Merge pull request #248 from arunkannawadi/u/arunkannawadi/np2

Compatibility with numpy 2

Author: esheldon

.github/workflows/test.yml

@@ -11,7 +11,7 @@ jobs:
     name: tests
     strategy:
       matrix:
-        pyver: ["3.9", "3.10", "3.11"]
+        pyver: ["3.9", "3.10", "3.11", "3.12"]
 
     runs-on: "ubuntu-latest"
 

CHANGES.md

@@ -1,3 +1,13 @@
+## v2.4.0
+
+### Compatibility
+
+    - Update to use either numpy>2. or 1.x
+
+ ### Misc
+
+    - Raise an exception if negative integers are passed to ``get_flags_str``.
+
 ## v2.3.2
 
 

README.md

@@ -1,7 +1,7 @@
 ngmix
 =====
 
-[![Build Status](https://travis-ci.com/esheldon/ngmix.svg?branch=master)](https://travis-ci.com/esheldon/ngmix)
+[![Build Status](https://github.com/esheldon/ngmix/actions/workflows/test.yml/badge.svg?branch=master)](https://github.com/esheldon/ngmix/actions/workflows/test.yml)
 
 Gaussian mixture models and other tools for working with 2d images, implemented
 in python. The code is made fast using the numba package.

ngmix/defaults.py

@@ -1,5 +1,10 @@
 import numpy as np
 
+# Shim to support numpy >= 2 and < 2.0.0.
+if np.lib.NumpyVersion(np.__version__) >= "2.0.0":
+    copy_if_needed = None
+else:
+    copy_if_needed = False
 
 # default values
 PDEF = -9.999e9  # parameter defaults

ngmix/fitting/galsim_results.py

@@ -5,7 +5,7 @@
 import numpy as np
 from .results import FitModel, PSFFluxFitModel
 from ..gexceptions import GMixRangeError
-from ..defaults import LOWVAL
+from ..defaults import copy_if_needed, LOWVAL
 from .. import observation
 from ..observation import Observation, ObsList, MultiBandObsList
 
@@ -269,7 +269,7 @@ def _check_guess(self, guess):
         exception
         """
 
-        guess = np.array(guess, dtype="f8", copy=False)
+        guess = np.array(guess, dtype="f8", copy=copy_if_needed)
         if guess.size != self.npars:
             raise ValueError(
                 "expected %d entries in the "

ngmix/fitting/results.py

@@ -3,7 +3,7 @@
 import numpy as np
 from .. import gmix
 from ..gexceptions import GMixRangeError
-from ..defaults import PDEF, CDEF, LOWVAL, BIGVAL
+from ..defaults import PDEF, CDEF, LOWVAL, BIGVAL, copy_if_needed
 from ..observation import Observation, ObsList, get_mb_obs
 from ..gmix.gmix_nb import gmix_convolve_fill, fill_fdiff
 from ..gmix import GMixList, MultiBandGMixList
@@ -361,7 +361,7 @@ def _setup_fit(self, guess):
         setup the mixtures based on the initial guess
         """
 
-        guess = np.array(guess, dtype="f8", copy=False)
+        guess = np.array(guess, dtype="f8", copy=copy_if_needed)
 
         npars = guess.size
         mess = "guess has npars=%d, expected %d" % (npars, self.npars)

ngmix/flags.py

@@ -1,3 +1,5 @@
+import numpy as np
+
 NO_ATTEMPT = 2**0
 CEN_SHIFT = 2**1
 NONPOS_FLUX = 2**2
@@ -61,7 +63,7 @@ def get_flags_str(val, name_map=None):
     Parameters
     ----------
     val : int
-        The flag value.
+        The flag value. This must be non-negative.
     name_map : dict, optional
         A dictionary mapping values to names. Default is global at
         ngmix.flags.NAME_MAP.
@@ -74,8 +76,18 @@ def get_flags_str(val, name_map=None):
     if name_map is None:
         name_map = NAME_MAP
 
+    # Negative values are always invalid and cause confusion if cast to an
+    # unsigned integer.
+    if val < 0:
+        raise ValueError(f"Flag value {val} must be non-negative.")
+
+    # Cast to uint32 is sufficient given the range of flags.
+    # This is because the second argument to the bitwise AND operator (&) below
+    # would get implicitly cast to the same type as `val`.
+    val = np.array(val, dtype=np.uint32)
+
     nstrs = []
-    for pow in range(32):
+    for pow in range(31):
         fval = 2**pow
         if ((val & fval) != 0):
             if fval in name_map:

ngmix/gaussap.py

@@ -5,6 +5,7 @@
 import numpy as np
 from .gmix import GMixModel, GMixCM
 from .gexceptions import GMixRangeError
+from ngmix.defaults import copy_if_needed
 from ngmix.flags import NO_ATTEMPT, GMIX_RANGE_ERROR
 
 DEFAULT_FLUX = np.nan
@@ -117,19 +118,19 @@ def _prepare(pars,
              TdByTe=None,
              mask=None):
 
-    pars = np.array(pars, dtype='f8', ndmin=2, copy=False)
+    pars = np.array(pars, dtype='f8', ndmin=2, copy=copy_if_needed)
 
     if mask is not None:
-        mask = np.array(mask, dtype=bool, ndmin=1, copy=False)
+        mask = np.array(mask, dtype=bool, ndmin=1, copy=copy_if_needed)
         assert mask.shape[0] == pars.shape[0], \
             'mask and pars must be same length'
     else:
         mask = np.ones(pars.shape[0], dtype=bool)
 
     if model == 'cm':
 
-        fracdev = np.array(fracdev, dtype='f8', ndmin=1, copy=False)
-        TdByTe = np.array(TdByTe, dtype='f8', ndmin=1, copy=False)
+        fracdev = np.array(fracdev, dtype='f8', ndmin=1, copy=copy_if_needed)
+        TdByTe = np.array(TdByTe, dtype='f8', ndmin=1, copy=copy_if_needed)
         assert fracdev.size == pars.shape[0], 'fracdev/pars must be same size'
         assert TdByTe.size == pars.shape[0], 'TdByTe/pars must be same length'
 

ngmix/priors/priors.py

@@ -6,7 +6,7 @@
 
 from ..gexceptions import GMixRangeError
 from .random import make_rng
-from ..defaults import LOWVAL
+from ..defaults import LOWVAL, copy_if_needed
 
 
 class PriorBase(object):
@@ -260,7 +260,7 @@ def get_prob_array(self, vals):
             The locations at which to evaluate
         """
 
-        vals = np.array(vals, ndmin=1, dtype="f8", copy=False)
+        vals = np.array(vals, ndmin=1, dtype="f8", copy=copy_if_needed)
         pvals = np.zeros(vals.size)
 
         for i in range(vals.size):
@@ -309,7 +309,7 @@ def _get_fdiff_array(self, vals):
         vals: number
             The locations at which to evaluate
         """
-        vals = np.array(vals, ndmin=1, dtype="f8", copy=False)
+        vals = np.array(vals, ndmin=1, dtype="f8", copy=copy_if_needed)
         fdiff = np.zeros(vals.size)
 
         for i in range(vals.size):
@@ -780,7 +780,7 @@ def get_lnprob_array(self, vals):
         vals: array
             The locations at which to evaluate
         """
-        vals = np.array(vals, dtype="f8", copy=False)
+        vals = np.array(vals, dtype="f8", copy=copy_if_needed)
         if self.shift is not None:
             vals = vals - self.shift
 

ngmix/priors/shape.py

@@ -10,7 +10,7 @@
 from .priors import PriorBase
 import logging
 from ..util import print_pars
-from ..defaults import LOWVAL
+from ..defaults import LOWVAL, copy_if_needed
 
 LOGGER = logging.getLogger(__name__)
 
@@ -115,8 +115,8 @@ def get_lnprob_array2d(self, g1arr, g2arr):
         Get the 2d prior for the array inputs
         """
 
-        g1arr = array(g1arr, dtype="f8", copy=False)
-        g2arr = array(g2arr, dtype="f8", copy=False)
+        g1arr = array(g1arr, dtype="f8", copy=copy_if_needed)
+        g2arr = array(g2arr, dtype="f8", copy=copy_if_needed)
 
         output = numpy.zeros(g1arr.size) + LOWVAL
         self.fill_lnprob_array2d(g1arr, g2arr, output)
@@ -133,8 +133,8 @@ def get_prob_array2d(self, g1arr, g2arr):
         Get the 2d prior for the array inputs
         """
 
-        g1arr = array(g1arr, dtype="f8", copy=False)
-        g2arr = array(g2arr, dtype="f8", copy=False)
+        g1arr = array(g1arr, dtype="f8", copy=copy_if_needed)
+        g2arr = array(g2arr, dtype="f8", copy=copy_if_needed)
 
         output = numpy.zeros(g1arr.size)
         self.fill_prob_array2d(g1arr, g2arr, output)
@@ -151,7 +151,7 @@ def get_prob_array1d(self, garr):
         Get the 1d prior for the array inputs
         """
 
-        garr = array(garr, dtype="f8", copy=False)
+        garr = array(garr, dtype="f8", copy=copy_if_needed)
 
         output = numpy.zeros(garr.size)
         self.fill_prob_array1d(garr, output)
@@ -726,8 +726,8 @@ def get_prob_array2d(self, x, y):
         """
         get prob at the input positions
         """
-        x = numpy.array(x, dtype="f8", ndmin=1, copy=False)
-        y = numpy.array(y, dtype="f8", ndmin=1, copy=False)
+        x = numpy.array(x, dtype="f8", ndmin=1, copy=copy_if_needed)
+        y = numpy.array(y, dtype="f8", ndmin=1, copy=copy_if_needed)
         out = numpy.zeros(x.size, dtype="f8")
 
         r2 = x ** 2 + y ** 2