Merge pull request #241 from discos/fix_recent_numpy

Fix issues with recent versions of Python and dependencies

.github/workflows/ci_tests.yml

@@ -103,13 +103,13 @@ jobs:
             toxenv: black
             experimental: false
 
-          - name: Python 3.10 with all optional dependencies and coverage checking
+          - name: Python 3.11 with all optional dependencies and coverage checking
             os: ubuntu-latest
-            python: '3.10'
-            toxenv: py310-test-alldeps-cov
+            python: '3.11'
+            toxenv: py311-test-alldeps-cov
             experimental: false
 
-          - name: OS X - Python 3.8 with all optional dependencies
+          - name: OS X - Python 3.8 with all optional dependencies at their 3.8-compatible versions
             os: macos-latest
             python: '3.8'
             toxenv: py38-test-alldeps
@@ -121,10 +121,10 @@ jobs:
             toxenv: py310-test-alldeps
             experimental: false
 
-          - name: Python 3.11 with latest dev versions of key dependencies
+          - name: Python 3.12 with latest dev versions of key dependencies
             os: ubuntu-latest
-            python: '3.11'
-            toxenv: py311-test-devdeps
+            python: '3.12'
+            toxenv: py312-test-devdeps
             experimental: true
 
     steps:

docs/changes/241.trivial.rst

@@ -0,0 +1 @@
+Update dependencies

srttools/__init__.py

@@ -23,11 +23,8 @@ def warning_on_one_line(message, category, filename, lineno, line=None):
 
 warnings.formatwarning = warning_on_one_line
 
-# warnings.filterwarnings("error", category=np.VisibleDeprecationWarning)
-# warnings.filterwarnings("error", ".*")
 warnings.filterwarnings("once", category=UserWarning)
 warnings.filterwarnings("once", category=DeprecationWarning)
-warnings.filterwarnings("once", category=np.VisibleDeprecationWarning)
 warnings.filterwarnings("ignore", "table path was not set via the path= ")
 
 __all__ = []

srttools/converters/classfits.py

@@ -57,7 +57,6 @@
 
 """
 
-
 from astropy.io import fits
 from astropy.table import Table, vstack
 from astropy.time import Time
@@ -338,21 +337,18 @@ def find_cycles(table, list_of_keys):
     >>> list_of_keys = ['A', 'B']
     >>> new_table = find_cycles(table, list_of_keys) # doctest:+ELLIPSIS
     -etc-
-    >>> np.all(new_table['CYCLE'] == [0, 0, 0, 0, 1, 1, 1, 1])
-    True
+    >>> assert np.all(new_table['CYCLE'] == [0, 0, 0, 0, 1, 1, 1, 1])
     >>> table = Table(data=[[0, 0, 1, 1, 0, 0, 1, 1],
     ...                     [0, 1, 0, 1, 0, 1, 0, 1]], names=['A', 'B'])
     >>> list_of_keys = ['A', 'B']
     >>> new_table = find_cycles(table, list_of_keys) # doctest:+ELLIPSIS
     -etc-
-    >>> np.all(new_table['CYCLE'] == [0, 0, 0, 0, 1, 1, 1, 1])
-    True
+    >>> assert np.all(new_table['CYCLE'] == [0, 0, 0, 0, 1, 1, 1, 1])
     >>> table = Table(data=[[0, 1, 0, 1], [1, 0, 1, 0]], names=['A', 'B'])
     >>> list_of_keys = ['A', 'B']
     >>> new_table = find_cycles(table, list_of_keys) # doctest:+ELLIPSIS
     -etc-
-    >>> np.all(new_table['CYCLE'] == [0, 0, 1, 1])
-    True
+    >>> assert np.all(new_table['CYCLE'] == [0, 0, 1, 1])
     """
     binary_values = 10 ** np.arange(len(list_of_keys), dtype=int)
     table["BINARY_COL"] = np.zeros(len(table), dtype=int)

srttools/converters/sdfits.py

@@ -232,10 +232,8 @@ def _get_empty_array(length, dim):
     """
     Examples
     --------
-    >>> np.all(_get_empty_array(10, "0")[1].flatten() == np.zeros(10))
-    True
-    >>> np.all(_get_empty_array(10, "(2,2)")[1].flatten() == np.zeros(40))
-    True
+    >>> assert np.all(_get_empty_array(10, "0")[1].flatten() == np.zeros(10))
+    >>> assert np.all(_get_empty_array(10, "(2,2)")[1].flatten() == np.zeros(40))
 
     """
 

srttools/destripe.py

@@ -32,18 +32,14 @@ def mask_zeros(image, expo=None, npix_tol=None):
     >>> import numpy as np
     >>> img = [[0, 1, 1], [0, 1, 1], [1, 1, 1]]
     >>> masked_image, mask = mask_zeros(img, expo=img, npix_tol=1)
-    >>> np.all(masked_image == [[1, 1], [1, 1], [1, 1]])
-    True
-    >>> np.all(mask == [[False, True, True], [False, True, True],
+    >>> assert np.all(masked_image == [[1, 1], [1, 1], [1, 1]])
+    >>> assert np.all(mask == [[False, True, True], [False, True, True],
     ...                 [False, True, True]])
-    True
     >>> masked_image, mask = mask_zeros(img, npix_tol=2)
-    >>> np.all(masked_image == img)
-    True
+    >>> assert np.all(masked_image == img)
     >>> img = [[0, 0, 0], [1, 1, 1], [1, 1, 1]]
     >>> masked_image, mask = mask_zeros(img, npix_tol=1)
-    >>> np.all(masked_image == [[1, 1, 1], [1, 1, 1]])
-    True
+    >>> assert np.all(masked_image == [[1, 1, 1], [1, 1, 1]])
     """
     image = np.asarray(image)
     mask = np.ones(image.shape, dtype=bool)
@@ -78,14 +74,11 @@ def clip_and_smooth(img, clip_sigma=3, smooth_window=10, direction=0):
     Examples
     --------
     >>> img = np.zeros((2,2))
-    >>> np.all(clip_and_smooth(img, smooth_window=(5, 5)) == img)
-    True
+    >>> assert np.all(clip_and_smooth(img, smooth_window=(5, 5)) == img)
     >>> img = np.array([[0, 0], [1, 1]])
-    >>> np.all(clip_and_smooth(img, direction=0) == img)
-    True
+    >>> assert np.all(clip_and_smooth(img, direction=0) == img)
     >>> img = np.array([[0, 1], [0, 1]])
-    >>> np.all(clip_and_smooth(img, direction=1) == img)
-    True
+    >>> assert np.all(clip_and_smooth(img, direction=1) == img)
     >>> img = np.array([[1, 1.], [8., 1]])
     >>> np.allclose(clip_and_smooth(img, clip_sigma=1, smooth_window=0),
     ...             [[1, 1], [3.0310889132455352, 1]])

srttools/imager.py

@@ -11,7 +11,7 @@
 import traceback
 import copy
 import functools
-from datetime import datetime
+from datetime import datetime, timezone
 from collections.abc import Iterable
 
 from scipy.stats import binned_statistic_2d
@@ -1483,7 +1483,7 @@ def save_ds9_images(
             warnings.warn("Azimuth is wrapping around 0. Beware.")
 
         header["CREATOR"] = "SDT"
-        ut = Time(datetime.utcnow(), scale="utc")
+        ut = Time(datetime.now(timezone.utc), scale="utc")
         header["COMMENT"] = f"Made with the SRT Single-Dish Tools on UT {ut.fits}"
         hdu = fits.PrimaryHDU(header=header)
         hdulist.append(hdu)

srttools/io.py

@@ -1,4 +1,5 @@
 """Input/output functions."""
+
 import astropy.io.fits as fits
 from astropy.table import Table
 import numpy as np
@@ -236,9 +237,9 @@ def observing_angle(rest_angle, derot_angle):
 
     Examples
     --------
-    >>> observing_angle(0 * u.rad, TWOPI * u.rad).to(u.rad).value
+    >>> float(observing_angle(0 * u.rad, TWOPI * u.rad).to(u.rad).value)
     0.0
-    >>> observing_angle(0, TWOPI).to(u.rad).value
+    >>> float(observing_angle(0, TWOPI).to(u.rad).value)
     0.0
     """
     if not hasattr(rest_angle, "unit"):
@@ -375,10 +376,8 @@ def is_close_to_sun(ra, dec, obstime, tolerance=3 * u.deg):
     --------
     >>> ra, dec = 131.13535699 * u.deg, 18.08202663 * u.deg
     >>> obstime = Time("2017-08-01")
-    >>> is_close_to_sun(ra, dec, obstime, tolerance=3 * u.deg)
-    True
-    >>> is_close_to_sun(ra, dec + 4 * u.deg, obstime, tolerance=3 * u.deg)
-    False
+    >>> assert is_close_to_sun(ra, dec, obstime, tolerance=3 * u.deg)
+    >>> assert not is_close_to_sun(ra, dec + 4 * u.deg, obstime, tolerance=3 * u.deg)
     """
     coords = SkyCoord(ra=ra, dec=dec, frame=GCRS(obstime=obstime))
     sun_position = get_sun(obstime).transform_to(GCRS(obstime=obstime))

srttools/scan.py

@@ -1,4 +1,5 @@
 """Scan class."""
+
 import time
 import pickle
 import glob
@@ -76,31 +77,24 @@ def angular_distance(angle0, angle1):
     >>> dist = 0.1
     >>> a0 = 1.
     >>> a1 = 1. + dist
-    >>> np.isclose(angular_distance(a0, a1), dist)
-    True
+    >>> assert np.isclose(angular_distance(a0, a1), dist)
     >>> a0 = -0.05
     >>> a1 = 0.05
-    >>> np.isclose(angular_distance(a0, a1), dist)
-    True
+    >>> assert np.isclose(angular_distance(a0, a1), dist)
     >>> a0 += TWOPI
-    >>> np.isclose(angular_distance(a0, a1), dist)
-    True
+    >>> assert np.isclose(angular_distance(a0, a1), dist)
     >>> a1 += 6 * np.pi
-    >>> np.isclose(angular_distance(a0, a1), dist)
-    True
+    >>> assert np.isclose(angular_distance(a0, a1), dist)
     >>> a0 = np.pi - 0.5 * dist
     >>> a1 = np.pi + 0.5 * dist
-    >>> np.isclose(angular_distance(a0, a1), dist)
-    True
+    >>> assert np.isclose(angular_distance(a0, a1), dist)
     >>> a0 = TWOPI - 0.5 * dist
     >>> a1 = TWOPI + 0.5 * dist
-    >>> np.isclose(angular_distance(a0, a1), dist)
-    True
-    >>> np.all(np.isclose(
+    >>> assert np.isclose(angular_distance(a0, a1), dist)
+    >>> assert np.all(np.isclose(
     ...     angular_distance([0, np.pi, TWOPI],
     ...                      np.asarray([0, np.pi, TWOPI]) + dist),
     ...                   dist))
-    True
     """
     angle0 = np.fmod(angle0, TWOPI)
     angle1 = np.fmod(angle1, TWOPI)

srttools/simulate.py

@@ -1,6 +1,5 @@
 """Functions to simulate scans and maps."""
 
-
 import numpy as np
 import numpy.random as ra
 import os
@@ -161,7 +160,7 @@ def _default_flat_shape(x):
 
     Examples
     --------
-    >>> _default_flat_shape(4314)
+    >>> float(_default_flat_shape(4314))
     100.0
     >>> np.allclose(_default_flat_shape(np.arange(3)),
     ...             np.array([100., 100., 100.]))
@@ -294,7 +293,7 @@ def _default_map_shape(x, y):
 
     Examples
     --------
-    >>> _default_map_shape(4314, 234)
+    >>> int(_default_map_shape(4314, 234))
     100
     >>> res = np.array([[ 100.,  100.,  100.,  100.],
     ...                 [ 100.,  100.,  100.,  100.],
@@ -620,12 +619,9 @@ def _single_value_as_tuple(value, nvals=2):
 
     Examples
     --------
-    >>> np.all(_single_value_as_tuple(1) == (1, 1))
-    True
-    >>> np.all(_single_value_as_tuple((1, 1, 1)) == (1, 1, 1))
-    True
-    >>> np.all(_single_value_as_tuple(1, nvals=3) == (1, 1, 1))
-    True
+    >>> assert np.all(_single_value_as_tuple(1) == (1, 1))
+    >>> assert np.all(_single_value_as_tuple((1, 1, 1)) == (1, 1, 1))
+    >>> assert np.all(_single_value_as_tuple(1, nvals=3) == (1, 1, 1))
     """
     if isinstance(value, Iterable):
         return value

srttools/utils.py

@@ -159,10 +159,8 @@ def get_circular_statistics(array):
     --------
     >>> array = np.array([6.1, 6.2, 0.16, 0.26])
     >>> res = get_circular_statistics(array)
-    >>> np.isclose(res['min'], 6.1 - 2*np.pi)
-    True
-    >>> res['max'] == 0.26
-    True
+    >>> assert np.isclose(res['min'], 6.1 - 2*np.pi)
+    >>> assert res['max'] == 0.26
     """
     array = np.asarray(array) % TWOPI
     mean_ = circmean(array)
@@ -284,8 +282,7 @@ def compare_strings(s1, s2):
     True
     >>> import numpy as np
     >>> res = np.array([ True, False], dtype=bool)
-    >>> np.all(compare_strings(np.array(['a', 'b'], dtype='S'), u'a') == res)
-    True
+    >>> assert np.all(compare_strings(np.array(['a', 'b'], dtype='S'), u'a') == res)
     """
 
     s1 = standard_string(s1)
@@ -362,12 +359,10 @@ def interpolate_invalid_points_image(array, zeros_are_invalid=False):
     --------
     >>> img = np.ones((3, 3))
     >>> img[1, 1] = np.nan
-    >>> np.all(interpolate_invalid_points_image(img) == np.ones((3, 3)))
-    True
+    >>> assert np.all(interpolate_invalid_points_image(img) == np.ones((3, 3)))
     >>> img = np.ones((3, 3))
     >>> img[1, 1] = 0
-    >>> np.all(interpolate_invalid_points_image(img, True) == np.ones((3, 3)))
-    True
+    >>> assert np.all(interpolate_invalid_points_image(img, True) == np.ones((3, 3)))
     """
     from scipy import interpolate
 
@@ -429,23 +424,19 @@ def get_center_of_mass(im, radius=1, approx=None):
     ...                   [0,1,1,0],
     ...                   [0,1,1,0]))
     >>> cm = get_center_of_mass(image)
-    >>> np.all(cm == np.array([2.0, 1.5]))
-    True
+    >>> assert np.all(cm == np.array([2.0, 1.5]))
     >>> image = np.array(([0, 0,0,0,0, 0],
     ...                   [0, 0,0,0,0, 0],
     ...                   [0, 0,1,1,0, 0],
     ...                   [0, 0,1,1,0, 0],
     ...                   [0, 0,1,1,0, 0],
     ...                   [0, 0,0,0,0, 0]))
     >>> cm = get_center_of_mass(image, radius=0.4)
-    >>> np.all(cm == np.array([2.5, 2.5]))
-    False
+    >>> assert not np.all(cm == np.array([2.5, 2.5]))
     >>> cm = get_center_of_mass(image, radius=0.4, approx='max')
-    >>> np.all(cm == np.array([2.5, 2.5]))
-    True
+    >>> assert np.all(cm == np.array([2.5, 2.5]))
     >>> cm = get_center_of_mass(image)
-    >>> np.all(cm == np.array([3., 2.5]))
-    True
+    >>> assert np.all(cm == np.array([3., 2.5]))
     """
     import scipy.ndimage
 
@@ -750,8 +741,7 @@ def calculate_moments(y, imax=None, window_length=5):
     --------
     >>> y = np.exp(-np.linspace(-10, 10, 1101)**2/2)
     >>> mo = calculate_moments(y)
-    >>> np.all(np.isclose(mo['skewness'], 0))
-    True
+    >>> assert np.all(np.isclose(mo['skewness'], 0))
     """
     from scipy.signal import savgol_filter
 
@@ -798,8 +788,7 @@ def scantype(ra, dec, az=None, el=None):
     >>> els = np.linspace(0.5, 0.7, 100)
     >>> azs = np.linspace(0.5, 0.7, 100)
     >>> st = scantype(ras, decs, azs, els)
-    >>> np.all(st[0] == ras)
-    True
+    >>> assert np.all(st[0] == ras)
     >>> st[1] == 'RA>'
     True
     >>> # Opposite direction
@@ -818,8 +807,7 @@ def scantype(ra, dec, az=None, el=None):
     >>> els = list(zip(np.linspace(0.5, 0.7, 100), np.linspace(0.5, 0.7, 100)))
     >>> azs = list(zip(np.linspace(0.5, 0.7, 100), np.linspace(0.5, 0.7, 100)))
     >>> st = scantype(ras, decs, azs, els)
-    >>> np.all(st[0] == ras)
-    True
+    >>> assert np.all(st[0] == ras)
     >>> st[1] == 'RA>'
     True
     """
@@ -853,10 +841,8 @@ def median_diff(array, sorting=False):
 
     Examples
     --------
-    >>> median_diff([1, 2, 0, 4, -1, -2])
-    -1.0
-    >>> median_diff([1, 2, 0, 4, -1, -2], sorting=True)
-    1.0
+    >>> assert median_diff([1, 2, 0, 4, -1, -2]) == -1.0
+    >>> assert median_diff([1, 2, 0, 4, -1, -2], sorting=True) == 1.0
     """
     if len(array) == 0:
         return 0