Free visualize software for linux

Tree::Visualize is a Perl module for visualizing Tree structures.

SYNOPSIS

use Tree::Visualize;
use Tree::Binary;

my $tree = Tree::Binary->new("*")
->setLeft(
Tree::Binary->new("+")
->setLeft(Tree::Binary->new("2"))
->setRight(Tree::Binary->new("2"))
)
->setRight(
Tree::Binary->new("+")
->setLeft(Tree::Binary->new("4"))
->setRight(Tree::Binary->new("5"))
);

my $visualize = Tree::Visualize->new($tree, ASCII, TopDown);
print $visualize->draw();

# +---+
# +--------| * |-------+
# | +---+ |
# +---+ +---+
# +--| + |--+ +--| + |--+
# | +---+ | | +---+ |
# +---+ +---+ +---+ +---+
# | 2 | | 2 | | 4 | | 5 |
# +---+ +---+ +---+ +---+

my $tree = Tree::Binary::Search->new();
foreach my $value (7, 3, 1, 0, 2, 5, 4, 6, 11, 9, 10, 8, 13, 12, 14) {
$tree->insert($value => $value);
}

my $visualize = Tree::Visualize->new($tree, ASCII, Diagonal);
print $visualize->draw();

# (7)-------------(11)-----(13)-(14)
# | | |
# | | (12)
# | |
# | (9)-(10)
# | |
# | (8)
# |
# (3)-----(5)-(6)
# | |
# | (4)
# |
# (1)-(2)
# |
# (0)

my $tree = Tree::Simple->new("test")
->addChildren(
Tree::Simple->new("test-1")
->addChildren(
Tree::Simple->new("test-1-1")
),
Tree::Simple->new("test-2"),
Tree::Simple->new("test-3")
);

my $visualize = Tree::Visualize->new($tree, ASCII, TopDown);
print $visualize->draw();

# |
# +------+
# | test |
# +------+
# ____________|_____________
# | | |
# +--------+ +--------+ +--------+
# | test-1 | | test-2 | | test-3 |
# +--------+ +--------+ +--------+
# |
# |
# +----------+
# | test-1-1 |
# +----------+

NOTE: This is very early release alpha software
The goal of this module is to provide a means of easily visualizing trees in a number of output formats and layouts. Currently only ASCII output and a limited number of formats are supported. There is some support for output as GraphViz dot files, but that is buggy at best right now.

As I said, this is alpha software, and so please dont expect it to do all that much. Many of the classes inside are not even implemented, and few if any are documented. I am releasing this to CPAN largely as a means of self-motivation, although I can make no promises about the speed of my progress.

VisIt is an interactive parallel visualization and graphical analysis tool for viewing scientific data.
Users can quickly generate visualizations from their data, animate them through time, manipulate them, and save the resulting images for presentations. VisIt contains a rich set of visualization features so that you can view your data in a variety of ways.
It can be used to visualize scalar and vector fields defined on two- and three-dimensional (2D and 3D) structured and unstructured meshes.
It was designed to interactively handle very large data set sizes in the terascale range, and works well down to small data sets in the kilobyte range.
Enhancements:
- This release includes a number of bugfixes and new features.
- VisIt can be built automatically with the build_visit script on many Linux, Mac OS X, and AIX platforms.
- The build_visit script downloads relevant VisIt and 3rd party source code, and configures and builds it all using your C++ compiler.
- This release can tunnel its network connections through SSH, has support for reading several new file formats, and has a new Macros window that allows 1-click access to user-defined Python functions.
- Support for user settings and file association on the Windows platform has been improved.

Graidle (Graph aid), is a project that is proposed to create an application web for the realization of graph; it comes divided in four parts:
Graidle Fx proposed like didactic instrument for the visualization of diagrams of function to one variable;
Graidle SQL Friendly assists the creation of a graph starting from one query;
Graidle FrontEnd supplies to the user a graph personalized second every own requirement;
Graidle Class is the class that comes supplied for the development;
The realization of the site is apt to the demonstration of the operation of the same application, that it can be more complete visualizing sources releasable liberations in the appropriate Download section. We will have therefore one dedicated section to every part of the plan: In Function the customer will insert the number of functions to visualize, the interval and the quality of the curve and will come created a diagram to the flight; With the FronEnd they will be able to be inserted until to nine series give to you, choosing of the type, the name, the options like the colors, the title it, maximum and minimal, the lines grid etc... the customer will be able to save the just graphical one and to insert it in situated presentations or web; From SQL is a pure demonstrative and educational section, that it concurs to create given diagram of one query SQL; between the multiple usefullnesses there is that one of being able to visualize in realtime the graph of some give you present in database without or that one of being able to enclose to the tables of resultset a diagram that can clarify the visualization of gives to you; the handbook for who is available also wanted to externally use the class to this situated one;
The Graidle project is realized in PHP with the aid of GD2 library.
Enhancements:
- Introducing of Horizontal Histogram graph type;
- Introducing of Extended Legend for Horizontal Histogram;
- Introducing of new legend management system for a better visualization of all type of strings;
- Introducing of Selection standard CSS color on setValue function;
- New setMultiColor() to visualize different color on same value serie ;
- New setColors() to add one or more colors;
- New Bold Font type ;
- New setFontBD() method;
- Modified carry2file() for select patch and filename;

Snake is an experimental algorithm for exchanging information in a dynamic growing network, where a sender and receiver must stay synchronized despite the changing distance. snake5 is a communication algorithm for exchanging information between nodes in a dynamic changing network
Settings:
- Update speed and frequency
- Listen to a node in the signal mode
- Sliders changing appearance in the topology mode
- Stretch folding animation (YES/NO)
- Draw lines between the nodes (YES/NO)
- Makes the nodes twiddle (visualize data in a node)
Press t to switch to the signal mode. You see the wavelet table over time from octave 0 (top) to octave 11 (bottom). The red signal indicates the current folding-distance (odist).
Wait until the signals in all the different octaves (vertical) become stable and repetitive. At that point the system has learned the pattern.
Now increase the distance of sender and receiver using folding (+ and -). The signal stays stable, despite the increased distance (*). If the signal quality should degrade then decrease the distance again by folding or wait until the system stabilizes itself.

Filelight creates an interactive map of concentric segmented-rings that helps visualize disk usage on your computer.

It is like a pie-chart, but the segments nest, allowing you to see not only which directories take up all your space, but which directories and files inside those directories are the real culprits.

Remote Filesystems

If you want to have a filelight-style map prerendered at set times during the week, and then controlled in a web browser, take a look at Philesight, an excellent utilty that is also open source.

You can also browser remote servers using the fish:// or ftp:// KIO slave inside FIlelight, but for a system administrator I think philesight is more useful, check it out.

Installing From Source

You should be able to just copy and paste the following into a terminal:

cd ~
wget http://methylblue.com/filelight/packages/filelight-1.0.tar.bz2
tar xjf filelight-1.0.tar.bz2
cd filelight-1.0
./configure --disable-debug && make
su -c make install

SigBrowser is a small tool to display large signals (up to 2 GB filesize / 1-6 channels / 16 bit integer).

SigBrowser allows you to smoothly browse in a large signal. It can load 16 bit signed integer data with up to 6 interlaced channels.

Unfortunately theres no large-file support, so the limit is at 2 GB. You cant do much except looking at the signal with various zooming factors.

But if youre searching for certain artefacts in a signal then its probably quite useful for you.

It can visualize large signals with filesizes of up to 2 GB. Currently only 16 bit signed integer signals with up to 8 interlaced channels can be loaded.

Using a P4 @ 1.8 GHz with 512 MB RAM and a GeForce 4 graphics card you can scroll and zoom quite smoothly through the whole signal. On a Sun Ultra 1500 its a bit slower but you can still work fine with it.

By using something which I call block-reduction (BL). BL uses the fact that todays screens only have a limited amount of pixels. That means to display the whole signal at once, the worst case regarding performance restrictions, you would have to display thousands of samples on one pixel coordinate in x (horizontal) direction.

Assuming we plot lines between each pair of following samples the user will see a colored area which borders in vertical direction are the minimum and maximum value of all samples falling on the same x-coordinate.

Using this fact we let the user create a so called signal profile. Besides storing the sampling rate, file format info, number of channels to visualize and similar things its main purpose is to contain min/max pairs each of which calculated from a block of N samples per channel. N gets specified by the user, usually 10..50, depending on signal size and computer beeing used.

By visualizing these min/max blocks instead of the real signal as long as the user doesnt zoom into the signal to much we dont loose any information on the screen. But we get a nice performance boost as the signal profile has a much smaller size (signal_lengh_in_samples / N * 2) than the original signal has. Unfortunately we cant do this anymore when the user zooms into details. Then SigBrowser switches to direct display of the signal but it loads only about 1 MB of the original signal at once, which would result in a width of usually several screens.

Example:

* C = number of channels in origianl signal
* V = number of channels to visualize
* S = original signal length in samples per channel
* B = block size

I have a signal of 1.1 GB, C = V = 8 channels, 16 bit integer samples which in my case contains S = 73298610 samples per channel. Using a block size of B = 10 samples per min/max block (really smooth interaction on a P4 3.2 GHz) you get a signal-profile of S / B * 4 / (1024*1024) = 84 MB which you have to keep in memory.

ParaView project is an application designed with the need to visualize large data sets in mind. The goals of the ParaView project include the following:
- Develop an open-source, multi-platform visualization application.
- Support distributed computation models to process large data sets.
- Create an open, flexible, and intuitive user interface.
- Develop an extensible architecture based on open standards.
ParaView runs on distributed and shared memory parallel as well as single processor systems and has been succesfully tested on Windows, Linux and various Unix workstations and clusters. Under the hood, ParaView uses the Visualization Toolkit as the data processing and rendering engine and has a user interface written using a unique blend of Tcl/Tk and C++. Please go here for a detailed list of features.
ParaView was created by Kitware in conjunction with Jim Ahrens of the Advanced Computing Laboratory at Los Alamos National Laboratory (LANL). Contributors and developers of ParaView currently include: Kitware, LANL, Sandia National Laboratories, and Army Research Laboratory. ParaView is funded by the US Department of Energy ASCI Views program as part of a three-year contract awarded to Kitware, Inc. by a consortium of three National Labs - Los Alamos, Sandia, and Livermore. The goal of the project is to develop scalable parallel processing tools with an emphasis on distributed memory implementations. The project includes parallel algorithms, infrastructure, I/O, support, and display devices. One significant feature of the contract is that all software developed is to be delivered open source. Hence ParaView is available as an open-source system.
Main features:
- Handles structured (uniform rectilinear, non-uniform rectilinear, and curvilinear grids), unstructured, polygonal and image data.
- All processing operations (filters) produce datasets. This allows the user to either further process or save as a data file the result of every operation. For example, the user can extract a cut surface, reduce the number of points on this surface by masking, and apply glyphs (for example, vector arrows) to the result.
- Contours and isosurfaces can be extracted from all data types using scalars or vector components. The results can be colored by any other variable or processed further. When possible, structured data contours/isosurfaces are extracted with fast and efficient algorithms which make use of the special data layout.
- Vectors fields can be inspected by applying glyphs (arrows, cones, lines, spheres, and various 2D glyphs) to the points in a dataset. The glyphs can be scaled by scalars, vector component or vector magnitude and can be oriented using a vector field.
- A sub-region of a dataset can be extracted by cutting or clipping with an arbitrary plane (all data types), specifying a threshold criteria to exclude cells (all data types) and/or specifying a VOI (volume of interest - structured data types only)
- Streamlines can be generated using constant step or adaptive integrators. The results can be displayed as points, lines, tubes, ribbons, etc., and can be processed by a multitude of filters.
- The points in a dataset can be warped (displaced) with scalars (given a user defined displacement vector) or with vectors (unavailable for non-linear rectilinear grids).
- With the array calculator, new variables can be computed using existing point or cell field arrays. A multitude of scalar and vector operations are supported.
- Data can be probed at a point or along a line. The results are displayed either graphically or as text and can be exported for further analysis.
- ParaView provides many other data sources and filters by default (edge extraction, surface extraction, reflection, decimation, extrusion, smoothing...) and any VTK filter can be added by providing a simple XML description (VTK provides hundreds of sources and filters, see VTK documentation for a complete list).
Enhancements:
- This release adds parallel uniform rectilinear grid volume rendering (vtkImageData).
- It introduces new algorithms for parallel unstructured grid volume rendering.
- Support for hardware accelerated offscreen rendering using OpenGL framebuffers.
- Improved multi-block support.
- Improved AMR support.
- Animation saving with ffmpeg.
- Filters have been added for FLUENT, OpenFOAM, MFIX, LSDyna, and AcuSolve.
- A gradient filter for unstructured data.
- Many other enhancements and bugfixes.

TopAZ, short from Topology Analysis and Visualization, is a tool developed in Java with a visual editor which helps visualize changes caused to the attributes of the graph when it is manipulated. It is mainly used for viewing, creating, editing & analyzing graphs.