Index-label dot syntax

2026-06-25T22:03:00Z

Mhenrion: THis page was redundant with the redirect page -- so I replaced it with the redirect.

#REDIRECT [[Index labels auto updates]]

Index labels auto updates

2026-06-25T21:57:19Z

Mhenrion:

''New to [[Analytica 7.0]]''

When you rename an identifier Analytica automatically updates expressions using that identifier. And when you change labels in an Index, it automatically updates edit tables using that index (what we call [[Table Splicing]]). But prior to release 7.0, there was one annoying exception. When you change a label in an index, it wouldn't update expressions using that label.
For example. suppose
Index Power_type := ['solar', 'wind', 'gas', 'nuclear']
If you edited <code>Power_type</code> to change <code>'solar'</code> to <code>'PV'</code> , it would break this expression:
Capacity[Power_type = 'solar']
But now, it automatically updates it to:
Capacity[Power_type = 'PV']
It sees that <code>'solar'</code> is an element of Index <code>Power_type</code> and when you change it to <code>'PV'</code> it so update the expression automatically. It can similarly detect and update equality and inequality comparisons and other expressions mentioning the Index and label, including
[[Choice]], [[Multichoice]], [[PositionInIndex]], [[SubIndex]], and <code>@[ Power_type = 'solar']</code>).

== Index-dot-label syntax ==

However, there are some expressions where Analytica can't fix it because it can't figure out that the label is associated with the index. For example:
Index Renewable_power_types := ['solar', 'wind'];
Capacity[Power_type =Renewable_power_types ]
You can make sure that the index values are associated with their index using the <index>.<label> syntax, for example:
Index Renewable_power_types := [Power_type .'solar', Power_type .'wind'];

In this case, any change to elements of Power_type will update the corresponding text values wherever they occur associated with the Index. This dot expression also checks that the label is a valid value of the Index and gives a warning if not.

This syntax provides two advantages:
# It tells Analytica that the text literal is the value in the index. If you later change the label in the index. Analytica will automatically rewrite this expression, replacing it with the new value. Hence, it makes the model robust to changes in index labels.
# During evaluation, it checks that <code>"label"</code> is indeed an element of the index. If not, it issues an evaluation-time warning. If you ignore the warning, the value is <code>"label"</code>.

=== Domain attribute to check text values ===

You can also make use of the [[Domain]] attribute to also help Analytica spot cases where text literals should be associated with an index value. For example, suppose in another variable you have an edit table like:

Variable Power_plant_type ::= [[Table]]( Power_plant )( 'gas', 'hydro', 'gas', 'solar' ....)

Each cell of the table contains a text entry. By itself there is no intrinsic association of these cell values to the index values of <code>Power_type</code>. The overlap may just be coincidence; hence, if you change a label in the <code>Power_type</code> index, Analytica won't rewrite these table cells. If they were indeed meant to refer to the labels of <code>Power_type</code>, that change could introduce a logical error into your model. You may also be faced with a time-consuming task of updating all the cells of the table.

In an example like this, you can use the [[Domain]] attribute to establish the association so that Analytica knows that the text values in this table are supposed to be the same text used in <code>Power_type</code>'s index labels. You should set the domain type to be "Copy from index", and select <code>Power_type</code> as the index. With that configuration, if you now rename a label in <code>Power_type</code>, it will automatically rewrite the corresponding cells of the table.

== See also ==
* [[Index-label dot syntax]]

Mhenrion: /* Python integration */

[[category:What's new pages]]
[[category:Analytica releases]]

[[Analytica 7.0]] will be the next major Analytica release and is currently in [[Beta Tester Page|beta testing]]. Go to [[Beta Tester Page]] to try it. The current official release is [[Analytica 6.6]].

==Highlights of Analytica 7.0==

* '''Python integration:''' The major enhancement is integration with Python and hence the entire Python ecosystem of libraries. You can easily call functions from Python libraries, access Python variables, and even write Python code right inside Analytica variables and functions. So now you can mix and match Analytica and Python according to which language you think best for your modeling or coding needs.
* '''Index label updating:''' A common source of errors has been when you change a text label in an Index without remembering to change expressions that refer to that same text label. [[# Index label auto updates|New features]] now automatically update these labels, and so eliminate most of those errors.
* '''Enterprise renamed Developer edition:''' The Analytica Enterprise edition has been renamed the [[#Developer Edition (formerly known as Enterprise) |Developer edition]], which better reflects what it is.
* It introduces two new object Classes:
** [[Struct]] lets you bundle disparate values, like text, numbeers, atoms and arrays, together in one object that does not array abstract -- similar to Records and Classes in other languages).
** [[Callable]] is like a user-defined Function but it's Definition can be a [[handle]] to a Python class or a Python function.
* [[ParseJSON]] and [[MakeJSON]] now use Structs, which are much more convenient for representing the hierarchical structure of JSON.
* [[#SpreadsheetOpen|Read and write spreadsheets without Excel]]: This is faster and more robust, and you don't need Excel installed.

== [[Using Python from Analytica|Python integration]] ==

You can now write Python code inside Analytica definitions! It's easy to call Python functions, with Analytica-style Intelligent Arrays!. So you can access the vast ecosystem of Python libraries (''modules'' in Python lingo). Among the gazillion possibilities are specialized libraries for data visualization, statistics, machine learning, and much more.
It means that you can mix and match Analytica and Python -- write Analytica code for what's easiest in Analytica and Python code for what's easiest in Python.

See: [[Using Python from Analytica]]
(In [[Analytica Developer]] edition or better).

For the Analytica modeler, this puts a ton of resources at your fingertips.

It's also pretty cool for the Python developer. Analytica is like a new interactive development environment with a lot of unique advantages, especially during interactive code development:
* Analytica's dependency maintenance can be really convenient during interactive development, creating automatic dependency maintenance between your Python functions, classes and variables that don't exist in Python.
* The visual influence diagram layout can be a super useful to way organize and visualize your code.
* It naturally encourages declarative code practices, which leads to better and more maintainable coding style.
* You get the benefits of Analytica's edit tables, plus for results, Analytica's multi-D result tables and one-click, no-code, graphing.
* It is easy to wrap existing Python models to get Monte Carlo, parametric analysis and sensitivity analysis with Analytica ease.
* Sometimes one or the other language is more convenient for a particular task. You can freely switch between whichever language feels better suited to the immediate task, and intermix languages easily.

== Developer Edition (formerly known as Enterprise) ==

Analytica's middle-tier edition formerly known as the ''Enterprise Edition'', it is now called the [[Analytica Developer|Analytica Developer edition]]. That name better reflects what it is--software for developers of decision applications. If you're now a user of Analytica Enterprise you don't have to update your license or do anything special. The name will just change when you install Analytica 7.0. In Analytica docs, when you select "7.0" on the release bar (at the top of pages that have release-contingent content), all the docs automatically use the new Analytica Developer edition name.

== Analytica language extensions ==

=== Index label auto updates ===

When you change a text label in an Index, it can update code to use the new text label. Iit automatically updates text literals in other expressions that compare to or subscript on an index. The new [[Index-label dot syntax]] ( <code>I . "label"</code>) associates a text literal with its index to prevent it from getting out of sync, and to warn if it ever does. These [[Keeping text literals consistent with index labels| features]] help avoid common errors when updating text labels in Indexes.

=== Callable ===

The new object [[Class]] [[Callable]] is a variable-like object, meaning it has a [[Definition]] and a computed value, but can be used for convenience and documentation when the computed value itself is something that can be called, such as a [[Local function]] (aka ''lambda function''), a [[handle]] to an global function, a Python class or a Python function.

If you "compute" the identity of a callable data item inside a normal [[Variable]] instance, <code>X</code>, you could call it using the syntax <code>X->(a,b,c)</code>. On your influence diagram the object would have a rounded rectangle and thus would not communicate that the result is something that can be called. When you change its class to be a [[Callable]], you can then invoke the call using the syntax <code>X(a,b,c)</code> and the shape of the node changes to something that resembles a function shape, thus communicating that this holds something that is callable.

To create a callable, first create a [[Variable]] node, then use the [[Class]] dropdown from the [[Object window]] or [[Attribute pane]] to change the class to ''Callable''.

=== Struct ===
A [[Struct]] defines a new atomic, immutable data type. For use when you need to bundle multiple heterogeneous items and don't want their dimensionalities to interact. Array abstract treats an instance of a Struct as a single cell (an atom).

=== Expression and Lazy qualifiers ===
An expression passed to a function parameter declared with the qualifier as <code>[[Function_parameter_qualifiers#Expression|Expression]]</code> can now include local variable identifiers. The local variables are captured (similar to how they would be captured by a [[Local function]]).

A new function parameter qualifier, [[Function_parameter_qualifiers#Lazy]], has been added, which does lazy evaluation of the expression passed to it. In the function Definition, you can use it as if it were a normal value parameter, but evaluation occurs when the value is used rather than when the function is called, and in the evaluation context (which includes the [[Evaluation modes|evaluation mode]]) where the value is used instead as in the context of the call.

=== Excess parameter qualifier ===
A new function declaration allows a function to tolerate or capture excess named parameters in the call that are not declared as parameter names in the function's Parameters declaration. It can also be used in a [[Struct]] declaration.

== Functions ==
=== ParseJSON ===
Changed to parse to [[Struct]]s, thus greatly simplifying and improving the convenience of using JSON in Analytica expressions.

For parsing with a schema, a Struct's declaration serves as the schema, which is far easier and more familiar for an Analytica user than the former scheme for specifying a schema.

[[MakeJSON]] is able to generate JSON from a Struct (or nested structs) as well, which is the most convenient representation for JSON representations.

=== SpreadsheetOpen ===
Added a new «backend» parameter to [[SpreadsheetOpen]] with a new option of <code>'LibXl'</code>, allowing you to read and manipulate a spreadsheet without having Excel installed. But unlike the Excel backend, the LibXl option does not have a calculation engine (so can't recompute cell formulas after you change cells). This option is be better when you simply want to read (or write) data in a *.xlsx file format.

== Example models and libraries ==

* There is a new "Auto insurance claim risk analysis.ana" in the Example Models / Risk Analysis folder.
* The [[Mutables library]] has been updated. It provides a new [[Mutable]] [[Struct]] which is superior to the older representation, which displays the actual value in result table cells and is atomic. The legacy functions ([[MutableNew]], [[MutableSet]] and [[MutableGet]]) are still there for backward compatibility, but have been changed to just wrap the new Mutable.

== Result tables and graphs ==
* A blank (none) entry was added to the [[XY_comparison#Use_comparison_index|comparison index pulldown]]. Use this to quickly unset the comparison index without having to re-enter the [[XY_comparison]] dialog. Also, the pulldown is now visible and enabled in browse mode.
* Comparison variables are no longer summed over slicer indexes that are set to '''Totals''' when the value for that variable does not include the slicer index. Note that this results in some changes to what is displayed in table body cells and in axis scaling on graphs.

== Assista ==

You can now copy-paste from Expression blocks in Assista's response using the little copy icon in the top-right corner of the expression block.

== Experimental ==
* A way for an Analytica model running in desktop Analytica to [[MCP server in Analytica|act as a Model Context Protocol (MCP) server]].

== ADE ==
* Added a new example: <code>Mcp_server</code>. This is an MCP server that wraps ADE. Among other things, it can give AI agents like Claude Code the ability to build, explore and use Analytica models.

What's new in Analytica 7.0?

2026-01-28T00:12:18Z

Mhenrion: /* Highlights of Analytica 7.0 */

[[category:What's new pages]]
[[category:Analytica releases]]

[[Analytica 7.0]] will be the next major Analytica release and is currently in [[Beta Tester Page|beta testing]]. Go to [[Beta Tester Page]] to try it. The current official release is [[Analytica 6.6]].

==Highlights of Analytica 7.0==

* '''Python integration:''' The major enhancement is integration with Python and hence the entire Python ecosystem of libraries. You can easily call functions from Python libraries, access Python variables, and even write Python code right inside Analytica variables and functions. So now you can mix and match Analytica and Python according to which language you think best for your modeling or coding needs.
* '''Index label updating:''' A common source of errors has been when you change a text label in an Index without remembering to change expressions that refer to that same text label. [[# Index label auto updates|New features]] now automatically update these labels, and so eliminate most of those errors.
* '''Enterprise renamed Developer edition:''' The Analytica Enterprise edition has been renamed the [[#Developer Edition (formerly known as Enterprise) |Developer edition]], which better reflects what it is.
* It introduces two new object Classes:
** [[Struct]] lets you bundle disparate values, like text, numbeers, atoms and arrays, together in one object that does not array abstract -- similar to Records and Classes in other languages).
** [[Callable]] is like a user-defined Function but it's Definition can be a [[handle]] to a Python class or a Python function.
* [[ParseJSON]] and [[MakeJSON]] now use Structs, which are much more convenient for representing the hierarchical structure of JSON.
* [[#SpreadsheetOpen|Read and write spreadsheets without Excel]]: This is faster and more robust, and you don't need Excel installed.

== [[Using Python from Analytica|Python integration]] ==

You can now benefit from the large ecosystem of Python libraries from the [[Analytica Developer]] edition or better (i.e., [[Analytica Optimizer]] edition or [[ADE]]). Use Python libraries (called modules in Python lingo) or Python code directly from your Analytica model, and it is super easy and convenient to do so! Among the gazillion possibilities are specialized data visualizations, using machine learning libraries, third party libraries, etc.

See: [[Using Python from Analytica]]

For the Analytica modeler, this puts a ton of resources at your fingertips.

For the Python developer, this is also pretty cool. Analytica is like a new interactive development environment in which there are a lot of unique advantages, especially during interactive code development, including these:
* Analytica's dependency maintenance can be really convenient during interactive development, creating automatic dependency maintenance between your python functions, classes and variables that don't exist in Python.
* The visual influence diagram layout can be a super useful to way organize and visualize your code.
* It naturally encourages declarative code practices, which leads to better and more maintainable coding style.
* You get the benefits of Analytica's edit tables, plus for results, Analytica's multi-D result tables and one-click, no-code, graphing.
* It is easy to wrap existing Python models to get Monte Carlo, parametric analysis and sensitivity analysis with Analytica ease.
* Sometimes one or the other language is more convenient for a particular task. You can freely switch between whichever language feels better suited to the immediate task, and intermix languages easily.

== Developer Edition (formerly known as Enterprise) ==

Analytica's middle-tier edition formerly known as the ''Enterprise Edition'', it is now called the [[Analytica Developer|Analytica Developer edition]]. That name better reflects what it is--software for developers of decision applications. If you're now a user of Analytica Enterprise you don't have to update your license or do anything special. The name will just change when you install Analytica 7.0. In Analytica docs, when you select "7.0" on the release bar (at the top of pages that have release-contingent content), all the docs automatically use the new Analytica Developer edition name.

== Analytica language extensions ==

=== Index label auto updates ===

When you change a text label in an Index, it can update code to use the new text label. Iit automatically updates text literals in other expressions that compare to or subscript on an index. The new [[Index-label dot syntax]] ( <code>I . "label"</code>) associates a text literal with its index to prevent it from getting out of sync, and to warn if it ever does. These [[Keeping text literals consistent with index labels| features]] help avoid common errors when updating text labels in Indexes.

=== Callable ===

The new object [[Class]] [[Callable]] is a variable-like object, meaning it has a [[Definition]] and a computed value, but can be used for convenience and documentation when the computed value itself is something that can be called, such as a [[Local function]] (aka ''lambda function''), a [[handle]] to an global function, a Python class or a Python function.

If you "compute" the identity of a callable data item inside a normal [[Variable]] instance, <code>X</code>, you could call it using the syntax <code>X->(a,b,c)</code>. On your influence diagram the object would have a rounded rectangle and thus would not communicate that the result is something that can be called. When you change its class to be a [[Callable]], you can then invoke the call using the syntax <code>X(a,b,c)</code> and the shape of the node changes to something that resembles a function shape, thus communicating that this holds something that is callable.

To create a callable, first create a [[Variable]] node, then use the [[Class]] dropdown from the [[Object window]] or [[Attribute pane]] to change the class to ''Callable''.

=== Struct ===
A [[Struct]] defines a new atomic, immutable data type. For use when you need to bundle multiple heterogeneous items and don't want their dimensionalities to interact. Array abstract treats an instance of a Struct as a single cell (an atom).

=== Expression and Lazy qualifiers ===
An expression passed to a function parameter declared with the qualifier as <code>[[Function_parameter_qualifiers#Expression|Expression]]</code> can now include local variable identifiers. The local variables are captured (similar to how they would be captured by a [[Local function]]).

A new function parameter qualifier, [[Function_parameter_qualifiers#Lazy]], has been added, which does lazy evaluation of the expression passed to it. In the function Definition, you can use it as if it were a normal value parameter, but evaluation occurs when the value is used rather than when the function is called, and in the evaluation context (which includes the [[Evaluation modes|evaluation mode]]) where the value is used instead as in the context of the call.

=== Excess parameter qualifier ===
A new function declaration allows a function to tolerate or capture excess named parameters in the call that are not declared as parameter names in the function's Parameters declaration. It can also be used in a [[Struct]] declaration.

== Functions ==
=== ParseJSON ===
Changed to parse to [[Struct]]s, thus greatly simplifying and improving the convenience of using JSON in Analytica expressions.

For parsing with a schema, a Struct's declaration serves as the schema, which is far easier and more familiar for an Analytica user than the former scheme for specifying a schema.

[[MakeJSON]] is able to generate JSON from a Struct (or nested structs) as well, which is the most convenient representation for JSON representations.

=== SpreadsheetOpen ===
Added a new «backend» parameter to [[SpreadsheetOpen]] with a new option of <code>'LibXl'</code>, allowing you to read and manipulate a spreadsheet without having Excel installed. But unlike the Excel backend, the LibXl option does not have a calculation engine (so can't recompute cell formulas after you change cells). This option is be better when you simply want to read (or write) data in a *.xlsx file format.

== Example models and libraries ==

* There is a new "Auto insurance claim risk analysis.ana" in the Example Models / Risk Analysis folder.
* The [[Mutables library]] has been updated. It provides a new [[Mutable]] [[Struct]] which is superior to the older representation, which displays the actual value in result table cells and is atomic. The legacy functions ([[MutableNew]], [[MutableSet]] and [[MutableGet]]) are still there for backward compatibility, but have been changed to just wrap the new Mutable.

== Result tables and graphs ==
* A blank (none) entry was added to the [[XY_comparison#Use_comparison_index|comparison index pulldown]]. Use this to quickly unset the comparison index without having to re-enter the [[XY_comparison]] dialog. Also, the pulldown is now visible and enabled in browse mode.
* Comparison variables are no longer summed over slicer indexes that are set to '''Totals''' when the value for that variable does not include the slicer index. Note that this results in some changes to what is displayed in table body cells and in axis scaling on graphs.

== Assista ==

You can now copy-paste from Expression blocks in Assista's response using the little copy icon in the top-right corner of the expression block.

== Experimental ==
* A way for an Analytica model running in desktop Analytica to [[MCP server in Analytica|act as a Model Context Protocol (MCP) server]].

== ADE ==
* Added a new example: <code>Mcp_server</code>. This is an MCP server that wraps ADE. Among other things, it can give AI agents like Claude Code the ability to build, explore and use Analytica models.