add README.md

README.md

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 ---
 license: apache-2.0
+pretty_name: FSSDataBase - Frequency-Selective Surface Simulation Dataset
+size_categories:
+- 1K<n<10K
+tags:
+- electromagnetics
+- frequency-selective-surfaces
+- s-parameters
+- hfss
+- simulation-data
+- scientific-computing
+- tabular
 ---
+
+# FSSDataBase
+
+**A data-only collection of 5,607 simulated frequency-selective surface (FSS) unit cells, with structural metadata, per-metal-layer masks, and frequency-dependent reflection and transmission responses.**
+
+The dataset connects randomly generated single- and multilayer structures with HFSS electromagnetic responses. It includes both TE- and TM-labelled co-polarized S-parameter magnitudes and phases, supporting forward-response modelling, structural representation learning, polarization/angle comparisons, and response-based retrieval.
+
+This release contains numerical data rather than rendered figures: **no PNG/JPG plots, screenshots, or HFSS project files are included**. HFSS and PyAEDT are not required to read the exported files.
+
+> **Quality notice:** This is a preserved simulation archive, not a fully cleaned benchmark. Some records contain nonfinite values, incomplete angle coverage, or unusually large S-parameter magnitudes. Read [Data Quality and Limitations](#data-quality-and-limitations) before training models or interpreting device performance.
+
+## Dataset at a Glance
+
+The following statistics describe the database-registered samples in the data-only export dated **2026-09-14**, inspected on **2026-09-15**.
+
+| Property | Content |
+| --- | --- |
+| Registered structures | 5,607 |
+| Sample metadata files | 5,607 JSON files |
+| Raw response files / label files | 5,607 / 5,607 headerless CSV files |
+| Metal-layer masks | 8,920 CSV files; producer resolution 500 x 500 |
+| Observed metal-mask counts | 1 layer: 2,716 samples; 2 layers: 2,469; 3 layers: 422 |
+| Frequency grid in raw responses | 10-20 GHz, 101 points per recorded angle, 0.1 GHz spacing |
+| Recorded angles | 0 degrees in 5,607 samples; 30 degrees in 5,521 samples |
+| Raw channels | S11-TE, S11-TM, S21-TE, S21-TM; magnitude and phase for each |
+| Stored `unit.size` parameter | 5 mm for all samples; see the geometry convention below |
+| Total substrate thickness | 1 mm: 1,896 samples; 2 mm: 3,711 samples |
+| Used substrate material | F4BM348; other materials may appear in the metadata catalogue |
+| Stored wire-width parameter | Approximately 0.4000-0.6000 mm |
+| SQLite tables | `samples`: 5,607 rows; `responses`: 22,256; `responses_angle`: 22,256 |
+| Legacy cache | 221 NPZ files; 21,928 rows covering 5,522 distinct sample IDs |
+| Data size | 4,831,636,373 bytes, approximately 4.83 GB / 4.50 GiB, for `database/` and `datasets/` |
+| Recorded generation dates | 2026-08-16 to 2026-09-09, from stored timestamps |
+| Predefined train/validation/test splits | None |
+
+The 5,607 structures are the sample population. Frequency rows, polarization channels, masks, and cache rows are **not** additional independent structures. Layer counts above refer to saved mask files, not an independent CAD reconstruction.
+
+## Repository Layout
+
+```text
+FSSDataBase/
+  README.md
+  .gitattributes
+  database/
+    DataBase.db
+  datasets/
+    <sample_id>/
+      data.json
+      raw_result.csv
+      label_result.csv
+      mask_0.csv
+      mask_1.csv          # only when another metal mask is present
+      mask_2.csv          # only when another metal mask is present
+    cache/
+      cache_00000.npz
+      ...
+```
+
+Use `samples.id` as the authoritative index and join it to `datasets/<sample_id>/`. Keep IDs as **strings**: legacy IDs resemble decimal timestamps, while newer IDs contain underscores. Do not convert IDs to floating-point numbers.
+
+`samples.sample_path` is relative to the **repository root**, not to `database/` or the current working directory. For example, `datasets/1786866648.2374983` resolves below the downloaded repository root.
+
+## Data Generation and Scope
+
+The FSSDataBase generation pipeline creates randomized metal geometries and layer stacks, constructs a periodic HFSS unit-cell model, solves the configured frequency/angle conditions, and exports the responses and structural records. The generator provides three procedural families: centrally connected patterns (`group1`), loop-like patterns (`group2`), and filled patterns (`group3`). These family names describe generation methods, not performance classes.
+
+The available modelling code uses periodic boundaries and top/bottom Floquet ports. In the producer's channel convention, Floquet mode 1 is labelled TE and mode 2 TM. S11 denotes reflection at the top port; S21 denotes transmission from the top to the bottom port. The archived CSVs contain the corresponding **co-polarized** channels, not a complete multimode scattering matrix.
+
+The collection is limited to the actual recorded conditions; it is not a general sweep over arbitrary materials, frequencies, angles, or manufacturing tolerances. Generation and file retention introduce selection effects, so random generation does not imply uniform sampling of all possible FSS designs.
+
+The exported metadata does not record a per-sample solver version, random seed, full meshing history, or achieved convergence criterion. A later version of the generator is therefore not, by itself, evidence of exact reproducibility of every archived sample.
+
+## File and Field Definitions
+
+### Structural Metadata: `data.json`
+
+All published sample JSON files use the legacy field layout below.
+
+| Field | Meaning |
+| --- | --- |
+| `idx` | Original sample identifier; may be numeric in legacy JSON. Use the database/folder string ID for joins. |
+| `time` | Producer timestamp; no explicit timezone offset is stored. |
+| `author` | Producer-supplied attribution field. |
+| `material` | Material catalogue with relative permittivity, relative permeability, and dielectric loss tangent. Inclusion does not mean a material was used. |
+| `sub` | Actual substrate layers, such as `sub1` and `sub2`, with material name and thickness `h` in mm. |
+| `unit` | Two-element array **`[wire_width, size]`**, in mm. |
+| `range_freq` | Requested frequency configuration `[start_GHz, stop_GHz, point_count]`. |
+| `range_angle` | Legacy requested angle configuration. Use the actual CSV angle column to determine available results. |
+| `build` | Recorded geometry-building operations, including geometry expressions and coordinate-system operations. |
+
+**Geometry convention:** `samples.size` stores the generator's `Unit.size`, not the full lateral cell span. The available generator code constructs the substrate with `d = 2 * Unit.size`, corresponding to a 10 mm lateral span when `size = 5`. Use the producer's coordinate and scaling conventions when interpreting geometry; do not assume that the stored value 5 means a 5 mm period.
+
+**Angle convention:** all sample metadata contains `range_angle = [[0, 30, 2]]`, but the stored data contains **0 and 30 degrees only**, with 86 samples containing 0 degrees only. Do not interpret this release as measurements every 2 degrees or manufacture missing intermediate angles.
+
+There is no explicit per-metal-layer `group` field, canonical metal-height table, `geometry` field, or `schema_version` field in this legacy release. Layer heights and family assignments inferred from `build` require a separate, checked interpretation; they should not be presented as supplied ground-truth labels. Treat geometry-expression strings as data rather than executing them with unrestricted `eval`.
+
+### Continuous Responses: `raw_result.csv`
+
+This is the preferred source for quantitative S-parameter analysis. Files have **no header**, 10 columns, and either 101 rows (0 degrees only) or 202 rows (0 and 30 degrees). Numeric values are serialized to six decimal places.
+
+| Column, zero-based | Name | Unit |
+| --- | --- | --- |
+| 0 | `angle_deg` | degrees |
+| 1 | `frequency_GHz` | GHz |
+| 2 | `S11_TE_dB` | dB |
+| 3 | `S11_TM_dB` | dB |
+| 4 | `S21_TE_dB` | dB |
+| 5 | `S21_TM_dB` | dB |
+| 6 | `S11_TE_phase_deg` | degrees |
+| 7 | `S11_TM_phase_deg` | degrees |
+| 8 | `S21_TE_phase_deg` | degrees |
+| 9 | `S21_TM_phase_deg` | degrees |
+
+Magnitudes are `20 * log10(abs(S))`, not linear amplitudes. Reconstruct a stored complex coefficient with `10**(magnitude_db / 20) * exp(1j * deg2rad(phase_deg))`. Phases are wrapped angular values; compare phase differences circularly rather than subtracting values across the wrap boundary without correction.
+
+### Threshold Labels: `label_result.csv`
+
+The shape and column order match `raw_result.csv`. Columns 0-1 retain angle/frequency, columns 6-9 retain phase, and columns 2-5 contain:
+
+```text
++1  if the producer's unrounded magnitude is greater than -5 dB
+-1  otherwise
+```
+
+These are thresholded responses, not human annotations or universal passband/stopband judgements. For example, a high S11 label indicates stronger reflection, not necessarily desirable transmission. The threshold is applied before CSV rounding.
+
+**A label of -1 is not a validity flag.** The producer's comparison can also assign -1 to a nonfinite raw magnitude. Always inspect the corresponding raw response before using labels as training targets.
+
+### Metal Masks: `mask_<n>.csv`
+
+Each headerless CSV stores a two-dimensional numerical occupancy mask: **1 for metal, 0 for background**. The producer writes 500 x 500 masks. The suffix is a zero-based metal-mask index, not a substrate index or sample ID.
+
+Retain masks as separate layers and preserve their order. Do not merge layers into one mask when the task depends on stack arrangement. These numerical masks are included even though rendered image files have been removed; raster boundaries are a representation of geometry, not independent manufacturing metrology.
+
+### SQLite Database: `database/DataBase.db`
+
+| Table | Key and fields | Interpretation |
+| --- | --- | --- |
+| `samples` | `id`, `sample_path`, `size`, `height` | Master index and basic geometric parameters; `height` is total substrate thickness in mm. |
+| `responses` | `(id, direct, angle)`, `p000` ... `p299` | 300-point **TE threshold-label** representation, not raw dB amplitude. |
+| `responses_angle` | `(id, direct, angle)`, `p000` ... `p299` | Corresponding stored TE phase representation in degrees. |
+
+`direct = 0` means S11 and `direct = 1` means S21. It does **not** distinguish TE from TM: the producer's database path uses TE columns only. Use the raw/label CSVs for TM data or both polarizations.
+
+The producer's legacy normalization uses `np.linspace(1, 30, 300, dtype=np.float32)` and previous-node sampling. The raw solved band is only 10-20 GHz. A 300-column database row is therefore **not** 300 solved points over 10-20 GHz, and it is not evidence of a simulated 1-30 GHz band. Zero labels outside the represented band are sentinels; unavailable phases can be SQL `NULL`. Phase values passed through float16 storage before insertion, so SQLite's REAL type does not restore raw CSV precision.
+
+The 30-degree condition may be stored as `29.999999999999996` in SQLite. Use a tolerance, such as `ABS(angle - 30.0) < 1e-6`, instead of exact float equality.
+
+### Legacy NPZ Cache: `datasets/cache/`
+
+Files contain `ids`, `directs`, `angles`, `Sparameters`, and `phase`. Typically `Sparameters` has shape `(N, 300)` and dtype int8, and `phase` has shape `(N, 300)` and dtype float16. Their meanings follow the database's TE-only discretized representation, despite the generic name `Sparameters`. Frequency coordinates are not stored as a separate array.
+
+The preserved cache is **not a complete replacement for the database or sample files**: it contains 5,522 distinct IDs, leaving 85 registered sample IDs without cache coverage. Use `samples` as the master index, check joins explicitly, and load NPZ files with `allow_pickle=False`.
+
+## Download and Read
+
+Reading requires Python and NumPy; downloading with the example below additionally requires `huggingface_hub`. SQLite support is part of Python's standard library. No simulator is launched.
+
+### Download the Archive
+
+The Hub client supports repository downloads and optional file filtering; see the [official download guide](https://huggingface.co/docs/huggingface_hub/guides/download).
+
+```python
+from huggingface_hub import snapshot_download
+
+snapshot_download(
+    repo_id="kkking789/FSSDataBase",
+    repo_type="dataset",
+    local_dir="FSSDataBase",
+    max_workers=4,
+    # revision="<full commit hash>",  # Pin a real revision for reproducible work.
+    # ignore_patterns=["datasets/cache/*"],  # Optional: omit the legacy cache.
+)
+```
+
+This is a heterogeneous file archive, not one rectangular table. Do not concatenate every CSV into a single dataset: mask matrices, continuous responses, and threshold labels have different semantics.
+
+### Load One Registered Sample
+
+```python
+from pathlib import Path
+import json
+import sqlite3
+import numpy as np
+
+root = Path("FSSDataBase").resolve()
+database = root / "database" / "DataBase.db"
+connection = sqlite3.connect(database.as_uri() + "?mode=ro", uri=True)
+try:
+    sample_id, relative_path, size, height = connection.execute(
+        "SELECT id, sample_path, size, height FROM samples ORDER BY id LIMIT 1"
+    ).fetchone()
+finally:
+    connection.close()
+
+sample_dir = (root / relative_path).resolve()
+if not sample_dir.is_relative_to(root):
+    raise ValueError("Sample path is outside the dataset root")
+with (sample_dir / "data.json").open(encoding="utf-8") as handle:
+    metadata = json.load(handle)
+raw = np.loadtxt(sample_dir / "raw_result.csv", delimiter=",", ndmin=2)
+labels = np.loadtxt(sample_dir / "label_result.csv", delimiter=",", ndmin=2)
+mask_paths = sorted(
+    sample_dir.glob("mask_*.csv"),
+    key=lambda path: int(path.stem.rsplit("_", 1)[1]),
+)
+masks = [np.loadtxt(path, delimiter=",", dtype=np.uint8) for path in mask_paths]
+
+assert raw.shape[1] == 10 and labels.shape == raw.shape
+print("Sample:", sample_id, "substrate thickness (mm):", height)
+print("Angles (degrees):", np.unique(raw[:, 0]))
+print("Mask shapes:", [mask.shape for mask in masks])
+print("All raw entries finite:", bool(np.isfinite(raw).all()))
+
+# Example: inspect the complete recorded 0-degree TE transmission trace.
+trace = raw[np.isclose(raw[:, 0], 0.0, rtol=0, atol=1e-6)]
+trace = trace[np.argsort(trace[:, 1])]
+if trace.shape[0] != 101 or not np.isfinite(trace).all():
+    raise ValueError("This example requires a complete finite 0-degree trace")
+frequency_ghz = trace[:, 1]
+s21_te_db = trace[:, 4]
+s21_te_phase_deg = trace[:, 8]
+s21_te_complex = 10 ** (s21_te_db / 20) * np.exp(1j * np.deg2rad(s21_te_phase_deg))
+```
+
+This example selects a condition for illustration; it does not define an official clean subset or silently repair rejected values.
+
+## Data Quality and Limitations
+
+### Observed Quality of This Release
+
+A read-only scan of the 5,607 registered samples found:
+
+| Check | Result |
+| --- | --- |
+| SQLite `PRAGMA quick_check` | `ok` |
+| Presence of `data.json`, raw/label CSVs, and `mask_0.csv` | Present for all 5,607 samples |
+| Entire raw file finite | 5,498 samples |
+| At least one nonfinite raw entry | 109 samples; 75,136 nonfinite cells in total |
+| Both 0- and 30-degree rows recorded | 5,521 samples, including records with nonfinite values |
+| Only 0-degree rows recorded | 86 samples |
+| Complete finite 0-degree condition | 5,604 samples |
+| Complete finite 30-degree condition | 5,414 samples |
+| All-finite samples with any stored magnitude above +0.1 dB | 81 samples |
+| Label disagreements with the -5 dB rule on finite saved magnitudes | 0 cells |
+
+The all-finite population is a numerical eligibility subset, **not** a physically certified subset. Some stored magnitudes exceed +30 dB. Such values require investigation of solver settings, normalization, interpolation, or convergence before physical interpretation; this archive does not establish the cause. The available co-polarized channels alone are insufficient for a full multimode energy-balance assessment.
+
+The data-only export retained the database records and numerical files without imputation, clipping, relabelling, or removal of numerical outliers. Export verification compared the source and copied file hashes and database values; only the copied `sample_path` values were made relative. **Copy integrity is distinct from scientific validation.** The presence check above also does not independently prove that every intended CAD layer has a saved mask.
+
+Statistics from broader working directories can differ because those directories included samples absent from the database. Counts in this card refer only to this release's 5,607 registered structures.
+
+### Appropriate Use
+
+- Define and report numerical/physical screening criteria before model training or comparative evaluation. Do not replace NaNs or missing conditions with successful-looking responses.
+- Split at the **structure/sample-ID level**, keeping all angles, polarizations, layers, and derived records of a structure together. Otherwise, train/test leakage can occur. Also consider checking near-duplicate geometries.
+- Use the observed frequency grids and actual angle coverage. Do not infer intermediate-angle behaviour from two angle values, or extrapolate the solved band from the database's padded representation.
+- Use circular phase comparisons. Phase near deep transmission/reflection nulls can be sensitive and should not be treated as a robust device objective without amplitude constraints.
+- This release does not include measured prototypes, a universal convergence certificate, fabrication-tolerance sweeps, finite-array validation, cross-polarized channels, or official baseline model scores. It is not evidence of experimentally verified device performance or superiority over other datasets.
+
+## License, Citation, and Contact
+
+The repository declares **Apache-2.0** in its dataset metadata. See the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0) for the license text. Proprietary solver software and third-party material/product names are not distributed with this dataset.
+
+For reproducible use, cite the dataset and record the exact downloaded repository commit. The following is a dataset citation, not a claim of an associated peer-reviewed publication:
+
+```bibtex
+@misc{fssdatabase2026,
+  author = {{kkking789}},
+  title = {{FSSDataBase}: Frequency-Selective Surface Simulation Dataset},
+  year = {2026},
+  url = {https://huggingface.co/datasets/kkking789/FSSDataBase},
+  note = {Data-only export dated 2026-09-14}
+}
+```
+
+For questions or data-quality reports, use the repository's [Community discussions](https://huggingface.co/datasets/kkking789/FSSDataBase/discussions). Include the sample ID, file, angle, channel, and dataset revision so that the record can be checked.