VOPlot –
The VOTable plotting utility (Version 1.0) |
Creating data subsets by applying filters
Statistical Functions on Plotted Data
The standalone version of the VOPlot (VOTable Plot) is an application for plotting different astronomical graphs using data stored in VOTable format. Its web-based version is integrated with the VizieR Catalogue Service and can be used to plot any catalogue by selecting output layout as "Plot (VOPlot)". Click here for Release Notes and disclaimer information.
VOPlot has been developed as a part of the Virtual Observatory - India initiative by Persistent Systems and the Inter-University Centre for Astronomy and Astrophysics (IUCAA), in collaboration with Centre de Données astronomiques de Strasbourg (CDS), with a support from the European AVO project. The collaboration between VO-I and CDS extends to several related projects.The VO-I project is supported by the Ministry of Information and Communication Technology of the Governement of India.
VOPlot uses Ptplot 5.2, a 2D data plotter and histogram tool implemented in Java. Ptplot has been developed at EECS department at the University of California, Berkeley.
To use the standalone version of VOPlot, you will need to download the executable jar file named voplot.jar. The file can be executed by typing the following command at the command prompt:
java -jar voplot.jar
This will open a java application window as shown in the Fig. 0. To use data from a VOTable you will need to load it first. You can either specify the URL of a VOTable or specify the path of a VOTable on your machine by using the “Browse” button. The name of the selected VOTable will appear in the text box. Click on the “Load” button to start using the VOTable. The message on the status bar will indicate whether the file was loaded successfully.
To draw a plot of one columns against the other,
You can see the scatter plot. If required, you can plot data points on a log scale by setting the option appropriately using the "Log" checkbox.
You can draw connected line plots by checking the “Connected” checkbox in the Plot Properties dialog box.
To change various plot properties, such as title, labels ranges etc., click on the format icon .
Figure 2
To draw the histogram of a column
A sample histogram is shown in Figure 3.
Figure 3
To plot the histogram bar heights on a logarithmic scale, check the "Log" checkbox corresponding to the Y-axis If you want to plot the histogram of data points on a log scale, then check the "Log" checkbox corresponding to the X-axis.
When drawing histograms on a logarithmic Y-axis, the bars with height 1 cannot be drawn. You can force the VOPlot to draw such bars by incrementing the height of all the bars by 1. This is done by checking the “Incremented Y” checkbox in the Histogram Properties dialog box.
To change the histogram properties, including the bin width, click on the format icon .
Figure 4
To zoom in, drag the left mouse button down and to the right to draw a box around an area that you want to see in detail.
To zoom out, drag the left mouse button up and to the left.
To get the original graph click on the "Reset" icon represented by .
To overlay plots (simultaneously viewing multiple plots with similar range on the same axes system)
You can see the second plot overlaid on the first one if the second one is in the same range as the previous one. Only that portion of the second plot is visible that is within the already plotted range.
An example of overlaid plots is shown in Figure 5.
Figure 5
To see the plots overlaid together (even if they don’t lie in the same range) click on the fill icon represented by . Figure 6 shows the complete datasets of all the overlaid plots in the graph above. A different marker will be used for each plot, to allow one to differentiate between the plots.
Figure 6
To overlay histograms (simultaneously viewing multiple histograms with similar range)
The second histogram is seen only if it lies within the same X and Y range as the first one. Click on the fill icon represented by to see both histograms irrespective of the range. A different color will be used for each histogram, to allow one to differentiate between the histograms.
Example of overlaid histogram is shown in Figure 7.
Figure 7
One can create new columns by defining transformations on them. You can use expressions with arithmetic operators, trigonometric functions, and miscellaneous functions shown below to create new columns. You can use transformed columns for plotting.
+ |
Addition |
- |
Subtraction |
* |
Multiplication |
/ |
Division |
log(a) |
Log to the base 10. |
ln(a) |
Log to the base e. |
pow(a,b) |
"a" raised to power of "b". |
sqrt(a) |
Square root of "a". |
exp(a) |
Euler's number e raised to the power of "a". |
dexp(a) |
10 raised to the power of "a". |
cos(a) |
Trigonometric cosine of an angle. a = an angle in radians. |
acos(a) |
Arc cosine of an angle |
sin(a) |
Trigonometric sine of an angle. a = an angle in radians. |
asin(a) |
Arc sine of an angle |
tan(a) |
Trigonometric tangent of an angle. a = an angle in radians. |
atan(a) |
Arc tangent of an angle |
toradians(a) |
Converts an angle measured in degrees to an equivalent angle measured in radians. |
todegrees(a) |
Converts an angle measured in radians to an equivalent angle measured in degrees. |
The dialog box for creating new columns is shown in Figure 8.
Figure 8
You can create new data subsets by defining filters on them. You can use filter definition with relational operators and logical operators with operators and functions shown above to create new data subsets. Data subsets can be used for plotting.
< |
Less than |
<= |
Less than or equal to |
> |
Greater than |
>= |
Greater than or equal to |
== |
Equal to |
!= |
Not equal to |
&& |
And |
|| |
Or |
! |
Not |
The dialog box for creating data subsets is shown in Figure 9.
Figure 9
Once a data subset is created you can plot data from the subset. This can be done by choosing the data subset from the Filters combo box in the main applet window.
Note: "All" represents the complete data. Only data points satisfying the filter condition will be considered for plotting.
Statistical functions can be applied on the plotted data.
The dialog box is divided into two tabs – basic and advanced functions. The basic functions require only one data array, while the advanced functions require two or three data arrays as parameters.
The following statistical functions are currently supported.
Sr. No. |
Function name |
Input Columns |
1 |
Number of observations |
X |
2 |
Range |
X |
3 |
Minimum |
X |
4 |
Maximum |
X |
5 |
Mean |
X |
6 |
Variance |
X |
7 |
Standard deviation |
X |
8 |
Skew |
X |
9 |
Kurtosis |
X |
10 |
Linear correlation |
X, Y |
11 |
Significance (t) for Linear correlation |
X, Y |
12 |
Probability for Linear correlation |
X, Y |
13 |
Rank correlation |
X, Y |
14 |
Partial correlation |
X, Y, Z |
VOPlot, by default, takes the complete dataset into consideration while evaluating the statistical functions. However you can force it to consider only the plotted data range by selecting the "Use only plot data" checkbox. This will evaluate the statistical functions for the currently plotted columns, along with the applied filter, if any, in the current axes ranges.
Sample dialog box with basic tab selected showing plot statistics is shown in Figure 10.
Figure 10
Sample "Advanced Functions" tab is shown in Figure 11.
Figure 11
For saving the plot as an image, plot the desired image and click on save icon represented by . The save as dialog box will appear. Select a file and click on OK to save the image as an EPS file onto your machine. Currently, the image can only be saved as an EPS file
For feedback on VOPlot contact voindia@vo.iucaa.ernet.in.