mc

DOI-USGS · Jun 13, 2024 · 820e8a4 · 820e8a4
2 parents c128682 + 7bc9cfb
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diff --git a/docs/_downloads/021b6cf14de4fd76c7a3e2f90a173578/hdf5.ipynb b/docs/_downloads/021b6cf14de4fd76c7a3e2f90a173578/hdf5.ipynb
@@ -136,7 +136,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.10.12"
+      "version": "3.12.3"
     }
   },
   "nbformat": 4,

diff --git a/docs/_downloads/16ec1efc89ed8eeea10bd844b92557de/plot_rectilinear_mesh_1d.ipynb b/docs/_downloads/16ec1efc89ed8eeea10bd844b92557de/plot_rectilinear_mesh_1d.ipynb
@@ -277,7 +277,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.10.12"
+      "version": "3.12.3"
     }
   },
   "nbformat": 4,

diff --git a/docs/_downloads/2dd62cc642303de6b0d2af1a789eccaa/plot_skytem_datapoint.py b/docs/_downloads/2dd62cc642303de6b0d2af1a789eccaa/plot_skytem_datapoint.py
@@ -39,9 +39,9 @@
 # For more information about the time domain data set, see :ref:`Time domain dataset`
 
 # The data file name
-dataFile=dataFolder + 'skytem_512_saline_clay.csv'
+dataFile=dataFolder + 'skytem_saline_clay.csv'
 # The EM system file name
-systemFile=[dataFolder + 'SkytemHM_512.stm', dataFolder + 'SkytemLM_512.stm']
+systemFile=[dataFolder + 'SkytemHM.stm', dataFolder + 'SkytemLM.stm']
 
 #%%
 # Initialize and read an EM data set
@@ -108,7 +108,7 @@
 #%%
 # Plot the misfits for a range of half space conductivities
 plt.figure()
-_ = tdp.plotHalfSpaceResponses(-6.0, 4.0, 200)
+_ = tdp.plot_halfspace_responses(-6.0, 4.0, 200)
 plt.title("Halfspace responses")
 
 #%%

diff --git a/docs/_downloads/36c869e825ae3b16a184379512e44203/plot_model_2d.ipynb b/docs/_downloads/36c869e825ae3b16a184379512e44203/plot_model_2d.ipynb
@@ -64,7 +64,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.10.12"
+      "version": "3.12.3"
     }
   },
   "nbformat": 4,

diff --git a/docs/_downloads/36d592b131669bd825431209f21f3531/plot_histogram_2d.ipynb b/docs/_downloads/36d592b131669bd825431209f21f3531/plot_histogram_2d.ipynb
@@ -450,7 +450,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.10.12"
+      "version": "3.12.3"
     }
   },
   "nbformat": 4,

diff --git a/docs/_downloads/439c06574d36795305525eb492c7861b/plot_tempest_datapoint.py b/docs/_downloads/439c06574d36795305525eb492c7861b/plot_tempest_datapoint.py
@@ -132,7 +132,7 @@
 # Plot the misfits for a range of half space conductivities
 plt.figure()
 plt.subplot(1, 2, 1)
-_ = tdp.plotHalfSpaceResponses(-6.0, 4.0, 200)
+_ = tdp.plot_halfspace_responses(-6.0, 4.0, 200)
 plt.title("Halfspace responses")
 
 #%%

diff --git a/docs/_downloads/48f0be9987c0cd931b23ce187c305d56/plot_inference_2d_resolve.py b/docs/_downloads/48f0be9987c0cd931b23ce187c305d56/plot_inference_2d_resolve.py
@@ -38,12 +38,15 @@ def plot_2d_summary(folder, data_type, model_type):
          "cmap" : 'jet'
          }
 
+   import warnings
+   warnings.filterwarnings('error')
+
    fig = plt.figure(figsize=(16, 8))
    plt.suptitle("{} {}".format(data_type, model_type))
    gs0 = fig.add_gridspec(6, 2, hspace=1.0)
 
    true_model = Model.create_synthetic_model(model_type)
-   true_model.mesh.y_edges = true_model.mesh.y_edges / 4.1
+   true_model.mesh.y_edges = true_model.mesh.y_edges / 10.0
 
    kwargs['vmin'] = np.log10(np.min(true_model.values))
    kwargs['vmax'] = np.log10(np.max(true_model.values))
@@ -134,17 +137,16 @@ def plot_2d_summary(folder, data_type, model_type):
    results_2d.plot_data_elevation(linewidth=0.3, ax=ax1);
    results_2d.plot_elevation(linewidth=0.3, ax=ax1);
 
-
-   plt.show()
-   # plt.savefig('{}_{}.png'.format(data_type, model_type), dpi=300)
+   # plt.show()
+   plt.savefig('{}_{}.png'.format(data_type, model_type), dpi=300)
 
 if __name__ == '__main__':
    models = ['glacial', 'saline_clay', 'resistive_dolomites', 'resistive_basement', 'coastal_salt_water', 'ice_over_salt_water']
 
    for model in models:
-      try:
+      # try:
          plot_2d_summary("../../../Parallel_Inference/", "resolve", model)
-      except Exception as e:
-         print(model)
-         print(e)
-         pass
+      # except Exception as e:
+      #    print(model)
+      #    print(e)
+      #    pass
diff --git a/docs/_downloads/525bc65bfe238dea5610d6856bece19c/plot_model_3d.ipynb b/docs/_downloads/525bc65bfe238dea5610d6856bece19c/plot_model_3d.ipynb
@@ -205,7 +205,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.10.12"
+      "version": "3.12.3"
     }
   },
   "nbformat": 4,

diff --git a/docs/_downloads/53dc65a717762d4693b891c0caabbde0/plot_StatArray.py b/docs/_downloads/53dc65a717762d4693b891c0caabbde0/plot_StatArray.py
@@ -55,7 +55,6 @@
 # The StatArray class has been built so that we may easily
 # attach not only names and units, but statistical distributions too.
 # We won't go into too much detail about the different distribution
-# classes here so check out the :ref:`Distribution Class` for a better description.
 #
 # Two types of distributions can be attached to the StatArray.
 #

diff --git a/docs/_downloads/54ce350904e65ae0e6717397118ed43f/plot_inference_2d_tempest.py b/docs/_downloads/54ce350904e65ae0e6717397118ed43f/plot_inference_2d_tempest.py
@@ -134,8 +134,8 @@ def plot_2d_summary(folder, data_type, model_type):
    results_2d.plot_data_elevation(linewidth=0.3, ax=ax1);
    results_2d.plot_elevation(linewidth=0.3, ax=ax1);
 
-   plt.show()
-   # plt.savefig('{}_{}.png'.format(data_type, model_type), dpi=300)
+   # plt.show()
+   plt.savefig('{}_{}.png'.format(data_type, model_type), dpi=300)
 
 
 if __name__ == '__main__':

diff --git a/docs/_downloads/6651de36bdd3440bb761887dd2b00831/plot_histogram_1d.ipynb b/docs/_downloads/6651de36bdd3440bb761887dd2b00831/plot_histogram_1d.ipynb
@@ -320,7 +320,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.10.12"
+      "version": "3.12.3"
     }
   },
   "nbformat": 4,

diff --git a/...ource/examples/Data/plot_pointcloud3d.py1 → ...a7e415f479abafdaf81d/plot_pointcloud3d.py b/...ource/examples/Data/plot_pointcloud3d.py1 → ...a7e415f479abafdaf81d/plot_pointcloud3d.py
@@ -5,13 +5,13 @@
 
 #%%
 
-from geobipy import PointCloud3D
+from geobipy import Point
 from os.path import join
 import numpy as np
 import matplotlib.pyplot as plt
 import h5py
 
-nPoints = 10000
+nPoints = 200
 
 #%%
 # Create a quick test example using random points
@@ -20,15 +20,15 @@
 y = -np.abs((2.0 * np.random.rand(nPoints)) - 1.0)
 z = x * (1.0 - x) * np.cos(np.pi * x) * np.sin(np.pi * y)
 
-PC3D = PointCloud3D(x=x, y=y, z=z)
+PC3D = Point(x=x, y=y, z=z)
 
 #%%
 # Append pointclouds together
 x = np.abs((2.0 * np.random.rand(nPoints)) - 1.0)
 y = np.abs((2.0 * np.random.rand(nPoints)) - 1.0)
 z = x * (1.0 - x) * np.cos(np.pi * x) * np.sin(np.pi * y)
 
-Other_PC = PointCloud3D(x=x, y=y, z=z)
+Other_PC = Point(x=x, y=y, z=z)
 PC3D.append(Other_PC)
 
 #%%
@@ -41,7 +41,6 @@
 
 Point = PC3D[50]
 # Print the point to the screen
-print(Point)
 
 #%%
 # Plot the locations with Height as colour
@@ -58,7 +57,7 @@
 
 #%%
 # Interpolate the points to a 2D rectilinear mesh
-mesh, dum = PC3D.interpolate(0.01, 0.01, values=PC3D.z, method='mc', mask=0.03)
+mesh, dum = PC3D.interpolate(0.01, 0.01, values=PC3D.z, method='sibson', mask=0.03)
 
 # We can save that mesh to VTK
 PC3D.to_vtk('pc3d.vtk')
@@ -68,44 +67,50 @@
 # Grid the points using a triangulated CloughTocher, or minimum curvature interpolation
 
 plt.figure()
-plt.subplot(321)
+plt.subplot(331)
 PC3D.map(dx=0.01, dy=0.01, method='ct')
-plt.subplot(322)
+plt.subplot(332)
 PC3D.map(dx=0.01, dy=0.01, method='mc')
+plt.subplot(333)
+PC3D.map(dx=0.01, dy=0.01, method='sibson')
 
-plt.subplot(323)
+plt.subplot(334)
 PC3D.map(dx=0.01, dy=0.01, method='ct', mask=0.03)
-plt.subplot(324)
+plt.subplot(335)
 PC3D.map(dx=0.01, dy=0.01, method='mc', mask=0.03)
+plt.subplot(336)
+PC3D.map(dx=0.01, dy=0.01, method='sibson', mask=0.03)
 #%%
 # For lots of points, these surfaces can look noisy. Using a block filter will help
 PCsub = PC3D.block_median(0.005, 0.005)
-plt.subplot(325)
+plt.subplot(337)
 PCsub.map(dx=0.01, dy=0.01, method='ct', mask=0.03)
-plt.subplot(326)
+plt.subplot(338)
 PCsub.map(dx=0.01, dy=0.01, method='mc', mask=0.03)
+plt.subplot(339)
+PCsub.map(dx=0.01, dy=0.01, method='sibson', mask=0.03)
 
 
 #%%
 # We can perform spatial searches on the 3D point cloud
 
-PC3D.setKdTree(nDims=2)
+PC3D.set_kdtree(ndim=2)
 p = PC3D.nearest((0.0,0.0), k=200, p=2, radius=0.3)
 
 #%%
 # .nearest returns the distances and indices into the point cloud of the nearest points.
 # We can then obtain those points as another point cloud
 
-pNear = PC3D[p[1]]
-plt.figure()
-ax1 = plt.subplot(1,2,1)
-pNear.scatter2D()
-plt.plot(0.0, 0.0, 'x')
-plt.subplot(1,2,2, sharex=ax1, sharey=ax1)
-ax, sc, cb = PC3D.scatter2D(edgecolor='k')
-searchRadius = plt.Circle((0.0, 0.0), 0.3, color='b', fill=False)
-ax.add_artist(searchRadius)
-plt.plot(0.0, 0.0, 'x')
+# pNear = PC3D[p[1]]
+# plt.figure()
+# ax1 = plt.subplot(1,2,1)
+# pNear.scatter2D()
+# plt.plot(0.0, 0.0, 'x')
+# plt.subplot(1,2,2, sharex=ax1, sharey=ax1)
+# ax, sc, cb = PC3D.scatter2D(edgecolor='k')
+# searchRadius = plt.Circle((0.0, 0.0), 0.3, color='b', fill=False)
+# ax.add_artist(searchRadius)
+# plt.plot(0.0, 0.0, 'x')
 
 #%%
 # Read in the xyz co-ordinates in columns 2,3,4 from a file. Skip 1 header line.
@@ -126,9 +131,9 @@
     PC3D.writeHdf(f, 'test')
 
 with h5py.File('test.h5', 'r') as f:
-    PC3D1 = PointCloud3D.fromHdf(f['test'])
+    PC3D1 = Point.fromHdf(f['test'])
 
 with h5py.File('test.h5', 'r') as f:
-    point = PointCloud3D.fromHdf(f['test'], index=0)
+    point = Point.fromHdf(f['test'], index=0)
 
 plt.show()
diff --git a/docs/_downloads/6dec5e41149e94d435270c1dffe803e1/plot_rectilinear_mesh_2d.ipynb b/docs/_downloads/6dec5e41149e94d435270c1dffe803e1/plot_rectilinear_mesh_2d.ipynb
@@ -320,7 +320,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.10.12"
+      "version": "3.12.3"
     }
   },
   "nbformat": 4,

diff --git a/...rce/examples/Data/plot_skytem_dataset.py1 → ...294ca843748ae360e3/plot_skytem_dataset.py b/...rce/examples/Data/plot_skytem_dataset.py1 → ...294ca843748ae360e3/plot_skytem_dataset.py
@@ -18,10 +18,10 @@
 #%%
 dataFolder = "..//..//supplementary//data//"
 # The data file name
-dataFiles=dataFolder + 'skytem_304_saline_clay.csv'
+dataFiles=dataFolder + 'skytem_saline_clay.csv'
 # dataFiles = dataFolder + 'Skytem.csv'
 # The EM system file name
-systemFiles=[dataFolder + 'SkytemHM_304.stm', dataFolder + 'SkytemLM_304.stm']
+systemFiles=[dataFolder + 'SkytemHM.stm', dataFolder + 'SkytemLM.stm']
 
 from pathlib import Path
 for f in systemFiles[:1]:
@@ -56,7 +56,7 @@
 
 #%%
 plt.figure(5)
-ax = TD.scatter2D(s=1.0, c=TD.secondary_field[:, TD.channel_index(system=0, channel=6)], equalize=True, log=10)
+ax = TD.scatter2D(c=TD.secondary_field[:, TD.channel_index(system=0, channel=6)], log=10)
 plt.axis('equal')
 
 

diff --git a/docs/_downloads/7d8af6f7b40a771fd3b189fc4fd80360/plot_model_1d.ipynb b/docs/_downloads/7d8af6f7b40a771fd3b189fc4fd80360/plot_model_1d.ipynb
@@ -44,7 +44,7 @@
       },
       "outputs": [],
       "source": [
-        "# Make a test model with 10 layers, and increasing parameter values\nnLayers = 2\npar = StatArray(np.linspace(0.001, 0.02, nLayers), \"Conductivity\", \"$\\\\frac{S}{m}$\")\nthk = StatArray(np.full(nLayers, fill_value=10.0))\nthk[-1] = np.inf\nmesh = RectilinearMesh1D(widths = thk)\n\nmod = Model(mesh = mesh, values=par)\n# mod = Model1D(parameters=par, widths=thk)\n\nplt.figure()\nmod.plotGrid(transpose=True, flip=True)"
+        "# Make a test model with 10 layers, and increasing parameter values\nnLayers = 2\npar = StatArray(np.linspace(0.001, 0.02, nLayers), \"Conductivity\", \"$\\\\frac{S}{m}$\")\nthk = StatArray(np.full(nLayers, fill_value=10.0))\nthk[-1] = np.inf\nmesh = RectilinearMesh1D(widths = thk)\n\nmod = Model(mesh = mesh, values=par)\n\nplt.figure()\nmod.plotGrid(transpose=True, flip=True)"
       ]
     },
     {
@@ -219,7 +219,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.10.12"
+      "version": "3.12.3"
     }
   },
   "nbformat": 4,