Class: Noise

URI: tvbo:Noise

 classDiagram
    class Noise
    click Noise href "./Noise.html"
      Noise : additive
        
          
    
        
        
        Noise --> "0..1" Boolean : additive
        click Boolean href "../http://www.w3.org/2001/XMLSchema#boolean.html"
    

        
      Noise : correlated
        
          
    
        
        
        Noise --> "0..1" Boolean : correlated
        click Boolean href "../http://www.w3.org/2001/XMLSchema#boolean.html"
    

        
      Noise : correlated_over
        
          
    
        
        
        Noise --> "0..1" DimensionType : correlated_over
        click DimensionType href "../../enums/DimensionType.html"
    

        
      Noise : covariance
        
          
    
        
        
        Noise --> "0..1" Parameter : covariance
        click Parameter href "./Parameter.html"
    

        
      Noise : distribution
        
          
    
        
        
        Noise --> "0..1" Distribution : distribution
        click Distribution href "./Distribution.html"
    

        
      Noise : equation
        
          
    
        
        
        Noise --> "0..1" Equation : equation
        click Equation href "./Equation.html"
    

        
      Noise : function
        
          
    
        
        
        Noise --> "0..1" Function : function
        click Function href "./Function.html"
    

        
      Noise : gaussian
        
          
    
        
        
        Noise --> "0..1" Boolean : gaussian
        click Boolean href "../http://www.w3.org/2001/XMLSchema#boolean.html"
    

        
      Noise : noise_type
        
          
    
        
        
        Noise --> "0..1" String : noise_type
        click String href "../http://www.w3.org/2001/XMLSchema#string.html"
    

        
      Noise : parameters
        
          
    
        
        
        Noise --> "*" Parameter : parameters
        click Parameter href "./Parameter.html"
    

        
      Noise : pycode
        
          
    
        
        
        Noise --> "0..1" String : pycode
        click String href "../http://www.w3.org/2001/XMLSchema#string.html"
    

        
      Noise : random_state
        
          
    
        
        
        Noise --> "0..1" RandomStream : random_state
        click RandomStream href "./RandomStream.html"
    

        
      Noise : seed
        
          
    
        
        
        Noise --> "0..1" Integer : seed
        click Integer href "../http://www.w3.org/2001/XMLSchema#integer.html"
    

        
      Noise : settle_seed
        
          
    
        
        
        Noise --> "0..1" Integer : settle_seed
        click Integer href "../http://www.w3.org/2001/XMLSchema#integer.html"
    

        
      Noise : targets
        
          
    
        
        
        Noise --> "*" StateVariable : targets
        click StateVariable href "./StateVariable.html"

Class Properties

Property Value
Class URI tvbo:Noise

Slots

Name Cardinality and Range Description Inheritance
parameters *
Parameter		 direct
equation 0..1
Equation		 direct
noise_type 0..1
xsd:string		 Temporal character of the process: gaussian/white (delta-correlated in ti… direct
covariance 0..1
Parameter		 Covariance of the unit-intensity noise increment across the axis named by co... | direct | | [correlated_over](../slots/correlated_over.qmd) | 0..1 <br/> [DimensionType](../enums/DimensionType.qmd) | Which axiscovarianceindexes —node(equivalentlyregion`) for spatiall… direct
correlated 0..1
xsd:boolean		 Deprecated direct
gaussian 0..1
xsd:boolean		 Indicates whether the noise is Gaussian direct
additive 0..1
xsd:boolean		 Indicates whether the noise is additive direct
seed 0..1
xsd:integer		 direct
settle_seed 0..1
xsd:integer		 Seed for the noise the settle integrates, when the settle runs as its own sca… direct
random_state 0..1
RandomStream		 direct
distribution 0..1
Distribution		 Optional probability distribution from which the noise draws its samples direct
function 0..1
Function		 Optional functional form of the noise (callable specification) direct
pycode 0..1
xsd:string		 Inline Python code representation of the noise process direct
targets *
StateVariable		 State variables this noise applies to; if omitted, applies globally direct

Usages

used by used in type used
Stimulus noise range Noise
StateVariable noise range Noise
Integrator noise range Noise
FieldStateVariable noise range Noise

Identifier and Mapping Information

Schema Source

  • from schema: https://w3id.org/tvbo

Mappings

Mapping Type Mapped Value
self tvbo:Noise
native tvbo:Noise

LinkML Source

Direct

name: Noise
from_schema: https://w3id.org/tvbo
slots:
- parameters
- equation
attributes:
  noise_type:
    name: noise_type
    description: 'Temporal character of the process: `gaussian`/`white` (delta-correlated
      in time) or `ou`/`ornstein-uhlenbeck` (exponentially correlated in time). Governs
      the TIME axis only, and composes freely with `covariance`, which governs a spatial
      axis.'
    from_schema: https://w3id.org/tvbo
    rank: 1000
    ifabsent: gaussian
    domain_of:
    - Noise
    range: string
  covariance:
    name: covariance
    description: 'Covariance of the unit-intensity noise increment across the axis
      named by `correlated_over` — the second-order structure of the driving process,
      stated as mathematics rather than as a factorisation. Must be square in that
      axis, symmetric and positive semi-definite; its diagonal carries per-element
      variances and need NOT be unity, so unequal variances and cross-element correlation
      are expressed together. The realised increment is the declared sigma times a
      draw from this covariance, so `parameters: {sigma: ...}` continues to mean what
      it means for uncorrelated noise. Absent (the default) means the increment is
      independent across that axis. Being a `Parameter`, it carries the full provenance
      triple: a literal `value:`, existing bytes via `source:`+`measure:`, or — the
      usual case for a derived operator — `producer:`, whose FunctionCall records
      how the structure was obtained (projecting a spatially white field into a modal
      basis, spreading independent per-region drives through a connectome). The generative
      account therefore lives in the provenance, and the matrix itself stays a statement
      about the process. How a backend samples it (Cholesky, eigendecomposition, whitening)
      is a backend concern and is never stated here.'
    from_schema: https://w3id.org/tvbo
    rank: 1000
    domain_of:
    - Noise
    range: Parameter
    required: false
    inlined: true
  correlated_over:
    name: correlated_over
    description: 'Which axis `covariance` indexes — `node` (equivalently `region`)
      for spatially correlated drive, or `state` for correlation between the noise
      on different state variables. Required whenever `covariance` is set: a covariance
      without a named axis does not identify a process. A multi-mode model carries
      its modes inside the state axis, so a modal covariance is declared over `state`.'
    from_schema: https://w3id.org/tvbo
    rank: 1000
    domain_of:
    - Noise
    range: DimensionType
    required: false
  correlated:
    name: correlated
    description: Deprecated. Whether the noise is correlated, without saying across
      which axis or by how much. Use `covariance` + `correlated_over`.
    deprecated: Superseded by `covariance` + `correlated_over`. A bare boolean never
      identified a process — it said neither which axis was correlated nor how strongly
      — so no backend could act on it. Read and ignored, so recipes carrying it keep
      loading; delete it, and declare `covariance` if the noise really is correlated.
    from_schema: https://w3id.org/tvbo
    rank: 1000
    domain_of:
    - Noise
    range: boolean
  gaussian:
    name: gaussian
    description: Indicates whether the noise is Gaussian
    from_schema: https://w3id.org/tvbo
    rank: 1000
    ifabsent: 'False'
    domain_of:
    - Noise
    range: boolean
  additive:
    name: additive
    description: Indicates whether the noise is additive
    from_schema: https://w3id.org/tvbo
    rank: 1000
    ifabsent: 'True'
    domain_of:
    - Noise
    range: boolean
  seed:
    name: seed
    from_schema: https://w3id.org/tvbo
    ifabsent: integer(42)
    domain_of:
    - GraphGenerator
    - Distribution
    - Noise
    - Inference
    range: integer
  settle_seed:
    name: settle_seed
    description: 'Seed for the noise the settle integrates, when the settle runs as
      its own scan. Absent -- the default -- leaves the settle on whatever stream
      its solver hands it, which is what an unmodified upstream warm start does; the
      backend is not silently given a different draw than the reference implementation
      it is checked against. Present means the settle uses exactly this seed. Both
      interesting cases are then sayable: equal to `seed` puts the two scans on one
      stream, and different from it decorrelates them. Equal is not neutral -- where
      the two scans take the same number of steps a shorter draw is a prefix of a
      longer one, so the measured noise repeats the settle''s sample for sample, and
      corr(settle, measured) on demeaned fluctuations is +0.49 against -0.01 decorrelated.
      Its effect on the reported statistics was null everywhere it was measured (FC
      bias below 0.03 sigma, no trend), so this slot exists to make the choice visible
      and reproducible rather than because either answer is known to be wrong.'
    from_schema: https://w3id.org/tvbo
    rank: 1000
    domain_of:
    - Noise
    range: integer
    required: false
  random_state:
    name: random_state
    from_schema: https://w3id.org/tvbo
    rank: 1000
    domain_of:
    - Noise
    range: RandomStream
    inlined: true
  distribution:
    name: distribution
    description: Optional probability distribution from which the noise draws its
      samples. When set, takes precedence over the `noise_type` / `gaussian` flags
      — any Distribution family is accepted (Uniform { lo, hi }, Normal { mean, std
      }, LogNormal { mu, sigma }, Beta, …). Reuses the existing Distribution class
      also used by Parameter.distribution.
    from_schema: https://w3id.org/tvbo
    domain_of:
    - ProcedureStep
    - StateVariable
    - Parameter
    - Noise
    - Prior
    - Coupling
    range: Distribution
    required: false
    inlined: true
  function:
    name: function
    description: Optional functional form of the noise (callable specification).
    from_schema: https://w3id.org/tvbo
    domain_of:
    - Distribution
    - FunctionCall
    - Noise
    range: Function
    inlined: true
  pycode:
    name: pycode
    description: Inline Python code representation of the noise process.
    from_schema: https://w3id.org/tvbo
    domain_of:
    - Equation
    - Noise
    range: string
  targets:
    name: targets
    description: State variables this noise applies to; if omitted, applies globally.
    from_schema: https://w3id.org/tvbo
    rank: 1000
    domain_of:
    - Noise
    range: StateVariable
    multivalued: true
    inlined: true
class_uri: tvbo:Noise

Induced

name: Noise
from_schema: https://w3id.org/tvbo
attributes:
  noise_type:
    name: noise_type
    description: 'Temporal character of the process: `gaussian`/`white` (delta-correlated
      in time) or `ou`/`ornstein-uhlenbeck` (exponentially correlated in time). Governs
      the TIME axis only, and composes freely with `covariance`, which governs a spatial
      axis.'
    from_schema: https://w3id.org/tvbo
    rank: 1000
    ifabsent: gaussian
    owner: Noise
    domain_of:
    - Noise
    range: string
  covariance:
    name: covariance
    description: 'Covariance of the unit-intensity noise increment across the axis
      named by `correlated_over` — the second-order structure of the driving process,
      stated as mathematics rather than as a factorisation. Must be square in that
      axis, symmetric and positive semi-definite; its diagonal carries per-element
      variances and need NOT be unity, so unequal variances and cross-element correlation
      are expressed together. The realised increment is the declared sigma times a
      draw from this covariance, so `parameters: {sigma: ...}` continues to mean what
      it means for uncorrelated noise. Absent (the default) means the increment is
      independent across that axis. Being a `Parameter`, it carries the full provenance
      triple: a literal `value:`, existing bytes via `source:`+`measure:`, or — the
      usual case for a derived operator — `producer:`, whose FunctionCall records
      how the structure was obtained (projecting a spatially white field into a modal
      basis, spreading independent per-region drives through a connectome). The generative
      account therefore lives in the provenance, and the matrix itself stays a statement
      about the process. How a backend samples it (Cholesky, eigendecomposition, whitening)
      is a backend concern and is never stated here.'
    from_schema: https://w3id.org/tvbo
    rank: 1000
    owner: Noise
    domain_of:
    - Noise
    range: Parameter
    required: false
    inlined: true
  correlated_over:
    name: correlated_over
    description: 'Which axis `covariance` indexes — `node` (equivalently `region`)
      for spatially correlated drive, or `state` for correlation between the noise
      on different state variables. Required whenever `covariance` is set: a covariance
      without a named axis does not identify a process. A multi-mode model carries
      its modes inside the state axis, so a modal covariance is declared over `state`.'
    from_schema: https://w3id.org/tvbo
    rank: 1000
    owner: Noise
    domain_of:
    - Noise
    range: DimensionType
    required: false
  correlated:
    name: correlated
    description: Deprecated. Whether the noise is correlated, without saying across
      which axis or by how much. Use `covariance` + `correlated_over`.
    deprecated: Superseded by `covariance` + `correlated_over`. A bare boolean never
      identified a process — it said neither which axis was correlated nor how strongly
      — so no backend could act on it. Read and ignored, so recipes carrying it keep
      loading; delete it, and declare `covariance` if the noise really is correlated.
    from_schema: https://w3id.org/tvbo
    rank: 1000
    owner: Noise
    domain_of:
    - Noise
    range: boolean
  gaussian:
    name: gaussian
    description: Indicates whether the noise is Gaussian
    from_schema: https://w3id.org/tvbo
    rank: 1000
    ifabsent: 'False'
    owner: Noise
    domain_of:
    - Noise
    range: boolean
  additive:
    name: additive
    description: Indicates whether the noise is additive
    from_schema: https://w3id.org/tvbo
    rank: 1000
    ifabsent: 'True'
    owner: Noise
    domain_of:
    - Noise
    range: boolean
  seed:
    name: seed
    from_schema: https://w3id.org/tvbo
    ifabsent: integer(42)
    owner: Noise
    domain_of:
    - GraphGenerator
    - Distribution
    - Noise
    - Inference
    range: integer
  settle_seed:
    name: settle_seed
    description: 'Seed for the noise the settle integrates, when the settle runs as
      its own scan. Absent -- the default -- leaves the settle on whatever stream
      its solver hands it, which is what an unmodified upstream warm start does; the
      backend is not silently given a different draw than the reference implementation
      it is checked against. Present means the settle uses exactly this seed. Both
      interesting cases are then sayable: equal to `seed` puts the two scans on one
      stream, and different from it decorrelates them. Equal is not neutral -- where
      the two scans take the same number of steps a shorter draw is a prefix of a
      longer one, so the measured noise repeats the settle''s sample for sample, and
      corr(settle, measured) on demeaned fluctuations is +0.49 against -0.01 decorrelated.
      Its effect on the reported statistics was null everywhere it was measured (FC
      bias below 0.03 sigma, no trend), so this slot exists to make the choice visible
      and reproducible rather than because either answer is known to be wrong.'
    from_schema: https://w3id.org/tvbo
    rank: 1000
    owner: Noise
    domain_of:
    - Noise
    range: integer
    required: false
  random_state:
    name: random_state
    from_schema: https://w3id.org/tvbo
    rank: 1000
    owner: Noise
    domain_of:
    - Noise
    range: RandomStream
    inlined: true
  distribution:
    name: distribution
    description: Optional probability distribution from which the noise draws its
      samples. When set, takes precedence over the `noise_type` / `gaussian` flags
      — any Distribution family is accepted (Uniform { lo, hi }, Normal { mean, std
      }, LogNormal { mu, sigma }, Beta, …). Reuses the existing Distribution class
      also used by Parameter.distribution.
    from_schema: https://w3id.org/tvbo
    owner: Noise
    domain_of:
    - ProcedureStep
    - StateVariable
    - Parameter
    - Noise
    - Prior
    - Coupling
    range: Distribution
    required: false
    inlined: true
  function:
    name: function
    description: Optional functional form of the noise (callable specification).
    from_schema: https://w3id.org/tvbo
    owner: Noise
    domain_of:
    - Distribution
    - FunctionCall
    - Noise
    range: Function
    inlined: true
  pycode:
    name: pycode
    description: Inline Python code representation of the noise process.
    from_schema: https://w3id.org/tvbo
    owner: Noise
    domain_of:
    - Equation
    - Noise
    range: string
  targets:
    name: targets
    description: State variables this noise applies to; if omitted, applies globally.
    from_schema: https://w3id.org/tvbo
    rank: 1000
    owner: Noise
    domain_of:
    - Noise
    range: StateVariable
    multivalued: true
    inlined: true
  parameters:
    name: parameters
    from_schema: https://w3id.org/tvbo
    rank: 1000
    owner: Noise
    domain_of:
    - Equation
    - Stimulus
    - Event
    - ExperimentResultSidecar
    - Network
    - GraphGenerator
    - Node
    - Edge
    - Observation
    - Analysis
    - Dynamics
    - Distribution
    - Noise
    - Exploration
    - Discretization
    - BranchSwitch
    - Integrator
    - Coupling
    - PDE
    range: Parameter
    multivalued: true
    inlined: true
  equation:
    name: equation
    from_schema: https://w3id.org/tvbo
    rank: 1000
    slot_uri: tvbo:Equation
    owner: Noise
    domain_of:
    - Stimulus
    - Event
    - ProcedureStep
    - Observation
    - StateVariable
    - Parameter
    - Function
    - FunctionCall
    - DerivedParameter
    - DerivedVariable
    - Noise
    - UpdateRule
    - DifferentialOperator
    - BoundaryCondition
    range: Equation
    inlined: true
class_uri: tvbo:Noise