This interface allows gnuplot to be controlled from C++ and is designed to be the lowest hanging fruit. In other words, if you know how gnuplot works it should only take 30 seconds to learn this library. Basically it is just an iostream pipe to gnuplot with some extra functions for pushing data arrays and getting mouse clicks. Data sources include STL containers (eg. vector), Blitz++, and armadillo. You can use nested data types like std::vector<std::vector<std::pair<double, double>>> (as well as even more exotic types). Support for custom data types is possible.

This is a low level interface, and usage involves manually sending commands to gnuplot using the "<<" operator (so you need to know gnuplot syntax). This is in my opinion the easiest way to do it if you are already comfortable with using gnuplot. If you would like a more high level interface check out the gnuplot-cpp library (http://code.google.com/p/gnuplot-cpp).

Download

Documentation

Documentation is available [here] but also you can look at the example programs (starting with "example-misc.cc").

Example 1

Lectra Modaris V8r4 - --39-link--39- Best

The modern "On-Demand" manufacturing model—producing garments only after an order is placed—relies entirely on the speed of data manipulation. When a brand needs to produce a variation of a classic shirt in a new fabric with slightly different shrinkage properties, speed is currency.

Users can apply complex grading rules across entire size ranges quickly.

: Real-time charts monitor seam lengths, ensuring that sleeves fit perfectly into armholes during alterations. 2. High-Precision Grading

Save iterative versions of complex patterns before making major changes. Key Modules and Tools Summary Modaris Main Pattern Design & Grading Software Diamino Marker Making (used to optimize fabric consumption) Viewer Used to view and check models without editing Lectra Modaris V8r4 --39-LINK--39-

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The V8R4 iteration focused on speed, accurate 2D-to-3D simulation, and robust grading systems [3, 4].

I can provide tailored advice on or file compatibility based on your setup. Share public link : Real-time charts monitor seam lengths, ensuring that

The V8 series introduced significant advancements in collaborative workflows and 3D prototyping, allowing widely dispersed teams to maintain data consistency and accelerate time-to-market. Core Features of Modaris V8

Heat maps and strain visualization maps show where a garment is too tight or loose, reducing the need for multiple physical fit samples. 4. Smart Variant Management

Automatically grading patterns into a full range of sizes, maintaining consistency across a collection. Key Modules and Tools Summary Modaris Main Pattern

Lectra Modaris V8r4 represents a mature stage in the evolution of Computer-Aided Design (CAD) for the fashion industry. For decades, the primary function of CAD software was the digitization of manual tasks—drawing lines and curves on a screen rather than on paper. However, as supply chains globalized and production cycles shrank, the industry demanded more than just "digital drawing"; it required "digital intelligence."

Grading—the process of scaling a base pattern up or down into various sizes—is where Modaris V8R4 truly shines.

Modaris V8R4 acts as the bridge between creative design and physical manufacturing. A typical workflow involves:

Example 2

// Demo of sending data via temporary files.  The default is to send data to gnuplot directly
// through stdin.
//
// Compile it with:
//   g++ -o example-tmpfile example-tmpfile.cc -lboost_iostreams -lboost_system -lboost_filesystem

#include <map>
#include <vector>
#include <cmath>

#include "gnuplot-iostream.h"

int main() {
	Gnuplot gp;

	std::vector<std::pair<double, double> > xy_pts_A;
	for(double x=-2; x<2; x+=0.01) {
		double y = x*x*x;
		xy_pts_A.push_back(std::make_pair(x, y));
	}

	std::vector<std::pair<double, double> > xy_pts_B;
	for(double alpha=0; alpha<1; alpha+=1.0/24.0) {
		double theta = alpha*2.0*3.14159;
		xy_pts_B.push_back(std::make_pair(cos(theta), sin(theta)));
	}

	gp << "set xrange [-2:2]\nset yrange [-2:2]\n";
	// Data will be sent via a temporary file.  These are erased when you call
	// gp.clearTmpfiles() or when gp goes out of scope.  If you pass a filename
	// (e.g. "gp.file1d(pts, 'mydata.dat')"), then the named file will be created
	// and won't be deleted (this is useful when creating a script).
	gp << "plot" << gp.file1d(xy_pts_A) << "with lines title 'cubic',"
		<< gp.file1d(xy_pts_B) << "with points title 'circle'" << std::endl;

#ifdef _WIN32
	// For Windows, prompt for a keystroke before the Gnuplot object goes out of scope so that
	// the gnuplot window doesn't get closed.
	std::cout << "Press enter to exit." << std::endl;
	std::cin.get();
#endif
}