sift:sift_query_overview
Differences
This shows you the differences between two versions of the page.
| Both sides previous revisionPrevious revisionNext revision | Previous revision | ||
| sift:sift_query_overview [2026/03/24 19:02] – removed - external edit (Unknown date) 127.0.0.1 | sift:sift_query_overview [2026/08/11 14:47] (current) – [Query Overview] julia | ||
|---|---|---|---|
| Line 1: | Line 1: | ||
| + | ====== Query Overview ====== | ||
| + | Data exploration in SIFT begins with queries, the mechanism for defining which data to analyze and how to structure it for comparison. Typically, queries sit in the following order of operations: | ||
| + | Library → Query → Groups (which can contain multiple conditions) → Analysis | ||
| + | |||
| + | ===== Groups ===== | ||
| + | Querying data creates groups. Groups | ||
| + | |||
| + | ===== Conditions ===== | ||
| + | Within a group, multiple conditions allow you to specify distinct requirements for different traces while maintaining their relationship. Conditions define the different rules traces can meet to be part of the same group. | ||
| + | |||
| + | ===== Building Effective Queries ===== | ||
| + | Query design should reflect your analytical intent. Traces you plan to compare or analyze together belong in the same group. Traces representing different experimental conditions should be separated into distinct groups to enable meaningful comparison. | ||
| + | |||
| + | ===== Working with Queries ===== | ||
| + | ==== Autopopulate Queries ==== | ||
| + | Sift can generate queries automatically based on signals present in your library / the underlying CMZ. This approach surfaces all available data within a specified scope, making it well-suited for open-ended exploration when your direction is still taking shape. | ||
| + | |||
| + | **When to use**: Use ' | ||
| + | |||
| + | Learn More: [[sift: | ||
| + | |||
| + | Tutorial: See the [[sift: | ||
| + | |||
| + | ==== Custom Queries ==== | ||
| + | Sift lets you build precise queries tailored to your specific requirements. Custom queries support replication of previous analyses and enable advanced refinements including time-normalization to event sequences and filtering based on signal characteristics. | ||
| + | |||
| + | **When to use**: Use Custom Queries when the signals of interest are known in advance, when a previous analysis needs to be replicated, or when precise control over time-normalization or signal filtering is required. Query definitions can be saved as .q3d files for reuse across sessions. | ||
| + | |||
| + | Learn More: [[sift: | ||
| + | |||
| + | Tutorial: See the [[sift: | ||
| + | ===== Example ===== | ||
| + | In gait analysis, comparing knee joint angles across three walking speeds (SLOW, MEDIUM, FAST) might use three separate groups (one per speed condition). Each group would contain two conditions: left knee angle time-normalized from left heel strike (LHS)-LHS and right knee angle from right heel strike (RHS)-RHS, both refined by the appropriate speed tag. This structure enables direct comparison across speed conditions while properly handling bilateral symmetry within each condition. | ||
| + | |||
| + | {{: | ||
| + | |||
| + | Once queried your new groups will appear within the data tree on the Explore and Analyse pages like so: | ||
| + | |||
| + | {{: | ||
| + | ===== Tutorials ===== | ||
| + | [[sift: | ||
| + | * Practical applications of query refinement | ||
| + | |||
| + | [[sift: | ||
| + | * Build Necessary Queries for Normal Database | ||
| + | * Build ' | ||
