Resizing Non-Square Images in Rcpp using OpenCV ===================================================== In this article, we will explore how to resize a non-square image in Rcpp using OpenCV. This process involves several steps, including converting the input image from R’s EBImage format to OpenCV’s Mat format, resizing the image, and finally converting it back to R’s EBImage format. Introduction OpenCV is an open-source computer vision library that provides a wide range of functionalities for image processing.

Understanding the ZXing 1.6 iPhone Barcodes Building Error In this article, we’ll delve into the specifics of the error message provided in a Stack Overflow question regarding the building of a project using ZXing 1.6 on an iPhone with iOS 4.0.1. Background Information on ZXing ZXing is a popular open-source barcode scanning library for Android and iOS applications. It provides a set of tools to help developers create their own mobile apps that can read barcodes, QR codes, and other data carriers.

Understanding the UITableViewDataSource Method -cellForRowAtIndexPath Introduction In this article, we will delve into the world of table view data sources and explore one of the most fundamental methods in iOS development: cellForRowAtIndexPath. This method is crucial for populating a table view with data from an array or other data source. We will examine common pitfalls, best practices, and strategies for troubleshooting issues that may arise during implementation. Table View Data Sources Before we dive into cellForRowAtIndexPath, let’s first understand the concept of a table view data source.

Understanding glBindTexture in OpenGLES for iPhone OpenGL ES (OpenGLES) is a subset of the OpenGL API that is designed specifically for embedded systems, including mobile devices like the iPhone. In this article, we will explore how to use glBindTexture in OpenGLES to bind and draw textures. Introduction to Textures in OpenGLES In OpenGLES, textures are used to display images on the screen. A texture is a two-dimensional array of color values that can be stored in video memory.

Binning and Visualization with Pandas Introduction When working with data that has multiple categories or intervals, it is often necessary to bin the data into these categories. Binning allows us to group similar values together and perform calculations on these groups as a whole. In this article, we will explore how to use Pandas to bin data and create visualizations of the binned data. Understanding Binning Binning is the process of dividing a dataset into discrete intervals or bins.

DELIMITER ;; /*!50003 CREATE*/ /*!50017 DEFINER=`root`@`localhost`*/ CREATE TRIGGER `copies BEFORE INSERT ON `copies` FOR EACH ROW BEGIN DECLARE v_title VARCHAR(254); DECLARE v_BorD INT; SET v_BorD = (SELECT copies.artNr FROM copies WHERE barcode = NEW.barcode AND title IS NULL); IF(v_BorD > 0) THEN SET NEW.title = (SELECT bTitle FROM books JOIN copies ON books.isbn=copies.isbn WHERE copies.barcode=NEW.barcode); END IF; END */;; DELIMITER ; Explanation: The issue is that the triggers are being applied before the data is inserted or updated, and since title doesn’t exist yet in the table being triggered on (copies), it throws an error.

Table Separation and Formatting Using R In this article, we’ll explore how to separate a column into single columns and format entries in R. We’ll use the tidyr, stringr, and purrr libraries to achieve this. Introduction Many data tables have complex entries with multiple values separated by commas or other characters. In these cases, it’s useful to separate each value into its own column. Additionally, formatting the entries according to specific rules can be challenging.

Extracting Time from a Pandas DataFrame with Unix Timestamp When working with time series data in pandas DataFrames, it’s common to encounter datetime objects or strings representing timestamps. In this article, we’ll explore how to extract only the time component from a timestamp represented as Unix time, which is an integer value representing the number of seconds that have elapsed since January 1, 1970, at 00:00:00 UTC. Introduction Unix time is widely used in various applications and systems for date and time representation.

Working with Pandas Series in Python Pandas is a powerful library for data manipulation and analysis in Python. It provides efficient data structures and operations for working with structured data, including tabular data such as spreadsheets and SQL tables. In this article, we will explore how to map multiple keys to a single value in a pandas Series using various techniques. We will discuss the different approaches, their advantages and disadvantages, and provide examples to illustrate each method.

Understanding the S4 Object Creation Process in R The question of an “unused argument error” when creating an S4 object in R is a common one, especially among new users. In this article, we will delve into the world of S4 objects and explore what causes this error. What are S4 Objects? S4 objects represent classes of objects in R. They allow us to create custom data structures that can be used across different packages and libraries.