API Reference

Simulation

Simulation([size, center, resolution, …])	Main class for building a simulation model.
Simulation.materials	List containing all materials included in the simulation.
Simulation.structures	List containing all Structure objects.
Simulation.sources	List containing all Source objects.
Simulation.monitors	List containing all Monitor objects.
Simulation.epsilon([monitor, center, size, …])	Compute the complex relative permittivity inside a volume.
Simulation.set_time([run_time, courant])	Change the value of the run time of the simulation and the time step determined by the courant stability factor.

Saving and loading

Simulation.load_results(dfile[, ind_src_norm])	Load all monitor data recorded from a Tidy3D run.
Simulation.export()	Return a dictionary with all simulation parameters and objects.
Simulation.export_json(fjson)	Export the simulation specification to a JSON file.
Simulation.import_json(fjson)	Import a simulation specification from a JSON file.

Material

Medium([name])	Base class for a custom defined material.
Medium.epsilon([freqs, component])	Evaluate the (complex) relative permittivity of the medium.
PEC	Perfect electric conductor.

material_library

A library of pre-defined materials.

Dispersive models

DispersionModel([eps_inf, poles, name])	Base class for a model of material dispersion.
Sellmeier(coeffs[, name])	Sellmeier dispersion refractive index model.
Sellmeier.from_dn(wl, n, dn_dwl[, name])	Create a 1-pole Sellmeier model from dispersion data.
Lorentz(eps_inf, coeffs[, name])	Lorentz dispersion permittivity model.
Debye(eps_inf, coeffs[, name])	Debye dispersion permittivity model.
Drude(eps_inf, coeffs[, name])	Drude dispersion permittivity model.

Fitting optical data

fit.DispersionFit(wavelengths, n_data[, k_data])
fit.DispersionFit.fit([num_poles, …])	Fits data a number of times and returns best results.
fit.DispersionFit.plot([wavelengths, ax, …])	Make plot of model vs data, at a set of wavelengths (if supplied).
fit.load_nk_file(fname, **load_txt_kwargs)	Loads nk data from file, performs validation on input.
fit.load_poles([fname, name])	Loads txt file with (num_poles, 2) complex array data into Medium.

Structure

Structure(material[, name])	Base class for regions defined by geometric shapes in a simulation domain.
Box(center, size, material[, name])	Box structure, i.e. a 3D rectangular axis-aligned prism.
Sphere(center, radius, material[, name])	Sphere structure.
Cylinder(center, axis, radius, height, material)	Cylinder structure.
PolySlab(material, vertices[, z_cent, …])	A structure defined as polygon in x and y, and extruded in z.
GdsSlab(material, gds_cell[, gds_layer, …])	A structure defined through a GDS cell imported through gdspy.

Source

Source(source_time, span[, amplitude, name])	Base class for defining spatial profiles of excitation conditions.
VolumeSource(source_time, center, size, …)	A source specified as an electric or a magnetic current of a fixed component (one of Ex, Ey, Ez, Hx, Hy, Hz) with a constant amplitude inside a 3D volume region.
PointDipole(source_time, center, component)	A source specified as an electric or a magnetic current of a fixed component (one of Ex, Ey, Ez, Hx, Hy, Hz) at a given point.
ModeSource(source_time, center, size[, …])	Eigenmode source spanning a 2D cross section of a given size inside a Simulation.
PlaneWave(source_time, injection_axis, …)	Plane-wave source with a specified direction and polarization, spanning the whole 2D simulation cross-section at a given position normal to a given injection axis.
GaussianBeam(source_time, center, normal[, …])	Plane-wave source with a specified direction and polarization, spanning the whole simulation cross-section at a given position and axis normal.
Simulation.compute_modes(mode_object, Nmodes)	Compute the eigenmodes of the 2D cross-section of a ModeSource or ModeMonitor object, assuming translational invariance in the third dimension.
Simulation.set_mode(source, mode_ind[, …])	Set the index of the mode to be used by the mode source.
Simulation.spectrum(source, freqs)	Returns the spectrum of a Source.

Time dependence

SourceTime()	Base class for the time dependence of a source.
GaussianPulse(frequency, fwidth[, offset, phase])	Source with a Gaussian-envelope time dependence.

Monitor

Monitor(center, size[, name])	Base class for defining field monitors.
TimeMonitor(center, size[, t_start, t_stop, …])	Monitor recording the time-domain fields within a 3D region.
FreqMonitor(center, size, freqs[, store, …])	Monitor recording a discrete Fourier transform of the fields within a 3D region, for a given list of frequencies.
ModeMonitor(center, size, freqs[, …])	FreqMonitor subclass defining a 2D plane in which the recorded frequency-domain fields can be decomposed into propagating eigenmodes.
Simulation.compute_modes(mode_object, Nmodes)	Compute the eigenmodes of the 2D cross-section of a ModeSource or ModeMonitor object, assuming translational invariance in the third dimension.
Simulation.set_monitor_modes(monitor[, …])	Set the parameters for the modes to be used in the modal decomposition in the monitor.

Simulation Outputs

Simulation.data(monitor)	Return a dictionary with all the stored data in a Monitor.
Simulation.flux(monitor[, normal])	Compute the area-integrated Poynting flux in a given direction.
Simulation.poynting(monitor)	Compute the Poynting vector at every point recorded by a Monitor.
Simulation.decompose(mode_monitor)	Compute the decomposition of the fields recorded in a ModeMonitor into the eigenmodes in the monitor plane.

Near Field to Far Field

Near2Far(monitor_data[, freq_index])	Near field to far field transformation tool.
Near2Far.get_fields_cartesian(x, y, z)	Get fields at a point relative to monitor center in cartesian coordintes.
Near2Far.get_fields_spherical(r, theta, phi)	Get fields at a point relative to monitor center in spherical coordintes.
Near2Far.get_power_cartesian(x, y, z)	Get power scattered to a point relative to monitor center in cartesian coordinates.
Near2Far.get_power_spherical(r, theta, phi)	Get power scattered to a point relative to monitor center in spherical coordinates.
Near2Far.get_radar_cross_section(theta, phi)	Get radar cross section at a point relative to monitor center in units of incident power.

Plotting tools

Simulation.viz_eps_2D([normal, position, …])	Plot the real part of the relative permittivity distribution of a 2D cross-section of the simulation.
Simulation.viz_source(source[, axs])	Plot both the time and frequency dependence of a source.
Simulation.viz_source_time(source[, ax])	Plot the time dependence of a source.
Simulation.viz_source_spectrum(source[, ax, …])	Plot the frequency dependence of a source.
Simulation.viz_field_2D(monitor[, …])	Plot a 2D cross-section of a field stored in a Monitor.
Simulation.viz_modes(mode_obj[, freq_ind, …])	Plot the field distribution of the 2D eigenmodes of a ModeSource or a ModeMonitor object.

Web API

web.new_project(sim_dict[, task_name, …])	Create new project.
web.get_project(task_id)	Get all project details from a given task_id.
web.delete_project(task_id)	Delete a project from a given task_id.
web.monitor_project(task_id[, silent])	Monitor the status of a given project every second.
web.list_projects([Nprojects])	Print a summary of all projects of the current user, in chronological order of submission.
web.download_json(task_id[, target_folder])	Download the project json file
web.download_results(task_id[, target_folder])	Download the results of a solver run, including the json file defining the simulation, a single file containing all the monitor data, and a log file.
web.run(simulation[, task_name, …])	Runs a simulation and loads the results.
web.load(task_id[, simulation, target_folder])	Loads results from web to simulation.

Job Management

web.Job(simulation[, base_dir, task_id, …])	Container for single simulation and associated task.
web.Job.load_from_task_id(task_id[, …])	Loads a Job from it’s task id.
web.Job.get_info()	Returns dictionary containing Job metadata.
web.Job.delete()	Deletes the Job from our server.
web.Job.monitor()	Prints status of Job in real time.
web.Job.load_results([target_folder])	Downloads data to target_folder, loads data into either saved simulation or newly created simulation.
web.Job.download_json([target_folder])	Download the json file associated with this job to target_folder.
web.Job.download_results([target_folder])	Download the job results to target_folder.

Batch Management

web.Batch(simulations[, task_ids, …])	Container for processing set of simulations.
web.Batch.save(filename)	Save Batch info to file of newline-separated task_ids.
web.Batch.load_from_file(filename[, …])	Load a Batch from file containing newline separated list of task_ids.
web.Batch.load_from_task_ids(task_ids[, …])	Load a Batch from file containing newline separated list of task_ids.
web.Batch.get_info()	Return list of dictionaries storing Batch metadata.
web.Batch.delete()	Delete all jobs in Batch.
web.Batch.monitor()	Monitor progress of Batch in terms of number of jobs completed.
web.Batch.load_results()	downloads results and either loads into list of simulations or returns list of new simulations
web.Batch.download_json()	Downalod json file of each Job to it’s corresponding target_folder.
web.Batch.download_results()	Downalod data of each Job to it’s corresponding target_folder.

Miscellaneous

dft_spectrum(time_series, dt, freqs)	Computes the frequency spectrum associated to a time series directly using the discrete fourier transform.
logging_default()	Set the default logging configuration.
logging_file(fname[, filemode, level])	Set a file to write log to, independently from the stdout and stderr output chosen using logging_level().
logging_level(level)	Set the lowest severity level to print to the console, as per the python logger.