Multi-step Amperometry

Create multi-step amperometry method parameters.

With Multistep amperometry you can specify the number of potential steps to apply and how long each step should last. Each step works exactly as a Chronoamperometry step. The current is continuously sampled with the specified interval time. A whole cycle of steps can be repeated several times.

Levels can be specified using pypalmsens.settings.ELevel.

Methods:

• to_dict –

  Return the technique instance as a new key/value dictionary mapping.

• from_dict –

  Structure technique instance from dict.

• from_method_id –

  Create new instance of appropriate technique from method ID.

Attributes:

• general (General) –

  Sets general/other settings.

• multiplexer (Multiplexer) –

  Set the multiplexer settings.

• data_processing (DataProcessing) –

  Set the data processing settings.

• ir_drop_compensation (IrDropCompensation) –

  Set the iR drop compensation settings.

• current_limits (CurrentLimits) –

  Set the current limit settings.

• post_measurement (PostMeasurement) –

  Set the post measurement settings.

• bipot (BiPot) –

  Set the bipot settings.

• pretreatment (Pretreatment) –

  Set the pretreatment settings.

• current_range (CurrentRange) –

  Set the autoranging current.

• id (Literal['ma']) –

  Unique method identifier.

• equilibration_time (float) –

  Equilibration time in s.

• interval_time (float) –

  The time between two samples in s.

• n_cycles (int) –

  Number of repetitions.

• levels (list[ELevel]) –

  The cto apply within a cycle.

• enable_bipot_current (bool) –

  Enable bipot current.

• record_auxiliary_input (bool) –

  Record auxiliary input.

• record_cell_potential (bool) –

  Record cell potential.

• record_we_potential (bool) –

  Record applied working electrode potential.

general: General = Field(default_factory=General)

multiplexer: Multiplexer = Field(default_factory=Multiplexer)

data_processing: DataProcessing = Field(default_factory=DataProcessing)

ir_drop_compensation: IrDropCompensation = Field(default_factory=IrDropCompensation)

current_limits: CurrentLimits = Field(default_factory=CurrentLimits)

post_measurement: PostMeasurement = Field(default_factory=PostMeasurement)

bipot: BiPot = Field(default_factory=BiPot)

pretreatment: Pretreatment = Field(default_factory=Pretreatment)

current_range: CurrentRange = Field(default_factory=CurrentRange)

id: Literal['ma'] = 'ma'

equilibration_time: float = 0.0

interval_time: float = 0.1

n_cycles: int = 1

levels: list[ELevel] = Field(default_factory=lambda: [ELevel()])

enable_bipot_current: bool = False

record_auxiliary_input: bool = False

record_cell_potential: bool = False

record_we_potential: bool = False

to_dict() -> dict[str, Any]

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def to_dict(self) -> dict[str, Any]:
    """Return the technique instance as a new key/value dictionary mapping."""
    return self.model_dump()

from_dict(obj: dict[str, Any]) -> BaseTechnique

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@classmethod
def from_dict(cls, obj: dict[str, Any]) -> BaseTechnique:
    """Structure technique instance from dict.

    Opposite of `.to_dict()`"""
    return cls.model_validate(obj)

from_method_id(id: str) -> BaseTechnique

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@classmethod
def from_method_id(cls, id: str) -> BaseTechnique:
    """Create new instance of appropriate technique from method ID."""
    new = cls._registry[id]
    return new()