DisplaySettings

Symbolica documentation for getting started, symbolic expressions, numerical evaluation, pattern matching, and APIs in Python and Rust.

DisplaySettings

class DisplaySettings

Immutable presentation options for tensor notation and component displays.

Formatting does not change indices, tensor algebra, or component order. The defaults use representation-specific index alphabets and an interactive component explorer. Typst/plain source supports ports layout; alternative layouts and custom spacing require a rich HTML or SVG renderer.

Examples

from symbolica.community.tensor import DisplaySettings
settings = DisplaySettings(component_style="array", index_style="alphabet")

Attributes

Name	Description
commas	Show comma separators.
component_style	Concrete component labels: “superscript” for A(x,7)^{0,1},.
factor_gap	Spacing between rendered factors, using the same length units as index_gap.
index_gap	Spacing between rendered indices, as a finite Typst length using.
index_style	“alphabet” assigns representation-specific letters to generated indices;.
invariant_style	Choose compact or degree-explicit scalar invariant notation.
parentheses	Include the optional grouping parentheses used by tensor notation.
show_dimensions	Include representation dimensions in index notation.
symbol_scripts	Render index and component information using symbol scripts where supported.
tensor_layout	Rich layout: “ports” places indices by tensor axes; “schoonschip”.
tensor_view	Concrete-tensor HTML: “interactive” provides a component explorer with.

commas

DisplaySettings.commas: typing.Optional[builtins.bool]

Show comma separators. None follows the layout: enabled for “call”,

Returns

• bool or None Show comma separators. None follows the layout: enabled for “call”, disabled otherwise.

Examples

from symbolica.community.tensor import DisplaySettings
value = DisplaySettings().commas

component_style

DisplaySettings.component_style: typing.Literal['superscript', 'array']

Concrete component labels: “superscript” for A(x,7)^{0,1},

Returns

• str Concrete component labels: “superscript” for A(x,7)^{0,1}, or “array” for A(x,7)[0,1]. Scalar arguments stay in parentheses.

Examples

from symbolica.community.tensor import DisplaySettings
value = DisplaySettings().component_style

factor_gap

DisplaySettings.factor_gap: builtins.str

Spacing between rendered factors, using the same length units as index_gap.

Returns

• str Spacing between rendered factors, using the same length units as index_gap.

Examples

from symbolica.community.tensor import DisplaySettings
value = DisplaySettings().factor_gap

index_gap

DisplaySettings.index_gap: builtins.str

Spacing between rendered indices, as a finite Typst length using

Returns

• str Spacing between rendered indices, as a finite Typst length using pt, mm, cm, in, em, or %.

Examples

from symbolica.community.tensor import DisplaySettings
value = DisplaySettings().index_gap

index_style

DisplaySettings.index_style: typing.Literal['alphabet', 'graph', 'raw']

“alphabet” assigns representation-specific letters to generated indices;

Returns

• str “alphabet” assigns representation-specific letters to generated indices; “graph” shows graph identities; “raw” retains the original labels.

Examples

from symbolica.community.tensor import DisplaySettings
value = DisplaySettings().index_style

invariant_style

DisplaySettings.invariant_style: typing.Literal['compact', 'explicit']

Choose compact or degree-explicit scalar invariant notation.

Returns

• str “compact” uses C_F, C_A and T_R for the quadratic color invariants; “explicit” uses C_2(F), C_2(A) and I_2(F). Higher degrees use C_k(R), I_k(R) and G_k(R, S) in either style.

Examples

from symbolica.community.tensor import DisplaySettings
DisplaySettings(invariant_style="explicit").invariant_style
'explicit'

parentheses

DisplaySettings.parentheses: builtins.bool

Include the optional grouping parentheses used by tensor notation.

Returns

• bool Include the optional grouping parentheses used by tensor notation.

Examples

from symbolica.community.tensor import DisplaySettings
value = DisplaySettings().parentheses

show_dimensions

DisplaySettings.show_dimensions: builtins.bool

Include representation dimensions in index notation.

Returns

• bool Include representation dimensions in index notation and scalar invariants. Invariants then show their degree and representation, such as C_2(F_3).

Examples

from symbolica.community.tensor import DisplaySettings
value = DisplaySettings().show_dimensions

symbol_scripts

DisplaySettings.symbol_scripts: builtins.bool

Render index and component information using symbol scripts where supported.

Returns

• bool Render index and component information using symbol scripts where supported.

Examples

from symbolica.community.tensor import DisplaySettings
value = DisplaySettings().symbol_scripts

tensor_layout

DisplaySettings.tensor_layout: typing.Literal['ports', 'schoonschip', 'call']

Rich layout: “ports” places indices by tensor axes; “schoonschip”

Returns

• str Rich layout: “ports” places indices by tensor axes; “schoonschip” uses compact contracted-vector notation; “call” uses function-call notation.

Examples

from symbolica.community.tensor import DisplaySettings
value = DisplaySettings().tensor_layout

tensor_view

DisplaySettings.tensor_view: typing.Literal['interactive', 'matrix']

Concrete-tensor HTML: “interactive” provides a component explorer with

Returns

• str Concrete-tensor HTML: “interactive” provides a component explorer with a Memory grid / Matrix toggle; “matrix” selects static mathematical output.

Examples

from symbolica.community.tensor import DisplaySettings
value = DisplaySettings().tensor_view

Methods

Name	Description
__new__	Choose tensor notation, index labels, and component presentation.
__repr__	Return a readable object description for inspection.
call	Select the call tensor layout with default options.
ports	Select the ports tensor layout with default options.
schoonschip	Select the schoonschip tensor layout with default options.

__new__

DisplaySettings.__new__(
    tensor_layout: typing.Literal['ports', 'schoonschip', 'call'] = 'ports',
    show_dimensions: builtins.bool = False,
    parentheses: builtins.bool = True,
    commas: typing.Optional[builtins.bool] = None,
    symbol_scripts: builtins.bool = True,
    index_gap: builtins.str = '0.08em',
    factor_gap: builtins.str = '0.12em',
    index_style: typing.Literal['alphabet', 'graph', 'raw'] = 'alphabet',
    component_style: typing.Literal['superscript', 'array'] = 'superscript',
    tensor_view: typing.Literal['interactive', 'matrix'] = 'interactive',
    invariant_style: typing.Literal['compact', 'explicit'] = 'compact',
) -> DisplaySettings

Choose tensor notation, index labels, and component presentation.

Parameters

• tensor_layout (str, default “ports”) Rich layout: “ports” places indices by tensor axes; “schoonschip” uses compact contracted-vector notation; “call” uses function-call notation.
• show_dimensions (bool, default False) Include representation dimensions in index notation and scalar invariants. Invariants then show their degree and representation, such as C_2(F_3).
• parentheses (bool, default True) Include the optional grouping parentheses used by tensor notation.
• commas (bool or None, default None) Show comma separators. None follows the layout: enabled for “call”, disabled otherwise.
• symbol_scripts (bool, default True) Render index and component information using symbol scripts where supported.
• index_gap (str, default “0.08em”) Spacing between rendered indices, as a finite Typst length using pt, mm, cm, in, em, or %.
• factor_gap (str, default “0.12em”) Spacing between rendered factors, using the same length units as index_gap.
• index_style (str, default “alphabet”) “alphabet” assigns representation-specific letters to generated indices; “graph” shows graph identities; “raw” retains the original labels.
• component_style (str, default “superscript”) Concrete component labels: “superscript” for A(x,7)^{0,1}, or “array” for A(x,7)[0,1]. Scalar arguments stay in parentheses.
• tensor_view (str, default “interactive”) Concrete-tensor HTML: “interactive” provides a component explorer with a Memory grid / Matrix toggle; “matrix” selects static mathematical output.
• invariant_style ({“compact”, “explicit”}, default “compact”) Compact quadratic color notation uses C_F, C_A and T_R. Explicit notation uses C_2(F), C_2(A) and I_2(F). Both use C_k(R), I_k(R) and G_k(R, S) for higher invariants. show_dimensions adds the dimension to each representation label and disables quadratic aliases. Older scalar symbols have no representation dimension to display.

Returns

• DisplaySettings Immutable settings to pass to formatting methods.

Notes

The tensor_view option affects concrete tensor HTML, not symbolic TensorExpression algebra or TensorNetwork graph rendering.

Examples

from symbolica.community.tensor import DisplaySettings
settings = DisplaySettings(component_style="array", tensor_view="matrix")

__repr__

DisplaySettings.__repr__() -> builtins.str

Return a readable object description for inspection.

Examples

from symbolica.community import tensor as sp
settings = sp.DisplaySettings()
text = repr(settings)

call

DisplaySettings.call() -> DisplaySettings

Select the call tensor layout with default options.

Returns

• DisplaySettings Default presentation with this layout; comma separators are enabled.

Notes

Use with rich HTML or SVG rendering. Plain and Typst source methods require ports layout.

Examples

from symbolica.community.tensor import DisplaySettings
DisplaySettings.call().tensor_layout
'call'

ports

DisplaySettings.ports() -> DisplaySettings

Select the ports tensor layout with default options.

Returns

• DisplaySettings Default presentation with this layout.

Examples

from symbolica.community.tensor import DisplaySettings
DisplaySettings.ports().tensor_layout
'ports'

schoonschip

DisplaySettings.schoonschip() -> DisplaySettings

Select the schoonschip tensor layout with default options.

Returns

• DisplaySettings Default presentation with this layout.

Notes

Use with rich HTML or SVG rendering. Plain and Typst source methods require ports layout.

Examples

from symbolica.community.tensor import DisplaySettings
DisplaySettings.schoonschip().tensor_layout
'schoonschip'