Accepting request 1296400 from devel:languages:python:numeric

- Update to 4.17.1:
  * enhancements:
    + improved handling for OGIP products that do not follow the standards
    + Models can now be combined using arbitrary ufuncs
    + various updates to XSpec interface and support for XSpec 12.15.0
      including the additional of 17 new models
    + added interface to support ArviZ for analysis of Bayesian models
  * infrastructure and testing:
    + updated tests to work with python 3.13
  * bug fixes:
    + fixed a bug in the caching code that limited the cache size to 1
    + update to use fake_pha for missions which don't use 1 as the first
      channel
- Dropped patches:
  * sherpa-pr2188-np2docstrings.patch
  * sherpa-pr2207-mpl.patch
  * support-pytest-8.3.4.patch
- Refresed sherpa-suse-libdir.patch
- Add patch support-gcc-15.patch:
  * Specify function declarations correctly.

OBS-URL: https://build.opensuse.org/request/show/1296400
OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/python-sherpa?expand=0&rev=26

numpy2.patch

@@ -1,297 +0,0 @@
-From 72028ffe7ce2566a8f1e88c2c06d79cf5f0be9c1 Mon Sep 17 00:00:00 2001
-From: Douglas Burke <dburke.gw@gmail.com>
-Date: Thu, 27 Jun 2024 12:42:52 -0400
-Subject: [PATCH 1/7] root: internal code cleanup
-
-The root-finding code is not documented well. This adds a small
-wrapper routine to avoid some replicated code, but could we
-just add this to transformed_quad_coef() instead - which is
-not explicitly marked as an external routine?
-
-Several comments have been added for potential future work.
----
- sherpa/utils/__init__.py        | 38 ++++++++++++++++++++++-----------
- sherpa/utils/tests/test_root.py |  5 +++++
- 2 files changed, 30 insertions(+), 13 deletions(-)
-
-Index: sherpa-4.16.1/sherpa/utils/__init__.py
-===================================================================
---- sherpa-4.16.1.orig/sherpa/utils/__init__.py
-+++ sherpa-4.16.1/sherpa/utils/__init__.py
-@@ -1480,7 +1480,7 @@ def create_expr_integrated(lovals, hival
-     delim : str, optional
-         The separator for a range.
-     eps : number, optional
--        The tolerance for comparing two numbers with sao_fcmp.
-+        This value is unused.
- 
-     Raises
-     ------
-@@ -3389,6 +3389,7 @@ def bisection(fcn, xa, xb, fa=None, fb=N
-         return [[None, None], [[xa, fa], [xb, fb]], nfev[0]]
- 
- 
-+# Is this used at all?
- def quad_coef(x, f):
-     """
-     p( x ) = f( xc ) + A ( x - xc ) + B ( x - xc ) ( x - xb )
-@@ -3461,6 +3462,11 @@ def transformed_quad_coef(x, f):
-     xa, xb, xc = x[0], x[1], x[2]
-     fa, fb, fc = f[0], f[1], f[2]
- 
-+    # What happens if xb_xa or xc_xa are 0? That is, either
-+    #     xa == xb
-+    #     xc == xa
-+    # Is the assumption that this just never happen?
-+    #
-     xc_xb = xc - xb
-     fc_fb = fc - fb
-     A = fc_fb / xc_xb
-@@ -3472,6 +3478,21 @@ def transformed_quad_coef(x, f):
-     return [B, C]
- 
- 
-+def _get_discriminant(xa, xb, xc, fa, fb, fc):
-+    """Wrap up code to transformed_quad_coef.
-+
-+    This is common code that could be added to transformed_quad_coef
-+    but is left out at the moment, to make it easier to look back
-+    at code changes. There is no description of the parameters as
-+    the existing code has none.
-+
-+    """
-+
-+    [B, C] = transformed_quad_coef([xa, xb, xc], [fa, fb, fc])
-+    discriminant = max(C * C - 4.0 * fc * B, 0.0)
-+    return B, C, discriminant
-+
-+
- def demuller(fcn, xa, xb, xc, fa=None, fb=None, fc=None, args=(),
-              maxfev=32, tol=1.0e-6):
-     """A root-finding algorithm using Muller's method.
-@@ -3578,10 +3599,7 @@ def demuller(fcn, xa, xb, xc, fa=None, f
- 
-         while nfev[0] < maxfev:
- 
--            [B, C] = transformed_quad_coef([xa, xb, xc], [fa, fb, fc])
--
--            discriminant = max(C * C - 4.0 * fc * B, 0.0)
--
-+            B, C, discriminant = _get_discriminant(xa, xb, xc, fa, fb, fc)
-             if is_nan(B) or is_nan(C) or \
-                     0.0 == C + mysgn(C) * np.sqrt(discriminant):
-                 return [[None, None], [[None, None], [None, None]], nfev[0]]
-@@ -3685,11 +3703,7 @@ def new_muller(fcn, xa, xb, fa=None, fb=
-             if abs(fc) <= tol:
-                 return [[xc, fc], [[xa, fa], [xb, fb]], nfev[0]]
- 
--            tran = transformed_quad_coef([xa, xb, xc], [fa, fb, fc])
--            B = tran[0]
--            C = tran[1]
--
--            discriminant = max(C * C - 4.0 * fc * B, 0.0)
-+            B, C, discriminant = _get_discriminant(xa, xb, xc, fa, fb, fc)
- 
-             xd = xc - 2.0 * fc / (C + mysgn(C) * np.sqrt(discriminant))
- 
-@@ -3827,11 +3841,9 @@ def apache_muller(fcn, xa, xb, fa=None,
-         oldx = 1.0e128
-         while nfev[0] < maxfev:
- 
--            tran = transformed_quad_coef([xa, xb, xc], [fa, fb, fc])
--            B = tran[0]
--            C = tran[1]
--            discriminant = max(C * C - 4.0 * fc * B, 0.0)
--            den = mysgn(C) * np.sqrt(discriminant)
-+
-+            B, C, discriminant = _get_discriminant(xa, xb, xc, fa, fb, fc)
-+            den = np.sign(C) * np.sqrt(discriminant)
-             xplus = xc - 2.0 * fc / (C + den)
-             if C != den:
-                 xminus = xc - 2.0 * fc / (C - den)
-@@ -4008,9 +4020,13 @@ def zeroin(fcn, xa, xb, fa=None, fb=None
-             warning('%s: %s fa * fb < 0 is not met', __name__, fcn.__name__)
-             return [[None, None], [[None, None], [None, None]], nfev[0]]
- 
-+        # With NumPy 2.0 the casting rules changed, leading to some
-+        # behavioural changes in this code. The simplest fix was to
-+        # make sure DBL_EPSILON did not remain a np.float32 value.
-+        #
-         xc = xa
-         fc = fa
--        DBL_EPSILON = np.finfo(np.float32).eps
-+        DBL_EPSILON = float(np.finfo(np.float32).eps)
-         while nfev[0] < maxfev:
- 
-             prev_step = xb - xa
-Index: sherpa-4.16.1/sherpa/utils/tests/test_root.py
-===================================================================
---- sherpa-4.16.1.orig/sherpa/utils/tests/test_root.py
-+++ sherpa-4.16.1/sherpa/utils/tests/test_root.py
-@@ -1,5 +1,6 @@
- #
--#  Copyright (C) 2007, 2016, 2018, 2020, 2021  Smithsonian Astrophysical Observatory
-+#  Copyright (C) 2007, 2016, 2018, 2020, 2021, 2024
-+#  Smithsonian Astrophysical Observatory
- #
- #
- #  This program is free software; you can redistribute it and/or modify
-@@ -27,7 +28,7 @@ from sherpa.utils import demuller, bisec
-     zeroin
- 
- 
--def sqr(x, *args):
-+def sqr(x):
-     return x * x
- 
- 
-@@ -177,9 +178,7 @@ def prob34(x, *args):
-     return 1.0 / x - numpy.sin(x) + 1.0
- 
- 
--def prob35(x, *args):
--    return (x*x - 2.0) * x - 5.0
--
-+# prob35 was the same as prob16
- 
- def prob36(x, *args):
-     return 1.0 / x - 1.0
-@@ -288,7 +287,6 @@ def demuller2(fcn, xa, xb, fa=None, fb=N
-                           (prob32, 0.1, 0.9),
-                           (prob33, 2.8, 3.1),
-                           (prob34, -1.3, -0.5),
--                          (prob35, 2.0, 3.0),
-                           (prob36, 0.5, 1.5),
-                           (prob37, 0.5, 5.0),
-                           (prob38, 1.0, 4.0),
-Index: sherpa-4.16.1/sherpa/estmethods/__init__.py
-===================================================================
---- sherpa-4.16.1.orig/sherpa/estmethods/__init__.py
-+++ sherpa-4.16.1/sherpa/estmethods/__init__.py
-@@ -380,6 +380,11 @@ def covariance(pars, parmins, parmaxes,
-         eflag = est_success
-         ubound = diag[num]
-         lbound = -diag[num]
-+
-+        # What happens when lbound or ubound is NaN? This is
-+        # presumably why the code is written as it is below (e.g. a
-+        # pass if the values can be added to pars[num]).
-+        #
-         if pars[num] + ubound < parhardmaxes[num]:
-             pass
-         else:
-@@ -1093,6 +1098,7 @@ def confidence(pars, parmins, parmaxes,
-             print_status(myblog.blogger.info, verbose, status_prefix[dirn],
-                          delta_zero, lock)
- 
-+        # This should really set the error flag appropriately.
-         error_flags.append(est_success)
- 
-         #
-Index: sherpa-4.16.1/sherpa/fit.py
-===================================================================
---- sherpa-4.16.1.orig/sherpa/fit.py
-+++ sherpa-4.16.1/sherpa/fit.py
-@@ -277,7 +277,7 @@ class FitResults(NoNewAttributesAfterIni
- 
-         self.succeeded = results[0]
-         self.parnames = tuple(p.fullname for p in fit.model.get_thawed_pars())
--        self.parvals = tuple(results[1])
-+        self.parvals = tuple(float(r) for r in results[1])
-         self.istatval = init_stat
-         self.statval = results[2]
-         self.dstatval = np.abs(results[2] - init_stat)
-@@ -439,25 +439,28 @@ class ErrorEstResults(NoNewAttributesAft
-         self.sigma = fit.estmethod.sigma
-         self.percent = erf(self.sigma / sqrt(2.0)) * 100.0
-         self.parnames = tuple(p.fullname for p in parlist if not p.frozen)
--        self.parvals = tuple(p.val for p in parlist if not p.frozen)
-+        self.parvals = tuple(float(p.val) for p in parlist if not p.frozen)
-         self.parmins = ()
-         self.parmaxes = ()
--        self.nfits = 0
- 
-         for i in range(len(parlist)):
-             if (results[2][i] == est_hardmin or
--                    results[2][i] == est_hardminmax):
-+                results[2][i] == est_hardminmax or
-+                results[0][i] is None  # It looks like confidence does not set the flag
-+                ):
-                 self.parmins = self.parmins + (None,)
-                 warning("hard minimum hit for parameter %s", self.parnames[i])
-             else:
--                self.parmins = self.parmins + (results[0][i],)
-+                self.parmins = self.parmins + (float(results[0][i]),)
- 
-             if (results[2][i] == est_hardmax or
--                    results[2][i] == est_hardminmax):
-+                results[2][i] == est_hardminmax or
-+                results[1][i] is None  # It looks like confidence does not set the flag
-+                ):
-                 self.parmaxes = self.parmaxes + (None,)
-                 warning("hard maximum hit for parameter %s", self.parnames[i])
-             else:
--                self.parmaxes = self.parmaxes + (results[1][i],)
-+                self.parmaxes = self.parmaxes + (float(results[1][i]),)
- 
-         self.nfits = results[3]
-         self.extra_output = results[4]
-Index: sherpa-4.16.1/sherpa/astro/tests/test_astro.py
-===================================================================
---- sherpa-4.16.1.orig/sherpa/astro/tests/test_astro.py
-+++ sherpa-4.16.1/sherpa/astro/tests/test_astro.py
-@@ -206,7 +206,7 @@ def test_sourceandbg(parallel, run_threa
-         assert fit_results.numpoints == 1330
-         assert fit_results.dof == 1325
- 
--        assert covarerr[0] == approx(0.012097, rel=1e-3)
-+        assert covarerr[0] == approx(0.012097, rel=1.05e-3)
-         assert covarerr[1] == approx(0, rel=1e-3)
-         assert covarerr[2] == approx(0.000280678, rel=1e-3)
-         assert covarerr[3] == approx(0.00990783, rel=1e-3)
-Index: sherpa-4.16.1/docs/developer/index.rst
-===================================================================
---- sherpa-4.16.1.orig/docs/developer/index.rst
-+++ sherpa-4.16.1/docs/developer/index.rst
-@@ -100,6 +100,17 @@ files and shows exactly which lines were
- 
- Run doctests locally
- --------------------
-+
-+.. note::
-+   The documentation tests are known to fail if NumPy 2.0 is installed
-+   because the representation of NumPy types such as ``np.float64``
-+   have changed, leading to errors like::
-+
-+       Expected:
-+           2.5264364698914e-06
-+       Got:
-+           np.float64(2.5264364698914e-06)
-+
- If `doctestplus <https://pypi.org/project/pytest-doctestplus/>` is installed
- (and it probably is because it's part of
- `sphinx-astropy <https://pypi.org/project/sphinx-astropy/>`,
-Index: sherpa-4.16.1/docs/install.rst
-===================================================================
---- sherpa-4.16.1.orig/docs/install.rst
-+++ sherpa-4.16.1/docs/install.rst
-@@ -34,17 +34,14 @@ Requirements
- Sherpa has the following requirements:
- 
- * Python 3.9 to 3.11
--* NumPy (the exact lower limit has not been determined,
--  1.21.0 or later will work, earlier version may work)
-+* NumPy (version 2.0 should work but there has been limited testing)
- * Linux or OS-X (patches to add Windows support are welcome)
- 
- Sherpa can take advantage of the following Python packages
- if installed:
- 
- * :term:`Astropy`: for reading and writing files in
--  :term:`FITS` format. The minimum required version of astropy
--  is version 1.3, although only versions 2 and higher are used in testing
--  (version 3.2 is known to cause problems, but version 3.2.1 is okay).
-+  :term:`FITS` format.
- * :term:`matplotlib`: for visualisation of
-   one-dimensional data or models, one- or two- dimensional
-   error analysis, and the results of Monte-Carlo Markov Chain

sherpa-4.16.1.tar.gz

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:ed4dfba237c4a6b60b4141e5619b53b25cb9e23be26cbcd7dbf00f8822d4669c
-size 13738921

sherpa-4.17.0.tar.gz

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:f22f9dcb1b6326508d4142ea88931492972782fd292871ed942d1a212e70091a
-size 13985328

sherpa-pr2188-np2docstrings.patch

@@ -1,248 +0,0 @@
-From 388a7b3c87b8068c572041aeb57d2136a583e83b Mon Sep 17 00:00:00 2001
-From: Douglas Burke <dburke.gw@gmail.com>
-Date: Tue, 29 Oct 2024 14:35:02 -0400
-Subject: [PATCH] TEST: address numpy 2 changes to output for docstring tests
-
-The str/repr output in NumPy 2 is much-more verbose and no-longet
-matches the behaviour of the associated Python types. This breaks
-a number of doctests, which had things like
-
-    >>> (a == b).all()
-    True
-    >>> x.val
-    3.4
-
-which now fails for "textual" reasons even though the values are
-the same. The simplest approach is just to print the values, so
-we now have
-
-    >>> print((a == b).all())
-    True
-    >>> print(x.val)
-    3.4
-
-It is not ideal, but is a simple fix that works with versions 1
-and 2 of NumPy.
----
- sherpa/astro/data.py       | 14 +++++++-------
- sherpa/data.py             |  8 ++++----
- sherpa/models/basic.py     | 24 ++++++++++++------------
- sherpa/models/model.py     |  2 +-
- sherpa/models/parameter.py | 10 +++++-----
- 5 files changed, 29 insertions(+), 29 deletions(-)
-
-diff --git a/sherpa/astro/data.py b/sherpa/astro/data.py
-index 15f91fad72..87db02f617 100644
---- a/sherpa/astro/data.py
-+++ b/sherpa/astro/data.py
-@@ -2563,9 +2563,9 @@ def _get_ebins(self,
-         >>> pha.ungroup()
-         >>> pha.units = 'channel'
-         >>> clo, chi = pha._get_ebins()
--        >>> (clo == pha.channel).all()
-+        >>> print((clo == pha.channel).all())
-         True
--        >>> (chi == clo + 1).all()
-+        >>> print((chi == clo + 1).all())
-         True
- 
-         >>> pha.units = 'energy'
-@@ -2574,7 +2574,7 @@ def _get_ebins(self,
-         True
-         >>> elo[0:5]
-         array([0.00146, 0.0146 , 0.0292 , 0.0438 , 0.0584 ])
--        >>> (elo[1:] == ehi[:-1]).all()
-+        >>> print((elo[1:] == ehi[:-1]).all())
-         True
- 
-         >>> pha.group()
-@@ -2587,7 +2587,7 @@ def _get_ebins(self,
- 
-         >>> pha.units = 'wave'
-         >>> wlo, whi = pha._get_ebins()
--        >>> (wlo == glo).all()
-+        >>> print((wlo == glo).all())
-         True
-         """
- 
-@@ -2702,7 +2702,7 @@ def _get_indep(self,
-         array([0.1 , 0.11, 0.12, 0.13, 0.14])
-         >>> ehi[0:5]
-         array([0.11      , 0.12      , 0.13      , 0.14      , 0.15000001])
--        >>> (elo[1:] == ehi[:-1]).all()
-+        >>> print((elo[1:] == ehi[:-1]).all())
-         True
- 
-         >>> pha.units = 'wave'
-@@ -2711,7 +2711,7 @@ def _get_indep(self,
-         array([112.71289825, 103.32015848,  95.37245534,  88.56013348])
-         >>> whi[0:4]
-         array([123.98418555, 112.71289825, 103.32015848,  95.37245534])
--        >>> (wlo[:-1] == whi[1:]).all()
-+        >>> print((wlo[:-1] == whi[1:]).all())
-         True
- 
-         """
-@@ -3425,7 +3425,7 @@ def apply_grouping(self, data, groupfunc=np.sum):
-         >>> v1 = pha.apply_grouping(dvals)
-         >>> pha.notice(1.2, 4.5)
-         >>> v2 = pha.apply_grouping(dvals)
--        >>> np.all(v1 == v2)
-+        >>> print(np.all(v1 == v2))
-         True
- 
-         """
-diff --git a/sherpa/data.py b/sherpa/data.py
-index 30fe9dbf0f..daf79d93e2 100644
---- a/sherpa/data.py
-+++ b/sherpa/data.py
-@@ -2042,8 +2042,8 @@ def notice(self,
-         >>> x = np.arange(0.4, 2.6, 0.2)
-         >>> y = np.ones_like(x)
-         >>> d = Data1D('example', x, y)
--        >>> d.x[0], d.x[-1]
--        (0.4, 2.4000000000000004)
-+        >>> print(d.x[0], d.x[-1])
-+        0.4 2.4000000000000004
-         >>> d.notice()
-         >>> d.get_filter(format='%.1f')
-         '0.4:2.4'
-@@ -2326,8 +2326,8 @@ def notice(self,
-         >>> xlo, xhi = edges[:-1], edges[1:]
-         >>> y = np.ones_like(xlo)
-         >>> d = Data1DInt('example', xlo, xhi, y)
--        >>> d.xlo[0], d.xhi[-1]
--        (0.4, 2.400000000000001)
-+        >>> print(d.xlo[0], d.xhi[-1])
-+        0.4 2.400000000000001
-         >>> d.get_filter(format='%.1f')
-         '0.4:2.4'
-         >>> d.notice(0.8, 1.9)
-diff --git a/sherpa/models/basic.py b/sherpa/models/basic.py
-index c1061e033a..d5280eda0f 100644
---- a/sherpa/models/basic.py
-+++ b/sherpa/models/basic.py
-@@ -539,14 +539,14 @@ class Gauss1D(RegriddableModel1D):
-     >>> m1.pos, m2.pos = 10, 10
-     >>> m1.ampl, m2.ampl = 10, 10
-     >>> m1.fwhm, m2.fwhm = 5, 5
--    >>> m1(10)
-+    >>> print(m1(10))
-     10.0
--    >>> m2(10)
-+    >>> print(m2(10))
-     1.8788745573993026
-     >>> m1.fwhm, m2.fwhm = 1, 1
--    >>> m1(10)
-+    >>> print(m1(10))
-     10.0
--    >>> m2(10)
-+    >>> print(m2(10))
-     9.394372786996513
- 
-     The normalised version will sum to the amplitude when given
-@@ -558,9 +558,9 @@ class Gauss1D(RegriddableModel1D):
-     >>> m1.fwhm, m2.fwhm = 12.2, 12.2
-     >>> grid = np.arange(-90, 110, 0.01)
-     >>> glo, ghi = grid[:-1], grid[1:]
--    >>> m1(glo, ghi).sum()
-+    >>> print(m1(glo, ghi).sum())
-     129.86497637060958
--    >>> m2(glo, ghi).sum()
-+    >>> print(m2(glo, ghi).sum())
-     10.000000000000002
- 
-     """
-@@ -1923,12 +1923,12 @@ class TableModel(ArithmeticModel):
-     >>> d.staterror = [.2, .2, .2, .2, .2]
-     >>> tm1 = TableModel('tabmodel')
-     >>> tm1.load(None, [.6, .2, 1.1, .2, .5])
--    >>> tm1.ampl.val
-+    >>> print(tm1.ampl.val)
-     1.0
-     >>> tm1.fold(d)
-     >>> fit1 = Fit(d, tm1)
-     >>> res1 = fit1.fit()
--    >>> tm1.ampl.val
-+    >>> print(tm1.ampl.val)
-     1.9894736842102083
- 
-     In this case the `fold` method is necessary, to ensure that the
-@@ -1941,11 +1941,11 @@ class TableModel(ArithmeticModel):
-     >>> tm2 = TableModel('tabmodel')
-     >>> tm2.load(None, [.6, .2, 1.1, .2, .5])
-     >>> tm2.fold(d)
--    >>> tm2.ampl.val
-+    >>> print(tm2.ampl.val)
-     1.0
-     >>> fit2 = Fit(d, tm2)
-     >>> res2 = fit2.fit()
--    >>> tm2.ampl.val
-+    >>> print(tm2.ampl.val)
-     1.9866666666663104
- 
-     The masking also holds if the notice or ignore method has been
-@@ -1957,11 +1957,11 @@ class TableModel(ArithmeticModel):
-     >>> tm3 = TableModel('tabmodel')
-     >>> tm3.load(None, [.6, .2, 1.1, .2, .5])
-     >>> tm3.fold(d)
--    >>> tm3.ampl.val
-+    >>> print(tm3.ampl.val)
-     1.0
-     >>> fit3 = Fit(d, tm3)
-     >>> res = fit3.fit()
--    >>> tm3.ampl.val
-+    >>> print(tm3.ampl.val)
-     1.9866666666663104
- 
-     """
-diff --git a/sherpa/models/model.py b/sherpa/models/model.py
-index 5b89181d28..020ef7a30f 100644
---- a/sherpa/models/model.py
-+++ b/sherpa/models/model.py
-@@ -152,7 +152,7 @@
- 
-     >>> m1.ampl = 10
-     >>> m2.ampl = 12
--    >>> m3.ampl.val
-+    >>> print(m3.ampl.val)
-     11.0
-     >>> m3.ampl.link
-     <BinaryOpParameter '(gauss1d.ampl + gmdl.ampl) / 2'>
-diff --git a/sherpa/models/parameter.py b/sherpa/models/parameter.py
-index 3e1ee5215a..09af7c9bcf 100644
---- a/sherpa/models/parameter.py
-+++ b/sherpa/models/parameter.py
-@@ -60,7 +60,7 @@
- 
- The `val` attribute is used to retrieve or change the parameter value:
- 
--    >>> p.val
-+    >>> print(p.val)
-     2.0
-     >>> p.val = 3
- 
-@@ -72,9 +72,9 @@
- for these are the 32-bit floating point maximum value, and it's
- negative:
- 
--    >>> p.max
-+    >>> print(p.max)
-     3.4028234663852886e+38
--    >>> p.min
-+    >>> print(p.min)
-     -3.4028234663852886e+38
- 
- Setting a value outside this range will raise a
-@@ -578,9 +578,9 @@ def _set_link(self, link: Optional[Parameter]) -> None:
- >>> a = Parameter("mdl", "a", 2)
- >>> b = Parameter("mdl", "b", 1)
- >>> b.link = 10 - a
-->>> a.val
-+>>> print(a.val)
- 2.0
-->>> b.val
-+>>> print(b.val)
- 8.0
- """)
- 

sherpa-pr2207-mpl.patch

@@ -1,86 +0,0 @@
-From 5e3d13df1c09134fe5b1cbb27bfc3559ef0641a0 Mon Sep 17 00:00:00 2001
-From: Doug Burke <dburke@cfa.harvard.edu>
-Date: Fri, 3 Jan 2025 16:46:36 -0500
-Subject: [PATCH] TESTS: avoid matplotlib version differences (fix #2206)
-
-The matlpotlib get_linestyles method can return
-
-  [(x, None)]
-
-where x = None, 0.0, or np.float64(0.0) depending on matplotlib
-version (and probably NumPy).
-
-Since we don't really care too much here, just check the return
-has length of 1, the first element has length of 2, and the
-second element is None.
----
- sherpa/astro/ui/tests/test_astro_ui_plot.py | 35 +++++++++++----------
- 1 file changed, 18 insertions(+), 17 deletions(-)
-
-diff --git a/sherpa/astro/ui/tests/test_astro_ui_plot.py b/sherpa/astro/ui/tests/test_astro_ui_plot.py
-index a6b7c07aa8..5a41d3ce4e 100644
---- a/sherpa/astro/ui/tests/test_astro_ui_plot.py
-+++ b/sherpa/astro/ui/tests/test_astro_ui_plot.py
-@@ -1,5 +1,5 @@
- #
--#  Copyright (C) 2019 - 2024
-+#  Copyright (C) 2019 - 2025
- #  Smithsonian Astrophysical Observatory
- #
- #
-@@ -32,6 +32,7 @@
- 
- import copy
- import logging
-+
- import numpy as np
- 
- import pytest
-@@ -1843,15 +1844,15 @@ def test_pha1_plot_data_options(caplog, clean_astro_ui, requires_pylab,
- 
-     assert len(coll.get_segments()) == 42
- 
--    # The return value depends on matplotlib version (>= 3.3
--    # returns something). What has changed? Maybe this should
--    # not be tested?
-+    # The linestyles return value has changed with matplotib
-+    # and NumPy version, so just check the second element
-+    # and not the first (which can be None, 0.0, np.float64(0)).
-     #
--    expected = [(None, None)]
--    if matplotlib.__version__ >= '3.3.0':
--        expected = [(0.0, None)]
--
--    assert coll.get_linestyles() == expected
-+    #
-+    ls = coll.get_linestyles()
-+    assert len(ls) == 1
-+    assert len(ls[0]) == 2
-+    assert ls[0][1] is None
- 
-     # looks like the color has been converted to individual channels
-     # - e.g. floating-point values for R, G, B, and alpha.
-@@ -2041,15 +2042,15 @@ def test_pha1_plot_fit_options(clean_astro_ui, requires_pylab, basic_pha1):
- 
-     assert len(coll.get_segments()) == 42
- 
--    # The return value depends on matplotlib version (>= 3.3
--    # returns something). What has changed? Maybe this should
--    # not be tested?
-+    # The linestyles return value has changed with matplotib
-+    # and NumPy version, so just check the second element
-+    # and not the first (which can be None, 0.0, np.float64(0)).
-     #
--    expected = [(None, None)]
--    if matplotlib.__version__ >= '3.3.0':
--        expected = [(0.0, None)]
--
--    assert coll.get_linestyles() == expected
-+    #
-+    ls = coll.get_linestyles()
-+    assert len(ls) == 1
-+    assert len(ls[0]) == 2
-+    assert ls[0][1] is None
- 
-     # looks like the color has been converted to individual channels
-     # - e.g. floating-point values for R, G, B, and alpha.

sherpa-test-data-4.16.1.tar.gz

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:c61443bf3530e42322cec52887cc2f170c2d5d9aaba2822e107da2626c269a1c
-size 137775313

sherpa-test-data-4.17.0.tar.gz

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:215d3465c7a9d1b4307ec5eeb1f489a1251de9cee71e75e7162f491ad6037126
-size 137775257

support-pytest-8.3.4.patch

@@ -1,965 +0,0 @@
-From 0fafdd4522408e15561ae79a502b096317bb0d9e Mon Sep 17 00:00:00 2001
-From: Douglas Burke <dburke.gw@gmail.com>
-Date: Fri, 6 Dec 2024 12:06:50 -0500
-Subject: [PATCH 1/2] TEST: handle pytest 8.3.4 change in bool tests with
- approx
-
-Fix #2202
-
-In pytest 8.3.3 and earlier
-
-    >>> import numpy as np; import pytest
-    >>> pytest.__version__
-    '8.3.3'
-    >>> np.ones(2, dtype=bool) == pytest.approx([True, True])
-    True
-
-However, pytest 8.3.4 now causes this to fail
-
-    >>> import numpy as np; import pytest
-    >>> pytest.__version__
-    '8.3.4'
-    >>> np.ones(2, dtype=bool) == pytest.approx([True, True])
-    False
-
-This is because of "pytest.approx considers boolean numeric types"
-https://github.com/pytest-dev/pytest/issues/9353
-
-The solution is to make the "expected" value be a ndarray, and so
-
-    >>> np.ones(2, dtype=bool) == pytest.approx(np.asarray([True, True]))
-    True
-
-holds with both pytest 8.3.3 and 8.3.4.
-
-So this commit basically goes through and updates the tests so that
-we use a ndarray for boolean arrays.
-
-An alternative would be to change from
-
-    assert got == pytest.approx(expected)
-
-to something like
-
-    assert np.all(got == expected)
-
-However, the error message when the array lengths are different or
-an element is different are a **lot less** useful, and the change would
-be even-more invasive than this change.
----
- sherpa/astro/io/tests/test_io_pha.py          |   2 +-
- sherpa/astro/tests/test_astro_data.py         |  43 +++---
- sherpa/astro/tests/test_astro_data2.py        | 131 +++++++++++-------
- sherpa/astro/tests/test_astro_instrument.py   |   3 +-
- sherpa/astro/tests/test_astro_plot.py         |   6 +-
- sherpa/astro/ui/tests/test_astro_ui.py        |   3 +-
- sherpa/astro/ui/tests/test_astro_ui_unit.py   |   9 +-
- sherpa/astro/ui/tests/test_filtering.py       |   8 +-
- .../utils/tests/test_astro_utils_unit.py      |   8 +-
- sherpa/tests/test_data.py                     |   6 +-
- sherpa/ui/tests/test_session.py               |   3 +-
- sherpa/ui/tests/test_ui_unit.py               |  10 +-
- sherpa/utils/tests/test_utils.py              |  10 +-
- 13 files changed, 146 insertions(+), 96 deletions(-)
-
-diff --git a/sherpa/astro/io/tests/test_io_pha.py b/sherpa/astro/io/tests/test_io_pha.py
-index 84dcd4a98c..ceab1609a4 100644
---- a/sherpa/astro/io/tests/test_io_pha.py
-+++ b/sherpa/astro/io/tests/test_io_pha.py
-@@ -1504,7 +1504,7 @@ def test_write_pha_with_bad_quality(tmp_path):
-     counts = chans * 2
-     group = [1, -1, -1, 1, -1, 1, 1, 1, -1]
-     quality = [0, 5, 0, 0, 0, 0, 0, 2, 2]
--    qfilt = [True, False] + [True] * 5 + [False] * 2
-+    qfilt = np.asarray([True, False] + [True] * 5 + [False] * 2)
- 
-     pha0 = DataPHA("qual", chans, counts, grouping=group,
-                    quality=quality)
-diff --git a/sherpa/astro/tests/test_astro_data.py b/sherpa/astro/tests/test_astro_data.py
-index b4ab684ce5..9ca381763c 100644
---- a/sherpa/astro/tests/test_astro_data.py
-+++ b/sherpa/astro/tests/test_astro_data.py
-@@ -2367,7 +2367,7 @@ def test_pha_check_limit(ignore, lo, hi, evals):
-     pha.units = 'energy'
- 
-     assert pha.mask is True
--    assert pha.get_mask() == pytest.approx([True] * 10)
-+    assert pha.get_mask() == pytest.approx(np.ones(10, dtype=bool))
- 
-     func = pha.ignore if ignore else pha.notice
-     func(lo, hi)
-@@ -2380,7 +2380,7 @@ def test_pha_check_limit(ignore, lo, hi, evals):
-         vin = True
- 
-     c1, c2, c3 = evals
--    expected = [vout] * c1 + [vin] * c2 + [vout] * c3
-+    expected = np.asarray([vout] * c1 + [vin] * c2 + [vout] * c3)
-     assert pha.mask == pytest.approx(pha.get_mask())
-     assert pha.mask == pytest.approx(expected)
- 
-@@ -2449,7 +2449,7 @@ def test_pha_check_limit_channel(ignore, lo, hi, evals):
-     pha.units = 'channel'
- 
-     assert pha.mask is True
--    assert pha.get_mask() == pytest.approx([True] * 10)
-+    assert pha.get_mask() == pytest.approx(np.ones(10, dtype=bool))
- 
-     func = pha.ignore if ignore else pha.notice
-     func(lo, hi)
-@@ -2462,7 +2462,7 @@ def test_pha_check_limit_channel(ignore, lo, hi, evals):
-         vin = True
- 
-     c1, c2, c3 = evals
--    expected = [vout] * c1 + [vin] * c2 + [vout] * c3
-+    expected = np.asarray([vout] * c1 + [vin] * c2 + [vout] * c3)
-     assert pha.mask == pytest.approx(pha.get_mask())
-     assert pha.mask == pytest.approx(expected)
- 
-@@ -2672,7 +2672,9 @@ def test_is_mask_reset_pha(caplog):
-     # Pick a value somewhere within the independent axis
-     assert data.mask is True
-     data.ignore(None, 2)
--    assert data.mask == pytest.approx([False, False, True])
-+
-+    mask = np.asarray([False, False, True])
-+    assert data.mask == pytest.approx(mask)
- 
-     # Change the independent axis, but to something of the same
-     # length.
-@@ -2683,7 +2685,7 @@ def test_is_mask_reset_pha(caplog):
-     assert len(caplog.records) == 0
- 
-     # The mask has *not* been cleared
--    assert data.mask == pytest.approx([False, False, True])
-+    assert data.mask == pytest.approx(mask)
- 
- 
- def test_is_mask_reset_pha_channel(caplog):
-@@ -2703,7 +2705,8 @@ def test_is_mask_reset_pha_channel(caplog):
-     assert len(caplog.records) == 0
- 
-     # The mask has not been cleared
--    assert data.mask == pytest.approx([False, False, True])
-+    mask = np.asarray([False, False, True])
-+    assert data.mask == pytest.approx(mask)
- 
- 
- @requires_region
-@@ -3376,9 +3379,11 @@ def test_pha_notice_bkg_id_none():
- 
-     pha.notice(lo=2, bkg_id=None)  # the default
- 
--    assert pha.mask == pytest.approx([False, True])
--    assert b1.mask == pytest.approx([False, True])
--    assert bup.mask == pytest.approx([False, True])
-+    bfilt = np.asarray([False, True])
-+
-+    assert pha.mask == pytest.approx(bfilt)
-+    assert b1.mask == pytest.approx(bfilt)
-+    assert bup.mask == pytest.approx(bfilt)
- 
- 
- @pytest.mark.parametrize("bkg_id", [1, "up"])
-@@ -3394,13 +3399,15 @@ def test_pha_notice_bkg_id_scalar(bkg_id):
- 
-     pha.notice(lo=2, bkg_id=bkg_id)
- 
-+    bfilt = np.asarray([False, True])
-+
-     assert pha.mask is True
-     if bkg_id == 1:
--        assert b1.mask == pytest.approx([False, True])
-+        assert b1.mask == pytest.approx(bfilt)
-         assert bup.mask is True
-     else:
-         assert b1.mask is True
--        assert bup.mask == pytest.approx([False, True])
-+        assert bup.mask == pytest.approx(bfilt)
- 
- 
- def test_pha_notice_bkg_id_array_all():
-@@ -3415,9 +3422,11 @@ def test_pha_notice_bkg_id_array_all():
- 
-     pha.notice(lo=2, bkg_id=["up", 1])
- 
-+    bfilt = np.asarray([False, True])
-+
-     assert pha.mask is True
--    assert b1.mask == pytest.approx([False, True])
--    assert bup.mask == pytest.approx([False, True])
-+    assert b1.mask == pytest.approx(bfilt)
-+    assert bup.mask == pytest.approx(bfilt)
- 
- 
- @pytest.mark.parametrize("bkg_id", [1, "up"])
-@@ -3433,13 +3442,15 @@ def test_pha_notice_bkg_id_array_subset(bkg_id):
- 
-     pha.notice(lo=2, bkg_id=[bkg_id])
- 
-+    bfilt = np.asarray([False, True])
-+
-     assert pha.mask is True
-     if bkg_id == 1:
--        assert b1.mask == pytest.approx([False, True])
-+        assert b1.mask == pytest.approx(bfilt)
-         assert bup.mask is True
-     else:
-         assert b1.mask is True
--        assert bup.mask == pytest.approx([False, True])
-+        assert bup.mask == pytest.approx(bfilt)
- 
- 
- def get_img_spatial_mask():
-diff --git a/sherpa/astro/tests/test_astro_data2.py b/sherpa/astro/tests/test_astro_data2.py
-index b5eaf3b598..d6bdb19e49 100644
---- a/sherpa/astro/tests/test_astro_data2.py
-+++ b/sherpa/astro/tests/test_astro_data2.py
-@@ -97,7 +97,7 @@ def test_get_mask_is_none():
-     """
-     pha = DataPHA('name', [1, 2, 3], [1, 1, 1])
-     assert pha.mask is True
--    assert pha.get_mask() == pytest.approx([True] * 3)
-+    assert pha.get_mask() == pytest.approx(np.asarray([True] * 3))
- 
- 
- def test_get_mask_is_none_when_all_filtered():
-@@ -497,7 +497,7 @@ def test_288_a():
-     # with bools the use of approx is okay (it can tell the
-     # difference between 0 and 1, aka False and True).
-     #
--    assert pha.mask == pytest.approx([True, False, True])
-+    assert pha.mask == pytest.approx(np.asarray([True, False, True]))
- 
- 
- def test_288_a_energy():
-@@ -525,7 +525,7 @@ def test_288_a_energy():
-     # with bools the use of approx is okay (it can tell the
-     # difference between 0 and 1, aka False and True).
-     #
--    assert pha.mask == pytest.approx([True, False, True])
-+    assert pha.mask == pytest.approx(np.asarray([True, False, True]))
- 
- 
- def test_288_b():
-@@ -565,7 +565,7 @@ def test_288_b_energy():
-     assert pha.mask is True
-     pha.ignore(3.1, 4)
- 
--    assert pha.mask == pytest.approx([True, False, True])
-+    assert pha.mask == pytest.approx(np.asarray([True, False, True]))
- 
- 
- @requires_group
-@@ -621,8 +621,8 @@ def test_416_a():
-     #     grouped)
-     #   - pha.get_mask() always returns the ungrouped mask
-     #
--    mask_ungrouped = [False] * 3 + [True] * 3 + [False] * 4
--    mask_grouped = [False] * 3 + [True] * 2 + [False] * 4
-+    mask_ungrouped = np.asarray([False] * 3 + [True] * 3 + [False] * 4)
-+    mask_grouped = np.asarray([False] * 3 + [True] * 2 + [False] * 4)
- 
-     assert pha.mask == pytest.approx(mask_ungrouped)
-     assert pha.get_mask() == pytest.approx(mask_ungrouped)
-@@ -685,7 +685,7 @@ def test_416_c():
-     pha.notice(4.5, 6.5)
- 
-     # this should be ~pha.mask
--    tabstops = [True] * 3 + [False] * 3 + [True] * 4
-+    tabstops = np.asarray([True] * 3 + [False] * 3 + [True] * 4)
-     assert ~pha.mask == pytest.approx(tabstops)
- 
-     assert pha.grouping is None
-@@ -1688,10 +1688,13 @@ def test_pha_quality_all_bad_basic_checks():
- 
-     """
- 
-+    all4 = np.ones(4, dtype=bool)
-+    none4 = np.zeros(4, dtype=bool)
-+
-     pha = DataPHA("q", [1, 2, 3, 4], [9, 0, 1, 64])
-     fvals = [12, 2, 7, 8]
-     assert pha.mask is True
--    assert pha.get_mask() == pytest.approx([True] * 4)
-+    assert pha.get_mask() == pytest.approx(all4)
-     assert pha.get_filter() == "1:4"
-     assert pha.get_x() == pytest.approx([1, 2, 3, 4])
-     assert pha.apply_filter(fvals) == pytest.approx(fvals)
-@@ -1699,15 +1702,15 @@ def test_pha_quality_all_bad_basic_checks():
- 
-     pha.quality = [2, 2, 2, 5]
-     assert pha.mask is True
--    assert pha.get_mask() == pytest.approx([True] * 4)
-+    assert pha.get_mask() == pytest.approx(all4)
-     assert pha.get_filter() == "1:4"
-     assert pha.get_x() == pytest.approx([1, 2, 3, 4])
-     assert pha.apply_filter(fvals) == pytest.approx(fvals)
-     assert pha.apply_grouping(fvals) == pytest.approx(fvals)
- 
-     pha.ignore_bad()
--    assert pha.mask == pytest.approx([False] * 4)
--    assert pha.get_mask() == pytest.approx([False] * 4)
-+    assert pha.mask == pytest.approx(none4)
-+    assert pha.get_mask() == pytest.approx(none4)
-     assert pha.get_filter() == ""
-     assert pha.get_x() == pytest.approx([1, 2, 3, 4])
-     assert pha.apply_filter(fvals) == pytest.approx([])
-@@ -1742,7 +1745,7 @@ def test_pha_quality_change_mask(make_quality_pha):
-     pha.ignore_bad()
-     assert pha.mask is True
-     pha.mask = [1, 1, 0]
--    assert pha.mask == pytest.approx([True, True, False])
-+    assert pha.mask == pytest.approx(np.asarray([True, True, False]))
- 
- 
- def test_pha_quality_change_mask_ungrouped(make_quality_pha):
-@@ -1753,7 +1756,8 @@ def test_pha_quality_change_mask_ungrouped(make_quality_pha):
-     pha.ungroup()
-     assert pha.mask is True
-     pha.mask = [1, 1, 0, 1, 1, 0, 0, 1, 1]
--    assert pha.mask == pytest.approx([True, True, False, True, True, False, False, True, True])
-+    mask = np.asarray([True, True, False, True, True, False, False, True, True])
-+    assert pha.mask == pytest.approx(mask)
- 
- 
- def test_pha_quality_change_mask_fullsize(make_quality_pha):
-@@ -1972,23 +1976,26 @@ def test_pha_quality_ignore_bad_clear_filter(make_quality_pha):
- 
-     pha = make_quality_pha
- 
-+    mask0 = np.ones(9, dtype=bool)
-     assert pha.get_filter() == "1:9"
-     assert pha.mask is True
--    assert pha.get_mask() == pytest.approx([True] * 9)
-+    assert pha.get_mask() == pytest.approx(mask0)
-     assert pha.quality_filter is None
- 
-     # channels 2,3 and 7-9 are "bad"
-     pha.ignore(hi=3)
- 
-+    mask = np.asarray([False] + [True] * 3)
-+    mask_full = np.asarray([False] * 4 + [True] * 5)
-     assert pha.get_filter() == "5:9"
--    assert pha.mask == pytest.approx([False] + [True] * 3)
--    assert pha.get_mask() == pytest.approx([False] * 4 + [True] * 5)
-+    assert pha.mask == pytest.approx(mask)
-+    assert pha.get_mask() == pytest.approx(mask_full)
-     assert pha.quality_filter is None
- 
-     # This resets the previous filters
-     pha.ignore_bad()
- 
--    qflags = [True] * 1 + [False] * 2 + [True] * 3 + [False] * 3
-+    qflags = np.asarray([True] * 1 + [False] * 2 + [True] * 3 + [False] * 3)
-     assert pha.get_filter() == "1:9"
-     assert pha.mask is True
-     assert pha.get_mask() == pytest.approx(qflags)
-@@ -1996,16 +2003,19 @@ def test_pha_quality_ignore_bad_clear_filter(make_quality_pha):
- 
-     pha.ignore(hi=3)
- 
-+    mask2 = np.asarray([False] + [True] * 2)
-+    mask2_full = np.asarray([False] * 2 + [True] * 2)
-+
-     assert pha.get_filter() == "5:6"
--    assert pha.mask == pytest.approx([False] + [True] * 2)
--    assert pha.get_mask() == pytest.approx([False] * 2 + [True] * 2)
-+    assert pha.mask == pytest.approx(mask2)
-+    assert pha.get_mask() == pytest.approx(mask2_full)
-     assert pha.quality_filter == pytest.approx(qflags)
- 
-     pha.ignore(lo=2, hi=4)
- 
-     assert pha.get_filter() == "5:6"
--    assert pha.mask == pytest.approx([False] + [True] * 2)
--    assert pha.get_mask() == pytest.approx([False] * 2 + [True] * 2)
-+    assert pha.mask == pytest.approx(mask2)
-+    assert pha.get_mask() == pytest.approx(mask2_full)
-     assert pha.quality_filter == pytest.approx(qflags)
- 
-     # This removes the quality filter!
-@@ -2013,7 +2023,7 @@ def test_pha_quality_ignore_bad_clear_filter(make_quality_pha):
- 
-     assert pha.get_filter() == "1:9"
-     assert pha.mask is True
--    assert pha.get_mask() == pytest.approx([True] * 9)
-+    assert pha.get_mask() == pytest.approx(mask0)
-     assert pha.quality_filter is None
- 
- 
-@@ -2443,7 +2453,8 @@ def test_pha_change_quality_values(caplog):
-     pha.ignore_bad()
-     assert len(caplog.records) == 0
- 
--    assert pha.quality_filter == pytest.approx([True] * 5 + [False] * 2)
-+    qfilt = np.asarray([True] * 5 + [False] * 2)
-+    assert pha.quality_filter == pytest.approx(qfilt)
-     assert pha.get_dep(filter=True) == pytest.approx([6])
-     assert pha.get_filter() == '1:7'
- 
-@@ -2456,7 +2467,7 @@ def test_pha_change_quality_values(caplog):
-     assert pha.quality == pytest.approx([0, 0, 0, 2, 2, 0, 0])
- 
-     # Should quality filter be reset?
--    assert pha.quality_filter == pytest.approx([True] * 5 + [False] * 2)
-+    assert pha.quality_filter == pytest.approx(qfilt)
-     assert pha.get_dep(filter=True) == pytest.approx([4, 2])
-     assert pha.get_filter() == '1:7'
- 
-@@ -2499,14 +2510,14 @@ def test_pha_group_ignore_bad_then_filter(caplog):
-     assert len(caplog.records) == 0
- 
-     assert pha.mask is True
--    assert pha.get_mask() == pytest.approx([True] * 7)
-+    assert pha.get_mask() == pytest.approx(np.ones(7, dtype=bool))
-     assert pha.get_filter() == '1:7'
-     assert pha.quality_filter is None
- 
-     pha.ignore_bad()
-     assert len(caplog.records) == 0
- 
--    qual_mask = [True] * 2 + [False] + [True] * 3 + [False]
-+    qual_mask = np.asarray([True] * 2 + [False] + [True] * 3 + [False])
-     assert pha.mask is True
-     assert pha.get_mask() == pytest.approx(qual_mask)
-     assert pha.get_filter() == '1:7'
-@@ -2518,8 +2529,10 @@ def test_pha_group_ignore_bad_then_filter(caplog):
-     pha.ignore(4, 5)
-     assert len(caplog.records) == 0
- 
--    assert pha.mask == pytest.approx([True, False, True])
--    assert pha.get_mask() == pytest.approx([True] * 2 + [False] * 2 + [True])
-+    mask = np.asarray([True, False, True])
-+    mask_full = np.asarray([True] * 2 + [False] * 2 + [True])
-+    assert pha.mask == pytest.approx(mask)
-+    assert pha.get_mask() == pytest.approx(mask_full)
-     assert pha.get_filter() == '1:2,6'
-     assert pha.quality_filter == pytest.approx(qual_mask)
-     assert pha.quality == pytest.approx([0, 0, 2, 0, 0, 0, 2])
-@@ -2536,7 +2549,7 @@ def test_pha_group_ignore_bad_then_group(caplog):
-     pha.ignore_bad()
-     assert len(caplog.records) == 0
- 
--    qual_mask = [True] * 2 + [False] + [True] * 3 + [False]
-+    qual_mask = np.asarray([True] * 2 + [False] + [True] * 3 + [False])
-     assert pha.mask is True
-     assert pha.get_mask() == pytest.approx(qual_mask)
-     assert pha.quality_filter == pytest.approx(qual_mask)
-@@ -2562,7 +2575,7 @@ def test_pha_group_ignore_bad_then_group(caplog):
-     pha.ignore_bad()
-     assert len(caplog.records) == 0
- 
--    qual_mask = [True] + [False] + [True] * 5
-+    qual_mask = np.asarray([True] + [False] + [True] * 5)
-     assert pha.mask is True
-     assert pha.get_mask() == pytest.approx(qual_mask)
-     assert pha.get_filter() == '1:7'
-@@ -2584,7 +2597,7 @@ def test_pha_filter_ignore_bad_filter(caplog):
-     pha.ignore(lo=4, hi=4)
-     assert len(caplog.records) == 0
- 
--    data_mask = [True] * 3 + [False] + [True] * 3
-+    data_mask = np.asarray([True] * 3 + [False] + [True] * 3)
-     assert pha.mask == pytest.approx(data_mask)
-     assert pha.get_mask() == pytest.approx(data_mask)
-     assert pha.get_filter() == '1:3,5:7'
-@@ -2596,7 +2609,8 @@ def test_pha_filter_ignore_bad_filter(caplog):
-     pha.group_counts(5)
-     assert len(caplog.records) == 0
- 
--    assert pha.mask == pytest.approx([True] * 2 + [False] + [True] * 3)
-+    data_mask2 = np.asarray([True] * 2 + [False] + [True] * 3)
-+    assert pha.mask == pytest.approx(data_mask2)
-     assert pha.get_mask() == pytest.approx(data_mask)
-     assert pha.get_filter() == '1:3,5:7'
-     assert pha.quality_filter is None
-@@ -2612,7 +2626,7 @@ def test_pha_filter_ignore_bad_filter(caplog):
-     assert r.levelname == "WARNING"
-     assert r.getMessage() == "filtering grouped data with quality flags, previous filters deleted"
- 
--    new_mask = [True] * 2 + [False] + [True] * 4
-+    new_mask = np.asarray([True] * 2 + [False] + [True] * 4)
-     assert pha.mask is True
-     assert pha.get_mask() == pytest.approx(new_mask)
-     assert pha.get_filter() == '1:7'
-@@ -2624,8 +2638,10 @@ def test_pha_filter_ignore_bad_filter(caplog):
-     pha.ignore(lo=2, hi=2)
-     assert len(caplog.records) == 1
- 
--    assert pha.mask == pytest.approx([False] + [True] * 4)
--    assert pha.get_mask() == pytest.approx([False] * 2 + [True] * 4)
-+    mask3 = np.asarray([False] + [True] * 4)
-+    mask3_full = np.asarray([False] * 2 + [True] * 4)
-+    assert pha.mask == pytest.approx(mask3)
-+    assert pha.get_mask() == pytest.approx(mask3_full)
-     assert pha.get_filter() == '4:7'
-     assert pha.quality_filter == pytest.approx(new_mask)
-     assert pha.quality == pytest.approx([0, 0, 2, 0, 0, 0, 0])
-@@ -2732,7 +2748,7 @@ def test_pha_ignore_bad_group_quality(caplog):
-     assert pha.get_filter(format="%.1f") == "3.0:7.0"
-     assert pha.get_noticed_channels() == pytest.approx(np.arange(3, 7))
- 
--    omask = [False] * 2 + [True] * 4 + [False] * 4
-+    omask = np.asarray([False] * 2 + [True] * 4 + [False] * 4)
-     assert pha.mask == pytest.approx(omask)
-     assert pha.get_mask() == pytest.approx(omask)
- 
-@@ -2749,7 +2765,8 @@ def test_pha_ignore_bad_group_quality(caplog):
-     assert pha.get_dep(filter=False) == pytest.approx(y)
-     assert pha.get_dep(filter=True) == pytest.approx([3, 1])
- 
--    assert pha.mask == pytest.approx([False] * 2 + [True] * 2 + [False] * 4)
-+    mask = np.asarray([False] * 2 + [True] * 2 + [False] * 4)
-+    assert pha.mask == pytest.approx(mask)
-     assert pha.get_mask() == pytest.approx(omask)
- 
-     grouping = [0, 0, 1, -1, -1,  1, 0, 0, 0, 0]
-@@ -2788,7 +2805,7 @@ def test_pha_ignore_bad_group_quality(caplog):
-     # However, get_mask reflects the quality filter, so is all True
-     # except for the 6th element.
-     #
--    single_bad = [True] * 5 + [False] + [True] * 4
-+    single_bad = np.asarray([True] * 5 + [False] + [True] * 4)
-     assert pha.get_mask() == pytest.approx(single_bad)
- 
-     # What about the quality fields?
-@@ -2862,7 +2879,7 @@ def test_pha_ignore_bad_quality(groupit, caplog):
-     assert pha.get_dep(filter=False) == pytest.approx(y)
-     assert pha.get_dep(filter=True) == pytest.approx(y[2:6])
- 
--    mask = [False] * 2 + [True] * 4 + [False] * 4
-+    mask = np.asarray([False] * 2 + [True] * 4 + [False] * 4)
-     assert pha.mask == pytest.approx(mask)
-     assert pha.get_mask() == pytest.approx(mask)
- 
-@@ -2900,7 +2917,7 @@ def test_pha_ignore_bad_quality(groupit, caplog):
- 
-     # The mask changed (the channel=6 value is now filtered out).
-     #
--    mask2 = [False] * 2 + [True] * 3 + [False] * 5
-+    mask2 = np.asarray([False] * 2 + [True] * 3 + [False] * 5)
-     assert pha.mask == pytest.approx(mask2)
-     assert pha.get_mask() == pytest.approx(mask2)
- 
-@@ -3098,7 +3115,7 @@ def test_grouped_pha_mask(make_grouped_pha):
- def test_grouped_pha_get_mask(make_grouped_pha):
-     """What is the default get_mask value?"""
-     pha = make_grouped_pha
--    assert pha.get_mask() == pytest.approx([True] * 4 + [False])
-+    assert pha.get_mask() == pytest.approx(np.asarray([True] * 4 + [False]))
- 
- 
- def test_quality_pha_mask(make_quality_pha):
-@@ -3115,11 +3132,13 @@ def test_quality_pha_mask(make_quality_pha):
- def test_quality_pha_get_mask(make_quality_pha):
-     """What is the default get_mask value?"""
-     pha = make_quality_pha
--    assert pha.get_mask() == pytest.approx([True] * 9)
-+    m1 = np.ones(9, dtype=bool)
-+    assert pha.get_mask() == pytest.approx(m1)
- 
-     pha.ignore_bad()
-     # This is a regression test
--    assert pha.get_mask() == pytest.approx([True] + [False] * 2 + [True] * 3 + [False] * 3)
-+    m2 = np.asarray([True] + [False] * 2 + [True] * 3 + [False] * 3)
-+    assert pha.get_mask() == pytest.approx(m2)
- 
- 
- @pytest.mark.parametrize("field,expected",
-@@ -3576,8 +3595,10 @@ def test_pha_quality_filtered_apply_filter_invalid_size(vals, make_grouped_pha):
-     pha.ignore(hi=1)
- 
-     # safety check to make sure we've excluded points
--    assert pha.mask == pytest.approx([False, True])
--    assert pha.get_mask() == pytest.approx([False, False, False, True])
-+    m1 = np.asarray([False, True])
-+    m2 = np.asarray([False, False, False, True])
-+    assert pha.mask == pytest.approx(m1)
-+    assert pha.get_mask() == pytest.approx(m2)
- 
-     with pytest.raises(DataErr,
-                        match="^size mismatch between filtered data and array: 1 vs [28]$"):
-@@ -4193,7 +4214,7 @@ def test_rmf_simple_filter_check(startchan, na, nb, nc):
-     assert rmf.apply_rmf(mvals) == pytest.approx(mvals)
- 
-     selected = rmf.notice([startchan, startchan + 1, startchan + 2])
--    expected = [False] * na + [True] * nb + [False] * nc
-+    expected = np.asarray([False] * na + [True] * nb + [False] * nc)
-     assert selected == pytest.approx(expected)
- 
-     # Drop everything but the selected values.
-@@ -4295,7 +4316,7 @@ def test_rmf_offset_check_square(offset, caplog):
-     nchans = [offset + 2]
- 
-     selected = rmf.notice(nchans)
--    assert selected == pytest.approx([False, True, True, True])
-+    assert selected == pytest.approx(np.asarray([False, True, True, True]))
- 
-     expected2 = [0.0 * 0.2 + 0.6 * 0.4,
-                  0.4 * 0.4 + 0.5 * 0.2,
-@@ -4387,11 +4408,13 @@ def test_rmf_offset_check_rectangular(offset):
-     # - drop the last channel
-     nchans2 = offset + np.arange(0, 9)
- 
-+    mask = np.asarray([True] * 19 + [False])
-+
-     selected2 = rmf.notice(nchans2)
--    assert selected2 == pytest.approx([True] * 19 + [False])
-+    assert selected2 == pytest.approx(mask)
- 
-     selected2 = rmf.notice(offset + np.arange(0, 9))
--    assert selected2 == pytest.approx([True] * 19 + [False])
-+    assert selected2 == pytest.approx(mask)
- 
-     expected2 = mvals[selected2] @ full_matrix[selected2, :]
-     got2 = rmf.apply_rmf(mvals[selected2])
-@@ -4414,8 +4437,11 @@ def test_rmf_offset_check_rectangular(offset):
-     #
-     nchans3 = offset + np.asarray([4, 5, 6])
- 
-+    mask3 = np.asarray([True, False] * 2 + [True] * 10 +
-+                       [False] * 4 + [True, False])
-+
-     selected3 = rmf.notice(nchans3)
--    assert selected3 == pytest.approx([True, False] * 2 + [True] * 10 + [False] * 4 + [True, False])
-+    assert selected3 == pytest.approx(mask3)
- 
-     # It is not clear what the RMF application does here.
-     #
-@@ -5970,7 +5996,7 @@ def test_group_xxx_tabtops_not_ndarray(asarray):
- 
-     assert pha.get_y() == pytest.approx([2, 3, 4.5, 6])
-     assert pha.mask is True
--    assert pha.get_mask() == pytest.approx([True] * 5)
-+    assert pha.get_mask() == pytest.approx(np.ones(5, dtype=bool))
- 
- 
- @requires_group
-@@ -6002,7 +6028,8 @@ def test_group_xxx_tabstops_already_grouped():
-     assert pha.get_y(filter=True) == pytest.approx([12, 5.5, 4])
- 
-     tstops = ~pha.mask
--    assert tstops == pytest.approx([False, True, False, False, True])
-+    mask = np.asarray([False, True, False, False, True])
-+    assert tstops == pytest.approx(mask)
- 
-     # Apply the mask as the tabStops (after inversion) where
-     # len(tstops) < nchannel but does match the number of groups.
-diff --git a/sherpa/astro/tests/test_astro_instrument.py b/sherpa/astro/tests/test_astro_instrument.py
-index b466e3fe5a..584fe371c6 100644
---- a/sherpa/astro/tests/test_astro_instrument.py
-+++ b/sherpa/astro/tests/test_astro_instrument.py
-@@ -712,7 +712,8 @@ def test_rmfmodelpha_delta_no_ebounds(analysis, caplog):
- 
-     assert len(caplog.records) == 0
-     if analysis == "energy":
--        assert pha.mask == pytest.approx([False, True, True, True, False])
-+        expected = np.asarray([False, True, True, True, False])
-+        assert pha.mask == pytest.approx(expected)
-     else:
-         assert not pha.mask.any()
- 
-diff --git a/sherpa/astro/tests/test_astro_plot.py b/sherpa/astro/tests/test_astro_plot.py
-index 3f978728dc..a7df4cb1ee 100644
---- a/sherpa/astro/tests/test_astro_plot.py
-+++ b/sherpa/astro/tests/test_astro_plot.py
-@@ -227,8 +227,8 @@ def test_sourceplot_filtered(caplog, make_basic_datapha):
-     # The filtering should probably be this, but let's test the
-     # current behavior:
-     #
--    # expected = [False] * 2 + [True] * 6 + [False] * 2
--    expected = [False] * 3 + [True] * 5 + [False] * 2
-+    # expected = np.asarray([False] * 2 + [True] * 6 + [False] * 2)
-+    expected = np.asarray([False] * 3 + [True] * 5 + [False] * 2)
-     assert sp.mask == pytest.approx(expected)
-     assert len(caplog.records) == 0
-     check_sourceplot_energy(sp)
-@@ -365,7 +365,7 @@ def test_sourceplot_wavelength_filtered(caplog, make_basic_datapha):
-     # Given the filtering for energy didn't quite match, DJB is
-     # slightly surprised this works.
-     #
--    expected = [False] * 2 + [True] * 6 + [False] * 2
-+    expected = np.asarray([False] * 2 + [True] * 6 + [False] * 2)
-     assert sp.mask == pytest.approx(expected)
-     assert len(caplog.records) == 0
-     check_sourceplot_wavelength(sp)
-diff --git a/sherpa/astro/ui/tests/test_astro_ui.py b/sherpa/astro/ui/tests/test_astro_ui.py
-index 26acfb96b0..f6872a3497 100644
---- a/sherpa/astro/ui/tests/test_astro_ui.py
-+++ b/sherpa/astro/ui/tests/test_astro_ui.py
-@@ -1962,7 +1962,8 @@ def check_pha_offset(specresp, matrix, energ_lo, energ_hi,
-     ui.notice(0.5, 0.8)
- 
-     data = ui.get_data()
--    assert data.mask == pytest.approx([False] * 3 + [True] * 3 + [False] * 3)
-+    expected = np.asarray([False] * 3 + [True] * 3 + [False] * 3)
-+    assert data.mask == pytest.approx(expected)
- 
-     assert ui.get_filter(format="%.2f", delim="-") == "0.45-0.85"
- 
-diff --git a/sherpa/astro/ui/tests/test_astro_ui_unit.py b/sherpa/astro/ui/tests/test_astro_ui_unit.py
-index 5a321fa733..a5c23dca45 100644
---- a/sherpa/astro/ui/tests/test_astro_ui_unit.py
-+++ b/sherpa/astro/ui/tests/test_astro_ui_unit.py
-@@ -2957,7 +2957,7 @@ def test_pha_set_filter_unmasked(simple_pha):
-     expected = [True, True, False, True, False]
-     ui.set_filter(expected)
- 
--    assert data.mask == pytest.approx(expected)
-+    assert data.mask == pytest.approx(np.asarray(expected))
- 
- 
- def test_pha_set_filter_unmasked_wrong(simple_pha):
-@@ -2973,11 +2973,14 @@ def test_pha_set_filter_masked(simple_pha):
- 
-     data = ui.get_data()
- 
-+    mask = np.asarray([True, False, False, False, True])
-+    mask2 = np.asarray([True, False, True, False, True])
-+
-     ui.ignore(4, 8)
--    assert data.mask == pytest.approx([True, False, False, False, True])
-+    assert data.mask == pytest.approx(mask)
- 
-     ui.set_filter(np.asarray([True, False, True, False, False]))
--    assert data.mask == pytest.approx([True, False, True, False, True])
-+    assert data.mask == pytest.approx(mask2)
- 
- 
- def test_pha_set_filter_masked_wrong(simple_pha):
-diff --git a/sherpa/astro/ui/tests/test_filtering.py b/sherpa/astro/ui/tests/test_filtering.py
-index 6e7c331456..eeb41cad3f 100644
---- a/sherpa/astro/ui/tests/test_filtering.py
-+++ b/sherpa/astro/ui/tests/test_filtering.py
-@@ -709,7 +709,7 @@ def test_ignore_bad_simple_comparison(caplog):
- 
-         d = s.get_data(idval)
-         assert d.mask is True
--        assert d.get_mask() == pytest.approx([True] * 5)
-+        assert d.get_mask() == pytest.approx(np.ones(5, dtype=bool))
- 
-     assert len(caplog.records) == 2
-     s.ignore_bad(1)
-@@ -733,7 +733,7 @@ def test_ignore_bad_simple_comparison(caplog):
-     assert s.get_filter(1) == "1,3:5"
-     assert s.get_filter(2) == "1:5"
- 
--    mask = [True] + [False] + [True] * 3
-+    mask = np.asarray([True] + [False] + [True] * 3)
-     d1 = s.get_data(1)
-     assert d1.mask == pytest.approx(mask)
-     assert d1.get_mask() == pytest.approx(mask)
-@@ -762,12 +762,12 @@ def test_ignore_bad_simple_comparison(caplog):
-     assert s.get_filter(1) == "1,3"
-     assert s.get_filter(2) == "1:3"
- 
--    mask = [True] + [False] + [True] + [False] * 2
-+    mask = np.asarray([True] + [False] + [True] + [False] * 2)
-     d1 = s.get_data(1)
-     assert d1.mask == pytest.approx(mask)
-     assert d1.get_mask() == pytest.approx(mask)
- 
--    mask = [True] * 2 + [False] * 2
-+    mask = np.asarray([True] * 2 + [False] * 2)
-     d2 = s.get_data(2)
-     assert d2.mask == pytest.approx(mask)
-     assert d2.get_mask() == pytest.approx(mask)
-diff --git a/sherpa/astro/utils/tests/test_astro_utils_unit.py b/sherpa/astro/utils/tests/test_astro_utils_unit.py
-index 27551d5d22..de8b5e4bf5 100644
---- a/sherpa/astro/utils/tests/test_astro_utils_unit.py
-+++ b/sherpa/astro/utils/tests/test_astro_utils_unit.py
-@@ -194,7 +194,7 @@ def test_filter_resp_basics(offset, selected, ng, fch, nch, mat, msk):
-     assert f_chan2 == pytest.approx(np.asarray(fch) + delta)
-     assert n_chan2 == pytest.approx(nch)
-     assert matrix2 == pytest.approx(mat)
--    assert mask2 == pytest.approx(msk)
-+    assert mask2 == pytest.approx(np.asarray(msk))
- 
- 
- @pytest.mark.parametrize("lo, hi, expected",
-@@ -414,7 +414,8 @@ def test_qual_setting():
-     """Regression test."""
- 
-     pha = make_data("qual")
--    assert pha.quality_filter == pytest.approx([True, True, False, True])
-+    expected = np.asarray([True, True, False, True])
-+    assert pha.quality_filter == pytest.approx(expected)
- 
- 
- @pytest.mark.parametrize("data_class", ["1d", "1dint", "pha", "grp", "qual"])
-@@ -869,4 +870,5 @@ def test_expand_grouped_mask_ingalid_group():
- def test_expand_grouped_mask(mask, group, expected):
-     """Check how test_expand_grouped_mask works."""
- 
--    assert expand_grouped_mask(mask, group) == pytest.approx(expected)
-+    evals = np.asarray(expected)
-+    assert expand_grouped_mask(mask, group) == pytest.approx(evals)
-diff --git a/sherpa/tests/test_data.py b/sherpa/tests/test_data.py
-index f7a41ebf79..e6744aeb8d 100644
---- a/sherpa/tests/test_data.py
-+++ b/sherpa/tests/test_data.py
-@@ -1321,7 +1321,7 @@ def test_data_filter_invalid_size_scalar():
-     x = numpy.asarray([1, 2, 5])
-     d = Data1D('x', x, x)
-     d.ignore(None, 2)
--    assert d.mask == pytest.approx([False, False, True])
-+    assert d.mask == pytest.approx(numpy.asarray([False, False, True]))
- 
-     with pytest.raises(DataErr,
-                        match="Array must be a sequence or None"):
-@@ -1567,7 +1567,7 @@ def test_data1dint_check_limit(ignore, lo, hi, evals):
- 
-     c1, c2, c3 = evals
-     expected = [vout] * c1 + [vin] * c2 + [vout] * c3
--    assert d.mask == pytest.approx(expected)
-+    assert d.mask == pytest.approx(numpy.asarray(expected))
- 
- 
- def test_filter_apply_none():
-@@ -1993,7 +1993,7 @@ def test_mask_sent_array_non_bool():
-     expected = [True, False, True, False, True, True, False, True, False, True]
- 
-     data.mask = mask
--    assert data.mask == pytest.approx(expected)
-+    assert data.mask == pytest.approx(numpy.asarray(expected))
- 
- 
- @pytest.mark.parametrize("data", ALL_DATA_CLASSES, indirect=True)
-diff --git a/sherpa/ui/tests/test_session.py b/sherpa/ui/tests/test_session.py
-index 4b352c203b..5723f4a655 100644
---- a/sherpa/ui/tests/test_session.py
-+++ b/sherpa/ui/tests/test_session.py
-@@ -1408,7 +1408,8 @@ def test_load_filter_simple(idval, tmp_path):
-     else:
-         s.load_filter(idval, str(infile), ncols=1, ignore=True)
- 
--    assert s.get_data().mask == pytest.approx([True, True, False])
-+    expected = np.asarray([True, True, False])
-+    assert s.get_data().mask == pytest.approx(expected)
- 
- 
- @pytest.mark.parametrize("idval", [None, 1])
-diff --git a/sherpa/ui/tests/test_ui_unit.py b/sherpa/ui/tests/test_ui_unit.py
-index 99cc4e21b5..14f15a78e0 100644
---- a/sherpa/ui/tests/test_ui_unit.py
-+++ b/sherpa/ui/tests/test_ui_unit.py
-@@ -1209,7 +1209,7 @@ def test_set_filter_unmasked(ignore, clean_ui):
-     ui.load_arrays(1, x, y)
- 
-     data = ui.get_data()
--    assert data.mask
-+    assert data.mask is True
- 
-     if ignore:
-         expected = [False, True, False]
-@@ -1217,7 +1217,7 @@ def test_set_filter_unmasked(ignore, clean_ui):
-         expected = [True, False, True]
- 
-     ui.set_filter(np.asarray([True, False, True]), ignore=ignore)
--    assert data.mask == pytest.approx(expected)
-+    assert data.mask == pytest.approx(np.asarray(expected))
- 
- 
- def test_set_filter_unmasked_wrong(clean_ui):
-@@ -1245,7 +1245,9 @@ def test_set_filter_masked(ignore, clean_ui):
-     ui.ignore(lo=15, hi=45)
- 
-     data = ui.get_data()
--    assert data.mask == pytest.approx([True, False, False, False, True])
-+
-+    orig = np.asarray([True, False, False, False, True])
-+    assert data.mask == pytest.approx(orig)
- 
-     # Unlike test_set_filter_masked the two expected values are not
-     # logical inverses, since we need to consider the existing mask.
-@@ -1256,7 +1258,7 @@ def test_set_filter_masked(ignore, clean_ui):
-         expected = [True, False, True, False, True]
- 
-     ui.set_filter(np.asarray([True, False, True, False, False]), ignore=ignore)
--    assert data.mask == pytest.approx(expected)
-+    assert data.mask == pytest.approx(np.asarray(expected))
- 
- 
- def test_set_filter_masked_wrong(clean_ui):
-diff --git a/sherpa/utils/tests/test_utils.py b/sherpa/utils/tests/test_utils.py
-index a11338d8b8..60e56f82ba 100644
---- a/sherpa/utils/tests/test_utils.py
-+++ b/sherpa/utils/tests/test_utils.py
-@@ -1,5 +1,5 @@
- #
--#  Copyright (C) 2010, 2016, 2018, 2019, 2020, 2021, 2022, 2023
-+#  Copyright (C) 2010, 2016, 2018 - 2024
- #  Smithsonian Astrophysical Observatory
- #
- #
-@@ -374,9 +374,11 @@ def test_filter_bins_one(lo, hi, res):
-     lo>hi.
-     """
- 
-+    expected = numpy.asarray(res)
-+
-     dvals = numpy.asarray([1, 2, 3, 4, 5])
-     flags = utils.filter_bins([lo], [hi], [dvals])
--    assert flags == pytest.approx(res)
-+    assert flags == pytest.approx(expected)
- 
-     # We can also check an identity: that
-     #    a <= x <= b
-@@ -385,7 +387,7 @@ def test_filter_bins_one(lo, hi, res):
-     #    x <= b
-     #
-     flags = utils.filter_bins([lo, None], [None, hi], [dvals, dvals])
--    assert flags == pytest.approx(res)
-+    assert flags == pytest.approx(expected)
- 
- 
- 
-@@ -418,7 +420,7 @@ def test_filter_bins_one_int(lo, hi, res):
-     hivals = lovals + 1
-     flags = utils.filter_bins([None, lo], [hi, None], [lovals, hivals],
-                               integrated=True)
--    assert flags == pytest.approx(res)
-+    assert flags == pytest.approx(numpy.asarray(res))
- 
- 
- 
-
-From af47af723c4fb054f037555e9c5fd219871c9695 Mon Sep 17 00:00:00 2001
-From: Douglas Burke <dburke.gw@gmail.com>
-Date: Fri, 6 Dec 2024 12:58:17 -0500
-Subject: [PATCH 2/2] CI: use macos-13 for the macOS Intel run
-
-This also
-
-- bumps up the python version from 3.10 to 3.11
-- adds bokeh to the mac test (as it's supposed to be a
-  "gull build")
-- adds "Intel" to the name of the test, in preparation for
-  adding an ARM build, such as
-  https://github.com/sherpa/sherpa/pull/2198/
----
- .github/workflows/ci-conda-workflow.yml | 7 ++++---
- 1 file changed, 4 insertions(+), 3 deletions(-)
-
-diff --git a/.github/workflows/ci-conda-workflow.yml b/.github/workflows/ci-conda-workflow.yml
-index 6bab3c77ae..507c06efb2 100644
---- a/.github/workflows/ci-conda-workflow.yml
-+++ b/.github/workflows/ci-conda-workflow.yml
-@@ -30,13 +30,14 @@ jobs:
-     strategy:
-       matrix:
-         include:
--          - name: MacOS Full Build
--            os: macos-12
--            python-version: "3.10"
-+          - name: MacOS Intel Full Build
-+            os: macos-13
-+            python-version: "3.11"
-             install-type: develop
-             fits: astropy
-             test-data: submodule
-             matplotlib-version: 3
-+            bokeh-version: 3
-             xspec-version: 12.14.0i
- 
-           - name: Linux Minimum Setup (Python 3.10)