tidy3d.CustomAnisotropicMedium
tidy3d.CustomAnisotropicMedium#
- class tidy3d.CustomAnisotropicMedium#
Bases:
tidy3d.components.medium.AbstractCustomMedium,tidy3d.components.medium.AnisotropicMediumDiagonally anisotropic medium with spatially varying permittivity in each component.
- Parameters
name (Optional[str] = None) – Optional unique name for medium.
frequency_range (Optional[Tuple[float, float]] = None) – [units = (Hz, Hz)]. Optional range of validity for the medium.
allow_gain (Optional[bool] = None) – This field is ignored. Please set
allow_gainin each componentxx (Union[CustomPoleResidue, CustomSellmeier, CustomLorentz, CustomDebye, CustomDrude, CustomMedium]) – Medium describing the xx-component of the diagonal permittivity tensor.
yy (Union[CustomPoleResidue, CustomSellmeier, CustomLorentz, CustomDebye, CustomDrude, CustomMedium]) – Medium describing the yy-component of the diagonal permittivity tensor.
zz (Union[CustomPoleResidue, CustomSellmeier, CustomLorentz, CustomDebye, CustomDrude, CustomMedium]) – Medium describing the zz-component of the diagonal permittivity tensor.
interp_method (Optional[Literal['nearest', 'linear']] = None) – When the value is ‘None’, each component will follow its own interpolation method. When the value is other than ‘None’, the interpolation method specified by this field will override the one in each component.
subpixel (Optional[bool] = None) – This field is ignored. Please set
subpixelin each component
Note
Only diagonal anisotropy is currently supported.
Example
>>> Nx, Ny, Nz = 10, 9, 8 >>> x = np.linspace(-1, 1, Nx) >>> y = np.linspace(-1, 1, Ny) >>> z = np.linspace(-1, 1, Nz) >>> coords = dict(x=x, y=y, z=z) >>> permittivity= SpatialDataArray(np.ones((Nx, Ny, Nz)), coords=coords) >>> conductivity= SpatialDataArray(np.ones((Nx, Ny, Nz)), coords=coords) >>> medium_xx = CustomMedium(permittivity=permittivity, conductivity=conductivity) >>> medium_yy = CustomMedium(permittivity=permittivity, conductivity=conductivity) >>> d_epsilon = SpatialDataArray(np.random.random((Nx, Ny, Nz)), coords=coords) >>> f = SpatialDataArray(1+np.random.random((Nx, Ny, Nz)), coords=coords) >>> delta = SpatialDataArray(np.random.random((Nx, Ny, Nz)), coords=coords) >>> medium_zz = CustomLorentz(eps_inf=permittivity, coeffs=[(d_epsilon,f,delta),]) >>> anisotropic_dielectric = CustomAnisotropicMedium(xx=medium_xx, yy=medium_yy, zz=medium_zz)
Show JSON schema
{ "title": "CustomAnisotropicMedium", "description": "Diagonally anisotropic medium with spatially varying permittivity in each component.\n\nParameters\n----------\nname : Optional[str] = None\n Optional unique name for medium.\nfrequency_range : Optional[Tuple[float, float]] = None\n [units = (Hz, Hz)]. Optional range of validity for the medium.\nallow_gain : Optional[bool] = None\n This field is ignored. Please set ``allow_gain`` in each component\nxx : Union[CustomPoleResidue, CustomSellmeier, CustomLorentz, CustomDebye, CustomDrude, CustomMedium]\n Medium describing the xx-component of the diagonal permittivity tensor.\nyy : Union[CustomPoleResidue, CustomSellmeier, CustomLorentz, CustomDebye, CustomDrude, CustomMedium]\n Medium describing the yy-component of the diagonal permittivity tensor.\nzz : Union[CustomPoleResidue, CustomSellmeier, CustomLorentz, CustomDebye, CustomDrude, CustomMedium]\n Medium describing the zz-component of the diagonal permittivity tensor.\ninterp_method : Optional[Literal['nearest', 'linear']] = None\n When the value is 'None', each component will follow its own interpolation method. When the value is other than 'None', the interpolation method specified by this field will override the one in each component.\nsubpixel : Optional[bool] = None\n This field is ignored. Please set ``subpixel`` in each component\n\nNote\n----\nOnly diagonal anisotropy is currently supported.\n\nExample\n-------\n>>> Nx, Ny, Nz = 10, 9, 8\n>>> x = np.linspace(-1, 1, Nx)\n>>> y = np.linspace(-1, 1, Ny)\n>>> z = np.linspace(-1, 1, Nz)\n>>> coords = dict(x=x, y=y, z=z)\n>>> permittivity= SpatialDataArray(np.ones((Nx, Ny, Nz)), coords=coords)\n>>> conductivity= SpatialDataArray(np.ones((Nx, Ny, Nz)), coords=coords)\n>>> medium_xx = CustomMedium(permittivity=permittivity, conductivity=conductivity)\n>>> medium_yy = CustomMedium(permittivity=permittivity, conductivity=conductivity)\n>>> d_epsilon = SpatialDataArray(np.random.random((Nx, Ny, Nz)), coords=coords)\n>>> f = SpatialDataArray(1+np.random.random((Nx, Ny, Nz)), coords=coords)\n>>> delta = SpatialDataArray(np.random.random((Nx, Ny, Nz)), coords=coords)\n>>> medium_zz = CustomLorentz(eps_inf=permittivity, coeffs=[(d_epsilon,f,delta),])\n>>> anisotropic_dielectric = CustomAnisotropicMedium(xx=medium_xx, yy=medium_yy, zz=medium_zz)", "type": "object", "properties": { "name": { "title": "Name", "description": "Optional unique name for medium.", "type": "string" }, "frequency_range": { "title": "Frequency Range", "description": "Optional range of validity for the medium.", "units": [ "Hz", "Hz" ], "type": "array", "minItems": 2, "maxItems": 2, "items": [ { "type": "number" }, { "type": "number" } ] }, "allow_gain": { "title": "Allow gain medium", "description": "This field is ignored. Please set ``allow_gain`` in each component", "type": "boolean" }, "type": { "title": "Type", "default": "CustomAnisotropicMedium", "enum": [ "CustomAnisotropicMedium" ], "type": "string" }, "xx": { "title": "XX Component", "description": "Medium describing the xx-component of the diagonal permittivity tensor.", "discriminator": { "propertyName": "type", "mapping": { "CustomPoleResidue": "#/definitions/CustomPoleResidue", "CustomSellmeier": "#/definitions/CustomSellmeier", "CustomLorentz": "#/definitions/CustomLorentz", "CustomDebye": "#/definitions/CustomDebye", "CustomDrude": "#/definitions/CustomDrude", "CustomMedium": "#/definitions/CustomMedium" } }, "oneOf": [ { "$ref": "#/definitions/CustomPoleResidue" }, { "$ref": "#/definitions/CustomSellmeier" }, { "$ref": "#/definitions/CustomLorentz" }, { "$ref": "#/definitions/CustomDebye" }, { "$ref": "#/definitions/CustomDrude" }, { "$ref": "#/definitions/CustomMedium" } ] }, "yy": { "title": "YY Component", "description": "Medium describing the yy-component of the diagonal permittivity tensor.", "discriminator": { "propertyName": "type", "mapping": { "CustomPoleResidue": "#/definitions/CustomPoleResidue", "CustomSellmeier": "#/definitions/CustomSellmeier", "CustomLorentz": "#/definitions/CustomLorentz", "CustomDebye": "#/definitions/CustomDebye", "CustomDrude": "#/definitions/CustomDrude", "CustomMedium": "#/definitions/CustomMedium" } }, "oneOf": [ { "$ref": "#/definitions/CustomPoleResidue" }, { "$ref": "#/definitions/CustomSellmeier" }, { "$ref": "#/definitions/CustomLorentz" }, { "$ref": "#/definitions/CustomDebye" }, { "$ref": "#/definitions/CustomDrude" }, { "$ref": "#/definitions/CustomMedium" } ] }, "zz": { "title": "ZZ Component", "description": "Medium describing the zz-component of the diagonal permittivity tensor.", "discriminator": { "propertyName": "type", "mapping": { "CustomPoleResidue": "#/definitions/CustomPoleResidue", "CustomSellmeier": "#/definitions/CustomSellmeier", "CustomLorentz": "#/definitions/CustomLorentz", "CustomDebye": "#/definitions/CustomDebye", "CustomDrude": "#/definitions/CustomDrude", "CustomMedium": "#/definitions/CustomMedium" } }, "oneOf": [ { "$ref": "#/definitions/CustomPoleResidue" }, { "$ref": "#/definitions/CustomSellmeier" }, { "$ref": "#/definitions/CustomLorentz" }, { "$ref": "#/definitions/CustomDebye" }, { "$ref": "#/definitions/CustomDrude" }, { "$ref": "#/definitions/CustomMedium" } ] }, "interp_method": { "title": "Interpolation method", "description": "When the value is 'None', each component will follow its own interpolation method. When the value is other than 'None', the interpolation method specified by this field will override the one in each component.", "enum": [ "nearest", "linear" ], "type": "string" }, "subpixel": { "title": "Subpixel averaging", "description": "This field is ignored. Please set ``subpixel`` in each component", "type": "boolean" } }, "required": [ "xx", "yy", "zz" ], "additionalProperties": false, "definitions": { "CustomPoleResidue": { "title": "CustomPoleResidue", "description": "A spatially varying dispersive medium described by the pole-residue pair model.\nThe frequency-dependence of the complex-valued permittivity is described by:\n\nParameters\n----------\nname : Optional[str] = None\n Optional unique name for medium.\nfrequency_range : Optional[Tuple[float, float]] = None\n [units = (Hz, Hz)]. Optional range of validity for the medium.\nallow_gain : bool = False\n Allow the medium to be active. Caution: simulations with gain medium are unstable, and are likely to diverge.Simulations where 'allow_gain' is set to 'True' will still be charged even if diverged. Monitor data up to the divergence point will still be returned and can be useful in some cases.\neps_inf : SpatialDataArray\n [units = None (relative permittivity)]. Relative permittivity at infinite frequency (:math:`\\epsilon_\\infty`).\npoles : Tuple[Tuple[tidy3d.components.data.data_array.SpatialDataArray, tidy3d.components.data.data_array.SpatialDataArray], ...] = ()\n [units = (rad/sec, rad/sec)]. Tuple of complex-valued (:math:`a_i, c_i`) poles for the model.\ninterp_method : Literal['nearest', 'linear'] = nearest\n Interpolation method to obtain permittivity values that are not supplied at the Yee grids; For grids outside the range of the supplied data, extrapolation will be applied. When the extrapolated value is smaller (greater) than the minimal (maximal) of the supplied data, the extrapolated value will take the minimal (maximal) of the supplied data.\nsubpixel : bool = False\n If ``True`` and simulation's ``subpixel`` is also ``True``, applies subpixel averaging of the permittivity on the interface of the structure, including exterior boundary and intersection interfaces with other structures.\n\nNote\n----\n.. math::\n\n \\epsilon(\\omega) = \\epsilon_\\infty - \\sum_i\n \\left[\\frac{c_i}{j \\omega + a_i} +\n \\frac{c_i^*}{j \\omega + a_i^*}\\right]\n\nExample\n-------\n>>> x = np.linspace(-1, 1, 5)\n>>> y = np.linspace(-1, 1, 6)\n>>> z = np.linspace(-1, 1, 7)\n>>> coords = dict(x=x, y=y, z=z)\n>>> eps_inf = SpatialDataArray(np.ones((5, 6, 7)), coords=coords)\n>>> a1 = SpatialDataArray(-np.random.random((5, 6, 7)), coords=coords)\n>>> c1 = SpatialDataArray(np.random.random((5, 6, 7)), coords=coords)\n>>> a2 = SpatialDataArray(-np.random.random((5, 6, 7)), coords=coords)\n>>> c2 = SpatialDataArray(np.random.random((5, 6, 7)), coords=coords)\n>>> pole_res = CustomPoleResidue(eps_inf=eps_inf, poles=[(a1, c1), (a2, c2)])\n>>> eps = pole_res.eps_model(200e12)", "type": "object", "properties": { "name": { "title": "Name", "description": "Optional unique name for medium.", "type": "string" }, "frequency_range": { "title": "Frequency Range", "description": "Optional range of validity for the medium.", "units": [ "Hz", "Hz" ], "type": "array", "minItems": 2, "maxItems": 2, "items": [ { "type": "number" }, { "type": "number" } ] }, "allow_gain": { "title": "Allow gain medium", "description": "Allow the medium to be active. Caution: simulations with gain medium are unstable, and are likely to diverge.Simulations where 'allow_gain' is set to 'True' will still be charged even if diverged. Monitor data up to the divergence point will still be returned and can be useful in some cases.", "default": false, "type": "boolean" }, "type": { "title": "Type", "default": "CustomPoleResidue", "enum": [ "CustomPoleResidue" ], "type": "string" }, "eps_inf": { "title": "DataArray", "description": "Relative permittivity at infinite frequency (:math:`\\epsilon_\\infty`).", "units": "None (relative permittivity)", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] }, "poles": { "title": "Poles", "description": "Tuple of complex-valued (:math:`a_i, c_i`) poles for the model.", "default": [], "units": [ "rad/sec", "rad/sec" ], "type": "array", "items": { "type": "array", "minItems": 2, "maxItems": 2, "items": [ { "title": "DataArray", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] }, { "title": "DataArray", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] } ] } }, "interp_method": { "title": "Interpolation method", "description": "Interpolation method to obtain permittivity values that are not supplied at the Yee grids; For grids outside the range of the supplied data, extrapolation will be applied. When the extrapolated value is smaller (greater) than the minimal (maximal) of the supplied data, the extrapolated value will take the minimal (maximal) of the supplied data.", "default": "nearest", "enum": [ "nearest", "linear" ], "type": "string" }, "subpixel": { "title": "Subpixel averaging", "description": "If ``True`` and simulation's ``subpixel`` is also ``True``, applies subpixel averaging of the permittivity on the interface of the structure, including exterior boundary and intersection interfaces with other structures.", "default": false, "type": "boolean" } }, "required": [ "eps_inf" ], "additionalProperties": false }, "CustomSellmeier": { "title": "CustomSellmeier", "description": "A spatially varying dispersive medium described by the Sellmeier model.\nThe frequency-dependence of the refractive index is described by:\n\nParameters\n----------\nname : Optional[str] = None\n Optional unique name for medium.\nfrequency_range : Optional[Tuple[float, float]] = None\n [units = (Hz, Hz)]. Optional range of validity for the medium.\nallow_gain : bool = False\n Allow the medium to be active. Caution: simulations with gain medium are unstable, and are likely to diverge.Simulations where 'allow_gain' is set to 'True' will still be charged even if diverged. Monitor data up to the divergence point will still be returned and can be useful in some cases.\ncoeffs : Tuple[Tuple[tidy3d.components.data.data_array.SpatialDataArray, tidy3d.components.data.data_array.SpatialDataArray], ...]\n [units = (None, um^2)]. List of Sellmeier (:math:`B_i, C_i`) coefficients.\ninterp_method : Literal['nearest', 'linear'] = nearest\n Interpolation method to obtain permittivity values that are not supplied at the Yee grids; For grids outside the range of the supplied data, extrapolation will be applied. When the extrapolated value is smaller (greater) than the minimal (maximal) of the supplied data, the extrapolated value will take the minimal (maximal) of the supplied data.\nsubpixel : bool = False\n If ``True`` and simulation's ``subpixel`` is also ``True``, applies subpixel averaging of the permittivity on the interface of the structure, including exterior boundary and intersection interfaces with other structures.\n\nNote\n----\n.. math::\n\n n(\\lambda)^2 = 1 + \\sum_i \\frac{B_i \\lambda^2}{\\lambda^2 - C_i}\n\nExample\n-------\n>>> x = np.linspace(-1, 1, 5)\n>>> y = np.linspace(-1, 1, 6)\n>>> z = np.linspace(-1, 1, 7)\n>>> coords = dict(x=x, y=y, z=z)\n>>> b1 = SpatialDataArray(np.random.random((5, 6, 7)), coords=coords)\n>>> c1 = SpatialDataArray(np.random.random((5, 6, 7)), coords=coords)\n>>> sellmeier_medium = CustomSellmeier(coeffs=[(b1,c1),])\n>>> eps = sellmeier_medium.eps_model(200e12)", "type": "object", "properties": { "name": { "title": "Name", "description": "Optional unique name for medium.", "type": "string" }, "frequency_range": { "title": "Frequency Range", "description": "Optional range of validity for the medium.", "units": [ "Hz", "Hz" ], "type": "array", "minItems": 2, "maxItems": 2, "items": [ { "type": "number" }, { "type": "number" } ] }, "allow_gain": { "title": "Allow gain medium", "description": "Allow the medium to be active. Caution: simulations with gain medium are unstable, and are likely to diverge.Simulations where 'allow_gain' is set to 'True' will still be charged even if diverged. Monitor data up to the divergence point will still be returned and can be useful in some cases.", "default": false, "type": "boolean" }, "type": { "title": "Type", "default": "CustomSellmeier", "enum": [ "CustomSellmeier" ], "type": "string" }, "coeffs": { "title": "Coefficients", "description": "List of Sellmeier (:math:`B_i, C_i`) coefficients.", "units": [ null, "um^2" ], "type": "array", "items": { "type": "array", "minItems": 2, "maxItems": 2, "items": [ { "title": "DataArray", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] }, { "title": "DataArray", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] } ] } }, "interp_method": { "title": "Interpolation method", "description": "Interpolation method to obtain permittivity values that are not supplied at the Yee grids; For grids outside the range of the supplied data, extrapolation will be applied. When the extrapolated value is smaller (greater) than the minimal (maximal) of the supplied data, the extrapolated value will take the minimal (maximal) of the supplied data.", "default": "nearest", "enum": [ "nearest", "linear" ], "type": "string" }, "subpixel": { "title": "Subpixel averaging", "description": "If ``True`` and simulation's ``subpixel`` is also ``True``, applies subpixel averaging of the permittivity on the interface of the structure, including exterior boundary and intersection interfaces with other structures.", "default": false, "type": "boolean" } }, "required": [ "coeffs" ], "additionalProperties": false }, "CustomLorentz": { "title": "CustomLorentz", "description": "A spatially varying dispersive medium described by the Lorentz model.\nThe frequency-dependence of the complex-valued permittivity is described by:\n\nParameters\n----------\nname : Optional[str] = None\n Optional unique name for medium.\nfrequency_range : Optional[Tuple[float, float]] = None\n [units = (Hz, Hz)]. Optional range of validity for the medium.\nallow_gain : bool = False\n Allow the medium to be active. Caution: simulations with gain medium are unstable, and are likely to diverge.Simulations where 'allow_gain' is set to 'True' will still be charged even if diverged. Monitor data up to the divergence point will still be returned and can be useful in some cases.\neps_inf : SpatialDataArray\n [units = None (relative permittivity)]. Relative permittivity at infinite frequency (:math:`\\epsilon_\\infty`).\ncoeffs : Tuple[Tuple[tidy3d.components.data.data_array.SpatialDataArray, tidy3d.components.data.data_array.SpatialDataArray, tidy3d.components.data.data_array.SpatialDataArray], ...]\n [units = (None (relative permittivity), Hz, Hz)]. List of (:math:`\\Delta\\epsilon_i, f_i, \\delta_i`) values for model.\ninterp_method : Literal['nearest', 'linear'] = nearest\n Interpolation method to obtain permittivity values that are not supplied at the Yee grids; For grids outside the range of the supplied data, extrapolation will be applied. When the extrapolated value is smaller (greater) than the minimal (maximal) of the supplied data, the extrapolated value will take the minimal (maximal) of the supplied data.\nsubpixel : bool = False\n If ``True`` and simulation's ``subpixel`` is also ``True``, applies subpixel averaging of the permittivity on the interface of the structure, including exterior boundary and intersection interfaces with other structures.\n\nNote\n----\n.. math::\n\n \\epsilon(f) = \\epsilon_\\infty + \\sum_i\n \\frac{\\Delta\\epsilon_i f_i^2}{f_i^2 - 2jf\\delta_i - f^2}\n\nExample\n-------\n>>> x = np.linspace(-1, 1, 5)\n>>> y = np.linspace(-1, 1, 6)\n>>> z = np.linspace(-1, 1, 7)\n>>> coords = dict(x=x, y=y, z=z)\n>>> eps_inf = SpatialDataArray(np.ones((5, 6, 7)), coords=coords)\n>>> d_epsilon = SpatialDataArray(np.random.random((5, 6, 7)), coords=coords)\n>>> f = SpatialDataArray(1+np.random.random((5, 6, 7)), coords=coords)\n>>> delta = SpatialDataArray(np.random.random((5, 6, 7)), coords=coords)\n>>> lorentz_medium = CustomLorentz(eps_inf=eps_inf, coeffs=[(d_epsilon,f,delta),])\n>>> eps = lorentz_medium.eps_model(200e12)", "type": "object", "properties": { "name": { "title": "Name", "description": "Optional unique name for medium.", "type": "string" }, "frequency_range": { "title": "Frequency Range", "description": "Optional range of validity for the medium.", "units": [ "Hz", "Hz" ], "type": "array", "minItems": 2, "maxItems": 2, "items": [ { "type": "number" }, { "type": "number" } ] }, "allow_gain": { "title": "Allow gain medium", "description": "Allow the medium to be active. Caution: simulations with gain medium are unstable, and are likely to diverge.Simulations where 'allow_gain' is set to 'True' will still be charged even if diverged. Monitor data up to the divergence point will still be returned and can be useful in some cases.", "default": false, "type": "boolean" }, "type": { "title": "Type", "default": "CustomLorentz", "enum": [ "CustomLorentz" ], "type": "string" }, "eps_inf": { "title": "DataArray", "description": "Relative permittivity at infinite frequency (:math:`\\epsilon_\\infty`).", "units": "None (relative permittivity)", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] }, "coeffs": { "title": "Coefficients", "description": "List of (:math:`\\Delta\\epsilon_i, f_i, \\delta_i`) values for model.", "units": [ "None (relative permittivity)", "Hz", "Hz" ], "type": "array", "items": { "type": "array", "minItems": 3, "maxItems": 3, "items": [ { "title": "DataArray", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] }, { "title": "DataArray", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] }, { "title": "DataArray", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] } ] } }, "interp_method": { "title": "Interpolation method", "description": "Interpolation method to obtain permittivity values that are not supplied at the Yee grids; For grids outside the range of the supplied data, extrapolation will be applied. When the extrapolated value is smaller (greater) than the minimal (maximal) of the supplied data, the extrapolated value will take the minimal (maximal) of the supplied data.", "default": "nearest", "enum": [ "nearest", "linear" ], "type": "string" }, "subpixel": { "title": "Subpixel averaging", "description": "If ``True`` and simulation's ``subpixel`` is also ``True``, applies subpixel averaging of the permittivity on the interface of the structure, including exterior boundary and intersection interfaces with other structures.", "default": false, "type": "boolean" } }, "required": [ "eps_inf", "coeffs" ], "additionalProperties": false }, "CustomDebye": { "title": "CustomDebye", "description": "A spatially varying dispersive medium described by the Debye model.\nThe frequency-dependence of the complex-valued permittivity is described by:\n\nParameters\n----------\nname : Optional[str] = None\n Optional unique name for medium.\nfrequency_range : Optional[Tuple[float, float]] = None\n [units = (Hz, Hz)]. Optional range of validity for the medium.\nallow_gain : bool = False\n Allow the medium to be active. Caution: simulations with gain medium are unstable, and are likely to diverge.Simulations where 'allow_gain' is set to 'True' will still be charged even if diverged. Monitor data up to the divergence point will still be returned and can be useful in some cases.\neps_inf : SpatialDataArray\n [units = None (relative permittivity)]. Relative permittivity at infinite frequency (:math:`\\epsilon_\\infty`).\ncoeffs : Tuple[Tuple[tidy3d.components.data.data_array.SpatialDataArray, tidy3d.components.data.data_array.SpatialDataArray], ...]\n [units = (None (relative permittivity), sec)]. List of (:math:`\\Delta\\epsilon_i, \\tau_i`) values for model.\ninterp_method : Literal['nearest', 'linear'] = nearest\n Interpolation method to obtain permittivity values that are not supplied at the Yee grids; For grids outside the range of the supplied data, extrapolation will be applied. When the extrapolated value is smaller (greater) than the minimal (maximal) of the supplied data, the extrapolated value will take the minimal (maximal) of the supplied data.\nsubpixel : bool = False\n If ``True`` and simulation's ``subpixel`` is also ``True``, applies subpixel averaging of the permittivity on the interface of the structure, including exterior boundary and intersection interfaces with other structures.\n\nNote\n----\n.. math::\n\n \\epsilon(f) = \\epsilon_\\infty + \\sum_i\n \\frac{\\Delta\\epsilon_i}{1 - jf\\tau_i}\n\nExample\n-------\n>>> x = np.linspace(-1, 1, 5)\n>>> y = np.linspace(-1, 1, 6)\n>>> z = np.linspace(-1, 1, 7)\n>>> coords = dict(x=x, y=y, z=z)\n>>> eps_inf = SpatialDataArray(1+np.random.random((5, 6, 7)), coords=coords)\n>>> eps1 = SpatialDataArray(np.random.random((5, 6, 7)), coords=coords)\n>>> tau1 = SpatialDataArray(np.random.random((5, 6, 7)), coords=coords)\n>>> debye_medium = CustomDebye(eps_inf=eps_inf, coeffs=[(eps1,tau1),])\n>>> eps = debye_medium.eps_model(200e12)", "type": "object", "properties": { "name": { "title": "Name", "description": "Optional unique name for medium.", "type": "string" }, "frequency_range": { "title": "Frequency Range", "description": "Optional range of validity for the medium.", "units": [ "Hz", "Hz" ], "type": "array", "minItems": 2, "maxItems": 2, "items": [ { "type": "number" }, { "type": "number" } ] }, "allow_gain": { "title": "Allow gain medium", "description": "Allow the medium to be active. Caution: simulations with gain medium are unstable, and are likely to diverge.Simulations where 'allow_gain' is set to 'True' will still be charged even if diverged. Monitor data up to the divergence point will still be returned and can be useful in some cases.", "default": false, "type": "boolean" }, "type": { "title": "Type", "default": "CustomDebye", "enum": [ "CustomDebye" ], "type": "string" }, "eps_inf": { "title": "DataArray", "description": "Relative permittivity at infinite frequency (:math:`\\epsilon_\\infty`).", "units": "None (relative permittivity)", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] }, "coeffs": { "title": "Coefficients", "description": "List of (:math:`\\Delta\\epsilon_i, \\tau_i`) values for model.", "units": [ "None (relative permittivity)", "sec" ], "type": "array", "items": { "type": "array", "minItems": 2, "maxItems": 2, "items": [ { "title": "DataArray", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] }, { "title": "DataArray", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] } ] } }, "interp_method": { "title": "Interpolation method", "description": "Interpolation method to obtain permittivity values that are not supplied at the Yee grids; For grids outside the range of the supplied data, extrapolation will be applied. When the extrapolated value is smaller (greater) than the minimal (maximal) of the supplied data, the extrapolated value will take the minimal (maximal) of the supplied data.", "default": "nearest", "enum": [ "nearest", "linear" ], "type": "string" }, "subpixel": { "title": "Subpixel averaging", "description": "If ``True`` and simulation's ``subpixel`` is also ``True``, applies subpixel averaging of the permittivity on the interface of the structure, including exterior boundary and intersection interfaces with other structures.", "default": false, "type": "boolean" } }, "required": [ "eps_inf", "coeffs" ], "additionalProperties": false }, "CustomDrude": { "title": "CustomDrude", "description": "A spatially varying dispersive medium described by the Drude model.\nThe frequency-dependence of the complex-valued permittivity is described by:\n\nParameters\n----------\nname : Optional[str] = None\n Optional unique name for medium.\nfrequency_range : Optional[Tuple[float, float]] = None\n [units = (Hz, Hz)]. Optional range of validity for the medium.\nallow_gain : bool = False\n Allow the medium to be active. Caution: simulations with gain medium are unstable, and are likely to diverge.Simulations where 'allow_gain' is set to 'True' will still be charged even if diverged. Monitor data up to the divergence point will still be returned and can be useful in some cases.\neps_inf : SpatialDataArray\n [units = None (relative permittivity)]. Relative permittivity at infinite frequency (:math:`\\epsilon_\\infty`).\ncoeffs : Tuple[Tuple[tidy3d.components.data.data_array.SpatialDataArray, tidy3d.components.data.data_array.SpatialDataArray], ...]\n [units = (Hz, Hz)]. List of (:math:`f_i, \\delta_i`) values for model.\ninterp_method : Literal['nearest', 'linear'] = nearest\n Interpolation method to obtain permittivity values that are not supplied at the Yee grids; For grids outside the range of the supplied data, extrapolation will be applied. When the extrapolated value is smaller (greater) than the minimal (maximal) of the supplied data, the extrapolated value will take the minimal (maximal) of the supplied data.\nsubpixel : bool = False\n If ``True`` and simulation's ``subpixel`` is also ``True``, applies subpixel averaging of the permittivity on the interface of the structure, including exterior boundary and intersection interfaces with other structures.\n\nNote\n----\n.. math::\n\n \\epsilon(f) = \\epsilon_\\infty - \\sum_i\n \\frac{ f_i^2}{f^2 + jf\\delta_i}\n\nExample\n-------\n>>> x = np.linspace(-1, 1, 5)\n>>> y = np.linspace(-1, 1, 6)\n>>> z = np.linspace(-1, 1, 7)\n>>> coords = dict(x=x, y=y, z=z)\n>>> eps_inf = SpatialDataArray(np.ones((5, 6, 7)), coords=coords)\n>>> f1 = SpatialDataArray(np.random.random((5, 6, 7)), coords=coords)\n>>> delta1 = SpatialDataArray(np.random.random((5, 6, 7)), coords=coords)\n>>> drude_medium = CustomDrude(eps_inf=eps_inf, coeffs=[(f1,delta1),])\n>>> eps = drude_medium.eps_model(200e12)", "type": "object", "properties": { "name": { "title": "Name", "description": "Optional unique name for medium.", "type": "string" }, "frequency_range": { "title": "Frequency Range", "description": "Optional range of validity for the medium.", "units": [ "Hz", "Hz" ], "type": "array", "minItems": 2, "maxItems": 2, "items": [ { "type": "number" }, { "type": "number" } ] }, "allow_gain": { "title": "Allow gain medium", "description": "Allow the medium to be active. Caution: simulations with gain medium are unstable, and are likely to diverge.Simulations where 'allow_gain' is set to 'True' will still be charged even if diverged. Monitor data up to the divergence point will still be returned and can be useful in some cases.", "default": false, "type": "boolean" }, "type": { "title": "Type", "default": "CustomDrude", "enum": [ "CustomDrude" ], "type": "string" }, "eps_inf": { "title": "DataArray", "description": "Relative permittivity at infinite frequency (:math:`\\epsilon_\\infty`).", "units": "None (relative permittivity)", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] }, "coeffs": { "title": "Coefficients", "description": "List of (:math:`f_i, \\delta_i`) values for model.", "units": [ "Hz", "Hz" ], "type": "array", "items": { "type": "array", "minItems": 2, "maxItems": 2, "items": [ { "title": "DataArray", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] }, { "title": "DataArray", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] } ] } }, "interp_method": { "title": "Interpolation method", "description": "Interpolation method to obtain permittivity values that are not supplied at the Yee grids; For grids outside the range of the supplied data, extrapolation will be applied. When the extrapolated value is smaller (greater) than the minimal (maximal) of the supplied data, the extrapolated value will take the minimal (maximal) of the supplied data.", "default": "nearest", "enum": [ "nearest", "linear" ], "type": "string" }, "subpixel": { "title": "Subpixel averaging", "description": "If ``True`` and simulation's ``subpixel`` is also ``True``, applies subpixel averaging of the permittivity on the interface of the structure, including exterior boundary and intersection interfaces with other structures.", "default": false, "type": "boolean" } }, "required": [ "eps_inf", "coeffs" ], "additionalProperties": false }, "PermittivityDataset": { "title": "PermittivityDataset", "description": "Dataset storing the diagonal components of the permittivity tensor.\n\nParameters\n----------\neps_xx : ScalarFieldDataArray\n Spatial distribution of the xx-component of the relative permittivity.\neps_yy : ScalarFieldDataArray\n Spatial distribution of the yy-component of the relative permittivity.\neps_zz : ScalarFieldDataArray\n Spatial distribution of the zz-component of the relative permittivity.\n\nExample\n-------\n>>> x = [-1,1]\n>>> y = [-2,0,2]\n>>> z = [-3,-1,1,3]\n>>> f = [2e14, 3e14]\n>>> coords = dict(x=x, y=y, z=z, f=f)\n>>> sclr_fld = ScalarFieldDataArray((1+1j) * np.random.random((2,3,4,2)), coords=coords)\n>>> data = PermittivityDataset(eps_xx=sclr_fld, eps_yy=sclr_fld, eps_zz=sclr_fld)", "type": "object", "properties": { "type": { "title": "Type", "default": "PermittivityDataset", "enum": [ "PermittivityDataset" ], "type": "string" }, "eps_xx": { "title": "DataArray", "description": "Spatial distribution of the xx-component of the relative permittivity.", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] }, "eps_yy": { "title": "DataArray", "description": "Spatial distribution of the yy-component of the relative permittivity.", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] }, "eps_zz": { "title": "DataArray", "description": "Spatial distribution of the zz-component of the relative permittivity.", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] } }, "required": [ "eps_xx", "eps_yy", "eps_zz" ], "additionalProperties": false }, "CustomMedium": { "title": "CustomMedium", "description": ":class:`.Medium` with user-supplied permittivity distribution.\n\nParameters\n----------\nname : Optional[str] = None\n Optional unique name for medium.\nfrequency_range : Optional[Tuple[float, float]] = None\n [units = (Hz, Hz)]. Optional range of validity for the medium.\nallow_gain : bool = False\n Allow the medium to be active. Caution: simulations with gain medium are unstable, and are likely to diverge.Simulations where 'allow_gain' is set to 'True' will still be charged even if diverged. Monitor data up to the divergence point will still be returned and can be useful in some cases.\ninterp_method : Literal['nearest', 'linear'] = nearest\n Interpolation method to obtain permittivity values that are not supplied at the Yee grids; For grids outside the range of the supplied data, extrapolation will be applied. When the extrapolated value is smaller (greater) than the minimal (maximal) of the supplied data, the extrapolated value will take the minimal (maximal) of the supplied data.\nsubpixel : bool = False\n If ``True`` and simulation's ``subpixel`` is also ``True``, applies subpixel averaging of the permittivity on the interface of the structure, including exterior boundary and intersection interfaces with other structures.\npermittivity : Optional[SpatialDataArray] = None\n [units = None (relative permittivity)]. Spatial profile of relative permittivity.\nconductivity : Optional[SpatialDataArray] = None\n [units = S/um]. Spatial profile Electric conductivity. Defined such that the imaginary part of the complex permittivity at angular frequency omega is given by conductivity/omega.\neps_dataset : Optional[PermittivityDataset] = None\n [To be deprecated] User-supplied dataset containing complex-valued permittivity as a function of space. Permittivity distribution over the Yee-grid will be interpolated based on ``interp_method``.\n\nExample\n-------\n>>> Nx, Ny, Nz = 10, 9, 8\n>>> X = np.linspace(-1, 1, Nx)\n>>> Y = np.linspace(-1, 1, Ny)\n>>> Z = np.linspace(-1, 1, Nz)\n>>> coords = dict(x=X, y=Y, z=Z)\n>>> permittivity= SpatialDataArray(np.ones((Nx, Ny, Nz)), coords=coords)\n>>> conductivity= SpatialDataArray(np.ones((Nx, Ny, Nz)), coords=coords)\n>>> dielectric = CustomMedium(permittivity=permittivity, conductivity=conductivity)\n>>> eps = dielectric.eps_model(200e12)", "type": "object", "properties": { "name": { "title": "Name", "description": "Optional unique name for medium.", "type": "string" }, "frequency_range": { "title": "Frequency Range", "description": "Optional range of validity for the medium.", "units": [ "Hz", "Hz" ], "type": "array", "minItems": 2, "maxItems": 2, "items": [ { "type": "number" }, { "type": "number" } ] }, "allow_gain": { "title": "Allow gain medium", "description": "Allow the medium to be active. Caution: simulations with gain medium are unstable, and are likely to diverge.Simulations where 'allow_gain' is set to 'True' will still be charged even if diverged. Monitor data up to the divergence point will still be returned and can be useful in some cases.", "default": false, "type": "boolean" }, "type": { "title": "Type", "default": "CustomMedium", "enum": [ "CustomMedium" ], "type": "string" }, "interp_method": { "title": "Interpolation method", "description": "Interpolation method to obtain permittivity values that are not supplied at the Yee grids; For grids outside the range of the supplied data, extrapolation will be applied. When the extrapolated value is smaller (greater) than the minimal (maximal) of the supplied data, the extrapolated value will take the minimal (maximal) of the supplied data.", "default": "nearest", "enum": [ "nearest", "linear" ], "type": "string" }, "subpixel": { "title": "Subpixel averaging", "description": "If ``True`` and simulation's ``subpixel`` is also ``True``, applies subpixel averaging of the permittivity on the interface of the structure, including exterior boundary and intersection interfaces with other structures.", "default": false, "type": "boolean" }, "permittivity": { "title": "DataArray", "description": "Spatial profile of relative permittivity.", "units": "None (relative permittivity)", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] }, "conductivity": { "title": "DataArray", "description": "Spatial profile Electric conductivity. Defined such that the imaginary part of the complex permittivity at angular frequency omega is given by conductivity/omega.", "units": "S/um", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] }, "eps_dataset": { "title": "Permittivity Dataset", "description": "[To be deprecated] User-supplied dataset containing complex-valued permittivity as a function of space. Permittivity distribution over the Yee-grid will be interpolated based on ``interp_method``.", "allOf": [ { "$ref": "#/definitions/PermittivityDataset" } ] } }, "additionalProperties": false } } }
- attribute allow_gain: bool = None#
This field is ignored. Please set
allow_gainin each component- Validated by
_ignored_fields
- attribute frequency_range: Tuple[float, float] = None#
Optional range of validity for the medium.
- Validated by
_ignored_fields
- attribute interp_method: Optional[Literal['nearest', 'linear']] = None#
When the value is ‘None’, each component will follow its own interpolation method. When the value is other than ‘None’, the interpolation method specified by this field will override the one in each component.
- Validated by
_ignored_fields
- attribute name: str = None#
Optional unique name for medium.
- Validated by
_ignored_fieldsfield_has_unique_names
- attribute subpixel: bool = None#
This field is ignored. Please set
subpixelin each component- Validated by
_ignored_fields
- attribute xx: Union[tidy3d.components.medium.CustomPoleResidue, tidy3d.components.medium.CustomSellmeier, tidy3d.components.medium.CustomLorentz, tidy3d.components.medium.CustomDebye, tidy3d.components.medium.CustomDrude, tidy3d.components.medium.CustomMedium] [Required]#
Medium describing the xx-component of the diagonal permittivity tensor.
- Validated by
_ignored_fields_isotropic_xx
- attribute yy: Union[tidy3d.components.medium.CustomPoleResidue, tidy3d.components.medium.CustomSellmeier, tidy3d.components.medium.CustomLorentz, tidy3d.components.medium.CustomDebye, tidy3d.components.medium.CustomDrude, tidy3d.components.medium.CustomMedium] [Required]#
Medium describing the yy-component of the diagonal permittivity tensor.
- Validated by
_ignored_fields_isotropic_yy
- attribute zz: Union[tidy3d.components.medium.CustomPoleResidue, tidy3d.components.medium.CustomSellmeier, tidy3d.components.medium.CustomLorentz, tidy3d.components.medium.CustomDebye, tidy3d.components.medium.CustomDrude, tidy3d.components.medium.CustomMedium] [Required]#
Medium describing the zz-component of the diagonal permittivity tensor.
- Validated by
_ignored_fields_isotropic_zz
- classmethod add_type_field() None#
Automatically place “type” field with model name in the model field dictionary.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model#
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(**kwargs) tidy3d.components.base.Tidy3dBaseModel#
Copy a Tidy3dBaseModel. With
deep=Trueas default.
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny#
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- classmethod dict_from_file(fname: str, group_path: Optional[str] = None) dict#
Loads a dictionary containing the model from a .yaml, .json, or .hdf5 file.
- Parameters
fname (str) – Full path to the .yaml or .json file to load the
Tidy3dBaseModelfrom.group_path (str, optional) – Path to a group inside the file to use as the base level.
- Returns
A dictionary containing the model.
- Return type
dict
Example
>>> simulation = Simulation.from_file(fname='folder/sim.json')
- classmethod dict_from_hdf5(fname: str, group_path: str = '', custom_decoders: Optional[List[Callable]] = None) dict#
Loads a dictionary containing the model contents from a .hdf5 file.
- Parameters
fname (str) – Full path to the .hdf5 file to load the
Tidy3dBaseModelfrom.group_path (str, optional) – Path to a group inside the file to selectively load a sub-element of the model only.
custom_decoders (List[Callable]) – List of functions accepting (fname: str, group_path: str, model_dict: dict, key: str, value: Any) that store the value in the model dict after a custom decoding.
- Returns
Dictionary containing the model.
- Return type
dict
Example
>>> sim_dict = Simulation.dict_from_hdf5(fname='folder/sim.hdf5')
- classmethod dict_from_json(fname: str) dict#
Load dictionary of the model from a .json file.
- Parameters
fname (str) – Full path to the .json file to load the
Tidy3dBaseModelfrom.- Returns
A dictionary containing the model.
- Return type
dict
Example
>>> sim_dict = Simulation.dict_from_json(fname='folder/sim.json')
- classmethod dict_from_yaml(fname: str) dict#
Load dictionary of the model from a .yaml file.
- Parameters
fname (str) – Full path to the .yaml file to load the
Tidy3dBaseModelfrom.- Returns
A dictionary containing the model.
- Return type
dict
Example
>>> sim_dict = Simulation.dict_from_yaml(fname='folder/sim.yaml')
- eps_comp(row: Literal[0, 1, 2], col: Literal[0, 1, 2], frequency: float) complex#
Single component the complex-valued permittivity tensor as a function of frequency.
- Parameters
row (int) – Component’s row in the permittivity tensor (0, 1, or 2 for x, y, or z respectively).
col (int) – Component’s column in the permittivity tensor (0, 1, or 2 for x, y, or z respectively).
frequency (float) – Frequency to evaluate permittivity at (Hz).
- Returns
Element of the relative permittivity tensor evaluated at
frequency.- Return type
complex
- eps_comp_on_grid(row: Literal[0, 1, 2], col: Literal[0, 1, 2], frequency: float, coords: tidy3d.components.grid.grid.Coords) tidy3d.components.types.ArrayLike[dtype=complex, ndim=3]#
Spatial profile of a single component of the complex-valued permittivity tensor at
frequencyinterpolated at the supplied coordinates.- Parameters
row (int) – Component’s row in the permittivity tensor (0, 1, or 2 for x, y, or z respectively).
col (int) – Component’s column in the permittivity tensor (0, 1, or 2 for x, y, or z respectively).
frequency (float) – Frequency to evaluate permittivity at (Hz).
coords (
Coords) – The grid point coordinates over which interpolation is performed.
- Returns
Single component of the complex-valued permittivity tensor at
frequencyinterpolated at the supplied coordinates.- Return type
ArrayComplex3D
- static eps_complex_to_eps_sigma(eps_complex: complex, freq: float) Tuple[float, float]#
Convert complex permittivity at frequency
freqto permittivity and conductivity values.- Parameters
eps_complex (complex) – Complex-valued relative permittivity.
freq (float) – Frequency to evaluate permittivity at (Hz).
- Returns
Real part of relative permittivity & electric conductivity.
- Return type
Tuple[float, float]
- static eps_complex_to_nk(eps_c: complex) Tuple[float, float]#
Convert complex permittivity to n, k values.
- Parameters
eps_c (complex) – Complex-valued relative permittivity.
- Returns
Real and imaginary parts of refractive index (n & k).
- Return type
Tuple[float, float]
- eps_dataarray_freq(frequency: float) Tuple[tidy3d.components.data.data_array.SpatialDataArray, tidy3d.components.data.data_array.SpatialDataArray, tidy3d.components.data.data_array.SpatialDataArray]#
Permittivity array at
frequency.- Parameters
frequency (float) – Frequency to evaluate permittivity at (Hz).
- Returns
The permittivity evaluated at
frequency.- Return type
- eps_diagonal(frequency: float) Tuple[complex, complex, complex]#
Main diagonal of the complex-valued permittivity tensor at
frequency. Spatially, we take max{||eps||}, so that autoMesh generation works appropriately.
- eps_diagonal_on_grid(frequency: float, coords: tidy3d.components.grid.grid.Coords) Tuple[tidy3d.components.types.ArrayLike[dtype=complex, ndim=3], tidy3d.components.types.ArrayLike[dtype=complex, ndim=3], tidy3d.components.types.ArrayLike[dtype=complex, ndim=3]]#
Spatial profile of main diagonal of the complex-valued permittivity at
frequencyinterpolated at the supplied coordinates.- Parameters
frequency (float) – Frequency to evaluate permittivity at (Hz).
coords (
Coords) – The grid point coordinates over which interpolation is performed.
- Returns
The complex-valued permittivity tensor at
frequencyinterpolated at the supplied coordinate.- Return type
Tuple[ArrayComplex3D, ArrayComplex3D, ArrayComplex3D]
- eps_model(frequency: float) complex#
Complex-valued spatially averaged permittivity as a function of frequency.
- static eps_sigma_to_eps_complex(eps_real: float, sigma: float, freq: float) complex#
convert permittivity and conductivity to complex permittivity at freq
- Parameters
eps_real (float) – Real-valued relative permittivity.
sigma (float) – Conductivity.
freq (float) – Frequency to evaluate permittivity at (Hz). If not supplied, returns real part of permittivity (limit as frequency -> infinity.)
- Returns
Complex-valued relative permittivity.
- Return type
complex
- classmethod from_file(fname: str, group_path: Optional[str] = None, **parse_obj_kwargs) tidy3d.components.base.Tidy3dBaseModel#
Loads a
Tidy3dBaseModelfrom .yaml, .json, or .hdf5 file.- Parameters
fname (str) – Full path to the .yaml or .json file to load the
Tidy3dBaseModelfrom.group_path (str, optional) – Path to a group inside the file to use as the base level. Only for
.hdf5files. Starting / is optional.**parse_obj_kwargs – Keyword arguments passed to either pydantic’s
parse_objfunction when loading model.
- Returns
An instance of the component class calling load.
- Return type
Tidy3dBaseModel
Example
>>> simulation = Simulation.from_file(fname='folder/sim.json')
- classmethod from_hdf5(fname: str, group_path: str = '', custom_decoders: Optional[List[Callable]] = None, **parse_obj_kwargs) tidy3d.components.base.Tidy3dBaseModel#
Loads
Tidy3dBaseModelinstance to .hdf5 file.- Parameters
fname (str) – Full path to the .hdf5 file to load the
Tidy3dBaseModelfrom.group_path (str, optional) – Path to a group inside the file to selectively load a sub-element of the model only. Starting / is optional.
custom_decoders (List[Callable]) – List of functions accepting (fname: str, group_path: str, model_dict: dict, key: str, value: Any) that store the value in the model dict after a custom decoding.
**parse_obj_kwargs – Keyword arguments passed to pydantic’s
parse_objmethod.
Example
>>> simulation = Simulation.from_file(fname='folder/sim.hdf5')
- classmethod from_json(fname: str, **parse_obj_kwargs) tidy3d.components.base.Tidy3dBaseModel#
Load a
Tidy3dBaseModelfrom .json file.- Parameters
fname (str) – Full path to the .json file to load the
Tidy3dBaseModelfrom.- Returns
Tidy3dBaseModel– An instance of the component class calling load.**parse_obj_kwargs – Keyword arguments passed to pydantic’s
parse_objmethod.
Example
>>> simulation = Simulation.from_json(fname='folder/sim.json')
- classmethod from_orm(obj: Any) Model#
- classmethod from_yaml(fname: str, **parse_obj_kwargs) tidy3d.components.base.Tidy3dBaseModel#
Loads
Tidy3dBaseModelfrom .yaml file.- Parameters
fname (str) – Full path to the .yaml file to load the
Tidy3dBaseModelfrom.**parse_obj_kwargs – Keyword arguments passed to pydantic’s
parse_objmethod.
- Returns
An instance of the component class calling from_yaml.
- Return type
Tidy3dBaseModel
Example
>>> simulation = Simulation.from_yaml(fname='folder/sim.yaml')
- classmethod generate_docstring() str#
Generates a docstring for a Tidy3D mode and saves it to the __doc__ of the class.
- classmethod get_sub_model(group_path: str, model_dict: dict | list) dict#
Get the sub model for a given group path.
- get_submodels_by_hash() Dict[int, List[Union[str, Tuple[str, int]]]]#
Return a dictionary of this object’s sub-models indexed by their hash values.
- static get_tuple_group_name(index: int) str#
Get the group name of a tuple element.
- static get_tuple_index(key_name: str) int#
Get the index into the tuple based on its group name.
- help(methods: bool = False) None#
Prints message describing the fields and methods of a
Tidy3dBaseModel.- Parameters
methods (bool = False) – Whether to also print out information about object’s methods.
Example
>>> simulation.help(methods=True)
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode#
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- nk_model(frequency: float) Tuple[float, float]#
Real and imaginary parts of the refactive index as a function of frequency.
- Parameters
frequency (float) – Frequency to evaluate permittivity at (Hz).
- Returns
Real part (n) and imaginary part (k) of refractive index of medium.
- Return type
Tuple[float, float]
- static nk_to_eps_complex(n: float, k: float = 0.0) complex#
Convert n, k to complex permittivity.
- Parameters
n (float) – Real part of refractive index.
k (float = 0.0) – Imaginary part of refrative index.
- Returns
Complex-valued relative permittivty.
- Return type
complex
- static nk_to_eps_sigma(n: float, k: float, freq: float) Tuple[float, float]#
Convert
n,kat frequencyfreqto permittivity and conductivity values.- Parameters
n (float) – Real part of refractive index.
k (float = 0.0) – Imaginary part of refrative index.
frequency (float) – Frequency to evaluate permittivity at (Hz).
- Returns
Real part of relative permittivity & electric conductivity.
- Return type
Tuple[float, float]
- classmethod parse_file(path: Union[str, pathlib.Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) Model#
- classmethod parse_obj(obj: Any) Model#
- classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) Model#
- plot(freqs: float, ax: matplotlib.axes._axes.Axes = None) matplotlib.axes._axes.Axes#
Plot n, k of a
Mediumas a function of frequency.
- classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') DictStrAny#
- classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) unicode#
- sigma_model(freq: float) complex#
Complex-valued conductivity as a function of frequency.
- Parameters
freq (float) – Frequency to evaluate conductivity at (Hz).
- Returns
Complex conductivity at this frequency.
- Return type
complex
- to_file(fname: str) None#
Exports
Tidy3dBaseModelinstance to .yaml, .json, or .hdf5 file- Parameters
fname (str) – Full path to the .yaml or .json file to save the
Tidy3dBaseModelto.
Example
>>> simulation.to_file(fname='folder/sim.json')
- to_hdf5(fname: str, custom_encoders: Optional[List[Callable]] = None) None#
Exports
Tidy3dBaseModelinstance to .hdf5 file.- Parameters
fname (str) – Full path to the .hdf5 file to save the
Tidy3dBaseModelto.custom_encoders (List[Callable]) – List of functions accepting (fname: str, group_path: str, value: Any) that take the
valuesupplied and write it to the hdf5fnameatgroup_path.
Example
>>> simulation.to_hdf5(fname='folder/sim.hdf5')
- to_json(fname: str) None#
Exports
Tidy3dBaseModelinstance to .json file- Parameters
fname (str) – Full path to the .json file to save the
Tidy3dBaseModelto.
Example
>>> simulation.to_json(fname='folder/sim.json')
- to_yaml(fname: str) None#
Exports
Tidy3dBaseModelinstance to .yaml file.- Parameters
fname (str) – Full path to the .yaml file to save the
Tidy3dBaseModelto.
Example
>>> simulation.to_yaml(fname='folder/sim.yaml')
- classmethod tuple_to_dict(tuple_values: tuple) dict#
How we generate a dictionary mapping new keys to tuple values for hdf5.
- classmethod update_forward_refs(**localns: Any) None#
Try to update ForwardRefs on fields based on this Model, globalns and localns.
- updated_copy(**kwargs) tidy3d.components.base.Tidy3dBaseModel#
Make copy of a component instance with
**kwargsindicating updated field values.
- classmethod validate(value: Any) Model#
- property components: Dict[str, tidy3d.components.medium.Medium]#
Dictionary of diagonal medium components.
- property elements: Dict[str, Union[tidy3d.components.medium.Medium, tidy3d.components.medium.PoleResidue, tidy3d.components.medium.Sellmeier, tidy3d.components.medium.Lorentz, tidy3d.components.medium.Debye, tidy3d.components.medium.Drude]]#
The diagonal elements of the medium as a dictionary.
- property is_isotropic#
Whether the medium is isotropic.
- property n_cfl#
This property computes the index of refraction related to CFL condition, so that the FDTD with this medium is stable when the time step size that doesn’t take material factor into account is multiplied by
n_cfl.For this medium, it takes the minimal of
n_clfin all components.