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skills/fluidsim/references/output_analysis.md

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+# Output and Analysis
+
+## Output Types
+
+FluidSim automatically saves several types of output during simulations.
+
+### Physical Fields
+
+**File format**: HDF5 (`.h5`)
+
+**Location**: `simulation_dir/state_phys_t*.h5`
+
+**Contents**: Velocity, vorticity, and other physical space fields at specific times
+
+**Access**:
+```python
+sim.output.phys_fields.plot()
+sim.output.phys_fields.plot("vorticity")
+sim.output.phys_fields.plot("vx")
+sim.output.phys_fields.plot("div")  # check divergence
+
+# Save manually
+sim.output.phys_fields.save()
+
+# Get data
+vorticity = sim.state.state_phys.get_var("rot")
+```
+
+### Spatial Means
+
+**File format**: Text file (`.txt`)
+
+**Location**: `simulation_dir/spatial_means.txt`
+
+**Contents**: Volume-averaged quantities vs time (energy, enstrophy, etc.)
+
+**Access**:
+```python
+sim.output.spatial_means.plot()
+
+# Load from file
+from fluidsim import load_sim_for_plot
+sim = load_sim_for_plot("simulation_dir")
+sim.output.spatial_means.load()
+spatial_means_data = sim.output.spatial_means
+```
+
+### Spectra
+
+**File format**: HDF5 (`.h5`)
+
+**Location**: `simulation_dir/spectra_*.h5`
+
+**Contents**: Energy and enstrophy spectra vs wavenumber
+
+**Access**:
+```python
+sim.output.spectra.plot1d()  # 1D spectrum
+sim.output.spectra.plot2d()  # 2D spectrum
+
+# Load spectra data
+spectra = sim.output.spectra.load2d_mean()
+```
+
+### Spectral Energy Budget
+
+**File format**: HDF5 (`.h5`)
+
+**Location**: `simulation_dir/spect_energy_budg_*.h5`
+
+**Contents**: Energy transfer between scales
+
+**Access**:
+```python
+sim.output.spect_energy_budg.plot()
+```
+
+## Post-Processing
+
+### Loading Simulations for Analysis
+
+#### Fast Loading (Read-Only)
+
+```python
+from fluidsim import load_sim_for_plot
+
+sim = load_sim_for_plot("simulation_dir")
+
+# Access all output types
+sim.output.phys_fields.plot()
+sim.output.spatial_means.plot()
+sim.output.spectra.plot1d()
+```
+
+Use this for quick visualization and analysis. Does not initialize full simulation state.
+
+#### Full State Loading
+
+```python
+from fluidsim import load_state_phys_file
+
+sim = load_state_phys_file("simulation_dir/state_phys_t10.000.h5")
+
+# Can continue simulation
+sim.time_stepping.start()
+```
+
+### Visualization Tools
+
+#### Built-in Plotting
+
+FluidSim provides basic plotting through matplotlib:
+
+```python
+# Physical fields
+sim.output.phys_fields.plot("vorticity")
+sim.output.phys_fields.animate("vorticity")
+
+# Time series
+sim.output.spatial_means.plot()
+
+# Spectra
+sim.output.spectra.plot1d()
+```
+
+#### Advanced Visualization
+
+For publication-quality or 3D visualization:
+
+**ParaView**: Open `.h5` files directly
+```bash
+paraview simulation_dir/state_phys_t*.h5
+```
+
+**VisIt**: Similar to ParaView for large datasets
+
+**Custom Python**:
+```python
+import h5py
+import matplotlib.pyplot as plt
+
+# Load field manually
+with h5py.File("state_phys_t10.000.h5", "r") as f:
+    vx = f["state_phys"]["vx"][:]
+    vy = f["state_phys"]["vy"][:]
+
+# Custom plotting
+plt.contourf(vx)
+plt.show()
+```
+
+## Analysis Examples
+
+### Energy Evolution
+
+```python
+from fluidsim import load_sim_for_plot
+import matplotlib.pyplot as plt
+
+sim = load_sim_for_plot("simulation_dir")
+df = sim.output.spatial_means.load()
+
+plt.figure()
+plt.plot(df["t"], df["E"], label="Kinetic Energy")
+plt.xlabel("Time")
+plt.ylabel("Energy")
+plt.legend()
+plt.show()
+```
+
+### Spectral Analysis
+
+```python
+sim = load_sim_for_plot("simulation_dir")
+
+# Plot energy spectrum
+sim.output.spectra.plot1d(tmin=5.0, tmax=10.0)  # average over time range
+
+# Get spectral data
+k, E_k = sim.output.spectra.load1d_mean(tmin=5.0, tmax=10.0)
+
+# Check for power law
+import numpy as np
+log_k = np.log(k)
+log_E = np.log(E_k)
+# fit power law in inertial range
+```
+
+### Parametric Study Analysis
+
+When running multiple simulations with different parameters:
+
+```python
+import os
+import pandas as pd
+from fluidsim import load_sim_for_plot
+
+# Collect results from multiple simulations
+results = []
+for sim_dir in os.listdir("simulations"):
+    if not os.path.isdir(f"simulations/{sim_dir}"):
+        continue
+
+    sim = load_sim_for_plot(f"simulations/{sim_dir}")
+
+    # Extract key metrics
+    df = sim.output.spatial_means.load()
+    final_energy = df["E"].iloc[-1]
+
+    # Get parameters
+    nu = sim.params.nu_2
+
+    results.append({
+        "nu": nu,
+        "final_energy": final_energy,
+        "sim_dir": sim_dir
+    })
+
+# Analyze results
+results_df = pd.DataFrame(results)
+results_df.plot(x="nu", y="final_energy", logx=True)
+```
+
+### Field Manipulation
+
+```python
+sim = load_sim_for_plot("simulation_dir")
+
+# Load specific time
+sim.output.phys_fields.set_of_phys_files.update_times()
+times = sim.output.phys_fields.set_of_phys_files.times
+
+# Load field at specific time
+field_file = sim.output.phys_fields.get_field_to_plot(time=5.0)
+vorticity = field_file.get_var("rot")
+
+# Compute derived quantities
+import numpy as np
+vorticity_rms = np.sqrt(np.mean(vorticity**2))
+vorticity_max = np.max(np.abs(vorticity))
+```
+
+## Output Directory Structure
+
+```
+simulation_dir/
+├── params_simul.xml         # Simulation parameters
+├── stdout.txt               # Standard output log
+├── state_phys_t*.h5         # Physical fields at different times
+├── spatial_means.txt        # Time series of spatial averages
+├── spectra_*.h5            # Spectral data
+├── spect_energy_budg_*.h5  # Energy budget data
+└── info_solver.txt         # Solver information
+```
+
+## Performance Monitoring
+
+```python
+# During simulation, check progress
+sim.output.print_stdout.complete_timestep()
+
+# After simulation, review performance
+sim.output.print_stdout.plot_deltat()  # plot time step evolution
+sim.output.print_stdout.plot_clock_times()  # plot computation time
+```
+
+## Data Export
+
+Convert fluidsim output to other formats:
+
+```python
+import h5py
+import numpy as np
+
+# Export to numpy array
+with h5py.File("state_phys_t10.000.h5", "r") as f:
+    vx = f["state_phys"]["vx"][:]
+    np.save("vx.npy", vx)
+
+# Export to CSV
+df = sim.output.spatial_means.load()
+df.to_csv("spatial_means.csv", index=False)
+```