Guide To Learn
Static and strong typing are often confused and used interchangeably. However, they describe two different properties of a programming language. A statically typed language assumes that all variables must have either a manifestly declared data type (like in Fortran or C) or a data type inferred from their use (like in Julia, Nim, or Rust) at compile time. […]
Before jumping into writing our first generic procedure, let’s briefly introduce a few new concepts that will get us there: Although Fortran is both statically and strongly typed, don’t confuse the two. I’ll explain the difference in the following subsection.
To find the city with the optimal climate, we’ll go through the following steps: Sounds easy, right? We covered most of the logistics around reading and processing time series data in chapters 5 and 7. Here, we’ll focus on implementing the generic average function that can operate on integer, real, or logical data.
As I said earlier, we’re looking to parse weather data to identify the city with the most pleasant climate (average weather). What is the most pleasant climate? The answer will likely vary depending on who you ask, but for me, that means To be fair, these are quite crude and arbitrary criteria, but they will […]
The dataset that we’ll work in this chapter is based on weather data collected at automated ground stations all over the world and gathered every hour to a central database. The specific weather parameters, their units, and their data types are summarized in table 9.1. Table 9.1 Variables and their units and data types in […]
Consider the following scenario: You’re fresh out of school, or perhaps ready to move on to the next step in your career. You’re looking into a number of cities around the world to live in: Seattle, New York City, Miami, London, Mexico City, and a few others. For many people, myself included, weather is an […]
Finally, we’re getting close to the home stretch. The following listing provides the (almost) complete code of the derived type implementation of the tsunami simulator. I’ve omitted the declaration section for brevity. Listing 8.13 Derived type implementation of the tsunami solver ❶ Initializes Fields ❷ Sets initial water height perturbation and sync ❸ Sets a constant mean water […]
To use finite difference functions directly with our new Field instances, we’ll make simple wrappers around those functions. First, we’ll import the functions and make them available in the mod_field module: ❶ Renames on import so we can use the original names We want to keep the original names diffx and diffy, so I’ve renamed them on import to avoid a name conflict. In […]
In addition to an extra equation and a finite difference term for each of the x and y axes, we need specific implementations of diff for each of them. diffx will return a difference along array rows, and diffy along array columns. The function in the following listing served us well in the one-dimensional solver. Listing 8.9 One-dimensional version of the finite difference function ❶ Input array […]
This is the part that you’ll either enjoy very much, if you’re into math and physics, or not care for at all, if you’re not–expanding our equation set from one to two dimensions. Either way, feel free to read through or skip to the next subsection. Up to this chapter, our solver consisted of two […]