fluidsim

Name: fluidsim
Author: K-Dense-AI

31kstars3.1kforks

How to install fluidsim?

k-dense-ai/scientific-agent-skills/fluidsim

$npx -y skills add K-Dense-AI/scientific-agent-skills --skill fluidsim

Installs into the current project.

Summary

Framework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D/3D), shallow water equations, stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. Provides pse

Files · 1

View on GitHub

SKILL.md

1	# FluidSim
2
3	## Overview
4
5	FluidSim is an object-oriented Python framework for high-performance computational fluid dynamics (CFD) simulations. It provides solvers for periodic-domain equations using pseudospectral methods with FFT, delivering performance comparable to Fortran/C++ while maintaining Python's ease of use.
6
7	Key strengths:
8	- Multiple solvers: 2D/3D Navier-Stokes, shallow water, stratified flows
9	- High performance: Pythran/Transonic compilation, MPI parallelization
10	- Complete workflow: Parameter configuration, simulation execution, output analysis
11	- Interactive analysis: Python-based post-processing and visualization
12
13	## Core Capabilities
14
15	### 1. Installation and Setup
16
17	Install fluidsim using uv with appropriate feature flags:
18
19	```bash
20	# Basic installation
21	uv pip install fluidsim
22
23	# With FFT support (required for most solvers)
24	uv pip install "fluidsim[fft]"
25
26	# With MPI for parallel computing
27	uv pip install "fluidsim[fft,mpi]"
28	```
29
30	Set environment variables for output directories (optional):
31
32	```bash
33	export FLUIDSIM_PATH=/path/to/simulation/outputs
34	export FLUIDDYN_PATH_SCRATCH=/path/to/working/directory
35	```
36
37	No API keys or authentication required.
38
39	See `references/installation.md` for complete installation instructions and environment configuration.
40
41	### 2. Running Simulations
42
43	Standard workflow consists of five steps:
44
45	Step 1: Import solver
46	```python
47	from fluidsim.solvers.ns2d.solver import Simul
48	```
49
50	Step 2: Create and configure parameters
51	```python
52	params = Simul.create_default_params()
53	params.oper.nx = params.oper.ny = 256
54	params.oper.Lx = params.oper.Ly = 2 * 3.14159
55	params.nu_2 = 1e-3
56	params.time_stepping.t_end = 10.0
57	params.init_fields.type = "noise"
58	```
59
60	Step 3: Instantiate simulation
61	```python
62	sim = Simul(params)
63	```
64
65	Step 4: Execute
66	```python
67	sim.time_stepping.start()
68	```
69
70	Step 5: Analyze results
71	```python
72	sim.output.phys_fields.plot("vorticity")
73	sim.output.spatial_means.plot()
74	```
75
76	See `references/simulation_workflow.md` for complete examples, restarting simulations, and cluster deployment.
77
78	### 3. Available Solvers
79
80	Choose solver based on physical problem:
81
82	2D Navier-Stokes (`ns2d`): 2D turbulence, vortex dynamics
83	```python
84	from fluidsim.solvers.ns2d.solver import Simul
85	```
86
87	3D Navier-Stokes (`ns3d`): 3D turbulence, realistic flows
88	```python
89	from fluidsim.solvers.ns3d.solver import Simul
90	```
91
92	Stratified flows (`ns2d.strat`, `ns3d.strat`): Oceanic/atmospheric flows
93	```python
94	from fluidsim.solvers.ns2d.strat.solver import Simul
95	params.N = 1.0 # Brunt-Väisälä frequency
96	```
97
98	Shallow water (`sw1l`): Geophysical flows, rotating systems
99	```python
100	from fluidsim.solvers.sw1l.solver import Simul
101	params.f = 1.0 # Coriolis parameter
102	```
103
104	See `references/solvers.md` for complete solver list and selection guidance.
105
106	### 4. Parameter Configuration
107
108	Parameters are organized hierarchically and accessed via dot notation:
109
110	Domain and resolution:
111	```python
112	params.oper.nx = 256 # grid points
113	params.oper.Lx = 2 * pi # domain size
114	```
115
116	Physical parameters:
117	```python
118	params.nu_2 = 1e-3 # viscosity
119	params.nu_4 = 0 # hyperviscosity (optional)
120	```
121
122	Time stepping:
123	```python
124	params.time_stepping.t_end = 10.0
125	params.time_stepping.USE_CFL = True # adaptive time step
126	params.time_stepping.CFL = 0.5
127	```
128
129	Initial conditions:
130	```python
131	params.init_fields.type = "noise" # or "dipole", "vortex", "from_file", "in_script"
132	```
133
134	Output settings:
135	```python
136	params.output.periods_save.phys_fields = 1.0 # save every 1.0 time units
137	params.output.periods_save.spectra = 0.5
138	params.output.periods_save.spatial_means = 0.1
139	```
140
141	The Parameters object raises `AttributeError` for typos, preventing silent configuration errors.
142
143	See `references/parameters.md` for comprehensive parameter documentation.
144
145	### 5. Output and Analysis
146
147	FluidSim produces multiple output types automatically saved during simulation:
148
149	Physical fields: Velocity, vorticity in HDF5 format
150	```python
151	sim.output.phys_fields.plot("vorticity")
152	sim.output.phys_fields.plot("vx")
153	```
154
155	Spatial means: Time series of volume-averaged quantities
156	```python
157	sim.output.spatial_means.plot()
158	```
159
160	Spectra: Energy and enstrophy spectra
161	```python
162	sim.output.spectra.plot1d()
163	sim.output.spectra.plot2d()
164	```
165
166	Load previous simulations:
167	```python
168	from fluidsim import load_sim_for_plot
169	sim = load_sim_for_plot("simulation_dir")
170	sim.output.phys_fields.plot()
171	```
172
173	Advanced visualization: Open `.h5` files in ParaView

People who liked this also viewed

6 picks

Type

fluidsim

31kstars3.1kforks

View on GitHub

How to install fluidsim?

k-dense-ai/scientific-agent-skills/fluidsim

$npx -y skills add K-Dense-AI/scientific-agent-skills --skill fluidsim

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# FluidSim
2
3	## Overview
4
5	FluidSim is an object-oriented Python framework for high-performance computational fluid dynamics (CFD) simulations. It provides solvers for periodic-domain equations using pseudospectral methods with FFT, delivering performance comparable to Fortran/C++ while maintaining Python's ease of use.
6
7	Key strengths:
8	- Multiple solvers: 2D/3D Navier-Stokes, shallow water, stratified flows
9	- High performance: Pythran/Transonic compilation, MPI parallelization
10	- Complete workflow: Parameter configuration, simulation execution, output analysis
11	- Interactive analysis: Python-based post-processing and visualization
12
13	## Core Capabilities
14
15	### 1. Installation and Setup
16
17	Install fluidsim using uv with appropriate feature flags:
18
19	```bash
20	# Basic installation
21	uv pip install fluidsim
22
23	# With FFT support (required for most solvers)
24	uv pip install "fluidsim[fft]"
25
26	# With MPI for parallel computing
27	uv pip install "fluidsim[fft,mpi]"
28	```
29
30	Set environment variables for output directories (optional):
31
32	```bash
33	export FLUIDSIM_PATH=/path/to/simulation/outputs
34	export FLUIDDYN_PATH_SCRATCH=/path/to/working/directory
35	```
36
37	No API keys or authentication required.
38
39	See `references/installation.md` for complete installation instructions and environment configuration.
40
41	### 2. Running Simulations
42
43	Standard workflow consists of five steps:
44
45	Step 1: Import solver
46	```python
47	from fluidsim.solvers.ns2d.solver import Simul
48	```
49
50	Step 2: Create and configure parameters
51	```python
52	params = Simul.create_default_params()
53	params.oper.nx = params.oper.ny = 256
54	params.oper.Lx = params.oper.Ly = 2 * 3.14159
55	params.nu_2 = 1e-3
56	params.time_stepping.t_end = 10.0
57	params.init_fields.type = "noise"
58	```
59
60	Step 3: Instantiate simulation
61	```python
62	sim = Simul(params)
63	```
64
65	Step 4: Execute
66	```python
67	sim.time_stepping.start()
68	```
69
70	Step 5: Analyze results
71	```python
72	sim.output.phys_fields.plot("vorticity")
73	sim.output.spatial_means.plot()
74	```
75
76	See `references/simulation_workflow.md` for complete examples, restarting simulations, and cluster deployment.
77
78	### 3. Available Solvers
79
80	Choose solver based on physical problem:
81
82	2D Navier-Stokes (`ns2d`): 2D turbulence, vortex dynamics
83	```python
84	from fluidsim.solvers.ns2d.solver import Simul
85	```
86
87	3D Navier-Stokes (`ns3d`): 3D turbulence, realistic flows
88	```python
89	from fluidsim.solvers.ns3d.solver import Simul
90	```
91
92	Stratified flows (`ns2d.strat`, `ns3d.strat`): Oceanic/atmospheric flows
93	```python
94	from fluidsim.solvers.ns2d.strat.solver import Simul
95	params.N = 1.0 # Brunt-Väisälä frequency
96	```
97
98	Shallow water (`sw1l`): Geophysical flows, rotating systems
99	```python
100	from fluidsim.solvers.sw1l.solver import Simul
101	params.f = 1.0 # Coriolis parameter
102	```
103
104	See `references/solvers.md` for complete solver list and selection guidance.
105
106	### 4. Parameter Configuration
107
108	Parameters are organized hierarchically and accessed via dot notation:
109
110	Domain and resolution:
111	```python
112	params.oper.nx = 256 # grid points
113	params.oper.Lx = 2 * pi # domain size
114	```
115
116	Physical parameters:
117	```python
118	params.nu_2 = 1e-3 # viscosity
119	params.nu_4 = 0 # hyperviscosity (optional)
120	```
121
122	Time stepping:
123	```python
124	params.time_stepping.t_end = 10.0
125	params.time_stepping.USE_CFL = True # adaptive time step
126	params.time_stepping.CFL = 0.5
127	```
128
129	Initial conditions:
130	```python
131	params.init_fields.type = "noise" # or "dipole", "vortex", "from_file", "in_script"
132	```
133
134	Output settings:
135	```python
136	params.output.periods_save.phys_fields = 1.0 # save every 1.0 time units
137	params.output.periods_save.spectra = 0.5
138	params.output.periods_save.spatial_means = 0.1
139	```
140
141	The Parameters object raises `AttributeError` for typos, preventing silent configuration errors.
142
143	See `references/parameters.md` for comprehensive parameter documentation.
144
145	### 5. Output and Analysis
146
147	FluidSim produces multiple output types automatically saved during simulation:
148
149	Physical fields: Velocity, vorticity in HDF5 format
150	```python
151	sim.output.phys_fields.plot("vorticity")
152	sim.output.phys_fields.plot("vx")
153	```
154
155	Spatial means: Time series of volume-averaged quantities
156	```python
157	sim.output.spatial_means.plot()
158	```
159
160	Spectra: Energy and enstrophy spectra
161	```python
162	sim.output.spectra.plot1d()
163	sim.output.spectra.plot2d()
164	```
165
166	Load previous simulations:
167	```python
168	from fluidsim import load_sim_for_plot
169	sim = load_sim_for_plot("simulation_dir")
170	sim.output.phys_fields.plot()
171	```
172
173	Advanced visualization: Open `.h5` files in ParaView

People who liked this also viewed

6 picks

Type