on stackoverflow.com, I recieved the great advice to use the Bioconductor rhdf5 package to work with HDF5 files. The package is not located on CRAN, but can be sourced from the Bioconductor website: source("http://bioconductor.org/biocLite.R")biocLite("rhdf5") Created by Pretty...

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Introducing imagemetrics

September 25, 2013
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Introducing imagemetrics

References In my recent projects, I had the opportunity to work with the professor Raphaël Proulx who introduced me to several metrics commonly used in landscape ecology for quantifying image texture. In order to make my life easier, I decided to implement...

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Classification of the Hyper-Spectral and LiDAR Imagery using R (mostly). Part 1: Result Evaluation

July 28, 2013
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Classification of the Hyper-Spectral and LiDAR Imagery using R (mostly). Part 1: Result Evaluation

Introduction There was the EEEI Data Fusion Contest this spring. This year they wanted people to elaborate about hyper-spectral (142-bands imagery) and LiDAR data. The resolution of the data-set was about 5 m.  There were 2 nominations: best classification and  the best scientific paper.  I work with high-resolution imagery quite often, but classification is a very rear task for me...

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