From 1eac9d3ee02eac5daff26ca107bde9c1d646a6a6 Mon Sep 17 00:00:00 2001
From: Evgeni Burovski <evgeny.burovskiy@gmail.com>
Date: Fri, 17 Feb 2023 18:03:51 +0300
Subject: [PATCH] TST: add numpy/lib/tests/test_type_check.py

NumPy commit 2aa0bf6973b709724624db8e8a51d8efbdeb5d22  (Feb 2023)
---
 torch_np/_wrapper.py                          |  16 +
 .../tests/numpy_tests/lib/test_type_check.py  | 497 ++++++++++++++++++
 2 files changed, 513 insertions(+)
 create mode 100644 torch_np/tests/numpy_tests/lib/test_type_check.py

diff --git a/torch_np/_wrapper.py b/torch_np/_wrapper.py
index 8fe98ad7..e4521b01 100644
--- a/torch_np/_wrapper.py
+++ b/torch_np/_wrapper.py
@@ -1190,6 +1190,22 @@ def array_equiv(a1, a2):
     return _impl.tensor_equal(a1_t, a2_t)
 
 
+def common_type():
+    raise NotImplementedError
+
+
+def mintypecode():
+    raise NotImplementedError
+
+
+def nan_to_num():
+    raise NotImplementedError
+
+
+def asfarray():
+    raise NotImplementedError
+
+
 ###### mapping from numpy API objects to wrappers from this module ######
 
 # All is in the mapping dict in _mapping.py
diff --git a/torch_np/tests/numpy_tests/lib/test_type_check.py b/torch_np/tests/numpy_tests/lib/test_type_check.py
new file mode 100644
index 00000000..8c9d9df4
--- /dev/null
+++ b/torch_np/tests/numpy_tests/lib/test_type_check.py
@@ -0,0 +1,497 @@
+import pytest
+
+import torch_np as np
+from torch_np.testing import assert_, assert_equal, assert_array_equal
+from pytest import raises as assert_raises
+
+from torch_np import (
+    common_type, mintypecode, isreal, iscomplex, isposinf, isneginf,
+    nan_to_num, isrealobj, iscomplexobj, asfarray, real_if_close
+    )
+
+
+def assert_all(x):
+    assert_(np.all(x), x)
+
+
+@pytest.mark.xfail(reason="common_type not implemented")
+class TestCommonType:
+    def test_basic(self):
+        ai32 = np.array([[1, 2], [3, 4]], dtype=np.int32)
+        af16 = np.array([[1, 2], [3, 4]], dtype=np.float16)
+        af32 = np.array([[1, 2], [3, 4]], dtype=np.float32)
+        af64 = np.array([[1, 2], [3, 4]], dtype=np.float64)
+        acs = np.array([[1+5j, 2+6j], [3+7j, 4+8j]], dtype=np.csingle)
+        acd = np.array([[1+5j, 2+6j], [3+7j, 4+8j]], dtype=np.cdouble)
+        assert_(common_type(ai32) == np.float64)
+        assert_(common_type(af16) == np.float16)
+        assert_(common_type(af32) == np.float32)
+        assert_(common_type(af64) == np.float64)
+        assert_(common_type(acs) == np.csingle)
+        assert_(common_type(acd) == np.cdouble)
+
+
+@pytest.mark.xfail(reason="not implemented")
+class TestMintypecode:
+
+    def test_default_1(self):
+        for itype in '1bcsuwil':
+            assert_equal(mintypecode(itype), 'd')
+        assert_equal(mintypecode('f'), 'f')
+        assert_equal(mintypecode('d'), 'd')
+        assert_equal(mintypecode('F'), 'F')
+        assert_equal(mintypecode('D'), 'D')
+
+    def test_default_2(self):
+        for itype in '1bcsuwil':
+            assert_equal(mintypecode(itype+'f'), 'f')
+            assert_equal(mintypecode(itype+'d'), 'd')
+            assert_equal(mintypecode(itype+'F'), 'F')
+            assert_equal(mintypecode(itype+'D'), 'D')
+        assert_equal(mintypecode('ff'), 'f')
+        assert_equal(mintypecode('fd'), 'd')
+        assert_equal(mintypecode('fF'), 'F')
+        assert_equal(mintypecode('fD'), 'D')
+        assert_equal(mintypecode('df'), 'd')
+        assert_equal(mintypecode('dd'), 'd')
+        #assert_equal(mintypecode('dF',savespace=1),'F')
+        assert_equal(mintypecode('dF'), 'D')
+        assert_equal(mintypecode('dD'), 'D')
+        assert_equal(mintypecode('Ff'), 'F')
+        #assert_equal(mintypecode('Fd',savespace=1),'F')
+        assert_equal(mintypecode('Fd'), 'D')
+        assert_equal(mintypecode('FF'), 'F')
+        assert_equal(mintypecode('FD'), 'D')
+        assert_equal(mintypecode('Df'), 'D')
+        assert_equal(mintypecode('Dd'), 'D')
+        assert_equal(mintypecode('DF'), 'D')
+        assert_equal(mintypecode('DD'), 'D')
+
+    def test_default_3(self):
+        assert_equal(mintypecode('fdF'), 'D')
+        #assert_equal(mintypecode('fdF',savespace=1),'F')
+        assert_equal(mintypecode('fdD'), 'D')
+        assert_equal(mintypecode('fFD'), 'D')
+        assert_equal(mintypecode('dFD'), 'D')
+
+        assert_equal(mintypecode('ifd'), 'd')
+        assert_equal(mintypecode('ifF'), 'F')
+        assert_equal(mintypecode('ifD'), 'D')
+        assert_equal(mintypecode('idF'), 'D')
+        #assert_equal(mintypecode('idF',savespace=1),'F')
+        assert_equal(mintypecode('idD'), 'D')
+
+
+@pytest.mark.xfail(reason="not implemented")
+class TestIsscalar:
+
+    def test_basic(self):
+        assert_(np.isscalar(3))
+        assert_(not np.isscalar([3]))
+        assert_(not np.isscalar((3,)))
+        assert_(np.isscalar(3j))
+        assert_(np.isscalar(4.0))
+
+
+@pytest.mark.xfail(reason="not implemented")
+class TestReal:
+
+    def test_real(self):
+        y = np.random.rand(10,)
+        assert_array_equal(y, np.real(y))
+
+        y = np.array(1)
+        out = np.real(y)
+        assert_array_equal(y, out)
+        assert_(isinstance(out, np.ndarray))
+
+        y = 1
+        out = np.real(y)
+        assert_equal(y, out)
+        assert_(not isinstance(out, np.ndarray))
+
+    def test_cmplx(self):
+        y = np.random.rand(10,)+1j*np.random.rand(10,)
+        assert_array_equal(y.real, np.real(y))
+
+        y = np.array(1 + 1j)
+        out = np.real(y)
+        assert_array_equal(y.real, out)
+        assert_(isinstance(out, np.ndarray))
+
+        y = 1 + 1j
+        out = np.real(y)
+        assert_equal(1.0, out)
+        assert_(not isinstance(out, np.ndarray))
+
+
+@pytest.mark.xfail(reason="not implemented")
+class TestImag:
+
+    def test_real(self):
+        y = np.random.rand(10,)
+        assert_array_equal(0, np.imag(y))
+
+        y = np.array(1)
+        out = np.imag(y)
+        assert_array_equal(0, out)
+        assert_(isinstance(out, np.ndarray))
+
+        y = 1
+        out = np.imag(y)
+        assert_equal(0, out)
+        assert_(not isinstance(out, np.ndarray))
+
+    def test_cmplx(self):
+        y = np.random.rand(10,)+1j*np.random.rand(10,)
+        assert_array_equal(y.imag, np.imag(y))
+
+        y = np.array(1 + 1j)
+        out = np.imag(y)
+        assert_array_equal(y.imag, out)
+        assert_(isinstance(out, np.ndarray))
+
+        y = 1 + 1j
+        out = np.imag(y)
+        assert_equal(1.0, out)
+        assert_(not isinstance(out, np.ndarray))
+
+
+@pytest.mark.xfail(reason="not implemented")
+class TestIscomplex:
+
+    def test_fail(self):
+        z = np.array([-1, 0, 1])
+        res = iscomplex(z)
+        assert_(not np.sometrue(res, axis=0))
+
+    def test_pass(self):
+        z = np.array([-1j, 1, 0])
+        res = iscomplex(z)
+        assert_array_equal(res, [1, 0, 0])
+
+
+@pytest.mark.xfail(reason="not implemented")
+class TestIsreal:
+
+    def test_pass(self):
+        z = np.array([-1, 0, 1j])
+        res = isreal(z)
+        assert_array_equal(res, [1, 1, 0])
+
+    def test_fail(self):
+        z = np.array([-1j, 1, 0])
+        res = isreal(z)
+        assert_array_equal(res, [0, 1, 1])
+
+
+@pytest.mark.xfail(reason="not implemented")
+class TestIscomplexobj:
+
+    def test_basic(self):
+        z = np.array([-1, 0, 1])
+        assert_(not iscomplexobj(z))
+        z = np.array([-1j, 0, -1])
+        assert_(iscomplexobj(z))
+
+    def test_scalar(self):
+        assert_(not iscomplexobj(1.0))
+        assert_(iscomplexobj(1+0j))
+
+    def test_list(self):
+        assert_(iscomplexobj([3, 1+0j, True]))
+        assert_(not iscomplexobj([3, 1, True]))
+
+    def test_duck(self):
+        class DummyComplexArray:
+            @property
+            def dtype(self):
+                return np.dtype(complex)
+        dummy = DummyComplexArray()
+        assert_(iscomplexobj(dummy))
+
+    def test_pandas_duck(self):
+        # This tests a custom np.dtype duck-typed class, such as used by pandas
+        # (pandas.core.dtypes)
+        class PdComplex(np.complex128):
+            pass
+        class PdDtype:
+            name = 'category'
+            names = None
+            type = PdComplex
+            kind = 'c'
+            str = '<c16'
+            base = np.dtype('complex128')
+        class DummyPd:
+            @property
+            def dtype(self):
+                return PdDtype
+        dummy = DummyPd()
+        assert_(iscomplexobj(dummy))
+
+    def test_custom_dtype_duck(self):
+        class MyArray(list):
+            @property
+            def dtype(self):
+                return complex
+
+        a = MyArray([1+0j, 2+0j, 3+0j])
+        assert_(iscomplexobj(a))
+
+
+@pytest.mark.xfail(reason="not implemented")
+class TestIsrealobj:
+    def test_basic(self):
+        z = np.array([-1, 0, 1])
+        assert_(isrealobj(z))
+        z = np.array([-1j, 0, -1])
+        assert_(not isrealobj(z))
+
+
+@pytest.mark.xfail(reason="not implemented")
+class TestIsnan:
+
+    def test_goodvalues(self):
+        z = np.array((-1., 0., 1.))
+        res = np.isnan(z) == 0
+        assert_all(np.all(res, axis=0))
+
+    def test_posinf(self):
+        with np.errstate(divide='ignore'):
+            assert_all(np.isnan(np.array((1.,))/0.) == 0)
+
+    def test_neginf(self):
+        with np.errstate(divide='ignore'):
+            assert_all(np.isnan(np.array((-1.,))/0.) == 0)
+
+    def test_ind(self):
+        with np.errstate(divide='ignore', invalid='ignore'):
+            assert_all(np.isnan(np.array((0.,))/0.) == 1)
+
+    def test_integer(self):
+        assert_all(np.isnan(1) == 0)
+
+    def test_complex(self):
+        assert_all(np.isnan(1+1j) == 0)
+
+    def test_complex1(self):
+        with np.errstate(divide='ignore', invalid='ignore'):
+            assert_all(np.isnan(np.array(0+0j)/0.) == 1)
+
+
+@pytest.mark.xfail(reason="not implemented")
+class TestIsfinite:
+    # Fixme, wrong place, isfinite now ufunc
+
+    def test_goodvalues(self):
+        z = np.array((-1., 0., 1.))
+        res = np.isfinite(z) == 1
+        assert_all(np.all(res, axis=0))
+
+    def test_posinf(self):
+        with np.errstate(divide='ignore', invalid='ignore'):
+            assert_all(np.isfinite(np.array((1.,))/0.) == 0)
+
+    def test_neginf(self):
+        with np.errstate(divide='ignore', invalid='ignore'):
+            assert_all(np.isfinite(np.array((-1.,))/0.) == 0)
+
+    def test_ind(self):
+        with np.errstate(divide='ignore', invalid='ignore'):
+            assert_all(np.isfinite(np.array((0.,))/0.) == 0)
+
+    def test_integer(self):
+        assert_all(np.isfinite(1) == 1)
+
+    def test_complex(self):
+        assert_all(np.isfinite(1+1j) == 1)
+
+    def test_complex1(self):
+        with np.errstate(divide='ignore', invalid='ignore'):
+            assert_all(np.isfinite(np.array(1+1j)/0.) == 0)
+
+
+@pytest.mark.xfail(reason="not implemented")
+class TestIsinf:
+    # Fixme, wrong place, isinf now ufunc
+
+    def test_goodvalues(self):
+        z = np.array((-1., 0., 1.))
+        res = np.isinf(z) == 0
+        assert_all(np.all(res, axis=0))
+
+    def test_posinf(self):
+        with np.errstate(divide='ignore', invalid='ignore'):
+            assert_all(np.isinf(np.array((1.,))/0.) == 1)
+
+    def test_posinf_scalar(self):
+        with np.errstate(divide='ignore', invalid='ignore'):
+            assert_all(np.isinf(np.array(1.,)/0.) == 1)
+
+    def test_neginf(self):
+        with np.errstate(divide='ignore', invalid='ignore'):
+            assert_all(np.isinf(np.array((-1.,))/0.) == 1)
+
+    def test_neginf_scalar(self):
+        with np.errstate(divide='ignore', invalid='ignore'):
+            assert_all(np.isinf(np.array(-1.)/0.) == 1)
+
+    def test_ind(self):
+        with np.errstate(divide='ignore', invalid='ignore'):
+            assert_all(np.isinf(np.array((0.,))/0.) == 0)
+
+
+@pytest.mark.xfail(reason="not implemented")
+class TestIsposinf:
+
+    def test_generic(self):
+        with np.errstate(divide='ignore', invalid='ignore'):
+            vals = isposinf(np.array((-1., 0, 1))/0.)
+        assert_(vals[0] == 0)
+        assert_(vals[1] == 0)
+        assert_(vals[2] == 1)
+
+
+@pytest.mark.xfail(reason="not implemented")
+class TestIsneginf:
+
+    def test_generic(self):
+        with np.errstate(divide='ignore', invalid='ignore'):
+            vals = isneginf(np.array((-1., 0, 1))/0.)
+        assert_(vals[0] == 1)
+        assert_(vals[1] == 0)
+        assert_(vals[2] == 0)
+
+
+@pytest.mark.xfail(reason="not implemented")
+class TestNanToNum:
+
+    def test_generic(self):
+        with np.errstate(divide='ignore', invalid='ignore'):
+            vals = nan_to_num(np.array((-1., 0, 1))/0.)
+        assert_all(vals[0] < -1e10) and assert_all(np.isfinite(vals[0]))
+        assert_(vals[1] == 0)
+        assert_all(vals[2] > 1e10) and assert_all(np.isfinite(vals[2]))
+        assert_equal(type(vals), np.ndarray)
+        
+        # perform the same tests but with nan, posinf and neginf keywords
+        with np.errstate(divide='ignore', invalid='ignore'):
+            vals = nan_to_num(np.array((-1., 0, 1))/0., 
+                              nan=10, posinf=20, neginf=30)
+        assert_equal(vals, [30, 10, 20])
+        assert_all(np.isfinite(vals[[0, 2]]))
+        assert_equal(type(vals), np.ndarray)
+
+        # perform the same test but in-place
+        with np.errstate(divide='ignore', invalid='ignore'):
+            vals = np.array((-1., 0, 1))/0.
+        result = nan_to_num(vals, copy=False)
+
+        assert_(result is vals)
+        assert_all(vals[0] < -1e10) and assert_all(np.isfinite(vals[0]))
+        assert_(vals[1] == 0)
+        assert_all(vals[2] > 1e10) and assert_all(np.isfinite(vals[2]))
+        assert_equal(type(vals), np.ndarray)
+        
+        # perform the same test but in-place
+        with np.errstate(divide='ignore', invalid='ignore'):
+            vals = np.array((-1., 0, 1))/0.
+        result = nan_to_num(vals, copy=False, nan=10, posinf=20, neginf=30)
+
+        assert_(result is vals)
+        assert_equal(vals, [30, 10, 20])
+        assert_all(np.isfinite(vals[[0, 2]]))
+        assert_equal(type(vals), np.ndarray)
+
+    def test_array(self):
+        vals = nan_to_num([1])
+        assert_array_equal(vals, np.array([1], int))
+        assert_equal(type(vals), np.ndarray)
+        vals = nan_to_num([1], nan=10, posinf=20, neginf=30)
+        assert_array_equal(vals, np.array([1], int))
+        assert_equal(type(vals), np.ndarray)
+
+    def test_integer(self):
+        vals = nan_to_num(1)
+        assert_all(vals == 1)
+        assert_equal(type(vals), np.int_)
+        vals = nan_to_num(1, nan=10, posinf=20, neginf=30)
+        assert_all(vals == 1)
+        assert_equal(type(vals), np.int_)
+
+    def test_float(self):
+        vals = nan_to_num(1.0)
+        assert_all(vals == 1.0)
+        assert_equal(type(vals), np.float_)
+        vals = nan_to_num(1.1, nan=10, posinf=20, neginf=30)
+        assert_all(vals == 1.1)
+        assert_equal(type(vals), np.float_)
+
+    def test_complex_good(self):
+        vals = nan_to_num(1+1j)
+        assert_all(vals == 1+1j)
+        assert_equal(type(vals), np.complex_)
+        vals = nan_to_num(1+1j, nan=10, posinf=20, neginf=30)
+        assert_all(vals == 1+1j)
+        assert_equal(type(vals), np.complex_)
+
+    def test_complex_bad(self):
+        with np.errstate(divide='ignore', invalid='ignore'):
+            v = 1 + 1j
+            v += np.array(0+1.j)/0.
+        vals = nan_to_num(v)
+        # !! This is actually (unexpectedly) zero
+        assert_all(np.isfinite(vals))
+        assert_equal(type(vals), np.complex_)
+
+    def test_complex_bad2(self):
+        with np.errstate(divide='ignore', invalid='ignore'):
+            v = 1 + 1j
+            v += np.array(-1+1.j)/0.
+        vals = nan_to_num(v)
+        assert_all(np.isfinite(vals))
+        assert_equal(type(vals), np.complex_)
+        # Fixme
+        #assert_all(vals.imag > 1e10)  and assert_all(np.isfinite(vals))
+        # !! This is actually (unexpectedly) positive
+        # !! inf.  Comment out for now, and see if it
+        # !! changes
+        #assert_all(vals.real < -1e10) and assert_all(np.isfinite(vals))
+    
+    def test_do_not_rewrite_previous_keyword(self):
+        # This is done to test that when, for instance, nan=np.inf then these 
+        # values are not rewritten by posinf keyword to the posinf value.
+        with np.errstate(divide='ignore', invalid='ignore'):
+            vals = nan_to_num(np.array((-1., 0, 1))/0., nan=np.inf, posinf=999)
+        assert_all(np.isfinite(vals[[0, 2]]))
+        assert_all(vals[0] < -1e10)
+        assert_equal(vals[[1, 2]], [np.inf, 999])
+        assert_equal(type(vals), np.ndarray)
+
+
+@pytest.mark.xfail(reason="not implemented")
+class TestRealIfClose:
+
+    def test_basic(self):
+        a = np.random.rand(10)
+        b = real_if_close(a+1e-15j)
+        assert_all(isrealobj(b))
+        assert_array_equal(a, b)
+        b = real_if_close(a+1e-7j)
+        assert_all(iscomplexobj(b))
+        b = real_if_close(a+1e-7j, tol=1e-6)
+        assert_all(isrealobj(b))
+
+
+@pytest.mark.xfail(reason="not implemented")
+class TestArrayConversion:
+
+    def test_asfarray(self):
+        a = asfarray(np.array([1, 2, 3]))
+        assert_equal(a.__class__, np.ndarray)
+        assert_(np.issubdtype(a.dtype, np.floating))
+
+        # previously this would infer dtypes from arrays, unlike every single
+        # other numpy function
+        assert_raises(TypeError,
+            asfarray, np.array([1, 2, 3]), dtype=np.array(1.0))