doe model

class friendly_doe.doe_model.CandidateSet(*, data: list[list[int | str | float | None]])

Bases: BaseModel

data: list[list[int | str | float | None]]

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class friendly_doe.doe_model.Constants(*, c1: float, c2: float, c3: float | None = None)

Bases: BaseModel

c1: float

c2: float

c3: float | None

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class friendly_doe.doe_model.Design(*, type: DesignType | None = '', settings: dict[str, Any] | None = None)

Bases: BaseModel

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

settings: dict[str, Any] | None

type: DesignType | None

class friendly_doe.doe_model.DesignType(value)

Bases: Enum

An enumeration.

AxE = 'AxE'

AxN = 'AxN'

AxR = 'AxR'

BB = 'BB'

CCC = 'CCC'

CCF = 'CCF'

CCO = 'CCO'

Custom = 'Custom'

DOpt = 'DOpt'

Definitive_Screening = 'Definitive Screening'

Doehlert = 'Doehlert'

FF2 = 'FF2'

FF3 = 'FF3'

FFM = 'FFM'

FFR_III = 'FFR_III'

FFR_IV = 'FFR_IV'

FFR_V = 'FFR_V'

Generalized_Subset_Designs = 'Generalized Subset Designs'

J2 = 'J2'

L18 = 'L18'

L27 = 'L27'

L36 = 'L36'

L9 = 'L9'

Levels = 'Levels'

OnionDOpt = 'OnionDOpt'

PB = 'PB'

PB_SS = 'PB_SS'

RCCC = 'RCCC'

RCCF = 'RCCF'

RED_MUP = 'RED-MUP'

RSR = 'RSR'

RSS = 'RSS'

SimC = 'SimC'

SimF = 'SimF'

SimM = 'SimM'

SimSC = 'SimSC'

Stability = 'Stability'

field_ = ''

class friendly_doe.doe_model.DoeSchema(*, apiVersion: str, name: str | None = '', factors: list[~friendly_doe.doe_model.Factor] | None = <factory>, responses: list[~friendly_doe.doe_model.Response] | None = <factory>, settings: ~friendly_doe.doe_model.Settings | None = <factory>, worksheet: ~friendly_doe.doe_model.Worksheet | None = None, setpoints: ~friendly_doe.doe_model.Setpoints | None = None, objective: ~friendly_doe.doe_model.Objective1 | None = '', design: ~friendly_doe.doe_model.Design | None = None, model: ~friendly_doe.doe_model.Model | None = None, models: list[~friendly_doe.doe_model.Model1] | None = <factory>, predictions: ~friendly_doe.doe_model.Predictions | None = None, candidateSet: ~friendly_doe.doe_model.CandidateSet | None = None)

Bases: BaseModel

apiVersion: str

candidateSet: CandidateSet | None

design: Design | None

factors: list[Factor] | None

model: Model | None

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

models: list[Model1] | None

name: str | None

objective: Objective1 | None

predictions: Predictions | None

responses: list[Response] | None

setpoints: Setpoints | None

settings: Settings | None

worksheet: Worksheet | None

class friendly_doe.doe_model.Factor(*, name: str, unit: str | None = '', abbreviation: Annotated[str, _PydanticGeneralMetadata(pattern='^.{1,5}$')], type: FactorType, settings: list[float | str], precision: Precision | None = None, transform: Transform | None = None, scaling: Scaling | None = None)

Bases: BaseModel

abbreviation: str

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str

precision: Precision | None

scaling: Scaling | None

settings: list[float | str]

transform: Transform | None

type: FactorType

unit: str | None

class friendly_doe.doe_model.FactorTransformType(value)

Bases: Enum

An enumeration.

exp = 'exp'

linear = 'linear'

log = 'log'

logit = 'logit'

negLog = 'negLog'

power = 'power'

class friendly_doe.doe_model.FactorType(value)

Bases: Enum

An enumeration.

filler = 'filler'

formulation = 'formulation'

multilevel = 'multilevel'

qualitative = 'qualitative'

quantitative = 'quantitative'

class friendly_doe.doe_model.FitMethod(value)

Bases: Enum

An enumeration.

Auto = 'Auto'

MLR = 'MLR'

PLS = 'PLS'

Scheffé_MLR = 'Scheffé MLR'

class friendly_doe.doe_model.Model(*, type: ModelType | None = ModelType.interaction, fitMethod: FitMethod | None = FitMethod.Auto, settings: Settings | None = None)

Bases: BaseModel

fitMethod: FitMethod | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

settings: Settings | None

type: ModelType | None

class friendly_doe.doe_model.Model1(*, excluded: list[float] | None = [], response: str, terms: list[str])

Bases: BaseModel

excluded: list[float] | None

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

response: str

terms: list[str]

class friendly_doe.doe_model.ModelType(value)

Bases: Enum

An enumeration.

cubic = 'cubic'

interaction = 'interaction'

linear = 'linear'

linear_quadratic = 'linear_quadratic'

quadratic = 'quadratic'

special_cubic = 'special cubic'

class friendly_doe.doe_model.Objective(*, type: str, min: float | None = None, target: float | None = None, max: float | None = None)

Bases: BaseModel

max: float | None

min: float | None

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

target: float | None

type: str

class friendly_doe.doe_model.Objective1(value)

Bases: Enum

An enumeration.

field_ = ''

optimization = 'optimization'

robust_verification = 'robust_verification'

screening = 'screening'

system_characterization = 'system_characterization'

class friendly_doe.doe_model.OptimizationSettings(*, condition: str, objective: Objective)

Bases: BaseModel

condition: str

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

objective: Objective

class friendly_doe.doe_model.Precision(*, factorPrecision: float | None = 0.99999, normalOperatingRange: float | None = None, numDecimals: float | None = 3)

Bases: BaseModel

factorPrecision: float | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

normalOperatingRange: float | None

numDecimals: float | None

class friendly_doe.doe_model.Predictions(*, intervalType: str | None = None, confidenceLevel: float | None = 0.95, toleranceProportion: float | None = 0.95)

Bases: BaseModel

confidenceLevel: float | None

intervalType: str | None

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

toleranceProportion: float | None

class friendly_doe.doe_model.Response(*, name: str, abbreviation: str, unit: str | None = None, type: ResponseType, scaling: Scaling1 | None = None, transform: Transform1 | None = None, optimizationSettings: OptimizationSettings | None = None)

Bases: BaseModel

abbreviation: str

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str

optimizationSettings: OptimizationSettings | None

scaling: Scaling1 | None

transform: Transform1 | None

type: ResponseType

unit: str | None

class friendly_doe.doe_model.ResponseTransformType(value)

Bases: Enum

An enumeration.

exp = 'exp'

linear = 'linear'

log = 'log'

logit = 'logit'

negLog = 'negLog'

power = 'power'

class friendly_doe.doe_model.ResponseType(value)

Bases: Enum

An enumeration.

derived = 'derived'

regular = 'regular'

class friendly_doe.doe_model.Scaling(*, type: ScalingType)

Bases: BaseModel

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

type: ScalingType

class friendly_doe.doe_model.Scaling1(*, type: str, autoScaleModifier: float | None = 1.0)

Bases: BaseModel

autoScaleModifier: float | None

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

type: str

class friendly_doe.doe_model.ScalingType(value)

Bases: Enum

An enumeration.

midRange = 'midRange'

orthogonal = 'orthogonal'

unitVariance = 'unitVariance'

class friendly_doe.doe_model.Setpoints(*, optimalSetpoint: list[Any] | None = [])

Bases: BaseModel

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

optimalSetpoint: list[Any] | None

class friendly_doe.doe_model.Settings(*, alphaLevel: float | None = 0.0, coefficients: str | None = '', confidenceLevel: float | None = 0.0, toleranceProportion: float | None = 0.0, intervalType: str | None = '', power: float | None = 0.0, replicateTolerance: float | None = 0.0, residuals: str | None = '', r2: str | None = '')

Bases: BaseModel

alphaLevel: float | None

coefficients: str | None

confidenceLevel: float | None

intervalType: str | None

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

power: float | None

r2: str | None

replicateTolerance: float | None

residuals: str | None

toleranceProportion: float | None

class friendly_doe.doe_model.Transform(*, type: FactorTransformType, constants: Constants)

Bases: BaseModel

constants: Constants

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

type: FactorTransformType

class friendly_doe.doe_model.Transform1(*, type: ResponseTransformType, constants: Constants)

Bases: BaseModel

constants: Constants

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

type: ResponseTransformType

class friendly_doe.doe_model.Worksheet(*, columns: list[str], data: list[list[int | str | float | None]])

Bases: BaseModel

columns: list[str]

data: list[list[int | str | float | None]]

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].