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/dports/devel/py-pythran/pythran-0.11.0/pythran/pythonic/include/numpy/
H A Dcomplex64.hpp16 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
/dports/devel/py-pythran/pythran-0.11.0/pythran/pythonic/numpy/
H A Dcomplex64.hpp19 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
/dports/science/py-cirq-pasqal/Cirq-0.13.1/cirq-core/cirq/qis/
H A Dstates_test.py91 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 …]
/dports/science/py-cirq-core/Cirq-0.13.1/cirq-core/cirq/qis/
H A Dstates_test.py91 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 …]
/dports/science/py-cirq-google/Cirq-0.13.0/cirq-core/cirq/qis/
H A Dstates_test.py91 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 …]
/dports/science/py-cirq-ionq/Cirq-0.13.1/cirq-core/cirq/qis/
H A Dstates_test.py91 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 …]
/dports/science/py-cirq-aqt/Cirq-0.12.0/cirq-core/cirq/qis/
H A Dstates_test.py91 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 …]
/dports/math/py-jax/jax-0.2.9/jax/experimental/jax2tf/tests/
H A Djax2tf_limitations.py152 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 …]
/dports/math/arpack-ng/arpack-ng-3.8.0/EXAMPLES/PYARPACK/
H A DpyarpackDenseLDLT.py.in68 …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…
H A DpyarpackDenseQRPP.py.in67 …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…
H A DpyarpackDenseQRRR.py.in67 …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…
/dports/science/py-cirq-core/Cirq-0.13.1/cirq-core/cirq/protocols/json_test_data/
H A DMixedUnitaryChannel.repr7 (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)),
/dports/science/py-cirq-aqt/Cirq-0.12.0/cirq-core/cirq/protocols/json_test_data/
H A DMixedUnitaryChannel.repr7 (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)),
/dports/science/py-cirq-pasqal/Cirq-0.13.1/cirq-core/cirq/protocols/json_test_data/
H A DMixedUnitaryChannel.repr7 (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)),
/dports/science/py-cirq-google/Cirq-0.13.0/cirq-core/cirq/protocols/json_test_data/
H A DMixedUnitaryChannel.repr7 (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)),
/dports/science/py-cirq-ionq/Cirq-0.13.1/cirq-core/cirq/protocols/json_test_data/
H A DMixedUnitaryChannel.repr7 (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)),
/dports/comms/limesuite/LimeSuite-20.10.0/SoapyLMS7/
H A DBasicStreamTests.py49 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)
/dports/science/py-scipy/scipy-1.7.1/scipy/signal/tests/
H A Dtest_upfirdn.py75 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 …]
/dports/math/py-pandas/pandas-1.2.5/pandas/tests/io/pytables/
H A Dtest_complex.py16 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,
/dports/science/py-cirq-pasqal/Cirq-0.13.1/cirq-core/cirq/sim/
H A Dact_on_state_vector_args_test.py32 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),
/dports/science/py-cirq-core/Cirq-0.13.1/cirq-core/cirq/sim/
H A Dact_on_state_vector_args_test.py32 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),
/dports/science/py-cirq-google/Cirq-0.13.0/cirq-core/cirq/sim/
H A Dact_on_state_vector_args_test.py32 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),
/dports/science/py-cirq-ionq/Cirq-0.13.1/cirq-core/cirq/sim/
H A Dact_on_state_vector_args_test.py32 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),
/dports/science/py-cirq-aqt/Cirq-0.12.0/cirq-core/cirq/sim/
H A Dact_on_state_vector_args_test.py32 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 …]
/dports/devel/py-numba/numba-0.51.2/numba/tests/
H A Dtest_complex.py44 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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