3D Geometry
3D Geometry 1 / 57
20 29ms
20 29ms 2 / 57
Ad
Ad 3 / 57
Air Traffic At Altitude
Air Traffic At Altitude 4 / 57
Bar3d
Bar3d 5 / 57
Bartest
Bartest 6 / 57
Bess
Bess 7 / 57
Cltdmnd
Cltdmnd 8 / 57
Cnttest
Cnttest 9 / 57
Collision Geometry
Collision Geometry 10 / 57
Complex
Complex 11 / 57
Cylinderz
Cylinderz 12 / 57
Cylinderz
Cylinderz 13 / 57
D2test
D2test 14 / 57
D3test
D3test 15 / 57
DELAYS
DELAYS 16 / 57
DLYCHN560
DLYCHN560 17 / 57
Dlychn735 0
Dlychn735 0 18 / 57
Erftest
Erftest 19 / 57
Extra Pipes
Extra Pipes 20 / 57
Fermi
Fermi 21 / 57
Fig1
Fig1 22 / 57
Fig5b
Fig5b 23 / 57
Fig8
Fig8 24 / 57
Fig10
Fig10 25 / 57
Fntdemo
Fntdemo 26 / 57
Freq
Freq 27 / 57
GateGeometry
GateGeometry 28 / 57
Intersection Geometry
Intersection Geometry 29 / 57
Landing Predictions
Landing Predictions 30 / 57
Logtest
Logtest 31 / 57
Look Ahead
Look Ahead 32 / 57
Multi Y
Multi Y 33 / 57
NWA Traffic To MSP
NWA Traffic To MSP 34 / 57
Nwa Fleet Savings Regression
Nwa Fleet Savings Regression 35 / 57
Nwa Msp Arrival Banks
Nwa Msp Arrival Banks 36 / 57
Nwa Schedule Recovery
Nwa Schedule Recovery 37 / 57
Orbits
Orbits 38 / 57
ORD Air Traffic
ORD Air Traffic 39 / 57
Patrn256
Patrn256 40 / 57
Pattern
Pattern 41 / 57
Pietest
Pietest 42 / 57
Poltest
Poltest 43 / 57
Resequence
Resequence 44 / 57
Sample
Sample 45 / 57
SavingsperFlight
SavingsperFlight 46 / 57
Sector Traffic At 10000 Ft
Sector Traffic At 10000 Ft 47 / 57
Sector Traffic At Altitude
Sector Traffic At Altitude 48 / 57
Sigma
Sigma 49 / 57
Simplex
Simplex 50 / 57
Smtest
Smtest 51 / 57
Traffic For ZMP
Traffic For ZMP 52 / 57
Triplex
Triplex 53 / 57
Tritest
Tritest 54 / 57
Vfield
Vfield 55 / 57
Zny5501m1
Zny5501m1 56 / 57
Zob48
Zob48 57 / 57
Live Production Demo Updated every 5 minutes • Java 22 FFM Native

See GraphiC in Action: 24/7 Live Koi Pond Temperature Monitor

GraphiC is not just for static publication figures—it is an active, production-grade telemetry engine. An automated Aquascape IoT sensor continuously records water temperature in Dr. Rome's pond, streaming telemetry through a private server ingest pipe to a background Java 22 FFM engine on macOS that renders fresh 30-day diurnal vector curves in real time.

📊 Launch Live Interactive Monitor & System Architecture → Includes interactive zoom/pan viewer, data flow architecture, & Java 22 source code 

History of GraphiC

The IBM PC was released in 1981. At the time, George Kelley and I (James Rome) were plasma physicists studying nuclear fusion. We realized that generating graphical plots would give us critical insight into plasma equilibria and physical behavior, but the original IBM PC had very low-resolution graphics (CGA 320×200). To overcome this, we each purchased a Corona PC, which offered an amazing 640×480 pixel display.

However, we soon discovered that there was no software available to produce publication-grade scientific plots on microcomputers. We had been using the DISSPLA™ Fortran package on mainframes and were heavily influenced by its methodology. In both DISSPLA and GraphiC, plotting is a structured, procedural state machine:

  1. Initialize Session: bgnplot(device, mode, file)

  2. Page Dimensions & Units: page(width, height)

  3. Start Page Canvas: startplot(bgcolor)

  4. Set Plot Area & Origin: area2d(xlen, ylen) and physor(x, y)

  5. Calibrate Axes & Labels: box(), heading(title), xname(x), yname(y), graf(...)

  6. Execute Plot Routines: Calling the authentic GraphiC routines across all languages (conmat, curve, surmat, smdraw, polgrid, xlog, etc.) without obscuring them behind generic OOP abstractions.

  7. Close Frame & Subsystem: Always conclude with endplot() followed by stopplot().

We insisted on vector graphics—where everything is a discrete point, stroke, or filled polygon—so that we could zoom in to inspect fine details on our computer screens and reproduce plots cleanly across pen plotters and laser printers.

We decided that the C language was best suited to run efficiently on a personal computer, but we had to learn it from scratch! We also studied 8086 assembly language and hand-coded critical inner loops in assembly to maximize rendering speed, since numerical math co-processors (like the 8087) were not yet available. It took us several years to perfect our lean, mean, fast C graphics engine. We subsequently founded Scientific Endeavors Corporation to market GraphiC worldwide to scientists and other technical workers.

After George passed away, his son Steve Kelley took his place in the company. Steve cleaned up numerous bugs, expanded features, and managed dedicated customer support. When Steve suffered an untimely death, we terminated Scientific Endeavors. And there the codebase sat, untouched, for over 30 years…

The 2026 Renaissance: Enter AI and Google Antigravity

In 2026, working in close collaboration with me, Google’s Antigravity autonomous AI coding agent resurrected the original GraphiC C archives.

Over the course of this modernization: Archaic 16-bit DOS segmented pointers, expanded memory (EMS) page banking, and disk overlays were eliminated in favor of a clean, flat 64-bit POSIX/C99 architecture running natively across macOS (Apple Silicon ARM64 & Intel), Linux, and Windows.  Obsolete pen plotter support and the Tektronix storage file format were replaced by a modern W3C Scalable Vector Graphics (SVG) driver with an interactive browser-based viewer and live monitor streaming. And, complete multi-language parity was established—delivering first-class bindings for Modern Fortran (2003/2018/legacy F77), Python 3, and Java 22 (Foreign Function & Memory API).

Most importantly, the core mathematical soul of GraphiC remains unaltered: the exact procedural state machine, analytical 3D hidden-surface horizon algorithms, Hershey stroke vector fonts (and now Postscript and TrueType), and precision coordinate transforms developed four decades ago are now preserved and running at native 64-bit speed for the next generation of scientific research.

Advantages of GraphiC

  • GraphiC is made for users who want to display data in new ways that are not part of standard "give me the data and I will plot it for you" programs.
  • GraphiC can plot multiple views of data as it is being generated. Thus, long experiments can be monitored and stopped if things go awry. See a LIVE plot of my Koi Pond temperature here.
  • Vector graphics allow zooming and panning in the included viewer. This allows an overview and study of details in one plot.
  • GraphiC is fully self-contained and needs no other libraries or programs except for your compiler..
  • The GraphiC C code was designed before numeric co-processors, and is extremely fast and compact.
  • It was bug tested for many years and eventually, no changes were needed. (Bad for upgrade sales.)
  • GraphiC has support for things such as Smith Charts and error function plots that are not included in most competitive packages.
  • The Manual has numerous examples (ported to other languages on disk) that can be used as boiler plate for new plots. Several real-world examples that used GraphiC are also included.
🚀 Introductory Launch Special

Get GraphiC 2026 Today

Complete C, Fortran 2003, Python 3, and Java 22 source code • 23 Hershey vector fonts & TrueType engine • 35+ production-ready examples • 230-page manual

$499.99 $299.99 (Single-User Developer License)
🎉 Save $200 with Launch Code: Coupon LAUNCH is automatically applied at checkout!

Instant digital download • Free 2D Community Edition with zero fees • Professional edition via Lemon Squeezy secure checkout

Free EditionGraphiC 2D Community Edition Available Now

Get started immediately at zero cost. The free 2D Community Edition provides core 2D Cartesian plotting, linear/log axes, error bars, bar charts, polygons, and SVG export with auto-cropping across all four languages: C/C++, Modern Fortran 2003+, Python 3, and Java 22. Includes outline Hershey fonts (Swiss & News) and native TrueType text engine (Unicode.ttf). Fully packaged with native Fortran Package Manager (fpm) support—build the entire library and run examples with a single command.

⚠️ Important Notice Regarding Example & Test Programs: The full GraphiC suite contains dozens of test and example programs. Those that utilize 3D surfaces (surmat), contouring (conmat), RF Smith charts (smdraw), ternary phase diagrams (trimat), polar grids (polgrid), or advanced publication typography controls (tickht, titlht, upright, charspc, widen, skew) will not work with the free 2D Community Edition. Dedicated 2D-only test examples are included in the Community package.
Technical Evaluation & Architectural Benchmark

GraphiC vs. The Landscape: Modern Scientific Graphics Compared

How the modernized 2026 edition of GraphiC compares against Matplotlib, Gnuplot, MATLAB, OriginPro, DISLIN, PLplot, and Plotly across binary footprint, execution latency, polyglot language parity, and specialized scientific visualization.

⚡ Sub-Millisecond Execution (<0.002s) ? <700 KB Static Footprint ? Zero External Dependencies ? 4 First-Class Languages: C, Fortran 2003, Python 3, Java 22

1. Executive Overview: The Right Tool for the Job

In computational science, engineering simulations, and mission-critical automated pipelines, visualization tools fall into two divergent paradigms:

  • Heavyweight, Interactive Desktop Environments (MATLAB, OriginPro, Tecplot): Feature-rich with extensive graphical user interfaces and thousands of analysis tools, but carry multi-gigabyte footprints, restrictive per-seat commercial licenses, and prohibitive cold-start latencies that make them unsuitable for autonomous microservices, HPC compute nodes, or embedded systems.
  • Dynamic Language & Web Frameworks (Matplotlib, Plotly): Ubiquitous in interactive exploratory data science (Jupyter Notebooks, web dashboards), but burdened by massive dependency stacks (CPython, NumPy, FreeType, libpng, V8, Node.js, Chromium), slow process startup (500–1,500 ms), and lack of native binary linkage for compiled simulation codes written in C and Modern Fortran.

GraphiC occupies a unique, high-value tier: an ultra-lean, high-precision, self-contained scientific plotting engine with zero external runtime dependencies. Developed originally for high-performance scientific publication and modernized in 2026, GraphiC delivers sub-millisecond execution, true physical layout precision (inches/centimeters), pure algorithmic 3D hidden-surface removal with zero GPU/OpenGL prerequisites, and identical API semantics across C/C++, Modern Fortran 2003, Python 3, and Java 22 (FFM).

2. Comprehensive Feature Matrix

Scroll horizontally to compare all 9 tools, or vertically through features (the header row remains fixed at the top).

⇄ Fixed Header • Scroll Horizontally & Vertically
Feature / Dimension GraphiC (Modern 2026) Matplotlib Gnuplot MATLAB OriginPro DISLIN PLplot Plotly
Binary Footprint ~655 KB static
(407 KB dynamic)
150–350 MB
(Python + wheels)
15–30 MB
(standalone bin)
15–25 GB
(MCR runtime: 4GB)
3–5 GB
(Windows suite)
10–25 MB
(compiled libs)
15–40 MB
(shared libs + drivers)
30–80 MB
(Python wheel + 3.5MB JS)
External Dependencies ZERO
(Pure standard libc/libm)
Python, NumPy, FreeType, libpng, pyparsing, dateutil cairo, pango, libpng, readline, Qt/X11 Java VM, Intel MKL, OpenGL drivers, Qt Windows COM, MSVC CRT, DirectX/OpenGL FreeType, Motif/X11, GL, zlib CMake, FreeType 2, libpango, libcairo, libltdl, Qt/X11 Node.js/V8, Chromium/Kaleido (for headless export), d3.js
Cold-Start Execution Latency < 0.002s
(Sub-millisecond)
0.50 – 1.50s
(module import overhead)
0.05 – 0.15s
(process fork/pipe)
3.0 – 10.0s
(desktop engine boot)
4.0 – 8.0s
(GUI suite launch)
0.01 – 0.03s
(compiled binary)
0.02 – 0.08s
(driver plugin loading)
1.0 – 3.0s
(headless browser launch)
Language Integration True 4-Way Parity:
C/C++, Fortran 2003 (fpm),
Python 3, Java 22 FFM
Python only
(C/Fortran bridges brittle)
Piped scripts only
(no direct C/Fortran API)
MATLAB syntax
(MEX/Engine IPC required)
LabTalk & Origin C
(proprietary desktop)
C, Fortran, Python
(legacy Java JNI wrappers)
C, C++, Fortran 2003, Python, Java
(SWIG wrappers; CMake build)
JavaScript, Python, R
(No compiled C or Fortran)
Vector & Web Output Native SVG + Auto Interactive HTML5 Viewer, PostScript, WMF SVG, PDF, PNG
(HTML requires mpld3/bokeh)
SVG, PostScript, Canvas (HTML5 JS driver) FIG, EPS, PDF, SVG
(complex 3D often rasterized)
EPS, PDF, SVG, EMF, TIFF PostScript, PDF, SVG, WMF, PNG PostScript, PDF, SVG, PNG
(requires Cairo/SVG drivers)
Interactive HTML/SVG
(Static PDF/SVG requires Kaleido)
Serverless & Cloud Containers
(AWS Lambda, GCP Cloud Run)
Native & Trivial
(<2 MB container layer, instant cold boot)
Possible but bulky
(250+ MB layer, high cold start)
Requires apt dependencies in container Impractical / Costly
(Production Server license: $10k+)
Unsupported
(Windows desktop only)
Supported via dynamic shared object Bulky container setup
(multiple shared lib packages)
Very heavy / impractical
(~300 MB Chromium/Kaleido layer)
Typography & Fonts Dual-Engine:
23 Built-in Hershey Vector Fonts + TrueType Engine (Zero FreeType dep)
External FreeType library + system TTF/OTF Relies on host fontconfig & pango System fonts + internal TeX engine Windows GDI TrueType & OpenType Hershey fonts + external FreeType FreeType 2 & system fontconfig (or legacy Hershey) Web browser CSS fonts & SVG text elements
3D Hidden-Surface Engine Pure Software Algorithmic:
No GPU, No OpenGL, No X11 required
Painter's Algorithm
(notorious depth sorting artifacts)
Software hidden3d algorithm Hardware OpenGL / Software Mesa fallback OpenGL hardware acceleration Software hidden-line removal Basic wireframe & mesh
(plmesh / plot3d; basic occlusion)
WebGL / GPU Canvas
(No software headless renderer)
Specialized Built-In Plots
(Smith charts, Ternary, Quiver)
Built-In:
RF Smith Charts, Ternary Phase, 3D Columns, Vector Quiver
Requires 3rd-party add-ons
(scikit-rf, python-ternary)
Complex manual math transform scripts Requires RF Toolbox or File Exchange scripts Built-in (Ternary & Smith templates) Polar/contour built-in; lacks native Smith Polar & contour built-in; lacks native Smith Rich web/financial & Ternary; lacks native Smith
Simultaneous Active Plots simuplot(n)
Up to 10 live concurrent coordinate systems
Subplots & Axes objects (OOP state) multiplot (sequential write) subplot / tiled layout Multi-layer graph windows Multiple page zones Subpage layouts & multiple stream windows Subplot grids (declarative JSON spec)
Cost & Distribution Model $499.99 / Single User
(Perpetual license; OEM redistribution negotiated)
Open Source (PSF / BSD) Open Source (Gnuplot License) $$$$ Proprietary
($2,000+ / seat; cloud expensive)
$$$ Proprietary
($1,000–$3,000 / seat)
Freeware / Commercial license Open Source (LGPL v2.1+) Open Source core (MIT) / Commercial tier

3. In-Depth Comparative Analyses

GraphiC vs. Matplotlib (Python): The Burden of Runtime Overhead

Matplotlib is the standard for interactive ad-hoc data exploration in Jupyter Notebooks. However, when software architects attempt to use Matplotlib in high-throughput backend services, serverless execution (AWS Lambda), or automated high-performance computing (HPC) loops, its architectural limits quickly emerge:

  • Cold-Start Lag & Footprint: Matplotlib requires between 500 ms and 1.5 seconds just to import its modules (due to Python bytecode parsing, CPython ABI loading, NumPy array initialization, and font cache indexing). GraphiC compiles into a single 655 KB static binary that executes from cold start in under 2 milliseconds.
  • 3D Depth Sorting Artifacts: Matplotlib’s 3D engine (mplot3d) relies on a simple Painter’s algorithm that sorts polygons by centroid distance. On overlapping or concave 3D mesh surfaces, it frequently produces visual rendering errors (triangles popping in front of nearer surfaces). GraphiC’s 3D algorithms (d3plot, surmat, surfun) utilize rigorous mathematical hidden-line horizon algorithms that guarantee mathematically correct occlusion without requiring a GPU.
  • Polyglot Deployment: Matplotlib cannot be natively linked into Fortran 2003 or C/C++ simulations without running an embedded CPython interpreter instance. GraphiC provides native, zero-overhead C and Fortran bindings alongside its idiomatic Python wrapper.

GraphiC vs. Gnuplot: In-Process Binary Linkage vs. Brittle Shell Scripting

Gnuplot has long been a favorite tool for rapid terminal plotting. Yet from a software engineering perspective, Gnuplot is a standalone executable, not an embeddable C/Fortran library:

  • No In-Memory Pointer Passing: Integrating Gnuplot into a compiled C or Fortran simulation requires writing data to temporary disk files or piping formatted ASCII text across an OS subshell (e.g. popen("gnuplot", "w")). This introduces serialization overhead, disk I/O bottlenecks, and shell-injection risks.
  • True Library Architecture: GraphiC functions (such as curve(x, y, n, sym) or surmat(z, nx, ny, ...)) receive your existing memory buffers directly by pointer or array descriptor. There is zero serialization, zero disk writing, and zero IPC overhead.
  • Deterministic Page Layout: Gnuplot manages layouts through terminal-specific commands. GraphiC operates strictly on physical paper dimensions (page(8.5, 11), area2d(6.5, 4.5) in inches or cm), ensuring that multi-panel figures conform exactly to publisher specifications (IEEE, Nature, Elsevier).

GraphiC vs. MATLAB & OriginPro: Enterprise Agility vs. Proprietary Monoliths

MATLAB and OriginPro excel at interactive desktop exploratory plotting with hundreds of point-and-click dialogs. However, for automated production pipelines:

  • Licensing & Cost Barriers: Running MATLAB on a cluster of 500 cloud workers requires exorbitant MATLAB Production Server licenses or massive Compiler Runtime containers (~4 GB each). With GraphiC's $499.99 single-user perpetual license, you compile directly into your own executables and run batch jobs across your own workstations or cloud nodes without license servers or per-core metering. (Commercial redistribution in products sold or given to third parties requires a separate OEM agreement with Scientific Endeavors Corporation.)
  • Headless Architecture: OriginPro is tied to the Microsoft Windows desktop subsystem. GraphiC is 100% portable POSIX C, running headlessly on Alpine Linux, macOS (Apple Silicon & Intel), Windows, or supercomputing architectures with identical SVG vector output.

GraphiC vs. DISLIN & PLplot: Self-Contained Purity vs. Complex CMake & Driver Middleware

DISLIN and PLplot are the two best-known traditional scientific plotting libraries for compiled C and Fortran codes. While they share GraphiC's focus on compiled numerical performance, their software architecture introduces substantial maintenance overhead:

  • Build & Dependency Complexity: PLplot relies on an intricate CMake configuration requiring numerous dynamic driver plugins (Cairo, Qt, wxWidgets, Xwin) and external shared libraries (libpango, libcairo, libfreetype, libltdl). If a dynamic driver is missing or mismatched on a compute node, execution fails at runtime. DISLIN is distributed as closed-source precompiled binaries with separate downloads per compiler version. GraphiC is 100% self-contained standard C—drop the source into your code, build with make or Fortran Package Manager (fpm), and link with zero external packages.
  • 3D Hidden-Surface Quality: While PLplot and DISLIN support basic 3D meshes (plmesh, plot3d), their hidden-surface routines struggle with complex, multi-valued, or high-density surfaces. GraphiC’s Wright mathematical horizon algorithm performs analytical line-segment clipping, guaranteeing mathematically exact hidden-line occlusion without hardware OpenGL or GPU drivers.
  • Modern Language Parity: PLplot uses SWIG wrapper layers for Python and Java, which often break across major language updates. GraphiC delivers clean, idiomatic Python C-extensions and modern Java 22 Foreign Function & Memory (FFM) bindings with zero JNI wrapper code.

GraphiC vs. Plotly: In-Situ Sub-Millisecond Vector Generation vs. 300 MB Headless Browser Stacks

Plotly is widely celebrated for interactive web dashboards and browser-based data science. However, when deployed in automated HPC simulation loops, headless microservices, or embedded telemetry:

  • The Headless Browser Penalty: Plotly cannot natively render publication figures inside a compiled binary executable. To generate static vector output (SVG, PDF, EPS) headlessly, Plotly must spin up a background headless Chromium browser engine or the Kaleido daemon. This incurs a 1.0–3.0 second cold-start latency, consumes hundreds of megabytes of RAM, and creates a massive security surface in production containers. GraphiC emits publication-grade vector SVG directly to disk or stdout in under 2 milliseconds from pure C, Fortran, Python, or Java.
  • Zero-Framework Web Interactivity: You do not need a bloated 3.5 MB JavaScript charting library to inspect plots interactively. Every SVG emitted by GraphiC is paired with an ultra-lightweight, zero-framework HTML5 viewer providing smooth pan, zoom, and coordinate inspection using pure browser-native DOM APIs.

4. The Architectural Pillars of GraphiC

?

Zero Runtime Dependencies

Compiles cleanly on 64-bit platforms with nothing more than standard C library headers and -lm. No external graphical toolkits, no X11/Wayland servers, and no external font engines required.

?

Dual-Engine Typography

Includes 23 built-in Hershey vector stroke fonts (Simplex, Complex, Triplex, Gothic, Math, Astronomy, Dot-Matrix) plus an integrated TrueType (.ttf) quadratic B-spline tessellator with outline caching.

?

RF & Chemical Specialization

Native support for RF Smith transmission charts (impedance & admittance circles), ternary mixture phase diagrams (trimat, trifun), 3D column bars (d3bars), and vector quiver fields (vfield).

?

Polyglot First-Class Parity

The exact same API across C99/C11/C23, Modern Fortran 2003/2008, Python 3 (with Jupyter Notebook inline SVG support), and Java 22 FFM. Write in your team’s preferred language with zero feature divergence.

5. Polyglot Parity in Action

Compare how simple, clean, and consistent GraphiC code remains across all 4 supported environments. Each produces an identical, high-precision vector SVG figure:

// C / C++ (High Performance)
#include <graphic.h>
#include <math.h>

int main(void) {
    float x[100], y[100];
    for (int i = 0; i < 100; i++) {
        x[i] = i * 0.1f;
        y[i] = sinf(x[i]);
    }
    bgnplot(1, 'g', "wave.tkf");
    startplot(WHITE);
    page(8.0f, 6.0f);
    area2d(6.5f, 4.5f);
    color(BLACK); box();
    heading("Harmonic Oscillation");
    graf("%g", 0.0f, 2.0f, 10.0f,
         "%g", -1.5f, 0.5f, 1.5f);
    color(BLUE);
    curve(x, y, 100, 0);
    endplot(); stopplot();
    return 0;
}
! Modern Fortran 2003 (ISO_C_BINDING)⚡ fpm ready
program wave_demo
    use graphic_iso
    implicit none
    real(c_float) :: x(100), y(100)
    integer :: i

    do i = 1, 100
        x(i) = real(i - 1) * 0.1
        y(i) = sin(x(i))
    end do
    call bgnplot(1, 103, "wave.tkf")
    call startplot(WHITE)
    call page(8.0, 6.0)
    call area2d(6.5, 4.5)
    call color(BLACK); call box()
    call heading("Harmonic Oscillation")
    call graf("%g", 0.0, 2.0, 10.0, &
              "%g", -1.5, 0.5, 1.5)
    call color(BLUE)
    call curve(x, y, 100, 0)
    call endplot(); call stopplot()
end program wave_demo
⚡ Fortran Package Manager: fpm build • fpm run --example sample
# Python 3 (Object-Oriented & Jupyter)
import math
from graphic import Figure, BLUE, SOLID

x = [i * 0.1 for i in range(100)]
y = [math.sin(v) for v in x]

with Figure(8.0, 6.0, tkf_name="wave.tkf") as fig:
    fig.setup_axes(0.0, 2.0, 10.0,
                   -1.5, 0.5, 1.5)
    fig.title("Harmonic Oscillation")
    fig.xlabel("Time (s)")
    fig.ylabel("Amplitude (V)")
    fig.plot(x, y, color="blue")
    fig.save("wave.svg")
// Java 22 (Foreign Function & Memory API)
import com.sciend.graphic.*;

public class WaveDemo {
    public static void main(String[] args) {
        float[] x = new float[100];
        float[] y = new float[100];
        for (int i = 0; i < 100; i++) {
            x[i] = i * 0.1f;
            y[i] = (float) Math.sin(x[i]);
        }
        try (Figure fig = new Figure(8.0f, 6.0f,
                 Color.WHITE, "wave.tkf")) {
            fig.setupAxes(0f, 2f, 10f,
                          -1.5f, 0.5f, 1.5f);
            fig.title("Harmonic Oscillation");
            fig.plot(x, y, Color.BLUE, LineStyle.SOLID);
            fig.save("wave.svg");
        }
    }
}

When Should You Choose GraphiC?

GraphiC is the ideal solution if your project requires:

✔ High-Throughput Batch Generation: Rendering thousands of figures per minute where sub-millisecond execution eliminates CPU bottlenecks.
✔ High-Performance Computing (HPC): Direct in-process linkage to C or Fortran MPI simulation codes running on headless Linux supercomputers.
✔ Serverless / Container Microservices: Minimal Docker layers (<2 MB vs. 300 MB Matplotlib images) for AWS Lambda or Google Cloud Run.
✔ Specialized Engineering Disciplines: Out-of-the-box RF Smith charts, chemical ternary phase diagrams, and clean 3D hidden-surface removal.
✔ Real-time plotting of data as they are generated: 
✔ New types of plots: GraphiC gives you full control over all aspects of the plot.

Get Started with GraphiC Today

Download the free 2D Community Edition to test with your own pipelines, or upgrade to GraphiC Professional 2026 for full 3D surfaces, contours, and Smith charts.

GraphiC 2026 Change Log

Add new comment

Plain text

  • No HTML tags allowed.
  • Lines and paragraphs break automatically.
  • Web page addresses and email addresses turn into links automatically.
CAPTCHA

Enter the characters shown in the image.

This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.