New solutions with argparse to 1D data and new pdes added

FisherKPP/1D/ClampedFourier/dataset.h5

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FisherKPP/1D/ClampedFourier/metadata.json

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+{
+    "generate_dataset_py": {
+      "num_spatial_dims": 1,
+      "pde": "FisherKPP",
+      "ic": "ClampedFourier",
+      "bc": "None",
+      "x_domain_extent": 1.0,
+      "num_points": 2048,
+      "dt_save": 0.005,
+      "t_end": 50.0,
+      "save_freq": 1,
+      "simulations": 10,
+      "plotted_sim": 3,
+      "plot_sim": "True",
+      "stats": "True",
+      "seed": 42,
+      "nu": [0, 0.00001, 0.01], 
+      "reactivity": 10,
+      "pde_cmaps": {"FisherKPP": "viridis"}
+    },
+  
+    "generation_details": {
+      "library": "Exponax",
+      "library_url": "https://github.com/Ceyron/exponax/tree/main/exponax",
+      "spatial_method": "Fourier pseudo-spectral method",
+      "dealiasing": "2/3-rule",
+      "time_integration": "Exponential time-differencing",
+      "variant": "ETDRK2 (second-order Runge-Kutta)"
+    },
+  
+    "stepper_py": {
+      "cutoff": 5,
+      "include_init": true
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+  
+    "exponax_stepper": {
+      "diffusivity": 0.1,
+      "convection_scale": 1.0,
+      "single_channel": false,
+      "conservative": false,
+      "order": 2,
+      "dealiasing_fraction": 0.6666666666666666,
+      "num_circle_points": 16,
+      "circle_radius": 1.0
+    },
+  
+    "exponax_ic": {
+      "description": "This dataset uses the RandomTruncatedFourierSeries class to generate initial conditions.",
+      "amplitude_range": [0.0, 1.0],
+      "angle_range": [0.0, 6.283185307179586],
+      "offset_range": [0.0, 0.0],
+      "std_one": true,
+      "max_one": false,
+      "method": "Initial condition generated by sampling complex Fourier coefficients with random amplitude and phase, truncated using a low-pass filter. A small real offset is added to the zero mode. The result is transformed back to physical space using an inverse FFT. Optional normalization can enforce unit standard deviation or unit maximum.",
+      "source_module": "exponax.ic.RandomTruncatedFourierSeries"
+    },
+    
+    "dataset_global_statistics": {
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+        "std": 0.248977,
+        "min": -0.000006,
+        "max": 1.000009
+      }
+    },
+
+  "generation_metadata": {
+    "generation_time": "11.55 seconds",
+    "dataset_shape": [30, 1, 51, 2048]
+  }
+}

GrayScott/1D/RandomGaussianBlobs/dataset.h5

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+size 1040768

GrayScott/1D/RandomGaussianBlobs/metadata.json

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+{
+  "generate_dataset_py": {
+    "num_spatial_dims": 1,
+    "pde": "GrayScott",
+    "ic": "RandomGaussianBlobs",
+    "bc": "None",
+    "x_domain_extent": 2.5,
+    "num_points": 128,
+    "dt_save": 1,
+    "t_end": 5000.0,
+    "save_freq": 50,
+    "simulations": 10,
+    "plotted_sim": 3,
+    "plot_sim": "True",
+    "stats": "True",
+    "seed": 42,
+    "nu": [0, 0.00001, 0.01], 
+    "feed_rate": 0.028,
+    "kill_rate": 0.056,
+    "pde_cmaps": {"Burgers": "viridis"}
+  },
+
+  "generation_details": {
+    "library": "Exponax",
+    "library_url": "https://github.com/Ceyron/exponax/tree/main/exponax",
+    "spatial_method": "Fourier pseudo-spectral method",
+    "dealiasing": "2/3-rule",
+    "time_integration": "Exponential time-differencing",
+    "variant": "ETDRK2 (second-order Runge-Kutta)"
+  },
+
+  "stepper_py": {
+    "cutoff": 5,
+    "include_init": "True"
+  },
+
+  "exponax_stepper": {
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+    "convection_scale": 1.0,
+    "single_channel": false,
+    "conservative": false,
+    "order": 2,
+    "dealiasing_fraction": 0.6666666666666666,
+    "num_circle_points": 16,
+    "circle_radius": 1.0
+  },
+
+  "exponax_ic": {
+    "description": "This dataset uses the RandomTruncatedFourierSeries class to generate initial conditions.",
+    "amplitude_range": [0.0, 1.0],
+    "angle_range": [0.0, 6.283185307179586],
+    "offset_range": [0.0, 0.0],
+    "std_one": true,
+    "max_one": false,
+    "method": "Initial condition generated by sampling complex Fourier coefficients with random amplitude and phase, truncated using a low-pass filter. A small real offset is added to the zero mode. The result is transformed back to physical space using an inverse FFT. Optional normalization can enforce unit standard deviation or unit maximum.",
+    "source_module": "exponax.ic.RandomTruncatedFourierSeries"
+  },
+  
+  "dataset_global_statistics": {
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+  },
+
+  "generation_metadata": {
+  "generation_time": "9.66 seconds",
+  "dataset_shape": [10, 2, 101, 128]
+  }
+  
+}

KS/1D/RandomTruncatedFourierSeries/dataset.h5

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KS/2D/RandomTruncatedFourierSeries/dataset.h5

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KS/2D/RandomTruncatedFourierSeries/metadata.json

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-{
-    "pde": "KuramotoSivashinsky",
-  
-    "generate_dataset_py": {
-      "num_spatial_dims": 2,
-      "num_points": 200,
-      "num_channels": 1,
-      "x_domain_extent": 100.0,
-      "y_domain_extent": 100.0,
-      "dt_solver": 0.1,
-      "t_end": 1000.0,
-      "save_freq": 1,
-      "simulations": 10,
-      "plotted_sim": 5,
-      "ic": "RandomTruncatedFourierSeries",
-      "bc": "None",
-      "include_init": true,
-      "plot_min_max": [-2, 2]
-    },
-  
-    "generation_details": {
-      "equation": "Kuramoto–Sivashinsky (fluid dynamics form)",
-      "library": "Exponax",
-      "library_url": "https://github.com/Ceyron/exponax/tree/main/exponax",
-      "spatial_discretization": "Fourier pseudo-spectral method",
-      "nonlinearity": "Conservative convection term: (1/2) * ∂ₓ(u²)",
-      "linear_terms": {
-        "second_order": "∂ₓₓ (destabilizing, ψ₁ > 0)",
-        "fourth_order": "∂ₓₓₓₓ (stabilizing, ψ₂ > 0)"
-    },
-  
-    "stepper_py": {
-      "cutoff": 5
-    },
-  
-    "exponax_stepper": {
-      "diffusivity": 0.1,
-      "convection_scale": 1.0,
-      "second_order_scale": 1.0,
-      "forth_order_scale": 1.0,
-      "single_channel": false,
-      "conservative": true,
-      "dealiasing_fraction": 0.6666666666666666,
-      "order": 2,
-      "zero_mode_fix": true
-    },
-  
-    "exponax_ic": {
-      "num_circle_points": 16,
-      "circle_radius": 1.0
-    },
-  
-    "dataset_global_statistics": {
-      "mean": -0.000003,
-      "std": 4.424566,
-      "min": -18.658789,
-      "max": 22.338400
-    }
-    
-  }
-  }
-  

KS/2D/RandomTruncatedFourierSeries/plots/evolution_seed_0.mp4

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KS/2D/RandomTruncatedFourierSeries/plots/evolution_seed_1.mp4

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KS/2D/RandomTruncatedFourierSeries/plots/evolution_seed_2.mp4

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KS/2D/RandomTruncatedFourierSeries/plots/evolution_seed_3.mp4

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KS/2D/RandomTruncatedFourierSeries/plots/evolution_seed_9.mp4

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KS/3D/RandomTruncatedFourierSeries/dataset.h5

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KS/3D/RandomTruncatedFourierSeries/metadata.json

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-{
-    "pde": "KuramotoSivashinsky",
-  
-    "generate_dataset_py": {
-      "num_spatial_dims": 3,
-      "num_points": 100,
-      "num_channels": 1,
-      "x_domain_extent": 100.0,
-      "y_domain_extent": 100.0,
-      "z_domain_extent": 100.0,
-      "dt_solver": 0.0001,
-      "t_end": 100.0,
-      "save_freq": 1,
-      "simulations": 5,
-      "plotted_sim": 5,
-      "ic": "RandomTruncatedFourierSeries",
-      "bc": "None",
-      "include_init": true
-    },
-  
-    "generation_details": {
-      "equation": "Kuramoto–Sivashinsky (fluid dynamics form)",
-      "library": "Exponax",
-      "library_url": "https://github.com/Ceyron/exponax/tree/main/exponax",
-      "spatial_discretization": "Fourier pseudo-spectral method",
-      "nonlinearity": "Conservative convection term: (1/2) * ∂ₓ(u²)",
-      "linear_terms": {
-        "second_order": "∂ₓₓ (destabilizing, ψ₁ > 0)",
-        "fourth_order": "∂ₓₓₓₓ (stabilizing, ψ₂ > 0)"
-    },
-  
-    "stepper_py": {
-      "cutoff": 5
-    },
-  
-    "exponax_stepper": {
-      "diffusivity": 0.1,
-      "convection_scale": 1.0,
-      "second_order_scale": 1.0,
-      "forth_order_scale": 1.0,
-      "single_channel": false,
-      "conservative": true,
-      "dealiasing_fraction": 0.6666666666666666,
-      "order": 2,
-      "zero_mode_fix": true
-    },
-  
-    "exponax_ic": {
-      "num_circle_points": 16,
-      "circle_radius": 1.0
-    },
-  
-    "dataset_global_statistics": {
-      "mean": 0.000000,
-      "std": 3.471332,
-      "min": -15.732433,
-      "max": 16.369047
-    }
-    
-  }
-  }
-  

KS/3D/RandomTruncatedFourierSeries/plots/center_slice_seed_4_channel_0.mp4

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KortewegDeVries/1D/RandomTruncatedFourierSeries/dataset.h5

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+size 2581888

KortewegDeVries/1D/RandomTruncatedFourierSeries/metadata.json

@@ -1,63 +1,74 @@
 {
-    "generate_dataset_py": {
-      "pde": "KortewegDeVries",
-      "num_spatial_dims": 1,
-      "num_points": 200,
-      "num_channels": 1,
-      "x_domain_extent": 100.0,
-      "dt_solver": 0.01,
-      "t_end": 1000.0,
-      "save_freq": 1,
-      "simulations": 50,
-      "plotted_sim": 10,
-      "ic": "RandomTruncatedFourierSeries",
-      "bc": "None"
-    },
+  "generate_dataset_py": {
+    "num_spatial_dims": 1,
+    "pde": "KortewegDeVries",
+    "ic": "RandomTruncatedFourierSeries",
+    "bc": "None",
+    "x_domain_extent": 128.0,
+    "num_points": 128,
+    "dt_save": 0.0001,
+    "t_end": 500.0,
+    "save_freq": 1,
+    "simulations": 10,
+    "plotted_sim": 3,
+    "plot_sim": "True",
+    "stats": "True",
+    "seed": 42,
+    "nu": [0, 0.00001, 0.01], 
+    "pde_cmaps": {"KortewegDeVries": "RdBu"}
+  },
 
-    "generation_details": {
-      "library": "Exponax",
-      "library_url": "https://github.com/Ceyron/exponax/tree/main/exponax",
-      "spatial_method": "Fourier pseudo-spectral method",
-      "dealiasing": "2/3-rule",
-      "time_integration": "Exponential time-differencing",
-      "variant": "ETDRK2 (second-order Runge-Kutta)"
-    },
+  "generation_details": {
+    "library": "Exponax",
+    "library_url": "https://github.com/Ceyron/exponax/tree/main/exponax",
+    "spatial_method": "Fourier pseudo-spectral method",
+    "dealiasing": "2/3-rule",
+    "time_integration": "Exponential time-differencing",
+    "variant": "ETDRK2 (second-order Runge-Kutta)"
+  },
 
-    "stepper_py": {
-      "cutoff": 5
-    },
-  
-    "exponax_stepper": {
-        "convection_scale": -6.0,
-        "diffusivity": 0.0,
-        "dispersivity": 1.0,
-        "hyper_diffusivity": 0.01,
-        "advect_over_diffuse": "False",
-        "diffuse_over_diffuse": "False",
-        "single_channel": "False",
-        "conservative": "False",
-        "order": 2,
-        "dealiasing_fraction": 0.6666666666666666,
-        "num_circle_points": 16,
-        "circle_radius": 1.0
-    },
+  "stepper_py": {
+    "cutoff": 5,
+    "include_init": "True"
+  },
+
+  "exponax_stepper": {
+      "convection_scale": -6.0,
+      "diffusivity": 0.0,
+      "dispersivity": 1.0,
+      "hyper_diffusivity": 0.01,
+      "advect_over_diffuse": "False",
+      "diffuse_over_diffuse": "False",
+      "single_channel": "False",
+      "conservative": "False",
+      "order": 2,
+      "dealiasing_fraction": 0.6666666666666666,
+      "num_circle_points": 16,
+      "circle_radius": 1.0
+  },
+
+  "exponax_ic": {
+    "description": "This dataset uses the RandomTruncatedFourierSeries class to generate initial conditions.",
+    "amplitude_range": [0.0, 1.0],
+    "angle_range": [0.0, 6.283185307179586],
+    "offset_range": [0.0, 0.0],
+    "std_one": true,
+    "max_one": false,
+    "method": "Initial condition generated by sampling complex Fourier coefficients with random amplitude and phase, truncated using a low-pass filter. A small real offset is added to the zero mode. The result is transformed back to physical space using an inverse FFT. Optional normalization can enforce unit standard deviation or unit maximum.",
+    "source_module": "exponax.ic.RandomTruncatedFourierSeries"
+  },
   
-    "exponax_ic": {
-      "description": "This dataset uses the RandomTruncatedFourierSeries class to generate initial conditions.",
-      "amplitude_range": [0.0, 1.0],
-      "angle_range": [0.0, 6.283185307179586],
-      "offset_range": [0.0, 0.0],
-      "std_one": true,
-      "max_one": false,
-      "method": "Initial condition generated by sampling complex Fourier coefficients with random amplitude and phase, truncated using a low-pass filter. A small real offset is added to the zero mode. The result is transformed back to physical space using an inverse FFT. Optional normalization can enforce unit standard deviation or unit maximum.",
-      "source_module": "exponax.ic.RandomTruncatedFourierSeries"
-    },
-    
-    "dataset_global_statistics": {
+  "dataset_global_statistics": {
+    "channel_0": {
       "mean": 0.000000,
-      "std": 0.562932,
-      "min": -4.766301,
-      "max": 5.909781
-    } 
-    
+      "std": 0.920627,
+      "min": -2.5384331,
+      "max": 2.620492
+    }
+  },
+
+  "generation_metadata": {
+    "generation_time": "7.57 seconds",
+    "dataset_shape": [10, 1, 501, 128]
+  } 
 }

KuramotoSivashinsky/1D/RandomTruncatedFourierSeries/dataset.h5

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+oid sha256:26c4d449632ea072317c16e9d4857e419b67e1b7751f81a89a87c8e75fe9484e
+size 800

{KS → KuramotoSivashinsky}/1D/RandomTruncatedFourierSeries/metadata.json

@@ -1,44 +1,47 @@
 {
-  "pde": "KuramotoSivashinskyConservative",
-
   "generate_dataset_py": {
     "num_spatial_dims": 1,
-    "num_points": 200,
-    "num_channels": 1,
-    "x_domain_extent": 100.0,
-    "dt_solver": 0.1,
-    "t_end": 1000.0,
-    "save_freq": 1,
-    "simulations": 50,
-    "plotted_sim": 10,
+    "pde": "KuramotoSivashinskyConservative",
     "ic": "RandomTruncatedFourierSeries",
     "bc": "None",
-    "include_init": true,
-    "plot_min_max": [-2, 2]
+    "x_domain_extent": 128.0,
+    "num_points": 128,
+    "dt_save": 0.1,
+    "t_end": 1000.0,
+    "save_freq": 1,
+    "simulations": 10,
+    "plotted_sim": 3,
+    "plot_sim": "True",
+    "stats": "True",
+    "seed": 42,
+    "nu": [0, 0.01, 0.1, 0.05],  
+    "pde_cmaps": {"Burgers": "RdBu"}
   },
 
   "generation_details": {
-    "equation": "Kuramoto–Sivashinsky (fluid dynamics form)",
-    "library": "Exponax",
-    "library_url": "https://github.com/Ceyron/exponax/tree/main/exponax",
-    "spatial_discretization": "Fourier pseudo-spectral method",
-    "nonlinearity": "Conservative convection term: (1/2) * ∂ₓ(u²)",
-    "linear_terms": {
-      "second_order": "∂ₓₓ (destabilizing, ψ₁ > 0)",
-      "fourth_order": "∂ₓₓₓₓ (stabilizing, ψ₂ > 0)"
-  },
+      "equation": "Kuramoto–Sivashinsky (conservative / fluid dynamics form)",
+      "library": "Exponax",
+      "library_url": "https://github.com/Ceyron/exponax/tree/main/exponax",
+      "spatial_discretization": "Fourier pseudo-spectral method",
+      "nonlinearity": "Conservative convection term: (1/2) * ∂ₓ(u²)",
+      "linear_terms": {
+        "second_order": "∂ₓₓ (destabilizing, ψ₁ > 0)",
+        "fourth_order": "∂ₓₓₓₓ (stabilizing, ψ₂ > 0)"
+      }
+    },
 
   "stepper_py": {
-    "cutoff": 5
+    "cutoff": 5,
+    "include_init": true
   },
 
   "exponax_stepper": {
-    "diffusivity": 0.1,
     "convection_scale": 1.0,
     "second_order_scale": 1.0,
-    "forth_order_scale": 1.0,
+    "fourth_order_scale": 1.0,
     "single_channel": false,
     "conservative": true,
+    "num_channels": 1,
     "dealiasing_fraction": 0.6666666666666666,
     "order": 2,
     "zero_mode_fix": true
@@ -50,11 +53,17 @@
   },
 
   "dataset_global_statistics": {
-    "mean": 0.000000,
-    "std": 1.228146,
-    "min": -4.330707,
-    "max": 4.659098
+    "channel_0": {
+      "mean": 0.000000,
+      "std": 1.200984,
+      "min": -3.882072,
+      "max": 3.882204
+    }
+  },
+
+  "generation_metadata": {
+    "generation_time": "15.44 seconds",
+    "dataset_shape": [40, 1, 1001, 128]
   }
-  
-}
+
 }

KuramotoSivashinskyConservative/1D/RandomTruncatedFourierSeries/dataset.h5

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+size 800

KuramotoSivashinskyConservative/1D/RandomTruncatedFourierSeries/metadata.json

@@ -0,0 +1,69 @@
+{
+  "generate_dataset_py": {
+    "num_spatial_dims": 1,
+    "pde": "KuramotoSivashinskyConservative",
+    "ic": "RandomTruncatedFourierSeries",
+    "bc": "None",
+    "x_domain_extent": 128.0,
+    "num_points": 128,
+    "dt_save": 0.1,
+    "t_end": 1000.0,
+    "save_freq": 1,
+    "simulations": 10,
+    "plotted_sim": 3,
+    "plot_sim": "True",
+    "stats": "True",
+    "seed": 42,
+    "nu": [0, 0.01, 0.1, 0.05],  
+    "pde_cmaps": {"Burgers": "RdBu"}
+  },
+
+  "generation_details": {
+      "equation": "Kuramoto–Sivashinsky (conservative / fluid dynamics form)",
+      "library": "Exponax",
+      "library_url": "https://github.com/Ceyron/exponax/tree/main/exponax",
+      "spatial_discretization": "Fourier pseudo-spectral method",
+      "nonlinearity": "Conservative convection term: (1/2) * ∂ₓ(u²)",
+      "linear_terms": {
+        "second_order": "∂ₓₓ (destabilizing, ψ₁ > 0)",
+        "fourth_order": "∂ₓₓₓₓ (stabilizing, ψ₂ > 0)"
+      }
+    },
+
+  "stepper_py": {
+    "cutoff": 5,
+    "include_init": true
+  },
+
+  "exponax_stepper": {
+    "convection_scale": 1.0,
+    "second_order_scale": 1.0,
+    "fourth_order_scale": 1.0,
+    "single_channel": false,
+    "conservative": true,
+    "num_channels": 1,
+    "dealiasing_fraction": 0.6666666666666666,
+    "order": 2,
+    "zero_mode_fix": true
+  },
+
+  "exponax_ic": {
+    "num_circle_points": 16,
+    "circle_radius": 1.0
+  },
+
+  "dataset_global_statistics": {
+    "channel_0": {
+      "mean": 0.000000,
+      "std": 1.200984,
+      "min": -3.882072,
+      "max": 3.882204
+    }
+  },
+
+  "generation_metadata": {
+    "generation_time": "15.44 seconds",
+    "dataset_shape": [40, 1, 1001, 128]
+  }
+
+}

SwiftHohenberg/1D/RandomTruncatedFourierSeries/dataset.h5

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