ioGAS Quick Start Tutorial
Quick Start Tutorial Overview An ioGAS evaluation licence is valid for two weeks and the software is fully functional during this time. After this time the software can only be used with a valid licence file. *Note that the two week trial period is not available for MAC installations so if you are running a MAC please read the installation instructions in the download zip file for details on how to obtain an evaluation licence file. To learn how the ioGAS program works we recommend first viewing the Overview video available from the ioGAS website www.iogas.net www.iogas.net.. Use the steps in this tutorial to follow a typical workflow to get you up and running and using var ious features of the ioGAS software. The tutorial uses an excel version of the ioGAS demonstration dataset. For our maintained users there are a number of additional training videos available from the Help>Training Videos menu. Contact
[email protected] to purchase ioGAS or for any other licensing enquiries.
1. IMPORT DATA ioGAS can support the following file types:
Native ioGAS files
Tab-delimited TXT files
Comma-delimited CSV files
Excel Spreadsheet XLS & XLSX files
Geography Markup GML files
XRF Data files (Olympus Innov-X CSV/DB F files, Niton NTG files)
ODBC Database (Access, SQL, etc)
1.
Select File>Open or click on the Open File
2.
Browse to one of the following locations depending on what operating system is installed:
PC users (32-bit Installation): C:\Program Files (x86)\ioAnalytics\ioGAS\demo data folder
PC users (64-bit installation): C:\Program Files\ioAnalytics\ioGAS-64\demodata folder
3.
icon on the Main Toolbar.
MAC users: ioGAS Application\Contents\Resources\app\dem Application\Contents\Resources\app\demodata odata folder
Use the drop-down arrow next to Files of type: and select Excel Spreadsheet files - all (.xls, .xlsx files). Highlight the Demo.xlsx file and click on the Open File button.
DEFINE COLUMN TYPES
2.
Generally when a dataset is first imported into ioGAS the Column Properties dialog is displayed. This is where columns in the dataset are matched to columns required by ioGAS in order for data to be plotted successfully.
Special Columns This section is where the sample number and c oordinate columns in the dataset are selected so they can used to display data in the plot windows.
ID - Unique sample identifier. East/North - X and Y coordinate columns. Used to display data in all spatial map views. Generally these will be in a projected coordinate system such as UTM coordinates. East/North Projection - Coordinate system used for East/North columns above. This is the projection which will be used in some geographical exports, eg. gridded images as GeoTiff Images or ER Mapper grids, ArcGIS exports WGS84 Longitude/Latitude (decimal degrees) - Separate X and Y lat/long coordinate columns in decimal degrees required in order to export data to Google Earth.
1.
Match the columns in the demo dataset to the following Special Columns in ioGAS:
ID = Sample Num
East = East_AMG84_z51
North = North_AMG84_z51
East/North projection = AMG (AGD84) Zone 51
WGS84 Longitude (decimal degrees) = Long_WGS84
WGS84 latitude (decimal degrees) = Lat_WGS84
Column Name and Type Underneath in the Column Name and Type area ioGAS automatically assigns each column in the dataset as either Numeric, Text or Non-Plot. Sample ID and coordinate columns listed above are assigned as Non-Plot, ie. not variable columns. Variable columns are assigned as numeric or text. Analysis data to be used in plots is generally numeric whereas text data is used to 'group' data, for example Regolith Unit, Geology, Sample Medium, etc. If a column is imported as a text field yet contains numeric data then the column can be re-assigned as a numeric column co lumn and vice versa. 2.
Scroll down and have a look at the different column types assigned to this dataset
Non-Plot columns have a grey circle next to them while text columns have a black circle. Numeric columns can have either a blue circle or a green circle next to them depending on whether they are "aliased" or not. See Step 4 for more information on aliasing variables. Red circles denote that there is a problem such as duplicate column names and will need to be fixed before exiting this dialog. ioGAS lists the number of samples in each column that are numeric, text or null (blank) on the righthand side of the dialog. There are 999 records in the demo dataset. 3. Place the cursor over the original column name (without mouse clicking) to view tooltip information about the data in the selected column. Text columns display the individual categories and numeric columns display min, median and max values. If the tooltips do not appear click within the window to make it active and try again. Note that it is still possible to plot data and use many of the functions within ioGAS w ithout having an ID column selected. This is true for spatial fields as well and it is possible to set any of these at any time.
Column Properties Dialog Showing Assigned Special Columns
4.
It is also possible to remove any columns before import but clicking on the cross next to the column to delete. These columns will be permanently removed from the imported dataset when the OK button is clicked.
See Column Properties in the Help>Help menu for more information.
3.
SET COLUMN ALIAS NAMES
One very important feature of ioGAS is that if the element and the units that the values are captured in is known for each column, ioGAS can perform unit or element/oxide conversions on-the-fly in order to use the data with the classification diagrams, calculations and spider plot normalisations shipped with the program if the data is not already in the required format. The way to "alias" columns is to select a standard geochemical element/unit combination from the Alias pull-down list next to each variable. When a column is "aliased" the circle next to this c olumn is then coloured green (indicating that it is a numeric column that i s aliased) rather than blue (numeric) or black (text). See screen capture below. Observe the original names in the demonstration dataset compared with their "aliased" names which include what units they are captured in. If ioGAS can already guess the "aliased" name from the original column name it will attempt to automatically assign "aliased" names when a file is imported. Note: In ioGAS all variables can be renamed as desired and the new name will be shown everywhere in the program. To enter a new name for a column simply overwrite the one displayed in the Alias column for that variable. Use the following steps to "alias" the columns in the demonstration dataset to standard element/unit names: 1.
Click on the Guess Aliases button. ioGAS will automatically guess the element and unit from the original column name for each column. To alias a single column at a time use the Guess Alias icon next to each variable.
It is important to check the data to make sure that the correct element/oxide/unit combination name has been applied. To manually assign an alias name to a column select the appropriate element/oxide/unit combination from the pull-down list. To reset a single column back to the original name click on the black arrow button next to each column or reset them all using the Reset Aliases button. 2.
When you are satisfied that the columns have been "aliased" correctly click OK to proceed.
The Column Properties settings are retained when the file is saved in ioGAS format and can be modified at any time by clicking on the closed when you do this.
icon on the Main Toolbar. Note that all windows will be
See Column Properties and Alias Columns in the Help>Help file for more information.
4.
USER INTERFACE & ATTRIBUTE MAP
The imported dataset is now loaded into ioGAS with the file name and path displayed in the titlebar of the program. In the middle of the screen is the Attribute Manager window. The Attribute Manager is used to control the way data points appear in plot windows. It is used to apply colour, shape and size attributes and turn on/off the visibility for different groups of data. We will look at how to create and change attributes in Step 10 of this tutorial.
At the top of the screen are a series of pull-down menus with the Main Toolbar displayed underneath. Many functions are replicated in both the menus and the Main Toolbar and some functions also have keyboard shortcuts, eg. Open File (Ctrl + O). shortcuts are displayed next to the menu items. A status bar is present at the bottom of the screen. Information about objects in plot windows or data warnings are displayed here.
Attribute Map An Attribute Map is a pseudo-map or geographical view of a dataset which plots the X coordinates against the Y coordinates. It is used to view a dataset in a spatial context and is the main plot format for exporting data to Google Earth or GIS programs such as Ar cGIS or MapInfo.
1. Click on the Display Attribute Map
icon on the main toolbar.
When the Attribute Map is open a series of icons is displayed vertically on the right-hand side of the screen. This toolbar is referred to as the Right-Hand Side (RHS) Toolbar and will contain different icons depending on the active plot window. To make the RHS toolbar active simply click in the plot window or on the window titlebar that you want to work with. Place the cursor over each icon to view tooltip descriptions for each icon on the RHS toolbar. To move the Attribute Map window click on the titlebar and drag to a new location while holding down the left-mouse button. Plot and other windows which are opened into ioGAS can be re-sized by placing the cursor over one of the edges of the window and then dragging it in or out. Minimise, Restore and Close buttons are also available in the top right hand corner of each open window.
5.
SELECT VARIABLES
Before any data can be displayed in a plot window (besides an Attribute Map if coordinates are present) the variable columns must be selected for use. The current variable selection is shown in the main window title after the open file name which in this case is empty. Notice that a number of icons are greyed out on the main Toolbar. This indicates that there may not be enough variables selected to be used with that feature. Eg. a ternary plot requires three selected variables before the icon will be active.
1.
To select variables choose Data>Select Variables or click on the Toolbar.
2.
Add the following variables to the Selected Window: Zn_ppm, Ni_ppm, Fe2O3_pct and Cu_ppm. Double-click on each variable to move it across or use the arrows in the middle of the dialog. Multiple selections can be made using the Ctrl/Shift keys.
icon on the Main
Note that the colour of the variable columns match the colours used in the Column Properties dialog. As all the selected variables are green they are numeric columns which have been "aliased" to the standard ioGAS element/unit names. The black variables are text fields and can be selected for use with plots if they will produce meaningful results. Numeric variables which have not been aliased will appear in blue.
Select Variables dialog showing selected variables
The order of the variables in the Selected window can be modified using the Up and Down arrows or by dragging to a new location with the mouse cursor. For some plots such as XY Scatterplots the first variable is used as the X axis when there are multiple variables to be plotted. Ternary plots use only the first three variables in the Selected window so re-ordering is often required to ensure the correct variables are displayed. 2.
Click OK to exit the dialog. The current selection is saved and is available to be selected again from the History drop-down list at the top of the dialog.
See Select Variables in the Help>Help menu for more information.
VALIDATE DATA
6.
1.
Open the Validate menu and have a look at the options available to validate data. These include:
2.
Data Doctor - The Data Doctor tool displays the number of null, 0, -, > and < records for selected variables. It enables the replacement of “-“ and “<” detection limit values with ½ positive value or you can enter a custom value. Replace > values with custom value. Colour attribute any of these samples in open plot windows to see where they are located. Undo button available. All modifications reported in Change Log file. Search and Replace - Replace text or numeric entries in selected columns or entire dataset. All modifications reported in Change Log file. Converting Zeroes to Null (Non-Plot Columns) - Replace zero entries in non-plot or coordinates columns with null values. This is useful when there are 0 values in coordinate columns which plot at 0,0 in map views.
Click on the Data Doctor option.
The Zn_ppm and Cu_ppm contain some below detection limit data. The validation type, the value, the number of samples with this value and the % of valid data this affects is displayed along with a recommended replacement value which in this case is 1 (the half positive value of the below detection limit, ie. -2).
3.
Click in the Replace Value checkbox next to each entry and then click Apply. As the replacements are made the updated Data Doctor reports that there are now no data validation problems with the dataset.
4.
Click on the Show Log button at the bottom. In the Change Log window scroll to the right to view the number of Zn_ppm and Cu_ppm occurrences that have been updated with the replacement values. The Change Log lists all changes to a dataset from when it is first imported into ioGAS including data validation replacements, columns removed and rows deleted.
5.
Select Close to exit this window and then Close to exit the Data Doctor window.
See Data Validation Tools in the Help>Help menu for more information on other menu options
7.
DISPLAY DATA IN TABULAR VIEW
The View Data tools display the dataset in a spreadsheet or tabular view as rows/columns.
1.
Select Data>View Data (All Columns) or click on the icon on the Main Toolbar. This will display all the columns in the dataset regardless of what variables are selected.
2.
Click on the Maximise button in the middle of the buttons in the top right of the Data window to make the window bigger.
3.
Use the scroll-bars to scroll up and down and left and right to get a feel for the columns in the dataset. Note the colour, shape, size and visible columns which are showing the current attributes that are applied to each data row. These are currently set to the default attributes.
4.
Sort a variable column in ascending order by left-mouse clicking once in the column header. Click again in the header to reverse the sort. The [Order] column is automatically generated when the data is imported and can be used to sort the data back to its original import order at any time.
5.
It is possible to click on rows in this view and apply colour/shape/size attributes to the selection using the Apply Attributes to Selection button. This will be covered later in this tutorial. Data can also be copied into other programs using the two Copy buttons at the bottom of the dialog.
6.
Close the Data window using the X in the top right hand corner.
See Display Data in Tabular View in the Help>Help menu for more information.
8.
1.
DISPLAY DATA IN PLOT WINDOW Go back to the Attribute Map that we created earlier. If you need to re-open this plot select the Map>Attribute Map menu option or click on the icon on the Main Toolbar. If the RHS toolbar is not displayed click on the titlebar of this plot window. Maximise the window to make it easier to see.
On the RHS Toolbar there are a number of standard tools available to move about within a plot window and we will have a look at some of these now.
2.
To zoom in on an area click on the icon and drag a box in the window over some data points using the left-mouse button. The window contents are zoomed to the extents of this box.
3.
Click on the view.
4.
Right-mouse click in the window and select Undo Zoom from the pop-up menu. To restore the data to the original extents select Zoom to Data.
5.
You can also use the dynamic Zoom tool to zoom in and out by holding down the leftmouse button in the plot window and then dragging it up to zoom out or down to zoom in. Note that you can also use the scroll bar on the mouse to zoom in and out if available. Restore the plot view when you are finished.
icon and click and drag the left-mouse button in the plot window to pan the
6.
Place the cursor over a data point in the plot window (without clicking) until a tooltip information box is displayed. The information displayed in this box includes the ID, East and North coordinates, any colour/shape/size attribute groups which are assigned and any columns selected to be displayed as labels. Eg. Regolith and Geology units to which the sample belongs.
7.
Select the Data>Select Labels menu option. This is where it is possible to choose which other columns will display in the tooltip information box.
Select the Regolith and Geology columns and a couple of other variables and move them into the Selected window. Click OK. Click back in Attribute Map window to make it active and place the cursor over a sample. The new label columns are displayed. 8.
Close all the plot windows leaving only the Attribute Map window open..
See Display Data in Graph Windows in the Help>Help file for more information.
9.
OPEN MULTIPLE PLOT WINDOWS
Now we will open some other plots which are available in ioGAS and look at some of the different ways in which they can be displayed.
Scatterplots 1.
Select Graph>XY Plots or click on the
icon on the main Toolbar.
See that only three XY plots are created. This is because although we have four variables selected, Zn_ppm, Ni_ppm, Fe2O3_pct and Cu_ppm, the Zn_ppm column is used as the X axis in all three cases and the other variables as the Y axis.
2.
With the XY Plot window as the active window, select the Log X Axis
and Log Y Axis
icons from the RHS toolbar. Clicking on these icons will change the X and Y axes from raw data values to a Log scale.
3.
If you click on each of the or icons the X and Y axes will change to a Power Transformed axis. ioGAS uses a Lambda power transformation method to de-skew data so it more closely approximates a normal distribution. Click on the Power buttons axis icons again to return to the raw data value axes. See Scatterplot toolbar for information on the other features available to display on these plots.
Probability Plots 4.
To create a probability plot for each variable select Graph>Probability Plot or click on the icon on the main Toolbar. This time each variable is displayed in a single plot window. It is possible to zoom, pan and log/power transform the Y axis from the RHS Toolbar.
Use the
icon to display probability values along the X axis instead of N-Score (std dev)
values. Use the to change the distribution to show a cumulative frequency plot. See Probability Plot toolbar for more information. 5.
Select Window>Tabbed Window. A circle is placed next to this menu entry to show this window mode is selected.
Histograms 6.
Select Graph>histograms or click on the icon on the main Toolbar. See that each of the variable histograms is displayed in a separate tab in the same window. If we had not selected Tabbed Windows prior to creating the histograms they would have all been displayed in the same plot window like the probability plots. The histograms show the number of samples in each binning range. Binning ranges can be increased or decreased using the arrows on the RHS Toolbar.
and
7.
We now have four plot windows open but they are most likely all sitting on top of each other. To arrange multiple windows go to the Window menu. Click on the Cascade Windows option to view all the windows with their titlebars visible. Then select the Window>Tile Windows option to view all the plot windows without overlapping.
8.
Select Windows>Normal Windows again to return to the default window display. Note that this is applied to all windows opened from now on, not those already opened.
See Display Data in Graph Windows and Available Plots in the Help>Help file for more information.
10.
APPLY COLOUR/SHAPE/SIZE ATTRIBUTES
Now that we have some plot windows created we will look at how to change the colour, shape and size attributes for individual data points, apply them to data selections and turn the visibility of data points on and off. This is all controlled by the Attribute Manager.
Auto-Attribute Text Data Auto-Attributing is used to apply attributes to data based on unique values in a text column or data percentiles/custom ranges for numeric columns. 1.
To display the Attribute Manager select Graph>Display Attribute Manager or click on the icon. You can also use Ctrl-A as a keyboard shortcut to open the Attribute Manager window. This window can be dragged outside of the application if you are running dual screens to save you having to open it up all the time. Alternatively, select Window>External Windows Always on Top to keep the Attribute Manger window displayed on top of other plot windows instead of minimising.
The Attribute Manager contains three tabs, one each for colour, shape and size. 2.
Leave Regolith Unit as the selected column and click on the Auto-Attribute button. This will colour the data points according to which regolith unit they are assigned. The Attribute Manager also lists the number of data points in each colour category.
Note that the data is coloured by Regolith Unit in every plot window.
3.
Click on the Shape tab this time. Select Geology from the column pull-down list. Click on the Auto-Attribute button. The data points are now coloured by regolith unit and their shape represents the underlying geological unit.
Show Legend 4.
Click on the Legend icon on the main toolbar to open up a separate legend window. To view the attributes in a combined legend, right-mouse click within the legend window and choose the combined option.
Change Visibility Back in the Attribute Manager, if we want to sub-set our data so that we are only looking at data points from particular regolith units we can turn off the visibility for those groups we do not want to see.
5.
Uncheck the box in the Visible column next to the D9 and DA regolith groups in the Colour tab. Observe how the data points are removed from all open plot windows.
6.
Check the boxes to re-display the samples or click on the All Visible button at the bottom of the Attribute Manager.
Auto-Attribute Numeric Data 7. While still in the Colour Tab select a numeric variable column such as Cu_ppm from the column pull-down list. For numeric data columns, data points are attributed according to a selected percentile binning range, eg. 5 or 10 equal r anges, Quartile, Progressive, etc and then coloured using one of the supplied colour ramps. Use the small black arrows next to the colour ramp and the Binning Ranges to view the available options. 8.
Leave the default colour ramp and select Progressive from the binning range pull-down list. The Progressive binning range divides the data into percentiles based on 30, 60, 80, 90, 95 and 98% cut-offs. Click Auto-Attribute to apply the colours and overwrite the existing ones.
9.
Observe how the values are updated i n the legend.
10. Experiment with Auto-Attributing data using different text columns and numeric columns with different colour ramp/binning combinations.
11. To change the assigned colour/shape/size of an attribute double-click on the attribute (eg. red circle, square, etc) and select a different one from the colour palette or drop down list (for shape/size). It is also possible to change the name of an attribute by double-clicking in the Name column and overwriting the entry with a new one.
12. Highlight the PEw entry in the Shape Tab. To remove this entry from the list use the button. All of the PEw samples now show the Default Shape. To remove all the Shape attribute entries click on the
button.
13. To remove all the currently applied colour/shape and size attributes click on the button. It is possible to attribute data by applying the same variable to the colour, shape and size attribute tab or apply three different variables. It is also possible to create custom bin ranges rather than percentiles which can be applied to different datasets. See Create and Edit Bin Ranges for more information on how to do this. See Attribute Data using Colour, Shape, Size and visibility in the Help>Help menu for more information.
11.
MAKE DATA SELECTIONS
The Attribute Manager can also be used to assign colours, symbols or different sizes to manually selected data points in a plot window. 1.
Remove all existing attributes using the Global button in the Attribute Manager.
2.
Select the Colour tab and click on the Add an Attribute Colour row is added under the default colour row and is coloured red.
3.
Double-click on the New Colour entry to assign a name for the attribute ( ie. High Cu) and then click Enter. Click on the red colour circle to select a different colour if desired. Make sure that the High Cu row is highlighted (in blue) and that it is also displayed in the Attribute Manager titlebar.
4.
Select the Shape tab and click on the Add an Attribute button three times. See how each new row has a different shape in it. Click on the Triangle row so it is highlighted in blue. Repeat this process in the Size tab and click on the 10 row.
5.
The shape and size attributes should display in the title bar as "New Shape" and "New Size" when they are highlighted correctly.
6.
Click in the Probability Plot window created in Step 9. Otherwise click on the Probability Plot icon on the main toolbar again if the plot window has been closed. Re-size this window to make it bigger and make sure the Probability Plot RHS Toolbar is visible by clicking in the plot window.
7.
Select the Attribute Polygon
icon from the right-hand side toolbar.
button. A New
8.
In the Cu_ppm probability plot window hold down the left mouse button and click around the high values in the plot window to create a polygon (region) object. Double-click to finish. All of the data points within the polygon should be attributed with a red triangle 10 pt in size.
9.
Select Windows>Tile Windows again to view all the open plot windows. Note that the selected points are attributed in the other plot windows and if you open up the legend window it has also been updated.
10. Leave the High Cu samples attributed and repeat the process outlined in steps 2-8 to make another selection on the probability plot using a blue square 10 pt combination. Make sure that blue colour, square shape and Size 10 pt attributes are highlighted in their respective tabs and displayed in the Attribute Manager titlebar prior to making the data selection. 11. This time, zoom in on the probability plot and select individual points to attribute using the
Attribute Point
icon.
12. Use Data>View Data (All Columns) or click on the icon on the main toolbar to open a tabular view of the data and note the colour, shape and size attributes have been updated next to each row. To see this more easily left-mouse click in the [Colour] column header cell twice to display the data in descending order based on colour. 13. To save a selection as a new column use one of the options from the Data menu such as Make Variable from Colour. 14. Open the Attribute Manager again if it has closed and remove all attributes using the Global button and experiment with creating different colour, shape and size attribute combinations and applying them to data selections. Note that the selections can be made in any plot window (apart from certain plot types eg. Box Plots). 15. Close all plots at the completion of this exercise using Windows>Close All Windows.
See Make Selections and Apply Attributes (under the Attribute Data using ..... section) in the Help>Help menu for more information.
12.
UNIVARIATE STATISTICS
Summary Statistics When analysing data it is useful to look at various statistical parameters for either the entire dataset or for selected categories within a dataset. The selected categories are based on the colour groups as set in the Attribute Manager.
1.
Open up an Attribute Map ( Graph>Attribute Map) or click on the
2.
Open the Attribute Manager using Ctrl-A and colour Auto-Attribute the data using the Regolith unit column.
3.
Select Analysis>Display Summary Statistics or click on the
icon.
icon on the main toolbar.
In the Summary Statistics window all of the selected variables are displayed along with a number of basic statistics for each regolith group. The values in each group are also coloured according the colours in the Attribute Manager. The values at the top in black are the calculated statistics for all the entries in the dataset.
4.
To change the displayed statistics click on the icon on the RHS Toolbar. Check or uncheck the statistics as required and click Apply to update.
5.
Click on the Change Grouping rather than by group.
6.
Close the Statistics window and the Choose Statistics dialog using the X in the top left hand corner when complete.
icon on the RHS Toolbar to group the data by statistic
Frequency Table
View all the unique value for each selected variable and the counts for each in a Frequency Table. 1.
Select Analysis>Display Frequency Table .
Each variable is displayed in a separate tab.
Correlation Matrix
Display the correlation coefficient values for each paired combination of selected variables. 1.
Select Analysis>Display Correlation Matrix.
See Analysis Menu Tools in the Help>Help menu for more information.
13.
RANKED VARIABLE MAP AND GRIDDED IMAGES
Ranked Variable Maps A Ranked Variable Map displays each of the selected variables in a separate map view. The data points in each map are ranked and then displayed using one of the pre-defined colour and size ramping options. Ranked variable maps are good for comparing high or low concentrations across multiple elements. 1.
Select Window>Normal Window menu option if it is not already selected.
2.
Select Map>Ranked Variable Maps or click on the
3.
To view what data values correspond to each colour and sizes represent click on the
Show/Hide Colour Bar Legend
icon.
icon on the RHS toolbar.
4.
To modify the thematic settings click on the icon on the RHS (Right-Hand Side) Toolbar. Select from a number of different Colour and Size ramps and observe how the data appearance changes. To see what type of size ramp is being applied place the cursor over the entry in the pull-down list. Repeat for the colour ramps
5.
Ranked variable maps can be exported and viewed in Google Earth.
See Available Plot Types (Ranked Variable Maps) in the Help>Help menu for more information.
Gridded Images A gridded image is created from the interpolation of located data onto a regular grid or matrix which is then rendered so that it can be viewed as a continuous coloured or shaded surface image. ioGAS includes a gridding tool that uses a modified Inverse Distance Weighting algorithm to generate the grid cell values.
1.
Select Map>Gridding or click on the
2.
The Make Grids dialog is displayed.
icon.
ioGAS attempts to automatically select the appropriate gridding settings for the dataset based on an algorithm that analyses the spatial structure of the data. Parameters such as grid cell size, search radius, smoothing, etc can be customised. 3.
Leave the default settings and click OK. The grids are displayed in a single plot window.
4.
To view what grid cell values the colours represent click on the Show/Hide Grid Legend icon on the RHS toolbar.
The gridded images can be exported using the GeoTiff and ER Mapper Grid export options on the RHS Toolbar.
See Gridded Images in the Help>Help file for more information.
14.
DISPLAY DATA IN CLASSIFICATION DIAGRAM
ioGAS contains a number of standard classification diagrams arranged into a logical menu system. Data can be plotted on classification diagrams and then attributed according to the classification group in which they are located. These attributes can be written back to the file and then exported for use in 3rd party programs. In order to view data on a supplied classification diagram the variable columns must be "aliased" in the Column Properties dialog as outlined in Step 4. This is so ioGAS can perform any element/oxide/unit conversions to get the data into the correct format to display on the diagram. In this exercise we will display the demonstration dataset on a Regolith diagram which plots K/Al vs Mg/Al wt values to classify regolith data into transported clays, saprolite and younger alluvium/coluvium. 1.
Select Diagram>Provided>Regolith>Fractionation (McQueen, 2006)
2.
The data is plotted with the current attributes onto the diagram in a new plot window. The diagram window contains zooming, panning and selection tools the same as we have observed in other plots. If you zoom out you can see that not all the data plots within the diagram extents.
3.
Right-mouse click and select Zoom to Diagram from the pop-up menu to return to the original diagram view.
4.
To attribute the data points with the regolith classification group colours select the Colour
Rows from Polygon icon colour attributes.
on the RHS Toolbar and select "YES" to overwrite existing
5.
To make a new variable column which contains the regolith classification group for each row select Data>Make Variable from Colour menu option.
6.
Accept the default new column name and when the column is created open up a tabular view of the data ( View Data added columns.
icon on the main Toolbar) and scroll to the right to see the newly
One is a text column with the rock classification, the other is a numeric column which each rock classification assigned a different number. Note that data outside of the diagram is assigned Default Colour and a numeric value of 0. All other samples are assigned their regolith classification group.
It is possible to make and edit your own classification diagrams and share them with others within your organisation.
See Classification Diagrams in the Help>Help file for more information.
15.
ADDITIONAL FEATURES
Some additional features which are not covered in this Quick Start Guide are:
Additional Plots Experiment with other plots available in ioGAS including Scatterplot Matrix (SPLOM), 3D Plot, Spatial 3D Plots for drillhole data, Line Plot, Parallel Coordinate Plots, Spider Plots, Box Plots and Pie Charts. See Available Plot Types in the Help>Help file for more information.
Display Mineral and Rock Nodes:
Display Mineral Composition Nodes on selected plots such as XY scatterplots and tri-plots x using the icon.
icon on the RHS toolbar. To change the mineral nodes displayed use the
See Display Mineral and Rock Nodes in the Help>Help file for more information.
Generate Point Density Grids
Display Point Density Grid on selected plots using the icon on the RHS toolbar. Point density grids help to focus on ar eas where the bulk of the data are located. To change the grid options use the
icon.
See Display Point Density Grid in the Help>Help file for more information.
Calculations Menu
Create your own Calculated columns or select from one of the Quick Calculation options: log 10, z-Score and mean/median transformations and molar calculations. Otherwise use a calculation from the Provided library.
See Perform Calculations in the Help>Help file for more information.
Multivariate Outlier Detection (Including Robust) ioGAS provides standard versions of Principal Components Analysis. Save PCA score calculation parameters so that PCA results can be applied to other datasets. Use Mahalanobis Distance calculations with multivariate data to determine how atypical a sample is taking into account correlations between variables. ioGAS also supports "robust" versions of these statistical measures which minimise the impact of outliers, thereby enhancing the method’s ability to detect anomalies. The calculated data may be used to create plots, maps and images. See Analysis Menu Tools in the Help>Help file for more information.
RGB Zonation and Tukey Outlier Attribution Automatically make thematic maps that identify outliers using Tukey algorithm. Use red/green/blue colour addition to determine spatial relationships between three variables simultaneously to seek zonation patterns. See Analysis Menu Tools in the Help>Help file for more information.
Regression Analysis
Determine linear equation(s) that model the relationship between a response variable and one or more explanatory variables variables. The tool allows both simple and multiple linear regressions to be determined and also provides an option to perform a least median squares (LMS) robust analysis which determines regression equations while down-weighting outlying data points. Ability to perform Log/Power (Box Cox) transformation and regression by colour group. Create Predicted and Residual columns along with regression line diagrams and probability plots. Automated outlier analysis and thematic map creation. See Analysis Menu Tools in the Help>Help file for more information.
Generate Classification Diagrams Create and save your own Classification Diagrams and share them with other users.
See the Create, Save and Edit Diagrams step-by-step guide in the Help>Help file for more information.
16.
COPY, SAVE AND PRINT OPTIONS
Save ioGAS File 1.
Select File>Save or click on the
icon.
The Save option saves both the current data and the attribute information as a native ioGAS file. Any open plot windows are also saved and will be re-opened when the file is next loaded. To re-open a native ioGAS file use the File>Open menu option.
Save As ioGAS File To save a copy of an ioGAS file select File>Save As and choose ioGAS File from the Files of Type pulldown list. NOTE: The Demo file is Read-Only so cannot be saved with new changes. To make an editable copy of this data use File>Save As and save using a new name.
Copy Window as Image This option creates a bitmap image of the active window and copies it to the clipboard.
1.
Select Edit>Copy or click on the
2.
Paste into 3rd party program such as Word, Powerpoint or image processing package using "Paste" or Ctrl-V.
icon on the main toolbar.
Selected plots, eg. Scatterplots, scatterplot matrix, ranked variable maps and line plots have a copy button on the RHS toolbar which will copy the window at high resolution for large scale plotting, eg. at A1 or A0 size.
Copy Graph as Image or Vector File 1.
Right-mouse click in the graph window and select from one of the following Copy options. The Bitmap copy has a number of screen resolutions. The larger the resolution the larger the resulting image which is created.
2.
Paste into 3rd party program such as Word, Powerpoint or image processing package using "Paste" or Ctrl-V.
It is also possible to copy windows in EMF (Enhanced Metafile format) and EPS (Encapsulated Post Script format). These are both vector based file formats which enable the image to be re-sized while retaining resolution and editing of the individual map components in other programs such as Corel Draw, Paint Shop, Powerpoint and Word.
Save Graph as Vector File 1.
Right-mouse click in the graph window and select from one of the following Save options.
2.
Enter a name and location for the saved file.
The EPS (Encapsulated Post Script), EMF (Enhanced Metafile) and SVG (Scalable Vector Graphics) are all vector based file formats which enable the image to be re-sized while retaining resolution and editing of the individual map components in other programs such as Corel Draw, Paint Shop, Powerpoint and Word.
Print Graph To print an individual graph directly from a plot window right-mouse click and select Print from the pop-up menu.
See Save, Export, Copy and Print in the Help>Help file for more information.
EXPORT AND GIS OPTIONS
17.
Export Data 1.
Select File>Export (All Rows) or File>Export (Visible Rows) ioGAS can export data in the following formats:
Excel Spreadsheet File
CSV Text File
Tab Separated Text File
GML (Geography Markup Language) File
Google Earth KMZ File (as Attribute Map)
ESRI Layer File (with File Geodatabase)*
All Rows will export all the rows in the dataset whereas Visible Rows will only export data that is set as visible in the Attribute Manager. The Visible Row export option is good to use when you need to sub-set data into a separate file. The File>Export Selected Columns menu option will export only the columns flagged as special in the Column Properties dialog plus the columns selected in the Select Variables dialog. Options to export all rows and visible rows are also available. *This export is only available under the File>Export Selected Columns menu option.
Export to Google Earth 1.
Select Map>Export to Google Earth or click on the Variable Map RHS (Right-Hand Side) Toolbar.
icon on the Attribute Map or Ranked
To export into Google Earth the dataset must contain coordinates for each data point in Lat/Long WGS84 projection and these columns must be selected as the 'WGS84 Longitude' and 'WGS84 Latitude' columns in the Column Properties dialog (see Step 3). When the Attribute Map is exported to Google Earth, the shape, colour and size attributes will be rendered correctly. Ranked Variable Maps can also be exported into Google Earth, and like in ioGAS the colour and size are in proportion to the rank.
Google Earth KMZ Export Showing Data Points and Attributes
Export to ArcGIS This option will save an Attribute Map including any colour, shape, size and visibility attributes and export them to an ESRI geodatabase with an associated Layer file. The Export to ArcGIS utility can only be run using the ioGAS 32-bit version with at least ArcGIS version 10, SP 2 installed. 1.
In the Column Properties dialog make sure that the East/North Projection is selected to match the coordinates in the selected East and North columns. If a non-earth projection is selected the data can still be opened in ArcGIS but not overlain with other projected datasets.
2.
Display an Attribute Map as the active window and set the colour, shape, size and visibility as desired.
3.
Select Map>Export to ArcGIS or click on the Hand Side) Toolbar.
4.
Assign a name and location for the Geodatabase and layer file and click Export.
5.
Open ArcGIS and click on Add Data. Browse to the geodatabase and open.
icon on the Attribute Map RHS (Right-
See Save, Export, Copy and Print in the Help>Help file for more information.
Import into MapInfo The ioGAS File Import Tool is developed by Encom Technology (Pitney Bowes) in consultation with ioAnalytics. The ioGAS File Import Tool is available to users who are running the Discover add-on module for MapInfo Professional®. This tool enables users to import ".GAS" files and attributes directly into MapInfo and save as a series of *.TAB files. The main imported data table contains the sample locations plotted in geographical space which are displayed using the saved attribute symbology. Each attribute style also has an associated legend table. See Connect to Other Applications in the Help>Help menu for more information.
