Merge branch 'main' into fix_source_vis

Author: aknierim

.readthedocs.yaml

@@ -0,0 +1,21 @@
+version: 2
+
+build:
+  os: ubuntu-24.04
+  apt_packages:
+    - graphviz
+  tools:
+    python: "3.10"
+  jobs:
+    pre_create_environment:
+      - mkdir -p /home/docs/.casa/data
+
+python:
+  install:
+    - method: pip
+      path: .
+      extra_requirements:
+        - docs
+
+sphinx:
+  configuration: docs/conf.py

docs/changes/11.feature.rst

@@ -0,0 +1,2 @@
+- Add plotting submodule
+- Add ``radiotools.plotting.px2radec`` utility function

docs/changes/14.bugfix.rst

@@ -0,0 +1 @@
+Fix bug in ``radiotools.cleaning.WSClean`` that handled ``mf-weighting`` flag incorrectly

docs/changes/15.feature.rst

@@ -0,0 +1 @@
+- Added `min_alt` and `max_alt` parameters to be able to adapt to simulation or telescope altitude restrictions.

docs/changes/16.feature.rst

@@ -0,0 +1 @@
+- Added `desc_id` parameter to change what desc_id the gridded visibilities must have

docs/changes/17.optimization.rst

@@ -0,0 +1,2 @@
+- Add test for source visibility altitude restrictions in `tests/test_source_visibility.py`
+- Fix typo in `utils.py`

docs/changes/19.maintenance.rst

@@ -0,0 +1,5 @@
+- Remove forced rotation and inversion in plots
+- Change binning of grid
+- Use `numpy.float128` to ensure numerical stability
+- Add column name optional parameters to FITS import (default now `UU`, `VV`)
+- Remove flip and invert in `create_attributes` method

docs/changes/21.maintenance.rst

@@ -0,0 +1 @@
+- Update maintainers of the package

docs/changes/8.feature.rst

@@ -0,0 +1,5 @@
+- Add analysis submodule
+  - Add ``radiotools.analysis.get_source_rms`` function
+  - Add ``radiotools.analysis.dynamic_range`` function that calculates the dynamic range as a function of the maximum pixel value of an image and the RMS of the source
+
+- Add ``rms`` function to ``radiotools.utils``

pyproject.toml

@@ -9,6 +9,10 @@ readme = "README.rst"
 authors = [
     { name = "radionets-project developers" }
 ]
+maintainers = [
+  { name = "Anno Knierim", email = "[email protected]" },
+  { name = "Tom Groß", email = "[email protected]" },
+]
 license = { text = "MIT" }
 classifiers = [
     "Intended Audience :: Science/Research",
@@ -47,7 +51,26 @@ dev = [
 ]
 
 all = [
-    "radiotools[dev]"
+    "radiotools"
+]
+
+docs = [
+  "radiotools[all]",
+  "graphviz",
+  "ipython",
+  "jupyter",
+  "nbsphinx",
+  "notebook",
+  "numpydoc",
+  "pandas",
+  "pydata_sphinx_theme",
+  "pypandoc",
+  "sphinx",
+  "sphinx-design",
+  "sphinx_automodapi",
+  "sphinxcontrib-bibtex",
+  "tomli; python_version < '3.11'",
+  "toml"
 ]
 
 [project.urls]

radiotools/analysis/__init__.py

@@ -0,0 +1,3 @@
+from .analysis import dynamic_range, get_source_rms
+
+__all__ = ["dynamic_range", "get_source_rms"]

radiotools/analysis/analysis.py

@@ -0,0 +1,74 @@
+import torch
+from astropy.io import fits
+from numpy.typing import ArrayLike
+
+from radiotools.utils import rms
+
+
+def get_source_rms(image: ArrayLike, center: tuple[int, int], *, offset=75):
+    """Get the root mean square (RMS) of a given source.
+
+    Parameters
+    ----------
+    image : array_like, shape (N, M)
+        Array containing image data of the source.
+    center : tuple[int, int]
+        Tuple of the center coordinates where the RMS
+        is calculated for a region spanned by ``offset``.
+    offset : int, optional
+        Offset that spans a region around ``center``:
+
+        .. code::
+            x0 = center_x - offset
+            x1 = center_x + offset
+
+            y0 = center_y - offset
+            y1 = center_y + offset
+
+        Default: 75
+
+    Returns
+    -------
+    rms : float
+        RMS for the given source.
+    """
+    center_x = int(center[0])
+    center_y = int(center[1])
+
+    x0 = center_x - offset
+    x1 = center_x + offset
+
+    y0 = center_y - offset
+    y1 = center_y + offset
+
+    _rms = torch.from_numpy(rms(image[x0:x1, y0:y1]))
+
+    return torch.mean(_rms)
+
+
+def dynamic_range(path: str, *, offset: int = 75):
+    """Computes the dynamic range of a source.
+
+    Parameters
+    ----------
+    path : str or Path
+        Path to a FITS file containing image data of the source.
+    offset : int, optional
+        Offset for the region around the center pixel of the source.
+        Used to compute the RMS value of the source. Default: 75
+
+    Returns
+    -------
+    dr : float
+        Dynamic range of the source.
+    """
+    hdu = fits.open(path)
+
+    image = hdu[0].data[0, 0, ...]
+    center = hdu[0].header["CRPIX1"], hdu[0].header["CRPIX2"]
+
+    _rms = get_source_rms(image, center, offset=75)
+
+    dr = image.max() / _rms
+
+    return dr

radiotools/cleaning/clean.py

@@ -82,21 +82,35 @@ def __init__(
         _clean_config["auto-threshold"] = _clean_config.pop("auto_threshold")
         _clean_config["auto-mask"] = _clean_config.pop("auto_mask")
 
+        # We need to handle the case if size is an int and not a list.
+        # This assumes, however, that x- and y- size are the same
         if isinstance(_clean_config["size"], int):
             _clean_config["size"] = [_clean_config["size"]] * 2
 
+        # mf-weighting and no-mf-weighting are flags without arguments.
+        # Since the wrapper only takes the bool mf_weighting as input,
+        # we have to handle both cases and pass the respective WSClean
+        # flags with an empty string as "argument".
         if _clean_config["mf_weighting"] is False:
             del _clean_config["mf_weighting"]
             _clean_config["no-mf-weighting"] = ""
         else:
+            del _clean_config["mf_weighting"]
             _clean_config["mf-weighting"] = ""
 
+        # Same as with mf-weighting, WSClean has two flags -- verbose
+        # and quiet -- to handle output during cleaning. The wrapper
+        # only takes the bool verbose as input, as such we have to
+        # handle both cases.
         if _clean_config["verbose"] is False:
             del _clean_config["verbose"]
             _clean_config["quiet"] = ""
         else:
             del _clean_config["verbose"]
 
+        # multiscale is another case of a flag without any arguments.
+        # As such, we have to either delete the key and value pair,
+        # or replace the bool with an empty string.
         if _clean_config["multiscale"] is False:
             del _clean_config["multiscale"]
         else: