Select Similar

Historical Context & Motivation

As computer-aided design matured from simple 2D line-drawing tools into complex platforms managing thousands of objects across dozens of layers, the need for intelligent selection mechanisms became critical. Early AutoCAD releases required users to manually click individual objects or define cumbersome rectangular and crossing windows to build selection sets, an approach that scaled poorly as drawings grew more complex. The Select Similar command emerged as part of Autodesk's broader strategy to introduce property-aware, context-sensitive selection tools that mirror the kind of query-based filtering familiar to computer scientists working with databases and structured data. Rather than selecting by geometry alone, Select Similar lets users specify an exemplar object and then gather all objects in the drawing that match a configurable set of properties—layer, color, linetype, object type, block name, and more.

The core question Select Similar addresses is fundamentally one of set-based retrieval: given an exemplar entity with a vector of properties, how do we efficiently identify all entities in the drawing database that match on a user-specified subset of those properties? This is analogous to a parameterized SQL WHERE clause running against AutoCAD's internal entity table, and understanding it in those terms will make the command's configuration options immediately intuitive.

Core Principles & Definitions

Select Similar operates on a straightforward but powerful paradigm: the user designates one or more seed objects, and AutoCAD queries its drawing database for all entities whose properties match the seed objects on every dimension enabled in the current SELECTSIMILARMODE bitmask. The result is a selection set containing every matching entity, ready for batch operations such as layer reassignment, property changes, deletion, or move/copy transformations. Understanding the following foundational ideas is essential before exploring the command's configuration.

Visual Explanation — Select Similar Workflow

The diagram above illustrates the critical distinction: Select Similar is not a geometric proximity query—it is a property-predicate filter that operates over the entire drawing database (or the current layout/model space). The seed object's properties are extracted and compared against every other entity of the same type in the drawing. The SELECTSIMILARMODE bitmask determines exactly which properties must match, giving users fine-grained control over selectivity. In algorithmic terms, this is a linear scan with a constant-time per-entity comparison whose cost is bounded by the total entity count in the drawing, making it O(n) where n is the number of entities sharing the seed's object type.

The SELECTSIMILARMODE Bitmask — How It Works

The behavior of Select Similar is entirely governed by the system variable SELECTSIMILARMODE, an integer whose binary representation encodes which property dimensions participate in the filter. Each bit position corresponds to a specific property, and because the bits are independent, multiple properties can be combined by summing their individual bit values—exactly the same way Unix file permissions use octal flags. The bitmask approach is space-efficient (a single 32-bit integer encodes all possible combinations) and computationally cheap (property matching reduces to bitwise AND operations against each entity's property vector).

Property Dimensions & Classification of Match Types

Not all property dimensions are equally useful in every drawing context. Understanding which dimensions to enable—and why—requires classifying properties by their semantic role in a drawing's organizational hierarchy. We can group the eight property dimensions into three functional categories: organizational properties (Layer, Name) that control logical grouping, visual properties (Color, Linetype, Lineweight, Linetype Scale) that control appearance, and output properties (Plot Style, Object Style) that control how entities render in print or display contexts. Choosing the right combination determines whether your selection set is too broad (capturing unintended entities) or too narrow (missing desired ones).

When setting SELECTSIMILARMODE, think carefully about the granularity you need. A value of 1 (Layer only) is broad—it captures every entity of the same type on a given layer regardless of visual attributes. A value of 7 (Layer + Color + Linetype) is much more restrictive, useful when your drawing uses per-entity overrides rather than ByLayer assignments. The maximum possible value, 255 (all bits set), enforces exact property matching across every dimension, effectively finding only near-duplicates of the seed entity. In practice, most professionals work with values between 1 and 131, depending on whether their CAD standards are layer-centric or property-centric.

Worked Example — Reassigning Block References to a New Layer

Consider a floor plan drawing containing 47 door block references (INSERT entities with block name "Door-Single-36") scattered across three layers: "A-Door", "0", and "Misc". Your task is to move all of them to the correct layer "A-Door" using Select Similar. This mirrors a common standards-compliance cleanup scenario in architectural CAD workflows.

Select Similar vs. Alternative Selection Methods

AutoCAD provides several mechanisms for building selection sets, each optimized for different use cases. Select Similar occupies a unique niche as a fast, exemplar-based selection tool that requires minimal user input, but understanding its trade-offs relative to other approaches is essential for choosing the right tool in any given scenario.

Connection to Scripting, LISP, and Advanced Workflows

For computer science students, the real power of Select Similar becomes apparent when it is integrated into automated workflows via AutoLISP, .NET (C#), or Python (via pyautocad). The SELECTSIMILAR command itself can be invoked programmatically, and the SELECTSIMILARMODE variable can be set dynamically before execution, enabling scripts that perform context-aware batch operations across large drawing sets. Understanding how Select Similar relates to its more programmatic counterparts is essential for building scalable CAD automation pipelines.

As you progress into CAD automation and BIM integration, Select Similar serves as a conceptual stepping stone toward more powerful selection paradigms. In environments like Revit (which uses element-level filtering with parameter queries) or industry data standards like IFC (where entities carry rich semantic metadata), the same exemplar-based selection philosophy appears in more sophisticated forms. Mastering Select Similar now builds the mental model for understanding property-driven selection and filtering in any data-rich design environment.

Practice Problems

Select Similar — Summary