Comparison of mathematical programs for data analysis |
|
Author : | Stefan Steinhaus (University of Frankfurt, Germany) |
E-Mail / Homepage : | stefan@steinhaus-net.de / http://www.steinhaus-net.de |
Edition : | 2.12 |
Date : | September 8, 1997 |
Last modified : | September 27, 1997 |
In the first part of this test report you can find an overview over the mathematical functionality divided into different subsections, in the second part you can find an overview about the graphical functionality, in the third part you can find an overview about the programming environment, in the fourth part you can find a list of available export/import options, in the fifth part there is a list of operating systems for which the programs are available and in the sixth part you can find a speed comparison on these systems. In the seventh part there will be a final summarize to relate all the different parts of the test report. The relation between these six parts will be 38 : 10 : 8 : 5 : 2 : 37 but for those who want to have their own weighting I will describe detailed the calculation for the summarize so that you can easily calculate the result with your own weighting.
The actual tested programs are :
+ - Function is implemented
in the program
m - Function is supported by
an additional module
- - Function is not implemented
Functions
(Version) |
GAUSS | Mac-
syma |
Maple | Mathe-
matica |
Mat-
lab |
Mu-
PAD |
O-
Matrix |
Ox | S-
Plus |
(3.2.29) | (2.2.1) | (V4) | (3.0.1) | (5.1) | (1.3.0) | (3.2) | (1.11) | (V4) | |
Trig. functions | + | + | + | + | + | + | + | + | + |
Gamma function | + | + | + | + | + | + | - | - | + |
Poly gamma | - | + | + | + | - | - | - | + | - |
Log-Gammafunc. | + | + | + | + | + | + | + | + | + |
Beta function | - | + | + | + | + | + | + | + | - |
Implemented functions | 60.000%
(3/5) |
100.000%
(5/5) |
100.000%
(5/5) |
100.000%
(5/5) |
80.000%
(4/5) |
80.000%
(4/5) |
60.000%
(3/5) |
80.000%
(4/5) |
60.000%
(3/5) |
Functions
(Version) |
GAUSS | Mac-
syma |
Maple | Mathe-
matica |
Mat-
lab |
Mu-
PAD |
O-
Matrix |
Ox | S-
Plus |
(3.2.29) | (2.2.1) | (V4) | (3.0.1) | (5.1) | (1.3.0) | (3.2) | (1.11) | (V4) | |
Eigenvalues | + | + | + | + | + | + | + | + | + |
Eigenvectors | + | + | + | + | + | + | + | + | + |
Cholesky decomposition | + | + | + | + | + | + | + | + | + |
Crout decomposition | + | - | - | - | - | - | - | - | - |
LU decomposition | + | + | + | + | + | - | - | + | + |
Singular value decomposition | + | + | + | + | + | - | + | + | + |
Upper Hessenberg form | + | + | - | - | + | - | - | - | - |
Toeplitz matrix | + | + | + | m | + | - | - | - | - |
Schur form of quadratic matrix | + | + | - | + | + | - | - | - | + |
Optimization
(Unconstr. / Constr.) |
m / m | + / - | + / - | + / + | m / m | - / - | + / + | + / - | + / + |
Linear equation solver | + | + | + | + | + | + | + | + | + |
Non-linear equation solver | m | + | + | + | m | + | + | - | + |
Ordinary Differential Equation solver | m | + | + | + | + | + | + | - | + |
Partial Differential Equation solver | - | m | + | + | m | - | - | - | - |
Sparse matrices handling | + | + | - | + | + | - | - | - | - |
Moore-Penrose pseudo-inverse | + | + | - | + | + | - | - | + | + |
Implemented functions | 94.118%
(16/17) |
88.235%
(15/17) |
64.706%
(11/17) |
88.235%
(15/17) |
94.118%
(16/17) |
35.294%
(6/17) |
52.941%
(9/17) |
47.059%
(8/17) |
70.588%
(12/17) |
Functions
(Version) |
GAUSS | Mac-
syma |
Maple | Mathe-
matica |
Mat-
lab |
Mu-
PAD |
O-
Matrix |
Ox | S-
Plus |
(3.2.29) | (2.2.1) | (V4) | (3.0.1) | (5.1) | (1.3.0) | (3.2) | (1.11) | (V4) | |
Numerical integration | + | + | + | + | + | + | + | m | + |
Double integration | + | + | + | + | + | + | + | - | - |
Triple integration | + | + | + | + | - | + | - | - | - |
Numerical differentiation | + | + | + | + | + | + | - | + | + |
Fourier transf.
(1D / 2D /multidim.) |
+ / + / + | + / - / - | + / - / - | + / + / + | + / + / + | + / - / - | + / + / - | + / - / - | + / + / + |
Inverse Fourier transformation
(1D / 2D / multidim.) |
+ / + / + | + / - / - | + / - / - | + / + / + | + / + / + | + / - / - | + / + / - | + / - / - | + / + / + |
Implemented functions | 100.000%
(10/10) |
60.000%
(6/10) |
60.000%
(6/10) |
100.000%
(10/10) |
90.000%
(9/10) |
60.000%
(6/10) |
60.000%
(6/10) |
40.000%
(4/10) |
60.000%
(6/10) |
Functions
(Version) |
GAUSS | Mac-
syma |
Maple | Mathe-
matica |
Mat-
lab |
Mu-
PAD |
O-
Matrix |
Ox | S-
Plus |
(3.2.29) | (2.2.1) | (V4) | (3.0.1) | (5.1) | (1.3.0) | (3.2) | (1.11) | (V4) | |
Classical Interpolation | - | + | + | + | + | + | + | - | + |
Pade Interpolation | m | + | + | + | - | + | + | - | - |
k-Spline Interpolation | + | + | + | + | m | - | + | + | + |
B-Spline Interpolation | - | - | + | + | m | - | - | + | + |
Newton method for finding roots | m | + | + | + | m | + | + | - | - |
Bisection | m | + | - | m | m | - | - | - | - |
Runge Kutta method for solving ODE | m | + | + | + | m | - | + | - | - |
Implemented functions | 71.429%
(5/7) |
85.714%
(6/7) |
85.714%
(6/7) |
100.000%
(7/7) |
85.714%
(6/7) |
42.857%
(3/7) |
71.429%
(5/7) |
28.571%
(2/7) |
42.857%
(3/7) |
Functions
(Version) |
GAUSS | Mac-
syma |
Maple | Mathe-
matica |
Mat-
lab |
Mu-
PAD |
O-
Matrix |
Ox | S-
Plus |
(3.2.29) | (2.2.1) | (V4) | (3.0.1) | (5.1) | (1.3.0) | (3.2) | (1.11) | (V4) | |
Markov models | m | + | - | - | - | - | - | - | - |
Mean | + | + | + | + | + | + | + | + | + |
Median | + | + | + | + | + | - | + | + | + |
Mode | m | - | + | + | - | + | - | - | - |
Variance | + | + | + | + | + | + | + | + | + |
Beta distribution
(Density / CDF / random num.) |
m / + / + | + / + / - | + / + / + | + / + / + | m / m / m | - / - / - | - / - / - | + / + / + | + / + / + |
Chi-squared distr.
(Density / CDF / random num.) |
m / + / m | + / + / - | + / + / + | + / + / + | m / m / m | - / - / - | - / - / - | + / + / + | + / + / + |
Gamma distr.
(Density / CDF / random num.) |
m / + / + | + / + / - | + / + / + | + / + / + | m / m / m | - / - / - | - / - / - | + / + / + | + / + / + |
Log-normal distr.
(Density / CDF / random num.) |
+ / + / m | + / + / - | + / + / + | + / + / + | m / m / m | - / - / - | - / - / - | - / - / - | + / + / + |
Normal distr.
(Density / CDF / random num.) |
+ / + / + | + / + / - | + / + / + | + / + / + | + / + / + | - / - / - | - / + / + | + / + / + | + / + / + |
Poisson distr.
(Density / CDF / random num.) |
m / m / + | + / + / - | + / + / + | + / + / + | m / m / m | - / - / - | - / - / - | - / - / + | + / + / + |
Uniform distr.
(Density / CDF / random num.) |
m / m / + | + / + / + | + / + / + | + / + / + | + / + / + | - / - / + | - / - / + | - / - / + | + / + / + |
More distr.
(Density / CDF / random num.) |
+ / + / + | + / + / - | + / + / + | + / + / + | m / m / m | - / - / - | - / + / - | + / + / + | + / + / + |
Implemented functions | 100.000%
(29/29) |
72.414%
(21/29) |
96.552%
(28/29) |
96.552%
(28/29) |
93.103%
(27/29) |
13.793%
(4/29) |
24.138%
(7/29) |
68.966%
(20/29) |
93.103%
(27/29) |
Functions
(Version) |
GAUSS | Mac-
syma |
Maple | Mathe-
matica |
Mat-
lab |
Mu-
PAD |
O-
Matrix |
Ox | S-
Plus |
(3.2.29) | (2.2.1) | (V4) | (3.0.1) | (5.1) | (1.3.0) | (3.2) | (1.11) | (V4) | |
Linear regression | + | + | + | + | + | - | + | + | + |
Polynomial regression | m | + | + | + | + | - | + | - | + |
Nonlinear Regression | m | + | - | + | m | - | + | - | + |
Loess regression | + | - | - | m | + | - | - | - | + |
LOGIT regression | m | - | - | - | - | - | - | - | + |
PROBIT regression | m | - | - | - | - | - | - | m | + |
PSN regression | m | - | - | - | - | - | - | - | - |
Event count models | m | - | - | - | - | - | - | - | + |
Duration models | m | - | - | - | - | - | - | - | - |
Goodness of fit test | m | - | - | - | - | - | - | - | + |
T-Test | - | - | - | + | m | - | + | - | + |
F-Test | - | - | - | + | - | - | + | - | + |
Q-Test | m | - | - | - | - | - | - | - | - |
Z-Test | - | - | - | - | m | - | - | - | + |
Maximum Likelihood
(Unconstr. / Constr.) |
m / m | - / - | - / - | - / - | m / - | - / - | - / - | - / - | + / + |
ARIMA | m | - | - | m | m | - | - | m | + |
Time series analysis
(Stationary / Non-stat.) |
m / m | - / - | - / - | m / m | m / m | - / - | - / - | + / m | + / + |
GARCH models
(Univariate / Multivar.) |
m / m | - / - | - / - | m / m | - / - | - / - | - / - | - / - | m / m |
Wavelets | m | - | - | m | m | - | + | - | m |
Cluster analysis | - | - | - | - | - | - | - | - | + |
Survival analysis | - | - | - | - | - | - | - | - | + |
Implemented functions | 79.167%
(19/24) |
12.500%
(3/24) |
8.333%
(2/24) |
50.000%
(12/24) |
45.833%
(11/24) |
0.000%
(0/24) |
25.000%
(6/24) |
20.833%
(5/24) |
87.500%
(21/24) |
Functions
(Version) |
GAUSS | Mac-
syma |
Maple | Mathe-
matica |
Mat-
lab |
Mu-
PAD |
O-
Matrix |
Ox | S-
Plus |
(3.2.29) | (2.2.1) | (V4) | (3.0.1) | (5.1) | (1.3.0) | (3.2) | (1.11) | (V4) | |
Cointegration models | m | - | - | - | - | - | - | + | - |
Black Scholes model | - | + | + | m | m | - | - | - | - |
Dynamic rational expectation models | m | - | - | - | - | - | - | - | - |
Linear rational expectation models | m | - | - | - | m | - | - | - | - |
Non-linear rational expectation models | m | - | - | - | - | - | - | - | - |
Social network models | m | - | - | - | - | - | - | - | - |
Kalman filter | m | - | - | m | m | - | + | m | - |
Neuronal networks | m | - | - | m | m | - | - | - | - |
Regressive-autore-
gressive models |
m | - | - | m | m | - | - | - | + |
Portfolio analysis | m | - | - | m | m | - | - | - | - |
State-space models | m | - | - | m | m | - | - | m | - |
Implemented
functions |
90.909%
(10/11) |
9.091%
(1/11) |
9.091%
(1/11) |
54.545%
(6/11) |
63.636%
(7/11) |
0.000%
(0/11) |
9.091%
(1/11) |
27.273%
(3/11) |
9.091%
(1/11) |
Functions
(Version) |
GAUSS | Mac-
syma |
Maple | Mathe-
matica |
Mat-
lab |
Mu-
PAD |
O-
Matrix |
Ox | S-
Plus |
(3.2.29) | (2.2.1) | (V4) | (3.0.1) | (5.1) | (1.3.0) | (3.2) | (1.11) | (V4) | |
Standard mathematics (5%) | 60.000% | 100.000% | 100.000% | 100.000% | 80.000% | 80.000% | 60.000% | 80.000% | 60.000% |
Linear Algebra (15%) | 94.118% | 88.235% | 64.706% | 88.235% | 94.118% | 35.294% | 52.941% | 47.059% | 70.588% |
Analysis (10%) | 100.000% | 60.000% | 60.000% | 100.000% | 90.000% | 60.000% | 60.000% | 40.000% | 60.000% |
Numerical mathematics (10%) | 71.429% | 85.714% | 85.714% | 100.000% | 85.714% | 42.857% | 71.429% | 28.571% | 42.857% |
Stochastic (20%) | 100.000% | 72.414% | 96.552% | 96.552% | 93.103% | 13.793% | 24.138% | 68.966% | 93.103% |
Statistics (20%) | 79.167% | 12.500% | 8.333% | 50.000% | 45.833% | 0.000% | 25.000% | 20.833% | 87.500% |
Other mathematics (20%) | 90.909% | 9.091% | 9.091% | 54.545% | 63.636% | 0.000% | 9.091% | 27.273% | 9.091% |
Overall result
(100% = Best) |
88.276%
(92/103) |
51.608%
(57/103) |
52.073%
(59/103) |
78.455%
(83/103) |
76.204%
(80/103) |
22.338%
(23/103) |
35.730%
(37/103) |
41.330%
(46/103) |
61.813%
(75/103) |
100% would mean that all listed functions are implemented (103 of 103).
Functions
(Version) |
GAUSS | Mac-
syma |
Maple | Mathe-
matica |
Mat-
lab |
Mu-
PAD |
O-
Matrix |
Ox | S-
Plus |
(3.2.29) | (2.2.1) | (V4) | (3.0.1) | (5.1) | (1.3.0) | (3.2) | (1.11) | (V4) | |
2D-Graphics | |||||||||
Bar charts | + | + | + | + | + | - | + | - | + |
Other charts | + | - | - | + | + | - | + | - | + |
Error bars | - | - | - | + | + | - | + | - | + |
High-Low-Average Plot | - | - | - | m | m | - | - | - | + |
Histograms | + | + | + | + | + | - | + | + | + |
Log Plot | + | + | + | + | + | - | + | - | + |
Log-log Plot | + | + | + | + | + | - | + | - | + |
Polar Plot | + | + | + | + | + | + | + | - | + |
XY Plot | + | + | + | + | + | + | + | + | + |
3D-Graphics | |||||||||
Charts | - | - | - | + | + | - | - | - | + |
Contour Plot | + | + | + | + | + | + | + | - | + |
Error bars | - | - | - | - | - | - | - | - | - |
Height colors | + | + | + | + | + | + | + | - | + |
Surface Plot | + | + | + | + | + | + | + | - | + |
XYZ Plot | + | + | + | + | + | + | + | - | + |
Special graphic types and functions | |||||||||
Animations | - | + | + | + | + | + | - | - | - |
Bollinger bands | - | - | - | m | m | - | - | - | - |
Box & Whisker Plots | + | - | + | m | m | - | - | - | + |
Candlestick charts | - | - | - | m | m | - | - | - | - |
Cluster graphs | - | - | - | - | - | - | - | - | m |
Dendograms | - | - | - | - | - | - | - | - | m |
Periodograms | - | - | - | - | - | - | - | + | + |
QQ Plot | - | - | + | - | m | - | - | + | + |
Overall result
(100% = Best) |
52.174%
(12/23) |
47.826%
(11/23) |
56.522%
(13/23) |
78.261%
(18/23) |
82.609%
(19/23) |
30.435%
(7/23) |
52.174%
(12/23) |
17.391%
(4/23) |
82.609%
(19/23) |
Programming facilities | GAUSS | Mac-
syma |
Maple | Mathe-
matica |
Mat-
lab |
Mu-
PAD |
O-
Matrix |
Ox | S-
Plus |
(3.2.29) | (2.2.1) | (V4) | (3.0.1) | (5.1) | (1.3.0) | (3.2) | (1.11) | (V4) | |
Editing features | |||||||||
Built-in editor | + | + | + | + | + | + | + | + | + |
External editor configurable | + | - | + | + | + | - | - | - | + |
Source code formatting | m | + | - | - | + | - | - | - | + |
Syntax highlighting | - | - | - | - | + | - | - | m | - |
Debugging | |||||||||
Breakpoints | + | + | + | - | + | + | + | - | + |
Function Tracer | - | + | + | + | - | + | - | - | - |
Line Tracing | + | - | - | - | + | + | + | - | + |
Profiler | - | + | + | m | + | + | + | - | - |
Stack inspection | + | + | - | + | + | + | + | - | + |
Variable inspection | + | + | - | + | + | + | + | - | + |
Language features | |||||||||
API-interface | + | - | - | + | + | - | + | + | m |
DDE support | - | - | - | - | + | + | - | - | + |
GUI programming | - | - | - | + | + | - | + | - | + |
N-dimensional arrays (> 3) | - | + | + | + | + | + | - | + | + |
Object oriented programming | - | - | - | + | + | + | + | + | + |
OLE support | - | - | + | + | + | + | - | - | + |
P code compiling | + | + | - | + | + | - | - | + | - |
Language interfaces | |||||||||
Assembler | + | - | - | + | - | - | - | + | - |
C/C++ | + | - | - | + | + | - | - | + | + |
FORTRAN | + | - | + | + | + | - | - | + | + |
GAUSS | + | - | - | - | - | - | - | + | - |
Macsyma | - | + | - | - | - | - | - | - | - |
Maple | m | - | + | - | m | - | - | - | - |
Mathematica | - | - | - | + | m | - | - | - | - |
Matlab | - | + | - | m | + | - | - | - | - |
MuPAD | - | - | - | - | - | + | - | - | - |
O-Matrix | - | - | - | - | - | - | + | - | - |
Ox | - | - | - | - | - | - | - | + | - |
S-Plus | - | - | - | - | - | - | - | - | + |
DLL-Calls | + | - | - | + | + | - | + | + | + |
Overall result
(100% = Best) |
50.000%
(15/30) |
36.667%
(11/30) |
30.000%
(9/30) |
60.000%
(18/30) |
73.333%
(22/30) |
40.000%
(12/30) |
36.667%
(11/30) |
40.000%
(12/30) |
56.667%
(17/30) |
Data import/export
possibilities |
GAUSS | Mac-
syma |
Maple | Mathe-
matica |
Mat-
lab |
Mu-
PAD |
O-
Matrix |
Ox | S-
Plus |
(3.2.29) | (2.2.1) | (V4) | (3.0.1) | (5.1) | (1.3.0) | (3.2) | (1.11) | (V4) | |
ACCESS | - | - | - | m | - | - | - | - | + |
Applixware | - | - | - | - | m | - | - | - | - |
ASCII | + | + | + | + | + | + | + | + | + |
AutoCAD | - | + | - | + | - | - | - | - | - |
Binary | + | - | + | + | + | + | + | + | - |
dBase | m | - | - | - | - | - | - | - | + |
Excel | m | - | - | m | m | - | - | + | + |
FoxPro | m | - | - | - | - | - | - | - | + |
GAUSS | + | - | - | - | - | - | - | + | + |
Hypercard | - | - | - | m | - | - | - | - | - |
Informix | - | - | - | m | - | - | - | - | - |
Labview | - | - | - | m | - | - | - | - | - |
Lotus 1-2-3 | m | - | - | - | + | - | - | + | + |
Lotus Symphony | m | - | - | - | - | - | - | - | + |
Matlab | - | - | - | m | + | - | + | - | + |
ODBC-connections | - | - | - | - | - | - | - | - | + |
Ox | - | - | - | - | - | - | - | + | - |
Paradox | m | - | - | - | - | - | - | - | + |
Quattro Pro | m | - | - | - | - | - | - | - | + |
SAS | - | - | - | - | - | - | - | - | + |
SigmaPlot | - | - | - | - | - | - | - | - | + |
S-Plus | - | - | - | - | - | - | - | - | + |
SPSS | - | - | - | - | - | - | - | - | + |
STATA | - | - | - | - | - | - | - | - | + |
Systat | - | - | - | - | - | - | - | - | + |
Transform | - | - | - | m | - | - | - | - | - |
Overall result
(100% = Best) |
38.462%
(10/26) |
7.692%
(2/26) |
7.692%
(2/26) |
38.462%
(10/26) |
23.077%
(6/26) |
7.692%
(2/26) |
11.538%
(3/26) |
23.077%
(6/26) |
69.231%
(18/26) |
Platform
(Version) |
GAUSS | Mac-
syma |
Maple | Mathe-
matica |
Mat-
lab |
Mu-
PAD |
O-
Matrix |
Ox | S-
Plus |
(3.2.29) | (2.2.1) | (V4) | (3.0.1) | (5.1) | (1.3.0) | (3.2) | (1.11) | (V4) | |
Convex | - | - | + | + | - | + | - | - | - |
DEC
(Linux / UNIX / VMS) |
- / + / + | - / - / + | - / + / - | - / + / + | - / + / + | + / + / + | - / - / - | - / + / - | - / + / - |
HP 9000
(HP-UX / NextStep) |
+ / - | + / - | + / - | + / + | + / - | + / - | - / - | + / - | + / - |
IBM RISC
(IBM AIX) |
+ | + | + | + | + | + | - | + | + |
Intel (DOS) | + | - | + | - | - | + | - | + | - |
Intel (OS/2) | + | - | + | + | - | + | - | - | - |
Intel
(Win. 3.1x / 95,NT) |
- / + | + / + | + / + | - / + | - / + | - / + | + / + | + / + | + / + |
Intel (Linux) | + | - | + | + | + | + | - | + | - |
Intel
(Solaris x86/NextStep) |
+ / - | - / - | - / - | - / + | - / - | + / + | - / - | - / - | - / - |
Motorola
(MAC OS / NextStep) |
- / - | - / - | + / + | + / + | + / - | + / - | - / - | - / - | - / - |
SGI (SGI IRIX) | + | + | + | + | + | + | - | + | + |
SUN (Solaris) | + | + | + | + | + | + | - | + | + |
Total amount | 61.111%
(11/18) |
33.333%
(6/18) |
72.222%
(13/18) |
77.778%
(14/18) |
50.000%
(9/18) |
83.333%
(15/18) |
11.111%
(2/18) |
50.000%
(9/18) |
38.889%
(7/18) |
The assessment for this part of the test report is also calculated by the key amount of available platforms divided by the total amount of listed platforms and will be displayed in percentage.
Functions | GAUSS | Mac-
syma |
Maple | Mathe-
matica |
Mat-
lab |
Mu-
PAD |
O-
Matrix |
Ox | S-
Plus |
(3.2.29) | (2.2.1) | (V4) | (3.0.1) | (5.1) | (1.3.0) | (3.2) | (1.11) | (V4) | |
400 x 400 random matrix^1000 | 16.476 | 136.747 | > 1h | 30.023 | 5.468 | > 1h | 0.400 | 1.011 | 1.260 |
Eigenvalues of a 300 x 300 random matrix | 44.670 | 9.984 | > 1h | 45.626 | 48.760 | > 1h | 11.937 | 41.202 | 49.830 |
Inverse of a 500 x 500 random matrix | 27.476 | 149.014 | > 1h | 142.054 | 27.504 | * | 26.678 | 26.969 | 99.280 |
Sorting of 500000 random values | 8.202 | 434.013 | *** | 108.550 | 33.782 | 54.58 | 11.877 | 8.258 | 5.150 |
Creation of a 800 x 800 Toeplitzmatrix | 1.718 | 1660.788 | 207.748 | 187.289 | 2.009 | > 1h | 37.735 | 0.307 | 13.160 |
Cholesky decomposition of a 500 x 500 random matrix | 4.100 | ** | > 1h | 927.624 | 3.939 | ** | 134.453 | 4.089 | 9.750 |
Creation of a 500 x 500 cross-product matrix | 28.265 | > 1h | > 1h | 59.366 | 24.423 | > 1h | 7.621 | 13.205 | 35.320 |
FFT over 100000 random values | 6.940 | 2103.384 | **** | 23.054 | 2.686 | 46.76 | 1.502 | 5.651 | 3.180 |
Gaussian error function over a 500 x 500 random matrix | 4.048 | 966.599 | > 1h | 55.74 | 15.790 | > 1h | 1.572 | 1.228 | - |
Gamma function on a 600 x 600 random matrix | 2.715 | > 1h | > 1h | 94.946 | 27.886 | > 1h | 6.138 | 6.723 | 6.600 |
Linear regression over a 500 x 500 random matrix | 22.184 | 2017.682 | 77.702 | > 1h | 10.886 | - | 7.661 | 16.941 | 29.770 |
Overall performance | 49.937% | 10.971% | 0.013% | 7.674% | 39.975% | 1.658% | 70.799% | 66.207% | 37.176% |
The overall performance will be calculated in the following way :
The best timing result of a benchmark function makes 100%; for calculating the results for each function I'll take the fastest timing and divide it by the timing of the tested program (the formula will look MIN(A1;A2;...)/A2 for example) and that makes the ranking in percentage. To calculate the final "Overall performance" I'll than sum the percentage values for each tested program and divide by the amount of tested functions (in the moment 12) which will make the result in percentage again.
Test | GAUSS | Mac-
syma |
Maple | Mathe-
matica |
Mat-
lab |
Mu-
PAD |
O-
Matrix |
Ox | S-
Plus |
(3.2.29) | (2.2.1) | (V4) | (3.0.1) | (5.1) | (1.3.0) | (3.2) | (1.11) | (V4) | |
Comparison of the mathematical functionality (38%) | 88.276% | 51.608% | 52.073% | 78.455% | 76.204% | 22.338% | 35.730% | 41.330% | 61.813% |
Comparison of the graphical functionality (10%) | 52.174% | 47.826% | 56.522% | 78.261% | 82.609% | 30.435% | 52.174% | 17.391% | 82.609% |
Functionality of the programming environment (8%) | 50.000% | 36.667% | 30.000% | 60.000% | 73.333% | 40.000% | 36.667% | 40.000% | 56.667% |
Data import/export (5%) | 38.462% | 7.692% | 7.692% | 38.462% | 23.077% | 7.692% | 11.538% | 23.077% | 69.231% |
Available platforms (2%) | 61.111% | 33.333% | 72.222% | 77.778% | 50.000% | 83.333% | 11.111% | 50.000% | 38.889% |
Speed comparison (37%) | 49.937% | 10.971% | 0.013% | 7.674% | 39.975% | 1.658% | 70.799% | 66.207% | 37.176% |
Overall result | 64.384% | 32.437% | 29.674% | 48.757% | 60.029% | 17.397% | 48.723% | 47.295% | 54.277% |
Note : The overall results of some tested programs are pretty bad due to the specific weighting of this testreport. I would like to mention that this does of course not mean that the software is bad but that the programs are maybe not perfect for the specific usage mentioned in the testreport, for other weightings/usages they might be much better or even leading.
Pricing : Another important point to mention is also that I have not reported the prices for each software product nor the additional modules which might make some products quiete expensive. Summarizing I would like to notice that the programs MuPAD, the lightversion of O-Matrix and Ox are available free of charge for educational and academic usage. The other software products are varying very strongly in their prices and in their license politics.