TSTool_UserManual_10-21-00 - Laserfiche WebLink

TSView Time Series Viewing Tools Appendix - TSView - 2 Overview The TSView package contains integrated software components that can be used with software applications to enable time series viewing capabilities. The main purpose of the TSView package is to provide sim ple, consistent, and flexible displays that can be used in a variety of applications with little or no reconfiguration. TSView also provides features to configure and process time series products (e.g., graphs), where the time series data are stored separ ately from the configuration information. The TSView package has been developed by Riverside Technology, inc., using Java technology. TSView interfaces can be embedded in Java applications and can be used in web pages either as embedded applets or stand -alone windows. TSView tools operate similarly on Microsoft Windows and UNIX operating systems. This appendix describes general TSView features and can be used as a reference for how to configure and use TSView components. Software program documentation may include specific information about using TSView features. Time Series Terminology The TSView package treats time series as objects that can be read, manipulated, and output in various formats. A time series is defined as having header information (a ttributes) and data, which usually consists of a series of date/time versus data pairs. Internally, time series are considered to have either regular interval (equal spacing of date/time) or irregular interval (e.g., occasional observations). Regular tim e series lend themselves to simpler storage and faster processing because date/time information can be stored only for the endpoints. The following basic attributes are stored for each time series: • Data interval as an interval base (e.g., Month , Hour ) a nd multiplier (e.g., 1 for month, or 24 for hour) - in many cases, the multiplier is 1 and is not shown in output (e.g., Month rather than 1Month ), • Data type (e.g., Streamflow ), which ideally can be checked to determine if a time series contains mean, inst antaneous, or accumulated values, • Units (e.g., CFS ), which ideally can be used to make units conversions and look up precision for output, • Period of record, using dates that are of an appropriate precision for the interval, • Data limits (the maximum, minimu m, etc.), • Description (generally a station, structure, or sensor name), • Missing data value (used internally to mark missing data and trigger data filling, often -999 ), • Comments (often station comments, if available), • Genesis history (a list of comments abo ut how the time series was created). In order to uniquely and consistently identify time series, a multi -part time series identifier is employed, having the following parts: • Location (or location -sublocation) • Data source • Data type (or datatype -subdatatyp e) • Data interval (time step) • Scenario 156