AdjustedMatrix.py

import numpy as np
from obspy import UTCDateTime
from pydantic import BaseModel
from typing import Any, List, Optional

from .. import pydantic_utcdatetime
from .Metric import Metric


class AdjustedMatrix(BaseModel):
    """Attributes pertaining to adjusted(affine) matrices, applied by the AdjustedAlgorithm

    Attributes
    ----------
    matrix: affine matrix generated by Affine's calculate method
    pier_correction: pier correction generated by Affine's calculate method
    starttime: beginning of interval that matrix is valid for
    endtime: end of interval that matrix is valid for
    NOTE: valid intervals are only generated when bad data is encountered.
    Matrix is non-constrained otherwise
    """

    matrix: Any
    pier_correction: float
    metrics: Optional[List[Metric]] = None
    starttime: Optional[UTCDateTime] = None
    endtime: Optional[UTCDateTime] = None

    def process(self, values: List[List[float]], outchannels=["X", "Y", "Z", "F"]):
        """ Apply matrix to raw data. Apply pier correction to F when necessary """
        data = np.vstack([values[0:3]] + [np.ones_like(values[0])])
        adjusted = self.matrix @ data
        if "F" in outchannels:
            f = values[-1] + self.pier_correction
            adjusted = np.vstack([adjusted[0 : len(outchannels) - 1]] + [f])
        else:
            adjusted = adjusted[0 : len(outchannels)]
        return adjusted