.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_examples/ex_fill_undef.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. or to run this example in your browser via Binder .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_ex_fill_undef.py: *************** Fill NaN values *************** The undefined values in the grids do not allow interpolation of values located in the neighborhood. This behavior is a concern when you need to interpolate values near the land/sea mask of some maps. .. GENERATED FROM PYTHON SOURCE LINES 11-21 .. code-block:: Python import cartopy.crs import cartopy.feature import matplotlib.pyplot import numpy import pyinterp.backends.xarray # Module that handles the filling of undefined values. import pyinterp.fill import pyinterp.tests .. GENERATED FROM PYTHON SOURCE LINES 22-27 For example, in the figure above, if you want to interpolate the gray point with a bilinear interpolation, the undefined red value, set to NaN, will not allow its calculation (the result of the arithmetic operation using a value equal to NaN is NaN). On the other hand, the green point can be interpolated normally because the 4 surrounding points are defined. .. GENERATED FROM PYTHON SOURCE LINES 27-54 .. code-block:: Python fig = matplotlib.pyplot.figure(figsize=(10, 8)) ax = fig.add_subplot(111, projection=cartopy.crs.PlateCarree()) ax.set_extent([-6, 1, 47.5, 51.5], crs=cartopy.crs.PlateCarree()) ax.add_feature(cartopy.feature.LAND.with_scale('110m')) ax.gridlines(draw_labels=True, dms=True, x_inline=False, y_inline=False) lons, lats = numpy.meshgrid(numpy.arange(-6, 2), numpy.arange(47.5, 52.5), indexing='ij') mask = numpy.array([ [1, 1, 1, 0, 0, 0, 0, 0], # yapf: disable [1, 1, 0, 0, 0, 0, 0, 0], # yapf: disable [1, 1, 1, 1, 1, 1, 0, 0], # yapf: disable [1, 0, 0, 1, 1, 1, 1, 1], # yapf: disable [1, 1, 1, 0, 0, 0, 0, 0] ]).T ax.scatter(lons.ravel(), lats.ravel(), c=mask, cmap='bwr_r', transform=cartopy.crs.PlateCarree(), vmin=0, vmax=1) ax.plot([-3.5], [49], linestyle='', marker='.', color='dimgray', markersize=15) ax.plot([-2.5], [50], linestyle='', marker='.', color='green', markersize=15) fig.show() .. image-sg:: /auto_examples/images/sphx_glr_ex_fill_undef_001.png :alt: ex fill undef :srcset: /auto_examples/images/sphx_glr_ex_fill_undef_001.png :class: sphx-glr-single-img .. GENERATED FROM PYTHON SOURCE LINES 55-73 To overcome this problem, the library provides methods to fill undefined values. .. note:: In the case of an interpolation of the nearest neighbor the undefined values have no impact because no arithmetic operation is done on the grid values: we just return the value of the nearest point. LOESS ===== The :py:func:`first ` method applies a weighted local regression to extrapolate the boundary between defined and undefined values. The user must indicate the number of pixels on the X and Y axes to be considered in the calculation. Let's start by building the object handling our grid. .. GENERATED FROM PYTHON SOURCE LINES 73-76 .. code-block:: Python ds = pyinterp.tests.load_grid2d() grid = pyinterp.backends.xarray.Grid2D(ds.mss) .. GENERATED FROM PYTHON SOURCE LINES 77-78 The function filling the holes near the mask is called .. GENERATED FROM PYTHON SOURCE LINES 78-80 .. code-block:: Python filled = pyinterp.fill.loess(grid, nx=3, ny=3) .. GENERATED FROM PYTHON SOURCE LINES 81-82 The image below illustrates the result: .. GENERATED FROM PYTHON SOURCE LINES 82-113 .. code-block:: Python fig = matplotlib.pyplot.figure() ax1 = fig.add_subplot( 211, projection=cartopy.crs.PlateCarree(central_longitude=180)) lons, lats = numpy.meshgrid(grid.x, grid.y, indexing='ij') pcm = ax1.pcolormesh(lons, lats, ds.mss.T, cmap='jet', shading='auto', transform=cartopy.crs.PlateCarree(), vmin=-0.1, vmax=0.1) ax1.coastlines() ax1.set_title('Original MSS') ax1.set_extent([0, 170, -45, 30], crs=cartopy.crs.PlateCarree()) ax2 = fig.add_subplot( 212, projection=cartopy.crs.PlateCarree(central_longitude=180)) pcm = ax2.pcolormesh(lons, lats, filled, cmap='jet', shading='auto', transform=cartopy.crs.PlateCarree(), vmin=-0.1, vmax=0.1) ax2.coastlines() ax2.set_title('MSS modified using the LOESS filter') ax2.set_extent([0, 170, -45, 30], crs=cartopy.crs.PlateCarree()) fig.colorbar(pcm, ax=[ax1, ax2], shrink=0.8) fig.show() .. image-sg:: /auto_examples/images/sphx_glr_ex_fill_undef_002.png :alt: Original MSS, MSS modified using the LOESS filter :srcset: /auto_examples/images/sphx_glr_ex_fill_undef_002.png :class: sphx-glr-single-img .. GENERATED FROM PYTHON SOURCE LINES 114-121 Gauss-Seidel ============ The :py:func:`second ` method consists of replacing all undefined values (NaN) in a grid using the Gauss-Seidel method by relaxation. This `link `_ contains more information on the method used. .. GENERATED FROM PYTHON SOURCE LINES 121-123 .. code-block:: Python has_converged, filled = pyinterp.fill.gauss_seidel(grid) .. GENERATED FROM PYTHON SOURCE LINES 124-125 The image below illustrates the result: .. GENERATED FROM PYTHON SOURCE LINES 125-154 .. code-block:: Python fig = matplotlib.pyplot.figure(figsize=(10, 10)) ax1 = fig.add_subplot( 211, projection=cartopy.crs.PlateCarree(central_longitude=180)) pcm = ax1.pcolormesh(lons, lats, ds.mss.T, cmap='jet', shading='auto', transform=cartopy.crs.PlateCarree(), vmin=-0.1, vmax=0.1) ax1.coastlines() ax1.set_title('Original MSS') ax1.set_extent([0, 170, -45, 30], crs=cartopy.crs.PlateCarree()) ax2 = fig.add_subplot( 212, projection=cartopy.crs.PlateCarree(central_longitude=180)) pcm = ax2.pcolormesh(lons, lats, filled, cmap='jet', shading='auto', transform=cartopy.crs.PlateCarree(), vmin=-0.1, vmax=0.1) ax2.coastlines() ax2.set_title('MSS modified using Gauss-Seidel') ax2.set_extent([0, 170, -45, 30], crs=cartopy.crs.PlateCarree()) fig.colorbar(pcm, ax=[ax1, ax2], shrink=0.8) fig.show() .. image-sg:: /auto_examples/images/sphx_glr_ex_fill_undef_003.png :alt: Original MSS, MSS modified using Gauss-Seidel :srcset: /auto_examples/images/sphx_glr_ex_fill_undef_003.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 7.227 seconds) .. _sphx_glr_download_auto_examples_ex_fill_undef.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: binder-badge .. image:: images/binder_badge_logo.svg :target: https://mybinder.org/v2/gh/CNES/pangeo-pyinterp/master?urlpath=lab/tree/notebooks/auto_examples/ex_fill_undef.ipynb :alt: Launch binder :width: 150 px .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: ex_fill_undef.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: ex_fill_undef.py ` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: ex_fill_undef.zip ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_