Input/Output API

Data Export

CSV Exporter

class prismo.io.exporters.csv_exporter.CSVExporter(output_dir=None)[source]

CSV data exporter.

Exports field data, spectra, and S-parameters to CSV format. Suitable for small to medium datasets that can be easily opened in spreadsheet applications.

export_fields(filename, fields, coordinates, metadata=None)[source]

Export field data to CSV.

Creates a CSV file with columns: x, y, z, Ex, Ey, Ez, Hx, Hy, Hz, |E|, |H|

Parameters:

filename (str) – Output filename (without .csv extension).
fields (dict) – Dictionary with keys ‘Ex’, ‘Ey’, ‘Ez’, ‘Hx’, ‘Hy’, ‘Hz’.
coordinates (dict) – Dictionary with keys ‘x’, ‘y’, ‘z’ (coordinate arrays).
metadata (dict, optional) – Additional metadata to write as header comments.

Returns:

Path to exported CSV file.

Return type:

Path

export_spectrum(filename, frequencies, spectrum, metadata=None)[source]

Export spectrum data to CSV.

Creates a CSV file with columns: frequency, spectrum, (optional phase).

Parameters:

filename (str) – Output filename.
frequencies (array) – Frequency values (Hz).
spectrum (array) – Spectrum data (can be real or complex).
metadata (dict, optional) – Additional metadata.

Returns:

Path to exported CSV file.

Return type:

Path

export_sparameters(filename, frequencies, sparameters, metadata=None)[source]

Export S-parameters to CSV.

Creates a CSV file with columns for each S-parameter (magnitude and phase).

Parameters:

filename (str) – Output filename.
frequencies (array) – Frequency values (Hz).
sparameters (dict) – Dictionary of S-parameters (e.g., {‘S11’: array, ‘S21’: array}).
metadata (dict, optional) – Additional metadata.

Returns:

Path to exported CSV file.

Return type:

Path

export_field_slice(filename, field_slice, extent, metadata=None)[source]

Export a 2D field slice to CSV.

Parameters:

filename (str) – Output filename.
field_slice (ndarray) – 2D array of field values.
extent (tuple) – Physical extent (xmin, xmax, ymin, ymax).
metadata (dict, optional) – Additional metadata.

Returns:

Path to exported CSV file.

Return type:

Path

Parquet Exporter

class prismo.io.exporters.parquet_exporter.ParquetExporter(output_dir=None, compression='snappy')[source]

Parquet data exporter using Polars.

Exports field data, spectra, and S-parameters to Apache Parquet format. Parquet provides efficient columnar storage with compression, making it ideal for large datasets.

Parameters:

output_dir (Path, optional) – Output directory for exported files.
compression (str, optional) – Compression algorithm (‘snappy’, ‘gzip’, ‘lz4’, ‘zstd’). Default=’snappy’.

__init__(output_dir=None, compression='snappy')[source]

Initialize exporter.

Parameters:: output_dir (Path, optional) – Output directory for exported files. If None, uses current directory.

export_fields(filename, fields, coordinates, metadata=None)[source]

Export field data to Parquet format.

Creates a Parquet file with efficient columnar storage.

Parameters:

filename (str) – Output filename (without .parquet extension).
fields (dict) – Dictionary with field arrays.
coordinates (dict) – Dictionary with coordinate arrays.
metadata (dict, optional) – Additional metadata (stored in Parquet metadata).

Returns:

Path to exported Parquet file.

Return type:

Path

export_spectrum(filename, frequencies, spectrum, metadata=None)[source]

Export spectrum data to Parquet.

Parameters:

filename (str) – Output filename.
frequencies (array) – Frequency values.
spectrum (array) – Spectrum data (real or complex).
metadata (dict, optional) – Additional metadata.

Returns:

Path to exported Parquet file.

Return type:

Path

export_sparameters(filename, frequencies, sparameters, metadata=None)[source]

Export S-parameters to Parquet.

Parameters:

filename (str) – Output filename.
frequencies (array) – Frequency values.
sparameters (dict) – Dictionary of S-parameters.
metadata (dict, optional) – Additional metadata.

Returns:

Path to exported Parquet file.

Return type:

Path

export_timeseries(filename, time, data, metadata=None)[source]

Export time-series data to Parquet.

Parameters:

filename (str) – Output filename.
time (array) – Time values.
data (dict) – Dictionary of time-series data.
metadata (dict, optional) – Additional metadata.

Returns:

Path to exported Parquet file.

Return type:

Path

static read_parquet(filepath)[source]

Read a Parquet file.

Parameters:: filepath (Path) – Path to Parquet file.
Returns:: Polars DataFrame with the data.
Return type:: pl.DataFrame

static read_with_filter(filepath, filter_expr=None, columns=None)[source]

Read Parquet file with lazy evaluation and filtering.

Parameters:

filepath (Path) – Path to Parquet file.
filter_expr (polars expression, optional) – Filter expression to apply.
columns (list, optional) – Specific columns to read.

Returns:

Filtered DataFrame.

Return type:

pl.DataFrame

Lumerical Import

FSP Parser

class prismo.io.lumerical.fsp_parser.FSPParser(fsp_file)[source]

Parser for Lumerical .fsp files.

Lumerical FDTD Solutions saves projects as .fsp files, which are compressed archives containing XML and binary data. This parser extracts the relevant information for conversion to Prismo.

Parameters:: fsp_file (Path) – Path to .fsp file.

__init__(fsp_file)[source]

parse()[source]

Parse the .fsp file.

Returns:: Parsed project data.
Return type:: FSPProject

to_prismo_simulation()[source]

Convert FSP project to Prismo Simulation.

Returns:: Prismo simulation object configured from FSP file.
Return type:: Simulation

export_summary(output_file=None)[source]

Export summary of FSP contents to JSON.

Parameters:: output_file (Path, optional) – Output file path.
Returns:: Path to summary file.
Return type:: Path

class prismo.io.lumerical.fsp_parser.FSPProject(filename, geometries=<factory>, sources=<factory>, monitors=<factory>, simulation_region=<factory>, materials=<factory>, metadata=<factory>)[source]

Complete FSP project data.

filename

Original .fsp filename.

Type:: Path

geometries

Geometry objects.

Type:: List[FSPGeometry]

sources

Source definitions.

Type:: List[FSPSource]

monitors

Monitor definitions.

Type:: List[FSPMonitor]

simulation_region

Simulation domain parameters.

Type:: dict

materials

Custom material definitions.

Type:: Dict[str, Any]

metadata

Additional metadata.

Type:: dict

filename: Path

geometries: list[FSPGeometry]

sources: list[FSPSource]

monitors: list[FSPMonitor]

simulation_region: dict[str, Any]

materials: dict[str, Any]

metadata: dict[str, Any]

__init__(filename, geometries=<factory>, sources=<factory>, monitors=<factory>, simulation_region=<factory>, materials=<factory>, metadata=<factory>)

Material Database

class prismo.io.lumerical.material_db.LumericalMaterialDB(db_path)[source]

Parser for Lumerical material database files.

Lumerical stores material data in various formats including: - Text files with (n, k) data - XML files with dispersion model parameters - MDF (Material Data Format) files

Parameters:: db_path (Path) – Path to Lumerical material database directory or file.

__init__(db_path)[source]

load_material(material_name)[source]

Load a material from the database.

Parameters:: material_name (str) – Name of material to load.
Returns:: Material object if found.
Return type:: DispersiveMaterial or None

prismo.io.lumerical.material_db.import_lumerical_material(file_path, material_name=None)[source]

Import a single material from a Lumerical file.

Parameters:

file_path (Path) – Path to material data file.
material_name (str, optional) – Material name to use. If None, uses filename.

Returns:

Imported material.

Return type:

DispersiveMaterial or None

Examples

>>> mat = import_lumerical_material('path/to/Silicon.txt')
>>> prismo.add_material('Silicon_imported', mat)