Time Series Analysis Demo The data shown in this demonstration is from feeder circuits at a large power generation station. The data was collected from many circuits, every half-hour for a period exceeding one year. To display the data, first select a circuit by clicking on the corresponding button. Once a circuit has been selected, you may, if desired, select a specific month and/or day to subset the data. NOTE: You will need to select a month before you can select a particular day, and you must select a circuit before you can select a month, since not all circuits have readings for the same dates. Once the circuit has been selected, and any desired subset has been chosen, you can view the data. When viewed, the data will be processed by the selected process. This demo allows you to view the data using three different methods: 1. CHART The selected data is displayed as a line graph. If the process is "None" then the line color will be yellow, and you will be allowed to click on the graph. The closest data point will be found, and the date, time, and data value of that point will be displayed. If the process type is "Least Absolute Deviation", Then the original data is plotted with red markers, and the data trend is displayed as a green line. The calculations are performed by IDL's "LADFIT" function. If the process type is "Autoregressive Forecast", then the original data is displayed as a red line, and the forecast data as a dotted green line. The forecast calculations are performed by IDL's "TS_FCAST" function. If a particular day is selected, and one of the 24-hour processes is chosen, then the result of the process is a single value, which is displayed in a status window rather than as a graph. 2. IMAGE The day must be set to "All" to display an image. Also, the process type must not be set to "Least Absolute Deviation". The selected data is displayed as an image with the day of the year (or month) on the X axis, and the time of day on the Y axis. This is performed by IDL's "REFORM" function, which changes the data from a one- dimensional array of N elements to a two-dimensional array of dimensions M by 48, where M = N / 48. Note that there are 48 samples taken during each day (every half-hour). The "Autoregressive Forecast" process will display only the forecast data as an image. Once the image is displayed, you may drag the cursor over the image data, and this will cause dynamic profiles of the data to be displayed as graphs. The data value under the cursor will be displayed in the status area in the lower left corner of the image window. 3. SURFACE The process type must be set to "None" to display a surface. Also, the month must be set to "All". This method allows you to compare multiple data sets by using one set of data as the surface elevation, and a different set of data for the surface shading.