>[!warning] >This content has not been peer reviewed. # SPARC evaluation — implementation (rst + notebooks) This note documents the **code** in this folder: the **rst** package and the **notebooks** that run the SPARC evaluation. For **method and data source** see **[[../python calculations/SPARC Evaluation - Code]]**. For **results summary** see **[[../python calculations results/SPARC Evaluation Results]]**. --- ## Purpose - **rst:** Implements the RST gravity-sector pipeline: $\mu(\eta,n)$, solvers for $q'$ from $g_N$, cosmology $a_0(z)$, $n(z)$, and rotation-curve prediction $v(r) = \sqrt{r \cdot q'}$. - **notebooks:** Scripts that load SPARC data, fit $\Upsilon_{\text{disk}}$, and produce plots and CSV outputs (e.g. RAR curve, rotation curves, high-z shift). --- ## Engine (same as applications) **`rst/interpolation.py`** does **not** reimplement the core maths. It imports from the shared **`rst_engine`** at the workspace root: - **$\mu(\eta,n)$:** `mu_rst(eta, n)` from `rst_engine`. - **Solve for $q'$:** For generic $n$, `solve_acceleration(g_N, a0, n)` calls `solve_omega(g_N, a0, n)` from `rst_engine` (same equation: $I = \Omega \cdot \mu(\Omega/N)$ with $I = g_N$, $N = a_0$, $\Omega = q'$). Closed-form solvers for $n=1$ and $n=2$ remain in rst for speed. **Path:** From `rst/`, the workspace root is three levels up; `sys.path` is set in `interpolation.py` so that `from rst_engine import mu_rst, solve_omega` works. See **[[../../expanded theory applied/How we do applications]]** for how all scripts plug into the engine. --- ## What lives where | Component | Location | Role | |:---|:---|:---| | $\mu$, generic solver | `rst_engine` (workspace root) | Single implementation shared with applications | | Closed-form $n=1$, $n=2$ | `rst/interpolation.py` | Speed; same maths as engine | | $a_0(z)$, $n(z)$, $H(z)$ | `rst/cosmology.py` | RST cosmology for evaluation | | $g_N \to v(r)$ | `rst/rotation_curve.py` | Uses `solve_acceleration` and cosmology | | Scripts (RAR, rotation curves, SPARC fit) | `notebooks/*.py` | Load data, call rst, write `notebooks/output/` | --- ## Outputs - **`notebooks/output/`** — PNG plots (e.g. RAR, rotation curves, high-z), CSV result tables (e.g. `sparc_results.csv`, `sparc_float_n_results.csv`). - **Results note:** **[[../python calculations results/SPARC Evaluation Results]]** summarises fit statistics (median $\Upsilon_{\text{disk}}$, $\chi^2$ rates). --- ## Links - **Method and data:** [[../python calculations/SPARC Evaluation - Code]] - **Verification and interpretation:** [[../python calculations/SPARC Evaluation Verification]] - **Results summary:** [[../python calculations results/SPARC Evaluation Results]] - **Engine:** `rst_engine/` at workspace root ([[../../rst_engine/README]]) - **Applications guide:** [[../../expanded theory applied/How we do applications]]