Remove reoder imports it seems to clash with black.

.pre-commit-config.yaml

@@ -8,10 +8,6 @@ repos:
       - id: check-toml
       - id: end-of-file-fixer
       - id: requirements-txt-fixer
-  - repo: https://github.com/asottile/reorder_python_imports
-    rev: v3.12.0
-    hooks:
-      - id: reorder-python-imports
   - repo: https://github.com/PyCQA/doc8
     rev: v1.1.1
     hooks:

src/pyrvt/peak_calculators.py

@@ -8,8 +8,10 @@
 import ctypes
 import itertools
 import pathlib
-from abc import ABC, abstractmethod
-from typing import List, Tuple
+from abc import ABC
+from abc import abstractmethod
+from typing import List
+from typing import Tuple
 
 import numba
 import numpy as np
@@ -140,13 +142,10 @@ def calc_moments(
     moment : list
         Computed spectral moments.
     """
-
     squared_fa = np.square(fourier_amps)
 
     # Use trapzoidal integration to compute the requested moments.
-    moments = [
-        2.0 * trapz(freqs, np.power(2 * np.pi * freqs, o) * squared_fa) for o in orders
-    ]
+    moments = [2.0 * trapz(freqs, np.power(2 * np.pi * freqs, o) * squared_fa) for o in orders]
 
     return moments
 
@@ -164,12 +163,13 @@ class SquaredSpectrum:
         Amplitude of the Fourier amplitude spectrum.
     """
 
-    def __init__(self, freqs, fourier_amps):
+    def __init__(self, freqs: npt.ArrayLike, fourier_amps: npt.ArrayLike):
+        """Initialize SquaredSpectrum."""
         self._freqs = freqs
         self._squared_fa = np.square(fourier_amps)
         self._moments = {}
 
-    def moment(self, num):
+    def moment(self, num: int) -> float:
         """Compute the spectral moments.
 
         The spectral moment is computed using the squared Fourier amplitude
@@ -191,7 +191,14 @@ def moment(self, num):
 
         return moment
 
-    def moments(self, *nums):
+    def moments(self, *nums) -> List[float]:
+        """Return the computed moments.
+
+        Returns
+        -------
+        moments : list[float]
+            Computed spectral moments.
+        """
         return [self.moment(n) for n in nums]
 
 
@@ -379,9 +386,7 @@ def _calc_peak_factor(self, duration: float, **kwargs) -> float:
         bandwidth = np.sqrt(1 - (m1 * m1) / (m0 * m2))
         bandwidth_eff = bandwidth**1.2
 
-        num_zero_crossings = self.limited_num_zero_crossings(
-            duration * np.sqrt(m2 / m0) / np.pi
-        )
+        num_zero_crossings = self.limited_num_zero_crossings(duration * np.sqrt(m2 / m0) / np.pi)
         # The expected peak factor is computed as the integral of the
         # complementary CDF (1 - CDF(x)).
         peak_factor = quad(
@@ -399,9 +404,7 @@ def _calc_peak_factor(self, duration: float, **kwargs) -> float:
         return peak_factor
 
     @classmethod
-    def nonstationarity_factor(
-        cls, osc_damping: float, osc_freq: float, duration: float
-    ) -> float:
+    def nonstationarity_factor(cls, osc_damping: float, osc_freq: float, duration: float) -> float:
         """Compute nonstationarity factor to modify duration.
 
         Parameters
@@ -457,9 +460,7 @@ def _calc_peak_factor(self, duration: float, **kwargs) -> float:
         m0, m2 = self._spectrum.moments(0, 2)
 
         # Compute the number of zero crossings
-        num_zero_crossings = self.limited_num_zero_crossings(
-            duration * np.sqrt(m2 / m0) / np.pi
-        )
+        num_zero_crossings = self.limited_num_zero_crossings(duration * np.sqrt(m2 / m0) / np.pi)
 
         peak_factor = self.asymtotic_approx(num_zero_crossings)
 
@@ -593,9 +594,7 @@ def _calc_peak_factor(self, duration: float, **kwargs) -> float:
         osc_freq = kwargs.get("osc_freq", None)
         osc_damping = kwargs.get("osc_damping", None)
         if osc_freq and osc_damping:
-            peak_factor *= Vanmarcke1975.nonstationarity_factor(
-                osc_damping, osc_freq, duration
-            )
+            peak_factor *= Vanmarcke1975.nonstationarity_factor(osc_damping, osc_freq, duration)
 
         return peak_factor
 
@@ -645,9 +644,7 @@ def _calc_peak_factor(self, duration: float, **kwargs) -> float:
         # Compute the peak factor by the indefinite integral.
         peak_factor = (
             np.sqrt(2.0)
-            * quad(
-                _calc_cartwright_pf.ctypes, 0, np.inf, args=(num_extrema, bandwidth)
-            )[0]
+            * quad(_calc_cartwright_pf.ctypes, 0, np.inf, args=(num_extrema, bandwidth))[0]
         )
 
         return peak_factor
@@ -702,9 +699,7 @@ def _calc_duration_rms(self, duration, **kwargs):
             coef = 1.0 / 3.0
             # This equation was rewritten in Boore and Thompson (2012).
             foo = 1.0 / (osc_freq * duration)
-            dur_ratio = 1 + 1.0 / (2 * np.pi * osc_damping) * (
-                foo / (1 + coef * foo**power)
-            )
+            dur_ratio = 1 + 1.0 / (2 * np.pi * osc_damping) * (foo / (1 + coef * foo**power))
             duration *= dur_ratio
 
         return duration
@@ -760,9 +755,7 @@ def _calc_duration_rms(self, duration, **kwargs):
             # Same model as used in Boore and Joyner (1984). This equation was
             # rewritten in Boore and Thompson (2012).
             foo = 1.0 / (osc_freq * duration)
-            dur_ratio = 1 + 1.0 / (2 * np.pi * osc_damping) * (
-                foo / (1 + coef * foo**power)
-            )
+            dur_ratio = 1 + 1.0 / (2 * np.pi * osc_damping) * (foo / (1 + coef * foo**power))
             duration *= dur_ratio
 
         return duration
@@ -787,10 +780,7 @@ def _make_bt_interpolator(region, ref):
         Interpolator for the data.
 
     """
-
-    fpath = pathlib.Path(__file__).parent.joinpath(
-        "data", f"{region}_{ref}_trms4osc.pars.gz"
-    )
+    fpath = pathlib.Path(__file__).parent.joinpath("data", f"{region}_{ref}_trms4osc.pars.gz")
     d = np.rec.fromrecords(
         np.loadtxt(str(fpath), skiprows=4, usecols=range(9)),
         names="mag,dist,c1,c2,c3,c4,c5,c6,c7",
@@ -1005,9 +995,7 @@ def _calc_duration_rms(self, duration, **kwargs):
             m = self.COEFS.d * af_ratio + self.COEFS.e * af_ratio**2
             incr_max = c * np.exp(-duration / m)
 
-            incr = incr_max * np.exp(
-                -((np.log(osc_freq / modes_f)) ** 2) / (2 * self.COEFS.sd**2)
-            )
+            incr = incr_max * np.exp(-((np.log(osc_freq / modes_f)) ** 2) / (2 * self.COEFS.sd**2))
             duration_rms += incr.sum()
 
         return duration_rms

src/pyrvt/runner.py

@@ -7,14 +7,13 @@
 
 from pyrvt import __version__
 from pyrvt.motions import DEFAULT_CALC
-from pyrvt.tools import operation_fa2psa, operation_psa2fa
+from pyrvt.tools import operation_fa2psa
+from pyrvt.tools import operation_psa2fa
 
 parser = argparse.ArgumentParser(
     prog="pyrvt", description="Compute response or Fourier amplitude spectra using RVT."
 )
-parser.add_argument(
-    "--version", action="version", version="%(prog)s version " + str(__version__)
-)
+parser.add_argument("--version", action="version", version="%(prog)s version " + str(__version__))
 parser.add_argument(
     "operation",
     help="""Operation to be performed: [psa2fa] converts from pseudo-spectral
@@ -72,13 +71,9 @@ def main():
     args = parser.parse_args()
 
     if args.operation == "psa2fa":
-        operation_psa2fa(
-            args.input, args.output, args.damping, args.method, args.fixed_spacing
-        )
+        operation_psa2fa(args.input, args.output, args.damping, args.method, args.fixed_spacing)
     elif args.operation == "fa2psa":
-        operation_fa2psa(
-            args.input, args.output, args.damping, args.method, args.fixed_spacing
-        )
+        operation_fa2psa(args.input, args.output, args.damping, args.method, args.fixed_spacing)
     else:
         raise NotImplementedError
 

src/pyrvt/tools.py

@@ -5,13 +5,14 @@
 import functools
 import multiprocessing
 from pathlib import Path
+from typing import List
 
 import numpy as np
 import numpy.typing as npt
 import pyexcel
-
 from pyrvt import motions
-from pyrvt.peak_calculators import get_peak_calculator, get_region
+from pyrvt.peak_calculators import get_peak_calculator
+from pyrvt.peak_calculators import get_region
 
 PARAMETER_NAMES = [
     ("magnitude", "Magnitude"),
@@ -23,13 +24,12 @@
 ]
 
 
-def get_fpaths(s):
-    return Path(".").glob(s) if "*" in s else [Path(s)]
+def get_fpaths(pat: str) -> List[Path]:
+    """Iterate over file paths."""
+    return Path(".").glob(pat) if "*" in pat else [Path(pat)]
 
 
-def read_events(
-    fpath: str | Path, response_type: str
-) -> tuple[str, np.ndarray, list[dict]]:
+def read_events(fpath: str | Path, response_type: str) -> tuple[str, np.ndarray, list[dict]]:
     """Read data from the file an Excel work book.
 
     Parameters
@@ -206,9 +206,7 @@ def calc_compatible_spectra(
     """
     target_freqs = 1.0 / periods
     with multiprocessing.Pool() as pool:
-        results = pool.map(
-            functools.partial(_calc_fa, target_freqs, damping, method), events
-        )
+        results = pool.map(functools.partial(_calc_fa, target_freqs, damping, method), events)
 
     # Copy values back into the dictionary
     modified = []
@@ -234,7 +232,7 @@ def operation_psa2fa(
     fixed_spacing: bool = True,
     verbose: bool = True,
 ):
-    """Compute the accel. response spectrum from a Fourier amplitude spectrum.
+    """Compute the acceleration response spectrum from a Fourier amplitude spectrum.
 
     Parameters
     ----------
@@ -256,7 +254,6 @@ def operation_psa2fa(
         Print status of calculation.
 
     """
-
     dst = Path(dst)
     dst.mkdir(parents=True, exist_ok=True)
 
@@ -275,9 +272,7 @@ def operation_psa2fa(
             periods = _periods
 
         # Compute the FA from the PSA
-        freqs, events = calc_compatible_spectra(
-            method, periods, events, damping=damping
-        )
+        freqs, events = calc_compatible_spectra(method, periods, events, damping=damping)
 
         basename = fpath.stem.rsplit("_", 1)[0]