.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "examples/Statistics/plot_histogram_3d.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code. .. rst-class:: sphx-glr-example-title .. _sphx_glr_examples_Statistics_plot_histogram_3d.py: Histogram 3D ------------ This 3D histogram class allows efficient updating of histograms, plotting and saving as HDF5. .. GENERATED FROM PYTHON SOURCE LINES 11-19 .. code-block:: Python import geobipy from geobipy import StatArray from geobipy import Histogram import matplotlib.pyplot as plt from geobipy import RectilinearMesh3D import numpy as np .. GENERATED FROM PYTHON SOURCE LINES 20-21 Create some histogram bins in x and y .. GENERATED FROM PYTHON SOURCE LINES 21-27 .. code-block:: Python x = StatArray(np.linspace(-4.0, 4.0, 11), 'Variable 1') y = StatArray(np.linspace(-4.0, 4.0, 21), 'Variable 2') z = StatArray(np.linspace(-4.0, 4.0, 31), 'Variable 3') mesh = RectilinearMesh3D(x_edges=x, y_edges=y, z_edges=z) .. GENERATED FROM PYTHON SOURCE LINES 28-29 Instantiate .. GENERATED FROM PYTHON SOURCE LINES 29-31 .. code-block:: Python H = Histogram(mesh=mesh) .. GENERATED FROM PYTHON SOURCE LINES 32-33 Generate some random numbers .. GENERATED FROM PYTHON SOURCE LINES 33-39 .. code-block:: Python a = np.random.randn(100000) b = np.random.randn(100000) c = np.random.randn(100000) # x = np.asarray([a, b, c]) .. GENERATED FROM PYTHON SOURCE LINES 40-41 Update the histogram counts .. GENERATED FROM PYTHON SOURCE LINES 41-43 .. code-block:: Python H.update(a, b, c) .. GENERATED FROM PYTHON SOURCE LINES 44-51 .. code-block:: Python plt.figure() plt.suptitle("Slice half way along each dimension") for axis in range(3): plt.subplot(1, 3, axis+1) s = [5 if i == axis else np.s_[:] for i in range(3)] _ = H[tuple(s)].pcolor(cmap='gray_r') .. image-sg:: /examples/Statistics/images/sphx_glr_plot_histogram_3d_001.png :alt: Slice half way along each dimension :srcset: /examples/Statistics/images/sphx_glr_plot_histogram_3d_001.png :class: sphx-glr-single-img .. GENERATED FROM PYTHON SOURCE LINES 52-53 Generate marginal histograms along an axis .. GENERATED FROM PYTHON SOURCE LINES 53-60 .. code-block:: Python plt.figure() plt.suptitle("Marginals along each axis") for axis in range(3): plt.subplot(1, 3, axis+1) _ = H.marginalize(axis=axis).plot() .. image-sg:: /examples/Statistics/images/sphx_glr_plot_histogram_3d_002.png :alt: Marginals along each axis :srcset: /examples/Statistics/images/sphx_glr_plot_histogram_3d_002.png :class: sphx-glr-single-img .. GENERATED FROM PYTHON SOURCE LINES 61-62 Take the mean estimate from the histogram .. GENERATED FROM PYTHON SOURCE LINES 62-68 .. code-block:: Python plt.figure() plt.suptitle("Mean along each axis") for axis in range(3): plt.subplot(1, 3, axis+1) _ = H.mean(axis=axis).pcolor() .. image-sg:: /examples/Statistics/images/sphx_glr_plot_histogram_3d_003.png :alt: Mean along each axis :srcset: /examples/Statistics/images/sphx_glr_plot_histogram_3d_003.png :class: sphx-glr-single-img .. GENERATED FROM PYTHON SOURCE LINES 69-70 Take the median estimate from the histogram .. GENERATED FROM PYTHON SOURCE LINES 70-100 .. code-block:: Python plt.figure() plt.suptitle("Median along each axis") for axis in range(3): plt.subplot(1, 3, axis+1) _ = H.median(axis=axis).pcolor() # #%% # # We can map the credible range to an opacity or transparency # H.opacity() # H.transparency() H.animate(0, 'test.mp4') H.to_vtk('h3d.vtk') # Create some histogram bins in x and y xx, yy = np.meshgrid(mesh.z.centres, mesh.y.centres) x_re = StatArray(np.sin(np.sqrt(xx ** 2.0 + yy ** 2.0)), "x_re") xx, yy = np.meshgrid(mesh.z.centres, mesh.x.centres) y_re = StatArray(np.sin(np.sqrt(xx ** 2.0 + yy ** 2.0)), "y_re") xx, yy = np.meshgrid(mesh.y.centres, mesh.x.centres) z_re = StatArray(np.sin(np.sqrt(xx ** 2.0 + yy ** 2.0)), "z_re") mesh = RectilinearMesh3D(x_edges=x, x_relative_to=x_re, y_edges=y, y_relative_to=y_re, z_edges=z, z_relative_to=z_re) .. rst-class:: sphx-glr-horizontal * .. image-sg:: /examples/Statistics/images/sphx_glr_plot_histogram_3d_004.png :alt: Median along each axis :srcset: /examples/Statistics/images/sphx_glr_plot_histogram_3d_004.png :class: sphx-glr-multi-img * .. image-sg:: /examples/Statistics/images/sphx_glr_plot_histogram_3d_005.png :alt: 3.60 :srcset: /examples/Statistics/images/sphx_glr_plot_histogram_3d_005.png :class: sphx-glr-multi-img .. GENERATED FROM PYTHON SOURCE LINES 101-102 Instantiate .. GENERATED FROM PYTHON SOURCE LINES 102-104 .. code-block:: Python H = Histogram(mesh=mesh) .. GENERATED FROM PYTHON SOURCE LINES 105-106 Generate some random numbers .. GENERATED FROM PYTHON SOURCE LINES 106-111 .. code-block:: Python a = np.random.randn(100000) b = np.random.randn(100000) c = np.random.randn(100000) # x = np.asarray([a, b, c]) .. GENERATED FROM PYTHON SOURCE LINES 112-113 Update the histogram counts .. GENERATED FROM PYTHON SOURCE LINES 113-115 .. code-block:: Python H.update(a, b, c) .. GENERATED FROM PYTHON SOURCE LINES 116-123 .. code-block:: Python plt.figure() plt.suptitle("Slice half way along each dimension") for axis in range(3): plt.subplot(1, 3, axis+1) s = [5 if i == axis else np.s_[:] for i in range(3)] _ = H[tuple(s)].pcolor(cmap='gray_r') .. image-sg:: /examples/Statistics/images/sphx_glr_plot_histogram_3d_006.png :alt: Slice half way along each dimension :srcset: /examples/Statistics/images/sphx_glr_plot_histogram_3d_006.png :class: sphx-glr-single-img .. GENERATED FROM PYTHON SOURCE LINES 124-125 Generate marginal histograms along an axis .. GENERATED FROM PYTHON SOURCE LINES 125-132 .. code-block:: Python plt.figure() plt.suptitle("Marginals along each axis") for axis in range(3): plt.subplot(1, 3, axis+1) _ = H.marginalize(axis=axis).plot() .. image-sg:: /examples/Statistics/images/sphx_glr_plot_histogram_3d_007.png :alt: Marginals along each axis :srcset: /examples/Statistics/images/sphx_glr_plot_histogram_3d_007.png :class: sphx-glr-single-img .. GENERATED FROM PYTHON SOURCE LINES 133-134 Take the mean estimate from the histogram .. GENERATED FROM PYTHON SOURCE LINES 134-140 .. code-block:: Python plt.figure() plt.suptitle("Mean along each axis") for axis in range(3): plt.subplot(1, 3, axis+1) _ = H.mean(axis=axis).pcolor() .. image-sg:: /examples/Statistics/images/sphx_glr_plot_histogram_3d_008.png :alt: Mean along each axis :srcset: /examples/Statistics/images/sphx_glr_plot_histogram_3d_008.png :class: sphx-glr-single-img .. GENERATED FROM PYTHON SOURCE LINES 141-142 Take the median estimate from the histogram .. GENERATED FROM PYTHON SOURCE LINES 142-158 .. code-block:: Python plt.figure() plt.suptitle("Median along each axis") for axis in range(3): plt.subplot(1, 3, axis+1) _ = H.median(axis=axis).pcolor() # #%% # # We can map the credible range to an opacity or transparency # H.opacity() # H.transparency() H.animate(0, 'test.mp4') plt.show() # H.to_vtk('h3d.vtk') .. rst-class:: sphx-glr-horizontal * .. image-sg:: /examples/Statistics/images/sphx_glr_plot_histogram_3d_009.png :alt: Median along each axis :srcset: /examples/Statistics/images/sphx_glr_plot_histogram_3d_009.png :class: sphx-glr-multi-img * .. image-sg:: /examples/Statistics/images/sphx_glr_plot_histogram_3d_010.png :alt: 3.60 :srcset: /examples/Statistics/images/sphx_glr_plot_histogram_3d_010.png :class: sphx-glr-multi-img .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 4.437 seconds) .. _sphx_glr_download_examples_Statistics_plot_histogram_3d.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_histogram_3d.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_histogram_3d.py ` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: plot_histogram_3d.zip ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_