Source code for psc_sim.simulation.types

"""Shared types for I–V sweeps and simulation results."""

from __future__ import annotations

from dataclasses import dataclass

import numpy as np




@dataclass(frozen=True)
class SweepSpec:
    v_min: float = -0.3
    v_max: float = 1.25
    step: float = 0.01





@dataclass
class IVResult:
    V: np.ndarray
    I: np.ndarray
    P: np.ndarray
    truncated: bool = False



    @classmethod
    def from_arrays(cls, V: np.ndarray, I: np.ndarray, P: np.ndarray) -> IVResult:
        return cls(V=V, I=I, P=P, truncated=bool(np.any(~np.isfinite(I))))






@dataclass(frozen=True)
class RsFitMask:
    """Rs linear-fit interval on the I_mA axis (generation-positive convention)."""

    i_mA_lo: float
    i_mA_hi: float
    positive_generation: bool = True





@dataclass(frozen=True)
class TranSpec:
    """LTspice .tran step/stop and Vbias PULSE (times in seconds; formatted with m = ms)."""

    t_step_s: float = 0.1e-3
    t_stop_s: float = 10e-3
    pulse_v_low: float = 0.0
    pulse_v_high: float = 0.5
    pulse_delay_s: float = 1e-3
    pulse_rise_s: float = 0.1e-3
    pulse_fall_s: float = 0.1e-3
    pulse_on_s: float = 5e-3
    pulse_period_s: float = 10e-3





@dataclass
class MeasuredEIS:
    """Measured EIS curve loaded from CSV (freq_hz, Re(Z), Im(Z))."""

    freqs_hz: np.ndarray
    zre: np.ndarray
    zim: np.ndarray

    @classmethod
    def from_arrays(
        cls,
        freqs_hz: np.ndarray,
        zre: np.ndarray,
        zim: np.ndarray,
    ) -> MeasuredEIS:
        return cls(
            freqs_hz=np.asarray(freqs_hz, dtype=float),
            zre=np.asarray(zre, dtype=float),
            zim=np.asarray(zim, dtype=float),
        )





@dataclass
class TRANResult:
    """Transient waveform from LTspice .tran."""

    t: np.ndarray
    V: np.ndarray
    I: np.ndarray