additional check around (0,) dim spectral axis (#88)

.pre-commit-config.yaml

@@ -1,14 +1,14 @@
 repos:
     - repo: https://github.com/pre-commit/pre-commit-hooks
-      rev: v5.0.0
+      rev: v6.0.0
       hooks:
         - id: trailing-whitespace
         - id: end-of-file-fixer
         - id: check-yaml
         - id: check-added-large-files
 
     - repo: https://github.com/astral-sh/ruff-pre-commit
-      rev: "v0.12.7"
+      rev: "v0.15.11"
       hooks:
         - id: ruff
           args: ["--fix", "--show-fixes"]

racs_tools/beamcon_3D.py

@@ -331,6 +331,9 @@ def _get_commonbeams(
         f"Expected target_beam to be type Beam or None, got {type(target_beam)}"
     )
 
+    logger.info("Finding common beam for all channels and cubes")
+    logger.info(f"Number of channels {nchans=}")
+
     if mode == "natural":
         big_beams = []
         for n in trange(
@@ -546,6 +549,7 @@ def _get_commonbeams(
             pa=commonbeams.pa * 0,
         )
 
+    logger.info(f"Number of common beams: {len(commonbeams)}")
     return commonbeams
 
 
@@ -765,10 +769,15 @@ def initfiles(
 
     ## Header
     spec_axis = wcs.spectral
-    crpix = int(spec_axis.wcs.crpix)
+    # account for either an float or array of single float. Anything else should fail!
+    crpix = (
+        int(np.squeeze(spec_axis.wcs.crpix))
+        if not np.isscalar(spec_axis.wcs.crpix)
+        else int(spec_axis.wcs.crpix)
+    )
     nchans = spec_axis.array_shape[0]
     assert nchans == len(commonbeams), (
-        "Number of channels in header and commonbeams do not match"
+        f"Number of channels {nchans=} in header and commonbeams {len(commonbeams)=} do not match"
     )
     chans = np.arange(nchans)
     if ref_chan is None:

racs_tools/convolve_uv.py

@@ -4,7 +4,7 @@
 __author__ = "Wasim Raja"
 
 import gc
-from typing import Literal, NamedTuple, Optional
+from typing import Literal, NamedTuple
 
 import numpy as np
 import scipy.signal
@@ -134,7 +134,7 @@ def convolve(
     new_beam: Beam,
     dx: u.Quantity,
     dy: u.Quantity,
-    cutoff: Optional[float] = None,
+    cutoff: float | None = None,
 ) -> ConvolutionResult:
     """Convolve by X-ing in the Fourier domain.
         - convolution with Gaussian kernels only
@@ -248,7 +248,7 @@ def convolve_scipy(
     new_beam: Beam,
     dx: u.Quantity,
     dy: u.Quantity,
-    cutoff: Optional[float] = None,
+    cutoff: float | None = None,
 ) -> ConvolutionResult:
     """Convolve using scipy's convolution
 
@@ -296,7 +296,7 @@ def convolve_astropy(
     new_beam: Beam,
     dx: u.Quantity,
     dy: u.Quantity,
-    cutoff: Optional[float] = None,
+    cutoff: float | None = None,
 ) -> ConvolutionResult:
     """Convolve using astropy's convolution
 
@@ -347,7 +347,7 @@ def convolve_astropy_fft(
     new_beam: Beam,
     dx: u.Quantity,
     dy: u.Quantity,
-    cutoff: Optional[float] = None,
+    cutoff: float | None = None,
 ) -> ConvolutionResult:
     """Convolve using astropy's FFT convolution
 
@@ -434,7 +434,7 @@ def get_convolving_beam(
     new_beam: Beam,
     dx: u.Quantity,
     dy: u.Quantity,
-    cutoff: Optional[float] = None,
+    cutoff: float | None = None,
 ) -> tuple[Beam, float]:
     """Get the beam to use for smoothing
 
@@ -502,7 +502,7 @@ def smooth(
     dx: u.Quantity,
     dy: u.Quantity,
     conv_mode: Literal["robust", "scipy", "astropy", "astropy_fft"] = "robust",
-    cutoff: Optional[float] = None,
+    cutoff: float | None = None,
 ) -> np.ndarray:
     """Apply smoothing to image in Jy/beam
 

racs_tools/getnoise_list.py

@@ -3,7 +3,6 @@
 
 import argparse
 import warnings
-from typing import Union
 
 import astropy.units as u
 import numpy as np
@@ -146,7 +145,7 @@ def main(
     blank: bool = False,
     cliplev: float = 5,
     iterate: int = 1,
-    outfile: Union[str, None] = None,
+    outfile: str | None = None,
     save_noise: bool = False,
 ) -> None:
     """Flag bad channels in Stokes Q and U cubes

racs_tools/logging.py

@@ -3,7 +3,6 @@
 import logging
 import multiprocessing as mp
 from logging.handlers import QueueHandler, QueueListener
-from typing import Optional
 
 logging.captureWarnings(True)
 
@@ -12,7 +11,7 @@
 
 
 def setup_logger(
-    filename: Optional[str] = None,
+    filename: str | None = None,
 ) -> tuple[logging.Logger, QueueListener, mp.Queue]:
     """Setup a logger
 

tests/test_spectral.py

@@ -0,0 +1,30 @@
+import numpy as np
+import pytest
+from astropy.io import fits
+from astropy.wcs import WCS
+
+
+@pytest.fixture
+def spec_axis() -> WCS:
+    header = fits.Header()
+    header["NAXIS"] = 1
+    header["NAXIS1"] = 288
+    header["CTYPE1"] = "FREQ"
+    header["CRVAL1"] = 800e6
+    header["CRPIX1"] = 1
+    header["CDELT1"] = 1e6
+    return WCS(header).spectral
+
+
+def test_crpix(spec_axis: WCS) -> None:
+    crpix = (
+        int(np.squeeze(spec_axis.wcs.crpix))
+        if not np.isscalar(spec_axis.wcs.crpix)
+        else int(spec_axis.wcs.crpix)
+    )
+    assert crpix == 1
+
+
+def test_nchan(spec_axis: WCS) -> None:
+    nchans = spec_axis.array_shape[0]
+    assert nchans == 288