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added more tests for dtype conversion
fixed errors in col creation of dtypes when calling csr.diags() Ensured that sparsegeometry.finalize accepts any arguments the csr.finalize accepts. Removed casting errors in mat2dtype. This may *hide* potential problems when there are non-zero imaginary parts. We should perhaps later revisit the problem considering that TB + Peierls has complex overlap matrices. Fixed issue when a construct was called with Python intrinsic complex values. Signed-off-by: Nick Papior <[email protected]>
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| Original file line number | Diff line number | Diff line change |
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| # This Source Code Form is subject to the terms of the Mozilla Public | ||
| # License, v. 2.0. If a copy of the MPL was not distributed with this | ||
| # file, You can obtain one at https://mozilla.org/MPL/2.0/. | ||
| from __future__ import annotations | ||
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| import numpy as np | ||
| import pytest | ||
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| import sisl | ||
| from sisl.io.siesta._help import _mat2dtype | ||
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| pytestmark = [pytest.mark.io, pytest.mark.siesta] | ||
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| listify = sisl.utils.listify | ||
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| @pytest.mark.parametrize("sort", [True, False]) | ||
| @pytest.mark.parametrize( | ||
| "matrix,ext", | ||
| (map(lambda x: ("Hamiltonian", x), ["nc", "TSHS"]) | listify) | ||
| + (map(lambda x: ("DensityMatrix", x), ["nc", "DM"]) | listify) | ||
| + (map(lambda x: ("EnergyDensityMatrix", x), ["nc"]) | listify), | ||
| ) | ||
| @pytest.mark.parametrize("read_dtype", [np.float64, np.complex128]) | ||
| @pytest.mark.parametrize("dtype", [np.float32, np.float64, np.complex128]) | ||
| def test_non_colinear(sisl_tmp, sort, matrix, ext, dtype, read_dtype): | ||
| M = getattr(sisl, matrix)(sisl.geom.graphene(), spin=sisl.Spin("NC"), dtype=dtype) | ||
| if np.issubdtype(dtype, np.complexfloating): | ||
| onsite = [0.1 + 0j, 0.2 + 0j, 0.3 + 0.4j] | ||
| nn = [0.2, 0.3, 0.4 + 0.5j] | ||
| else: | ||
| onsite = [0.1, 0.2, 0.3, 0.4] | ||
| nn = [0.2, 0.3, 0.4, 0.5] | ||
| M.construct(([0.1, 1.44], [onsite, nn])) | ||
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| f1 = sisl_tmp(f"M1.{ext}") | ||
| f2 = sisl_tmp(f"M2.{ext}") | ||
| M.write(f1, sort=sort) | ||
| M.finalize() | ||
| with sisl.get_sile(f1) as sile: | ||
| M2 = M.read(sile, dtype=read_dtype) | ||
| M2.write(f2, sort=sort) | ||
| with sisl.get_sile(f2) as sile: | ||
| M3 = M2.read(sile, dtype=read_dtype) | ||
|
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| if sort: | ||
| M.finalize(sort=sort) | ||
| assert M._csr.spsame(M2._csr) | ||
| assert M._csr.spsame(M3._csr) | ||
|
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| from sisl.io.siesta._help import _mat2dtype | ||
|
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| # Convert to the same dtype | ||
| _mat2dtype(M2, dtype) | ||
| _mat2dtype(M3, dtype) | ||
| if M.orthogonal and not M2.orthogonal: | ||
| assert np.allclose(M._csr._D, M2._csr._D[..., :-1]) | ||
| else: | ||
| assert np.allclose(M._csr._D, M2._csr._D) | ||
| if M.orthogonal and not M3.orthogonal: | ||
| assert np.allclose(M._csr._D, M3._csr._D[..., :-1]) | ||
| else: | ||
| assert np.allclose(M._csr._D, M3._csr._D) | ||
|
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|
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| @pytest.mark.parametrize("sort", [True, False]) | ||
| @pytest.mark.parametrize( | ||
| "matrix,ext", | ||
| (map(lambda x: ("Hamiltonian", x), ["nc", "TSHS"]) | listify) | ||
| + (map(lambda x: ("DensityMatrix", x), ["nc", "DM"]) | listify) | ||
| + (map(lambda x: ("EnergyDensityMatrix", x), ["nc"]) | listify), | ||
| ) | ||
| @pytest.mark.parametrize("read_dtype", [np.float64, np.complex128]) | ||
| @pytest.mark.parametrize("dtype", [np.float32, np.float64, np.complex128]) | ||
| def test_spin_orbit(sisl_tmp, sort, matrix, ext, dtype, read_dtype): | ||
| M = getattr(sisl, matrix)(sisl.geom.graphene(), spin=sisl.Spin("SO"), dtype=dtype) | ||
| if np.issubdtype(dtype, np.complexfloating): | ||
| onsite = [0.1 + 0j, 0.2 + 0j, 0.3 + 0.4j, 0.3 - 0.4j] | ||
| nn = [0.2 + 0.1j, 0.3 + 0.3j, 0.4 + 0.5j, 0.4 - 0.5j] | ||
| else: | ||
| onsite = [0.1, 0.2, 0.3, 0.4, 0, 0, 0.3, -0.4] | ||
| nn = [0.2, 0.3, 0.4, 0.5, 0.1, 0.3, 0.4, -0.5] | ||
| M.construct(([0.1, 1.44], [onsite, nn])) | ||
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| f1 = sisl_tmp(f"M1.{ext}") | ||
| f2 = sisl_tmp(f"M2.{ext}") | ||
| M.write(f1, sort=sort) | ||
| M.finalize() | ||
| with sisl.get_sile(f1) as sile: | ||
| M2 = M.read(sile, dtype=read_dtype) | ||
| M2.write(f2, sort=sort) | ||
| with sisl.get_sile(f2) as sile: | ||
| M3 = M2.read(sile, dtype=read_dtype) | ||
|
|
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| if sort: | ||
| M.finalize(sort=sort) | ||
| assert M._csr.spsame(M2._csr) | ||
| assert M._csr.spsame(M3._csr) | ||
|
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| # Convert to the same dtype | ||
| _mat2dtype(M2, dtype) | ||
| _mat2dtype(M3, dtype) | ||
| if M.orthogonal and not M2.orthogonal: | ||
| assert np.allclose(M._csr._D, M2._csr._D[..., :-1]) | ||
| else: | ||
| assert np.allclose(M._csr._D, M2._csr._D) | ||
| if M.orthogonal and not M3.orthogonal: | ||
| assert np.allclose(M._csr._D, M3._csr._D[..., :-1]) | ||
| else: | ||
| assert np.allclose(M._csr._D, M3._csr._D) |
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