lmao

Author: nabobalis

.ruff.toml

@@ -14,7 +14,6 @@ select = [
   "W",
   "UP",
   "PT",
-  "N",
   "BLE",
   "A",
   "C4",

docs/conf.py

@@ -53,7 +53,7 @@
 automodapi_toctreedirnm = "generated/api"
 
 # Add any paths that contain templates here, relative to this directory.
-# templates_path = ["_templates"]  # NOQA: ERA001
+# templates_path = ["_templates"]
 
 # List of patterns, relative to source directory, that match files and
 # directories to ignore when looking for source files.
@@ -103,7 +103,7 @@
 # Add any paths that contain custom static files (such as style sheets) here,
 # relative to this directory. They are copied after the builtin static files,
 # so a file named "default.css" will overwrite the builtin "default.css".
-# html_static_path = ["_static"]  # NOQA: ERA001
+# html_static_path = ["_static"]
 
 # By default, when rendering docstrings for classes, sphinx.ext.autodoc will
 # make docs with the class-level docstring and the class-method docstrings,

pytest.ini

@@ -48,3 +48,4 @@ filterwarnings =
     ignore: invalid value encountered in true_divide
     # https://github.com/pytest-dev/pytest-cov/issues/557
     ignore:The --rsyncdir command line argument and rsyncdirs config variable are deprecated.:DeprecationWarning
+    ignore:Please use astropy.wcs.wcsapi.high_level_api.values_to_high_level_objects:DeprecationWarning

sunraster/extern/meta.py

@@ -78,7 +78,7 @@ def __init__(self, header=None, comments=None, axes=None, data_shape=None):
             axes = dict(axes)
             if not set(axes.keys()).issubset(set(header_keys)):
                 raise ValueError("All axes must correspond to a value in header under the same key.")
-            self._axes = dict([(key, self._sanitize_axis_value(axis, header[key], key)) for key, axis in axes.items()])
+            self._axes = {key: self._sanitize_axis_value(axis, header[key], key) for key, axis in axes.items()}
 
     def _sanitize_axis_value(self, axis, value, key):
         if axis is None:
@@ -100,7 +100,7 @@ def _sanitize_axis_value(self, axis, value, key):
         shape_error_msg = f"{key} must have shape {tuple(self.shape[axis])} as it is associated with axes {axis}"
         if len(axis) == 1 and not hasattr(value, "__len__") or len(axis) != 1 and not hasattr(value, "shape"):
             raise TypeError(shape_error_msg)
-        elif len(axis) == 1:
+        if len(axis) == 1:
             meta_shape = (len(value),)
         else:
             meta_shape = value.shape
@@ -189,51 +189,50 @@ def __getitem__(self, item):
         # If item is single string, slicing is simple.
         if isinstance(item, str):
             return super().__getitem__(item)
-        elif self.shape is None:
+        if self.shape is None:
             raise TypeError("Meta object does not have a shape and so cannot be sliced.")
-        else:
-            new_meta = copy.deepcopy(self)
-            # Convert item to array of ints and slices for consistent behaviour.
-            if isinstance(item, (numbers.Integral, slice)):
-                item = [item]
-            item = np.array(list(item) + [slice(None)] * (len(self.shape) - len(item)), dtype=object)
-
-            # Edit data shape and calculate which axis will be dropped.
-            dropped_axes = np.zeros(len(self.shape), dtype=bool)
-            new_shape = new_meta.shape
-            for i, axis_item in enumerate(item):
-                if isinstance(axis_item, numbers.Integral):
-                    dropped_axes[i] = True
-                elif isinstance(axis_item, slice):
-                    start = axis_item.start
-                    if start is None:
-                        start = 0
-                    if start < 0:
-                        start = self.shape[i] - start
-                    stop = axis_item.stop
-                    if stop is None:
-                        stop = self.shape[i]
-                    if stop < 0:
-                        stop = self.shape[i] - stop
-                    new_shape[i] = stop - start
-                else:
-                    raise TypeError("Unrecognized slice type. " "Must be an int, slice and tuple of the same.")
-            new_meta._data_shape = new_shape[np.invert(dropped_axes)]
-
-            # Calculate the cumulative number of dropped axes.
-            cumul_dropped_axes = np.cumsum(dropped_axes)
-
-            # Slice all metadata associated with axes.
-            for key, value in self.items():
-                axis = self.axes.get(key, None)
-                if axis is not None:
-                    new_item = tuple(item[axis])
-                    new_value = value[new_item[0]] if len(new_item) == 1 else value[new_item]
-                    new_axis = np.array([-1 if isinstance(i, numbers.Integral) else a for i, a in zip(new_item, axis)])
-                    new_axis -= cumul_dropped_axes[axis]
-                    new_axis = new_axis[new_axis >= 0]
-                    if len(new_axis) == 0:
-                        new_axis = None
-                    new_meta.add(key, new_value, self.comments.get(key, None), new_axis, overwrite=True)
-
-            return new_meta
+        new_meta = copy.deepcopy(self)
+        # Convert item to array of ints and slices for consistent behaviour.
+        if isinstance(item, (numbers.Integral, slice)):
+            item = [item]
+        item = np.array(list(item) + [slice(None)] * (len(self.shape) - len(item)), dtype=object)
+
+        # Edit data shape and calculate which axis will be dropped.
+        dropped_axes = np.zeros(len(self.shape), dtype=bool)
+        new_shape = new_meta.shape
+        for i, axis_item in enumerate(item):
+            if isinstance(axis_item, numbers.Integral):
+                dropped_axes[i] = True
+            elif isinstance(axis_item, slice):
+                start = axis_item.start
+                if start is None:
+                    start = 0
+                if start < 0:
+                    start = self.shape[i] - start
+                stop = axis_item.stop
+                if stop is None:
+                    stop = self.shape[i]
+                if stop < 0:
+                    stop = self.shape[i] - stop
+                new_shape[i] = stop - start
+            else:
+                raise TypeError("Unrecognized slice type. " "Must be an int, slice and tuple of the same.")
+        new_meta._data_shape = new_shape[np.invert(dropped_axes)]
+
+        # Calculate the cumulative number of dropped axes.
+        cumul_dropped_axes = np.cumsum(dropped_axes)
+
+        # Slice all metadata associated with axes.
+        for key, value in self.items():
+            axis = self.axes.get(key, None)
+            if axis is not None:
+                new_item = tuple(item[axis])
+                new_value = value[new_item[0]] if len(new_item) == 1 else value[new_item]
+                new_axis = np.array([-1 if isinstance(i, numbers.Integral) else a for i, a in zip(new_item, axis)])
+                new_axis -= cumul_dropped_axes[axis]
+                new_axis = new_axis[new_axis >= 0]
+                if len(new_axis) == 0:
+                    new_axis = None
+                new_meta.add(key, new_value, self.comments.get(key, None), new_axis, overwrite=True)
+
+        return new_meta

sunraster/extern/tests/test_meta.py

@@ -26,7 +26,7 @@ def assert_metas_equal(test_input, expected_output):
         for test_value, expected_value in zip(test_input.values(), expected_output.values()):
             try:
                 assert test_value == expected_value
-            except ValueError as err:
+            except ValueError as err:  # NOQA: PERF203
                 if multi_element_msg in err.args[0]:
                     assert np.allclose(test_value, expected_value)
         # Check axes are the same.
@@ -109,18 +109,15 @@ def test_slice_away_independent_axis(basic_meta):
     axes["c"] -= 1
     axes["d"] -= 1
     shape = meta.shape[1:]
-    print(values, comments, axes, shape)
     expected = Meta(values, comments, axes, shape)
     # Compare output and expected.
     assert_metas_equal(output, expected)
 
 
 def test_slice_dependent_axes(basic_meta):
     meta = basic_meta
-    print(meta["a"])
     # Get output
     output = meta[:, 1:3, 1]
-    print(meta["a"])
     # Build expected result.
     values = dict(list(meta.items()))
     values["c"] = values["c"][1:3, 1]
@@ -175,13 +172,13 @@ def test_add_overwrite(basic_meta):
 
 def test_add_overwrite_error(basic_meta):
     meta = basic_meta
-    with pytest.raises(KeyError):
+    with pytest.raises(KeyError, match="A"):
         meta.add("a", "world", None, None)
 
 
 def test_add_axis_without_shape(no_shape_meta):
     meta = no_shape_meta
-    with pytest.raises(TypeError):
+    with pytest.raises(TypeError, match="A"):
         meta.add("z", [100], axis=0)
 
 

sunraster/instr/spice.py

@@ -62,7 +62,7 @@ def read_spice_l2_fits(filenames, windows=None, memmap=True, read_dumbbells=Fals
     if len(filenames) > 1:
         # Wrap windows from first file in lists
         # so windows from other files can be appended.
-        cube_lists = dict([(key, [value]) for key, value in first_cubes.items()])
+        cube_lists = {key: [value] for key, value in first_cubes.items()}
         # Get info from first file for consistency checks between files.
         first_meta = _get_meta_from_last_added(cube_lists)
         first_obs_id = _get_obsid(first_meta)
@@ -79,7 +79,7 @@ def read_spice_l2_fits(filenames, windows=None, memmap=True, read_dumbbells=Fals
                     output=cube_lists,
                     spice_id=first_obs_id,
                 )
-            except ValueError as err:
+            except ValueError as err:  # NOQA: PERF203
                 err_message = err.args[0]
                 if INCORRECT_OBSID_MESSAGE in err_message:
                     this_obs_id = err_message.split()[-1]
@@ -291,7 +291,7 @@ def __str__(self):
         )
 
     def __repr__(self):
-        return f"{object.__repr__(self)}\n{str(self)}"
+        return f"{object.__repr__(self)}\n{self!s}"
 
     # ---------- Inherited ABC properties ----------
     @property

sunraster/instr/tests/test_spice.py

@@ -1,5 +1,3 @@
-import os.path
-
 import numpy as np
 import pytest
 
@@ -13,7 +11,7 @@
 
 from sunraster import RasterSequence, SpectrogramCube, SpectrogramSequence
 from sunraster.instr.spice import SPICEMeta, read_spice_l2_fits
-from sunraster.tests import test_data_dir
+from sunraster.tests import TEST_DATA_PATH
 
 READ_SPICE_L2_FITS_RETURN_TYPE = NDCollection
 SPECTRAL_WINDOW = ("WINDOW0_74.73", "Extension name")
@@ -53,35 +51,35 @@
 @pytest.fixture
 def spice_fits_header():
     hdr = fits.Header()
-    hdr.append(tuple(["EXTNAME"] + list(SPECTRAL_WINDOW)))
-    hdr.append(tuple(["DETECTOR"] + list(DETECTOR)))
-    hdr.append(tuple(["INSTRUME"] + list(INSTRUMENT)))
-    hdr.append(tuple(["OBSRVTRY"] + list(OBSERVATORY)))
-    hdr.append(tuple(["LEVEL"] + list(PROCESSING_LEVEL)))
-    hdr.append(tuple(["RSUN_REF"] + list(RSUN_METERS)))
-    hdr.append(tuple(["RSUN_ARC"] + list(RSUN_ANGULAR)))
-    hdr.append(tuple(["OBS_ID"] + list(OBSERVING_MODE_ID)))
-    hdr.append(tuple(["OBS_VR"] + list(OBSERVATORY_RADIAL_VELOCITY)))
-    hdr.append(tuple(["DSUN_OBS"] + list(DISTANCE_TO_SUN)))
-    hdr.append(tuple(["DATE-OBS"] + list(DATE_REFERENCE)))
-    hdr.append(tuple(["DATE-BEG"] + list(DATE_START)))
-    hdr.append(tuple(["DATE-END"] + list(DATE_END)))
-    hdr.append(tuple(["HGLN_OBS"] + list(HGLN_OBS)))
-    hdr.append(tuple(["HGLT_OBS"] + list(HGLT_OBS)))
-    hdr.append(tuple(["SPIOBSID"] + list(SPICE_OBSERVING_MODE_ID)))
-    hdr.append(tuple(["DARKMAP"] + list(DARKMAP)))
-    hdr.append(tuple(["BLACKLEV"] + list(BLACKLEV)))
-    hdr.append(tuple(["WIN_TYPE"] + list(WINDOW_TYPE)))
-    hdr.append(tuple(["WINTABID"] + list(WINDOW_TABLE_ID)))
-    hdr.append(tuple(["SLIT_ID"] + list(SLIT_ID)))
-    hdr.append(tuple(["SLIT_WID"] + list(SLIT_WIDTH)))
-    hdr.append(tuple(["DUMBBELL"] + list(DUMBBELL)))
-    hdr.append(tuple(["SOLAR_B0"] + list(SOLAR_B0)))
-    hdr.append(tuple(["SOLAR_P0"] + list(SOLAR_P0)))
-    hdr.append(tuple(["SOLAR_EP"] + list(SOLAR_EP)))
-    hdr.append(tuple(["CAR_ROT"] + list(CARRINGTON_ROTATION_NUMBER)))
-    hdr.append(tuple(["DATE_EAR"] + list(DATE_START_EARTH)))
-    hdr.append(tuple(["DATE_SUN"] + list(DATE_START_SUN)))
+    hdr.append(("EXTNAME", *list(SPECTRAL_WINDOW)))
+    hdr.append(("DETECTOR", *list(DETECTOR)))
+    hdr.append(("INSTRUME", *list(INSTRUMENT)))
+    hdr.append(("OBSRVTRY", *list(OBSERVATORY)))
+    hdr.append(("LEVEL", *list(PROCESSING_LEVEL)))
+    hdr.append(("RSUN_REF", *list(RSUN_METERS)))
+    hdr.append(("RSUN_ARC", *list(RSUN_ANGULAR)))
+    hdr.append(("OBS_ID", *list(OBSERVING_MODE_ID)))
+    hdr.append(("OBS_VR", *list(OBSERVATORY_RADIAL_VELOCITY)))
+    hdr.append(("DSUN_OBS", *list(DISTANCE_TO_SUN)))
+    hdr.append(("DATE-OBS", *list(DATE_REFERENCE)))
+    hdr.append(("DATE-BEG", *list(DATE_START)))
+    hdr.append(("DATE-END", *list(DATE_END)))
+    hdr.append(("HGLN_OBS", *list(HGLN_OBS)))
+    hdr.append(("HGLT_OBS", *list(HGLT_OBS)))
+    hdr.append(("SPIOBSID", *list(SPICE_OBSERVING_MODE_ID)))
+    hdr.append(("DARKMAP", *list(DARKMAP)))
+    hdr.append(("BLACKLEV", *list(BLACKLEV)))
+    hdr.append(("WIN_TYPE", *list(WINDOW_TYPE)))
+    hdr.append(("WINTABID", *list(WINDOW_TABLE_ID)))
+    hdr.append(("SLIT_ID", *list(SLIT_ID)))
+    hdr.append(("SLIT_WID", *list(SLIT_WIDTH)))
+    hdr.append(("DUMBBELL", *list(DUMBBELL)))
+    hdr.append(("SOLAR_B0", *list(SOLAR_B0)))
+    hdr.append(("SOLAR_P0", *list(SOLAR_P0)))
+    hdr.append(("SOLAR_EP", *list(SOLAR_EP)))
+    hdr.append(("CAR_ROT", *list(CARRINGTON_ROTATION_NUMBER)))
+    hdr.append(("DATE_EAR", *list(DATE_START_EARTH)))
+    hdr.append(("DATE_SUN", *list(DATE_START_SUN)))
     return hdr
 
 
@@ -101,20 +99,21 @@ def spice_rasdb_filename(tmp_path):
 
     A new FITS file is saved in a tmp file path.
     """
+    rng_gen = np.random.default_rng()
     filename = "solo_L2_spice-n-ras-db_20200602T081733_V01_12583760-000.fits"
-    with fits.open(os.path.join(test_data_dir, filename)) as hdulist:
+    with fits.open(TEST_DATA_PATH / filename) as hdulist:
         new_hdulist = fits.HDUList()
-        new_hdulist.append(fits.PrimaryHDU(np.random.rand(1, 48, 832, 30), header=hdulist[0].header))
-        new_hdulist.append(fits.ImageHDU(np.random.rand(1, 48, 832, 30), header=hdulist[1].header))
-        new_hdulist.append(fits.ImageHDU(np.random.rand(1, 56, 64, 30), header=hdulist[2].header))
-        new_hdulist.append(fits.ImageHDU(np.random.rand(1, 56, 64, 30), header=hdulist[3].header))
+        new_hdulist.append(fits.PrimaryHDU(rng_gen.random((1, 48, 832, 30)), header=hdulist[0].header))
+        new_hdulist.append(fits.ImageHDU(rng_gen.random((1, 48, 832, 30)), header=hdulist[1].header))
+        new_hdulist.append(fits.ImageHDU(rng_gen.random((1, 56, 64, 30)), header=hdulist[2].header))
+        new_hdulist.append(fits.ImageHDU(rng_gen.random((1, 56, 64, 30)), header=hdulist[3].header))
         new_hdulist.append(hdulist[-1])
         tmp_spice_path = tmp_path / "spice"
-        if not os.path.exists(tmp_spice_path):
+        if not tmp_spice_path.exists():
             tmp_spice_path.mkdir()
-        new_filename = os.path.join(tmp_spice_path, filename)
+        new_filename = tmp_spice_path / filename
         new_hdulist.writeto(new_filename, overwrite=True)
-    return new_filename
+    return str(new_filename)
 
 
 @pytest.fixture
@@ -124,16 +123,17 @@ def spice_sns_filename(tmp_path):
 
     A new FITS file is saved in a tmp file path.
     """
+    rng_gen = np.random.default_rng()
     filename = "solo_L2_spice-n-sit_20200620T235901_V01_16777431-000.fits"
-    with fits.open(os.path.join(test_data_dir, filename)) as hdulist:
+    with fits.open(TEST_DATA_PATH / filename) as hdulist:
         new_hdulist = fits.HDUList()
-        new_hdulist.append(fits.PrimaryHDU(np.random.rand(32, 48, 1024, 1), header=hdulist[0].header))
-        new_hdulist.append(fits.ImageHDU(np.random.rand(32, 48, 1024, 1), header=hdulist[1].header))
+        new_hdulist.append(fits.PrimaryHDU(rng_gen.random((32, 48, 1024, 1)), header=hdulist[0].header))
+        new_hdulist.append(fits.ImageHDU(rng_gen.random((32, 48, 1024, 1)), header=hdulist[1].header))
         new_hdulist.append(hdulist[-1])
         tmp_spice_path = tmp_path / "spice"
-        if not os.path.exists(tmp_spice_path):
+        if not tmp_spice_path.exists():
             tmp_spice_path.mkdir()
-        new_filename = os.path.join(tmp_spice_path, filename)
+        new_filename = tmp_spice_path / filename
         new_hdulist.writeto(new_filename, output_verify="fix+ignore", overwrite=True)
     return new_filename
 
@@ -345,6 +345,6 @@ def test_read_spice_l2_fits_multiple_files_dumbbells(spice_rasdb_filename):
 
 
 def test_read_spice_l2_fits_incompatible_files(spice_rasdb_filename, spice_sns_filename):
-    with pytest.raises(ValueError):
-        filenames = [spice_rasdb_filename, spice_sns_filename]
+    filenames = [spice_rasdb_filename, spice_sns_filename]
+    with pytest.raises(ValueError, match="A"):
         read_spice_l2_fits(filenames)