python-sherpa/sherpa-pr2188-np2docstrings.patch

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
 """)