Autocompletion of configure.py

doc/wiki/ELBDM-related/ELBDM-Hybrid-Scheme.md

@@ -65,7 +65,7 @@ mpirun -map-by ppr:2:socket:pe=8 --report-bindings ./gamer 1>>log 2>&1
    ![Data_000069_PS](https://github.com/gamer-project/gamer/assets/6187378/260649c1-69e7-4a44-8dc9-06ccf6fe798d)
    </details>
 
-The wave scheme (`GRAMFE_MATMUL`) is used for the dark grey and black grids.
+The wave scheme (`MATMUL`) is used for the dark grey and black grids.
 The relative mass conservation error at $z=0$ with spectral interpolation on is $6.72e-04$.
 
 
@@ -90,15 +90,15 @@ The hybrid scheme is particularly suited for cosmological simulations where a si
 
 The configure.py script is the starting point for setting up a simulation. For the hybrid scheme, ensure the following flags are set:
 
-- `--elbdm_scheme = ELBDM_HYBRID`: Determines the scheme type for ELBDM simulations. There are two options:
-    - `ELBDM_WAVE`: Wave-only scheme.
-    - `ELBDM_HYBRID`: Fluid-wave hybrid scheme.
+- `--elbdm_scheme = HYBRID`: Determines the scheme type for ELBDM simulations. There are two options:
+    - `WAVE`: Wave-only scheme.
+    - `HYBRID`: Fluid-wave hybrid scheme.
 - `--hybrid_scheme`: This option is specific to the hybrid scheme, defining the fluid dynamics treatment:
-    - `HYBRID_UPWIND`: First-order upwind scheme. It is diffusive but stable.
-    - `HYBRID_FROMM`: Second-order Fromm scheme. It has no limiter but can be unstable.
-    - `HYBRID_MUSCL`: Second-order MUSCL scheme. It includes a limiter, balancing accuracy and stability.
+    - `UPWIND`: First-order upwind scheme. It is diffusive but stable.
+    - `FROMM`: Second-order Fromm scheme. It has no limiter but can be unstable.
+    - `MUSCL`: Second-order MUSCL scheme. It includes a limiter, balancing accuracy and stability.
 
-    For zoom-in and fluid-only simulations, use `--hybrid_scheme HYBRID_MUSCL` since unrefined regions may become unstable otherwise. For fully refined simulations use `--hybrid_scheme HYBRID_FROMM` since it is slightly faster and more accurate than `HYBRID_MUSCL`. In case you encounter instabilities, test the more diffusive, first-order scheme `--hybrid_scheme HYBRID_UPWIND`.
+    For zoom-in and fluid-only simulations, use `--hybrid_scheme MUSCL` since unrefined regions may become unstable otherwise. For fully refined simulations use `--hybrid_scheme FROMM` since it is slightly faster and more accurate than `MUSCL`. In case you encounter instabilities, test the more diffusive, first-order scheme `--hybrid_scheme UPWIND`.
 
 ## Configuring the `Input__Parameter` file
 
@@ -225,7 +225,7 @@ $$S(x, t) = \arctan\left(\frac{\Im(\psi(x, t))}{\Re(\psi(x, t)}\right).$$
 We must therefore determine the correct phase by requiring continuity at the matching boundary. On a discrete grid, this translates into the requirement that the phase field $S(x, t)$ must not change by more than $2 \pi$ between neighbouring grid points at the matching boundary. In other words, we must resolve the de Broglie wavelength at the matching boundary in order for the reverse boundary matching problem to admit a unique solution. This immediately shows that a useful hybrid scheme based on this approach necessarily requires an AMR algorithm with at least two refinement levels for the phase equation: An outer refinement level where the grids need not resolve the de Broglie wavelength and a second refinement level where the de Broglie wavelength is resolved and the reverse boundary matching problem has a unique solution.
 
 ## Implementation
-We evolve the continuity equation using a first-order upwind scheme (`HYBRID_UPWIND`), the second-order Fromm scheme without limiter (`HYBRID_FROMM`) or a MUSCL scheme with a linear subgrid model together with the van Albada limiter (`HYBRID_MUSCL`). As for the HJ scheme, we use a finite difference scheme. The convection term is discretised via the Sethian-Osher flux. The velocities at the cell faces are then computed as regular finite differences. We treat the cell averages $\bar{\rho}$ in the finite volume scheme as point values $\rho$ in the discretisation of the quantum pressure term. Technically, we use the MUSCL scheme as a conservative finite-difference method and not as a finite volume scheme. This has the consequence that the maximum order of accuracy we can reach with the linear subgrid MUSCL scheme is second order. The quantum pressure term is discretised as
+We evolve the continuity equation using a first-order upwind scheme (`UPWIND`), the second-order Fromm scheme without limiter (`FROMM`) or a MUSCL scheme with a linear subgrid model together with the van Albada limiter (`MUSCL`). As for the HJ scheme, we use a finite difference scheme. The convection term is discretised via the Sethian-Osher flux. The velocities at the cell faces are then computed as regular finite differences. We treat the cell averages $\bar{\rho}$ in the finite volume scheme as point values $\rho$ in the discretisation of the quantum pressure term. Technically, we use the MUSCL scheme as a conservative finite-difference method and not as a finite volume scheme. This has the consequence that the maximum order of accuracy we can reach with the linear subgrid MUSCL scheme is second order. The quantum pressure term is discretised as
 $$\frac{\Delta \sqrt{\rho}}{\sqrt{\rho}} = \left(\frac{1}{2} \Delta \log(\rho) + \frac{1}{4} \left(\nabla \log(\rho)\right)^2\right)$$
 with second-order central finite differences for both the gradient operator and the Laplacian.
 The resulting semi-discrete scheme is discretised with a third-order RK method. A second-order discretisation also works well, but requires a more stringent CFL condition.

doc/wiki/ELBDM-related/ELBDM-Spectral-Solver.md

@@ -3,9 +3,9 @@
 ## Setup and Configuration
 
 ### Compilation Options
-- **Wave Scheme Selection**: To enable the spectral solver, set `WAVE_SCHEME` to `WAVE_GRAMFE` in the Makefile or configure with `--wave_scheme=WAVE_GRAMFE` for the ELBDM model.
-- **Spectral Scheme Options**: Choose between `GRAMFE_MATMUL` (faster for `PATCH_SIZE=8`) and `GRAMFE_FFT` (faster for larger patch sizes) by setting `GRAMFE_SCHEME` in the Makefile or configure with `--gramfe_scheme` accordingly.
-- **Additional Libraries**: The CPU version requires FFTW 3 for single precision and FFTW 2/3 for double precision. The GPU version of `GRAMFE_FFT` needs the cuFFTDx library. Set `FFTW2_PATH`, `FFTW3_PATH`, and `CUFFTDX_PATH` in the Makefile or configuration files `*.config`.
+- **Wave Scheme Selection**: To enable the spectral solver, set `WAVE_SCHEME` to `WAVE_GRAMFE` in the Makefile or configure with `--wave_scheme=GRAMFE` for the ELBDM model.
+- **Spectral Scheme Options**: Choose between `MATMUL` (faster for `PATCH_SIZE=8`) and `FFT` (faster for larger patch sizes) by setting `SCHEME` in the Makefile or configure with `--gramfe_scheme` accordingly.
+- **Additional Libraries**: The CPU version requires FFTW 3 for single precision and FFTW 2/3 for double precision. The GPU version of `FFT` needs the cuFFTDx library. Set `FFTW2_PATH`, `FFTW3_PATH`, and `CUFFTDX_PATH` in the Makefile or configuration files `*.config`.
 
 ### Precision and Performance Options
 - **Floating Point Precision**: Controlled by `GRAMFE_ENABLE_SINGLE_PRECISION`. The default is double precision. Single precision is not recommended due to stability issues.
@@ -68,29 +68,29 @@
 4. **Avoidance of Gibbs Phenomenon**: Smooth extensions largely prevent the Gibbs phenomenon.
 5. **Discarding Extended Domain**: After computation, the extended domain is discarded.
 
-## Differences between GRAMFE_MATMUL and GRAMFE_FFT Schemes
+## Differences between MATMUL and FFT Schemes
 
 ### Overview
-Understanding the differences between the `GRAMFE_MATMUL` and `GRAMFE_FFT` schemes in GAMER is crucial for users to choose the appropriate method for their specific simulation needs. Both schemes are based on the Gram-Fourier extension algorithm but differ in their computational approach and performance characteristics.
+Understanding the differences between the `MATMUL` and `FFT` schemes in GAMER is crucial for users to choose the appropriate method for their specific simulation needs. Both schemes are based on the Gram-Fourier extension algorithm but differ in their computational approach and performance characteristics.
 
-### GRAMFE_MATMUL Scheme
+### MATMUL Scheme
 
 #### Description
-- **Matrix Multiplication Approach**: In the `GRAMFE_MATMUL` scheme, the entire operation sequence - GramFE extension, FFT, time evolution, IFFT, and discarding of extension data - is precomputed and represented as a single matrix (which is possible because of linearity).
+- **Matrix Multiplication Approach**: In the `MATMUL` scheme, the entire operation sequence - GramFE extension, FFT, time evolution, IFFT, and discarding of extension data - is precomputed and represented as a single matrix (which is possible because of linearity).
 - **Application to Input Vectors**: This precomputed matrix can be directly applied to input vectors, eliminating the need to compute each operation at runtime.
 
 #### Advantages
-- **Reduced Runtime Computation**: By precomputing the entire operation sequence, the `GRAMFE_MATMUL` scheme minimizes runtime computational overhead.
+- **Reduced Runtime Computation**: By precomputing the entire operation sequence, the `MATMUL` scheme minimizes runtime computational overhead.
 - **Efficiency for Small Patch Sizes**: This scheme is particularly efficient for smaller data sizes where the cost of matrix multiplication is lower.
 
 #### Disadvantages
 - **Memory Usage**: The precomputed matrix, especially for large patch sizes, can consume significant memory resources.
 - **Precomputation Time**: There is an upfront cost in time to compute and store the matrix, which might be substantial depending on the accuracy used.
 
-### GRAMFE_FFT Scheme
+### FFT Scheme
 
 #### Description
-- **Runtime Computation**: The `GRAMFE_FFT` scheme performs the GramFE extension, FFT, time evolution, IFFT, and discarding of extension data operations at runtime.
+- **Runtime Computation**: The `FFT` scheme performs the GramFE extension, FFT, time evolution, IFFT, and discarding of extension data operations at runtime.
 
 #### Advantages
 - **Scalability for Large Patch Sizes**: This scheme is more scalable for larger patch sizes, as it does not require storing large precomputed matrices.
@@ -100,10 +100,10 @@ Understanding the differences between the `GRAMFE_MATMUL` and `GRAMFE_FFT` schem
 - **Dependence on FFT Performance**: The efficiency of the scheme is closely tied to the performance of the FFT algorithm used.
 
 ### Conclusion
-- **Choice of Scheme**: By default `GRAMFE_MATMUL` should be used. `GRAMFE_FFT` should be considered for larger patch sizes and debugging.
+- **Choice of Scheme**: By default `MATMUL` should be used. `FFT` should be considered for larger patch sizes and debugging.
 
 ## Performance Metrics
-- The performance ratio `Perf_FD / Perf_Spectral` indicates the efficiency compared to the finite-difference scheme. This varies based on patch size (e.g., 4.3 for `PATCH_SIZE=8` and 2.6 for `PATCH_SIZE=16` for `GRAMFE_FFT`; comparable performance of `GRAMFE_MATMUL` and `WAVE_FD` for `PATCH_SIZE=8`).
+- The performance ratio `Perf_FD / Perf_Spectral` indicates the efficiency compared to the finite-difference scheme. This varies based on patch size (e.g., 4.3 for `PATCH_SIZE=8` and 2.6 for `PATCH_SIZE=16` for `FFT`; comparable performance of `MATMUL` and `FD` for `PATCH_SIZE=8`).
 
 ## Issues and Considerations
 - **Stability with Single Precision**: Using single precision can lead to instability in the scheme.
@@ -119,7 +119,7 @@ Understanding the differences between the `GRAMFE_MATMUL` and `GRAMFE_FFT` schem
 
 #### Current Precision and Limitations
 
-The calculation of the evolution matrix in the `GRAMFE_MATMUL` scheme currently requires at least 128-bit precision to maintain an error below single precision. The extension matrix has a high condition number, typically around 10^15 or higher, which necessitates this high precision.
+The calculation of the evolution matrix in the `MATMUL` scheme currently requires at least 128-bit precision to maintain an error below single precision. The extension matrix has a high condition number, typically around 10^15 or higher, which necessitates this high precision.
 
 #### Proposed Enhancements