The LISE++ Ray Reader is a plotting tool that takes Monte Carlo simulated data from the LISE++ program and plots it using Matplotlib in python. Allows for 1-D, 2-D, and 3-D plots to be compared simultaneously. Matplotlib plots can be saved and stored on a local computer. The LISE++ Ray Reader program can be downloaded from the LISE++ nscl.msu.edu website.
LISE++ Ray Reader is a stand alone utility that analyzes a comma delimited .ray file that is generated through the Monte Carlo fragment transmission simulator within LISE++. The Ray Reader program creates 1D, 2D, and 3D plot graphics that can be used for Power Point presentations, web graphics, reports, and other academic uses. The data within the .ray file can be manipulated by selecting specific locations and fields in combo boxes that can be filtered by restricting the data numeric values. The Ray Reader can generate five different plots simultaneously, the 1D (X, Y, and Z), 2D (X/Y), and 3D (X/Y/Z). The data results will also display in a "Data results" tab. Each of the five plots can have unique styles set such as the plot color, marker, and edge. At the time this documentation was written, the version of LISE++ was 16.3.7. This documentation is written for the Ray Reader version beta 1.0.
All data examples used in this documentation are specific to the A1900 fragment separator.
In order for this program to function properly, create a ray file from the LISE++ program.
Step 1: Launch LISE++. If you don't have it download it here.
Step 2: Click the preferences icon that is fourth from the left at of the top tool bar.
TopStep 3: Select the configuration file and options file you want. In our case we selected the A1900 fragment separator which is the default option.
TopStep 4: Select experimental parameters located in the yellow section.
TopStep 5: Select the "all nuclei" button that is twelfth from the right in the top tool bar once experimental parameters are selected. The table of nucleides will be empty before pressing the "all nuclei" button.
TopStep 6: Select the Monte Carlo icon that is second from the right in the top tool bar.
TopStep 7: Select the radio button for the "Group of isotopes already calculated by the Distribution method."
TopStep 8: Click the "MC transmission options" towards the bottom-left of the "Monte Carlo calculation of fragment transmission" box.
TopStep 9: In the "MC transmission options" box to the top-right check the box next to "Cross-sections independent calculations (all cross section equal)."
TopStep 10: Select the "MC calculation to file" at the bottom-left corner of the "Monte Carlo calculation of fragment transmission" box.
TopStep 11: Select locations to perform Monte Carlo simulation. In the locations combo box you can enter the number of locations you want. The example shown is for the A1900 fragment separator.
TopStep 12: Select fields to perform Monte Carlo simulation. In the fields combo box you can enter the number of fields you want. The example shown is for the A1900 fragment separator.
TopStep 13: To the bottom right of the "Rays generator" window select the comma option under the "Fields separator" drop down box.
TopStep 14: Click the Run button at the bottom left of the "Rays generator" box. You will see the file being generated indicated by the box saying "Generating Ray file." The "Isotope Group: Monte Carlo Transmission Plot" can be ignored. The save path on windows will be C:\Users\<user>\Documents\LISEcute\files.
TopOptional Step: If the user wished to rename the file or change where the ray file is saved you can click the "Output file name" button. The "Save As" box will show the directory where the ray file will be saved and the name of the file can be changed. It will automatically save to C:\Users\<user>\Documents\LISEcute\files with the file name "MC_LISE.ray." The first graphic below shows where to select the output file. The second graphic below shows the "Save File" dialogue box that appears when the "Output file name" button is clicked.
TopThe plot settings contain all the parameters necessary for plotting the simulated output produced from the LISE++ program. The main data is measured at the Locations and Fields that is simulated from the actual facility of interest.
The locations refer to individual portions of the fragment separator of interest. The following graphic is a snapshot of the A1900 fragment separator displayed in the LISE++ program.
TopThe list below defines each point in the A1900 fragment separator.
The user can select a location from the combo boxes in the "Locations" section. These locations are pulled from the .ray file that is generated from LISE++. The graphic below shows the X values in the combo box that was loaded from the ray file "ray-tutorial.ray."
The location values will be the same in every location combo box throughout the program. The location values come from the .ray file that was generated within the Monte Carlo simulation in the LISE++ program.
TopThe fields in the combo box are taken from the .ray file that is generated from the LISE++ Monte Carlo simulation of the fragment transmission. These parameters will load into the Ray Reader Fields combo box. An example list of available values for the A1900 fragment separator are defined below.
The field values will be the same in every field combo box throughout the program. The field values come from the .ray file that was generated within the Monte Carlo simulation in the LISE++ program.
TopThe graphic below shows what the fields look like after the .ray file is loaded.
TopThe "Data Range Filter" filters the data results to specific parameters. The data results can be narrowed down to a specific location, field, and numeric value range.
The "Location" combo box are the same as found in the Locations section. The "Locations" combo box is to allow the data set to be filtered to a specific range of data. This narrows the data results to a specific location within the fragment separator that is not necessarily the X, Y, or Z location chosen in the data sample you are plotting. For example in the graphic below , the X, Y, and Z locations are set to the location within the A1900 FP_PIN detector. The location selected in the "Data Range Filter" is selected to the location where the I1_Slits are within the A1900 fragment separator.
TopThe "Fields" combo box are the same as found in the Field section. Similar to the "Locations" in the previous section, the "Fields" can be filtered to a specific field quantity that is measured at the specific location. The graphic below shows where the "Data Range Filter" Field combo box is located.
TopThe boundary slider can filter the data results by the lowest negative and greatest positive number. You adjust the numeric value by dragging the slider handle or by clicking in the grayed out area of the slider. Moving the handle increments at a greater rate that clicking the gray area of the slider. Clicking the gray area will increment by 1 value per click. The below graphic shows the location of the boundary slider.
TopThe "Plot Style Settings" allow the user to customize the appearance of each graphic individually on each tab.
The color map combo box contains a various array of color styles that are supplied by the matplotlib documentation. The graphic below shows the available colormaps in the Ray Reader program combo box.
TopOnly a few of the possible colormaps available are supplied in the Ray Reader program. The below graphics are the key to the colormaps that are available in the Ray Reader program.
For a full list of color map style please visit the matplotlib colormap reference.
The markers used in the LISE++ Ray Reader is from Matplotlib's library. The table below is from the Matplotlib Documentation. For a comprehensive list of the marker styles, please visit the Matplotlib website regarding matplotlib.markers.
marker |
symbol |
description |
---|---|---|
|
point |
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pixel |
|
|
circle |
|
|
triangle_down |
|
|
triangle_up |
|
|
triangle_left |
|
|
triangle_right |
|
|
tri_down |
|
|
tri_up |
|
|
tri_left |
|
|
tri_right |
|
|
octagon |
|
|
square |
|
|
pentagon |
|
|
plus (filled) |
|
|
star |
|
|
hexagon1 |
|
|
hexagon2 |
|
|
plus |
|
|
x |
|
|
x (filled) |
|
|
diamond |
|
|
thin_diamond |
|
|
vline |
|
|
hline |
The "Location" combo box in the "Data Range Filter" allows the user to apply a colormap to your plots based on a different location that is specified in the X, Y, and Z Value columns. The graphic below shows where the "Location" combo box is in the "Data Range Filter."
TopThe "Field" combo box in the "Data Range Filter" allows the user to apply a colormap to your plots based on a different field that is specified in the X, Y, and Z Value columns. The graphic below shows where the "Field" combo box is in the "Data Range Filter."
TopThe "Edge" combo box shown in the graphic below adds an outline to each individual plot marker.
The below graphic shows what the edge looks like when a "black" edge is applied to the "gist_rainbow" colormap.
TopThe following graphics show examples of each tab in order of how the colormap, marker, location, field, and edge parameters are displayed when plotted. Each tab can be customized particularly to its own requirement and displayed simultaneously.
TopThe "Plot Analysis Window" displays the data results and the 1D, 2D, and 3D plots in separate tabs.
The "Data Results" tab contains the data that was plotted from the .ray file.
TopWhen the data is filtered using the "Data Range Filter" only the filtered data will appear in the "Data Results" tab. Below is a graphic of filtered data in the "Data Results" tab.
TopThe X, Y, and Z plots function the same. The "X Value" column in the "Plot Settings" will display in the "X Plot" tab, the "Y Value" column will display on the "Y Plot" tab, and the "Z Value" column will display in the "Z Plot" tab. These are the same data columns shown in the "Data Results" tab. The below image is the default style the user will see with no style changes.
TopThe X and Y columns in the "Plot Settings" will be combined in the "X and Y plot" tab. The following graphic is a default styled 2D X and Y plot.
TopThe 3D plots are a combination of the X, Y, and Z Values in the "Plot Settings." The below graphic is a default 3D plot with no style applied.
TopThe Matplotlib controls are located at the bottom left hand side of the plot window.
When changing the views of your particular plot, you can reset the view to the default position by clicking the "Reset" button shown in the graphic below.
The previous and forward buttons will allow the user access a history of views that were created in order. When the arrows are blanked out like the following image, there were no views made.
When you have zoomed, panned, or made a change in the view, the left arrow will become dark.
If you made multiple changes, both arrows will become dark indicating that you can go forward or backward in the order of the history of changes.
The plot can be panned in various directions, the "Pan" button is shown in the following graphic.
The default position prior to panning left or right is shown below.
You can pan left, right, up, or down.
First, click the "Pan" button.
Then hold the left mouse button down and move the cursor in the direction you wish to pan towards.
The first graphic on the bottom shows a pan to the left and the second bottom graphic shows a pan to the right.
TopYou can also pan the 3D graphic in any direction 360 degrees using the same method as the 1D and 2D pan.
First, click the "Pan" button.
Then hold the left mouse button down and move the cursor in any direction you wish to pan towards.
The first graphic below shows an upwards pan and the second graphic shows a left pan.
TopYou can zoom into your plot by using the "zoom" tool button shown in the graphic below.
After selecting the zoom button, you can use the square marquee to select the area you want to zoom into. The first graphic below shows the marquee tool in use. The second graphic below shows the plot after the area was selected by the zoom tool.
TopTo zoom into a 3D plot, hold the right mouse button down and move your mouse up (zoom in) or down (zoom out). The first graphic below is zoomed in and the second graphic is zoomed out.
If your mouse has a scroll wheel, you can use the scroll wheel to zoom in and out as well.
TopYou can adjust the view of each subplot configuration using the "Configure Subplots" button. The "Configure Subplots" button is displayed in the following graphic.
Clicking the "Configure Subplots" button brings up the "Subplot Configuration Tool" shown in the graphic below.
You can adjust the left, bottom, right, top, wspace, and hspace by moving the slider handles left or right.
TopYou can save your plot graphic by clicking the "Save" button shown in the graphic below.
When you click the "Save" button, a "Save the figure" dialogue box will appear allowing the user to choose the location, file name, and file type. You can save each plot as a .png, .jpg, .jpeg, .eps, .pdf, .pgf, .ps, .raw, .rgba, .svg, .svgz, .tif, or .tiff file format.
TopThe Ray Reader program has a console running in the background that provides meta data while the program runs. The user can use this to diagnose errors while using the program.
TopThe Ray Reader program also has a console running in the background in order to view raw data statistics and errors. When the program initially loads, there will be no .ray file data loaded. The below graphic shows the console at the initial state.
When a .ray file is loaded, the console will display the data from the .ray file. The below graphic shows what the .ray file data looks like in the console.
TopA common error is the "No such file or directory" error. See the following graphic.
This error occurs when the .ray file has cached in the program improperly or there was no file loaded in the Ray Reader. To get past this error, go to File > Restart in the Ray Reader program.
TopThis error occurs when the LISE++ program encodes your .ray file with a character or file encoding that is not compatible with the Ray Reader program. See the following graphic.
Contact the LISE++ developer and tell them the Monte Carlo Simulator is not creating a file with the correct character encoding. You can see the character encoding problem in the .ray file by opening the .ray file with notepad, excel or any other compatible program. You will see invalid characters in the file. The following graphic is an example of a file with invalid characters.
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