/dports/devel/py-pythran/pythran-0.11.0/pythran/pythonic/include/numpy/ |
H A D | complex64.hpp | 16 std::complex<float> complex64(); 18 std::complex<float> complex64(V v); 20 std::complex<float> complex64(std::complex<T> v); 23 #define NUMPY_NARY_FUNC_NAME complex64 24 #define NUMPY_NARY_FUNC_SYM details::complex64
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/dports/devel/py-pythran/pythran-0.11.0/pythran/pythonic/numpy/ |
H A D | complex64.hpp | 19 std::complex<float> complex64() in complex64() function 25 std::complex<float> complex64(V v) in complex64() function 31 std::complex<float> complex64(std::complex<T> v) in complex64() function 37 #define NUMPY_NARY_FUNC_NAME complex64 38 #define NUMPY_NARY_FUNC_SYM details::complex64
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/dports/science/py-cirq-pasqal/Cirq-0.13.1/cirq-core/cirq/qis/ |
H A D | states_test.py | 91 assert state.dtype == np.complex64 101 assert state.dtype == np.complex64 133 assert state.dtype == np.complex64 148 density_matrix_1 = np.eye(4, dtype=np.complex64) / 4 154 assert state.dtype == np.complex64 167 assert state.dtype == np.complex64 174 density_matrix_1 = np.eye(4, dtype=np.complex64) / 4 180 assert state.dtype == np.complex64 196 density_matrix_1 = np.eye(4, dtype=np.complex64) / 4 197 density_matrix_2 = np.eye(24, dtype=np.complex64) / 24 [all …]
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/dports/science/py-cirq-core/Cirq-0.13.1/cirq-core/cirq/qis/ |
H A D | states_test.py | 91 assert state.dtype == np.complex64 101 assert state.dtype == np.complex64 133 assert state.dtype == np.complex64 148 density_matrix_1 = np.eye(4, dtype=np.complex64) / 4 154 assert state.dtype == np.complex64 167 assert state.dtype == np.complex64 174 density_matrix_1 = np.eye(4, dtype=np.complex64) / 4 180 assert state.dtype == np.complex64 196 density_matrix_1 = np.eye(4, dtype=np.complex64) / 4 197 density_matrix_2 = np.eye(24, dtype=np.complex64) / 24 [all …]
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/dports/science/py-cirq-google/Cirq-0.13.0/cirq-core/cirq/qis/ |
H A D | states_test.py | 91 assert state.dtype == np.complex64 101 assert state.dtype == np.complex64 133 assert state.dtype == np.complex64 148 density_matrix_1 = np.eye(4, dtype=np.complex64) / 4 154 assert state.dtype == np.complex64 167 assert state.dtype == np.complex64 174 density_matrix_1 = np.eye(4, dtype=np.complex64) / 4 180 assert state.dtype == np.complex64 196 density_matrix_1 = np.eye(4, dtype=np.complex64) / 4 197 density_matrix_2 = np.eye(24, dtype=np.complex64) / 24 [all …]
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/dports/science/py-cirq-ionq/Cirq-0.13.1/cirq-core/cirq/qis/ |
H A D | states_test.py | 91 assert state.dtype == np.complex64 101 assert state.dtype == np.complex64 133 assert state.dtype == np.complex64 148 density_matrix_1 = np.eye(4, dtype=np.complex64) / 4 154 assert state.dtype == np.complex64 167 assert state.dtype == np.complex64 174 density_matrix_1 = np.eye(4, dtype=np.complex64) / 4 180 assert state.dtype == np.complex64 196 density_matrix_1 = np.eye(4, dtype=np.complex64) / 4 197 density_matrix_2 = np.eye(24, dtype=np.complex64) / 24 [all …]
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/dports/science/py-cirq-aqt/Cirq-0.12.0/cirq-core/cirq/qis/ |
H A D | states_test.py | 91 assert state.dtype == np.complex64 101 assert state.dtype == np.complex64 133 assert state.dtype == np.complex64 148 density_matrix_1 = np.eye(4, dtype=np.complex64) / 4 154 assert state.dtype == np.complex64 167 assert state.dtype == np.complex64 174 density_matrix_1 = np.eye(4, dtype=np.complex64) / 4 180 assert state.dtype == np.complex64 196 density_matrix_1 = np.eye(4, dtype=np.complex64) / 4 197 density_matrix_2 = np.eye(24, dtype=np.complex64) / 24 [all …]
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/dports/math/py-jax/jax-0.2.9/jax/experimental/jax2tf/tests/ |
H A D | jax2tf_limitations.py | 152 dtypes=[np.complex64, np.complex128], 282 dtypes=[np.complex64, np.complex128], 288 dtypes=[np.complex64, np.complex128], 533 if dtype in [np.float32, np.complex64]: 620 dtypes=[np.complex64, np.complex128], 746 dtypes=[np.complex64, np.complex128], 828 dtypes=np.complex64, 1000 missing_tf_kernel(dtypes=[np.complex64]), 1007 missing_tf_kernel(dtypes=[np.complex64]), 1113 dtypes=[np.complex64], [all …]
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/dports/math/arpack-ng/arpack-ng-3.8.0/EXAMPLES/PYARPACK/ |
H A D | pyarpackDenseLDLT.py.in | 68 …Aij = np.append(Aij, np.complex64(np.complex( 200., 200.))) # Casting value on append is MANDATOR… 69 …Bij = np.append(Bij, np.complex64(np.complex( 33.3, 33.3))) # Casting value on append is MANDATOR… 71 …Aij = np.append(Aij, np.complex64(np.complex(-101., -101.))) # Casting value on append is MANDATOR… 72 …Bij = np.append(Bij, np.complex64(np.complex( 16.6, 16.6))) # Casting value on append is MANDATOR… 74 …Aij = np.append(Aij, np.complex64(np.complex( -99., -99.))) # Casting value on append is MANDATOR… 75 …Bij = np.append(Bij, np.complex64(np.complex( 16.6, 16.6))) # Casting value on append is MANDATOR… 77 …Aij = np.append(Aij, np.complex64(np.complex( 0., 0.))) # Casting value on append is MANDATOR… 78 …Bij = np.append(Bij, np.complex64(np.complex( 0., 0.))) # Casting value on append is MANDATOR…
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H A D | pyarpackDenseQRPP.py.in | 67 …Aij = np.append(Aij, np.complex64(np.complex( 200., 200.))) # Casting value on append is MANDATOR… 68 …Bij = np.append(Bij, np.complex64(np.complex( 33.3, 33.3))) # Casting value on append is MANDATOR… 70 …Aij = np.append(Aij, np.complex64(np.complex(-101., -101.))) # Casting value on append is MANDATOR… 71 …Bij = np.append(Bij, np.complex64(np.complex( 16.6, 16.6))) # Casting value on append is MANDATOR… 73 …Aij = np.append(Aij, np.complex64(np.complex( -99., -99.))) # Casting value on append is MANDATOR… 74 …Bij = np.append(Bij, np.complex64(np.complex( 16.6, 16.6))) # Casting value on append is MANDATOR… 76 …Aij = np.append(Aij, np.complex64(np.complex( 0., 0.))) # Casting value on append is MANDATOR… 77 …Bij = np.append(Bij, np.complex64(np.complex( 0., 0.))) # Casting value on append is MANDATOR…
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H A D | pyarpackDenseQRRR.py.in | 67 …Aij = np.append(Aij, np.complex64(np.complex( 200., 200.))) # Casting value on append is MANDATOR… 68 …Bij = np.append(Bij, np.complex64(np.complex( 33.3, 33.3))) # Casting value on append is MANDATOR… 70 …Aij = np.append(Aij, np.complex64(np.complex(-101., -101.))) # Casting value on append is MANDATOR… 71 …Bij = np.append(Bij, np.complex64(np.complex( 16.6, 16.6))) # Casting value on append is MANDATOR… 73 …Aij = np.append(Aij, np.complex64(np.complex( -99., -99.))) # Casting value on append is MANDATOR… 74 …Bij = np.append(Bij, np.complex64(np.complex( 16.6, 16.6))) # Casting value on append is MANDATOR… 76 …Aij = np.append(Aij, np.complex64(np.complex( 0., 0.))) # Casting value on append is MANDATOR… 77 …Bij = np.append(Bij, np.complex64(np.complex( 0., 0.))) # Casting value on append is MANDATOR…
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/dports/science/py-cirq-core/Cirq-0.13.1/cirq-core/cirq/protocols/json_test_data/ |
H A D | MixedUnitaryChannel.repr | 7 (0.25, np.array([[1, 0], [0, 1]], dtype=np.complex64)), 8 (0.25, np.array([[0, 1], [1, 0]], dtype=np.complex64)), 9 (0.25, np.array([[0, -1j], [1j, 0]], dtype=np.complex64)), 10 (0.25, np.array([[1, 0], [0, -1]], dtype=np.complex64)),
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/dports/science/py-cirq-aqt/Cirq-0.12.0/cirq-core/cirq/protocols/json_test_data/ |
H A D | MixedUnitaryChannel.repr | 7 (0.25, np.array([[1, 0], [0, 1]], dtype=np.complex64)), 8 (0.25, np.array([[0, 1], [1, 0]], dtype=np.complex64)), 9 (0.25, np.array([[0, -1j], [1j, 0]], dtype=np.complex64)), 10 (0.25, np.array([[1, 0], [0, -1]], dtype=np.complex64)),
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/dports/science/py-cirq-pasqal/Cirq-0.13.1/cirq-core/cirq/protocols/json_test_data/ |
H A D | MixedUnitaryChannel.repr | 7 (0.25, np.array([[1, 0], [0, 1]], dtype=np.complex64)), 8 (0.25, np.array([[0, 1], [1, 0]], dtype=np.complex64)), 9 (0.25, np.array([[0, -1j], [1j, 0]], dtype=np.complex64)), 10 (0.25, np.array([[1, 0], [0, -1]], dtype=np.complex64)),
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/dports/science/py-cirq-google/Cirq-0.13.0/cirq-core/cirq/protocols/json_test_data/ |
H A D | MixedUnitaryChannel.repr | 7 (0.25, np.array([[1, 0], [0, 1]], dtype=np.complex64)), 8 (0.25, np.array([[0, 1], [1, 0]], dtype=np.complex64)), 9 (0.25, np.array([[0, -1j], [1j, 0]], dtype=np.complex64)), 10 (0.25, np.array([[1, 0], [0, -1]], dtype=np.complex64)),
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/dports/science/py-cirq-ionq/Cirq-0.13.1/cirq-core/cirq/protocols/json_test_data/ |
H A D | MixedUnitaryChannel.repr | 7 (0.25, np.array([[1, 0], [0, 1]], dtype=np.complex64)), 8 (0.25, np.array([[0, 1], [1, 0]], dtype=np.complex64)), 9 (0.25, np.array([[0, -1j], [1j, 0]], dtype=np.complex64)), 10 (0.25, np.array([[1, 0], [0, -1]], dtype=np.complex64)),
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/dports/comms/limesuite/LimeSuite-20.10.0/SoapyLMS7/ |
H A D | BasicStreamTests.py | 49 buff0 = np.zeros(1024, np.complex64) 50 buff1 = np.zeros(1024, np.complex64) 71 buff0 = np.zeros(1024, np.complex64) 72 buff1 = np.zeros(1024, np.complex64) 100 buff0 = np.zeros(1024, np.complex64) 101 buff1 = np.zeros(1024, np.complex64) 138 buff0 = np.zeros(1024, np.complex64) 139 buff1 = np.zeros(1024, np.complex64) 159 buff0 = np.zeros(1024, np.complex64) 160 buff1 = np.zeros(1024, np.complex64)
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/dports/science/py-scipy/scipy-1.7.1/scipy/signal/tests/ |
H A D | test_upfirdn.py | 75 if self.x_dtype in (np.complex64, np.complex128): 83 if self.x_dtype in (np.complex64, np.complex128): 100 if all(d == np.complex64 for d in dtypes): 101 assert_equal(y.dtype, np.complex64) 102 elif np.complex64 in dtypes and np.float32 in dtypes: 103 assert_equal(y.dtype, np.complex64) 106 elif np.complex128 in dtypes or np.complex64 in dtypes: 113 _UPFIRDN_TYPES = (int, np.float32, np.complex64, float, complex) 172 if dtype in (np.complex64, np.complex128): 251 [np.float32, np.float64, np.complex64, np.complex128], [all …]
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/dports/math/py-pandas/pandas-1.2.5/pandas/tests/io/pytables/ |
H A D | test_complex.py | 16 np.random.rand(4, 5).astype(np.complex64), 39 np.random.rand(4, 5).astype(np.complex64), 62 complex64 = np.array( 63 [1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j], dtype=np.complex64 72 "C": complex64, 85 complex64 = np.array( 86 [1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j], dtype=np.complex64 95 "C": complex64,
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/dports/science/py-cirq-pasqal/Cirq-0.13.1/cirq-core/cirq/sim/ |
H A D | act_on_state_vector_args_test.py | 32 target_tensor=cirq.one_hot(shape=(2, 2, 2), dtype=np.complex64), 33 available_buffer=np.empty((2, 2, 2), dtype=np.complex64), 41 args.target_tensor, cirq.one_hot(index=(0, 1, 0), shape=(2, 2, 2), dtype=np.complex64) 50 target_tensor=cirq.one_hot(shape=(2, 2, 2), dtype=np.complex64), 51 available_buffer=np.empty((2, 2, 2), dtype=np.complex64), 120 bottom_right = cirq.one_hot(index=(3, 3), shape=(4, 4), dtype=np.complex64) 121 top_right = cirq.one_hot(index=(0, 3), shape=(4, 4), dtype=np.complex64) 195 target_tensor=np.array([1, 0], dtype=np.complex64), 196 available_buffer=np.empty(2, dtype=np.complex64),
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/dports/science/py-cirq-core/Cirq-0.13.1/cirq-core/cirq/sim/ |
H A D | act_on_state_vector_args_test.py | 32 target_tensor=cirq.one_hot(shape=(2, 2, 2), dtype=np.complex64), 33 available_buffer=np.empty((2, 2, 2), dtype=np.complex64), 41 args.target_tensor, cirq.one_hot(index=(0, 1, 0), shape=(2, 2, 2), dtype=np.complex64) 50 target_tensor=cirq.one_hot(shape=(2, 2, 2), dtype=np.complex64), 51 available_buffer=np.empty((2, 2, 2), dtype=np.complex64), 120 bottom_right = cirq.one_hot(index=(3, 3), shape=(4, 4), dtype=np.complex64) 121 top_right = cirq.one_hot(index=(0, 3), shape=(4, 4), dtype=np.complex64) 195 target_tensor=np.array([1, 0], dtype=np.complex64), 196 available_buffer=np.empty(2, dtype=np.complex64),
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/dports/science/py-cirq-google/Cirq-0.13.0/cirq-core/cirq/sim/ |
H A D | act_on_state_vector_args_test.py | 32 target_tensor=cirq.one_hot(shape=(2, 2, 2), dtype=np.complex64), 33 available_buffer=np.empty((2, 2, 2), dtype=np.complex64), 41 args.target_tensor, cirq.one_hot(index=(0, 1, 0), shape=(2, 2, 2), dtype=np.complex64) 50 target_tensor=cirq.one_hot(shape=(2, 2, 2), dtype=np.complex64), 51 available_buffer=np.empty((2, 2, 2), dtype=np.complex64), 120 bottom_right = cirq.one_hot(index=(3, 3), shape=(4, 4), dtype=np.complex64) 121 top_right = cirq.one_hot(index=(0, 3), shape=(4, 4), dtype=np.complex64) 195 target_tensor=np.array([1, 0], dtype=np.complex64), 196 available_buffer=np.empty(2, dtype=np.complex64),
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/dports/science/py-cirq-ionq/Cirq-0.13.1/cirq-core/cirq/sim/ |
H A D | act_on_state_vector_args_test.py | 32 target_tensor=cirq.one_hot(shape=(2, 2, 2), dtype=np.complex64), 33 available_buffer=np.empty((2, 2, 2), dtype=np.complex64), 41 args.target_tensor, cirq.one_hot(index=(0, 1, 0), shape=(2, 2, 2), dtype=np.complex64) 50 target_tensor=cirq.one_hot(shape=(2, 2, 2), dtype=np.complex64), 51 available_buffer=np.empty((2, 2, 2), dtype=np.complex64), 120 bottom_right = cirq.one_hot(index=(3, 3), shape=(4, 4), dtype=np.complex64) 121 top_right = cirq.one_hot(index=(0, 3), shape=(4, 4), dtype=np.complex64) 195 target_tensor=np.array([1, 0], dtype=np.complex64), 196 available_buffer=np.empty(2, dtype=np.complex64),
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/dports/science/py-cirq-aqt/Cirq-0.12.0/cirq-core/cirq/sim/ |
H A D | act_on_state_vector_args_test.py | 32 target_tensor=cirq.one_hot(shape=(2, 2, 2), dtype=np.complex64), 33 available_buffer=np.empty((2, 2, 2), dtype=np.complex64), 41 args.target_tensor, cirq.one_hot(index=(0, 1, 0), shape=(2, 2, 2), dtype=np.complex64) 50 target_tensor=cirq.one_hot(shape=(2, 2, 2), dtype=np.complex64), 51 available_buffer=np.empty((2, 2, 2), dtype=np.complex64), 120 bottom_right = cirq.one_hot(index=(3, 3), shape=(4, 4), dtype=np.complex64) 121 top_right = cirq.one_hot(index=(0, 3), shape=(4, 4), dtype=np.complex64) 195 target_tensor=np.array([1, 0], dtype=np.complex64), 196 available_buffer=np.empty(2, dtype=np.complex64), 259 state = np.array([1, 0], dtype=np.complex64) [all …]
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/dports/devel/py-numba/numba-0.51.2/numba/tests/ |
H A D | test_complex.py | 44 prec = 'single' if tx in (types.float32, types.complex64) else 'double' 62 if set([tx, ty]) & set([types.float32, types.complex64]) 81 self.run_unary(real_usecase, [types.complex64, types.complex128], 92 self.run_unary(imag_usecase, [types.complex64, types.complex128], 103 self.run_unary(conjugate_usecase, [types.complex64, types.complex128], 120 (types.complex64, types.complex64)] 133 self.run_unary(pyfunc, [types.complex128, types.complex64], 142 self.run_unary(pyfunc, [types.complex64], 212 (types.complex64, types.complex64)]
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