sagemathgh-39242: Make tests compatible with numpy 2.1
    
Related to sagemath#38250 .

In numpy 2.1 it returns a `Token` object which gets printed out. This
assigns it to `_`.


### 📝 Checklist

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- [x] The title is concise and informative.
- [x] The description explains in detail what this PR is about.
- [x] I have linked a relevant issue or discussion.
- [x] I have created tests covering the changes.
- [x] I have updated the documentation and checked the documentation
preview.

### ⌛ Dependencies

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URL: sagemath#39242
Reported by: user202729
Reviewer(s): Tobias Diez, user202729

Author: Release Manager

src/doc/en/prep/Quickstarts/Statistics-and-Distributions.rst

@@ -25,7 +25,7 @@ the standard deviation::
 
     sage: import numpy as np
     sage: if int(np.version.short_version[0]) > 1:
-    ....:     np.set_printoptions(legacy="1.25")
+    ....:     _ = np.set_printoptions(legacy="1.25")
     sage: np.mean([1, 2, 3, 5])
     2.75
 

src/doc/en/thematic_tutorials/numerical_sage/numpy.rst

@@ -8,7 +8,7 @@ import it.
 
     sage: import numpy
     sage: if int(numpy.version.short_version[0]) > 1:
-    ....:     numpy.set_printoptions(legacy="1.25")  # to ensure numpy 2.0 compatibility
+    ....:     _ = numpy.set_printoptions(legacy="1.25")  # to ensure numpy 2.0 compatibility
 
 The basic object of computation in NumPy is an array. It is simple to
 create an array.

src/sage/combinat/fully_packed_loop.py

@@ -68,7 +68,7 @@ def _make_color_list(n, colors=None, color_map=None, randomize=False):
 
         sage: import numpy as np
         sage: if int(np.version.short_version[0]) > 1:
-        ....:     np.set_printoptions(legacy="1.25")
+        ....:     _ = np.set_printoptions(legacy="1.25")
         sage: from sage.combinat.fully_packed_loop import _make_color_list
         sage: _make_color_list(5)
         sage: _make_color_list(5, ['blue', 'red'])

src/sage/functions/special.py

@@ -218,7 +218,7 @@ class SphericalHarmonic(BuiltinFunction):
         0.345494149471335
         sage: import numpy as np                                                        # needs scipy
         sage: if int(np.version.short_version[0]) > 1:                                  # needs scipy
-        ....:     np.set_printoptions(legacy="1.25")                                    # needs scipy
+        ....:     _ = np.set_printoptions(legacy="1.25")                                # needs scipy
         sage: import scipy.version
         sage: if scipy.version.version < '1.15.0':
         ....:     from scipy.special import sph_harm # NB: arguments x and y are swapped   # needs scipy

src/sage/numerical/optimize.py

@@ -381,7 +381,7 @@ def minimize(func, x0, gradient=None, hessian=None, algorithm='default',
         ....:    return sum(100.0r*(x[1r:]-x[:-1r]**2.0r)**2.0r + (1r-x[:-1r])**2.0r)
         sage: import numpy
         sage: if int(numpy.version.short_version[0]) > 1:
-        ....:     numpy.set_printoptions(legacy="1.25")
+        ....:     _ = numpy.set_printoptions(legacy="1.25")
         sage: from numpy import zeros
         sage: def rosen_der(x):
         ....:    xm = x[1r:-1r]

src/sage/plot/arrow.py

@@ -55,7 +55,7 @@ def get_minmax_data(self):
 
             sage: import numpy  # to ensure numpy 2.0 compatibility
             sage: if int(numpy.version.short_version[0]) > 1:
-            ....:     numpy.set_printoptions(legacy="1.25")
+            ....:     _ = numpy.set_printoptions(legacy="1.25")
             sage: from sage.plot.arrow import CurveArrow
             sage: b = CurveArrow(path=[[(0,0),(.5,.5),(1,0)],[(.5,1),(0,0)]],
             ....:                options={})

src/sage/plot/multigraphics.py

@@ -766,7 +766,7 @@ def _add_subplot(self, figure, index, **options):
             (0.2, 0.3, 0.4, 0.1)
             sage: import numpy  # to ensure numpy 2.0 compatibility
             sage: if int(numpy.version.short_version[0]) > 1:
-            ....:     numpy.set_printoptions(legacy="1.25")
+            ....:     _ = numpy.set_printoptions(legacy="1.25")
             sage: ax1.get_position().bounds  # tol 1.0e-13
             (0.2, 0.3, 0.4000000000000001, 0.10000000000000003)
         """
@@ -1269,7 +1269,7 @@ def position(self, index):
             sage: G = graphics_array([g1, g2])
             sage: import numpy  # to ensure numpy 2.0 compatibility
             sage: if int(numpy.version.short_version[0]) > 1:
-            ....:     numpy.set_printoptions(legacy="1.25")
+            ....:     _ = numpy.set_printoptions(legacy="1.25")
             sage: G.position(0)  # tol 5.0e-3
             (0.025045451349937315,
              0.03415488992713045,

src/sage/plot/streamline_plot.py

@@ -72,7 +72,7 @@ def get_minmax_data(self):
             sage: x, y = var('x y')
             sage: import numpy  # to ensure numpy 2.0 compatibility
             sage: if int(numpy.version.short_version[0]) > 1:
-            ....:     numpy.set_printoptions(legacy="1.25")
+            ....:     _ = numpy.set_printoptions(legacy="1.25")
             sage: d = streamline_plot((.01*x, x+y), (x,10,20), (y,10,20))[0].get_minmax_data()
             sage: d['xmin']
             10.0

src/sage/rings/integer.pyx

@@ -595,7 +595,7 @@ cdef class Integer(sage.structure.element.EuclideanDomainElement):
             sage: # needs numpy
             sage: import numpy
             sage: if int(numpy.version.short_version[0]) > 1:
-            ....:     numpy.set_printoptions(legacy="1.25")
+            ....:     _ = numpy.set_printoptions(legacy="1.25")
             sage: numpy.int8('12') == 12
             True
             sage: 12 == numpy.int8('12')

src/sage/rings/real_mpfi.pyx

@@ -252,7 +252,7 @@ TESTS::
 
     sage: import numpy                                                                  # needs numpy
     sage: if int(numpy.version.short_version[0]) > 1:                                   # needs numpy
-    ....:     numpy.set_printoptions(legacy="1.25")                                     # needs numpy
+    ....:     _ = numpy.set_printoptions(legacy="1.25")                                     # needs numpy
     sage: RIF(2) == numpy.int8('2')                                                     # needs numpy
     True
     sage: numpy.int8('2') == RIF(2)                                                     # needs numpy