Fix the _array_ methods to avoid deprecation warnings

[RajSapale04]

fixed #26302

The signature of array methods is changed to:
def array(self, dtype=object, copy=None):
if copy is not None and not copy:
raise TypeError("Cannot implement copy=False when converting Matrix to ndarray")
...

as it is changed in the issue #25916

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fixed #26302 

The signature of _array_ methods is changed to:
   def __array__(self, dtype=object, copy=None):
        if copy is not None and not copy:
            raise TypeError("Cannot implement copy=False when converting Matrix to ndarray")
        ...

as it is changed in the issue #25916

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NO ENTRY
<!-- END RELEASE NOTES -->

[github-actions]

Benchmark results from GitHub Actions

Lower numbers are good, higher numbers are bad. A ratio less than 1
means a speed up and greater than 1 means a slowdown. Green lines
beginning with + are slowdowns (the PR is slower then master or
master is slower than the previous release). Red lines beginning
with - are speedups.

Significantly changed benchmark results (PR vs master)

Significantly changed benchmark results (master vs previous release)

| Change   | Before [a00718ba]    | After [8a619fce]    |   Ratio | Benchmark (Parameter)                                                |
|----------|----------------------|---------------------|---------|----------------------------------------------------------------------|
| -        | 70.1±2ms             | 45.6±0.7ms          |    0.65 | integrate.TimeIntegrationRisch02.time_doit(10)                       |
| -        | 69.1±0.5ms           | 45.4±0.5ms          |    0.66 | integrate.TimeIntegrationRisch02.time_doit_risch(10)                 |
| +        | 18.6±0.1μs           | 29.9±0.2μs          |    1.6  | integrate.TimeIntegrationRisch03.time_doit(1)                        |
| -        | 5.34±0.04ms          | 2.89±0.03ms         |    0.54 | logic.LogicSuite.time_load_file                                      |
| -        | 73.3±0.5ms           | 28.6±0.3ms          |    0.39 | polys.TimeGCD_GaussInt.time_op(1, 'dense')                           |
| -        | 25.7±0.1ms           | 17.0±0.2ms          |    0.66 | polys.TimeGCD_GaussInt.time_op(1, 'expr')                            |
| -        | 73.6±0.6ms           | 28.8±0.1ms          |    0.39 | polys.TimeGCD_GaussInt.time_op(1, 'sparse')                          |
| -        | 254±3ms              | 125±0.4ms           |    0.49 | polys.TimeGCD_GaussInt.time_op(2, 'dense')                           |
| -        | 256±2ms              | 125±0.5ms           |    0.49 | polys.TimeGCD_GaussInt.time_op(2, 'sparse')                          |
| -        | 654±3ms              | 378±2ms             |    0.58 | polys.TimeGCD_GaussInt.time_op(3, 'dense')                           |
| -        | 653±4ms              | 373±1ms             |    0.57 | polys.TimeGCD_GaussInt.time_op(3, 'sparse')                          |
| -        | 500±3μs              | 290±2μs             |    0.58 | polys.TimeGCD_LinearDenseQuadraticGCD.time_op(1, 'dense')            |
| -        | 1.78±0.01ms          | 1.05±0.01ms         |    0.59 | polys.TimeGCD_LinearDenseQuadraticGCD.time_op(2, 'dense')            |
| -        | 5.89±0.1ms           | 3.09±0.01ms         |    0.53 | polys.TimeGCD_LinearDenseQuadraticGCD.time_op(3, 'dense')            |
| -        | 448±2μs              | 232±1μs             |    0.52 | polys.TimeGCD_QuadraticNonMonicGCD.time_op(1, 'dense')               |
| -        | 1.49±0.01ms          | 673±3μs             |    0.45 | polys.TimeGCD_QuadraticNonMonicGCD.time_op(2, 'dense')               |
| -        | 4.87±0.02ms          | 1.67±0ms            |    0.34 | polys.TimeGCD_QuadraticNonMonicGCD.time_op(3, 'dense')               |
| -        | 375±4μs              | 206±2μs             |    0.55 | polys.TimeGCD_SparseGCDHighDegree.time_op(1, 'dense')                |
| -        | 2.39±0.01ms          | 1.24±0.01ms         |    0.52 | polys.TimeGCD_SparseGCDHighDegree.time_op(3, 'dense')                |
| -        | 9.97±0.05ms          | 4.31±0.02ms         |    0.43 | polys.TimeGCD_SparseGCDHighDegree.time_op(5, 'dense')                |
| -        | 356±3μs              | 169±2μs             |    0.47 | polys.TimeGCD_SparseNonMonicQuadratic.time_op(1, 'dense')            |
| -        | 2.48±0.02ms          | 896±10μs            |    0.36 | polys.TimeGCD_SparseNonMonicQuadratic.time_op(3, 'dense')            |
| -        | 9.57±0.1ms           | 2.64±0.02ms         |    0.28 | polys.TimeGCD_SparseNonMonicQuadratic.time_op(5, 'dense')            |
| -        | 1.04±0.01ms          | 425±2μs             |    0.41 | polys.TimePREM_LinearDenseQuadraticGCD.time_op(3, 'dense')           |
| -        | 1.71±0.01ms          | 502±5μs             |    0.29 | polys.TimePREM_LinearDenseQuadraticGCD.time_op(3, 'sparse')          |
| -        | 5.88±0.05ms          | 1.83±0.02ms         |    0.31 | polys.TimePREM_LinearDenseQuadraticGCD.time_op(5, 'dense')           |
| -        | 8.41±0.03ms          | 1.49±0.01ms         |    0.18 | polys.TimePREM_LinearDenseQuadraticGCD.time_op(5, 'sparse')          |
| -        | 285±2μs              | 65.1±0.9μs          |    0.23 | polys.TimePREM_QuadraticNonMonicGCD.time_op(1, 'sparse')             |
| -        | 3.45±0.02ms          | 397±3μs             |    0.12 | polys.TimePREM_QuadraticNonMonicGCD.time_op(3, 'dense')              |
| -        | 3.96±0.03ms          | 278±0.2μs           |    0.07 | polys.TimePREM_QuadraticNonMonicGCD.time_op(3, 'sparse')             |
| -        | 6.94±0.08ms          | 1.29±0.01ms         |    0.19 | polys.TimePREM_QuadraticNonMonicGCD.time_op(5, 'dense')              |
| -        | 8.62±0.08ms          | 848±3μs             |    0.1  | polys.TimePREM_QuadraticNonMonicGCD.time_op(5, 'sparse')             |
| -        | 5.00±0.01ms          | 3.01±0.02ms         |    0.6  | polys.TimeSUBRESULTANTS_LinearDenseQuadraticGCD.time_op(2, 'sparse') |
| -        | 12.3±0.2ms           | 6.60±0.08ms         |    0.54 | polys.TimeSUBRESULTANTS_LinearDenseQuadraticGCD.time_op(3, 'dense')  |
| -        | 22.4±0.3ms           | 9.05±0.02ms         |    0.4  | polys.TimeSUBRESULTANTS_LinearDenseQuadraticGCD.time_op(3, 'sparse') |
| -        | 5.27±0.02ms          | 865±4μs             |    0.16 | polys.TimeSUBRESULTANTS_QuadraticNonMonicGCD.time_op(1, 'sparse')    |
| -        | 12.6±0.1ms           | 7.09±0.02ms         |    0.56 | polys.TimeSUBRESULTANTS_QuadraticNonMonicGCD.time_op(2, 'sparse')    |
| -        | 101±0.4ms            | 25.9±0.1ms          |    0.26 | polys.TimeSUBRESULTANTS_QuadraticNonMonicGCD.time_op(3, 'dense')     |
| -        | 168±0.6ms            | 54.1±0.2ms          |    0.32 | polys.TimeSUBRESULTANTS_QuadraticNonMonicGCD.time_op(3, 'sparse')    |
| -        | 171±2μs              | 114±0.9μs           |    0.66 | polys.TimeSUBRESULTANTS_SparseGCDHighDegree.time_op(1, 'dense')      |
| -        | 359±3μs              | 214±1μs             |    0.6  | polys.TimeSUBRESULTANTS_SparseGCDHighDegree.time_op(1, 'sparse')     |
| -        | 4.32±0.06ms          | 844±7μs             |    0.2  | polys.TimeSUBRESULTANTS_SparseGCDHighDegree.time_op(3, 'dense')      |
| -        | 5.29±0.04ms          | 380±2μs             |    0.07 | polys.TimeSUBRESULTANTS_SparseGCDHighDegree.time_op(3, 'sparse')     |
| -        | 20.1±0.2ms           | 2.83±0.01ms         |    0.14 | polys.TimeSUBRESULTANTS_SparseGCDHighDegree.time_op(5, 'dense')      |
| -        | 22.9±0.2ms           | 646±20μs            |    0.03 | polys.TimeSUBRESULTANTS_SparseGCDHighDegree.time_op(5, 'sparse')     |
| -        | 484±6μs              | 135±1μs             |    0.28 | polys.TimeSUBRESULTANTS_SparseNonMonicQuadratic.time_op(1, 'sparse') |
| -        | 4.71±0.01ms          | 620±7μs             |    0.13 | polys.TimeSUBRESULTANTS_SparseNonMonicQuadratic.time_op(3, 'dense')  |
| -        | 5.36±0.04ms          | 140±2μs             |    0.03 | polys.TimeSUBRESULTANTS_SparseNonMonicQuadratic.time_op(3, 'sparse') |
| -        | 13.3±0.05ms          | 1.29±0ms            |    0.1  | polys.TimeSUBRESULTANTS_SparseNonMonicQuadratic.time_op(5, 'dense')  |
| -        | 13.8±0.06ms          | 141±0.3μs           |    0.01 | polys.TimeSUBRESULTANTS_SparseNonMonicQuadratic.time_op(5, 'sparse') |
| -        | 135±0.8μs            | 74.4±1μs            |    0.55 | solve.TimeMatrixOperations.time_rref(3, 0)                           |
| -        | 251±0.6μs            | 87.3±0.5μs          |    0.35 | solve.TimeMatrixOperations.time_rref(4, 0)                           |
| -        | 24.2±0.1ms           | 10.2±0.06ms         |    0.42 | solve.TimeSolveLinSys189x49.time_solve_lin_sys                       |
| -        | 29.2±0.3ms           | 15.7±0.2ms          |    0.54 | solve.TimeSparseSystem.time_linsolve_Aaug(20)                        |
| -        | 55.5±0.3ms           | 25.2±0.04ms         |    0.45 | solve.TimeSparseSystem.time_linsolve_Aaug(30)                        |
| -        | 28.4±0.2ms           | 15.5±0.3ms          |    0.55 | solve.TimeSparseSystem.time_linsolve_Ab(20)                          |
| -        | 54.7±0.3ms           | 25.2±0.1ms          |    0.46 | solve.TimeSparseSystem.time_linsolve_Ab(30)                          |

Full benchmark results can be found as artifacts in GitHub Actions
(click on checks at the top of the PR).

[oscarbenjamin]

There should be some tests for what happens when calling np.array(M) or np.array(M, copy=True/False/None) etc.

[SamLubelsky]

There seems to be an issue with how numpy is currently passing the copy argument to array. See thiscomment.

I will submit the test cases, but will keep the copy=False test cases commented out for now, because they will not pass.