Articles

Randomness Tests 🇺🇸

When a series looks noisy, it is still useful to check whether the noise is random or whether weak structure (trend or dependence) is present. The tests below are lightweight diagnostics for an IID or weak-dependence null...

Taylor Series 🇺🇸

The Taylor series is a fundamental tool in calculus and mathematical analysis, offering a powerful way to represent and approximate functions. By expanding a function around a specific point, known as the "center" or "point of expansion," we can express it as an infinite sum of polynomial terms deri...

Thin Plate Spline Interpolation 🇺🇸

Thin Plate Spline (TPS) interpolation is a non‑parametric, spline‑based technique for fitting a smooth surface through scattered data in two or more spatial dimensions. In its classical 2‑D form one seeks a function $f\colon\mathbb R^{2}\to\mathbb R$ that passes through specified data points while m...

Gaussian Interpolation 🇺🇸

Gaussian Interpolation, often associated with Gauss’s forward and backward interpolation formulas, is a technique that refines polynomial interpolation for equally spaced data points. Rather than building the interpolating polynomial from one end of the data interval (as Newton’s forward or backward...

Cubic Spline Interpolation 🇺🇸

Cubic spline interpolation is a refined mathematical tool frequently used within numerical analysis. It's an approximation technique that employs piecewise cubic polynomials, collectively forming a cubic spline. These cubic polynomials are specifically engineered to pass through a defined set of dat...

Least Squares 🇺🇸

Least Squares Regression is a fundamental technique in statistical modeling and data analysis used for fitting a model to observed data. The primary goal is to find a set of parameters that minimize the discrepancies (residuals) between the model’s predictions and the actual observed data. The "leas...

Linear Interpolation 🇺🇸

Linear interpolation is one of the most basic and commonly used interpolation methods. The idea is to approximate the value of a function between two known data points by assuming that the function behaves linearly (like a straight line) between these points. Although this assumption may be simplist...

Newton Polynomial 🇺🇸

Newton’s Polynomial, often referred to as Newton’s Interpolation Formula, is another classical approach to polynomial interpolation. Given a set of data points $(x_0,y_0),(x_1,y_1),\dots,(x_n,y_n)$ with distinct $x_i$ values, Newton’s method constructs an interpolating polynomial in a form that make...

Regression 🇺🇸

Regression analysis and curve fitting are important tools in statistics, econometrics, engineering, and modern machine-learning pipelines. At their core they seek a deterministic (or probabilistic) mapping $\widehat f: \mathcal X \longrightarrow \mathcal Y$ that minim...

Lagrange Polynomial Interpolation 🇺🇸

Lagrange Polynomial Interpolation is a widely used technique for determining a polynomial that passes exactly through a given set of data points. Suppose we have a set of $(n+1)$ data points $(x_0, y_0), (x_1, y_1), \ldots, (x_n, y_n)$ where all $x_i$ are distinct. The aim is to find a polynomial $L...

Liczby Losowe 🇵🇱

W języku C++ liczby losowe generuje się za pomocą standardowej biblioteki . Proces losowania zaczyna się od utworzenia generatora liczb pseudolosowych, np. std::mt19937, który bazuje na algorytmie Mersenne Twister. Aby uzyskać bardziej losowe wyniki, generator inicjalizuje się za pomocą unik...

L Wartosci R Wartosci 🇵🇱

W C++ bardzo dużo rzeczy kręci się wokół pytania: czy dane wyrażenie wskazuje na „konkretny obiekt w pamięci”, czy jest tylko tymczasowym wynikiem obliczeń. Z tego biorą się L-wartości (lvalues) i R-wartości (rvalues). Zrozumienie tego tematu odblokowuje m.in....

Typ Wyliczeniowy 🇵🇱

Typ wyliczeniowy (enum) pozwala opisać zamknięty zbiór możliwych wartości pod czytelnymi nazwami. Zamiast “magicznych liczb” (np. 0,1,2) używasz sensownych identyfikatorów (Poniedzialek, Wtorek), co poprawia czytelność i zmniejsza liczbę błędów...

Filters and Algorithms 🇺🇸

VTK’s filters and algorithms allow you to convert your data from “a static dataset” to a dynamic pipeline: you generate something, clean it up, extract meaning, and reshape it into a form that’s easier to analyze or visualize. Think of it like a workshop line: raw material comes in, tools operate on...

Data Types and Structures 🇺🇸

VTK is built to carry real-world 2D/3D data all the way from “numbers in memory” to “something you can see and reason about.” That means it needs data types that store values, but also store where those values live in space and how they connect. If you pick the right structure early, everything down...

Backward Difference 🇺🇸

The backward difference method is a finite difference technique employed to approximate the derivatives of functions. Unlike the forward difference method, which uses information from points ahead of the target point, the backward difference method relies on function values from points preceding the...

Forward Difference 🇺🇸

The forward difference method is a fundamental finite difference technique utilized for approximating the derivatives of functions. Unlike the central and backward difference methods, which use information from both sides or preceding points, respectively, the forward difference method relies solely...

Central Difference 🇺🇸

The central‐difference method is a finite‐difference scheme for estimating derivatives that combines forward and backward differences via Taylor‐series expansions. By evaluating the function at points symmetrically placed around the target, it cancels out many of the lower‐order error terms, yieldin...

Messaging System Integration 🇺🇸

In modern distributed architectures, messaging systems form an essential backbone for decoupling services, handling asynchronous communication, and enabling more resilient data flows. They allow separate applications or microservices to interact by sending and receiving messages through well-defined...

Optimistic vs Pessimistic Locking 🇺🇸

Locking is about managing concurrent access to shared data. Engineers often make it sound harder than it is, but the core idea is simple: choose between optimistic or pessimistic approaches depending on how costly retries are...

Data Warehousing 🇺🇸

Data warehousing unifies large volumes of information from different sources into a centralized repository that supports analytics, reporting, and strategic decision-making. By collecting operational data, transforming it, and then loading it into one or more specialized databases, data warehouses a...

Replication 🇺🇸

Replication is a method of maintaining copies of data across multiple nodes in distributed systems, making it useful for improving availability, reducing latency, and distributing load. Below are detailed notes, organized in bullet points, each containing one highlighted word in the middle to emphas...

Types of Databases 🇺🇸

Databases store and organize data so that applications and users can retrieve, manage, and manipulate information efficiently. The choice of database often depends on data structure requirements, scale, performance expectations, and the nature of the workload. Over the years, numerous types of datab...

Distributed Database Systems 🇺🇸

A distributed database system (DDS) is a collection of logically interrelated databases distributed across multiple physical locations, connected by a network. The data in these systems might be replicated and/or partitioned among different sites, but the system should ideally appear to the user as ...

Graphs 🇺🇸

In many areas of life, we come across systems where elements are deeply interconnected, whether through physical routes, digital networks, or abstract relationships. Graphs offer a flexible way to represent and make sense of these connections...

Mpi 🇺🇸

The Message Passing Interface (MPI) is a standardized and portable message-passing system designed to function on a wide variety of parallel computing architectures. It provides a set of library routines that can be called from programming languages like C, C++, and Fortran to write parallel applica...

Searching 🇺🇸

Searching is the task of finding whether a particular value exists in a collection and, if it does, where it lives (its index, pointer, node, or associated value). It shows up everywhere: checking if a username is taken, locating a record in a database, finding a file in an index, routing packets, o...

Custom Filters and Algorithms 🇺🇸

Creating custom filters and algorithms opens up a world of possibilities for tailored data processing and visualization. By extending VTK's capabilities, specialized techniques can be introduced that meet the unique needs of scientific research, engineering, medical imaging, or data analysis...

Visualization Techniques 🇺🇸

Modern datasets don’t just have “more rows”, they have more dimensions: space, time, uncertainty, multiple physical variables, and often multiple scales of detail. In that world, visualization isn’t decoration; it’s how you think. VTK matters here because it doesn’t force you into one visualization ...

Animations 🇺🇸

VTK offers a set of tools to create animations and visualize time-varying data. This is particularly useful in scenarios such as...

Backtracking 🇺🇸

Backtracking is a method used to solve problems by building potential solutions step by step. If it becomes clear that a partial solution cannot lead to a valid final solution, the process "backtracks" by undoing the last step and trying a different path. This approach is commonly applied to constra...

Brain Teasers 🇺🇸

Programming puzzles and brain teasers are a fun way to sharpen your coding and problem-solving skills. You’ll often see them in technical interviews, where they’re used to test how you think, analyze problems, and come up with efficient solutions. To do well, it helps to practice and build solid str...

Basic Concepts 🇺🇸

Data structures and algorithms are fundamental concepts in computer science and they are the only way to write efficient software...

Dynamic Programming 🇺🇸

Dynamic Programming (DP) is a way to solve complex problems by breaking them into smaller, easier problems. Instead of solving the same small problems again and again, DP stores their solutions in a structure like an array, table, or map. This avoids wasting time on repeated calculations and makes t...

Sorting 🇺🇸

In the realm of computer science, 'sorting' refers to the process of arranging a collection of items in a specific, predetermined order. This order is based on certain criteria that are defined beforehand...